pred,label
"9Country,Long-term price index in food commodities,1850-2015,World,1934
Lamb,103.7,103.7,103.7
Corn,103.13,103.13,103.13
Barley,102.46,102.46,102.46
Rye,87.37,87.37,87.37
Beef,85.27,85.27,85.27
Wheat,83.73,83.73,83.73
Coffee,82.2,82.2,82.2
Tea,68.48,68.48,68.48
Peanuts,64.71,64.71,64.71
Palm oil,57.6,57.6,57.6
Pork,55.36,55.36,55.36
Rice,",14
"15.89Country,""Long-term price index in food commodities, 1850-2015, World, 1934""
Lamb,103.7
Corn,103.13
Barley,102.46
Rye,87.37
Beef,85.27
Wheat,83.73
Coffee,82.2
Tea,68.48
Peanuts,64.71
Palm oil,57.6
Pork,55.36
Rice,42.48
Sugar,25.56
Cocoa,18.81",0.57
"3Country,""Armed forces personnel as share of total population, 1985""
Mauritania,0.48
Fiji,0.38
Madagascar,0.21",3
"YesCountry,""Armed forces personnel as share of total population, 1985""
Mauritania,0.48
Fiji,0.38
Madagascar,0.21",No
"68Entity,Limit its military role,Play a more active military role
,29
68,23",23
"19Entity,Limit its military role,Play a more military role
2015,68,23
2016,62,29",6
"62Entity,Values
Caring about ordinary people,23.0
Well-qualified to be president,26.0
Cha moatic,39.0
A strong leader,55.0
Dangerous,62.0
Intolerant,65.0
Arrogant,75.0",62
"NoEntity,Values
Caring about ordinary people,23.0
Well-qualified to be president,26.0
Chaismatic,39.0
A strong leader,55.0
Dangerous,62.0
Intolerant,65.0
Arrogant,75.0",Yes
"LonelyEntity,Frequently,Sometimes,NET
Lonely,24,24,31
Depressed,13,36,49
Inspired,16,53,69
Connected,21,49,71
Angry,25,47,71
Amused,44,,88",Inspired
"4Entity,Frequently,Sometimes,NET
Lonely,,24.0,31
Depressed,,36.0,49
Inspired,16.0,53.0,69
Connected,21.0,49.0,71
Angry,25.0,,71
Amused,44.0,,88",0.03
"1Country,""Gross enrollment ratio, secondary education, gender parity index (GPI),2006""
Slovenia,-
Albania,0.96
Cameroon,0.79
Low income,0.71",1
"0.04Country,""Gross enrollment ratio, secondary education, gender parity index (GPI),2006""
Slovenia,1.0
Albania,0.96
Cameroon,0.79
Low income,0.71",0.08
"17Entity,More,About the same,Less
China,,50,0
EU,19.0,59,21
U.S,29.0,41,29",17
"31.5Entity,More,About the same,Less
China,,50,0
EU,19.0,59,21
U.S.,29.0,41,29",21.6
"2Entity,Value
Refused,2
Don't know,2
Yes, abandoning news outlets,31
No, not abandoning news outlets,65",2
"2Entity,Value
Refused,2
Don't know,2
Yes, abandoning news outlets,31
No, not abandoning news outlets,65",2
"2014Entity,2010,2011,2012,2013,2014
England,1815,-,2310,-,2750",2014
"2014Entity,2010,2011,2012,2013,2014
England,1787.598,2247.231,2431.041,2531.071,2871.43",2011
"5Country,""Share that agrees that vaccines are important for children to have, 2018""
United Arab Emirates,94
Mauritania,91
Spain,88
Armenia,73
South Korea,72",1
"YesCountry,""Share that agrees that vaccines are important for children to have, 2018""
United Arab Emirates,94
Mauritania,91
Spain,88
Armenia,73
South Korea,72",No
"BlueEntity,2004,2005,2006,2007,2008,2009,2010,2011,2012
Child Labor (Boys, World, 2000-2012) (ILO),19.10185084,19.77539955,20.55511367,19.82770093,16.49921696,17.68907885,17.84308262,17.04245345,16.18233548
Child Labor (All, World, ILO-IPEC),17.8196722,17.5385767,17.31304414,17.36188092,16.53323855,16.767187",green line
"2010Entity,2004,2005,2006,2007,2008,2009,2010,2011,2012
Child Labor (Boys, World, 2000-2012) (ILO),19.36,,20.41,,,18.94,,
Child Labor (All, World, ILO-IPCE),16.81,,,18.81,,18.15,
Child Labor (Girls, World, 2000-2012) (ILO),18.16,,20.21,,,20.61,,",2008
"23Entity,Top 25 of tweeters,Bottom 75 of tweeters
U.S.,58,42
UK,67,33
Canada,68,32
Australia,71,29
New Zealand,76,24",29
"1.188888889Entity,Top 25% of tweeters,Bottom 75% of tweeters
U.S.,58,42
UK,67,33
Canada,68,32
Australia,71,29
New Zealand,76,24",1.216666667
"YesEntity,Value
Education,11
""Management, business, finance"",17
Social services, legal,,11
STEM,52
Other non-STEM,20",Yes
"YesEntity,Value
Other non-STEM,20
Social services legal,11
Management business,17",Yes
"80Entity,Value
DK,3
Oppose,17
Support,80",80
"71Entity,Value
DK,3
Support,80
Oppose,17",77
"16Entity,More,the same,Fewer,None (VOL)
Turkey,,30,53,0
Christian,,33,53,0
Sunni,,46,36,0
Shia,,44,33,0
Lebanon,,40,42,0
Jordan,,60,23,0",0.6
"56Entity,More,About the same,Fewer,None (VOL)
Turkey,,30.0,53.0,0
Christian,,,33.0,53.0
Sunni,,46.0,36.0,0
Shia,,44.0,33.0,0
Lebanon,13.0,40.0,42.0,0
Jordan,8.0,8.0,60.0,23.0
Syrian,,64.0,26.0,0",61
"13Entity,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019
Hungary,36.9,38.1,19.1,29.0,46.0,49.2,56.7,56.7,49.3,51.2,58.7,56.2,59.0
Lithuania,13.7,11.3,5.3,5.4,11.0,16.2,19.8,8.2,-1.6,7.2,15.7,-3.1,18.9",13
"5Country,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019
Hungary,32.0,30.0,19.0,32.0,48.0,46.0,58.0,57.0,29.0,55.0,54.0,52.0,56.0
Lithuania,17.0,13.0,4.0,7.0,10.0,9.0,-,4.0,-,-,14.0,-,18.0",5
"45Entity,Not at all,Not too,Somewhat,Very
Work effectively with Congress,54.0,33,13.0,43
Handle an international crisis,54.0,35,25.0,43
Make wise decisions about immigration policy,55.0,39,26.0,43
Manage the executive branch effectively,52.0,34,21.0,45
Make good appointments to the federal courts,48.0,32,25.0,46
Use military force wisely,51.0,32,26.0,46
Make good decisions about economic policy,46.0,29,31.0,53
Negotiate favorable trade agreements with other countries,44.0,26,30.0,54",24
"YesEntity,Not at all,Not too,Somewhat,Very
Work effectively with Congress,54.0,33,13,43
Handle an international crisis,54.0,35,25,43
Make wise decisions about immigration policy,55.0,39,26,43
Manage the executive branch effectively,52.0,34,21,45
appointmentsto the federal courts,48.0,32,25,46
Make good appointments to the federal courts,48.0,32,25,46
Use military force wisely,51.0,32,26,46
about economic policy,46.0,29,31,53
Make good decisions,46.0,29,31,53
with other countries,26.0,30,54,0
trade agreements,26.0,30,54,0
Negotiate favorable trade agreements with other countries,26.0,30,54,0",No
"ItalyCountry,2010,2011,2012,2013,2014,2015,2016,2017,2018
Spain,-,-,-,-,-,-,-,-,77.0
Mexico,-,-,-,-,-,56.0,55.0,58.0,62.0
Italy,-,-,-,-,-,72.0,75.0,80.0,89.0",Italy
"MexicoCountry,2010,2011,2012,2013,2014,2015,2016,2017,2018
Spain,58.0,59.0,60.0,68.0,67.0,70.0,73.0,76.0,75.0
Mexico,42.0,44.0,45.0,48.0,49.0,53.0,55.0,58.0,60.0
Italy,66.0,57.0,60.0,73.0,75.0,78.0,80.0,82.0,89.0",Mexico
"6Entity,Did not wait,10-30 minutes,10-30 mins,Over 30 mins
Rural,51,32,13,0
Suburban,45,34,15,0
Urban,46,33,13,0
West,53,28,13,0
South,40,34,18,0
Midwest,50,31,15,0
Northeast,52,36,8,0
Hispanic,39,31,20,0
Black,43,29,18,0
White,50,32,13,0
Total,47,33,14,0",33
"0.5Entity,Did not wait,
Rural,51,13
Suburban,45,15
Urban,46,33
West,53,13
South,40,18
Midwest,50,31
Northeast,52,15
Hispanic,39,20
Black,43,18
White,50,32
Total,,33",Over 30 mins
"4Entity,Values
Hispa nics,15
Blacks,22
Whites,41
Asians,63",4
"22Entity,Values
Hispa nics,15.0
Blacks,22.0
Whites,
Asians,63.0",22
"92Entity,Oppose,Favor
Rep/Lean Rep,22,
Dem/Lean Dem,8,92
All Hispanics,12,86",92
"18Entity,Oppose,Favor
Rep/Lean Rep,22,
Dem/Lean Dem,8,92.0
All Hispanics,12,86.0",96
"21Entity,Disap prove,Approve,DK
Jul 2015,45,33,22
Sep 2015,49,21,30",21
"12Entity,Disap prove,Approve,DK
Jul 2015,45,33,22
Sep 2015,49,21,30",12
"2009Year,Dissatisfied,Satisfied
2002,66,0
2007,30,0
2009,78,0
2011,76,34
2013,69,30
2015,72,0",2009
"36.7Year,Satisfied,Dissa tisfied
2002,16,30
2007,0,68
2009,20,78
2011,22,76
2013,29,69
2015,0,0",28.6
"0.68Year,Bad,Good
2019,53,0
2020,68,30",68
"2019Year,Bad,Good
2019,0,53
2020,68,30",2019
"83Entity,Disapprove,Approve
Corruption,29.0,62
Economy,23.0,70
Energy policy,14.0,73
Relations w/ EU,,82
Relations w/ Ukraine,13.0,83
Relations w/U.S,10.0,85
Relations w/ China,4.0,90",83
"0.4904Entity,Disapprove,Approve
Corruption,29,62
Economy,23,70
Energy policy,14,73
Relations w/ EU,11,52
Relations w/ Ukraine,13,83
Relations w/U.S.,10,85
Relations w/ China,,,90",2.13
"SimulationEntity,Values
Simulation,32
Team sport or racing,33
Role-playing,39
Shooter,42
Adventure,49
Strategy,62
Puzzle,62",Simulation
"4Entity,Values
Simulation,32.0
or racing Team sport,33.0
Role-playing,39.0
Shooter,42.0
Adventure,49.0
Strategy,62.0
Puzzle,62.0",4
"YesEntity,Not at all,Not too much,A fair amount,a great deal
government,84,49,35,15
Chinese,84,49,35,15
who,40,18,22,20
EU,36,10,26,51",Yes
"YesEntity,Not at all,Not too much,a fair amount,a great deal
government,84,49,35,,,0.0
Chinese,0,0,13.0,15.0,20,59
who,40,18,22,40,20,59
EU,36,10,26,51,11,62",No
"YesEntity,Value
Strong ties with Russia,15
Strong ties with U.S.,57
Don 't know,7
Equally close ties (VOL),21",Yes
"0.038388889Entity,Value
Russia,15
Strong ties with Russia,15
Equally close ties (VOL),21
Strong ties with U.S,57
Don't know,7",0.33333333
"RepublicanEntity,Full voter file,Have phone number,Confirmed respondents,Final weighted
""Independent (scores 41 to 59)"",11,0,10,35
Republican (scores 0 to 40),33,0,38,35
""Democrat (scores 60 to 100)"",55,54,54,54",Democrat (scores 60 to 100)
"13Entity,Full voter file,Have phone number,Confirmed respondents,Final weighted
Independent (scores 41 to 59),11,11,10,11
Republican (scores 0 to 40),33,34,38,35
Democrat (scores 60 to 100),55,54,54,54",0.01
"LiberiaCountry,""Human Development Index, 1993""
Denmark,0.81
Libya,0.69
Ecuador,0.65
Botswana,0.58",Libya
"0.23Country,""Human Development Index, 1993""
Denmark,0.81
Libya,0.69
Ecuador,0.65
Botswana,0.58",0.23
"28Year,China's military strength,China's economic strength
2012,28,59
2014,0,0
2016,37,50
2018,29,58",28
"65Year,China's strength,China's military strength
2012,59,28
2014,-,0
2016,50,0
2018,58,29",87.5
"United KingdomEntity,Values
UK,37.0
Spain,48.0
France,54.0
Poland,62.0
Greece,62.0
Italy,63.0
Germany,63.0
U.S,43.0",UK
"62.75Entity,Values
UK,37.0
Spain,48.0
France,54.0
Poland,62.0
Greece,62.0
Italy,63.0
Germany,63.0
U.S,43.0",50.25
"32Entity,1-3 terms,4-9 terms,10+ terms
Democrats (188),36.0,34.0,
Other Republicans (211),54.0,32.0,
Freedom Caucus Republicans (36),72.0,28.0,
Total (435 members),47.0,32.0,20.0",72
"0.1068Entity,1-3 terms,4-9 terms,10+ terms
Democrats (188),36,34,31
Other Republicans (211),54,32,14
Freedom Caucus Republicans (36),72,28,-
Total (435 members),47,32,20",0.633333333
"5.0Year,Hispanic eligible voters,Hispanic voters
1986,7.5,0.0
1990,8.1,0.0
1994,10.3,0.0
1998,12.4,0.0
2002,14.5,0.0
2006,17.3,5.6
2010,21.3,6.6
2014,25.1,6.8
2018,29.1,0.0",4.1
"10.6Year,Hispanic voters,Hispanic eligible voters
1986,0.0,7.5
1990,2.9,8.1
1994,3.5,10.3
1998,4.1,12.4
2002,4.5,14.5
2006,5.6,17.3
2010,6.6,21.3
2014,6.8,25.1
2018,6.8,29.1",14.5
"175Country,Deaths from cancer
Costa Rica,173
Colombia,175
Slovenia,262",175
"NoCountry,Deaths from cancer
Costa Rica,173
Colombia,175
Slovenia,262",No
"93.45Country,""Scheduled teaching time that teachers are in the classroom, 2002 to 2016""
Egypt,93.45
Tunisia,89.89
Madagascar,58.09
Mozambique,44.0",93.45
"0.4372Country,""Scheduled teaching time that teachers are in the classroom, 2002 to 2016""
Egypt,93.45
Tunisia,89.89
Madagascar,58.09
Mozambique,44.0",51.04
"YesEntity,Left-wing to far left,Center-left,Centrist,Center-right,Green or regionalist Right-wing to far right
2014,,25,,29,20
2009,5,25,12,36,15
2004,6,28,13,37,,11
1999,,29,,9,8
1994,,35,,30,14
1989,8,35,,30,8
1984,10,30,,11,5
1979,12,27,,42,7",Yes
"7.65Entity,Left-wing to far left,Center-left,Centrist,Green or right-wing to far right,Right-wing
2014,25,9,29,20,7
2009,5,25,12,36,15
2004,6,28,13,,0
1999,,29,,37,8
1994,5,35,,30,14
1989,8,35,,30,8
1984,10,30,37,11,0
1979,12,27,,42,7",21.5
"302.38Country,Regulation of financial markets,Dominica,2015
Net open position in foreign exchange to capital,302.38,302.38
Non-performing loans net of provisions to capital,103.88,103.88
Liquid assets to short term liabilities,52.42,52.42
Non-performing loans to total gross loans,15.12,15.12
Regulatory capital to assets,4.0,4.0
Return on assets,0.1,0.1",3.0238
"111.35Country,""Regulation of financial markets, Dominica, 2015""
""Net open position in foreign exchange to capital"",302.38
""Non-performing loans net of provisions to capital"",103.88
""Liquid assets to short term liabilities"",52.42
""Non-performing loans to total gross loans"",15.12
""Regulatory capital to assets"",4.0
""Return on assets"",0.1",0.1922
"16Entity,More,Aboutthe same,Less
Dem/Lean Dem,58.0,27.0,15
Re p/Lean Rep,48.0,,10
Women,58.0,28.0,13
Men,46.0,39.0,
Total,52.0,,13",52
"YesEntity,More,Aboutthe sa me,Less
Dem/Lean Dem,58,27,15
Rep/Lean Rep,48,41,10
Women,58,28,13
Men,46,39,14
Total,52,33,13",Yes
"UKEntity,Values
Portugal,84.0
Italy,80.0
France,83.0
UK,91.5
U.S.,92.9",U.S.
"FranceEntity,Values
Portugal,84.0
Italy,80.3",UK
"89Entity,Citizens should have to prove they want to vote by registering ahead of time,Everything possible should be done to make it v easy to vote
Liberal,11,89
Cons/Mod,20,80
Dem/Lean Dem,15,84
Mod/Lib,34,65
Conservative,63,36
Rep/Lean Rep,51,48
Total,32,67",67
"0.149144444Entity,Citizens should have to prove they want to vote by registering ahead of time,Everything possible should be done to vote it easy to make
Liberal,89.0,0
Cons/Mod,80.0,0
Dem/Lean Dem,84.0,15
Mod Lib,65.0,34
Conser vative,36.0,63
Rep/Lean Rep,48.0,51
Total,32.0,0",1.051388889
"68Entity,Very,Somewhat,Not too,Not at all
Across the United States,23.0,57,16,0
Your state,55.0,33,64,0
Your local area,68.0,27,0,0
""Officials who run elections in.."",0.0,0,0,0
""Poll workers in your community"",68.0,24,0,0",55
"Local areaEntity,Very,Somewhat,Not too,Not at all
Across the United States,23,57,16,0
Your state,55,33,64,0
Your local area,68,27,0,0
""Runction election officials in..."","""",0,0,0
""Poll workers in your community"",68,24,4,0",Poll workers in your community
"Rep/Lean RepEntity,Bad,Good
Dem/Lean Dem,54.0,
Rep/Lean Rep,82.0,15.0
50+,73.0,23.0
30-49,59.0,35.0
Ages 18-29,54.0,
Total,64.0,31.0",Rep/Lean Rep
"0.213888889Entity,Bad,Good
Dem/Lean Dem,54,42
Rep/Lean Rep,82,15
50+,73,23
30-49,59,35
Ages 18-29,54,41
Total,64,31",0.484375
"[77, 77]Year,Warming mostly because of human activity,Yes, solid evidence the earth warming
2006,0,0
2007,0,0
2008,47,0
2009,36,0
2010,5958,38
2011,0,0
2012,0,0
2013,69,0",77
"134Year,Warming mostly because of human activity,Yes, solid evidence the earth is warming
2006,0,0
2007,0,0
2008,0,0
2009,36,0
2010,3436,5958
2011,38,63
2012,0,0
2013,0,0",141
"41Entity,Your personal financial situation,Your personal health
65+,32,49
50-64,46,43
30-49,43,34
Ages 18-29,40,26
All adults,41,38",41
"0.67647Entity,Your personal financial situation,Your personal health
65+,32,49
50-64,46,43
30-49,43,34
Ages 18-29,40,26
All adults,41,38",1.684722222
"NicaraguaCountry,""Share of children with diarrhea receiving treatment, 1995""
Thailand,73.3
Nicaragua,55.7
Lesotho,35.0",Nicaragua
"YesCountry,""Share of children with diarrhea receiving treatment, 1995""
Thailand,73.3
Nicaragua,55.7
Lesotho,35.0",No
"10Entity,Major factor,Minor factor,Not a factor
Gender,,8,
Race or ethnicity,,19,73
Whether a relative attended the school,24,68,0
Athletic ability,34,57,0
Being first person in family to go to college,20,27,53
Community service involvement,21,48,30
Standardized test scores,47,41,
High school grades,,26,0",3
"85Entity,Major factor,Minor factor,Not a factor
Gender,14.0,81,0
Race or ethnicity,19.0,73,0
Whether a relative attended the school,8.0,24,68
Athletic ability,8.0,34,57
Being first person in family to go to college,20.0,27,53
Community service involvement,21.0,48,30
Standardized test scores,47.0,41,11
High school grades,67.0,26,0",99
"Solomon IslandsEntity,2005,2006,2007,2008,2009,2010,2011,2012
North Macedonia,232.40487354228015,235.8983850309457,174.21440454074625,177.24576185776627,168.20947908789046,168.11640832074063,151.49755974738403,156.41565011726202
Tonga,63.24167509234837,53.60937452735646,50.80097209645964,",Solomon Islands
"JamaicaEntity,2005,2006,2007,2008,2009,2010,2011,2012
Solomon Islands,255.39999999999885,252.6999999999998,244.9999999999998,248.3999999999998,247.9999999999997,215.1499999999997,272.88,255.4
North Macedonia,205.7675573153598,214.9246918703593,177.6427290768639,169.1342804851085,190.31558307",Jamaica
"50Year,Japan,U.S.
2007,0,50
2008,20,36
2009,20,0
2010,24,18
2011,18,0
2012,31,0
2013,33,27
2014,40,40
2015,40,0
2016,44,30",50
"40Year,Japan,U.S.
2007,0,50
2008,20,0
2009,20,0
2010,24,0
2011,,0
2012,31,0
2013,33,0
2014,35,40
2015,37,40
2016,30,0",35
"977633Country,""Annual CO2 emissions from deforestation for food production""
South Korea,21.32
Spain,19.72
Slovenia,977633",977633
"1.42Country,""Annual CO2 emissions from deforestation for food production""
South Korea,21.32
Spain,19.72
Slovenia,977633.0",1.6
"4Country,""Deaths from eating disorders, 1990""
Cote d'Ivoire,1
Iceland,1
Mali,1
Mauritius,1",4
"NoCountry,""Deaths from eating disorders, 1990""
Cote d'Ivoire,1
Iceland,1
Mali,1
Mauritius,1",No
"16Entity,Mexican,Central American,South American,Caribbean,Spanish/ Other
Silent/Greatest (69 and older),52.0,6.0,8.0,26.0,0
Boomer (50-68),57.0,88.0,20.0,,0
Gen X (34-49),63.0,,7.0,16.0,,0
Millennial adults (18-33),65.0,10.0,,16.0,,0
Youngerthan 18,69.0,8.0,,15.0,,0",0.08
"1Entity,Mexican,Central American,South American,Caribbean,Spanish/ Other
Silent/Greatest (69 and older),52.0,6.0,26.0,8.0,0
Boomer (50-68),57.0,8.0,20.0,6.0,0
Gen X (34-49),63.0,10.0,,16.0,0
Millennial adults (18-33),65.0,10.0,616.0,,0
Youngerthan 18,69.0,8.0,,15.0,0",65
"25Year,CNN,MSNBC,Fox News
98,23,8,17
,0,0,0
02,15,0,0
04,25,22,15
06,23,0,23
08,23,15,24
10,18,11,23
12,16,11,21",25
"3Year,CNN,Fox News,MSNBC
98,23,17,8
00,21,0,0
02,22,15,0
04,22,0,0
06,23,11,0
08,24,15,18
10,23,11,18
12,21,,16",2
"UnaffiliatedEntity,Unfavorable,Favorable
Unaffiliated,82.0,,18
Roman Catholic,69.0,27,0
College degree,81.0,14,0
No colle ge degree,,26,0
Women,79.0,19,0
Men,70.0,28,0
Total,74.0,23,0",28
"0.1347222Entity,Unfavorable,Favorable
Unaffiliated,82,18.0
Roman Catholic,69,2.0
College degree,81,14.0
No colle ge degree,71,26.0
Women,79,,19.0
Men,70,28,0.0
Total,74,23,0.0",1.179861111
"4Entity,NET Not likely,Not at all likely,Not very likely,Somewhat likely,Very likely,NET Likely
Dem/Lean Dem,36,9.0,27.0,,62
Rep/Lean Rep,14,,3.0,32.0,85
Total,26,19.0,,3.0,72",4
"19Entity,NET Not Likely,Not at Not all very likely likely,Somewhat likely,Very Likely,NET Likely
Dem/Lean Dem,36.0,9.0,27.0,42.0,20
Rep/Lean Rep,14.0,,32.0,54.0,85
Total,26.0,19.0,,35.0,72",37
"GreenEntity,Value
Moderation in enforcement,68
No choice,11
Vigorous enforcement,19",Gray
"53Entity,Value
No choice,No choice
Moderation in enforcement,68
Vigorous enforcement,19",8
"2.8Country,""Population of all world regions, including the UN projection until 2100, 1950""
World,-,2.54
Asia,-,1.4
Europe -,-,549.33
Africa -,-,227.79
Northern America,-,172.6
South America,-,113.77",1.4
"YesCountry,""Population of all world regions, including the UN projection until 2100, 1950""
World,-2.54
Asia,-1.4
Europe,-549.33
Africa,-227.79
Northern America,-172.6
South America,-113.77",No
"2.42Country,""Cereal yield, 2001""
Serbia and Montenegro,4.26
South America,3.19
India,2.42
Liberia,1.12
Rwanda,0.91",2.42
"1.09Country,""Cereal yield, 2001""
Serbia and Montenegro,4.26
South America,3.19
India,2.42
Liberia,1.12
Rwanda,0.91",0.77
"19Entity,Frequently,Sometimes,Hardly ever,Never
toward others,11,32,37,19
Are abusive or,11,32,37,19
in dangerous or troubling behavior,19,42,25,14
people Show engaging in,19,42,25,14
or false untrue or,15,48,23,12
Seem obviously,15,48,23,12",12
"NoEntity,Frequency,Sometimes,Hardly ever,Never
Are abusive or demearing toward others,11,32,,19
""Show people engaging in dangerous or troubling behavior"",19,42,25.0,
""Seem obviously false or untrue"",15,48,23.0,12",Yes
"92Entity,Hispanic,Non-Hispanic
Fourth or higher generation,50,50
Third generation,77,23
Second generation,92,8
Foreign born,97,3",3
"51.8Entity,Hispanic,Non-Hispanic
""Fourth or higher generation"",50,50
Third generation,77,23
Second generation,92,
Foreign born,97,0",21
"8Entity,Very,Somewhat,Not,Not at all
Worried,22.0,46,23,0
Enthusiastic,15.0,34,30,19",0.3
"0.6Entity,Very,Somewhat,Not,Not at all
Worried,-,22.0,46.0,23
Enthusiastic,15.0,34.0,30.0,19",0.07
"LD, LDPECountry,""Primary plastic production by polymer type, 2015""
PP,68
LD, LDPE,64
""PP&A fibers"",59
HDPE,52
PVC,38
PET,33
PUT,27
Additives,25
PS,25",PP
"3Country,""Primary plastic production by polymer type, 2015""
PP,68
""LD, LDPE"",64
""PP&A fibers"",59
HDPE,52
PVC,38
PET,33
PUT,27
Additives,25
PS,25",3
"71Entity,Value
Christian,3292.0
Other religions,821.0
Unaffiliated,7.0
Muslim,3410.0",71
"YesEntity,Value
Unaffiliated,71.0
Christian,3292.0
Moslim,3410.0
Other religions,821.0",No
"30Entity,Value
Stay about the same,31
Decrease,39
Increase,30",30
"YesEntity,Value
Stay about the same,31
Decrease,39
Increase,30",No
"Saudi ArabiaEntity,2000,2002,2004,2006,2008,2010,2012,2014,2016,2018
Finland,74.8,76.7,77.2,77.4,77.6,77.4,76.9,76.4,76.3
Ethiopia,16.2,16.1,16.6,16.7,16.6,17.2,17.2,17.7,17.5
Saudi Arabia,22.4,22.4,22.9,23.5,23.2,21.8,22.4,21.6,22.9
Cocos Islands,100.0,100.0,100.0,100.0,100.0,100.0,100.0,100.0,100.0",Saudi Arabia
"6Entity,2000,2002,2004,2006,2008,2010,2012,2014,2016,2018
Finland,68.8,69.2,69.5,70.1,70.6,71.2,71.2,72.0,74.9,80.0
Cocos Islands,100.0,100.0,100.0,100.0,100.0,100.0,100.0,100.0,100.0,100.0
Ethiopia,20.2,16.0,20.0,21.0,22.1,20.0,24.0,21.0,21.0,21.0
Saudi Arabia,31.2,23.0,28.0,25.0,31.0,32.0,3",1
"30Entity,Value
Fewer,29
Don't know,30
More,13
About the same,11
None at all (VOL),16",30
"GrayEntity,Value
Fewer,29
No know at all,16
Don't know,30
About the same,11
More,13",gray
"83Year,It matters really who wins the presidential election,Things will be pretty much the same regardless of who is elected
2000,50,44
2004,67,0
2008,63,32
2012,63,34
2016,74,22
2020,83,16",83
"1.5Year,It matters wins really who the presidential election,Things will be pretty much the same regardless of who is elected
2000,50,0
2004,67,29
2008,63,32
2012,63,34
2016,74,22
2020,83,16",0.32
"41Entity,As Americans,can't solve many of its important problems
Dem/Lean Dem,50.0,48
Rep/Lean Rep,65.0,32
Total,57.0,41",57
"0.8333Entity,As Americans, we can always find ways to solve our problems and get what we want,This country can't solve many of its important problems
Dem /Lean Dem,50,48
Rep/Lean Rep,65,32
Total,57,41",1.058333333
"61Entity,Lower,Middle,Upper
1971,25,61,
1981,26,59,
1991,27,56,
2001,28,54,
2011,29,51,20.0
2016,29,52,19.0",61
"YesEntity,Lower,Middle,Upper
1971,25,61,14
1981,26,59,15
1991,27,56,17
2001,28,54,18
2011,29,51,20
2016,29,52,19",No
"YesYear,Satisfied,Satisfied
2002,71,20
2004,0,26
2006,62,32
2008,56,43
2010,65,34
2012,46,32
2014,45,36
2016,0,0
2018,0,0",Yes
"1.81Year,Satisfied,Dissatisfied
2002,71,20
2004,69,26
2006,62,32
2008,56,36
2010,59,34
2012,46,37
2014,56,36
2016,58,37
2018,0,0",2.125694444
"2013Year,U.S.,EU
2013,0,50
2014,39,23
2015,15,0",2013
"2Year,EU,U.S.
2013,50,51
2014,39,0
2015,31,-",1
"YesYear,Satisfied,Dissatisfied
2002,0,20
2004,69,26
2006,62,32
2008,65,36
2010,59,34
2012,46,32
2014,558,36
2017,58,37",No
"4541Year,Satisfied,Dissatisfied
2002,20,0
2004,69,26
2006,0,32
2008,0,36
2010,0,34
2012,0,0
2014,56,36
2017,58,37",2577420
"Dark BlueYear,Democrat,Republican
2009,0,50
2011,56,51
2013,59,39
2015,56,43
2017,78,0",Red
"2Year,Democrat,Re publican
2009,61,48
2011,56,51
2013,59,39
2015,56,43
2017,78,0",3
"92Year,More mudslinging,Less mudslinging
92,68,16
96,49,36
0,34,46
4,72,14
8,54,27
12,68,19
16,92,0",92
"42.4Year,Less mudslinging,More mudslinging
92,68,16
96,49,36
0,46,34
0,0,0",62.43
"FavorableYear,Unfavorable,Favorable
2006,0,0
2016,86,0",Favorable
"1.59222Year,Unfavorable,Favorable
2006,71,27
2016,86,11",0.9375
"54Entity,Aug 2014,Oct 2014,Feb 2015,July 2015,Dec 2015
Disapprove,31,29,30,26,28
Approve,0,0,63,63,64",54
"YesYear,Disapprove,Approve
Aug 2014,54,53
Oct 2014,33,0
Feb 2015,30,63
July 2015,26,63
Dec 2015,28,0",No
"2009Year,Illegal,Legal
1969,84,12
1974,30,0
1979,66,0
1984,81,0
1994,31,0
1999,63,0
2004,32,60
2009,52,0
2014,45,52",2014
"1989Year,Legal,Illegal
1969,84,0
1974,0,30
1979,66,0
1984,0,0
1989,0,81
1994,0,0
1999,31,63
2004,0,32
2009,0,52
2014,0,45",1969
"OrangeYear,Taliban,India
2009,0,32
2010,23,53
2011,19,57
2012,23,59
2013,33,38
2014,25,51",orange
"35Year,Taliban,India,al Qaeda
2009,32,48,0
2010,23,53,0
2011,19,57,-
2012,23,59,-
2013,-,38,0
2014,25,51,0",57
"20Year,China,U.S.
2008,44,29
2009,45,28
2010,40,0
2011,0,0
2012,57,28
2013,53,33
2014,49,34",29
"2013Year,U.S.,China
2008,0,29
2009,28,45
2010,40,44
2011,37,0
2012,28,57
2013,33,53
2014,0,49",2010
"YesYear,Approve,Disapprove
Jan,0,0
Feb,51,0
Mar,0,0
Apr,0,0
May,51,0
Jun,49,0",Yes
"3Year,Approve,Disapprove
Jan,52,0
Feb,0,0
Mar,47,0
Apr,0,0
May,51,0
Jun,0,0",3
"2011Year,Favor,Oppose
Sept 2008,0,28
Apr 2009,68,0
Feb 2010,0,31
June 2010,52,0
Oct 2010,0,41
Mar 2011,0,57",March 2011
"FavorYear,Favor,Oppose
Sept 2008,0,0
Apr 2009,0,0
Feb 2010,63,0
June 2010,0,44
Oct 2010,51,0
Mar 2011,0,0",Favor
"YesYear,More important to..ownership gun control,Protect the right of Americans to own guns
1993,0,0
1999,0,0
2003,0,0
2008,0,0
2011,0,0",Yes
"1406Year,More important to.. ownership,Protectthe rightof Americans to own guns
1993,57,34
1999,65,30
2008,58,37
2011,50,46",2210
"26Entity,Value
Not only disagree over and plans but policies,73
Can agree on basic facts,even if they often disagree over and policies,26",1
"47Entity,Value
Not only disagree over plans and policies,73
Can agree on basic facts, if they often disagree over plans and policies,26",47
"YesEntity,Value
DK,3
Disapprove,39
Approve,58",Yes
"19.66666Entity,Value
DK,3
Disapprove,39
Approve,58",13
"BlueEntity,Value
Focus on scie entific work/stay out of public policy debates,13
Take active role in public policy debates about science & technology,87",Blue
"NoEntity,Value
Focus on scie nnific public policy debates,13
Take active role in public policy debates about science technology,87",No
"Don't knowEntity,Value
U.S has responsibility,39
U.S doesn't have responsibility,55
Don't know,6",Don't Know
"YesEntity,Value
U.S has responsibility,39
Don't know,6
U.S doesn't have responsibility,55",No
"10Entity,Value
Somewhat unfavorable,3
Favora ble,10
Very unfavorable,79
Don 't know,8",10
"88Entity,Value
Somewhat unfavorable,3
Very unfavorable,79
Don't know,88
Favorable,10",69
"0.41Entity,Value
Do not go online,41
Go online,no SNS,,32
Use SNS,27",41
"YesEntity,Value
Do not go online,41
Go online, no SNS,32
Use SNS,27",Yes
"67Entity,Value
Providing treatment,67
Prosecuting drug users,26
Don't know,7",67
"YesEntity,Value
Providing treatment,67
Prosecuting drug users,26
Don't know,7",No
"BadEntity,Value
Bad,22
Don't know/ Refused (VOL),4
Good,75",Bad
"53Entity,Value
Don't know/ Refused (VOL),4
Bad,22
Good,75",53
"Better offEntity,Value
Better off,72
Less well off,5
About the same,16",Better off
"Better offEntity,Value
About the same,16
Less off,5
Better off,72",Better off
"Important, but lower priorityEntity,Value
Don't know,11
""Not too important/ should not be done"",13
Top priority,35
Important, but lower priority,40","Important, but lower priority"
"40Entity,Value
Not too important/ should not be done,13
Top priority,35
Important, but lower priority,40
Don't know,11",75
"DKEntity,Value
Satisfied,20
DK,2
Dissa tisfied,78",Dissatisfied
"3.5Entity,Value
Satisfied,20
DK,2
Dissatisfied,78",3.9
"76Entity,Value
DK,6
Not safe,76
Safe,19",76
"YesEntity,Value
Not sate,76
DK,6
Safe,19",No
"YesEntity,Major,Minor,No arguments
Dem/Lean Dem,,29,60
Rep/Lean Rep,,30,62
Total,,29,61",Yes
"30Entity,Major,Minor,No arguments
Dem/Lean Dem,,29,60
Rep/Lean Rep,,30,62
Total,9.0,29,61",30
"16Entity,Always/a Imost always,Sometimes,Never
65+,23,36,34
50-64,34,41,24
30-49,47,45,0
Ages 18-29,53,43,0
U.S adults,40,42,16",16
"[0-49, 30-49]Entity,Always/a Imost always,Sometimes,Never
65+,23,36.0,34
50-64,34,41.0,24
30-49,47,45.0,0
Ages 18-29,53,43.0,0
U.S adults,40,42.0,16",65+
"30Entity,a major role,a minor role,No role
Elected officials,24,45,30
Food ind ustry lea ders,42,41,15
The general public,57,32,10
Smallfarm owners,60,30,0
Scientists,60,28,11",11
"60Entity,a major role,a minor role,a No role
Elected officials,24,45,30
leaders,42,41,15
Food ind ustry,42,41,15
The general public,57,32,10
Smallfarm owners,60,30,0
Scientists,60,28,11",60
"No roleEntity,maj or role,minor role,No role
Elected officials,24,45,30
leaders,42,,15
Food ind ustry leaders,42,41,15
The general public,57,32,10
Small farm owners,60,30,9
Scientists,60,28,11",No role
"37.6Entity,major role,minor role,No role
Elected officials,24,45,30
Food ind ustry leaders,42,41,15
The general public,57,32,10
Small farm owners,60,30,0
Scientists,60,28,,0",15
"JapanEntity,Values
Tensions with Russia,33
Large number of refugees leaving Iraq/Syria,39
U.S power and influence,52
Global economic instability,59
China's emergence as a world power,63
Global climate change,68
ISIS,69
countries,71
Cyberattacks from other,71",Japan
"46.5Entity,Values
Tensions with Russia,33
Large number of refugees leaving Iraq/Syria,39
U.S power and influence,52
Global economic instability,59
China's emergence as a world power,63
Global climate change,68
ISIS,69
countries,71",36
"5.32Country,""Share of children who are wasted, 2010""
Haiti,6.12
Libya,5.32
Morocco,5.11
Lebanon,4.5
Colombia,1.45",5.32
"24.65Country,""Share of children who are wasted, 2010""
Haiti,6.12
Libya,5.32
Morocco,5.11
Lebanon,4.5
Colombia,1.45",5.95
"GreenCountry,""Daily meat consumption per person, 1997""
Finland,175.09
Georgia,79.84
Western Asia,69.62",Finland
"YesCountry,""Daily meat consumption per person, 1997""
Finland,175.09
Georgia,79.84
Western Asia,69.62",No
"RedCountry,""Deaths from natural disasters as a share of total deaths, 2014""
Ecuador,0.02
China,0.02
Ireland,-0.01
Armenia,0
Israel,0",Pink
"NoCountry,""Deaths from natural disasters as a share of total deaths, 2014""
Ecuador,0.02
China,0.02
Ireland,0.01
Armenia,0.0
Israel,0.0",No
"Heart diseaseCountry,""Death rates through the 20th century, United States, 1966""
Heart disease,371.7
Cancers,155.3
Stroke,104.7
Accidents,58.1
Pneumonia and influenza,32.5
Road accidents,27.1
Diabetes,17.7
Suicide,10.9
Tuberculosis,3.9",Heart disease
"NoCountry,""Death rates through the 20th century, United States, 1966""
Heart disease,371.7
Cancers,155.3
Stroke,104.7
Accidents,58.1
Pneumonia and influenza,32.5
Road accidents,27.1
Diabetes,17.7
Suicide,10.9
Tuberculosis,3.9",Yes
"North AmericaCountry,""Installed geothermal energy capacity, 2005""
North America,3245
Philippines,1846.5
Croatia,0",North America
"YesCountry,""Installed geothermal energy capacity, 2005""
North America,3245
Philippines,1846.5
Croatia,0",Yes
"ObesityCountry,""Disease burden by risk factor,Northern Mariana Islands, 1990""
Obesity,1001
High blood sugar,879
High blood pressure,676
Smoking,474
Air pollution (outdoor & indoor),360
High cholesterol,328
Outdoor air pollution,177
Diet low in vegetables,169
Indoor air pollution,168
Diet low in fruits,164
Drug use,144
Secondhand smoke,133
Diet high in salt,131
Iron deficiency,119
Child wasting,86
Low physical activity,76
Vitamin A deficiency,43
Unsafe water source,38
Unsafe sanitation,0
Nonexclusive breastfeeding,8
Child stunting,7
Zinc deficiency,3",Obesity
"111Country,""Disease burden by risk factor,Northern Mariana Islands, 1990""
Obesity,1001
High blood sugar,879
High blood pressure,676
Smoking,474
""Air pollution (outdoor & indoor)"",360
High cholesterol,328
""Outdoor air pollution"",177
""Diet low in vegetables"",169
""Indoor air pollution"",168
""Diet low in fruits"",164
Drug use,144
Secondhand smoke,133
""Diet high in salt"",131
""Iron deficiency"",119
Child wasting,86
Low physical activity,76
""Vitamin A deficiency"",43
""Unsafe water source"",38
""Unsafe sanitation"",9
""Nonexclusive breastfeeding"",8
Child stunting,-
Zinc deficiency,3",203
"2Country,""Share of teachers in pre-primary education who are trained, 2004""
Cayman Islands,95.45
Belize,7.21",2
"50.225Country,""Share of teachers in pre-primary education who are trained, 2004""
Cayman Islands,95.45
Belize,7.21",51.33
"2Country,""Death rates from cocaine overdoses, 2011""
United States Virgin Islands,0.13
Gabon,0.13
Southern Sub-Saharan Africa,0.07
Tonga,0.01",2
"YesCountry,Death rates from cocaine overdoses,2011
United States Virgin Islands,0.13,0.13
Gabon,0.13,0.13
Southern Sub-Saharan Africa,0.07,0.07
Tonga,0.01,,,0.01",Yes
"0.1Country,""Government expenditure on pre-primary education as share of GDP, 2005""
United Kingdom,0.3
Colombia,0.1
Mauritius,0.06",0.1
"11.67Country,""Government expenditure on pre-primary education as share of GDP, 2005""
United Kingdom,0.3
Colombia,0.1
Mauritius,0.06",5
"1.93Country,""Rapeseed yields, 1976""
Europe,2.16
France,1.93
Argentina,0.67",1931
"2.18Country,Rapeseed yields,1976
Europe,2.16
France,1.93
Argentina,0.67",2.88
"Low bone mineral densityCountry,""Number of deaths by risk factor aged 15-49, World, 2004""
Unsafe sex,1.31
Alcohol use,880756
High blood pressure,619328
Smoking,597653
High body-mass index (obesity),409812
High blood sugar,334864
""Diet low in fruits"",316783
Drug use,226833
""Diet low in vegetables"",200275
""Outdoor air pollution"",194601
""Household air pollution"",181256
""Unsafe water source"",122777
""Secondhand smoke"",105318
Iron deficiency,96915
""Poor sanitation"",92072
""No access to handwashing facility"",68467
""Low physical activity"",48930
""Low bone mineral density"",13135",Low bone mineral density
"YesCountry,""Number of deaths by risk factor aged 15-49, World, 2004""
Unsafe sex,1.31
Alcohol use,880756.0
High blood pressure,619328.0
Smoking,597653.0
High body-mass index (obesity),409812.0
High blood sugar,334864.0
Diet low in fruits,316783.0
Drug use,226833.0
Diet low in vegetables,200275.0
Outdooor air pollution,194601.0
Household air pollution,181256.0
Unsafe water source,122777.0
Secondhand smoke,105318.0
Iron deficiency,96915.0
Poor sanitation,92072.0
No access to handwashing facility,68467.0
Low physical activity,48930.0
Low bone mineral density,13135",No
"27.5Country,""Mortality from non-communicable diseases, 2000""
Mali,27.5
Denmark,18.3
Kenya,17.3",27.5
"10.2Country,""Mortality from non-communicable diseases, 2000""
Mali,27.5
Denmark,18.3
Kenya,17.3",10.2
"12Country,""Land use per 100 grams of protein""
Lamb & Mutton,184.8
Beef (beef herd),163.6
Cheese,39.8
Milk,27.1
Beef (dairy herd),21.9
Pig Meat,10.7
Nuts,7.9
Other Pulses,7.3
Poultry Meat,7.1
Eggs,5.7
Grains,4.6
Fish (farmed),3.7
Groundnuts,3.5
Peas,3.4
Tofu (soybeans),2.2
Prawns (farmed),2.0",16
"YesCountry,""Land use per 100 grams of protein""
Lamb & Mutton,184.8
Beef (beef herd),163.6
Cheese,39.8
Milk,27.1
Beef (dairy herd),21.9
Pig Meat,10.7
Nuts,7.9
Other Pulses,7.3
Poultry Meat,7.1
Eggs,5.7
Grains,4.6
Fish (farmed),3.7
Groundnuts,3.5
Peas,3.4
Tofu (soybeans),2.2
Prawn (farmed),2",No
"2Country,""Government expenditure on secondary education as share of GDP, 2006""
Cuba,3.52
Nicaragua,0.28",2
"3.24Country,""Government expenditure on secondary education as share of GDP, 2006""
Cuba,3.52
Nicaragua,0.28",3.24
"CambodiaCountry,""Share of pregnant women who receive antiretroviral therapy, 2014""
Burkina Faso,75
Cambodia,70",Burkina Faso
"5Country,""Share of pregnant women who receive antiretroviral therapy, 2014""
Burkina Faso,75
Cambodia,70",5
"LithuaniaCountry,""Commercial bank branches, 2011""
Lithuania,19
Bolivia,9.3",Lithuania
"28.3Country,""Commercial bank branches, 2011""
Lithuania,19.0
Bolivia,9.3",28.3
"58Country,""Cashew nut yields, 1991""
Land Locked Developing Countries,0.6
Low Income Food Deficit Countries,0.58
World,0.52
Least Developed Countries,0.43
Brazil,0.29",0.6
"0.455Country,""Cashew nut yields, 1991""
Land Locked Developing Countries,0.6
Low Income Food Deficit Countries,0.58
World,0.52
Least Developed Countries,0.43
Brazil,0.29",0.475
"0.01Country,""Share of global domestic aviation passenger kilometers, 2018""
Egypt,0.01
Namibia,0.0099998471334612
Luxembourg,0.0",0.01
"0.0141Country,""Share of global domestic aviation passenger kilometers, 2018""
Egypt,0.01
Namibia,0.01
Luxembourg,0.0",0.02
"1.6Country,""Mental health as a risk factor for alcohol dependency or abuse""
Intermittent explosive disorder,6.0
""Dysthymia (persistent, mild depression)"",4.1
Oppositional defiant disorder,3.9
Bipolar disorder,3.6
Social phobia,3.3
Any anxiety disorder,3.2
""Post-traumatic stress disorder (PTSD)"",3.2
Panic disorder,3.2
""Any disruptive behavior disorder"",2.8
Separation anxiety,2.7
Specific phobia,2.7
""Antisocial personality disorder"",2.4
Agoraphobia,2.3
Conduct disorder,2.0
""Attention deficit hyperactivity (ADHD)"",1.8
Any mood disorder,1.8
""Generalized anxiety disorder (GAD)"",1.6
Major depression,1.6",1.6
"4.7Country,""Mental health as a risk factor for alcohol dependency or abuse""
Intermittent explosive disorder,6.0
""Dysthymia (persistent, mild depression)"",4.1
""Oppositional defiant disorder"",3.9
Bipolar disorder,3.6
""Social phobia"",3.3
Any anxiety disorder,3.2
""Post-traumatic stress disorder (PTSD)"",3.2
Panic disorder,3.2
""Any disruptive behavior disorder"",2.8
Separation anxiety,2.7
Specific phobia,2.7
""Antisocial personality disorder"",2.4
""Agoraphobia"",2.3
Conduct disorder,2.0
""Attention deficit hyperactivity (ADHD)"",1.8
Any mood disorder,1.8
""Generalized anxiety disorder (GAD)"",1.6
""Major depression"",1.6",3.2
"20.98Country,""Land use per 100 kilocalories by food and production type""
Mutton & Goat Meat (non-organic),20.98
Beef (organic, grass-fed),13.55
Beef (non-organic, grain-fed),8.27
Mutton & Goat Meat (organic),4.64
Beef (non-organic, grass-fed),3.01
Pork (non-organic),1.17
Poultry (organic),1.12
Pork (organic),1.06
Eggs (organic),0.52
Milk (organic),0.45
Poultry (non-organic),0.41
Eggs (non-organic),0.34
Barley (non-organic),0.27
Milk (non-organic),0.23
Wheat (non-organic),0.17
Soybean (non-organic),0.08
Potatoes (organic),0.08
Tomatoes (non-greenhouse),0.07
Wheat (organic),0.07
Rice (non-organic),0.",20.98
"1.3875Country,""Land use per 100 kilocalories by food and production type""
""Mutton & Goat Meat (non-organic)"",20.98
""Beef (organic, grass-fed)"",13.55
""Beef (non-organic, grain-fed)"",8.27
""Mutton & Goat Meat (organic)"",4.64
""Beef (non-organic, grass-fed)"",3.01
""Pork (non-organic)"",1.17
""Poultry (organic)"",1.12
""Pork (organic)"",1.06
""Eggs (organic)"",0.52
""Milk (organic)"",0.45
""Poultry (non-organic)"",0.41
""Eggs (non-organic)"",0.34
""Barley (non-organic)"",0.27
""Milk (non-organic)"",0.23
""Wheat (non-organic)"",0.17
""Soybean (non-organic)"",0.08
""Potatoes (organic)"",0.08
""Tomatoes (non-greenhouse)"",0.0",0.2
"41Country,""Distribution of job finding methods for employed workers in Europeancountries, Greece""
Personalcontacts,41
Directapplications,36
Other,14.3
Adverts,7.0
Jobagencies,1.6",41
"61Country,""Distribution of job finding methods for employed workers in Europeancountries, Greece""
Personalcontacts,41
Direct applications,36
Other,14.3
Adverts,7.0
Agencies,1.6",5.4
"NepalCountry,""Tuberculosis incidence per 100,000 people, 2000""
Ghana,216
Vietnam,197
Nepal,163",Nepal
"YesCountry,""Tuberculosis incidence per 100,000 people,2000""
Ghana,216
Vietnam,197
Nepal,163",Yes
"5.25Country,""Surface plastic particles by ocean basin, 2013""
Global ocean (total),5.25
North Pacific,1.98
Indian Ocean,1.3
North Atlantic,931.0
South Pacific,490.0
South Atlantic,297.5
Mediterranean Sea,247.4",5.25
"769.8Country,""Surface plastic particles by ocean basin, 2013""
Global ocean (total),52.5
North Pacific,1.98
Indian Ocean,1.3
North Atlantic,931.0
South Pacific,490.0
South Atlantic,297.5
Mediterranean Sea,247.4",252.65
"4Country,""Share of population with severe food insecurity, 2015 to 2017""
El Salvador,12.7
Romania,4.0
Moldova,2.8
Luxembourg,0.8
Switzerland,0.8",1
"14.8Country,""Share of population with severe food insecurity, 2015 to 2017""
El Salvador,12.7
Romania,4.0
Moldova,2.8
Luxembourg,0.8
Switzerland,0.8",1.6
"96.4Country,""Share of primary energy from fossil fuels, 1993""
Algeria,99.67
Indonesia,96.4
Portugal,87.63",96.4
"YesCountry,""Share of primary energy from fossil fuels, 1993""
Algeria,99.67
Indonesia,96.4
Portugal,87.63",Yes
"GreenCountry,""Corruption Perception Index, 2012""
Vanuatu,43
Togo,30
Somalia,8",Teal Blue
"38Country,""Corruption Perception Index, 2012""
Vanuatu,43
Togo,30
Somalia,8",38
"MexicoCountry,""Almond yields, 2001""
Mexico,1.5
""Land Locked Developing Countries"",1.34
Italy,1.2",Mexico
"1.35Country,""Almond yields, 2001""
Mexico,1.5
Land Locked Developing Countries,1.34
Italy,1.2",1.346
"40.7Country,""Share of tropical deforestation from agricultural products""
Cattle,40.7
Oilseeds,18.4
Forestry logging,13.1
Other cereals (excl. rice wheat),8.6
Vegetables, fruit & nuts,7.3
Paddy rice,5.6
Other crops,3.6
Sugar cane/beet,1.1
Wheat,1.0
Plant-based fibers,0.5",40.7
"27.65Country,""Share of tropical deforestation from agricultural products""
Cattle,40.7
Oilsseeds,18.4
Forestry logging,13.1
""Other cereals (excl. rice & wheat)"",8.6
""Vegetables, fruit & nuts"",7.3
Paddy rice,5.6
""Other crops"",3.6
""Sugar cane/beet"",1.1
Wheat,1.0
Plant-based fibers,0.5",6.2
"2Country,""Share of wealth held by top 1% (Chartbook of Economic Inequality 2017),1923""
France,48.53
United States,35.34",2
"39.375Country,""Share of wealth held by top 1% (Chartbook of Economic Inequality 2017),1923""
France,48.53
United States,35.34",41.935
"BelarusCountry,""Ratio of inbound-to-outbound tourists, 2018""
Belarus,13.76
Mauritius,4.73
Hungary,2.03
Papua New Guinea,0.59
Luxembourg,0.51",Belarus
"0.5Country,""Ratio of inbound-to-outbound tourists, 2018""
Belarus,13.76
Mauritius,4.73
Hungary,2.03
Papua New Guinea,0.59
Luxembourg,0.51",0.08
"MongoliaCountry,""Expected years of schooling, 2004""
Mongolia,11.8
Namibia,11.6
Tajikistan,10.6
Mauritania,7.1
Guam,5.6",Mongolia
"YesCountry,""Expected years of schooling, 2004""
Mongolia,11.8
Namibia,11.6
Tajikistan,10.6
Mauritania,7.1
Chad,5.6",Yes
"9.29Country,""Government expenditure on secondary education by country, 1974-2014,2003""
Czechia,21.37
Paraguay,12.51
Laos,9.29",9.29
"YesCountry,""Government expenditure on secondary education by country, 1974-2014,2003""
Czechia,21.37
Paraguay,12.51
Laos,9.29",No
"6Country,""Percentage of children who experience violent discipline at home""
Jamaica,85
Niger,82
Bangladesh,82
Azerbaijan,77
Albania,77",5
"4Country,Percentage of children who experience violent discipline at home
Jamaica,85
Niger,82
Bangladesh,82
Azerbaijan,77
Albania,77",2
"6.85Country,""Personal remittances as a share of GDP, 1986""
Morocco,7.19
Portugal,6.85
Saint Lucia,6.2",6.85
"NoCountry,""Personal remittances as a share of GDP, 1986""
Morocco,7.19
Portugal,6.85
Saint Lucia,6.2",Yes
"4Country,""Share of population using at least basic drinking water source, 2000""
Iceland,100.0
Hungary,99.96
Turkey,95.49
Cambodia,52.4",4
"47.51Country,""Share of population using at least basic drinking water source, 2000""
Iceland,100.0
Hungary,99.96
Turkey,95.49
Cambodia,52.4",47.6
"3Country,""Alcohol consumption per person, 2016""
Slovenia,12.6
Nauru,6.0
Ecuador,4.4",1
"NoCountry,""Alcohol consumption per person, 2016""
Slovenia,12.6
Nauru,6.0
Ecuador,4.4",No
"GreeceCountry,""Share of social protection in government expenditure, 2010""
Greece,35.84
Costa Rica,24.87
United States,21.05",Greece
"NoCountry,""Share of social protection in government expenditure, 2010""
Greece,35.84
Costa Rica,24.87
United States,21.05",Yes
"BlueCountry,""Proportion of female employees by economic sector, Nepal, 2008""
Female share in services,27.85
Female share in industry,42.33
Female share in agriculture,60.65",gray
"YesCountry,""Proportion of female employees by economic sector, Nepal, 2008""
Female share in agriculture,60.65
Female share in industry,42.33
Female share in services,27.85",Yes
"Human capitalCountry,""Total wealth by asset group (2014 US dollars), World, 1995 to 2014""
Human capital,742.07
Produced capital,303.55
Natural capital,107.43
Net foreign assets $1.58 trillion,-4.58",Human capital
"Human capitalCountry,""Total wealth by asset group (2014 US dollars), World, 1995 to 2014""
Human capital,742.07
Produced capital,303.55
Natural capital,107.43
Net foreign assets $4.58,-4.58",742.07
"2015Country,""Primary plastic production by industrial sector, 2015""
Packaging,146
""Building and Construction"",65
Textiles,59
""Other sectors"",47
Consumer & Institutional Products,42
Transportation,27
Electrical/Electronic,18
Industrial Machinery,3",2015
"153Country,""Primary plastic production by industrial sector, 2015""
Packaging,146
""Building and Construction"",65
Textiles,59
""Other sectors"",47
Consumer & Institutional Products,42
""Transportation"",27
""Electrical/Electronic"",18
Industrial Machinery,3",143
"48.01Country,""Emissions of air pollutants, Italy, 2008""
Nitrogen oxides (NOx),51.53
Carbon Monoxide (CO),48.01
Sulphur oxides (SO₂),16.22",48.01
"29.6Country,""Emissions of air pollutant,s, Italy, 2008""
Nitrogen oxides (NOx),51.53
Carbon Monoxide (CO),48.01
Sulphur oxides (SO₂),16.22",32.115
"0.04Country,""Change in stroke death rates by age, Belarus, 2011""
70+ years old,1289.43
50-69 years old,201.38
All ages,190.65
Age-standardized,119.23
15-49 years old,16.4
5-14 years old,0.07
Under-5s,0.04",0.04
"16.4Country,""Change in stroke death rates by age, Belarus, 2011""
70+ years old,1289.43
50-69 years old,201.38
All ages,190.65
Age-standardized,119.23
15-49 years old,16.4
5-14 years old,0.07
Under-5s,0.04",0.11
"56.6Country,""Child labor in Italy, 1901""
Boys,56.6
Both sexes,49.9
Girls,43.1",56.6
"12.7Country,""Child labor in Italy, 1901""
Boys,56.6
Both sexes,49.9
Girls,43.1",13.5
"0.69Country,""Agriculture orientation index for government expenditures, 2000""
Czechia,0.69
United Arab Emirates,0.52
Saint Lucia,0.36
Qatar,0.11",0.69
"0.265Country,""Agriculture orientation index for government expenditures, 2000""
Czechia,0.69
United Arab Emirates,0.52
Saint Lucia,0.36
Qatar,0.11",0.235
"24Country,""Protein efficiency of meat and dairy production""
Eggs,25
Whole Milk,24
Poultry,19.6
Pork,8.5
Lamb/mutton,6.3
Beef,3.8",24
"11.5Country,""Protein efficiency of meat and dairy production""
Eggs,25
Whole Milk,24
Poultry,19.6
Pork,8.5
Lamb/mutton,6.3
Beef,3.8",6.2
"SwitzerlandCountry,""Renewable freshwater resources per capita, 1987""
Switzerland,6172.55
Portugal,3788.62
Dominican Republic,3473.96
Ghana,2247.54",Switzerland
"114.77Country,""Renewable freshwater resources per capita, 1987""
Switzerland,6172.55
Portugal,3788.62
Dominican Republic,3473.96
Ghana,2247.54",1541.08
"AlcoholCountry,""Number of deaths from substance use disorders, United Kingdom, 1990""
Other illicit drugs,548
Alcohol,481
Opioids,264
Amphetamine,36
Cocaine,24",Alcohol
"524Country,""Number of deaths from substance use disorders, United Kingdom, 1990""
Other illicit drugs,548
Alcohol,481
Opioids,264
Amphetamine,36
Cocaine,24",60
"PhilippinesCountry,""Palm oil yields, 1961""
Oceania,18.18
Philippines,6.67
Net Food Importing Developing Countries,5.8
Gabon,5.63",Philippines
"YesCountry,""Palm oil yields, 1961""
Oceania,18.18
Philippines,6.67
Net Food importing Developing Countries,5.8
Gabon,5.63",No
"BrazilCountry,""Share of adults that are obese, 1989""
Brazil,9.8
Japan,1.5
Ethiopia,1.1
Laos,0.8",Brazil
"2.8Country,""Share of adults that are obese, 1989""
Brazil,9.8
Japan,1.5
Ethiopia,1.1
Lacs,0.8",3.4
"United StatesCountry,""Sugar beet production, 1961""
United States,16.26
Asia,6.02
Hungary,2.36
South America,423081.0",United States
"6.32Country,""Sugar beet production, 1961""
United States,16.26
Asia,6.02
Hungary,2.36
South America,423081.0",4.19
"95Country,""Share of one-year-olds vaccinated against hepatitis B (HepB3), 2003""
Mauritius,97
Bhutan,95
Italy,95
Eswatini,90",95
"YesCountry,""Share of one-year-olds vaccinated against hepatitis B (HepB3), 2003""
Mauritius,97
Bhutan,95
Italy,95
Eswatini,90",No
"Deaths from HIV/AIDSCountry,""Prevalence, new cases and deaths from HIV/AIDS, Cuba, 2010""
New infections of HIV/AIDS,2253
Number of people living with HIV (x10),1294
Deaths from HIV/AIDS,227",Deaths from HIV/AIDS
"NoCountry,""Prevalence, new cases and deaths from HIV/AIDS, Cuba, 2010""
New infections of HIV/AIDS,2253
Number of people living with HIV (x10),1294
Deaths from HIV/AIDS,227",Yes
"SamoaCountry,""Depth of the food deficit in kilocalories per person per day, 2010""
IDA blend,114.18
Gambia,71.0
Niger,71.0
Mauritius,37.0
Samoa,23.0",Samoa
"[Niger, Gambia]Country,""Depth of the food deficit in kilocalories per person per day, 2010""
IDA blend,114.18
Gambia,71.0
Niger,71.0
Mauritius,37.0
Samoa,23.0","[Gambia, Niger]"
"$24,688.3Country,""Median household disposable income, 2000""
Austria,24770.5
Norway,24688.3
United Kingdom,18178.53",24688.3
"20005.2Country,""Median household disposable income, 2000""
Austria,24770.5
Norway,24688.3
United Kingdom,18178.53",82.2
"11Country,""Number of deaths by risk factor aged 5-14, World, 2000""
Unsafe water source,59060
Poor sanitation,45009
No access to handwashing facility,32837
Household air pollution,23473
Outdoor air pollution,11326
Secondhand smoke,8538
Alcohol use,3909
Unsafe sex,3877
High blood sugar,2500
Iron deficiency,396
High body-mass index (obesity),221
High blood pressure,189
Drug use,43",13
"YesCountry,""Number of deaths by risk factor aged 5-14, World, 2000""
Unsafe water source,59060
Poor sanitation,45009
No access to handwashing facility,32837
Household air pollution,23473
Outdoor air pollution,11326
Secondhand smoke,8538
Alcohol use,3909
Unsafe sex,3877
High blood sugar,2500
Iron deficiency,396
High body-mass index (obesity),221
High blood pressure,189
Drug use,43",Yes
"5Country,""Prevalence of alcohol use disorders by age, East Asia, 2004""
30-34 years old,1.9
25-29 years old,1.8
15-49 years old,1.65
50-69 years old,1.62
20-24 years old,1.48
All ages,1.33
Age-standardized,1.17
70+ years old,0.97
15-19 years old,0.58
10-19 years old,0.07
5-14 years old,0.04",11
"NoCountry,""Prevalence of alcohol use disorders by age, East Asia, 2004""
30-34 years old,1.9
25-29 years old,1.8
15-49 years old,1.65
50-69 years old,1.62
20-24 years old,1.48
All ages,1.33
Age-standardized,1.17
70+ years old,0.97
15-19 years old,0.58
10-19 years old,0.07
5-14 years old,0.04",No
"Medium car (petrol)Country,""CO2 emissions by mode of transport, 2018""
Medium car (petrol),191.6
Medium car (diesel),168.8
Domestic flight,133.5
Bus,103.9
Motorcycle (medium),100.0
Short-haul flight (economy),81.5
Long-haul flight (economy),78.5
National rail,40.8
Eurostar (International rail),5.9",Medium car (petrol)
"YesCountry,""CO2 emissions by mode of transport, 2018""
Medium car (petrol),191.6
Medium car (diesel),168.8
Domestic flight,133.5
Bus,103.9
Motorcycle (medium),100.0
Short-haul flight (economy),81.5
Long-haul flight (economy),78.5
National rail,40.8
Eurostar (International rail),5.9",Yes
"MalawiCountry,""Proportion of labor force who are women, 2004""
Malawi,49.57
Turkey,26.17
Tunisia,26.01",Malawi
"1.881Country,""Proportion of labor force who are women, 2004""
Malawi,49.57
Turkey,26.17
Tunisia,26.01",1.905805459
"ItalyCountry,Values
Italy,22.0
Sweden,35.0
Ireland,38.0
Norway,56.0","[Italy , 22]"
"2.73Country,""Public health insurance coverage in Western Europe, 1935""
Norway,56
Ireland,38
Sweden,35
Italy,22",2.54
"15.08Country,""General government procurement as a percentage of GDP, OECD, 2015""
Slovakia,17.28
Germany,15.05
Poland,12.17
Switzerland,8.76",27.22
"28.412Country,""General government procurement as a percentage of GDP, OECD, 2015""
Slovakia,17.28
Germany,15.05
Poland,12.17
Switzerland,8.76",389.82
"BlueCountry,""Relative increase in mean heights of men born in 1996 vs. 1896""
New Zealand,6.12
Tajikistan,6.12
Algeria,6.04
Russia,5.68
Democratic Republic of Congo,3.06",navy blue
"0.12Country,""Relative increase in mean heights of men born in 1996 vs. 1896""
New Zealand,6.12
Tajikistan,6.12
Algeria,6.04
Russia,5.68
Democratic Republic of Congo,3.06",0.08
"8.5Country,""Human Rights Violations, 2012""
Central African Republic,8.5
Iraq,8.3
Gabon,6.8
Suriname,5.3
Peru,4.9",8.5
"15Country,""Human Rights Violations, 2012""
Central African Republic,8.5
Ira q,8.3
Gabon,6.8
Suriname,5.3
Peru,4.9",10.2
"3.88Country,""How much food can you buy for working one hour in the manufacturingsector?, 1950""
Milk (1/2 gallon),3.88
Flour (5 lb.),3.24
Eggs (dozen),2.65
Bacon (lb.),2.48
Butter (lb.),2.18
Pork chops (lb.),2.12
Round steak (lb.),1.69",3.88
"3Country,""How much food can you buy for working one hour in the manufacturingsector?, 1950""
Milk (1/2 gallon),3.88
Flour (5 lb.),3.24
Eggs (dozen),2.65
Bacon (lb.),2.48
Butter (lb.),2.18
Pork chops (lb.),2.12
Round steak (lb.),1.69",3
"5668.67Country,""Disposable household income of the lowest decile in the incomedistribution, 2003""
Denmark,14868.49
Germany,13633.5
Australia,5946.35
Greece,8484.68
Slovakia,5668.67",9545.35
"10235.8Country,""Disposable household income of the lowest decile in the incomedistribution, 2003""
Denmark,14868.49
Germany,13633.5
Australia,5946.35
Greece,8484.68
Slovakia,5668.67",14153.35
"YesCountry,""Change in suicide death rate by age, Kazakhstan, 1995""
50-69 years old,50.18
70+ years old,42.63
15-49 years old,39.89
Age-standardized,30.85
All ages,29.74
5-14 years old,2.5",No
"46.78Country,""Change in suicide death rate by age, Kazakhstan, 1995""
50-69 years old,50.18
70+ years old,42.63
15-49 years old,39.89
Age-standardized,30.85
All ages,29.74
5-14 years old,2.5",47.68
"28Country,""Share of women in top income groups, UK, 2013""
Share of women in top 10,28
Share of women in top 5,24.6
Share of women in top 1%,18
Share of women in top 0.5%,15.6
Share of women in top 0.25,13.3
Share of women in top 0.1%,10.8",28
"NoCountry,""Share of women in top income groups, UK, 2013""
Share of women in top 10,28
Share of women in top 5,24.6
Share of women in top 1%,18
Share of women in top 0.5,15.6
Share of women in top 0.25,13.3
Share of women in top 0.1,10.8",No
"BrazilCountry,""Cattle meat per animal, 1961""
United States,214.9
Argentina,210.0
Brazil,191.7
China,96.6",Argentina
"NoCountry,""Cattle meat per animal, 1961""
United States,214.9
Argentina,210.0
Brazil,191.7
China,96.6",No
"MathsCountry,""Male-to-Female Ratio of High School Courses in Math and Science, UnitedStates, 1982""
Chemistry,1.1
Science,1.08
Maths,1.06",Chemistry
"YesCountry,""Male-to-Female Ratio of High School Courses in Math and Science, UnitedStates, 1982""
Chemistry,1.1
Science,1.08
Maths,1.06",Yes
"ZambiaCountry,""Share of global forest area, 2012""
Venezuela,1.15
Zambia,1.13
Guatemala,0.09
Sierra Leone,0.07
Saint Vincent and the Grenadines,0.01",Venezuela
"0.02Country,""Share of global forest area, 2012""
Venezuela,1.15
Zambia,1.13
Guatemala,0.09
Sierra Leone,0.07
Saint Vincent and the Grenadines,0.01",0.02
"GreenCountry,""Average usual weekly hours worked, women 15 years and older, 2010""
Poland,38.15
Luxembourg,32.8
Denmark,31.16
Ireland,30.68",brown
"1.07773Country,Average usual weekly hours worked,women 15 years and older,2010
Poland,38.15,38.15,0
Luxembourg,32.8,32.8,0
Denmark,31.16,31.16,0
Ireland,30.68,30.68,0",1.015645372
"PurpleCountry,""People practicing open defecation in urban areas (%, of urban population),2000""
Eritrea,40.7
Other small states,3.73
Uganda,1.92
Armenia,0.14",Pink
"YesCountry,""People practicing open defecation in urban areas (Percentage of urban population),2000""
Eritrea,40.7
Other small states,3.73
Uganda,1.92
Armenia,0.14",No
"0.85Country,""Average weekly leisure estimates by age, United States, 1970""
Ages 65+ (total),59.5
Ages 14-17 (total),53.9
Ages 14+ (total),41.7
Ages 55-64 (total),41.3
Ages 18-24 (total),39.9
Ages 25-34 (total),34.8",53.9
"NoCountry,""Average weekly leisure estimates by age, United States, 1970""
Ages 65+ (total),59.5
Ages 14-17 (total),53.9
Ages 14+,41.7
Ages 55-64 (total),41.3
Ages 18-24 (total),39.9
Ages 25-64 (total),34.8",Yes
"8.87Country,""Share of the population living in urban areas, 1950""
Palestine,37.3
El Salvador,36.51
Reunion,23.49
South Sudan,8.87",8.87
"28.41Country,""Share of the population living in urban areas, 1950""
Palestine,37.3
El Salvador,36.51
Reunion,23.49
South Sudan,8.87",32.43
"7.54Country,""Expenditures on general government outsourcing ( %GDP)""
Germany,13.4
Norway,9.41
Turkey,7.54
Greece,7.11",7.54
"1.88076Country,""Expenditures on general government outsourcing (GDP)""
Germany,13.4
Norway,9.41
Turkey,7.54
Greece,7.11",1.88
"MyanmarEntity,2005,2006,2007,2008,2009,2010,2011,2012
Myanmar,69.09,,26.95,,,65.72
Zambia,28.50,,26.74,,,29.34
Eastern Sub-Saharan Africa,13.54,,,19.16,,,30.16
New Zealand,11.21,12.10,,13.02,,,23.86",Myanmar
"ZambiaEntity,2005,2006,2007,2008,2009,2010,2011,2012
Myanmar,,,,,,,,
Zambia,28.2,27.8,26.9,28.0,28.1,28.2,28.3,27.4
Eastern Sub-Saharan Africa,21.7,21.4,21.1,21.0,19.9,19.3,18.8,18.4
New Zealand,11.0,11.1,11.2,11.5,11.8,12.2,12.5,12.8",Zambia
"[2008, 2016]Entity,2005,2006,2008,2010,2012,2014,2016
Females (45 to 64),20.8,21.6,20.0,18.3,19.1,21.1,26.5","[2014, 2016]"
"2016Entity,2005,2006,2008,2010,2012,2014,2016
Females (45 to 64),20.3,20.7,22.2,19.5,19.2,21.6,26.8",2015
"GeorgiaEntity,1991,1995,2000,2005,2011
Spain,1.63,1.65,1.67,1.6,1.69
Bahrain,1.2,1.2,1.2,1.5,1.5
Georgia,1.25,1.3,1.25,1.2,1.3",Georgia
"SpainEntity,1991,1995,2000,2005,2011
Spain,1.676864945,1.747259706,1.700527722,1.963963289,2.012692784
Bahrain,1.324742067,1.215051842,1.223212171,1.700405798,1.662726219
Georgia,1.610402625,1.469078111,1.518400321,1.484978394,1.438642804",Spain
"BelizeEntity,2004,2006,2008,2010,2012,2014,2016,2017
Belize,67.09,66.09,68.84,58.67,57.77,59.26,66.03,68.21
Papua New Guinea,51.26,50.19,44.28,40.34,42.63,45.69,48.52,48.54",Belize
"Papua New GuineaEntity,2004,2006,2008,2010,2012,2014,2016,2017
Papua New Guinea,45.0,,,,,,54.0
Belize,67.0,,,,,,67.0",Papua New Guinea
"BeninEntity,1990,1995,2000,2005,2010
Albania,38.011979,52.708364,65.272820,66.356922,85.929022
Benin,74.163200,22.845710,87.604073,81.442261,84.27303
Sudan,51.128740,45.789366,42.839363,55.021583,67.064623",Benin
"SudanEntity,1990,1995,2000,2005,2010
Albania,85.0,,86.6,,86.5
Benin,82.3,,83.7,,85.5
Sudan,55.0,,57.1,,62.2",Sudan
"MongoliaEntity,Values
2017,31.0
2015,29.0
2010,35.0
2005,43.0
2000,54.0
1995,53.0
1991,47.0",Mongolia
"2Entity,1991,1995,2000,2005,2010,2015,2017
Mongolia,51.01,46.52,48.84,42.28,33.56,27.98,28.13",6
"North AmericaEntity,2004,2006,2008,2010,2012,2014
Eritrea,4.569182764,4.153084922,4.014895043,3.834441299,3.746285474,3.757640234
North America,4.634359595,4.221533933,2.929000515,2.869236143,2.78045922,2.80534263",North America
"2012Entity,2004,2006,2008,2010,2012,2014
Eritrea,4.556,4.461,4.422,4.362,4.284,4.226
North America,4.931,4.833,4.788,4.741,4.653,4.587",2014
"1Entity,2000,2002,2004,2006,2008,2010,2012,2014
North Korea,0,0,0,0,0,0,0,0",1
"increasingEntity,2000,2002,2004,2006,2008,2010,2012,2014
North Korea,0,0,0,0,0,0,0,0",No
"Hong KongEntity,2003,2004,2005,2006,2007
Hong Kong,1.811084,2.130848,2.539547,3.145352,3.190756
Serbia,1.731459,1.971101,2.232378,2.761663,2.990837",Hong Kong
"2005Entity,2003,2004,2005,2006,2007
Hong Kong,2.0,2.413,2.791,3.247,3.32
Serbia,1.937,2.149,2.454,3.041,3.2","[2003, 2004]"
"South Eastern AsiaEntity,1997,2000,2005,2010,2015,2017
South Eastern Asia,4.93,5.95,8.79,11.92,14.84,14.27
Honduras,0.02,0.02,0.02,0.02,0.02,0.02
Cameroon,0.02,0.02,0.02,0.02,0.02,0.02
Costa Rica,0.02,0.02,0.02,0.02,0.02,0.02
Solomon Islands,0.02,0.02,0.02,0.02,0.02,0.02",Cameroon
"redCountry,""Land use for palm oil production""
South Eastern Asia,14.6
Honduras,3.2
Cameroon,5.5
Costa Rica,2.2
Solomon Islands,1.8",Pink
"EstoniaEntity,1998,2000,2002,2004,2006,2008,2010,2012
Estonia,48113.04049,43173.6664,41660.18,40530.437,42934.2957,45820.11,51876.211,53708.615
Lebanon,44699.4816,41276.0614,40067.9216,39460.198,37360.0204,42040.5657,48846.360,47523.955
Costa Rica,24809.9426,28422.1063,27527.282,28",Estonia
"NoEntity,1998,2000,2002,2004,2006,2008,2010,2012
Estonia,46058.1,43325.8,43158.9,45530.4,51230.9,56018.6,55991.9,57024.6
Lebanon,44970.6,39761.2,42641.6,44039.8,41822.1,47337.7,51572.2,49259.8
Costa Rica,25859.5,28264.2,28016.5,28183.4,28841.2,29206.6,30050.5,32246.6
Nepal,-,5785.6,3",No
"1961Entity,1949,1955,1960,1965,1970,1975,1980
""China - Death Rate"",6.37,,,,,6.5,,,,,4.03
""China - Birth Rate"",37.25,,,,,31.6,,,,,22.51",1960
"5Entity,1949,1955,1960,1965,1970,1975,1980
Birth Rate,37.0,34.0,33.0,32.0,30.0,27.0,26.0
Death Rate,18.0,13.0,14.0,11.0,6.0,4.0,4.0",2
"4Entity,1990,1995,2000,2005,2011
Gender gap in managerial jobs,10.2,,,,
Gender gap in ""male"" professional jobs,,8.4,,,,
Gender gap in collective-bargaining coverage,,,,0.0",4
"1990Entity,1990,1995,2000,2005,2011
Gender gap in managerial jobs,10.19,8.7,5.7,4.2,3.2
Gender gap in """"male"" professional jobs,6.41,5.08,4.17,2.55,1.5
Gender gap in collective-bargaining coverage,3.66,6.61,4.04,2.84,2.0",1990
"2Entity,1880,1890,1900,1910,1920,1930
Australia,0.0,0.0,0.0,1.0,1.8,2.3
Canada,0.0,0.0,0.0,0.1,0.0,0.4",2
"YesEntity,1880,1890,1900,1910,1920,1930
Australia,0.052849967,0.097094096,0.170336309,0.286118425,0.408124408,0.546283332
Canada,0.029725694,0.065281011,0.083755081,0.107144596,0.208418191,0.299057044",Yes
"BlueEntity,2005,2006,2008,2010,2012,2014
Moldova,8.99,8.99,8.99,8.99,8.99,8.99
Tanzania,5.68,5.68,5.68,5.68,5.68,5.68
Suriname,5.89,5.89,5.89,5.89,5.89,5.89
Madagascar,3.51,3.51,3.51,3.51,3.51,3.51",Purple
"2008Entity,2005,2006,2008,2010,2012,2014
Moldova,9.0,9.0,9.0,9.0,9.0,9.0
Tanzania,7.0,7.0,7.0,7.0,7.0,7.0
Suriname,6.0,6.0,6.0,6.0,6.0,6.0
Madagascar,5.0,5.0,5.0,5.0,5.0,5.0",6
"2012Entity,2011,2012,2013,2014,2015,2016
Germany,57.4,,,,,,67.8
Dominican Republic,38.2,,,39.0,,,39.0
Bolivia,63.5,,,58.7,,,60.5","[2013, 2016]"
"[Germany, Bolivia, Dominican Republic]Entity,2011,2012,2013,2014,2015,2016
Germany,56.4,66.5,66.8,68.5,67.2,67.4
Bolivia,63.1,69.3,69.1,66.2,60.9,63.7
Dominican Republic,64.1,39.0,46.9,46.6,44.1,43.1","[Germany, Bolivia, Dominican Republic]"
"2Entity,1999,2000,2001,2002,2003
Philippines,9.67,10.0,8.67,9.73,9.93
Nepal,11.91,11.26,13.02,11.27,9.14",2
"4Entity,1999,2000,2001,2002,2003
Philippines,9.15938,9.96239,8.80565,9.59467,9.72054
Nepal,,,12.4518,9.95309,9.12411",3
"1988Entity,1979,1980,1982,1984,1986,1988,1990,1992,1994
Guinea,4.995999999999998,3.765999999999994,3.244300000000001,2.594100000000003,1.984099999999876,1.067100000000176,0.9619999999994414,1.012599999996629,1.014399999993735",1992
"2.0Entity,1979,1980,1982,1984,1986,1988,1990,1992,1994
Guinea,5.0,0.0,3.0,2.8,2.0,1.0,1.0,1.0,1.0",3
"2Entity,1850,1860,1870,1880,1890,1900,1910,1920,1930
United States,73.1,73.1,73.1,78.2,80.9,65.9,58.7,56.0,55.5",4
"4Entity,1850,1860,1870,1880,1890,1900,1910,1920,1930
""United States"",77.159,77.8022,80.8351,82.2639,84.8308,66.9744,56.7544,57.6026,59.2145",1
"2014Entity,2005,2006,2008,2010,2012,2014
Benin,0.0056,0.0348,0.0449,0.0447,0.0889,0.0873",2014
"10Entity,2005,2006,2008,2010,2012,2014
Benin,0.00903982814,0.0311490249,0.0443913837,0.0478587298,0.0868570427,0.0879773342",6
"4Entity,1995,1996,1998,2000,2002,2004,2006
Botswana,568500.0,649600.0,,1257700.0,,1699600.0
Nigeria,,,,,,1150800.0
Honduras,42000.0,,586600.0,586600.0,,731500.0
American Samoa,1000.0,,1000.0,,1000.0,,,0",4
"2Entity,1995,1996,1998,2000,2002,2004,2006
Botswana,519615.4284367684,556947.512311833,666104.3685218517,1188215.4909264968,1293462.02817676,1429272.568867658,1465307.329090641
Nigeria,395226.1822963893,382851.2325992655,466520.0840023186,1177930.690959485,1202653.15699968",2
"BurundiEntity,1990,1992,1994,1996,1998,2000,2002,2004
Burundi,1.0022817646,1.056494812,1.231315766,1.369725431,1.442679293,1.535100802,1.635814405,1.768619952
Russia,0.405036678,0.42676718,0.442870487,0.471842473,0.513720662,0.56865934,0.629710194,0.655889132",Burundi
"0.7Entity,1990,1992,1994,1996,1998,2000,2002,2004
Burundi,1.08521,1.16173,1.23645,1.28367,1.29959,1.32394,1.36432,1.40551
Russia,0.40473,0.40669,0.42418,0.53205,0.56249,0.56711,0.54965,0.47783",1.4
"1995Entity,1990,1992,1994,1996,1998,2000,2002,2004
United Kingdom,1898.389196,1681.555307,1780.230644,1717.149166,1648.65211,1568.38691,1541.045492,1213.570441",2004
"[United Kingdom, Cape Verde]Entity,1990,1992,1994,1996,1998,2000,2002,2004
United Kingdom,1947.6879974,1914.3421292,1863.1424341,1768.1850758,1641.6679693,1471.9551194,1549.7285336,1348.1960457
Cape Verde,2118.576052,1650.2504437,1702.8110653,1654.2813632,1615.9682259,1503.8571952,1514.673866,1733.536","[United Kingdom, Cape Verde]"
"GabonEntity,1989,1992,1994,1996,1998,2000,2002,2004,2007
Gabon,5,0,0,0,0,16,0,0,1
Sao Tome and Principe Dominica,0,0,0,0,0,0,0,0,0",Gabon
"2007Entity,1989,1992,1994,1996,1998,2000,2002,2004,2007
Gabon,3.02,2.36,5.38,5.44,2.84,16.54,6.3,4.13,1.95
Sao Tome and Principe,0.08,0.34,0.44,0.52,0.37,0.28,0.55,0.44,0.44
Dominica,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00",18
"YellowEntity,2004,2005,2006,2007,2008,2009,2010,2011
Jamaica,40.0,,55,,52,,57
Euro area,25.0,,28,,32,,29",orange
"2009Entity,2004,2005,2006,2007,2008,2009,2010,2011
Jamaica,41.6115997091484,59.4945093598389,58.1423884298926,47.9680301120449,46.3395205038817,54.1539589566741,56.9849622773883,48.9180467121314
Euro area,26.1692929816374,25.4399424548258,26.2345696426706,26.0240298437698,2",2005
"OrangeEntity,1992,1994,1996,1998,2000,2002,2004,2006,2008,2010
Netherlands,20861.34,21871.11,22692.3,23780.96,23956.12,23661.3,24109.19,25672.88,26980.59,26684.42
Poland,8610.16,8409.52,8205.64,8004.58,7978.01,8053.2,8594.31,9575.1,10893.5,11827.37",orange
"2000Entity,1992,1994,1996,1998,2000,2002,2004,2006,2008,2010
Netherlands,21675,21147,22344,23567,23709,23134,22753,26779,26924,26250
Poland,8757,8887,9177,9268,9058,9209,9882,10363,11435,12066",1992
"NepalEntity,2006,2007,2008,2009,2010,2011,2012,2013,2014
Nepal,46.1,47.32,69.31,56.08,32.59,80.81,45.36,26.47,15.48
Haiti,105.69,92.07,80.24,56.22,40.71,35.8,47.66,16.26,9.7
Belize,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0",Belize
"2Entity,2006,2007,2008,2009,2010,2011,2012,2013,2014
Nepal,110.1,83.1,56.7,65.1,42.5,60.8,48.2,16.7,17.5
Haiti,102.1,88.0,68.4,54.7,43.7,48.6,47.9,19.5,18.0
Belize,15.8,4.1,8.6,5.5,3.4,2.7,0.7,0.4,0.0",2
"AsiaEntity,1961,1965,1970,1975,1981
Asia,14.0,20.0,22.0,22.0,22.0",Asia
"[1975, 1976]Entity,1961,1965,1970,1975,1981
Asia,14.87868070833333,20.65714285714286,22.86458333333333,24.51606055555556,23.44694444444444","[1965, 1970]"
"2014Entity,2008,2009,2010,2011,2012,2013,2014
Eritrea,799317.3734013621,825105.7842976885,844988.2239052758,865495.1596487738,875991.1764173348,884698.2838240882,894419.5513142572
Fiji,819889.4310099611,821909.2784712341,823993.0777650953,825980.1312568043,827976.356",2014
"EritreaEntity,2008,2009,2010,2011,2012,2013,2014
United States Virgin Islands,166034.9,167712.8,170090.4,174498.9,178960.0,182764.0,186625.9
Fiji,775843.3,828648.4,882806.1,909549.6,919700.8,891359.5,880169.2
Eritrea,849529.8,892212.6,938069.7,949145.1,976777.0,982022.0,997384.8",Fiji
"1960Entity,1840,1860,1880,1900,1920,1940,1960,1975
,273.89,276.05,280.13,280.49,281.93,284.38,286.86,289.89",1975
"8Entity,1840,1860,1880,1900,1920,1940,1960,1975
Nitrous oxide (N2O) atmospheric concentration,276.216,276.697,277.527,278.428,279.281,280.25,281.434,283.429",75
"NoEntity,2000,2001,2002,2003,2004,2005,2006
Israel,100.0,100.0,100.0,,100.0,100.0
Angola,36.0,36.0,36.0,38.0,38.0,38.0,38.0
China,48.0,52.0,54.0,54.0,54.0,54.0,57.0
South Sudan,100.0,100.0,100.0,100.0,100.0,100.0,100.0",Yes
"NoEntity,2000,2001,2002,2003,2004,2005,2006
Angola,38.6,44.9,46.2,47.1,48.0,48.7,49.4
China,50.4,56.1,62.0,66.9,64.2,68.9,69.5
Israel,100.0,100.0,100.0,100.0,100.0,100.0,100.0
South Sudan,10.0,10.0,10.0,10.0,10.0,10.0,10.0",Yes
"EritreaEntity,1990,1992,1994,1996,1998,1999,2000
Jamaica,73.15,73.54,78.13,82.32,87.51,87.89,88.33
Eritrea,22.11,22.58,24.19,26.92,33.00,32.49,32.93
South Sudan,54.51,59.22,61.23,71.3,80.21,80.92,81.6",Eritrea
"South SudanEntity,1990,1992,1994,1996,1998,1999
Jamaica,74.58008,75.41434,76.84127,80.89005,83.93013,86.87027
Eritrea,23.307221,25.61863,27.12062,27.56976,28.55563,30.61934
South Sudan,50.14721,53.49451,55.97601,58.11154,59.5735,62.7684",South Sudan
"70+ years oldEntity,1995,1996,1998,2000,2002,2004,2005
70+ years old,61.18333333,60.82333333,60.12666667,60.24666667,36.67666667,35.64666667,37.74666667
50-69 years old,36.48333333,36.79166667,36.93333333,36.35833333,35.90833333,34.33333333,35.69166667
Age-standardized,11.73333333,11.87833333,12.",50-69 years old
"1Entity,1995,1996,1998,2000,2002,2004,2005
70+ years old,66.0,66.0,65.0,63.0,62.0,62.0,61.0
50-69 years old,38.0,39.0,39.0,39.0,38.0,38.0,38.0
Age-standardized,14.0,14.0,14.0,13.0,12.0,12.0,11.0
15-49 years old,25.0,25.0,25.0,23.0,21.0,19.0,15.0
All Ages,16.0,16.0,16.0,15.0,14.0,12.0,10.0
15-4 years old,14.0,1",16
"ChileEntity,1981,1985,1990,1995,2000,2002
Botswana,182.02678,155.37548,112.89817,130.87039,146.47627,132.78468
Chile,363.19232,295.3076,276.5111,144.8342,161.96845,112.23984
Comoros,21.09145,0.001872184,0.001872184,0.001872184,18.28707,22.77524",Botswana
"ChileEntity,1981,1985,1990,1995,2000,2002
Comoros,0.0,,,,,122.0
Botswana,168.0,158.0,,150.0,,,149.0
Chile,276.0,271.0,257.0,177.0,149.0,,148.0
Comoros,0.0,,,,,122.0",Chile
"Cape VerdeEntity,2010,2011,2012,2013,2014,2015,2016
Cape Verde,0.6298489514430625,0.9401747991480294,0.5949511889021826,0.9334869188531164,1.0101313283215745,0.8945640441461667,0.9970465147871388
Latvia,100.0,100.0,100.0,100.0,100.0,100.0,100.0
Tajikistan,0.03409695325371094,0.0953594980",Cape Verde
"[2013, 2014]Entity,2010,2011,2012,2013,2014,2015,2016
Cape Verde,0,100,50,100,100,89,100
Latvia,0,100,50,100,100,89,100
Tajikistan,30,42,55,62,86,93,96",2014
"SwitzerlandEntity,1995,1996,1998,2000,2002,2004,2006,2007
Switzerland,28.882,28.658,28.274,27.897,27.809,27.675,27.541,27.522
Romania,36.097,35.942,35.78,36.006,36.667,36.85,37.242,37.21
Portugal,39.5,39.3,38.9,38.0,38.1,38.0,38.7,38.7",Portugal
"2Entity,1995,1996,1998,2000,2002,2004,2006,2007
Romania,40.5518551139882,39.9095779767206,37.77738478460804,38.58937420650842,37.60028962849976,38.60740466814719,39.57628639771854,37.50998692706764
Portugal,46.23345884141336,44.12111220376808,40.26392099207621,37.3022672410",2
"Neonatal (first 28 days of life)Entity,1990,1995,2000,2005,2011
Child (before age 5),2.0,1.22,1.0125,0.9525,0.7875
Infant (first year of life),1.829187,1.315562,1.036671,0.944402,0.726454
Neonatal (first 28 days of life),1.436152,1.01323,0.575964,0.402581,0.286308",Child (before age 5)
"2005Entity,1990,1995,2000,2005,2011
""Child (before age 5)"",1.92,1.73,,,,,
""Infant (first year of life)"",1.98,1.65,,,,,
Neonatal (first 28 days of life),.24,1.44,,,,,",1990
"[1972, 1974]Entity,1970,1972,1974,1976,1978,1980
Fiji,0.2,0.2,0.22,0.33,0.85,0.89",1970
"[1979, 1980]Entity,1970,1972,1974,1976,1978,1980
Fiji,0.192,0.23,0.221,0.415,0.562,0.88",1978
"IndiaEntity,1999,2000,2002,2004,2006,2008,2009
Ireland,7.4,8.4,10.6,12.2,13.2,13.6,13.1
Bulga ria,4.0,4.0,4.0,4.0,4.0,5.0,5.0",Ireland
"IrelandEntity,1999,2000,2002,2004,2006,2008,2009
Ireland,7.294404285714286,,12.056808868451225,12.36198184566397,13.11968183012642,13.70521965211446
Bulgaria,,,,4.368421052631572
Romania,,,,2.791108701203464",Ireland
"TogoEntity,1990,1992,1994,1996,1998,2000,2002,2004
Bangladesh,662.0,676.0,690.0,695.0,705.0,720.0,730.0,745.0
Ukraine,284.0,290.0,295.0,297.0,297.0,298.0,299.0,300.0
Togo,234.0,237.0,240.0,243.0,245.0,247.0,249.0,250.0
Belize,119.0,122.0,123.0,124.0,124.0,125.0,126.0,126.0",Togo
"1Entity,1990,1992,1994,1996,1998,2000,2002,2004
Bangladesh,674.3510789,661.6707061,649.3884221,637.4096661,624.3505027,611.7392666,600.5902388,683.451086
Ukraine,288.4193071,288.4193071,288.4193071,288.4193071,288.4193071,288.4193071,288.4193071,288.4193071
Togo,223.2718028,223",3
"MaliEntity,2002,2003,2004,2005,2006,2007
Mali,4,4,3,5,2,6
Mongolia,1,0,0,1,1,2
Ecuador,0,0,0,0,0,1",Mali
"2005Entity,2002,2003,2004,2005,2006,2007
Mali,3.1,,20.8,,6.2
Mongolia,0.2,,0.7,,0.9
Ecuador,0.1,,0.2,,1.2",2005
"3Entity,1965,1970,1975,1980,1984
Iran,3.8,4.7,10.4,8.9,10.4
Taiwan,3.1,5.4,9.5,10.1,9.5
Morocco,1.2,2.1,2.4,3.0,2.9",3
"IranEntity,1965,1970,1975,1980,1984
Iran,3.72,4.8,9.81,9.3,10.06
Taiwan,2.94,3.7,6.94,9.77,10.25
Morocco,1.33,1.9,2.9,3.01,3.01",Taiwan
"2016Entity,2012,2013,2014,2015,2016
Upper secondary,89.0,88.0,87.0,86.0,89.0
Lower secondary,65.0,64.0,63.0,64.0,64.0
Primary school,45.0,45.0,45.0,45.0,47.0",2016
"Primary schoolEntity,2012,2013,2014,2015,2016
Primary school,50.2,,,,,53.3
Lower secondary,64.9,,,,,66.2
Upper secondary,86.9,,,,,88.9",Primary school
"SwitzerlandEntity,1990,1992,1994,1996,1998,2000,2002,2004
Switzerland,5.39,,,5.36,,,4.62",Switzerland
"2000Entity,1990,1992,1994,1996,1998,2000,2002,2004
Switzerland,5.649,5.552,5.702,5.58,5.454,4.977,5.104,4.867",2004
"BelgiumCountry,1976,1978,1980,1982,1984,1986,1988,1990,1992,1994,1996,1998,2000,2002,2004
Belgium,13.3224561,12.6654467,4.4698441,11.2489538,10.4467391,5.5855648,5.9426499,11.9617239,10.9873111,11.485299,12.2939476,12.0809718,11.0944906,11.071485,10.2398906
Libya,3.7776067,0.8",Belgium
"2Country,1976,1978,1980,1982,1984,1986,1988,1990,1992,1994,1996,1998,2000,2002,2004
Belgium,12.76,12.04,13.8,10.07,10.53,10.62,11.74,10.94,11.6,11.5,11.24,11.55,11.21,10.88,10.87
Libya,5.2,5.81,4.65,5.58,5.74,4.78,6.65,6.63,6.09,6.86,6.27,6.69,7.07,6.74,6.85
Uzbekistan,3.9,3.9,",1
"YesEntity,More,About the same,Less
China,17,31,50
U.S,29,41,29",Yes
"YesEntity,More,About the same,Less
China,,31,50
U.S.,29,41,29",No
"3Entity,Very closely,Fairly closely,Not too closely,Not at all closely
The coronavirus outbreak,46,42.0,10,
The 2020 presidential candidates,19,33,31,16",4
"38Entity,Very closely,Fairly closely,Not too closely,Not at all closely
The coronavirus outbreak,46,42,10,0
The 2020 presidential candidates,19,33,31,16",25
"Tend to favor one sideEntity,Tend to favor one side,fairly Deal with sides all
Dem/Lean Dem,69,29
Rep/Lean Rep,91,8
U.S adults,79,20",Tend to favor one side
"Dem/Lean DemEntity,Tend to favor one side,fairly Deal with all sides
Dem/Lean Dem,69,29
Rep/Lean Rep,91,8
U.S adults,79,20",Rep/Lean Rep
"Dark BlueEntity,Prioritize economic relations with China,Promote human rights in China
U.S.,23,73
IR scholars,24,76",Blue
"60Entity,Prioritize economic relations with China,Promote human rights in China
U.S.,23,73
IR scholars,24,76",98
"U.S.Entity,Bad,Good
U.S.,84.0,15
China,60.0,37
EU,39.0,57
who,34.0,64
Our country,25.0,74",U.S.
"U.SEntity,Bad,Good
U.S,84.0,15
China,60.0,0
EU,39.0,57
who,34.0,0
Our country,25.0,74",U.S.
"YesEntity,Major threat,Minor threat,Not a threat
""Large numbers of moving people country to another from one"",40,40,18
between groups ethnic or countries,48,41,0
""Long-standing conflict"",48,41,0
Global poverty,53,35,0
The condition of the global economy,58,35,0
weapons,61,31,0
""The spread of nuclear"",61,31,0
""Cyberattacks from other countries"",65,30,0
Terrorism,66,30,0
""The spread of infectious diseases"",69,28,0
Global climate change,70,24,5",Yes
"0.5Entity,Major threat,Minor threat,Not a threat
""Large numbers of people moving from one country to another"",40,40,18.0
between countries or ethnic groups,48,41,
Long-standing conflict,48,41,0.0
Global poverty,53,35,0.0
The condition of the global economy,58,35,0.0
weapons,61,31,0.0
The spread of nuclear,61,31,0.0
Cyberattacks from other countries,65,30,0.0
Terrorism,66,30,0.0
infectious diseases,69,28,0.0
The spread of infectious diseases,69,28,0.0
Global climate change,70,24,5.0",1
"62Entity,No significant changes are needed,Significant changes are needed
Dem/Lean Dem,20,79
Rep/ Lean Rep,57,41
Total,37,62",62
"39Entity,No significant changes are needed,Significant changes are needed
Dem/Lean Dem,20,79
Rep/Lean Rep,57,0
Total,37,62",49
"Too muchEntity,Too little,About the right amount,Too much
national parks,54.0,40,0
Protect open lands in,54.0,40,0
habitats,62.0,32,0
Protect animals and their,62.0,32,0
change,65.0,25,0
Reduce effects of climate,65.0,25,0
rivers and streams,67.0,29,0",Too little
"60Entity,Too little,About the right amount,Too much
national parks,54,40,5
habitats,62,32,6
change,65,25,9
Reduce effects of climate,65,25,0
Protect animals and their,62,32,6
national parks,54,40,5",62.6
"48Entity,Poor,Only fair,Good,Excellent,NET
Donald Trump,63,48,15.0,21.0,15
Your state elected officials,44.0,18.0,26.0,39.0,56
Your local elected officials,39.0,12.0,27.0,,0
as those at the CDC,36.0,,11.0,,0
Public health officials such,36.0,,11.0,25.0,,0
centers in your area,12.0,9.0,,45.0,,88
Hospitals and medical,12.0,,12.0,,0,0",15
"YesEntity,Poor,Only fair,Good,Excellent,NET
Donald Trump,63,48,15,21,15
Your state elected officials,,26,39,16,56
Your local elected officials,39,12,27,47,13
as those at the CDC,36,11,25,47,16
Public health officials such,36,11,25,47,16
centers in your area,NET,12,9,45,43,88
Hospitals and medical,36,,12,9,45,43
""Majority of Americans are critical of Trump's response to COVID-19; nearly half say he is doing 'poor' job"","""","""","""","""",""""",No
"63Entity,U.S.,Both (VOL),Russia
East,23,36,38
West,43,29,21",29
"YesEntity,U.S.,Both (VOL),Russia
East,23,36,38
West,43,29,21",No
"68Entity,Very well,Fairly well,NET
Lean Re publican,36,,77
Republican,,32,93
Mod/Lib,32,,75
Conserv,63,31,94
HS or less,56,33,89
Some colle ge,51,36,87
College grad,45,40,85
Postgrad,42,38,80
65+,68,26,94
50-64,58,33,92
30-49,,42,82
Ages 18-29,31,45,76
All Rep/Lean Rep,,36,87",68
"2Entity,Very well,Fairly well,NET
Lean Republican,36,41,77
Republican,61,32,93
Mod/Lib,32,44,75
Conserv,63,31,94
Postgrad College grad Some college HS or less,56,36,8785
65+,68,26,94
50-64,58,33,92
30-49,41,42,82
Ages 18-29,31,45,76
All Rep/Lean Rep,51,36,87",2
"182Entity,Very strong,Strong,Not very strong,No conflicts
People in cities & people in rural areas,15.0,25.0,35,20.0
Young & & People in cities &  older people,14.0,27.0,41,16.0
Black & white people,19.0,34.0,34,10.0
Rich & poor people,31.0,28.0,,
Democrats & Republicans,71.0,20.0,5,0.0",71
"25Entity,Very strong,Strong,Not very strong,No conflicts
People in cities & people in rural areas,15,25,35,20
Young & older people,14,27,,16
Black & white people,19,34,34,10
Rich & poor people,31,28,,11
Democrats & Republicans,71,20,5,0",24
"20Entity,All,Most,Only some,None
65+,34,56,,,,
50-64 5,29,59,7,,,,
30-49,24,57,15,,,,
Ages 18-29 2,20,54,23,,,,",20
"56Entity,All,Most,Only some,None
65+,34,56,0.0,0
50-64,29,59,0.0,0
30-49,24,57,0.0,15
Ages 18-29,20,54,23.0,0",44
"Generally produces accurate conclusionsEntity,Can be used to produce any conclusion the researcher wants,Generally produces accurate conclusions
Dem/lean Dem,29,70
Rep/lean Rep,44,55",Generally produces accurate conclusions
"0.238095238Entity,Can be used to produce any conclusion the researcher wants,Generally produces accurate conclusions
Dem/lean Dem,29,70
Rep/lean Rep,44,55",0.414285714
"LiberalEntity,Will focus too much,Will not focus enough
Liberal,46,52
Cons/Mod,55,43
Dem /Lean Dem,51,0",46
"YesEntity,Will focus too much,Will not focus enough
Liberal,46,52
Cons,55,43
Dem/Lean Dem,51,47",No
"Ages 18-29Entity,U.S. efforts usually make world problems worse,Problems in without would be worse U.S.
Liberal,40.0,54
Cons/Mod,35.0,59
Dem/Lean Dem,,,56
Mod/Lib,24.0,71
Rep/Lean Rep,19.0,76
65+,23.0,68
50-64,21.0,73
30-49,34.0,61
Ages 18-29,43.0,50
Total,29.0,64",Ages 18-29
"YesEntity,U.S. efforts usually make world problems worse,Problems in without would be worse U.S.
Liberal,40,54
Cons/Mod,35,59
Dem/Lean Dem,37,56
Mod/Lib,24,71
Conserv,16,79
Rep/Lean Rep,19,76
65+,23,68
50-64,21,73
30-49,34,61
Ages 18-29,43,50
Total,29,64",Yes
"BlueEntity,a lot,Some,Not too much,Not at all
Elected officials,26.0,38,30,0
The news media,34.0,33,23,0
People from holistic or alternative health groups,35.0,33,21,0
""Pharmaceutical industry leaders"",13.0,36,30,20
Medical scientists,55.0,35,5,0",Dark blue
"56Entity,a lot,Some,Not too much,Not atall
Elected officials,26,38,30,0
The news media,8,34,33,23
or alternative health groups,9,35,33,21
People from holistic,9,35,33,21
""Pharmaceutical leaders"",13,36,30,20
Medical scientists,55,35,,0",56
"37Entity,Values
MEDIAN,34.0
India,
Kenya,14.0
Philippines,20.0
Vietnam,30.0
South Africa,30.0
Mexico,34.0
Tunisia,37.0
Jordan,37.0
Colombia,40.0
Venezuela,
Lebanon,57.0",37
"3Entity,Values
median,34
India,11
Kenya,14",3
"18Entity,Very concerned,Somewhat concerned,Not concerned
communicating face-to-to,48,26,22
Losing the ability to,48,26,22
Harassment or bullying,59,21,16
Mobile phone addiction,62,17,18
""incorrect information"",64,25,14
Exposure to false or,64,25,14
thief,66,17,16
Identity theft,66,17,16
to harmful content,79,14,6
Children being exposed to,79,14,6",18
"NoEntity,Very concerned,Somewhat concerned,Not concerned
Losing the ability to communicate face-to-face,,22,0
Harassment or bullying,59.0,21,16
Mobile phone addiction,62.0,,18
Exposure to false or incorrect information,64.0,25,14
Identity theft,66.0,,16
Children being exposed to harmful content,79.0,14,,0",Yes
"53Entity,Not at all,Not too,Somewhat,Very
Work effectively with Congress 62,42,15.0,35,0
Make wise decisions immigration policy,58,45.0,29,0
Manage the executive branch effectively,56,41.0,23,0
Handle an international crisis,54,40.0,26,0
Use military force wisely,53,39.0,26,0
Make good appointments to the federal courts,51,39.0,29,0
about economic policy,49,32.0,32,0
Make good decisions about economic policy,49,32.0,32,0
with other countries,47,32.0,31,0
Negotiate favorable trade agreements with other countries,47,32.0,31,51",45
"2Entity,Not at all,Not too,Somewhat,Very
with Congress 62,42.0,15,35,0
Work effectively with Congress 62,42.0,15,35,0
about immigration policy,58.0,45,29,40
Make wise decisions about immigration policy,58.0,45,29,40
Manage the executive branch effectively,56.0,41,23,41
Handle an international crisis,54.0,40,26,44
Use military force wisely,53.0,39,26,44
Make good appointments to the federal courts,51.0,39,29,45
about economic policy,49.0,32,32,49
Make good decisions,49.0,32,32,49
with other countries,47.0,32,31,51
Negotiate favorable trade agreements,47.0,32,31,51",1
"52Entity,Confidence,No confidence,Don't know
Donald Trump,27,70,
Vadimir Putin,30,62,
Jinping Xi,34,56,15.0
Emmanuel Macron,46,34,12.0
Angela Merkel,52,31,11.0",52
"49Entity,Confidence,No confidence,Don't know
Donald Trump,27,70,
Vadimir Putin,30,62,
Xi Jinping,,,15
Emmanuel Macron,46,34,12.0
Angela Merkel,52,31,11.0",50.6
"8Entity,More strict,About right,Less strict
Non gun owner,,84,
Gun owner,,64,26.0
Among Rep/Lean Rep Gun owner,13.0,61,26
Dem/Lean Dem,80.0,15,0.0
Rep/Lean Rep,28.0,52,20
All ad lults,57.0,31,",3
"75Entity,More strict,About right,Less strict
Non gun owner,84.0,13.0,0
Gun owner,64.0,26.0,0
Among Dem/Lean Dem,80.0,15.0,0
Non-gun owner,40.0,46.0,13
Gun owner,13.0,61.0,26
Among Rep/Lean Rep,28.0,52.0,0
Dem /Lean Dem,80.0,15.0,0
Rep/Lean Rep,28.0,52.0,0
All adults,57.0,31.0,0",99
"51Entity,Oppose,Support
Germany,78,
U.S.,51,",51
"2.1Entity,Oppose,Support
Germany,17,78
U.S.,51,44",3.6
"71Entity,Voters should only be allowed to vote early or absentee with documented reason,Any voter should have the option of voting early or absentee
Dem/Lean Dem,16,83
Rep/Lean Rep,42,57
Total,28,71",71
"33Entity,Voters should only be allowed to vote early or absentee with reason documented,Any voter should have the option of voting early or absentee
Dem/Lean Dem,16,83
Rep/Lean Rep,42,57
Total,28,71",58
"42Entity,Values
New treatments are so complex that patients cannot make informed decisions,42.0
New treatments made available before fully understand their health effects we,44.0
Health care providers are too quick to order tests/procedures,46.0
Evaluation of safety/effectiveness of new medical treatments is too slow,49.0
Prescription med side effects create as many problems as they solve,59.0
People rely too much on prescription that med may not be necessary,68.0
Cost of treatments makes quality care unaffordable,83.0",42
"YesEntity,Values
New treatments made available before fully understand their health effects are,44
New treatmentsare so complex that decisions cannot make more informed patients,42",No
"5Entity,Mainly are incidents of individual misconduct,Mainly reflect widespread problems in society
Dem/Lean Dem,25,70
Rep/Lean Rep,34,61
College grad Some colle ge HS for less,19,33.060
Women,22,
Men,34,60
Total,28,66",4
"66Entity,Mainly are incidents of individual misconduct,Mainly reflect widespread problems in society
Dem/Lean Dem,25.0,70
Rep/Lean Rep,34.0,61
""College grad+ Some colle ge HS for less"",19.0,33
Women,22.0,
Men,34.0,60
Tota 28,28.0,66",60
"Young & older peopleEntity,Very strong,Strong,Not very strong,No conflicts
Young & people older,12,23,,19.0
People in cities & people in rural areas,,24,,20.0
Rich & poor,29,30,28.0,
Blacks & whites,27,38,26.0,0.0
Democrats & Republicans,64,22,82.0,0.0",Democrats & Republicans
"NoEntity,Very strong,Strong,Not very strong,No conflicts
Young & older people,12,23,,
People in cities & people in rural areas,,20.0,
Rich & poor,29,30,28.0,
Blacks & whites,27,38,26.0,
Democrats & Republicans,,22.0,",No
"0.4Entity,Very well,Fairly well,Not too well/not well at all
are safe to eat,14,28,53
Scientists agree that GM foods,14,28,53
change is due to human activity,27,35,35
safe to eat,14,28,53",10
"1.0Entity,Almost all,More than half,About half or fewer,Very well,Fairly well,Not too well/not well at all
Thes,55,28,115,0,0,100
""Scientists agree that GE foods are safe to eat"",14,28,53,0,0,100
""Change is due to human activity"" Climate scientists agree,,35,0,0,0
MMR vaccine is safe,55,28,15,0,0,100
Medical scientists agree the,55,28,15,0,0,100
""Effects of eating GM food"",19,,35,0,0,100
Scientists understand the health effects of eating GM food,19,35,0,19,0,0",0.431818182
"35Entity,Americans,Germans
Shared democratic values,35,21
Economic and trade ties,45,33
Security and defense ties,34,16",21
"YesEntity,Germans,Americans
Shared democratic values,35,21
Economic and trade ties,45,33
Security and defense ties,34,16",No
"9Entity,Not gone far enough,Been about right,Gone too far
Does not know a transgender person,31,29,37
Knows a transgender person,52,24,23
Dem/Lean Dem,,27,
Rep/Lean Rep,12,28,57
All ad lults,39,27,32",39
"NoEntity,Not gone far enough,Been about right,Gone too far
Does not know a transgender person,31.0,29,37
Knows a transgender person,52.0,24,23
Dem/Lean Dem,60.0,,
Rep/Lean Rep,,28,57
All ad lults,,39,32",Yes
"27Entity,A great deal,a fair amount,Total
India,23,37,60
Mexico,30,33,63
Kenya,30,38,68
Indonesia,27,48,75",27
"0.806Entity,A great deal,a fair amount,Total
India,23,37,60
Mexico,30,33,63
Kenya,30,38,68
Indonesia,27,48,75",1.111111111
"[Should not, Should]Entity,Should not,Should
Re publican,27,65
Independent,33,62
Democrat,39,52
Total,34,58","[Should not, Should]"
"0.527777778Entity,Should not,Should
Re publican,27,65
ndep end lent,33,62
Democrat,39,52
Total,34,58",0.75
"46Entity,Strongly agree,Agree
Math is one of my favorite subjects,21,26
""Because math is fun, I wouldn't want to give it up"",13,43
I like math,18,46",46
"63Entity,Strongly agree,Agree
subjects,21,26
Math is one of my favorite,21,26
because math is fun,13,43
I like math,18,46",72
"67Entity,Taking technology too far,Appropriate use
Equal to their own peak abilities,50,47
Much better than their own peak abilities,5,39
Far above that of any human known to date,67,30",47
"YesEntity,Taking technology too far,Appropriate use
Equal to theirpeak own abilities,50,
""much better than their own peak abilities"",57,39
""Far above that of any human known to date"",67,30",Yes
"26Entity,Much more liberal,Same,Somewhat more conser,Much more conser
Democrat,,26,33,20
Republican,,21,28,25",Same
"0.05Entity,Much more liberal. Somewhat more liberal,Same,Somewhat more conser,Much more conser.
Democrat,26,33,2010.0,10
Republican,21,28,2519,19",16
"62Entity,Reliance on principles,Ability to change
Silent,46,43
Boo mer,49,45
Generation X,,51
Millennial,35,62
Total,43,51",62
"9Entity,Reliance on principles,Ability to change
Silent,46,43
Boomer,49,45
Generation X,,51
Millennial,35,62
Total,43,51",7
"65+Entity,Not subject to additional scrutiny solely because of religion,Be subject to more scrutiny than people in other religious groups
Unaffiliated,72,24
Catholic,55,38
Black Prot,71,20
White mainline Prot,56,36
White evang Prot,43,50
Democrat,76,20
Indep end lent,62,31
Repu blican,44,,49
HS for less,58,34,0
Some coll,59,33,0
College grad,65,28,28
Postgrad,69,28,0
65+,50,41,0
50-64,50,40,0
30-49,63,30,0
18-29,80,,0
Hispa nic,66,25,0
Black,74,17,36
White,57,36,0
Total,61,32,0",65+
"15Entity,Not subject to additional scrutiny solely religion because of,subject to more scrutiny than people in other religious groups
Unaffiliated,72,24
Catholic,55,38
Black Prot,71,20
White mainline Prot,56,36
White evang Prot,43,50
Democrat,76,20
Independent,62,31
Republican,44,49
HS or less,58,34
Some coll,59,33
College grad,65,28
Postgrad,69,28",6
"0.37Entity,Bad,Good
Media,51,38
Courtsystem,48,41
Religious leaders,,41
National gov't,48,45
Police,44,46
Military,37,52",37
"40Entity,Bad,Good
Media,51,38
Courtsystem,48,41
Religious leaders,,41
National gov't,48,45
Police,44,46
Military,37,52",39.5
"47Country,Adequacy of minimum income benefits
Slovak Republic,19.0
France,39.0
Netherlands,47.0",47
"38.33Country,Adequacy of minimum income benefits
Slovak Republic,19.0
France,39.0
Netherlands,47.0",35
"213Country,Agricultural land
Luxembourg,0
Korea,2
Spain,25
Canada,62
Kazakhstan,213",213
"188Country,Agricultural land
Luxembourg,0
Korea,2
Spain,25
Canada,62
Kazakhstan,213",151
"BulgariaCountry,Benefits in unemployment,share of previous income
Bulgaria,15.0,-
Israel,25.0,-
Ireland,39.0,-
Malta,48.0,-
Luxembourg,57.0,-",Bulgaria
"IrelandCountry,Benefits in unemployment,share of previous income
Bulgaia,15.0
Israel,25.0
Ireland,39.0
Malta,48.0
Luxembourg,57.0",Ireland
"MontenegroCountry,Built-up area
Yemen,6
El Salvador,62
Montenegro,190",Montenegro
"13.5Country,Built-up area
Yemen,6
El Salvador,62
Montenegro,190",98
"5Country,Financial disincentive to return to work
Australia,41.9
Denmark,73.7
Norway,75.2
Slovenia,78.2
Luxembourg,89.2",5
"2Country,Financial disincentive to return to work
Australia,41.9
Denmark,73.7
Norway,75.2
Slovenia,78.2
Luxembourg,89.2",1
"PortugalCountry,Foreign-born participation rates
Canada,75.6
Portugal,82.7",Portugal
"7.1Country,Foreign-born participation rates
Canada,75.6
Portugal,82.7",7.1
"2Country,Freight transport
Portugal,0.0M
Finland,0.01M
Hungary,0.01M
India,0.26M
Russia,1.97M",2
"YesCountry,Freight transport
Portugal,0.00M
Finland,0.01M
Hungary,0.01M
India,0.26M
Russia,1.97M",Yes
"BlueCountry,Gross pension wealth
Australia,5.6
Estonia,6.7
Croatia,6.9
Luxembourg,18.7",Blue
"YesCountry,Gross pension wealth
Australia,5.6
Estonia,6.7
Croatia,6.9
Luxembourg,18.7",Yes
"JapanCountry,Housing prices
Russia,95.6
Japan,96.1",Japan
"1.5Country,Housing prices
Russia,95.6
Japan,96.1",0.5
"Light BlueCountry,Infant mortality rates
New Zealand,16.6
Estonia,17.5",Blue
"16.98Country,Infant mortality rates
New Zealand,16.6
Estonia,17.5",17.05
"4.2Country,National area distribution
Slovak Republic,4.2
Lithuania,15.0",4.2
"7.6Country,National area distribution
Slovak Republic,4.2
Lithuania,15.0",9.6
"98Country,Nuclear power plants
Germany,-
United Kingdom,-
Canada,-
Russia,35.0
Japan,0.0
France,-
United States,98.0",98
"YesCountry,Nuclear power plants
Germany,11.0
United Kingdom,4.0
Canada,20.0
Russia,35.0
Japan,43.0
France,20.0
United States,98.0",Yes
"United KingdomCountry,Poverty rate
Slovenia,0.085
United Kingdom,0.119",United Kingdom
"0.0025Country,Poverty rate
Slovenia,0.085
United Kingdom,0.119",0.034
"RedCountry,School principals
Singapore,48.3
Italy,57.0",Red
"95.3Country,School principals
Singapore,48.3
Italy,57.0",105.3
"YesCountry,Tax on goods and services
Korea,8.1
Chile,12.1
Estonia,13.0
Finland,14.2
Denmark,15.6",Yes
"YesCountry,Tax on goods and services
Korea,8.1
Chile,12.1
Estonia,13.0
Finland,14.2
Denmark,15.6",Yes
"NetherlandsCountry,Tax revenue
United Kingdom,36.7
Netherlands,39.6",Netherlands
"YesCountry,Tax revenue
United Kingdom,36.7
Netherlands,39.6",No
"5Country,Trade in goods and services forecast
Switzerland,4.8
Austria,5.5
Italy,8.8
Latvia,16.8
Iceland,21.9",5
"YesCountry,Trade in goods and services forecast
Switzerland,4.8
Austria,5.5
Italy,8.8
Latvia,16.8
Iceland,21.9",Yes
"2Country,""Violence against women""
Jamaica,4.9
Zimbabwe,38.7",2
"33.8Country,Violence against women
Jamaica,4.9
Zimbabwe,38.7",33.8
"CubaCountry,Women in politics
Angola,25.0
Azerbaijan,25.0
Ecuador,25.0
Thailand,25.0
Cuba,50.0",Cuba
"25Country,Women in politics
Angola,25.0
Azerbaijan,25.0
Ecuador,25.0
Thailand,25.0
Cuba,50.0",25
"89Entity,Values
Placed a call,33.0
Used an app,29.0
Searched or browsed the web,25.0
alert,0.34
Checkto see if've received any,0.34
Received an incoming caII,52.0
Sent a message such as a text or email,52.0
Took a photo or video,58.0
Read a message such as text or email,61.0
Did at least one of these activities below,89.0",89
"64Entity,Values
Searched or browsed the web,25.0
Used an app,29.0
Placed a ca Il,33.0
alerts,34.0
Checked to see if you've received any,
Received an incoming ca Il,52.0
Sent a message such as a text or email,52.0
Took a photo or video,58.0
Read a message such a text or email,0.0
Did at least one of these activities below,89.0",64
"36Entity,Values
The O'Reilly Factor,54
The Rachel Maddow Show,53
NBC Nightly News,52
Anderson Cooper 360,
The Colbert Report,33
The Daily Show,36",36
"3Entity,Values
The O'Reilly Factor,54
The Rachel Madden Show,53
NBC Nightly News,52
Anderson Cooper 360,47
The Colbert Report,33
The Daily Show,36",4
"Right decisionEntity,Wrong decision,right decision
Democrat,,74.0
Indep end lent,,53.0
Re publican,,
Hispa nic,28.0,52.0
Black,,
White,38.0,56.0
Total,34.0,57.0",Right decision
"67Entity,Wrong decision,Right decision
Democrat,19,74
Indep end lent,37,53
Re publican,49,43
Hispa nic,28,52
Black,12,76
White,38,56
Total,34,57",64
"42Entity,Disapprove,Approve
Independ lent,57,39
Democrat,48,
Republican,56,
TOTAL,54,42",42
"DemocratEntity,Disapprove,Approve
Indep end lent,57,39
Democrat,48,
Republican,56,41
TOTAL,54,42",Independent
"7Entity,Very secure,Somewhat secure,Not very secure,Not at all secure
Using social media sites,14,28,53,-
Using chat or IM,25,36,32,-
Sending email,35,36,21,-
Sending text messages,,37,22,-
Callin on your cell phone,43,29,17,-
Using landline,16,51,19,12",6
"YesEntity,Very secure,Somewhat secure,Not very secure,Not at all secure
Using social media sites,14.0,28,53,0
Using chat or IM,4.0,25,36,32
Sending email,5.0,35,36,21
Sending text messages,7.0,32,37,22
Calling on your phone,9.0,43,29,17
Using a landline,16.0,51,19,12",Yes
"IndonesiaCountry,""Share of marine territorial waters that are protected, 2016""
Greenland,4.52
Mauritania,4.15
Indonesia,2.88
Ireland,2.33",Indonesia
"0.39Country,""Share of marine territorial waters that are protected, 2016""
Greenland,4.52
Mauritania,4.15
Indonesia,2.88
Ireland,2.33",1.06
"GreenCountry,""Energy intensity of transport per passenger-kilometer, 1960""
International flight,1.68
Domestic flight,1.57",Pink
"1.01Country,""Energy intensity of transport per passenger-kilometer, 1960""
International flight,1.68
Domestic flight,1.57",0.11
"46Entity,More likely,Less Likely,Wouldn't matter
Independents,16,36,46
Democrats,26,20,53
Re publicans,15,36,46
Total,19,30,48",53
"21Entity,More likely,Less Likely,Would n 't matter
Independents,16,36,46
Democrats,26,20,53
Re pu blicans,15,36,46
Total,19,30,48",21
"YesCountry,""Sulphur oxide (SO2) emissions, 1990""
Czechia,100
Luxembourg,100
Poland,100
Turkey,100
United Kingdom,100",Yes
"United KingdomCountry,""Sulphur oxide (SO2) emissions, 1990""
Czechia,100
Luxembourg,100
Poland,100
Turkey,100
United Kingdom,100",Poland
"Sri LankaCountry,""Share of women with raised blood pressure, 1996""
Malawi,25.99
Grenada,22.81
Sri Lanka,19.36",Sri Lanka
"23.69Country,""Share of women with raised blood pressure, 1996""
Malawi,25.99
Grenada,22.81
Sri Lanka,19.36",22.675
"East Asia and PacificCountry,""Global mismanaged plastic by region, 2010""
East Asia and Pacific,60.0
South Asia,11.0
Sub-Saharan Africa,8.9
Middle East and North Africa,8.3
Latin America and Caribbean,7.2
Europe and Central Asia,3.6
North America,0.9",East Asia and Pacific
"11.83Country,""Global mismanaged plastic by region, 2010""
East Asia and Pacific,60.0
South Asia,11.0
Sub-Saharan Africa,8.9
Middle East and North Africa,8.3
Latin America and Caribbean,7.2
Europe and Central Asia,3.6
North America,0.9",9.1
"SpainCountry,""Mean body mass index (BMI) in men, 1986""
Venezuela,25.11
Austria,24.89
Montenegro,24.4
Spain,20.49",Benin
"0.946208Country,""Mean body mass index (BMI) in men, 1986""
Venezuela,25.11
Austria,24.89
Montenegro,24.4
Slovenia,20.49",0.99124
"43Country,""Share of people who say university is more important for boys""
Malaysia,43
Philippines,38.92
Ghana,27.58
Switzerland,8.82",43
"35.2Country,""Share of people who say university is more important for boys""
Malaysia,43.0
Philippines,38.92
Ghana,27.58
Switzerland,8.82",33.25
"SpainCountry,""Coverage by protected areas of important sites for mountain biodiversity,2000""
Togo,100.0
Europe,50.03
Spain,49.89
Eswatini,29.98
Colombia,25.82",Spain
"NoCountry,""Coverage by protected areas of important sites for mountain biodiversity,2000""
Togo,100.0
Europe,50.03
Spain,49.89
Eswatini,29.98
Colombia,25.82",Yes
"6Country,1996,1998,2000,2002,2004,2006,2008,2010,2012,2014,2016,2018
Chile,0.589203141,0.635439337,0.569170906,0.732291172,0.650499032,0.442001712,0.397630411,0.360572394,0.280956053,0.328165772,0.433983682,0.260309209
Australia,1.860347961,1.719211503,1.667451936,1.9132031",5
"2008Country,1996,1998,2000,2002,2004,2006,2008,2010,2012,2014,2016,2018
Australia,1.858667,1.734316,1.712047,1.983917,2.012895,1.282604,1.835132,1.568814,1.586123,3.31489,2.138441,2.713451
Israel,1.439914,1.983102,1.775364,0.586635,1.52774,1.130403,2.909895,3.011881,3.225028",2018
"AustraliaCountry,1975,1980,1985,1990,1995,2000,2005
Australia,40,39,32,37,38,40,44
Italy,35,34,33,32,33,33,32
Chile,46,40,42,40,35,32,36
South Africa,14,16,16,13,11,11,17",Australia
"[Australia, Chile]Country,1975,1980,1985,1990,1995,2000,2005
Australia,40.0,4.0,36.0,3.0,38.0,42.0,42.0
Italy,-,50.0,32.0,50.0,35.0,32.0,35.0
Chile,-,35.0,38.0,28.0,35.0,28.0,25.0
South Africa,48.0,,36.0,37.0,15.0,14.0,15.0","[Australia, Italy]"
"[Slovenia, Turkey]Country,2004,2005,2006,2007,2008,2009,2010,2011,2012
Slovenia,68.2,,67.4,,67.2,,66.8,,66.7
Turkey,47,,,,,,46.8,,48.7","[Slovenia, Turkey]"
"2008Country,2004,2005,2006,2007,2008,2009,2010,2011,2012
Slovenia,67.7921432,67.63244294,66.99451594,68.55106747,68.63890845,67.15529038,67.67781666,66.83649584,65.88140432
Turkey,47.28103695,44.21605394,45.50415183,46.17864949,46.49924853,44.16406959,47.31275462,48.67414",2008
"United StatesYear,Nutrient balance
1990,33.5
1995,35.3
2000,34.0
2005,33.6
2010,35.0
2015,32.0",United States
"2Country,1986,1990,1995,2000,2005,2010,2015
Sweden,67.2,53.8,66.0,56.2,47.3,40.9,58.2
United States,32.0,34.2,35.8,35.7,34.3,33.8,33.8",1
"1985Country,1965,1970,1975,1980,1985,1990,1995,2000
Japan,102.5,103.7,104.8,106.3,109.0,111.9,112.8,114.5
Portugal,15.5,16.0,16.4,16.6,16.7,16.8,16.7,17.2
Czech Republic,6.5,7.0,7.2,7.4,7.4,7.7,7.7,7.6
Slovak Republic,10.0,10.0,10.0,10.0,10.0,10.0,10.0,10.0",2010
"5Country,1965,1970,1975,1980,1985,1990,1995,2000,2005
Japan,100.99773,104.86225,109.8053,114.74383,119.79271,124.88069,129.91556,134.92363,139.90184
Portugal,17.621699,18.417931,19.23181,20.037649,20.835654,21.692134,22.529424,23.389657,24.23294
Czech Republic,10.714489,11.045091,11.4",3
"[Austria, Chile]Country,2013,2014,2015,2016,2017,2018
Austria,107.3883441917848,,,100.3110078362342,102.8342692351563,103.4369857829125,101.2762874765201
Chile,,,,70.6530091645438,72.2241565260145,77.0673555208962","[Austria, Chile]"
"3Country,2013,2014,2015,2016,2017,2018
Austria,107.7080922896783,108.5092733187016,100.5941472538697,100.1604234545004,100.4319301764336,101.3320702884120
Chile,72.6884975494815,68.6550908987344,68.64340841388,67.6314684477647,70.3325966944719,72.6568912868633",2
"[Lithuania, Saudi Arabia]Country,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020
Lithuania,18.504,18.531,18.569,18.589,18.604,18.634,18.66,18.683,18.708,18.733,18.763","[Lithuania, Saudi Arabia]"
"LithuaniaCountry,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020
Saudi Arabia,5.019418889,5.019418889,5.019418889,5.019418889,5.019418889,5.019418889,5.019418889,5.019418889,5.019418889,5.019418889,5.019418889
Lithuania,18.847419375,18.847419375,18.847419375,18.847419375,18.8474",Saudi Arabia
"BelgiumCountry,1988,1990,1992,1994,1996,1998,2000,2002
Belgium,4.0,,3.5,,3.6,,2.7
New Zealand,1.9,,2.7,,2.0,,1.3",Belgium
"New ZealandCountry,1988,1990,1992,1994,1996,1998,2000,2002
Belgium,3.95,3.42,3.53,3.73,3.63,3.2,2.86,3.05
New Zealand,1.85,2.75,2.79,2.2,1.73,2.0,1.64,1.3",New Zealand
"KoreaCountry,1992,1994,1996,1998,2000,2002,2004,2006,2008,2010,2012,2014
Korea,0.484,0.468,0.087,0.194,0.196,0.075,0.178,0.244,0.243,0.296,0.237,0.23
Turkey,0.533,0.491,0.858,0.657,0.04,0.059,0.082,0.054,0.115,0.129,0.115,0.109",Korea
"1Entity,1992,1994,1996,1998,2000,2002,2004,2006,2008,2010,2012,2014
Korea,0.4961977,0.4720324,0.0898329,0.1677836,0.2269454,0.0781246,0.3380554,0.2293276,0.2779032,0.3446652,0.3314789,0.2957919
Turkey,0.6783193,0.4931899,0.9149927,0.5530923,0.0672364,0.0563278,0.0881123",1
"EthiopiaCountry,1992,1994,1996,1998,2000,2002,2004,2006
Ethiopia,86.922187,83.176959,86.218789,94.291509,90.041036,89.664673,70.002144,93.122819
Congo,64.040641,75.831299,78.836188,82.823853,73.142676,67.956739,66.299291,66.763512
Egypt,8.423889,9.361842,8.695761,8.661278,7.871717",Ethiopia
"2Country,1992,1994,1996,1998,2000,2002,2004,2006
Egypt,7.48,7.41,7.66,7.56,7.85,7.59,7.49,7.84
Canada,18.76,18.92,18.86,18.91,19.1,18.33,19.2,19.7
Congo,60.66,71.7,76.0,81.2,65.3,67.2,66.6,66.4
Ethiopia,88.4,88.0,88.9,89.5,89.4,92.8,88.6,89.4",2
"1998Country,1984,1986,1988,1990,1992,1994,1996,1998,2000,2002,2004,2006
Belgium,3.6,,8.7,,10.5,11.2,9.5,,10.9,9.9,10.0,10.1
Mexico,7.1,,4.6,,2.8,2.7,,4.7,,3.9,7.9,8.6",1994
"1991Country,1984,1986,1988,1990,1992,1994,1996,1998,2000,2002,2004,2006
Belgium,3.3,5.5,8.1,10.4,10.9,11.6,9.4,10.7,10.9,10.4,6.9,9.9
Mexico,3.6,3.4,4.5,5.3,4.6,2.6,3.3,4.3,4.4,3.5,7.3,8.8",1987
"ChinaTaiwanCountry,1988,1990,1992,1994,1996,1998,2000,2002
Finland,-,1129.0,1895.0,3418.0,4730.0,4947.0,4302.0,3701.0
India,-,-,-,-,-,-,-,-
Chinese Taiwan,-,-,-,-,-,-,-,-
Turkey,-,-,-,-,-,-,-,-",Chinese Taipei
"1Country,1988,1990,1992,1994,1996,1998,2000,2012
Finland,120.5,,144.9,,460.7,,382
India,,10,,2,,12.8,,59
Chinese Taipei,5.8,,3.8,,5,,60.4,,127
Turkey,,,,,,1.8,,186
Iceland,,,,,,,,,",3
"2011Country,2010,2011,2012,2013,2014,2015,2016
Brazil,74.2747592880244,74.2289194835669,73.7218556786168,72.2569587892776,71.4629073251376,71.1242192780594,70.326850700988
Switzerland,58.4957754761914,58.1374622328442,58.0125489125796,59.2844419065553,60.6074331655971,61.33281",2016
"SwitzerlandCountry,2010,2011,2012,2013,2014,2015,2016
Brazil,74.3,74.4,73.7,71.9,71.6,71.7,70.8
Switzerland,58.3,57.8,58.1,59.3,59.6,60.4,60.9",Brazil
"Weixin/ WeChatCharacteristic,Monthly active users in millions
WhatsApp*,2000
Facebook Messenger*,1300
Weixin / WeChat,1225
QQ,595
Telegram,550
Snapchat*,528",Facebook Messenger*
"3225Characteristic,Monthly active users in millions
WhatsApp*,2000
Facebook Messenger*,1300
Weixin / WeChat,1225
QQ,595
Telegram,550
Snapchat*,528",3300
"Bridgestone (Japan)Characteristic,Revenue in billion U.S. dollars
Bridgestone (Japan),27.23
Michelin (France),26.55
Goodyear (U.S.),14.75
Continental (Germany),12.9",Bridgestone (Japan)
"14.52Characteristic,Revenue in billion U.S. dollars
Bridgestone (Japan),27.23
Michelin (France),26.55
Goodyear (U.S.),14.75
Continental (Germany),12.9",14.33
"American AirlinesCharacteristic,Share of domestic passengers
American Airlines,19.3%
Southwest Airlines,17.4%
Delta Air Lines,15.5%
United Airlines,12.4%
Spirit,5.8%
Alaska Airlines,5.3%
JetBlue Airways,4.7%
""Border Express"",3.6%
SkyWest,3.5%
""Sendway Air"",1.3%
Other,11.2%",American Airlines
"12.4Characteristic,Market share
American Airlines,19.3%
Southwest Airlines,17.4%
Delta Air Lines,15.5%
United Airlines,12.4%
Spirit,5.8%
Alaska Airlines,5.3%
JetBlue Airways,4.7%
""Frontier, 3.6%""
SkyWest,3.5%
""Envoy Air 1.3%""
Other,11.2%",12.4
"1000.97Characteristic,Cattle population in million head
2021*,1000.97
2020,987.75
2019,989.03
2018,996.36
2017,984.53
2016,978.77
2015,969.26
2014,1008.57
2013,1005.29
2012,1001.72",969.26
"49.68Characteristic,Cattle population in million head
2021*,1000.97
2020,987.75
2019,989.03
2018,996.36
2017,984.53
2016,978.77
2015,969.26
2014,1008.57
2013,1005.29
2012,1001.72",39.31
"[1.34, 1.37]Characteristic,Female to male ratio
2017,1.18
2016,1.2
2015,1.34
2014,1.39
2013,1.4
2012,1.37
2011,1.34
2010,1.37
2009,1.32
2008,1.33","[1.34, 1.37]"
"2.61Characteristic,Female to male ratio
2017,1.18
2016,1.2
2015,1.34
2014,1.39
2013,1.4
2012,1.37
2011,1.34
2010,1.37
2009,1.32
2008,1.33",5.11
"IncreasedCharacteristic,Share of respondents
Decreased,30%
No impact,35%
Increased,35%",Increased
"32.25Characteristic,Share of respondents
Decreased,30%
No impact,35%
Increased,35%",32.5
"4.3Characteristic,Growth rate of HICP
Dec '18,3%
Nov '18,3.2%
Oct '18,4.2%
Sep '18,4.7%
Aug '18,4.7%
Jul '18,4.3%
Jun '18,4.7%
May '18,4.6%
Apr '18,4.3%
Mar '18,4%
Feb '18,3.8%
Jan '18,3.4%",4.3
"0.07Characteristic,Growth rate of HICP
Dec '18,3%
Nov '18,3.2%
Oct '18,4.2%
Sep '18,4.7%
Aug '18,4.7%
Jul '18,4.3%
Jun '18,4.7%
May '18,4.6%
Apr '18,4.3%
Mar '18,4%
Feb '18,3.8%
Jan '18,3.4%",1
"2015Characteristic,Inflation rate
2020,0.5%
2019,1.1%
2018,1.8%
2017,1%
2016,0.2%
2015,0%
2014,0.5%
2013,0.9%
2012,2%
2011,2.1%
2010,1.5%
2009,0.1%
2008,0.1%
2007,2.8%
2006,1.6%
2005,1.8%
2004,2.1%",2015
"2.6Characteristic,Inflation rate
2020,0.5%
2019,1.1%
2018,1.8%
2017,1%
2016,0.2%
2015,0%
2014,0.5%
2013,2%
2012,2.1%
2011,1.5%
2010,2.1%
2009,1.5%
2008,0.1%
2007,2.8%
2006,1.6%
2005,1.8%
2004,2.1%",-1.6
"2015Characteristic,ACSI score
2020,72
2019,70
2018,70
2017,71
2016,70
2015,68
2014,72
2013,72
2012,70
2011,73
2010,70
2009,70
2008,70",2015
"3Characteristic,ACSI score
2020,72
2019,70
2018,70
2017,71
2016,70
2015,68
2014,72
2013,72
2012,70
2011,73
2010,70
2009,70
2008,70",7
"11Characteristic,Market size
Upright vacuums,51%
Canister vacuums,28%
Robot vacuum cleaners,11%
""Other (hand-held, tank-mounted, etc.)"",10%",10
"1.3263Upright vacuums,Canister vacuumsCharacteristic,Market share
Upright vacuums,51%
Canister vacuums,28%
Robot vacuum cleaners,11%
Other (hand-held, tank-mounted, etc.),10%",0.549
"SeptemberCharacteristic,Price in U.S. dollars per ton
October,1390
September,1300
August,1260
July,1240
June,1220
May,1270
April,1290
March,1210
February,1220
January,1210",October
"2Characteristic,Price in U.S. dollars per ton
October,1390
September,1300
August,1260
July,1240
June,1220
May,1270
April,1290
March,1210
February,1220
January,1210",3
"20Characteristic,Share of respondents
Only in Poland,66%
Only abroad,20%
In Poland and abroad,7%
Hard to say,7%",20
"66Characteristic,Share of respondents
Only in Poland,66%
Only abroad,20%
In Poland and abroad,7%
Hard to say,7%",73
"537689Characteristic,Number of students
2019/20*,509473
2018/19,519462
2017/18,522059
2016/17,537689",537689
"2Characteristic,Number of students
2019/20*,509473
2018/19,519462
2017/18,522059
2016/17,537689",2
"2015Characteristic,Consumption in million U.S. dollars*
2019,604.4
2018,575.4
2017,514.0
2016,486.9
2015,476.9
2014,482.5
2013,453.6
2012,402.3
2011,349.2
2010,378.2",2014
"40.2Characteristic,Consumption in million U.S. dollars*
2019,604.4
2018,575.4
2017,514.0
2016,486.9
2015,476.9
2014,482.5
2013,453.6
2012,402.3
2011,349.2
2010,378.2",59.8
"Not collected for recyclingCharacteristic,Share of e-waste
""Not collected for recycling"",80%
""Not documented, fate unknown*"",76%
Thrown into household waste,4%
""Documented, collected, and recycled"",20%","Not documented, fate unknown*"
"4Characteristic,Share of e-waste
Not collected for recycling,80%
""Not documented, fate unknown,  "",76%
Thrown into household waste,4%
""Documented, collected, and recycled,  "",20%",0.25
"4Characteristic,Share of respondents
Free Wi-Fi,49%
Free breakfast,14%
Proximity to mass transit, transportation and shops,11%
Comfortable work chair and desk,6%",4
"65Characteristic,Share of respondents
Free WI-Fi,49%
Free breakfast,14%
Proximity to mass transit, transportation and shops,11%
Comfortable work chair and desk,6%",31
"3996Characteristic,Number of pupils
Gaelic learner classes,3996
Gaelic medium education,3168",3996
"138Characteristic,Number of pupils
Gaelic medium education,3168
Gaelic learner classes,3996",828
"84Characteristic,Ease of doing business score
2020,84
2019,84
2018,84.14
2017,83.92
2016,84.07
2015,83.88
2014,83.4
2013,83.7",84
"2018Characteristic,Ease of doing business score
2020,84
2019,84
2018,84.14
2017,83.92
2016,84.07
2015,83.88
2014,83.4
2013,83.7",2015
"49976Characteristic,Construction cost in Russian rubles per square meter
Monolith,55937
Monolith brick,55157
Panel,49976
Block,48158
Brick,37392",49976
"YesCharacteristic,Construction cost in Russian rubles per square meter
Monolith,55937
Monolith brick,55157
Panel,49976
Block,48158
Brick,37392",Yes
"increasingCharacteristic,GERD as percentage of GDP
2017*,1.13%
2016,0.99%
2015,0.96%
2014,0.83%
2013,0.81%
2012,0.7%
2011,0.67%
2010 *,0.6%
2009 *,0.63%
2008 *,0.66%
2007 *,0.58%
2006,0.56%
2005,0.58%
2004,0.53%
2003,0.55%",increasing
"2Characteristic,GERD as percentage of GDP
2017*,1.13%
2016,0.99%
2015,0.96%
2014,0.83%
2013,0.81%
2012,0.7%
2011,0.67%
2010 *,0.6%
2009 *,0.63%
2008*,0.66%
2007*,0.58%
2006,0.56%
2005,0.58%
2004,0.53%
2003,0.55%",5
"Pulmonary arterial hypertensionCharacteristic,Number of patients per million population
Pulmonary arterial hypertension,46
Pulmonary veno occlusive disease and/or pulmonary capillary haemosidemiaosis,1
Pulmonary hypertension due to left heart disease,3
Pulmonary hypertension due to lung disease and/or hypoxia,4
Chronic thromboembolic pulmonary hypertension,21
Pulmonary hypertension with unclear/multifactorial mechanisms,2
Not pulmonary hypertension,11
No final diagnosis possible,1
No diagnosis,12",Pulmonary arterial hypertension
"4Characteristic,Number of patients per million population
Pulmonary arterial hypertension,46
""Pulmonary veno occlusive disease and/or pulmonary capillary haemosidema"",1
""Pulmonary hypertension due to left heart disease"",3
""Pulmonary hypertension due to lung disease and/or hypoxia"",4
Chronic thromboembolic pulmonary hypertension,21
""Pulmonary hypertension with unclear/multifactorial mechanisms"",2
Not pulmonary hypertension,11
No final diagnosis possible,1
No diagnosis,12",4
"Passenger carsCharacteristic,Market share
Passenger cars,71.7%
Air,9.6%
Bus & Coach,8%
Railway,6.9%
Powered two-wheelers,1.8%
Tram & Metro,1.5%
Sea,0.4%",Passenger cars
"12.6Characteristic,Market share
Passenger cars,71.7%
Air,9.6%
Bus & Coach,8%
Railway,6.9%
Powered two-wheelers,1.8%
Tram & Metro,1.5%
Sea,0.4%",3.7
"Russian FederationCharacteristic,Share of reserves
Russian Federation,20%
Brazil,12%
Canada,9%
United States,8%
China,5%
Democratic Republic of Congo,3%
Australia,3%
Indonesia,2%
Peru,2%
India,2%
Other,34%",Russian Federation
"[22,71,88]Characteristic,Share of reserves
Russian Federation,20%
Brazil,12%
Canada,9%
United States,8%
China,5%
Democratic Republic of the Congo,3%
Australia,3%
Indonesia,2%
Peru,2%
India,2%
Other,34%",41
"2009Characteristic,Percentage of GDP
2019**,3.5%
2018*,3.7%
2017,3.5%
2016,3.5%
2015,3.6%
2014,3.6%
2013,3.4%
2012,3.8%
2011,3.8%
2010,4.1%
2009,5.3%
2008,4.9%
2007,4.8%
2006,4.3%
2005,4.2%",2009
"2Characteristic,Percentage of GDP
2019**,3.5%
2018*,3.7%
2017,3.5%
2016,3.5%
2015,3.6%
2014,3.6%
2013,3.4%
2012,3.8%
2011,3.8%
2010,4.1%
2009,5.3%
2008,4.8%
2007,4.3%
2006,4.2%
2005,4.2%",6
"6.6Characteristic,Risk index score
2020,5.99
2019,6.24
2018,6.48
2017,6.6
2016,4.16
2015,4.16",6.6
"NoCharacteristic,Risk index score
2020,5.99
2019,6.24
2018,6.48
2017,6.6
2016,4.16
2015,4.16",Yes
"123.3Characteristic,Wholesale Price Index
FY 2020,125.3
FY 2019,123.3
FY 2018,118.7
FY 2017,109.0
FY 2016,106.5
FY 2015,106.7
FY 2014,104.8
FY 2013,102.1",123.3
"2Characteristic,Wholesale Price Index
FY 2020,125.3
FY 2019,123.3
FY 2018,118.7
FY 2017,109.0
FY 2016,106.5
FY 2015,106.7
FY 2014,104.8
FY 2013,102.1",2
"3Characteristic,Share of internet users
2019,72.1%
2018,69.9%
2017,67.4%
2016,66.8%
2015,64.3%
2014,62%
2013,60.6%
2012,55.7%
2011,50.7%
2010,47.7%
2009,41.5%
2008,38.5%
2007,39.8%
2006,37.2%
2005,25.1%
2004,27.8%
2003,23.2%
2002,19.4%
2001,15.8%
2000,12.7%",3
"61.8Characteristic,Share of internet users
2019,72.1%
2018,71.1%
2017,67.4%
2016,65.2%
2015,64.3%
2014,62%
2013,60.6%
2012,55.7%
2011,50.7%
2010,48.4%
2009,41.5%
2008,40%
2007,39.8%
2006,38.9%
2005,25.1%
2004,27.8%
2003,23.2%
2002,19.4%
2001,15.8%
2000,12.7%",70.4
"CanadaCharacteristic,Share of responses
West U.S.,69%
South U.S.,68%
Canada,68%
Northeast U.S.,65%
Midwest U.S.,65%",Canada
"1Characteristic,Revenue share
West U.S.,69%
South U.S.,68%
Canada,68%
Northeast U.S.,65%
Midwest U.S.,65%",3
"1Characteristic,Share of respondents
Yes,24%
No,76%
I was the victim*,1%",1
"52Characteristic,Share of respondents
Yes,24%
No,76%
I was the victim*,1%",52
"3Characteristic,Market value share
""Alibaba, Amazon, and eBay"",16%
Wildberries,5%
Mvideo,5%
DNS Group,3%
Citilink,3%
Ozon,3%
Lamoda,3%",3
"12Characteristic,Market value share
""Ali Baba, Amazon, and eBay"",16%
Wildberries,5%
Mvideo,5%
DNS Group,3%
Citilink,3%
OzOn,3%
Lamoda,3%",13
"2019Characteristic,Percentage change y-o-y
2019,-6.8%
2018,2.4%
2017,8.5%
2016,15.6%
2015,27.6%
2014,5.3%
2013,12.1%
2012,16.9%
2011,8.8%
2010,21.4%",2019
"4Characteristic,Percentage change y-o-y
2019,-6.8%
2018,2.4%
2017,8.5%
2016,15.6%
2015,27.6%
2014,5.3%
2013,12.1%
2012,16.9%
2011,8.8%
2010,21.4%",5
"Don't knowCharacteristic,Share of parents
Based on how much we can afford as a family,47%
Based on my child's age,29%
Based on my child's needs,25%
Based on what I know my child's friends receive,7%
If my child asks for more, I try to give them more,5%
Other,4%
Don't know,3%",Based on how much we can afford as a family
"12Characteristic,Share of parents
Based on how much we can afford as a family,47%
Based on my child's age,29%
Based on my child's needs,25%
Based on what I know my child's friends receive,7%
""If my child asks for more, I try to give them more"",5%
Other,4%
Don't know,3%",19
"2021Characteristic,Share of respondents
""I expect consumers to purchase a few, luxury items"",11.9%
""I expect consumers to buy more frivolous fun gifts this Christmas compared with recent years."",36.8%
""I expect practical presents to remain the most popular choice this Christmas."",51.3%",2014
"25.84Characteristic,Share of respondents
I expect consumers to purchase a few, luxury items,11.9%
I expect consumers to buy more frivolous fun gifts this Christmas compared with recent years.,36.8%
I expect practical presents to remain the most popular choice this Christmas.,51.3%",33.33
"CIC Lyonnaise de BanqueCharacteristic,Customer loans in million euros
CIC Lyonnaise de Banque,31846
CIC Est,24126
CIC Quest,20393
CIC Nord Ouest,21546
CIC Sud Ouest,15077",CIC Lyonnaise de Banque
"42686Characteristic,Customer loans in million euros
CIC Lyonnaise de Banque,31846
CIC Est,24126
CIC Quest,20393
CIC Nord Ouest,21546
CIC Sud Ouest,15077",44519
"PeriscopeCharacteristic,Share of respondents
WhatsApp,67%
Facebook,21%
Instagram,16%
Google,8%
eBay Kleinanzeigen,5%
Periscope,0%
Xing,0.6%
Other,1.2%
Don't know,12.3%",Periscope
"0.2Characteristic,Share of respondents
WhatsApp,67%
Facebook,21%
Instagram,16%
Google,8%
eBay Kleinanzeigen,5%
Periscope,0%
Xing,0.6%
Other,1.2%
Don't know,12.3%",2
"17Characteristic,Sales share
Retail,81%
Wholesale,17%
Rendered services,2%",17
"64Characteristic,Market share
Retail,81%
Wholesale,17%
Rendered services,2%",64
"2017Characteristic,Revenue in billion U.S. dollars
Roche (Switzerland)*,37.1
Amgen (U.S.),15.6
Novo Nordisk (Denmark)*,12.4
Gilead Sciences (U.S.),8.4
""Merkc Serono (Germany)"",8.2
Biogen Idec (U.S.),5.0
Celgene (U.S.),4.8",2011
"13.7Characteristic,Revenue in billion U.S. dollars
""Roche (Switzerland)*"",37.1
""Amgen (U.S.)"",15.6
""Novo Nordisk (Denmark)*"",12.4
""Gilead Sciences (U.S.)"",8.4
""Merck Serono (Germany)*"",8.2
""Biogen Idec (U.S.)"",5.0
""Celgene (U.S.)"",4.8",7.76
"2Characteristic,Number of likes in millions
The Simpsons,74.4
Mr. Bean,60.4
SpongeBob SquarePants,58.2
Family Guy,56.3
South Park,50.7
House,44.1
The Big Bang Theory,31.9
Two and a Half Men,30.9
Furturama,30.4
The Walking Dead,29.8",1
"46.5Characteristic,Number of likes in millions
The Simpsons,74.4
Mr. Bean,60.4
SpongeBob SquarePants,58.2
Family Guy,56.3
South Park,50.7
House,44.1
The Big Bang Theory,31.9
Two and a Half Men,30.9
Futurama,30.4
The Walking Dead,29.8",44.6
"Kit (Nike)Characteristic,Sponsorship revenue in million U.S. dollars
Kit (Nike),26
Jersey (Jeep),19
Stadium (Sportsfive),7",Kit (Nike)
"15.67Characteristic,Sponsorship revenue in million U.S. dollars
Kit (Nike),26
Jersey (Jeep),19
Stadium (Sportfive),7",17.3
"40889Characteristic,Per capita real GDP in chained 2012 U.S. dollars
2019,43576
2018,44759
2017,42528
2016,43202
2015,43544
2014,42073
2013,41866
2012,42220
2011,41585
2010,40925
2009,39978
2008,41326
2007,41856
2006,40340
2005,39439
2004,38801
2003,36807
2002,35678
2001,37202
2000,34716",41856
"42411Characteristic,Per capita real GDP in chained 2012 U.S. dollars
2019,43576
2018,44182
2017,43330
2016,42528
2015,43544
2014,
2013,41866
2012,42396
2011,
2010,40925
2009,39978
2008,
2007,41132
2006,40340
2005,39439
2004,38801
2003,36807
2002,35678
2001,34975
2000,34716",39146
"4Characteristic,Share of respondents
Definitely unlikely,26%
Rather unlikely,35%
Very likely,14%
Rather likely,26%",4
"26Characteristic,Share of respondents
Definitely unlikely,26%
Rather unlikely,35%
Very likely,14%
Rather likely,26%",40
"3Characteristic,Share of respondents
Recipe,75%
Comedy,4%
Crafts,5%
Fitness/Health,3%
DIY Home,3%
Other*,10%",2
"1Characteristic,Market share
Other*,10%
DIY Home,3%
Fitness/Health,3%
Comedy,4%
Crafts,5%
Recipe,75%",1.25
"69Characteristic,Market value share
Companion animal,69%
Aquatics,31%",69
"2.23Characteristic,Share of sales
Companion animal,69%
Aquatics,31%",2.2258
"LAAP*Characteristic,Share of sales
United States,64.11%
LAAP*,16.97%
EMEA,11.95%
Canada,6.97%",LAAP*
"145.97Characteristic,Share of revenue
United States,64.11%
""LAAP*16.97"",16.97%
EMEA,11.95%
Canada,6.97%",71.08
"1Characteristic,Emissions in million metric tons
2018,14766
2017,14506
2015,14607
2010,13828
2005,11447
2000,8937
1995,8505
1990,8288
1985,7392
1980,6600
1975,5648
1971,5230",3
"12005Characteristic,Emissions in million metric tons
2018,14766
2017,14506
2015,14607
2010,13828
2005,11447
2000,8937
1995,8505
1990,8288
1985,7392
1980,6600
1975,5648
1971,5230",10878
"41.5Characteristic,Share of respondents
Don't know,13.9%
No,44.5%
Yes,41.5%",41.5
"3.4Characteristic,Share of respondents
Don't know,13.9%
No,44.5%
Yes,41.5%",3
"Michael KorsCharacteristic,Revenue share
Michael Kors,74.82%
Versace,15.19%
Jimmy Choo,10%",Michael Kors
"25.9Characteristic,Sales share
Michael Kors,74.82%
Versace,15.19%
Jimmy Choo,10%",25.19
"TurkeyCharacteristic,Market share
UK,26%
Germany,16%
France,14%
Spain,11%
Sweden,7%
Netherlands,5%
Denmark,4%
Finland,3%
Belgium,2%
Switzerland,2%
Turkey,2%
Other,4%
Cyprus,0%",Netherlands
"15Characteristic,Share of respondents
UK,26%
Germany,16%
France,14%
Spain,11%
Sweden,7%
Netherlands,5%
Denmark,4%
Italy,4%
Finland,3%
Belgium,2%
Switzerland,2%
Turkey,2%
Cyprus,0%
Other,4%",18.6
"6Characteristic,Share of respondents
Yes,57%
No,37%
Don't know,6%",6
"1.63918Characteristic,Share of respondents
Yes,57%
No,37%
Don't know,6%",1.54
"18.2Characteristic,Share of respondents
Monthly,41.2%
Weekly,37.8%
Daily,18.2%
Stopped using,2.8%",18.2
"30.7Characteristic,Share of users
Monthly,41.2%
Weekly,37.8%
Daily,18.2%
Stopped using,2.8%",22
"Somewhat poorlyCharacteristic,Share of respondents
Very well,32%
Somewhat well,50%
Somewhat poorly,13%
Very poorly,4%
I do not know,2%",I do not know
"1Characteristic,Share of respondents
Very well,32%
Somewhat well,50%
Somewhat poorly,13%
Very poorly,4%
I do not know,2%",2
"6.6Characteristic,Share of immigrants
2015,9.3%
2010,8.5%
1999,7.3%
1990,7.4%
1982,7.4%
1975,7.4%
1968,6.6%
1962,6.2%
1954,5.4%
1946,5%
1936,5.6%
1931,6.6%
1926,5.7%
1921,3.7%",6.6
"12.8Characteristic,Share of immigrants
2015,9.3%
2010,8.5%
1999,7.3%
1990,7.4%
1982,7.4%
1975,7.4%
1968,6.6%
1962,6.2%
1954,5.4%
1946,5%
1936,5.6%
1931,6.6%
1926,5.7%
1921,3.7%",17.8
"19.7Characteristic,Return on equity (ROE) ratio
2020*,15.7%
2019,19.7%
2018,13.8%
2017,8%
2016,10%
2015,2%
2014,8%",19.7
"19.7Characteristic,Return on equity (ROE) ratio
2020*,15.7%
2019,19.7%
2018,13.8%
2017,8%
2016,10%
2015,2%
2014,8%",19.7
"Definitely yesCharacteristic,Share of respondents
Definitely yes,81.8%
Rather so,13.2%
Rather not,2.8%
Definitely not,2.3%",Definitely yes
"11.2Characteristic,Share of respondents
Definitely yes,81.8%
Rather so,13.2%
Rather not,2.8%
Definitely not,2.3%",18.3
"2019Characteristic,Unemployment rate
2020,9.38%
2019,8.8%
2018,7.3%
2017,7.2%
2016,7.44%
2015,7.45%
2014,7.54%
2013,7.51%
2012,6.6%
2011,7.24%
2010,7.11%
2009,6.25%
2008,7.28%
2007,8.63%
2006,8.61%
2005,10.66%
2004,15.07%
2003,16.78%
2002,16.17%
2001,13.04%
2000,13.99%
1999,14.53%",2004
"2.6Characteristic,Unemployment rate
2020,9.38%
2019,8.8%
2018,7.37%
2017,7.3%
2016,7.44%
2015,7.44%
2014,7.54%
2013,7.54%
2012,6.6%
2011,6.6%
2010,7.11%
2009,6.25%
2008,7.28%
2007,7.28%
2006,8.61%
2005,10.66%
2004,15.07%
2003,16.78%
2002,16.17%
2001,13.04%
2000,13.99%
1999,14.53%",10.53
"408Characteristic,Number of cases
Male,10335
Female,1408
Unknown,4502",1408
"4502Characteristic,Number of offenders
Male,10335
Female,1408
Unknown,4502",5910
"2019Characteristic,Average annual wages in euros
2019,39099
2018,38477
2017,37860
2016,37162
2015,36124
2014,35615
2013,36459
2012,35906
2011,35724
2010,35231
2009,35023
2008,33974
2007,33889
2006,33889
2005,33121
2004,32782
2003,32315
2002,31700
2001,32439
2000,31247",2019
"2012Characteristic,Average annual wages in euros
2019,39099
2018,38677
2017,37860
2016,37162
2015,37142
2014,36459
2013,36492
2012,35906
2011,35724
2010,35233
2009,35023
2008,33974
2007,33332
2006,33889
2005,33121
2004,32062
2003,32305
2002,32020
2001,31635
2000,31247",2009
"Staying alert and trustworthyCharacteristic,Share of respondents
Staying alert and trustworthy,57%
Don't believe it can impact us or anything,12%
Can't say,18%
Don't know much about coronavirus,3%
Don't believe it can impact us,3%",Staying alert and taking precautions
"3Characteristic,Share of respondents
Staying alert and test...,-,93%
Don't believe it can impact us or...,,,
Can't say,6%,0%
Don't know much about coronavirus,3%,0%
Don't believe it can impact us,3%,0%",6
"18-24Characteristic,Share of internet users
18-24,18%
25-34,32%
35-44,19%
45-54,14%
55-64,10%
65+,7%",25-34
"177Characteristic,Share of respondents
18-24,18%
25-34,32%
35-44,19%
45-54,14%
55-64,10%
65+,7%",25
"CornCharacteristic,Production in million metric tons
Corn,1116.34
Wheat,764.49
Rice (milled),495.78
Barley,156.41
Sorghum,57.97
Oats,22.83
Rye,12.17",Corn
"1143.54Characteristic,Production in million metric tons
Corn,116.34
Wheat,764.49
Rice (milled),495.78
Barley,156.41
Sorghum,57.97
Oats,22.83
Rye,12.17",1104.17
"91817Characteristic,Area in thousand acres
Alaska,91817
Georgia,24352
Oregon,24116
Alabama,22800
Mississippi,19495
Michigan,19262
Arkansas,18544
Montana,18429
Washington,18081
North Carolina,18078",91817
"24484Characteristic,Area in thousand acres
Alaska,91817
Georgia,24352
Oregon,24116
Alabama,22800
Mississippi,19495
Michigan,19262
Arkansas,18544
Montana,18429
Washington,18081
North Carolina,18078",67465
"83.29Characteristic,National debt to GDP ratio
2026*,86.71%
2025*,83.29%
2024*,80.42%
2023*,77.29%
2022*,69.61%
2021*,66.83%
2020*,57.05%
2019,66.33%
2018,57.05%
2017,51.73%
2016,48.24%
2015,39.97%
2014,39.97%
2013,37.04%
2012,33.77%
2011,33.77%
2010,33.77%
2009,34.57%",83.29
"8.35Characteristic,National debt to GDP ratio
2026*,87.35%
2025*,83.29%
2024*,80.42%
2023*,77.29%
2022*,69.61%
2021*,66.83%
2020*,65.48%
2019,57.05%
2018,55.04%
2017,51.73%
2016,48.24%
2015,39.97%
2014,37.04%
2013,35.66%
2012,37.04%
2011,33.77%
2010,31.36%
2009,34.57%",2.87
"NFL (2016)Characteristic,Average ticket price in U.S. dollars
MLB (2015),31.0
NBA (2015/16),55.88
NHL (2014/15),62.18
NFL (2016),92.98",NFL (2016)
"63.19Characteristic,Average ticket price in U.S. dollars
""NFL (2016)"",92.98
""NHL (2014/15)"",62.18
""NBA (2015/16)"",55.88
""MLB (2015)"",31",43.44
"2018Characteristic,Unemployment rate
2020,11.4%
2019,11.35%
2018,11.28%
2017,11.41%
2016,11.55%
2015,11.62%
2014,11.69%
2013,11.78%
2012,11.75%
2011,11.72%
2010,11.62%
2009,11.21%
2008,11.11%
2007,11.27%
2006,11.46%
2005,11.67%
2004,11.77%
2003,11.84%
2002,11.79%
2001,11.76%
2000,11",2008
"1.5Characteristic,Unemployment rate
2020,11.4%
2019,11.35%
2018,11.28%
2017,11.41%
2016,11.55%
2015,11.62%
2014,11.69%
2013,11.78%
2012,11.75%
2011,11.72%
2010,11.62%
2009,11.21%
2008,11.27%
2007,11.24%
2006,11.46%
2005,11.67%
2004,11.77%
2003,11.84%
2002,11.92%
2001,11.76%
2000,11.",0.19
"11-20 minsCharacteristic,Share of respondents
Less than a minute,4%
1-5 mins,29%
6-10 mins,31%
11-20 mins,27%
21-30 mins,7%
31-60 mins,1%",1-5 mins
"1Characteristic,Share of respondents
Less than a minute,4%
1-5 mins,29%
6-10 mins,31%
11-20 mins,27%
21-30 mins,7%
31-60 mins,1%",33
"2021Characteristic,Number of deaths
2021*,827
2020,1417
2019,1885
2018,2299
2017,3139
2016,5143
2015,4054
2014,3283",2021
"237Characteristic,Number of deaths
2021*,827
2020,1417
2019,1885
2018,2299
2017,3139
2016,5143
2015,4054
2014,3283",590
"White aloneCharacteristic,Number of residents
""White alone"",5212705
""Black or African American alone"",1625942
""Hispanic or Latino (of any race)"",828154
Asian alone,560030
""Two or more races"",263515
""Some other race alone"",23329
""American Indian and Alaska Native alone"",17497
Native Hawaiian and Other Pacific Islander alone,4347",Black or African American alone
"32024Characteristic,Number of residents
White alone,5212705
""Black or African American alone"",1625942
""Hispanic or Latino (of any race)"",828154
Asian alone,560030
""Two or more races"",263515
""Some other race alone"",23329
""American Indian and Alaska Native alone"",17497
""Native Hawaiian and Other Pacific Islander alone"",4347",542533
"[2003, 2010]Characteristic,Unemployment rate
2020,-
2019,1.84%
2018,-
2017,1.79%
2016,1.75%
2015,1.86%
2014,1.88%
2013,1.91%
2012,3.58%
2011,3.62%
2010,3.6%
2009,2.89%
2008,2.5%
2007,2.19%
2006,2.01%
2005,1.9%
2004,2.68%
2003,3.56%
2002,3.16%
2001,3.01%
2000,2.83%
1999,2.56%","[2003,2009]"
"0.16Characteristic,Unemployment rate
2020,1.84%
2019,1.85%
2018,1.79%
2017,1.8%
2016,1.79%
2015,1.82%
2014,1.86%
2013,1.91%
2012,3.56%
2011,3.58%
2010,3.6%
2009,2.89%
2008,2.5%
2007,2.19%
2006,2.5%
2005,1.9%
2004,2.68%
2003,3.56%
2002,3.16%
2001,3.48%
2000,2.83%
1999,2.56%",0
"PennsylvaniaCharacteristic,Number of specialist physicians
California,115347
New York,94152
Texas,66916
Florida,59065
Pennsylvania,53532
Illinois,45039
Ohio,44178
Michigan,40807
Massachusetts,37494
New Jersey,31545",Texas
"22,628Characteristic,Number of specialist physicians
California,115347
New York,94152
Texas,66916
Florida,59065
Pennsylvania,53532
Illinois,45039
Ohio,44178
Michigan,40807
Massachusetts,37494
New Jersey,31545",22738
"15017Characteristic,Average annual wages in euros
2019,15017
2018,14310
2017,13931
2016,13539
2015,13116
2014,12613
2013,12406
2012,12280
2011,12277
2010,11967
2009,11462
2008,10987
2007,10344
2006,10177
2005,10012
2004,9402
2003,9052
2002,8767
2001,8606
2000,8449",15017
"15717Characteristic,Average annual wages in euros
2019,15017
2018,14310
2017,13931
2016,13539
2015,13116
2014,12613
2013,12300
2012,12183
2011,12280
2010,11967
2009,11462
2008,10980
2007,10344
2006,10012
2005,9794
2004,9402
2003,9052
2002,8930
2001,8606
2000,8378",6411
"2013Characteristic,Percentage of population
2019,19.6%
2018,19.7%
2017,19.8%
2016,20.8%
2015,22%
2014,21.5%
2013,24%
2012,24.2%
2011,22.4%
2010,22.9%
2009,21.9%
2008,21.2%
2007,20.6%
2006,20.5%
2005,21.3%
2004,21.6%
2003,19.6%
2002,19.9%
2001,18.6%
2000,18.2%",2012
"21.5Characteristic,Percentage of population
2019,19.6%
2018,19.8%
2017,20.8%
2016,-
2015,22%
2014,21.5%
2013,24%
2012,24.2%
2011,-
2010,22.4%
2009,21.9%
2008,21.2%
2007,20.6%
2006,-
2005,21.3%
2004,21.6%
2003,20.6%
2002,19.9%
2001,18.6%
2000,18.2%",23.025
"53Characteristic,Share of respondents
More often than usual,17%
About the same as usual,53%
Less often than usual,27%
Not sure,3%",53
"54Characteristic,Share of respondents
More often than usual,17%
Less often than usual,27%
About the same as usual,53%
Not sure,3%",44
"10.2Characteristic,Share of deaths
- 90 years and older,19.4%
- 80-89 years,40.5%
- 70-79 years,25.2%
- 60-69 years,10.2%
- 50-59 years,3.5%
- 40-49 years,0.9%
- 30-39 years,0.2%
- 20-29 years,0.1%",10.2
"40.5Characteristic,Share of deaths
""90 years and older"",19.4%
""80-89 years"",40.5%
""70-79 years"",25.2%
""60-69 years"",10.2%
""50-59 years"",3.5%
""40-49 years"",0.9%
""30-39 years"",0.2%
""20-29 years"",0.1%",59.9
"1.45Characteristic,Exchange rate in Singapore dollars
2020,1.38
2019,1.36
2018,1.35
2017,1.38
2016,1.38
2015,1.37
2014,1.27
2013,1.25
2012,1.25
2011,1.26
2010,1.36
2009,1.45",1.45
"0.84Characteristic,Exchange rate in Singapore dollars
2020,1.38
2019,1.36
2018,1.35
2017,1.38
2016,1.38
2015,1.37
2014,1.27
2013,1.25
2012,1.25
2011,1.26
2010,1.36
2009,1.45",0.2
"2010Characteristic,Unemployment rate
2020,14.5%
2019,13.58%
2018,14.2%
2017,13.86%
2016,13.91%
2015,13.72%
2014,14.02%
2013,14%
2012,14.1%
2011,14.7%
2010,15.34%
2009,16.57%
2008,16.04%
2007,16.8%
2006,15.7%
2005,14.39%
2004,13.12%
2003,11.86%
2002,10.59%
2001,9.34%
2000,8.23%
1999,",2007
"28.3Characteristic,Unemployment rate
2020,14.5%
2019,13.58%
2018,13.8%
2017,13.8%
2016,13.86%
2015,13.9%
2014,14.02%
2013,14.1%
2012,14.1%
2011,14.7%
2010,15.34%
2009,16.04%
2008,16.8%
2007,16.8%
2006,15.57%
2005,14.39%
2004,13.12%
2003,11.86%
2002,10.59%
2001,9.34%
2000,8.23%
1999,",31.3
"8.6Characteristic,Market share
Mercadona,24.7%
Carrefour,8.6%
Lidl,6.3%
Grupo Dia,5.5%
Grupo Eroski,4.8%
Grupo Auchan (Alcampo),3.3%",8.6
"33.9Characteristic,Market share
Mercadona,24.7%
Carrefour,8.6%
Lidl,6.3%
Grupo Día,5.5%
Grupo Eroski,4.8%
Grupo Auchan (Alcampo),3.3%",31
"446.13Characteristic,Export value in million U.S. dollars
FY 2020,428.08
FY 2019,446.13
FY 2018,456.12
FY 2017,401.68
FY 2016,364.0
FY 2015,354.68",446.13
"754.62Characteristic,Export value in million U.S. dollars
FY 2020,428.08
FY 2019,446.13
FY 2018,456.12
FY 2017,401.68
FY 2016,364.0
FY 2015,354.68",756.36
"2019Characteristic,GDP in million euros
2020,451176.9
2019,476343.6
2018,460370.1
2017,445050.1
2016,430085.3
2015,416701.4
2014,403003.3
2013,392880.0
2012,386174.7
2011,375967.8",2019
"135,434.8Characteristic,GDP in million euros
2020,451176.9
2019,476343.6
2018,460370.1
2017,445050.1
2016,430085.3
2015,416701.4
2014,403003.3
2013,392880.0
2012,386174.7
2011,375967.8",100375.8
"May '21Characteristic,Number of full-time employees in millions
May '21,126.38
Apr '21,125.8
Mar '21,125.6
Feb '21,124.87
Jan '21,124.99
Dec '20,124.69
Nov '20,124.29
Oct '20,123.65
Sep '20,122.57
Aug '20,122.46
Jul '20,119.53
Jun '20,118.94
May '20,116.55",May '21
"0.25Characteristic,Number of full-time employees in millions
May '21,126.38
Apr '21,125.8
Mar '21,125.87
Feb '21,124.99
Jan '21,124.87
Dec '20,124.99
Nov '20,124.29
Oct '20,123.65
Sep '20,122.57
Aug '20,122.46
Jul '20,119.53
Jun '20,118.94
May '20,116.55",2.93
"CanadaCharacteristic,Market share
United States,28%
European Union,26%
India,18%
China,13%
Canada,2%
Rest of the world,13%",Canada
"31Characteristic,Share of reserves
United States,28%
European Union,26%
India,18%
China,13%
Canada,2%
Rest of the world,13%",31
"2010Characteristic,Production in million metric tons
2019,86.44
2018,86.36
2017,82.45
2016,78.5
2015,89.13
2014,78.51
2013,89.13
2012,87.04
2011,83.34
2010,75.7
2009,56.4
2008,88.77
2007,97.62
2006,98.53
2005,95.23
2004,101.68
2003,96.14
2002,98.01
2001,89.76
2000,98.93",2009
"46.86Characteristic,Production in million metric tons
2019,86.44
2018,82.04
2017,82.45
2016,78.5
2015,78.51
2014,89.13
2013,89.13
2012,87.04
2011,83.34
2010,75.7
2009,56.4
2008,88.77
2007,98.53
2006,97.56
2005,95.23
2004,101.68
2003,96.14
2002,91.46
2001,89.76
2000,98.93",45.28
"50.4Characteristic,Distribution of sales
Flanders,50.4%
Wallonia,36.6%
Brussels,13%",50.4
"49.7Characteristic,Share of respondents
Flanders,50.4%
Wallonia,36.6%
Brussels,13%",87
"2Characteristic,Net sales share
Europe,40%
North America,24%
Asia,24%
South America,6%
Africa and Oceania,6%",2
"12Characteristic,Market share
Europe,40%
North America,24%
Asia,24%
South America,6%
Africa and Oceania,6%",12
"6Characteristic,Market size share
Manufacturing,40.7%
Financial and insurance services,18.43%
""Transport, mailing & storage"",11.8%
Trade,7.15%
Mining,5.52%
Electricity generation,3.99%
Other,13.01%",7
"Electricity generationCharacteristic,Share of employers
Manufacturing,40.1%
Financial and insurance services,18.43%
""Transport, mailing & storage"",11.3%
Trade,7.15%
Mining,5.52%
Electricity generation,3.99%
Other,13.01%",Mining
"Trygg-HansaCharacteristic,Market share
Länsförsäkringar,30.3%
If Skadeförsäkring,18.2%
Folksam,16.4%
Trygg-Hansa,13.7%
Moderna,3.3%
Other Swedish companies,4.3%
Other,13.8%",Moderna
"FolksamCharacteristic,Market share
Länsförsäkringar,30.3%
If Skadeförsäkring,18.2%
Folksam,16.4%
Trygg-Hansa,13.7%
Moderna,3.3%
Other Swedish companies,4.3%
Other,13.8%",Folksam
"YesCharacteristic,E-commerce sales growth rate
2021*,9.7%
2020*,13.6%
2019*,17.5%
2018*,22%
2017*,25%
2016,25.9%",Yes
"2016Characteristic,E-commerce sales growth rate
2021*,9.7%
2020*,13.6%
2019*,17.5%
2018*,22%
2017*,25%
2016,25.9%",2016
"May '21Characteristic,Chained consumer Price Index (1999=100)
May '21,151.25
Apr '21,150.07
Mar '21,148.84
Feb '21,147.8
Jan '21,146.98
Dec '20,146.33
Nov '20,146.21
Oct '20,146.31
Sep '20,146.27
Aug '20,146.05
Jul '20,145.6
Jun '20,144.85
May '20,144.02",May '21
"0.1195Characteristic,Chained Consumer Price Index (1999=100)
May '21,151.25
Apr '21,150.07
Mar '21,148.84
Feb '21,148.05
Jan '21,146.98
Dec '20,146.33
Nov '20,146.21
Oct '20,146.31
Sep '20,146.27
Aug '20,146.05
Jul '20,145.6
Jun '20,144.85
May '20,143.04",7.23
"35900Characteristic,Reserves in million metric tons
Russia*,90447
Australia,76508
Germany,35900
United States,30003
Indonesia,11728
Turkey,10975
China,8128
Serbia,7112
New Zealand,6750
Poland,5865",6750
"FranceCharacteristic,Reserves in million metric tons
Russia*,90447
Australia,76508
Germany,35900
United States,30003
Indonesia,11728
Turkey,10975
China,8128
Serbia,7112
New Zealand,6750
Poland,5865","[Germany,United States]"
"22Characteristic,Retail sales share
Bed & bathroom,22%
Living room,19%
Kitchen & dining,15%
Children's IKEA,5%
IKEA food,5%
Other,34%",22
"1Characteristic,Share of sales
Bed & bathroom,22%
Living room,19%
Kitchen & dining,15%
Children's IKEA,5%
IKEA food,5%
Other,34%",0
"GroceryCharacteristic,Market share
Grocery,56.3%
General merchandise,32.3%
Health and wellness,10.4%
Other,1%",Grocery
"33.7Characteristic,Share of net sales
Grocery,56.3%
General merchandise,32.3%
Health and wellness,10.4%
Other,1%",11.4
"TizenCharacteristic,Market share
Tizen,22%
WebOS,14%
Android TV*,10%
Robku TV,8%
FireFox OS/My Home Screen**,8%
Amazon Fire TV Edition,6%
Others***,3%",Robku TV
"14Characteristic,Market share
Tizen,22%
WebOS,14%
Android TV*,10%
Robku TV,8%
FireFox OS/My Home Screen**,8%
Amazon Fire TV Edition,6%
Others***,3%",14
"2007Characteristic,Number of fatalities
2019,270
2018,260
2017,276
2016,275
2015,310
2014,295
2013,251
2012,352
2011,325
2010,353
2009,384
2008,606
2007,661
2006,608",2007
"408Characteristic,Number of fatalities
2019,270
2018,260
2017,276
2016,275
2015,310
2014,295
2013,251
2012,352
2011,325
2010,353
2009,384
2008,606
2007,661
2006,608",410
"28.49Characteristic,Population density in people per square kilometer
2018,30.6
2017,29.71
2016,29.28
2015,28.87
2014,28.49
2013,28.14
2012,27.8
2011,27.44
2010,27.06
2009,26.66",28.49
"60.48Characteristic,Population density in people per square kilometer
2018,30.6
2017,29.71
2016,29.28
2015,28.87
2014,28.49
2013,28.14
2012,27.8
2011,27.44
2010,27.06
2009,26.66",60.31
"2.06Characteristic,Exchange rate in Singapore dollars
2020,1.86
2019,1.94
2018,1.97
2017,2.12
2016,2.06
2015,2.14
2014,2.08
2013,2.14
2012,2.34
2011,2.7
2010,2.98
2009,3.01",2.06
"1.4Characteristic,Exchange rate in Singapore dollars
2020,1.86
2019,1.94
2018,1.97
2017,2.12
2016,2.06
2015,2.14
2014,2.08
2013,2.14
2012,2.34
2011,2.7
2010,2.98
2009,3.01",12
"PhilosophyCharacteristic,Sales in thousand euros
Moschino,262507
Pollini,35920
Alberta Ferretti,26144
Philosophy,18244
Other,8588",Philosophy
"131034.5Characteristic,Sales in thousand euros
Moschino,262507
Pollini,35920
Alberta Ferretti,26144
Philosophy,18244
Other,8588",131253.5
"Online authorized dealersSales channel,Own mono-brand boutique,Online authorized dealers,Brick and mortar mono- brand stores,Brick and mortar authorized deals
67%,42%,36%,24%",Online authorized dealers
"46.8Sales channel,Share of respondents
Own mono-brand e-,67%
Online authorized dealers,42%
Brick and mortar mono-brand stores,36%
Brick and mortar authorized deals,24%",42.25
"10Characteristic,Percentage of population
2019,9.3%
2018,8.8%
2017,9.5%
2016,9.3%
2015,10.6%
2014,11.4%
2013,10.8%
2012,11.6%
2011,12%
2010,10.7%
2009,10.4%
2008,9.1%
2007,8%
2006,9.3%
2005,9.8%
2004,10.6%
2003,10.9%
2002,10.1%
2001,10.4%
2000,8.8%",20
"7Characteristic,Percentage of population
2019,9.3%
2018,8.8%
2017,9.5%
2016,9.3%
2015,10.6%
2014,11.4%
2013,10.8%
2012,11.6%
2011,12%
2010,10.7%
2009,10.4%
2008,9.1%
2007,8%
2006,9.3%
2005,9.8%
2004,10.6%
2003,10.9%
2002,10.1%
2001,10.4%
2000,8.8%",3
"4Characteristic,GDP in billion U.S. dollars
""New York, U.S."",44
""Tokyo, Japan"",40
""Beijing, China"",10
""Osaka, Japan"",10
""Shanghai, China"",10
""Sao Paulo, Brazil"",8
""Bombay, India"",7
""Guangzhou, China"",6
""Mexico City, Mexico"",5
""Delhi, India"",4",3
"84Characteristic,GDP in billion U.S. dollars
""New York, U.S."",44
""Tokyo, Japan"",40
""Beijing, China"",10
""Osaka, Japan"",10
""Shanghai, China"",10
""Sao Paulo, Brazil"",8
""Bombay, India"",7
""Guangzhou, China"",6
""Mexico City, Mexico"",5
""Delhi, India"",4",93
"CanadaCharacteristic,Export value in million GBP
Canada,6.02
United States,5.48
Irish Republic,4.63
Germany,2.82
Australia,1.39",Canada
"0.66Characteristic,Export value in million GBP
Canada,6.02
United States,5.48
Irish Republic,4.63
Germany,2.82
Australia,1.39",1.43
"13942Characteristic,Number of deaths
Any opioid,47600
Synthetic opioids other than methodone,28466
Prescription opioids,17029
Heroin,15482
Natural and semi-synthetic opioids,14495
Cocaine,13942
Psychostimulants with abuse potential,10333
Methadone,3194",13942
"46827.5Characteristic,Number of deaths
Any opioid,47600
Synthetic opioids other than methodone,28466
Prescription opioids,17029
Heroin,15482
Natural and semi-synthetic opioids,14495
Cocaine,13942
Psychostimulants with abuse potential,10333
Methadone,3194",25397
"6Characteristic,Average daily usage time in minutes
Indonesia,66
India,62
Philippines,56
China,55
Malaysia,54
Thailand,50
South Korea,50
Vietnam,47
Singapore,46
Japan,38",10
"[Vietnam, South Korea]Characteristic,Average daily usage time in minutes
Indonesia,66
India,62
Philippines,56
China,55
Malaysia,54
Thailand,50
South Korea,50
Vietnam,47
Singapore,46
Japan,38","[Thailand, South Korea]"
"6Characteristic,Demand in million metric tons
2015*,63.9
2014*,61.2
2013*,58.5
2012*,55.8
2011*,52.8
2010*,50.7
2009,49.1
2008,54.0",8
"58.1Characteristic,Demand in million metric tons
2015*,63.9
2014*,61.2
2013*,58.5
2012*,55.8
2011*,52.8
2010*,50.7
2009,49.1
2008,54.0",61.2
"48Characteristic,Share of respondents
2013,48%
2011,43%
2009,33%
2007,26%
2005,18%",48
"35.5Characteristic,Share of respondents
2013,48%
2011,43%
2009,33%
2007,26%
2005,18%",33.6
"6Characteristic,Sales growth rate
Face masks,100%
Alcohol-based hand sanitizers,623%",6.23
"523Characteristic,Sales growth rate
Face masks,100%
Alcohol-based hand sanitizers,623%",200
"6Characteristic,Market share
United States,23.7%
United Kingdom,15.57%
Italy,10.63%
China,6.63%
France,6.07%
Australia,5.89%
Germany,5.33%
Denmark,0.16%
Other,26%",8
"39.4Characteristic,Distribution of sales
United States,23.7%
United Kingdom,15.57%
Italy,10.63%
France,6.07%
China,6.63%
Australia,5.89%
Germany,5.33%
Denmark,0.16%
Other,26%",39.27
"3Characteristic,Market size share
Fast-moving consumer goods,53%
Hardlines & leisure goods,28%
Apparel & Accessories,10%
Diversified,5%",5
"0.5Characteristic,Market share
Fast-moving consumer goods,-
Hardlines & leisure goods,-
Apparel & Accessories,10%
Diversified,5%",0.5
"Revenue from retail sales of Samsung electronicsCharacteristic,Estimated revenue in billion U.S. dollars
2019,51.9
2018,50.19
2017,46.24
2016,43.59
2015,40.7
2014,38.12
2013,37.79
2012,34.83
2011,31.3
2010,30.87
2009,29.18
2008,28.41
2007,30.67
2006,27.88
2005,26.01
2004,24.57
2003,22.41
2002,21.1
2001,20.36
2000,21.58",Estimated revenue in billion U.S. dollars
"2018Characteristic,Estimated revenue in billion U.S. dollars
2019,51.9
2018,50.19
2017,46.24
2016,43.59
2015,40.7
2014,38.12
2013,36.69
2012,34.83
2011,31.3
2010,30.87
2009,29.18
2008,29.69
2007,30.67
2006,27.88
2005,28.3
2004,24.57
2003,22.41
2002,21.1
2001,21.58",2009
"28Characteristic,Users in millions
Facebook,36.9
Instagram,27.7
LinkedIn,18.6
Pinterest,16.7
Twitter,10.0
TikTok,6.6
Reddit,2.8",16.7
"29Characteristic,Users in millions
Facebook,36.9
Instagram,27.7
LinkedIn,18.6
Pinterest,16.7
Twitter,10.0
TikTok,6.6
Reddit,2.8",3.38
"2018Characteristic,Revenue in million euros
2020*,3922
2019,3613
2018,3276
2017,1928
2016,1785
2015,1676
2014,1581
2013,1484",2018
"3199.46Characteristic,Revenue in million euros
2020*,3922
2019,3613
2018,3276
2017,1928
2016,1785
2015,1676
2014,1581
2013,1484",2408.125
"Dark BlueCharacteristic,Share of respondents
Beef,26%
Poultry,19%
Pork,19%
Fish and seafood,16%
Eggs,7%
Other meats,13%",red
"0Characteristic,Share of expenditures
Beef,26%
Poultry,19%
Pork,19%
Fish and seafood,16%
Eggs,7%
Other meats,13%",2.33
"24Characteristic,Share of respondents
No. I don't have any,37%
""Yes. I have a few"",35%
""Yes. lots of them"",24%
""What is a vinyl record?"",4%",24
"66Characteristic,Share of respondents
. No. I don't have any,37%
. Yes. I have a few,35%
- Yes. lots of them,24%
What is a vinyl record?,4%",59
"11Characteristic,Revenue share
United States,26.8%
Australia,9.3%
France,7.1%
Germany,6.1%
Netherlands,4.7%
Canada,4%
Spain,3.5%
Other countries,38.5%",8
"0.46Characteristic,Share of respondents
United States,26.8%
Australia,9.3%
France,7.1%
Germany,6.1%
Netherlands,4.7%
Canada,4%
Spain,3.5%
Other countries,38.5%",36.1
"32.4Characteristic,Market value share
Beer,32.4%
Food,25.5%
Spirits and spirit-based drinks,15.7%
Wine,11%
""Cider"",5.1%
Other,10.3%",32.4
"30Characteristic,Revenue share
Beer,32.4%
Food,25.5%
Spirits and spirit-based drinks,15.7%
Wine,11%
Cider,5.1%
Other,10.3%",67.6
"4Characteristic,Share of respondents
Internet,35%
Social media,26%
Television,21%
Friends & family,7%
Newspapers,6%
Other,4%
I don't keep myself updated,2%",7
"9Characteristic,Share of respondents
Internet,35%
Social media,26%
Television,21%
Friends & family,7%
Newspapers,6%
I don't keep myself updated,2%
Other,4%",9
"2015Characteristic,Growth rate
2019*,14.4%
2018*,14.9%
2017*,15.8%
2016*,17.6%
2015*,17.7%
2014,18.6%
2013,16.6%
2012,17.7%",2014
"2Characteristic,Growth rate
2019*,14.4%
2018*,14.9%
2017*,15.8%
2016*,17.6%
2015*,17.7%
2014,18.6%
2013,16.6%
2012,17.7%",7
"DatabaseCharacteristic,Market share
Application,52.3%
Infrastructure software,17.7%
SaaS,11.9%
OS,6.6%
Custom,5.8%
Database,4.1%
Analytics,1.5%",Analytics
"75.3Characteristic,Market share
Application,52.3%
Infrastructure software,17.7%
Saas,11.9%
OS,6.6%
Custom,5.8%
Database,4.1%
Analytics,1.5%",70
"25Characteristic,Share of respondents
Holidays in the UK,33%
A more extended period of time off  (e.g. a week or more) spent at home,26%
The occasional day off spent at home,23%
My employer has increased the number of days we can carry over to next year,11%
I expect to use less of my holiday allowance and will those days,9%
Other,3%
Don't know,25%",25
"25Characteristic,Share of respondents
Holidays in the UK,33%
""a more extended period of time off (e.g. a week or more) spent at home"",26%
The occasional day off spent at home,23%
My employer has increased the number of days we can carry over to next year,11%
I expect to use less of my holiday allowance and will those days,9%
Other,3%
Don't know,25%",23
"27.95Characteristic,0-14 years,15-64 years,65 years +
2019,14.58%,65.78%,19.65%
2018,14.67%,65.95%,19.38%
2017,14.7%,66.15%,19.15%
2016,14.77%,66.32%,18.91%
2015,14.91%,66.45%,18.65%
2014,14.91%,66.78%,18.32%
2013,14.94%,67.08%,17.98%
2012,14.98%,67.38%,17.64%
2011,14.94%,67.73%,17.33%
2010,14.79%,68.15",15.75
"2012Characteristic,0-14 years,15-64 years,65 years +
2019,14.58%,65.78%,19.65%
2018,14.67%,65.95%,19.38%
2017,14.7%,66.15%,19.15%
2016,14.77%,66.32%,18.91%
2015,14.91%,66.45%,18.65%
2014,14.91%,66.78%,18.32%
2013,14.94%,67.08%,17.98%
2012,14.98%,67.38%,17.64%
2011,14.94%,67.73%,17.33%
2010,14.79%,68.15%,",2019
"64.22Characteristic,Agriculture,Industry,Services
2019,0.73%,46.16%,53.11%
2018,0.74%,47.03%,52.25%
2017,0.77%,42.57%,56.65%
2016,0.78%,41.45%,57.78%
2015,0.74%,43.89%,55.37%
2014,0.64%,52.76%,46.6%
2013,0.54%,55.01%,44.35%
2012,0.64%,57.45%,41.91%
2011,0.67%,58.04%,41.29%
2010,0.76%,52.53%,46.71%
2009,1.04%,52.0",55.01
"5.05Characteristic,Agriculture,Industry,Services
2019,0.73%,46.16%,53.11%
2018,0.74%,47.03%,52.25%
2017,0.77%,42.57%,56.65%
2016,0.78%,41.45%,57.78%
2015,0.74%,43.89%,55.37%
2014,0.64%,52.76%,46.6%
2013,0.54%,55.01%,44.35%
2012,0.64%,57.45%,41.91%
2011,0.67%,58.04%,41.29%
2010,0.76%,52.53%,46.71%
2009,1.04%,52.04",16.59
"856.36Characteristic,1910,2010
Global North,502.9%,856.36%
Global South,108.91%,1327.7%
World Total,611.81%,2184.06%",856.36
"2010Characteristic,1910,2010
Global North,502.9%,856.36%
Global South,108.91%,1327.7%
World Total,611.81%,2184.06%",2010
"Too manyCharacteristic,Too many,Not enough,Just the right number,Don't know
Oct '19,30%,63%,30%,-
Oct '18,31%,63%,3%,-
Oct '17,34%,60%,3%,-
Oct '16,29%,63%,4%,-
Oct '15,30%,64%,4%,-
Oct '14,30%,63%,4%,-
Oct '13,30%,63%,4%,-
Oct '12,26%,66%,5%,-
Nov '11,24%,68%,5%,-
Sep '10,30%,63%,5%,-
Sep '09,31%,62%,5%,-
Sep '08,30%,64%,4%,-
Sep '07,32%,62%,5%,-
Sep '06,36%,58%,4%,-
Oct '05,36%,58%,4%,-
Oct '04,30%,53",Just the right number
"62Characteristic,Too many,Not enough,Just the right number,Don't know
Oct '19,30%,63%,63%,-
Oct '18,31%,63%,63%,-
Oct '17,34%,60%,60%,-
Oct '16,29%,63%,63%,-
Oct '15,30%,64%,64%,-
Oct '14,30%,63%,63%,-
Oct '13,30%,63%,63%,-
Nov '12,26%,66%,66%,-
Nov '11,24%,68%,68%,-
Sep '10,30%,63%,63%,-
Sep '09,31%,62%,62%,-
Sep '08,30%,64%,64%,-
Sep '07,30%,62%,62%,-
Sep '06,36%,58%,58%,-
Oct '05,36%,58%,5",63
"6Characteristic,Freelancers,U.S. workers overall
White,62%,66%
Hispanic or Latino,16%,15%
African or African descent,12%,10%
Asian-American/Asian,5%,5%
All others,4%,3%",5
"33Characteristic,Freelancers,U.S. workers overall
White,62%,66%
Hispanic or Latino,16%,15%
African or African descent,12%,10%
Asian- American/Asian,5%,5%
All others,4%,3%",37
"WhatsAppCharacteristic,Finland,Norway,Sweden,Denmark
Facebook Messenger,23%,51%,44%,43%
WhatsApp,12%,64%,16%,6%
iMessage,5%,24%,28%,21%",WhatsApp
"33Characteristic,Finland,Norway,Sweden,Denmark
Facebook Messenger,23%,51%,44%,43%
WhatsApp,12%,64%,16%,6%
iMessage,5%,24%,28%,21%",78
"[2017, 2023]Characteristic,2017,2023
Digestive health,73%,62.8%
Immune health,13.9%,25%
Women's health,7%,6.9%
Oral health,1.5%,1.2%
Others,4.6%,4.2%","[2017, 2023]"
"[Digestive health, Immune health]Characteristic,2017,2023
Digestive health,73%,62.8%
Immune health,13.9%,25%
Women's health,7%,6.9%
Oral health,1.5%,1.2%
Others,4.6%,4.2%",Digestive health
"78Characteristic,15-24,25-44,45-64,65-74,75+
""Fracture of lower leg and ankle"",30,56,94,21,31
""Fracture of ribs, sternum and thoracic spine"",22,55,108,51,62
""Fracture of forearm"",31,60,75,24,13
""Fracture of shoulder and upper arm"",32,58,69,1013,-
""Fracture of lumbar spine and pelvis"",30,48,69,19,25
""Fracture of femur"",15,32,47,25,56
""Other and unspecified injuries of head"",19,37,24,20,13
""Open wound on head"",32,43,39,11,17
""Intracranial injury"",26,35,15,18,-",108
"32.83Characteristic,15-24,25-44,45-64,65-74,75+
""Fracture of lower leg and ankle"",30,56,94,21,31
""Fracture of ribs, sternum and thoracic spine"",22,55,108,51,62
""Fracture of forearm"",31,60,75,24,13
""Fracture of shoulder and upper arm"",32,58,69,1013,0
""Fracture of lumbar spine and pelvis"",30,48,69,19,25
""Fracture of femur"",15,32,47,25,56
""Other and unspecified injuries of head"",19,37,24,20,13
""Open wound on head"",32,43,39,11,17
""Intracranial injury"",26,35,35,15,18",70
"94Characteristic,Women,Men,Both sexes
25 to 34,95%,93%,94%
35 to 44,95%,93%,94%
45 to 54,93%,91%,92%
55 to 64,89%,86%,87%
25 to 64,93%,91%,92%",91
"YesCharacteristic,Women,Men,Both sexes
25 to 34,95%,93%,94%
35 to 44,95%,93%,94%
45 to 54,93%,91%,92%
55 to 64,89%,86%,87%
25 to 64,93%,91%,92%",No
"2010Characteristic,2G,3G,4G,5G
2024*,40,25,540
2023*,40,25,585
2022*,50,50,625
2021**,75,55,650
2020*,110,60,645
2019*,110,70,155
2018*,85,70,190
2017,110,85,225
2016,135,110,280
2015,175,135,345
2014,240,175,400
2013,300,240,435
2012,350,300,435
2011,390,350,395
2010,420,390,",2010
"89Characteristic,2G,3G,4G,5G
2024*,25,40,40,540
2023*,40,40,40,585
2022*,50,50,50,625
2021**,75,55,55,650
2020*,60,60,60,645
2019*,70,60,70,155
2018*,85,70,85,190
2017,110,85,110,225
2016,135,110,135,280
2015,175,135,175,345
2014,240,175,240,400
2013,300,240,300,435
2012,350,3",92.02
"2005-2006Characteristic,Total,Principal diagnosis,Secondary diagnosis
2008-2009,29533,5587,23946
2007-2008,30754,7290,23464
2005-2006,28155,6012,22103
1999-2000,23807,5689,17118",2007-2008
"30462Characteristic,Total,Principal diagnosis,Secondary diagnosis
2008-2009,29533,5587,23946
2007-2008,30754,7290,23464
2005-2006,28155,6012,22103
1999-2000,23807,5689,17118",112249
"1036Characteristic,Narrowbody,Widebody
2022,1029,155
2021,1036,204
2020,1024,216
2019,1125,312
2018,934,310",1125
"1412.5Characteristic,Narrowbody,Widebody
2022,1029,155
2021,1036,204
2020,1024,216
2019,1125,312
2018,934,310",239.4
"FacebookCharacteristic,Active duty,General population
Instagram,9.0,6.2
Facebook,8.8,6.8
Youtube,8.6,4.7
Snapchat,8.1,5.8
TikTok,7.5,5.3",Facebook
"7.2Characteristic,Active duty,General population
Instagram,9.0,6.2
Facebook,8.8,6.8
Youtube,8.6,4.7
Snapchat,8.1,5.8
TikTok,7.5,5.3",5.76
"2011Characteristic,female,male
2019,77.84,71.65
2018,77.67,71.58
2017,77.45,71.53
2016,77.2,71.5
2015,76.9,71.42
2014,76.54,71.27
2013,76.13,71.01
2012,75.68,70.64
2011,75.22,70.15
2010,74.74,69.59
2009,74.29,69.01",2019
"0.335Characteristic,female,male
2019,77.84,71.65
2018,77.67,71.58
2017,77.45,71.53
2016,77.2,71.5
2015,76.9,71.42
2014,76.54,71.27
2013,76.13,71.01
2012,75.68,70.64
2011,75.22,70.15
2010,74.74,69.59
2009,74.29,69.01",7.53
"59Characteristic,Share of the whole sample,Share of those informed about the conflict**
Yes, it could,21%,25%
No, it could not,27%,31%
Difficult to answer,4%,4%",58
"47Characteristic,Share of the whole sample,Share of those informed about the conflict**
""Yes, it could"",21%,25%
""No, it could not"",27%,31%
Difficult to answer,4%,4%",No
"4Characteristic,High-income,Middle-income,Low-income
Data not reported,3,1,0
Equal or less than 25% of retail price is tax,3,13,8
26-50% of retail price is tax,5,38,18
51-75% of retail prices is tax,24,35,3
More than 75% of retail price is tax,23,14,1",5
"High-incomeCharacteristic,High-income,Middle-income,Low-income
Data not reported,3,1,4
Equal or less than 25% of retail price is tax,3,13,8
26-50% of retail price is tax,5,38,18
51-75% of retail prices is tax,24,35,3
More than 75% of retail price is tax,23,14,1",Data not reported
"100-500 eurosCharacteristic,Less than 50 euros,50 - 100 euros,100 - 500 euros,500 - 1,000 euros,1,000 euros or more,Don't know
2015,8.7%,14.1%,20.9%,5.5%,3.4%,1.4%,0%
2016,8.4%,13.7%,23%,5.7%,4.1%,2.2%,0%
2017,8.1%,14.7%,25.2%,7.1%,4.8%,2.2%,0%
2018,8.6%,14%,25.3%,7.2%,5.8%,3%,0%
2019,8.4%,14.2%,25.6%,5.1%,3.4%,7.2%,0%",100 - 500 euros
"3.895454545Characteristic,Less than 50 euros,50 - 100 euros,100 - 500 euros,500 - 1,000 euros,1,000 euros or more,Don't know
2019,3.4%,5.1%,14.2%,25.6%,7.2%,8.4%,-
2018,3%,5.8%,14%,25.3%,7.2%,8.6%,-
2017,2.2%,4.8%,14.7%,25.2%,7.1%,8.1%,-
2016,2.2%,4.1%,13.7%,23%,5.7%,8.4%,-
2015,3.4%,5.5%,1.4%,20.9%,14.1%,8.7%,-",2.44
"Insurered all year, not underinsuredCharacteristic,Insurered all year, not underinsured,Insurered all year, underinsured,Insurered now, had a coverage gap,Uninsured now
2020,110,19,24,19
2018,107,19,24,19
2016,105,18,23,41
2014,101,23,29,41
2012,99,19,36,31
2010,103,15,37,29
2005,109,16,16,32
2003,112,15,16,30","Insured all year, not underinsured"
"2020Characteristic,Insured all year, not underinsured,Insured all year, underinsured,Insured now, had a coverage gap,Uninsured now
2003,112,1516,30,-,-,-,-
2005,109,1616,32,-,-,-,-
2010,103,29,15,-,-,-,-
2012,99,29,19,36,-,-,-
2014,101,31,23,29,-,-,-
2016,105,18,23,41,-,-,-
2018,107,19,24,44,-,-,-
2020,110,19,24,41,-,-,-",2005
"13Characteristic,Mostly trust,Somewhat trust,Somewhat distrust,Mostly distrust,Not sure
Democrat,42%,24%,8%,22%,-
Republican,11%,20%,18%,46%,-
Indepedent,19%,23%,13%,22%,23%
Other,11%,20%,23%,36%,-
Not sure,6%,13%,15%,8%,58%",4
"7Characteristic,Mostly trust,Somewhat trust,Somewhat distrust,Mostly distrust,Not sure
Democrat,42%,24%,8%,22%,-
Republican,5%,11%,20%,18%,46%
Indepedent,19%,13%,22%,23%,20%
Other,11%,20%,23%,36%,10%
Not sure,6%,13%,15%,8%,58%",53
"2018Characteristic,ASML,Applied Materials,Tokyo Electron,Lam Research,KLA,Others
2020,15.4%,16.4%,12.3%,10.8%,6.2%,38.8%
2019,21.6%,19.4%,14.8%,14.2%,6.9%,23.1%
2018,18%,19.2%,15.6%,15.4%,6.2%,25.8%",2019
"6.9Characteristic,ASML,Applied Materials,Tokyo Electron,Lam Research,KLA,Others
2020,15.4%,16.4%,12.3%,10.8%,6.2%,38.8%
2019,21.6%,19.4%,14.8%,14.2%,6.9%,23.1%
2018,18%,19.2%,15.6%,15.4%,6.2%,25.8%",3.4
"2013Characteristic,2013,2014,2015,2016
Residential property: owner occupied & social housing,3831,4068,4460,4805
Residential property: privately rented,929,839,1102,1015
Infrastructure,960,1061,1102,1015
Commercial property,683,787,883,871
Other non-domestic buildings,127,146,163,147",2016
"2015Characteristic,2013,2014,2015,2016
Residential property: owner occupied & social housing,4805,4068,3831,-
Residential property: privately rented,110,1015,929,839
Infrastructure,960,1061,1102,-
Commercial property,787,683,871,883
Other non-domestic buildings,127,146,163,147",2014
"18Characteristic,United States,Global average
Immediately,20%,18%
Within an hour,24%,28%
Sometimes that day,31%,37%
I don't expect a response,25%,17%",20
"40Characteristic,United States,Global average
Immediately,20%,18%
Within an hour,24%,28%
Sometime that day,31%,37%
I don't expect a response,25%,17%",38
"65Characteristic,Yes,No,Not sure
All respondents,41%,34%,25%
Democrats,65%,17%,19%
Republicans,24%,54%,22%",65
"64Characteristic,Yes,No,Not sure
All respondents,41%,34%,25%
Democrats,65%,17%,19%
Republicans,24%,54%,22%",89
"105.4Characteristic,Computing,Wireless,Consumer,Automotive,Industrial,Wired Communications
2019*,107.2,61.4,41.3,42.9,29.0,0
2014,105.4,91.9,53.9,25.8,32.1,25.6",105.4
"157.3Characteristic,Computing,Wireless,Consumer,Automotive,Industrial,Wired Communications
2019*,107.2,107.8,61.4,41.3,42.9,29
2014,105.4,91.9,53.9,32.1,25.8,25.6",197.3
"57Characteristic,Good,Neither good nor poor,Poor
Argentina,58%,28%,15%
Chile,30%,31%,39%
Mexico,26%,37%,37%
Colombia,25%,31%,44%
Peru,20%,39%,41%
Brazil,18%,25%,57%",Poor
"17Characteristic,Good,Neither good nor poor,Poor
Brazil,18%,25%,57%
Peru,20%,39%,41%
Colombia,25%,31%,44%
Mexico,26%,37%,37%
Chile,30%,31%,39%
Argentina,58%,28%,15%",40
"1999.4Region,Asia*,Europe**,North America
2021,1017.2,1992.4,933.7
2020,1041.0,1659.9,1006.7
2019,3202.9,1585.1,1048.7
2018,3231.0,-,-
2017,3795.0,882.9,933.7
2016,561.8,893.5,1561.8
2015,4645.7,915.5,-
2014,4983.0,887.0,-
2013,4700.0,912.0,1447
2012,4865.1,970.0,1486.5
2011,3819.2,662.",64.6
"[1680.1, 1659.9]Region,Asia*,Europe**,North America
2021,1488.5,622.2,1002.0
2020,1170.0,302.9,1066.0
2019,1041.0,232.3,1026.0
2018,1585.0,933.7,874.0
2017,1678.1,882.9,964.0
2016,1561.8,959.5,852.6
2015,1620.0,915.5,718.0
2014,1580.0,887.0,689.0
2013,1447.0,912.0,552.0
2012,1486.5,,",832.5
"BlackCharacteristic,Hillary Clinton,Donald Trump
White,37%,58%
Black,88%,8%
Latino,65%,29%
Asian,65%,29%
Other race,56%,37%",black
"89Characteristic,Hillary Clinton,Donald Trump
White,37%,58%
Black,88%,8%
Latino,65%,29%
Asian,65%,29%
Other race,56%,37%",153
"2Characteristic,Franchise,Company-owned
2020,2097,144
2019,2106,137
2018,2100,137
2017,1975,276
2016,1838,417
2015,1836,413
2014,1819,431
2013,1786,465
2012,1703,547
2011,1592,629",1592
"751Characteristic,Franchise,Company-owned
2020,2097,144
2019,2106,137
2018,2100,137
2017,1975,276
2016,1838,417
2015,1836,413
2014,1819,431
2013,1786,465
2012,1703,547
2011,1592,629",505
"2020Year,Western Europe,North America,Japan,Emerging countries
2020,47,32,113,-
2019,46,43,31,102
2018,43,34,26,91
2017,47,29,30,78
2016,37,25,27,70
2015,35,21,25,61
2014,33,21,22,52
2013,31,21,17,46",2020
"2016Year,Western Europe,North America,Japan,Emerging countries
2020,47,32,113,-
2019,46,43,31,102
2018,43,34,26,91
2017,47,29,30,78
2016,37,25,27,70
2015,35,21,25,61
2014,33,22,21,52
2013,31,21,17,46",2020
"33Characteristic,Lowest ROI,Medium ROI,Highest ROI,Don't use or N/A
Display advertising including programmatic,26%,31%,10%,33%
Online PR and outreach,28%,37%,15%,20%
Website personalization,18%,26%,16%,40%
""Socia media (paid ads)"",24%,36%,17%,23%
Social media (organic),33%,39%,20%,8%
Paid search marketing (AdWords),19%,37%,20%,24%
E-mail marketing and marketing automation,17%,43%,30%,10%
Content marketing,17%,40%,30%,13%
SEO,15%,41%,32%,12%",40
"53Characteristic,Lowest ROI,Medium ROI,Highest ROI,Don't use or N/A
SEO,15%,41%,32%,12%
Content marketing,17%,40%,30%,13%
E-mail marketing and marketing automation,17%,43%,30%,10%
Paid search marketing (AdWords),19%,37%,20%,24%
Social media (organic),33%,39%,20%,8%
""Socia media (paid ads)"",24%,36%,17%,23%
Website personalization,18%,26%,16%,40%
Online PR and outreach,28%,37%,15%,20%
Display advertising including programmatic,26%,31%,10%,33%",56
"2017Characteristic,2016,2017
Ted Baker,60%,60%
Boohoo,58%,55%
Inditex,58%,57%
H&M,57%,55%
M&S,55%,56%
ASOS,50%,50%
Zalando,45%,45%",2017
"15Characteristic,2016,2017
Ted Baker,60%,60%
Boohoo,58%,55%
Inditex,58%,57%
H&M,57%,55%
M&S,55%,56%
ASOS,50%,50%
Zalando,45%,45%",5
"2006Year,Casual bag segment,Travel bag segment,Business bag segment
2015*,12721,12887,6014
2014*,12140,12173,5736
2013*,11607,11514,5461
2012*,11120,10942,5233
2011*,10636,10399,4997
2010,10168,9807,4770
2009,9037,9248,4241
2008,9526,10129,4493
2007,9461,10119,4368
2006,8703,9127,4158",2015
"2138Year,Casual bag segment,Travel bag segment,Business bag segment
2015*,12721,12887,6014
2014*,12140,12173,5736
2013*,11607,11514,5461
2012*,11120,10942,5233
2011*,10636,10399,4997
2010,10168,9807,4770
2009,9037,9248,4241
2008,9526,10129,4493
2007,9461,10119,4368
2006,8703,9127,4158",3594
"[2018/19, 2017/18]Characteristic,Boys,Girls
2018/19,35283,9650
2017/18,35060,9609
2016/17,35210,9599
2015/16,35155,9514
2014/15,35875,9418
2013/14,35393,9150
2012/13,35198,9447
2011/12,35732,8833
2010/11,36912,9022
2009/10,36475,8254",2010/11
"2475Characteristic,Boys,Girls
2018/19,35283,9650
2017/18,35060,9609
2016/17,35210,9599
2015/16,35155,9514
2014/15,35875,9418
2013/14,35393,9150
2012/13,35198,9447
2011/12,35732,8833
2010/11,36912,9022
2009/10,36475,8254",28568
"Pirates of the Caribbean: Dead Man's ChestCharacteristic,North America,Worldwide
""Pirates of the Caribbean: Dead Man's Chest"",423.32,1066.2
""Pirates of the Caribbean: At World's End"",309.42,963.4
""Pirates of the Caribbean: The Curse of the Black Pearl"",305.41,654.3
""Pirates of the Caribbean: On Stranger Tides"",241.07,1045.7
""Pirates of the Caribbean: Dead Men Tell No Tales"",172.56,794.9",Pirates of the Caribbean: Dead Man's Chest
"Pirates of the Caribbean: Dead Men Tell No TalesCharacteristic,North America,Worldwide
""Pirates of the Caribbean: Dead Man's Chest"",423.32,1066.2
""Pirates of the Caribbean: At World's End"",309.42,963.4
""Pirates of the Caribbean: The Curse of the Black Pearl"",305.41,654.3
""Pirates of the Caribbean: On Stranger Tides"",241.07,1045.7
""Pirates of the Caribbean: Dead Men Tell No Tales"",172.56,794.9",Pirates of the Caribbean: The Curse of the Black Pearl
"2019Characteristic,16-19 years,20-39 years,40-59 years,60-74 years
2017,99%,76%,44%,-
2018,99%,80%,52%,-
2019,99%,80%,57%,-
2020,96%,86%,63%,-",16-19 years
"68Characteristic,16-19 years,20-39 years,40-59 years,60-74 years
2020,96%,86%,96%,63%
2019,99%,94%,99%,57%
2018,99%,92%,92%,52%
2017,99%,92%,76%,44%",55
"""The Real World, Keeping up with the Kardashians, The Hills, etc.""Characteristic,Male,Female
""Documentaries / docu-series (e.g., The Real World, Keeping up with the Kardashians, The Hills, etc.)"",18%,26%
""Competition / elimination (e.g., Dancing with the Stars, America's Got Talent, etc.)"",34%,20%
""Makeover / renovation (e.g., Extreme Makeover, What Not to Wear, etc.)"",24%,10%
""Dating (e.g., The Bachelor / Bachelorette, etc.)"",8%,11%
""Hidden camera / amateur content (e.g., Impractical Jokers, America's Funniest Home Videos, etc.)"",17%,8%
""Supernatural (e.g., Ghost Hunters, Paranormal State, etc.)"",18%,17%
""Travel / aspirational (e.g., Lifestyles of the Rich and Famous, MTV Cribs, etc.)"",13%,14%
""Cooking (e.g., MasterChef, Chopped, etc.)"",41%,29%
Other,1","Cooking (e.g., MasterChef, Chopped, etc.)"
"19.2Characteristic,Male,Female
""Documentaries / -docu-series (e.g., The Real World, Keeping up with the Kardashians, The Hills, etc.)"",18%,26%
""Competition / elimination (e.g., Dancing with the Stars, America's Got Talent, etc.)"",34%,20%
""Makeover / renovation (e.g., Extreme Makeover, What Not to Wear, etc.)"",24%,10%
""Dating (e.g., The Bachelor / Bachelorette, etc.)"",11%,8%
""Hidden camera / amateur content (e.g., Impractical Jokers, America's Funniest Home Videos, etc.)"",17%,17%
""Supernatural (e.g., Ghost Hunters, Paranormal State, etc.)"",18%,17%
""Travel / aspirational (e.g., Lifestyles of the rich and Famous, MTV Cribs, etc.)"",13%,14%
""Cooking (e.g., MasterChef, Chopped, etc.)"",41%,29%
Other,16%,18%
""Don't",39
"YesCharacteristic,Male,Female
2019,71.4%,80.2%
2018,70.8%,79.7%
2017,71.3%,71.4%
2016,71.3%,62.4%
2015,70.3%,62.8%
2014,73.1%,64.7%
2013,73.3%,63.7%
2012,73.3%,65.4%
2011,72.6%,66%
2010,71.7%,65.4%
2009,72.6%,69.3%
2008,69.3%,62.1%
2007,66.8%,60.4%
2006,58.5%,58.4%
2005,65.2%,63.3%
2004,54.9%,5",No
"2020Characteristic,Male,Female
2000,61.1%,55%
2001,62.3%,55%
2002,62.4%,53.4%
2003,63.1%,54.9%
2004,63.3%,54.9%
2005,65.2%,57%
2006,58.5%,60.2%
2007,66.8%,62.1%
2008,69.3%,62.3%
2009,70.1%,66.5%
2010,72.6%,65.4%
2011,66%,64.5%
2012,73.3%,65.4%
2013,73.1%,63.7%
2014,73%,63.6%
2015,71.3%,64.7%",2020
"183Characteristic,National sponsoring,Entrance fees and other spectator revenue,Licensing,Other revenue**
2002 Salt Lake City,599,183,34,-
2006 Torino,360,93.43,15.57,342.56
2010 Vancouver,449.6,205.8,213.9,350
2014 Sochi*,350,-,129.37,517.69",599
"161.09Characteristic,National sponsoring,Entrance fees and other spectator revenue,Licensing,Other revenue**
2014 Sochi*,350,129.37,517.69,-
2010 Vancouver,44.2,213.9,449.6,-
2006 Torino,15.57,93.43,342.56,-
2002 Salt Lake City,34,183,599,-",479.5
"42%Characteristic,PET plastics collection rate,PET plastics recycling rate,PET bottles collection rate
France,44%,56%,21%
Germany,76%,36%,94%
UK,38%,22%,53%
Spain,41%,31%,60%
Italy,42%,42%,55%",55
"72Characteristic,PET plastics collection rate,PET plastics recycling rate,PET bottles collection rate
France,44%,56%,21%
Germany,76%,36%,94%
UK,38%,22%,53%
Spain,41%,31%,60%
Italy,42%,42%,55%",52
"155Characteristic,2010,2011,2012,2013,2014,2015,2016,2017
Q4,150,-,165,155,160,-,-,-
Q3,141,-,172,162,-,-,-,-
Q2,140,-,175,160,-,-,-,-
Q1,132,-,164,151,-,-,-,-",165
"28Characteristic,2010,2011,2012,2013,2014,2015,2016,2017
Q4,150,155,160,165,170,171,172,173
Q3,141,158,162,167,172,172,173,176
Q2,140,160,166,175,181,182,186,190
Q1,132,146,151,164,170,170,178,183",15
"31.6Characteristic,Female,Male
Firearms,41.9%,69.4%
Poisoning,31.6%,8.5%
Suffocation,20.3%,16.9%
Other,6.2%,5.2%",8.5
"4.5Characteristic,Female,Male
Firearms,41.9%,69.4%
Poisoning,31.6%,8.5%
Suffocation,20.3%,16.9%
Other,6.2%,5.2%",27.5
"Bill MaherCharacteristic,Very favorable,Somewhat favorable,Somewhat unfavorable,Heard of,no opinion,Never heard of
Jimmy Fallon,29%,8%,10%,1%,5%,1%
Jimmy Kimmel,26%,30%,12%,1%,5%,1%
Stephen Colbert,23%,21%,14%,9%,5%,2%
James Corden,19%,21%,20%,6%,5%,2%
Conan O'Brien,18%,30%,11%,6%,11%,7%
Trevor Noah,16%,7%,8%,8%,37%,2%
Seth Meyers,14%,26%,8%,8%,26%,1%
Bill Maher,12%,17%,16%,8%,27%,2%
John Oliver,12%,14%,5%,6%,21%,4%
Carson Daly,10%,26%,9%,6%,31%,18%",Jimmy Fallon
"40Characteristic,Very favorable,Somewhat favorable,Somewhat unfavorable,Heard of,no opinion,Never heard of
Jimmy Fallon,29%,8%,10%,5%,10%,18%
Jimmy Kimmel,26%,30%,12%,19%,19%,5%
Stephen Colbert,23%,21%,14%,19%,9%,13%
James Corden,21%,20%,11%,5%,29%,23%
Conan O'Brien,18%,30%,11%,6%,23%,7%
Trevor Noah,16%,14%,8%,7%,18%,37%
Seth Meyers,14%,26%,8%,5%,26%,17%
Bill Maher,12%,17%,8%,27%,16%,20%
John Oliver,12%,14%,5%,21%,41%,6%
Carson Daly,10%,26%,9%,31%,18%,18%",19
"113702Characteristic,Boys,Girls
2018/19,113702,99750
2017/18,113313,96904
2016/17,111842,93473
2015/16,109522,88050
2014/15,108450,84785
2013/14,106720,81969
2012/13,101687,77258
2011/12,100641,74993
2010/11,95683,74927
2009/10,90670,68768",99750
"32145Characteristic,Boys,Girls
2018/19,113702,99750
2017/18,113313,96904
2016/17,111842,93473
2015/16,109522,88050
2014/15,108450,84785
2013/14,106720,81969
2012/13,101687,77258
2011/12,100641,74993
2010/11,95683,74927
2009/10,90670,68768",18019
"85Characteristic,2013,2016
Air,85%,65%
Trucking,-,10%
Ocean,-,5%",85
"50Characteristic,2013,2016
Air,85%,65%
Trucking,10%,10%
Ocean,5%,25%",60
"12.2Characteristic,Consumables,Seasonal,Home products,Apparel
2020,76.8%,6.5%,12.1%,4.6%
2019,78%,5.8%,11.7%,4.5%
2018,77.5%,5.9%,11.9%,4.7%
2017,76.4%,6%,12.1%,5%
2016,76.4%,6.2%,12.2%,5.2%
2015,75.9%,6.3%,12.4%,5.4%
2014,75.7%,6.4%,12.4%,5.5%
2013,75.2%,6.4%,12.9%,5.5%
2012,73.9%,6.6%,13.6%,5.9%
2011,73.2%,6.8%,13.8%,6.2%
2010",6.2
"4.3Characteristic,Consumables,Seasonal,Home products,Apparel
2020,76.8%,6.5%,12.1%,4.6%
2019,78%,5.8%,11.7%,4.5%
2018,77.5%,5.9%,11.9%,4.7%
2017,76.7%,6%,12.1%,5%
2016,76.4%,6.2%,12.2%,5.2%
2015,75.9%,6.3%,12.4%,5.4%
2014,75.7%,6.4%,12.4%,5.5%
2013,75.2%,6.4%,12.9%,5.5%
2012,73.9%,6.6%,13.6%,5.9%
2011,73.2%,6.8%,13.8%,6.2%
2010,",5.45
"69Characteristic,Obama,Romney
White (non-Hispanic),37%,59%
Nonwhite,79%,15%
Black,90%,5%
Hispanic,69%,25%",69
"45Characteristic,Obama,Romney
White (non-Hispanic),37%,59%
Nonwhite,79%,15%
Black,90%,5%
Hispanic,69%,25%",85
"89Characteristic,Offline sales,Online sales
2013,93.2%,6.8%
2018*,89%,11%",11
"92.6Characteristic,Offline sales,Online sales
2013,93.2%,6.8%
2018*,89%,11%",91.1
"19.81Characteristic,0-14 years,15-64 years,65 years and older
2019,19.57%,64.44%,15.99%
2018,19.65%,64.69%,15.65%
2017,19.72%,64.95%,15.33%
2016,19.81%,65.19%,15%
2015,19.97%,65.38%,14.65%
2014,20.1%,65.6%,14.3%
2013,20.26%,65.8%,13.94%
2012,20.4%,66%,13.59%
2011,20.5%,66.21%,13.29%
2010,20.45%,66.45%,13.05%
20",19.81
"5.11Characteristic,0-14 years,15-64 years,65 years and older
2019,19.57%,64.44%,15.99%
2018,19.65%,64.69%,15.65%
2017,19.72%,64.95%,15.33%
2016,19.81%,65.19%,15%
2015,19.97%,65.38%,14.65%
2014,20.1%,65.6%,14.3%
2013,20.26%,65.8%,13.94%
2012,20.4%,66%,13.59%
2011,20.5%,66.21%,13.29%
2010,20.45%,66.45%,13.05%
200",45.83
"33Characteristic,Domestic market,Total market
2019,23,28
2018,30,25
2017,30,24
2016,27,33
2015,30,33
2014,24,24
2013,30,36
2012,32,25
2011,27,32",30
"80Characteristic,Domestic market,Total market
2019,23,28
2018,30,25
2017,30,24
2016,27,33
2015,33,30
2014,24,24
2013,30,36
2012,32,25
2011,27,32",66
"30.1Characteristic,Men,Women
1998,25.1,26.7
1999,25.1,26.9
2000,25.1,26.8
2001,25.1,26.9
2002,25.3,26.9
2003,25.3,26.9
2004,25.3,27.1
2005,25.3,27.1
2006,25.5,27.5
2007,25.6,27.6
2008,25.9,27.6
2009,25.9,28.1
2010,26.1,28.2
2011,26.4,28.6
2012,26.6,29.0
2013,26.6,29.2
2014,2",28.3
"24.2Characteristic,Men,Women
2019,30.1,-
2018,28.3,-
2017,29.9,28.1
2016,29.2,27.9
2015,29.3,27.1
2014,29.2,-
2013,29.0,26.6
2012,28.6,26.6
2011,28.4,26.4
2010,28.2,26.1
2009,28.1,25.9
2008,27.6,25.9
2007,27.5,25.6
2006,27.5,25.5
2005,27.1,25.3
2004,27.4,25.3
2003,27.1,25.3
200",10
"63Characteristic,Minimum strikes,Maximum strikes
2020*,12,12
2019,63,63
2018,45,45
2017,35,35
2016,14,14
2015,11,11
2014,3,3
2013,1,1
2012,2,2
2011,1,4",63
"59Characteristic,Minimum strikes,Maximum strikes
2020*,12,12
2019,63,63
2018,45,45
2017,35,35
2016,14,14
2015,11,11
2014,3,3
2013,1,1
2012,2,2
2011,1,4",28
"-59Characteristic,Cloud traffic,Non-cloud traffic
2019*,90%,10%
2018*,88%,12%
2017*,86%,14%
2016*,85%,15%
2015*,83%,17%
2014,81%,19%",62
"4Characteristic,Cloud traffic,Non-cloud traffic
2019*,90%,10%
2018*,88%,12%
2017*,86%,14%
2016*,85%,15%
2015*,83%,17%
2014,81%,19%",72
"[2014, 2015]Characteristic,Domestic market,Total market
2018,315,280
2017,347,311
2016,289,295
2015,305,300
2014,275,327
2013,329,329
2012,337,337
2011,361,361","[2011, 2012]"
"88Characteristic,Domestic market,Total market
2018,315,280
2017,311,347
2016,289,295
2015,305,300
2014,275,327
2013,329,329
2012,337,337
2011,361,361",35
"Below 100 SEKCharacteristic,2010,2012,2014,2016,2018,2020
Below 100 SEK,59%,55%,41%,26%,20%,12%
100-500 SEK,22%,19%,13%,9%,8%,5%
Above 500 SEK,11%,10%,7%,4%,5%,3%",2018
"48Characteristic,2010,2012,2014,2016,2018,2020
Below 100 SEK,59%,55%,41%,26%,20%,12%
100-500 SEK,22%,19%,13%,9%,8%,5%
Above 500 SEK,11%,10%,7%,4%,5%,3%",47
"3.7Characteristic,Apparel,Socks,Arms/legs sleeves
2010,4.8,1.2,2.3
2009,3.7,0.51,1.2
2008,2.7,0.17,0.27",3.7
"2010Characteristic,Apparel,Socks,Arms/legs sleeves
2010,4.8,1.2,2.3
2009,3.7,0.51,1.2
2008,2.7,0.17,0.27",2010
"FemaleCharacteristic,Male,Female
2015,27%,31%
2012,19%,23%
2008,15%,13%
2003,16%,15%",Female
"14Characteristic,Male,Female
2015,27%,31%
2012,19%,23%
2008,15%,13%
2003,16%,15%",14
"3.72Characteristic,Travel Solutions,Hospitality Solutions
2019,3.72,0.29
2020,1.18,0.17",3.72
"1.27Characteristic,Travel Solutions,Hospitality Solutions
2020,1.18,0.17
2019,3.72,0.29",0.46
"CinematographyCharacteristic,Male,Female
""Cinematography"",100%,0%
""Film Editing"",80%,20%
""Writing (adapted screenplay)"",71%,29%
""Best Picture"",70%,30%
""Best Director"",60%,40%
""Writing (original screenplay)"",60%,40%
""Documentary (short subject)"",60%,40%
""Documentary (feature)"",46%,54%",Cinematography
"53Characteristic,Male,Female
""Cinematography"",100%,0%
Film Editing,80%,20%
""Writing (adapted screenplay)"",71%,29%
Best Picture,70%,30%
Best Director,60%,40%
""Writing (original screenplay)"",60%,40%
""Documentary (short subject)"",60%,40%
Documentary (feature),46%,54%",50
"Joe BidenCharacteristic,Joe Biden,Donald Trump
Denmark,80%,6%
Germany,71%,11%
Spain,69%,16%
Sweden,65%,18%
France,64%,14%
Britain,61%,13%
Italy,58%,20%",80
"38Characteristic,Joe Biden,Donald Trump
Denmark,80%,6%
Germany,71%,11%
Spain,69%,16%
Sweden,65%,18%
France,64%,14%
Britain,61%,13%
Italy,58%,20%",38
"3.9Characteristic,LinkedIn,Facebook,Twitter
United States,2.5,1.3,1.3
Canada,3.0,2.0,1.2
Australia,3.4,1.4,1.4
China,3.0,1.3,1.2
India,3.9,1.5,1.3
United Kingdom,2.7,1.1,1.4",3.9
"6.9Characteristic,LinkedIn,Facebook,Twitter
United States,2.5,1.3,1.3
Canada,3.0,2.0,1.2
Australia,3.4,1.4,1.4
China,3.0,1.3,1.2
India,3.9,1.5,1.3
United Kingdom,2.7,1.1,1.4",6.7
"1481Characteristic,Over-The-Counter (OTC),Fixed odds betting terminals (FOBTs)
2011,1481,1301.7
2010,1461.3,1181.9
2009,1658,1070.4",1461.3
"3227.2Characteristic,Over-The-Counter (OTC),Fixed odds betting terminals (FOBTs)
2011,1481,1301.7
2010,1461.3,1181.9
2009,1658,1070.4",2372.1
"MaleCharacteristic,Male,Female
""Purchases made online"",41%,40%
""Shopping on Amazon 6+ times per month"",53%,45%
""Number of Amazon purchases has increased year-over-year"",60%,52%",Male
"10Characteristic,Male,Female
Purchases made online,41%,40%
""Shopping on Amazon 6+ times per month"",53%,45%
""Number of Amazon purchases has increased year-over-year"",60%,52%",1
"63.47Characteristic,0-14 years,15-64 years,65 years and older
2019,28.88%,63.47%,7.65%
2018,28.46%,64.15%,7.39%
2017,27.91%,64.95%,7.14%
2016,27.31%,65.77%,6.92%
2015,26.7%,66.54%,6.76%
2014,26.04%,67.2%,6.76%
2013,25.41%,67.81%,6.78%
2012,24.86%,68.34%,6.81%
2011,24.41%,68.78%,6.81%
2010,24.05%,69.13%,6.81%
20",7.65
"39.2Characteristic,0-14 years,15-64 years,65 years and older
2019,28.88%,63.47%,7.65%
2018,28.46%,64.15%,7.39%
2017,27.91%,64.95%,7.14%
2016,27.31%,65.77%,6.92%
2015,26.7%,66.54%,6.76%
2014,26.04%,67.2%,6.76%
2013,25.41%,67.81%,6.78%
2012,24.86%,68.34%,6.81%
2011,24.41%,68.78%,6.81%
2010,24.05%,69.13%,6.81%
200",5.66
"23.74Characteristic,Agriculture,Industry,Services
2019,6.1%,23.74%,55.49%
2018,5.89%,24.52%,54.93%
2017,5.6%,23.91%,55.78%
2016,6.37%,23.16%,55.5%
2015,6.24%,22.54%,56.26%
2014,5.95%,22.06%,56.88%
2013,6.84%,22.23%,56.25%
2012,6.14%,21.54%,56.87%
2011,6.76%,22.13%,55.88%
2010,6.8%,22.39%,55.57%
2009,7.08%,22.84%,5",54.93
"86.87Characteristic,Agriculture,Industry,Services
2019,6.1%,23.74%,55.49%
2018,5.89%,24.52%,54.93%
2017,5.6%,23.91%,55.78%
2016,6.37%,23.16%,55.5%
2015,6.24%,22.54%,56.26%
2014,5.95%,22.06%,56.88%
2013,6.84%,22.23%,56.25%
2012,6.14%,21.54%,56.87%
2011,6.76%,22.13%,55.88%
2010,6.8%,22.39%,55.57%
2009,7.08%,22.84%,5",11.99
"MenCharacteristic,Men,Women
75 years and over,11.7,5.7
65-74 years,20.9,9.3
55-64 years,19.5,10.0
45-54 years,17.4,9.6
35-44 years,13.4,9.0
25-34 years,12.8,8.3
16-24 years,12.3,7.1",Men
"20.4Characteristic,Men,Women
75 years and over,11.7,5.7
65-74 years,20.9,9.3
55-64 years,19.5,10.0
45-54 years,17.4,9.6
35-44 years,13.4,9.0
25-34 years,12.8,8.3
16-24 years,12.3,7.1",19.4
"53Characteristic,Male,Female
More,41%,49%
No change,53%,43%
Less,2%,2%
""Don't know/no opinion"",4%,6%",49
"LessCharacteristic,Male,Female
More,41%,49%
No change,53%,43%
Less,2%,2%
Don't know/no opinion,4%,6%",Less
"7Characteristic,Men,Women
75 years and over,6%,6%
65-74 years,9%,11%
55-64 years,15%,15%
45-54 years,20%,12%
35-44 years,21%,16%
25-34 years,28%,22%
16-24 years,23%,19%",16
"6Characteristic,Men,Women
75 years and over,6%,6%
65-74 years,9%,11%
55-64 years,15%,15%
45-54 years,20%,12%
35-44 years,21%,16%
25-34 years,28%,22%
16-24 years,23%,19%",28
"80 to 89 yearsCharacteristic,Male,Female
9 years and younger,1.3,1.2
10 to 19 years,1.8,2.2
20 to 29 years,12.9,13.4
30 to 39 years,12.8,8.7
40 to 49 years,12.0,6.2
50 to 59 years,13.2,8.1
60 to 69 years,9.4,5.0
70 to 79 years,6.9,4.4
80 to 89 years,7.6,5.1
90 years and older,8.3,6.9",20 to 29 years
"90 years and olderCharacteristic,Male,Female
9 years and younger,1.3,1.2
10 to 19 years,1.8,2.2
20 to 29 years,12.9,13.4
30 to 39 years,12.8,8.7
40 to 49 years,12.0,6.2
50 to 59 years,13.2,8.1
60 to 69 years,9.4,5.0
70 to 79 years,6.9,4.4
80 to 89 years,7.6,5.1
90 years and older,8.3,6.9",9 years and younger
"73.3Characteristic,Male,Female
2002,73.3,20.1
2012,54.7,16.6
2016,53.0,17.1",73.3
"47.5Characteristic,Male,Female
2016,53.0,17.1
2012,54.7,16.6
2002,73.3,20.1",53.8
"Media workersCharacteristic,Media workers,Motive unconfirmed,Motive confirmed
2021*,3,0,5
2020,0,32,17
2019,10,25,26
2018,8,10,22
2017,2,8,47
2016,2,28,51
2015,3,24,73
2014,4,11,62
2013,2,4,74
2012,2,0,30
2011,5,2,49
2010,4,32,44
2009,3,3,76
2008,24,20,42
2007,17,22,57
2006,120,29,50
2005,11,11,60
2004,3,12,42
2003,7,",Media workers
"73Characteristic,Media workers,Motive unconfirmed,Motive confirmed
201*,3,32,5
2020,0,0,32
2019,10,25,26
2018,8,10,56
2017,2,20,47
2016,2,28,51
2015,3,24,73
2014,4,11,62
2013,2,24,74
2012,2,30,0
2011,5,0,49
2010,4,32,44
2009,3,32,76
2008,24,0,42
2007,17,20,22
2006,120,29,57
2005,11,50,60
2004,12,0,42
2003,7",72
"12.82Characteristic,Male,Female
16 to 17,5.0,6.2
18 to 21,9.21,9.06
22 to 29,12.99,12.82
30 to 39,16.25,16.13
40 to 49,16.29,18.43
50 to 59,17.04,14.77
60 and over,14.45,12.53",12.99
"19.06Characteristic,Male,Female
16 to 17,5.0,6.2
18 to 21,9.21,9.06
22 to 29,12.99,12.82
30 to 39,16.25,16.13
40 to 49,18.43,16.29
50 to 59,17.04,14.77
60 and over,14.45,12.53",18.27
"""No""Characteristic,Yes,No
16 to 24 years,27%,73%
25 to 34 years,38%,62%
35 to 44 years,35%,65%
45 to 54 years,30%,70%
55 years and over,24%,76%",No
"2Characteristic,Yes,No
16 to 24 years,27%,73%
25 to 34 years,38%,62%
35 to 44 years,35%,65%
45 to 54 years,30%,70%
55 years and over,24%,76%",1
"BlueCharacteristic,0-14,15-64,65+
Female,16.65,66.45,9.21
Male,17.06,63.9,8.63",gray
"46.95Characteristic,0-14,15-64,65+
Female,16.65,66.45,9.21
Male,17.06,63.9,8.63",2.72
"0.1217Characteristic,2017,2018,2019
Kidney,49.2,47.0,43.9
Liver,18.5,20.7,17.2
Lung,13.3,13.3,11.4
Heart,7.4,7.4,7.6
Pancreas,2.3,2.3,1.7
Small bowel,0.0,0.0,0.1",43.9
"30.7Characteristic,2017,2018,2019
Kidney,49.2,47.0,43.9
Liver,18.5,20.7,17.2
Lung,13.3,13.3,11.4
Heart,7.4,7.4,7.6
Pancreas,2.3,2.3,1.7
Small bowel,0.0,0.0,0.1",38
"2Characteristic,Total,Male,Female
Not sure,8%,7%,8%
Not at all common,2%,3%,2%
Not very common,16%,22%,11%
Somewhat common,40%,43%,36%
Very common,34%,24%,43%",5
"8.5Characteristic,Total,Male,Female
Very common,34%,24%,43%
Somewhat common,40%,43%,36%
Not very common,16%,22%,11%
Not at all common,2%,3%,2%
Not sure,8%,7%,8%",5
"21.4Characteristic,2006,2011
Europe,14.6,15.6
North America,7.5,7.9
Asia/Pacific,4.8,6.6
Central & South America,1.2,1.3
Middle East,0.7,0.8
Africa,0.5,0.5",1
"Middle EastCharacteristic,2006,2011
Europe,14.6,15.6
North America,7.5,7.9
""Asia/Pacific"",4.8,6.6
""Central & South America"",1.2,1.3
""Middle East"",0.7,0.8
Africa,0.5,0.5",Africa
"18/19Characteristic,Stranger,Acquaintance
18/19,614,459
17/18,542,629
16/17,589,548
15/16,559,604
14/15,671,660
13/14,598,664
12/13,778,777
11/12,895,832
10/11,770,756
09/10,852,732
08/09,816,721
07/08,745,852
06/07,950,896
05/06,933,879
04/05,866,893
03/04,934,941
02/03,1000,991
01/",18/19
"160Characteristic,Stranger,Acquaintance
18/19,614,459
17/18,542,629
16/17,559,548
15/16,559,604
14/15,571,660
13/14,598,671
12/13,664,598
11/12,778,832
10/11,895,756
09/10,770,732
08/09,852,721
07/08,745,816
06/07,950,896
05/06,933,879
04/05,866,893
03/04,1000,934
02/03,991,941
01/02",991
"80.7Characteristic,female,male
2018,86.3,80.7
2017,86.1,80.6
2016,86.3,80.5
2015,85.7,80.1
2014,86.2,80.4
2013,86.1,80.2
2012,85.5,79.5
2011,85.6,79.5
2010,84.7,78.7
2009,84.6,78.5
2008,84.3,78.2",80.7
"6.5Characteristic,female,male
2018,86.3,80.7
2017,86.1,80.6
2016,86.3,80.5
2015,85.7,80.1
2014,86.2,80.4
2013,86.1,80.2
2012,85.5,79.5
2011,85.6,79.5
2010,84.7,78.7
2009,84.6,78.5
2008,84.3,78.2",2
"5Characteristic,Very useful,Useful
""Find and book hotels etc."",22%,31%
""Manage parking lots / car services"",27%,13%
Internet TV,21%,7%
""Voice to email technology"",7%,17%
Twitter / social networks,5%,13%",5
"28Characteristic,Very useful,Useful
Find and book hotels etc.,22%,31%
""Manage parking lots / car services"",27%,13%
Internet TV,21%,7%
Voice to email technology,7%,17%
""Twitter / social networks"",5%,13%",28
"56Characteristic,2014,2016
Instagram,20%,30%
Snapchat,17%,30%",47
"InstagramCharacteristic,2014,2016
Instagram,20%,30%
Snapchat,17%,30%",Snapchat
"BlueCharacteristic,How consumers can pay,How providers can receive payments
Cash,41%,38%
Account,15%,46%
Mobile,44%,23%
PayPal,26%,31%
Debit/credit card,79%,23%",light blue
"CashCharacteristic,How consumers can pay,How providers can receive payments
Cash,41%,38%
Account,15%,46%
Mobile,44%,23%
PayPal,26%,31%
Debit/credit card,79%,23%",Cash
"66.8Characteristic,Non-food products,Food products
2014,66.8%,33.2%
2013,63.5%,36.5%
2012,62%,38%
2011,59.3%,40.7%
2010,58.1%,41.9%
2009,57.6%,42.4%",66.8
"124.3Characteristic,Non-food products,Food products
2014,66.8%,33.2%
2013,63.5%,36.5%
2012,62%,38%
2011,59.3%,40.7%
2010,58.1%,41.9%
2009,57.6%,42.4%",124.4
"97Characteristic,Number of properties
North America (and Caribbean),590
Asia Pacific,601
Europe,288
""Africa and the Middle East"",158
Latin America (and Mexico),86
85,85
79,79",317
"92Characteristic,North America (and Caribbean),Asia Pacific,Europe,Africa and the Middle East,Latin America (and Mexico)
2015,590,622,317,174,97
2014,601,288,163,86,84
2013,590,263,158,85,79",54
"1.16Characteristic,Q4 '12,Q4 '13
Facebook,1.16,1.24
Pinterest,0.665,0.74
Twitter,0.43,0.65
Reddit,0.27,0.57",0.27
"0.5Characteristic,Q4 '12,Q4 '13
Facebook,1.16,1.24
Pinterest,0.66,0.74
Twitter,0.43,0.65
Reddit,0.27,0.57",0.89
"41Characteristic,Inbound,Domestic,Outbound
2014,32%,34%,32%
2012-13,31%,47%,38%
2010-11,28%,35%,26%
2008-09,20%,13%,41%",41
"34.5Characteristic,Inbound,Domestic,Outbound
2008-09,20%,13%,41%
2010-11,28%,26%,35%
2012-13,31%,47%,38%
2014,32%,34%,32%",32.66
"47.4Characteristic,30-39 years,40-49 years,50-64 years,Over 65 years
Medium (100-499 employees),7.5%,27.3%,51%,14.2%
Small (1-99 employees),14.7%,26.1%,47.4%,11.8%",11.8
"40-49 yearsCharacteristic,30-39 years,40-49 years,50-64 years,Over 65 years
Small (1-99 employees),14.7%,26.1%,47.4%,11.8%
Medium (100-499 employees),7.5%,27.3%,51%,14.2%",50-64 years
"75Characteristic,Urban,Rural
YouTube,72%,81%
Facebook,80%,75%
Google+,40%,35%
Twitter,46%,50%
WhatsApp,61%,27%
LinkedIn,34%,34%
Pinterest,31%,38%
Instagram,43%,33%
Snapchat,32%,22%
Skype,42%,31%",80
"15Characteristic,Urban,Rural
YouTube,72%,81%
Facebook,75%,80%
Google+,40%,35%
Twitter,46%,50%
WhatsApp,61%,27%
Linkedin,34%,-
Pinterest,31%,38%
Instagram,43%,33%
Snapchat,32%,22%
Skype,42%,31%",53
"2626Characteristic,New cars,Used cars
2013,3231,2734
2014,2968,2787
2015,2993,2877
2016,2626,3280
2017,2343,3538
2018,2314,3871
2019,2225,4186",3280
"2015Characteristic,New cars,Used cars
2019,2225,4186
2018,2314,3871
2017,2343,3538
2016,2626,3280
2015,2877,2993
2014,2787,2968
2013,3231,2734",2015
"Beauty and cosmeticsCharacteristic,My spending has increased,My spending has decreased
Food,47%,-
Cleaning products,45%,-
Health and medicines,25%,-
Sport items,38%,-
Office and stationery items,30%,-
Beauty and cosmetics,28%,-",Beauty and cosmetics
"3Characteristic,My spending has increased,'My spending has decreased'
Beauty and cosmetics,28%,-
Office and stationery items,30%,-
Sport items,38%,-
Health and medicines,25%,-
Cleaning products,45%,-
Food,47%,-",2
"FemaleCharacteristic,Male,Female
Current,17.2%,19.9%
Binge,10.4%,11.8%
Heavy,2.1%,2.3%",Binge
"11.01Characteristic,Male,Female
Current,17.2%,19.9%
Binge,10.4%,11.8%
Heavy,2.1%,2.3%",9.9
"WomenCharacteristic,Women,Men
""It's natural. I understand that homosexuals want to find love."",25%,13%
I don't discriminate against them, nor do I fear them.,62%,59%
Unacceptable,14%,28%",Women
"UnacceptableCharacteristic,Women,Men
It's natural. I understand that homosexuals want to find love.,25%,13%
I don't discriminate against them, nor do I fear them.,62%,59%
Unacceptable,14%,28%","I don't discriminate against them, nor do I fear them."
"49Characteristic,""Worried about personal health"",""Worried about health of people you live with""
Very worried,28%,37%
Somewhat worried,49%,38%
Not very worried,19%,9%
Not worried at all,4%,3%",49
"Somewhat worriedCharacteristic,Worried about personal health,Worried about health of people you live with
Very worried,28%,37%
Somewhat worried,49%,38%
Not very worried,19%,9%
Not worried at all,4%,3%",Not worried at all
"BlueCharacteristic,Not Hispanic or Latino white,Not Hispanic or Latino other,Hispanic or Latino
Anorexia nervosa*,12,-,0
Bulimia Nervosa,41,12,0
One of more eating disorders,53,12,0",light blue
"One of more eating disordersCharacteristic,Not Hispanic or Latino white,Not Hispanic or Latino other,Hispanic or Latino
Anorexia nervosa*,12,-,0
Bulimia Nervosa,41,12,-,0
One of more eating disorders,53,12,4,-",Bulimia Nervosa
"PneumoniaCharacteristic,Deaths among children aged 1-59 months (53%),Neonatal deaths (47%)
Pneumonia,12%,3%
Preterm birth complications,2%,16%
Intrapartum-related events,1%,11%
Sepsis or meningitis,2%,7%
Congenital,4%,5%
Other,12%,3%
AIDS,1%,-
Diarrhoea,8%,-0.3%
Tetanus,1%,5%
Malaria,5%,6%
Injury,1%,-
Measles,2%,-",Preterm birth complications
"34Characteristic,Deaths among children aged 1-59 months (53%),Neonatal deaths (47%)
Pneumonia,12%,3%
Preterm birth complications,2%,16%
Intrapartum-related events,1%,11%
Sepsis or meningitis,2%,7%
Congenital,4%,5%
Other,12%,3%
AIDS,1%,8%
Diarrhoea,8%,0.3%
Tetanus,1%,5%
Malaria,5%,6%
Injury,6%,1%
Measles,2%,2%",12
"2015Characteristic,Multiple unit-linked contracts - unit-linked products*,Multiple unit-linked contracts - euro products*,Euro-denominated contracts
2019,23%,54%,24%
2018,21%,53%,26%
2017,22%,51%,28%
2016,19%,51%,29%
2015,18%,51%,31%
2014,17%,50%,33%
2011,15%,47%,38%
2008,16%,39%,45%
2005,19%,25%,56%",2019
"79Characteristic,Multiple unit-linked contracts - unit-linked products*,Multiple unit-linked contracts - euro products*,Euro-denominated contracts
2019,23%,54%,24%
2018,21%,53%,26%
2017,22%,51%,28%
2016,19%,51%,29%
2015,18%,51%,31%
2014,17%,50%,33%
2011,15%,47%,38%
2008,16%,39%,45%
2005,19%,25%,56%",74
"74.8Characteristic,Red 1,Red 2
2016-17,68.7%,62.5%
2015-16,72.5%,67.3%
2014-15,71.9%,69.1%
2013-14,75.6%,74.8%
2012-13,74%,75.6%",75.6
"1.8Characteristic,Red 1,Red 2
2016-17,68.7%,62.5%
2015-16,72.5%,67.3%
2014-15,71.9%,69.1%
2013-14,75.6%,74.8%
2012-13,74%,75.6%",1.6
"4.8Characteristic,Men,Women
2020,4.5%,4.7%
2019,3.9%,3.4%
2018,3.6%,4.1%
2017,4%,4.3%
2016,3.9%,4.4%
2015,4.4%,4.8%
2014,4.8%,5.2%
2013,5.7%,6.8%
2012,6.1%,6%
2011,5.7%,6.2%
2010,6.9%,5.1%",4.4
"5.6Characteristic,Men,Women
2020,4.5%,4.7%
2019,3.9%,3.4%
2018,3.6%,4.1%
2017,4%,4.3%
2016,3.9%,4.4%
2015,4.4%,4.8%
2014,4.8%,5.2%
2013,5.7%,5.8%
2012,6.1%,6%
2011,5.7%,6.2%
2010,6.9%,5.1%",4.2
"GermanyCharacteristic,Germany,Poland,Czechia,Slovakia,Hungary,Ust Luga*
Jan'18,0.52,0.07,0.11,0.06,0.0,0.42
Feb'18,0.68,0.09,0.11,0.08,0.09,0.44
Mar'18,0.52,0.09,0.08,0.09,0.0,0.43
Apr'18,0.54,0.05,0.09,0.08,0.09,0.45
May'18,0.52,0.07,0.1,0.08,0.09,0.4
Jun'18,0.51,0.13,0.09,0.12,0.09,0.39
Jul'18,0.47,0.09,0.08,0.09,0.0,",Hungary
"0.86Characteristic,Germany,Poland,Czechia,Slovakia,Hungary,Ust Luga*
Dec'18,0.32,0.08,0.13,0.09,0.52,0.5
Nov'18,0.34,0.08,0.12,0.09,0.66,0.68
Oct'18,0.38,0.08,0.11,0.1,0.66,0.6
Sep'18,0.43,0.1,0.09,0.09,0.51,0.5
Aug'18,0.42,0.32,0.1,0.09,0.54,0.5
Jul'18,0.39,0.26,0.12,0.09,0.13,0.47
Jun'18,0.41,0.3,0.1,0.09,0.07,0",1.19
"MarriedCharacteristic,Women,Men
Never married,170,252
Married,524,633
[of them] in an unregistered marriage,69,84
Widowed,186,38
Divorced or separated,120,77",Married
"197Characteristic,Women,Men
Never married,170,252
Married,524,633
[of them] in an unregistered marriage,69,84
Widowed,186,38
Divorced or separated,120,77",306
"63000Characteristic,Total,United States
2020,61000,-
2019,63000,-
2018,68000,-
2017,67200,-
2016,67800,-",7000
"17000Characteristic,Total,United States
2020,61000,-
2019,63000,8000
2018,68000,8000
2017,67200,8000
2016,67800,7800",7760
"FemaleCharacteristic,Female,Male
2019,5.83,5.9
2018,5.73,5.83
2017,5.67,5.77
2016,5.6,5.7
2015,5.54,5.64
2014,5.49,5.58
2013,5.44,5.51
2012,5.39,5.45
2011,5.35,5.39
2010,5.33,5.27
2009,5.26,5.27",Female
"0.85Characteristic,Female,Male
2019,5.83,5.9
2018,5.73,5.83
2017,5.67,5.77
2016,5.6,5.7
2015,5.54,5.64
2014,5.49,5.58
2013,5.44,5.51
2012,5.39,5.45
2011,5.35,5.39
2010,5.33,5.31
2009,5.27,5.22",0.63
"65Characteristic,Male,Female
Leaders (Directors and above),71%,29%
Tech,76%,24%
Non-tech,49%,51%",100
"Leaders (Directors and above)Characteristic,Male,Female
Leaders (Directors and above),71%,29%
Tech,76%,24%
Non-tech,49%,51%",Tech
"BlueCharacteristic,Women,Men
Production,transportation,and material moving,18.5%
Natural resources,construction,and maintenance,17.1%
Office and administrative support,18.6%,6.4%
Sales and related,8.4%,8.5%
Service,16.5%,12.1%
Professional and related,20.2%,31%
""Management, business and financial operations"",18.2%,17.1%",light blue
"Production, transportation, and material movingCharacteristic,Women,Men
""Management, business and financial operations"",18.2%,17.1%
Professional and related,31%,20.2%
Service,16.5%,12.1%
Sales and related,8.4%,8.5%
""Office and administrative support"",18.6%,6.4%
Natural resources, construction, and maintenance,1%,17.1%
Production, transportation, and material moving,6.3%,18.5%","Natural resources, construction, and maintenance"
"[2004/05, 2005/06, 2006/07, 2007/08, 2008/09, 2009/10, 2010/11, 2011/12, 2012/13, 2013/14, 2014/15, 2015/16, 2016/17, 2017/18, 2018/19, 2019/20]",Year
"3Characteristic,Undergraduate,Graduate,Non-degree
2019/20,-,-,-
2018/19,-,-,-
2017/18,-,-,-
2016/17,-,-,-
2015/16,-,-,-
2014/15,-,-,-
2013/14,-,-,-
2012/13,625512.5,-,-
2011/12,600556.0,-,-
2010/11,578598.0,-,-
2009/10,568238.5,-,-
2008/09,554070.0,-,-
2007/08,590294.0,-,-
2006/07,530174.0,-,-
2005/06,591438.0,-,-
2004/05,561456.",7
"-3Characteristic,Sales value,Number of orders,Value of shopping basket
Toys,34%,13%,18%
Baby,10%,13%,-3%",-3
"45Characteristic,Sales value,Number of orders,Value of shopping basket
Toys,34%,13%,18%
Baby,10%,13%,-3%",44
"0.1Characteristic,Male,Female
Anorexia nervosa*,0.1,0.1
Bulimia Nervosa,0.1,0.1
One of more eating disorders,0.1,0.1",0.1
"0.1Characteristic,Male,Female
""Anorexia nervosa*"",0.1,0.1
""Bulimia Nervosa"",0.1,0.1
""One of more eating disorders"",0.1,0.1",0.05
"SpainCountry,No, it is not necessary,Yes, it is necessary,Don't know / refused
United States,46%,53%,2%,-
Britain,78%,20%,2%,-
France,85%,15%,0%,-
Germany,66%,33%,1%,-
Spain,80%,19%,1%,-",France
"GermanyCountry,No, it is not necessary,Yes, it is necessary,Don't know / refused
United States,46%,53%,2%,-
Britain,78%,20%,-,-
France,85%,15%,0%,-
Germany,66%,33%,1%,-
Spain,80%,19%,1%,-",France
"NoCharacteristic,Excessive, they are spreading social concern,In this context, the appropriate behavior,They are downplaying the situation
Men,56%,33%,11%
Women,48%,37%,15%",No
"MenCharacteristic,Excessive,they are spreading social concern,In this context,the appropriate behavior,They are downplaying the situation
Men,56%,33%,11%
Women,48%,37%,15%",They are downplaying the situation
"BlueCharacteristic,Search ad clicks,Search ad conversion rate
Medical supplies,5%,24%
Pharmaceuticals,34%,47%",Navy blue
"79Characteristic,Search ad clicks,Search ad conversion rate
Medical supplies,5%,24%
Pharmaceuticals,34%,47%",110
"January 2009Characteristic,Have become more,Consistent,Have become weaker
December 2010,36%,33%,31%
January 2010,36%,24%,40%
January 2009,33%,43%,24%
November 2007,42%,34%,24%",November 2007
"18Characteristic,Have become more,Consistent,Have become weaker
December 2010,36%,33%,31%
January 2010,36%,24%,40%
January 2009,43%,24%,33%
November 2007,42%,34%,24%",11
"Dark blueCharacteristic,Oppose,Favor
Total Millennials (ages 18-33),27%,68%
Total Gen Xers (ages 34-49),38%,55%
Total Boomers (ages 50-68),45%,48%
Total Silents (ages 69-86),50%,38%",Dark blue
"Total Millenials (ages 18-33)Characteristic,Oppose,Favor
Total Millennials (ages 18-33),27%,68%
Total Gen Xers (ages 34-49),38%,55%
Total Boomers (ages 50-68),45%,48%
Total Silents (ages 69-86),50%,38%",Total Millennials (ages 18-33)
"5Characteristic,Better,About the same,Worse
""Lending/Investment standards"",7%,38%,15%
""Keeping information and money safe"",8%,38%,18%
Know-how of own industry workings,14%,37%,17%
Moral standards,14%,32%,12%
Cost of capital,16%,36%,11%
""Generating social returns on investment"",16%,34%,10%
""Generating financial returns on investments"",17%,41%,7%
Accessibility,21%,36%,10%
Speed,23%,33%,10%
Flexibility,26%,33%,9%
Willingness to take risks,29%,29%,10%",11
"36Characteristic,Better,About the same,Worse
Lending/Investment standards,7%,38%,15%
Keeping information and money safe,8%,38%,18%
Know-how of own industry workings,14%,37%,17%
Moral standards,14%,32%,12%
Cost of capital,16%,36%,11%
Generating social returns on investment,16%,34%,10%
Generating financial returns on investments,17%,41%,7%
Accessibility,21%,36%,10%
Speed,23%,33%,10%
Flexibility,26%,33%,9%
Willingness to take risks,29%,29%,10%",24.75
"YesCharacteristic,Total,18-34,35-44,45-54,55+
From home,55%,40%,55%,58%,65%
Live event,35%,53%,38%,30%,20%
Don't watch sports,10%,7%,7%,10%,13%",Yes
"54Characteristic,Total,18-34,35-44,45-54,55+
From home,55%,40%,55%,58%,65%
Live event,35%,53%,38%,30%,20%
Don't watch sports,7%,10%,7%,10%,13%",35.2
"Very confidentCharacteristic,Not at all confident,Not too confident,Somewhat confident,Very confident
Their cellphone manufacturers,13%,13%,43%,27%
Their credit card companies,15%,15%,42%,27%
Their cellphone service providers,15%,15%,47%,21%
Their e-mail providers,13%,17%,46%,20%
Companies/retatiers they do business with,15%,21%,46%,14%
The federal government,28%,21%,37%,12%
Social media sites they use,24%,27%,38%,9%",Very confident
"12Characteristic,Not at all confident,Not too confident,Somewhat confident,Very confident
Their cellphone manufacturers,13%,13%,43%,27%
Their credit card companies,15%,15%,42%,27%
Their cellphone service providers,15%,15%,47%,21%
Their e-mail providers,13%,17%,46%,20%
Companies/retatiers they do business with,15%,21%,46%,14%
The federal government,28%,21%,37%,12%
Social media sites they use,24%,27%,38%,9%",98
"Girls grade 9Characteristic,Too thin,Too fat
Boys grade 6,14%,18%
Boys grade 7,15%,25%
Boys grade 8,17%,23%
Boys grade 9,20%,24%
Boys grade 10,20%,23%
Girls grade 6,19%,9%
Girls grade 7,10%,28%
Girls grade 8,11%,26%
Girls grade 9,10%,31%
Girls grade 10,10%,34%",Girls grade 10
"30.5Characteristic,Too thin,Too fat
Boys grade 6,14%,18%
Boys grade 7,15%,25%
Boys grade 8,17%,23%
Boys grade 9,20%,24%
Girls grade 10,34%,20%
Girls grade 9,10%,31%
Girls grade 8,11%,26%
Girls grade 7,10%,28%
Girls grade 6,19%,9%",30.33
"9Characteristic,2014,2010
Love eating at quick service restaurants,63%,48%
Like eating at quick service restaurants,26%,22%
Hate eating at quick service restaurants,1%,9%",9
"25Characteristic,2014,2010
Hate eating at quick service restaurants,1%,9%
Like eating at quick service restaurants,26%,48%
Love eating at quick service restaurants,63%,48%",4
"Private nonprofit institutionCharacteristic,Average tuition cost and fees,Average student loan amount
Public institutions,7411,6639
Private nonprofit institution,35659,8224
Private for-profit institution,14991,7553",Private nonprofit institution
"Private nonprofit institutionCharacteristic,Average tuition cost and fees,Average student loan amount
Private nonprofit institution,35659,8224
Private for-profit institution,14991,7553
Public institutions,7411,6639",Public institutions
"2019Characteristic,Worker's health,Productivity and performance,Healthcare costs
2019,83%,84%,72%
2018,79%,77%,71%
2017,78%,75%,69%
2016,82%,80%,72%
2015,82%,80%,71%",2019
"82.35Characteristic,Worker's health,Productivity and performance,Healthcare costs
2019,83%,84%,72%
2018,79%,77%,71%
2017,78%,75%,69%
2016,82%,80%,72%
2015,82%,80%,71%",80
"YesCharacteristic,female,male
2018,83.38,76.35
2017,83.27,76.18
2016,83.15,76.01
2015,83.03,75.85
2014,82.9,75.68
2013,82.76,75.49
2012,82.6,75.27
2011,82.44,75.03
2010,82.26,74.76
2009,82.08,74.49
2008,81.89,74.22",No
"82.3Characteristic,female,male
2018,83.38,76.35
2017,83.27,76.18
2016,83.15,76.01
2015,83.03,75.85
2014,82.9,75.68
2013,82.76,75.49
2012,82.6,75.27
2011,82.44,75.03
2010,82.26,74.76
2009,82.08,74.49
2008,81.89,74.22",75
"Less likelyCharacteristic,Less likely,Neither more nor less likely,Don't know/no opinion,More likely
Go to the grocery store,11%,63%,20%,-
Vote in a political election,13%,51%,11%,24%
Go out to eat in a restaurant or cafe,19%,57%,8%,17%
Invest in the stock market,24%,46%,19%,11%
Go to a religious gathering or meeting,24%,51%,13%,12%
Go to a work conference,25%,48%,20%,6%
Go to a work social event,26%,53%,10%,10%
Go to a shopping mall,27%,52%,8%,13%
Go to a movie theater,29%,50%,10%,11%
Go to a museum,29%,52%,11%,8%
Use a ride-hailing service,30%,47%,15%,8%
Go to the gym,30%,47%,14%,9%
Take a vacation,3",More likely
"68Characteristic,Less likely,Neither more nor less likely,Don't know/no opinion,More likely
Go to the grocery store,11%,63%,20%,-
Vote in a political election,13%,51%,11%,24%
Go out to eat in a restaurant or cafe,19%,57%,8%,17%
Invest in the stock market,24%,46%,19%,11%
To a religious gathering or meeting,24%,51%,13%,12%
Go to a work conference,25%,48%,20%,6%
Go to a social event,26%,53%,10%,10%
Go to a shopping mall,27%,52%,8%,13%
Go to a movie thea ter,29%,50%,10%,11%
Go to a museum,29%,52%,11%,8%
Use a ride-hailing service,30%,47%,15%,8%
Go to the gym,30%,47%,14%,9%
Take a vacation,3",46
"448Year,J. Crew**,Madewell
2019,352,140
2018,377,129
2017,411,121
2016,462,113
2015,448,103
2014,419,85
2013,386,65",113
"2Year,J. Crew**,Madewell
2013,386,65
2014,419,85
2015,448,103
2016,462,113
2017,411,121
2018,377,129
2019,352,140",4
"Dark blueCharacteristic,0-14 years,15-64 years,65 years and older
2019,15.53%,68.3%,16.17%
2018,15.45%,68.92%,15.63%
2017,15.34%,69.58%,15.08%
2016,15.26%,70.19%,14.55%
2015,15.26%,70.7%,14.05%
2014,15.19%,71.16%,13.65%
2013,15.17%,71.52%,13.3%
2012,15.2%,71.8%,13%
2011,15.26%,70.02%,12.72%
2010,15.34%,72.21%,12.45%
2",gray
"25.79Characteristic,0-14 years,15-64 years,65 years and older
2019,15.53%,68.3%,16.17%
2018,15.45%,68.92%,15.63%
2017,15.34%,69.58%,15.08%
2016,15.26%,70.19%,14.55%
2015,15.26%,70.7%,14.05%
2014,15.19%,71.16%,13.65%
2013,15.17%,71.52%,13.3%
2012,15.2%,71.8%,13%
2011,15.26%,70.02%,12.72%
2010,15.34%,72.21%,12.45",100
"ServiceCharacteristic,Service,Product sales
2020,2639.59,475.9
2019,3099.22,930.89
2018,4046.31,784.94
2017,4136.56,802.4
2016,4375.59,778.31
2015,3977.69,711.36",Service
"1.6126Characteristic,Service,Product sales
2020,2639.59,475.9
2019,3099.22,930.89
2018,4046.31,784.94
2017,4136.56,802.4
2016,4375.59,778.31
2015,3977.69,711.36",5.546
"YesCharacteristic,Female,Male
2019,21.43,-
2018,20.92,-
2017,20.43,-
2016,19.95,-
2015,19.48,-
2014,19.02,-
2013,18.57,-
2012,18.14,-
2011,17.72,-
2010,17.31,-
2009,16.92,-",No
"1.62275Characteristic,Female,Male
2019,21.43,20.92
2018,20.92,20.69
2017,20.43,20.43
2016,19.95,19.66
2015,19.48,19.3
2014,19.02,18.96
2013,18.57,18.48
2012,18.14,17.86
2011,17.72,17.29
2010,17.31,16.83
2009,16.92,16.47",1
"131Characteristic,2012,2013,2014
Solvesd homicides,415,406,385
Unsolved homicides,128,106,131",131
"189.5Characteristic,2012,2013,2014
Solved homicides,415,406,385
Unsolved homicides,128,106,131",273
"4717Characteristic,Production in thousand metric tons
India,6423
China,5933
United States,4336
Brazil,2918
Pakistan,1350
Uzbekistan,762
Turkey,751
Greece,365
Mexico,342
Argentina,305",2112
"5756.66667Characteristic,Production in thousand metric tons
India,6423
China,5933
United States,4336
Brazil,2918
Pakistan,1350
Uzbekistan,762
Turkey,751
Greece,365
Mexico,342
Argentina,305",5564
"2021Characteristic,2017,2018,2019,2020,2021*
White,457,399,370,457,485
Black,130,223,209,235,241
Hispanic,179,148,158,169,180
Other,44,36,39,28,4
Unknown,84,204,202,126,193",2021
"311Characteristic,2017,2018,2019,2020,2021*
Unknown,84,204202,126,193,-
Other,44,36,39,28,0
Hispanic,39,148,158,169,-
Black,209,235241,74,-,-
White,457,399,370,457,-",216
"YesCharacteristic,Agriculture,Industry,Services
2020,41.49%,26.18%,32.33%
2019,42.39%,25.58%,32.04%
2018,43.33%,24.95%,31.72%
2017,44.05%,24.7%,31.25%
2016,45.14%,23.98%,30.87%
2015,45.67%,24.06%,30.27%
2014,45.84%,24.55%,29.61%
2013,46.36%,24.55%,29.09%
2012,47%,24.36%,28.64%
2011,48.98%,23.49%,27.53%
2010,51.52%,",Yes
"4Characteristic,Agriculture,Industry,Services
2020,41.49%,26.18%,32.33%
2019,42.39%,25.58%,32.04%
2018,43.33%,24.95%,31.72%
2017,44.05%,24.7%,31.25%
2016,45.14%,23.98%,30.87%
2015,45.67%,24.06%,30.27%
2014,45.84%,24.55%,29.61%
2013,46.36%,24.55%,29.09%
2012,47%,24.36%,28.64%
2011,48.98%,23.49%,27.53%
2010,51.52%,",7
"41Characteristic,Under 15 years,Over 65 years
Africa,41%,3%
World,26%,9%
Latin America,Caribbean,24%,9%
Asia,24%,9%
Oceania,23%,12%
North America,18%,17%
Europe,16%,19%",41
"AfricaCharacteristic,Under 15 years,Over 65 years
Africa,41%,3%
World,26%,9%
Latin America, Caribbean,24%,9%
Asia,24%,9%
Oceania,23%,12%
North America,18%,17%
Europe,16%,19%",Africa
"Eastern EuropeCharacteristic,Males,Females
Europe (total),75,82
Western Europe,79,84
Southern Europe,79,84
Northern Europe,79,84
Eastern Europe,69,79",Eastern Europe
"Eastern EuropeCharacteristic,Males,Females
Europe (total),75,82
Western Europe,79,84
Southern Europe,79,84
Northern Europe,79,84
Eastern Europe,69,79",Eastern Europe
"NoCharacteristic,Agriculture,Industry,Services
2019,25.1%,27.5%,47.4%
2018,26.1%,27.6%,46.3%
2017,27%,28.1%,44.9%
2016,27.7%,28.8%,43.5%
2015,28.3%,29.3%,42.4%
2014,29.5%,30.1%,40.6%
2013,31.4%,30.1%,38.5%
2012,33.6%,30.3%,36.1%
2011,34.8%,29.5%,35.7%
2010,36.7%,28.7%,34.6%
2009,38.1%,27.8%,34.1%",No
"AgricultureCharacteristic,Agriculture,Industry,Services
2019,25.1%,27.5%,47.4%
2018,26.1%,27.6%,46.3%
2017,27%,28.1%,44.9%
2016,27.7%,28.8%,43.5%
2015,28.3%,29.3%,42.4%
2014,29.5%,29.9%,40.6%
2013,31.4%,30.1%,38.5%
2012,33.6%,30.3%,36.1%
2011,34.8%,29.5%,35.7%
2010,36.7%,28.7%,34.6%
2009,38.1%,27.8%,34.1%",Services
"30Characteristic,Share of companies
Compulsory checks,37%
Work from home,30%
Others,33%",30
"60Characteristic,Share of respondents
Compulsory checks,37%
Work from home,30%
Others,33%",67
"53Characteristic,Mean,Median
Western Europe,52.13,44
Canada,56.15,52
United Kingdom,44.98,40
United States,59.66,53",59.66
"51.99Characteristic,Mean,Median
Western Europe,52.13,44
Canada,56.15,52
United Kingdom,44.98,40
United States,59.66,53",53.23
"49Characteristic,Share of respondents
Optimistic,43%
Hopeful,49%
Cautious,6%
Pessimistic,2%",49
"36.8Characteristic,Share of respondents
Optimistic,43%
Hopeful,49%
Cautious,6%
Pessimistic,2%",25
"NetflixCharacteristic,Share of average demand expressions*
Netflix,67.9%
Amazon Prime Video,9.2%
Hulu,9.2%
DC Universe,4.9%
CBS All Access,4.3%
Other,4.5%",Netflix
"68Characteristic,Share of average demand expressions*
Netflix,67.9%
Amazon Prime Video,9.2%
Hulu,9.2%
DC Universe,4.9%
CBS All Access,4.3%
Other,4.5%",9.2
"FemaleCharacteristic,Share of respondents
Female,53.5%
Male,46.5%",Female
"8.0Characteristic,Share of respondents
Female,53.5%
Male,46.5%",7
"2018Characteristic,female,male
2018,78.17,74.08
2017,78.01,73.9
2016,77.84,73.72
2015,77.66,73.52
2014,77.48,73.32
2013,77.29,73.11
2012,77.11,72.9
2011,76.92,72.7
2010,76.73,72.5
2009,76.55,72.3
2008,76.37,72.1",2018
"7.1Characteristic,female,male
2018,78.17,74.08
2017,78.01,73.9
2016,77.84,73.72
2015,77.66,73.52
2014,77.48,73.32
2013,77.29,73.11
2012,77.11,72.9
2011,76.92,72.7
2010,76.73,72.5
2009,76.55,72.3
2008,76.37,72.1",1.98
"2018Characteristic,One purchase day,Multiple purchase days
2018,59.9%,40.1%
2017,60.4%,39.6%
2016,59%,41%
2015,59%,41%
2014,60%,40%
2013,61%,39%
2012,61%,39%
2011,60%,40%","[2015, 2016]"
"43.93Characteristic,One purchase day,Multiple purchase days
2018,59.9%,40.1%
2017,60.4%,39.6%
2016,59%,41%
2015,59%,41%
2014,60%,40%
2013,61%,39%
2012,61%,39%
2011,60%,40%",39.9
"RabbitCharacteristic,Cat,Dog*,Rabbit**
2018,12000,7750,11750",Rabbit**
"4500Characteristic,Cat,Dog*,Rabbit**
2018,12000,11750,7750",250
"3693693Characteristic,Number of TEUs
Owned,1065731
Chartered,701548
Orderbook,283920",1065731
"2878829Characteristic,Number of TEUs
Owned,1065731
Chartered,701548
Orderbook,283920",985468
"Licensing and otherCharacteristic,Retail,Wholesale,E-shop,Licensing and other
2019/2020,33%,33%,33%,1%",Licensing and other
"31.3Characteristic,Retail,Wholesale,E-shop,Licensing and other
2019/2020,33%,33%,33%,1%",25
"Overall quality of lifeShare of respondents,satisfied,dissatisfied
Overall quality of life,74%,25%
Influence of religion,54%,40%
Opportunity to get ahead through hard work,45%,35%
Moral and ethical climate,62%,35%
Size and influence of major corporations,63%,35%
Our system and how well it works,35%,65%
Size and power of federal government,33%,66%
Income and wealth distribution,32%,67%",Overall quality of life
"Size and power of federal governmentShare of respondents,satisfied,dissatisfied
Overall quality of life,74%,25%
Influence of organized religion,54%,40%
Opportunity to get ahead through hard work,54%,45%
Moral and ethical climate,35%,62%
Size and influence of major corporations,35%,63%
Our system of government and how well it works,35%,65%
Size and power of federal government,33%,66%
Income and wealth distribution,32%,67%",Opportunity to get ahead through hard work
"PoliticiansCharacteristic,Ordinary people,Business owners,Politicians
Ukraine,11%,76%,95%
Lithuania,20%,78%,91%
Russia,26%,80%,82%",Russia
"1.205Characteristic,Ordinary people,Business owners,Politicians
Ukraine,11%,76%,95%
Lithuania,20%,78%,91%
Russia,26%,80%,82%",0.55
"7Characteristic,Aged 18-34 years,All new investors
2009,1%,2%
2019,5%,7%",7
"2019Characteristic,Aged 18-34 years,All new investors
2009,1%,2%
2019,5%,7%",2019
"BusCharacteristic,Share of respondents
""Metro / small bus*"",83%
Bus,34%
""Private car /motorbike"",28%
Walking,27%
Bicycle,12%
""Taxi, Uber or similar"",11%
Other,5%",Metro / small bus*
"13Characteristic,Share of respondents
""Metro / small bus*"",83%
Bus,34%
""Private car /motorbike"",28%
Walking,27%
Bicycle,12%
""Taxi, Uber or similar"",11%
Other,5%",72
"42.1Characteristic,Banknotes,Coins
2019,55.2,42.1
2018,58.0,33.1
2017,72.9,32.5
2016,82.2,33.0
2015,95.5,46.0
2014,63.0,46.0",42.1
"3Characteristic,Banknotes,Coins
2019,55.2,42.1
2018,58.0,33.1
2017,72.9,32.5
2016,82.2,33.0
2015,95.5,46.0
2014,63.0,46.0",3
"37Characteristic,Percentage of respondents
Always, often or sometimes,63%
Rarely or never,37%",37
"2.057Characteristic,Percentage of respondents
Always, often or sometimes,63%
Rarely or never,37%",1.702702703
"2020*Characteristic,Number of visits in thousands
2020*,261.87
2019,1215.83
2018,1197.39
2017,1181.64
2016,1342.23
2015,1368.53
2014,1254.14
2013,1110.34
2012,953.35
2011,852.21",2020
"4Characteristic,Number of visitors in thousands
2020*,261.87
2019,1215.83
2018,1197.39
2017,1181.64
2016,1342.23
2015,1368.53
2014,1254.14
2013,1110.34
2012,953.35
2011,852.21",3
"Rest of the Gulf Cooperation CouncilCharacteristic,Dubai,Abu Dhabi,Rest of the Gulf Cooperation Council
2030*,850,650
2020*,700,450
2015*,450,408
2012,386,180
2006,8,35.1",Rest of the Gulf Cooperation Council
"42.1Characteristic,Dubai,Abu Dhabi,Rest of the Gulf Cooperation Council
2030*,850,-,650
2020*,700,450,498
2015*,450,250,-,408
2012,386,180,-,308
2006,35,8.1,-,-",51.1
"45 to 54Characteristic,""No high school degree"",High school graduate,""Some college, no degree"",Associate degree,Bachelor's degree,65 and older
25 to 34,45%,54%,71%,68%,81%,43%
35 to 44,64%,71%,79%,43%,51%
45 to 54,36%,52%,62%,67%,78%
55 to 64,32%,48%,56%,61%,75%
65 and older,30%,42%,52%,61%,67%",35 to 44
"11Characteristic,No high school degree,High school graduate,Some college, no degree,Associate degree,Bachelor's degree
25 to 34,54%,71%,68%,81%,43%,51%
35 to 44,64%,71%,79%,43%,51%,64%
45 to 54,36%,52%,62%,67%,78%,44%
55 to 64,32%,48%,56%,61%,75%,23%
65 and older,30%,42%,52%,61%,67%,15%",14
"YesCharacteristic,Share of respondents
""Yes, I'm ready"",16%
""No, but I plan to soon"",11%
""No, and I don't plan to"",73%",Yes
"No, but I plan to soonCharacteristic,Share of respondents
""No, but I plan to soon"",11%
Yes,16%
""No, and I don't plan to"",73%","No, but I plan to soon"
"YesCharacteristic,Men,Women
2019,38.4,35.5
2018,38.0,35.2
2017,38.0,35.0
2016,37.7,34.7
2015,37.5,34.4
2014,37.1,33.9
2013,37.0,33.8
2012,37.0,33.8
2011,36.9,33.8
2010,36.6,34.0
2009,35.8,33.4
2008,36.4,33.4",No
"35.6Characteristic,Men,Women
2019,38.4,35.5
2018,38.2,35.2
2017,38.0,35.0
2016,37.7,34.7
2015,37.5,34.4
2014,37.1,33.9
2013,37.0,33.8
2012,37.0,33.8
2011,36.9,33.8
2010,36.6,33.4
2009,36.5,33.4
2008,36.4,33.4",70.8
"1.69615Characteristic,Share of individuals
Women,38.8%
Men,61.2%",1.577
"61.2Characteristic,Share of users
Women,38.8%
Men,61.2%",61.2
"2002Characteristic,Per capita real GDP in chained 2012 U.S. dollars
2019,52664
2018,51848
2017,50972
2016,50893
2015,49960
2014,49291
2013,47578
2012,48150
2011,46663
2010,45158
2009,44169
2008,44777
2007,47077
2006,48393
2005,47433
2004,46660
2003,45707
2002,45122
2001,44068
2000,44792",2001
"405Characteristic,Per capita real GDP in chained 2012 U.S. dollars
2019,52664
2018,51848
2017,50972
2016,49392
2015,49960
2014,49291
2013,47578
2012,48234
2011,46663
2010,45158
2009,46332
2008,44169
2007,47077
2006,48428
2005,47433
2004,46660
2003,45707
2002,45122
2001,44068
2000,44792",585
"BlackCharacteristic,No, most are not corrupt,""Yes, some are corrupt"",""Yes, almost all of them are corrupt""
16-17 years,13%,21%,66%
18-25 years,16%,21%,63%
26-34 years,12%,27%,61%
34 years and older,10%,35%,56%
Total,14%,24%,62%",Navy blue
"No, most are not corruptCharacteristic,No, most are not corrupt,Yes, some are corrupt,Yes, almost all of them are corrupt
16-17 years,13%,21%,66%
18-25 years,16%,63%
26-34 years,12%,61%
34 years and older,10%,56%
Total,14%,24%","Yes, almost all of them are corrupt"
"Workshops conducted by outside consultants, authors or expertsFormats of professional development,Teachers,Principals
Professional conferences,72%,65%
""Workshops conducted by outside consultants, authors or experts"",62%,60%
Observations,67%,60%
""Workshops conducted by my colleagues"",55%,63%
""Participating in a personal learning community"",43%,64%
Coaches or mentors,37%,57%
Reading professional books,37%,57%
""Participating in an online community of peers"",25%,23%
Webinars,24%,27%",Professional conferences
"52Formats of professional development,""Teachers"",Principals""Professional conferences"",65%,72.0""Workshops conducted by outside consultants, authors or experts"",60%,62.0""Observations"",60%,67.0""Workshops conducted by my colleagues"",55%,63.0""Participating in a personal learning community"",43%,64.0""Coaches or mentors"",37%,57.0""Reading professional books"",37%,57.0""Participating in an online community of peers"",25%,23.0""Webinars"",24%,27.0"""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""","""",""""""",42
"11Characteristic,Yes,No,Not sure about
God,79%,11%,10%
Angels,72%,16%,12%
Heaven,71%,15%,14%
Hell,64%,22%,13%
The Devil,61%,27%,12%",10
"49Characteristic,Yes,No,Not sure about
God,79%,11%,10%
Angels,72%,16%,12%
Heaven,71%,15%,14%
Hell,64%,22%,13%
The Devil,61%,27%,12%",18
"4Characteristic,Market share
North America,41%
EMEA*,26%
Greater China,19%
APLA**,14%",4
"33Characteristic,Market share
North America,41%
EMEA*,26%
Greater China,19%
APLA**,14%",33
"2Characteristic,Share of shipments
Commercial,42%
Non-commercial,42%
Unknown,16%",2
"2.777777778Characteristic,Market value share
Commercial,42%
Non-commercial,42%
Unknown,16%",2.625
"NoCharacteristic,Share of respondents
Yes,12.7%
No,87.3%",No
"9.46Characteristic,Share of respondents
Yes,12.7%
No,87.3%",74.6
"15Characteristic,Black or African American,Hispanic American or Latino,White / Caucasian
0 check-ups,20%,19%,19%
Up to three check-ups,61%,60%,62%
Up to five check-ups,12%,16%,11%
More than five check-ups,7%,5%,8%",7
"43Characteristic,Black or African American,Hispanic American or Latino,White/Caucasian
More than five check-ups,7%,5%,8%
Up to five check-ups,12%,16%,11%
Up to three check-ups,61%,60%,62%
0 check-ups,20%,19%,19%",68
"685Characteristic,2017,2018,2019
Kidney,685,660,670
Liver,106,98,95
Lung,90,85,69
Heart,37,37,33
Pancreas,18,24,27",685
"2017Characteristic,2017,2018,2019
Kidney,685,660,670
Liver,106,98,95
Lung,90,85,69
Heart,37,37,33
Pancreas,18,24,27",2017
"1991Characteristic,Lower income class,Middle income class,Upper income class
2015,70.3,120.8,51
2011,68,117.6,46.6
2001,57.6,111.2,38.3
1991,50.1,102.1,31
1981,42.4,94.8,24.6
1971,33.2,80.0,18.4",2015
"94.1Characteristic,Lower income class,Middle income class,Upper income class
2015,70.3,120.8,51
2011,68.0,117.6,46.6
2001,57.6,111.2,38.3
1991,50.1,102.1,31
1981,42.4,94.8,24.6
1971,33.2,80.0,18.4",34.98
"4Characteristic,Share of respondents who believe coronavirus is a threat
United Kingdom,60%
Italy,60%
Germany,50%
Sweden,48%
Spain,48%
Finland,39%
Norway,39%
Denmark,30%",3
"[United Kingdom, Denmark]Characteristic,Share of respondents who believe Coronavirus is a threat
United Kingdom,60%
Italy,60%
Germany,50%
Sweden,48%
Spain,48%
Finland,39%
Norway,39%
Denmark,30%",3
"CaliforniaProduction value in thousand U.S. dollars,California,7676076
Arizona,1154644
North Carolina,469399
Washington,299824
New York,222273
Texas,215990
Michigan,196907
Wisconsin,150694",California
"453.33Production value in thousand U.S. dollars,Population
California,7676076
Florida,1168155
Arizona,1154644
Georgia,583351
North Carolina,469399
Washington,299824
New York,222273
Texas,215990
Michigan,196907
Wisconsin,150694",187863.67
"GreenCharacteristic,Market share
Paramount 2,36
Sony 1,26
Fox 4,23
Universal 3,12
Disney 1,12
Warner Bros. 2,-",green
"Sony 1Characteristic,Market share value
Paramount 2,2
Sony 1,1
Universal 3,3
Fox 4,4
Warner Bros. 2,2
Dinsley,1",Fox
"44.51Characteristic,Agriculture,Industry,Services
2019,6.78%,31.3%,48.82%
2018,6.59%,31.27%,47.81%
2017,7.57%,31.55%,47.63%
2016,6.9%,30.96%,48.52%
2015,6.28%,32.69%,47.74%
2014,7.3%,35.38%,45.65%
2013,6.81%,35.9%,45.42%
2012,8.13%,36.28%,43.29%
2011,8%,36.09%,44.13%
2010,8.89%,35.39%,43.48%
2009,8.13%,36.11%,42.1",-30.03
"AgricultureCharacteristic,Agriculture,Industry,Services
2019,6.78%,31.3%,48.82%
2018,6.59%,31.27%,47.81%
2017,7.57%,31.55%,47.63%
2016,6.9%,30.96%,48.52%
2015,6.28%,32.69%,47.74%
2014,7.3%,35.38%,45.65%
2013,6.81%,35.9%,45.42%
2012,8.13%,36.28%,43.29%
2011,8%,36.09%,44.13%
2010,8.89%,35.39%,43.48%
2009,8.13%,36.11%,42.17%",36.28
"578.4Characteristic,Men,Women
2019,928.34,1181.71
2018,928.34,1181.71
2017,863.83,1177.59
2016,894.49,1154.19
2015,863.83,1155.34
2014,892.76,1156.91
2013,863.45,1159.36
2012,863.35,1118.29
2011,876.73,1067.49
2010,818.71,1069.38
2009,751.52,998.79
2008,754.02,988.36
2007,72",1343.75
"2014Characteristic,Men,Women
2019,967.61,1181.71
2018,928.34,1181.71
2017,889.74,1173.87
2016,894.49,1154.19
2015,889.12,1156.2
2014,892.76,1156.91
2013,883.59,1154.68
2012,863.35,1118.29
2011,868.05,1098.7
2010,818.71,1069.38
2009,786.16,998.79
2008,751.52,987.9
2007,725.31",2000
"RBSCharacteristic,Barclays,RBS,Lloyds,HSBC,SCB
H1 2014,406,217,240,195,210
H1 2013,400,197,201,217,220
H1 2012,186,190,193,237,230",Barclays
"52Characteristic,Barclays,RBS,Lloyds,HSBC,SCB
H1 2014,406,217,240,-,195
H1 2013,-,-,217,220,-
H1 2012,186,190,-,193,230",35
"70Characteristic,Laptop,Smartphone,Tablets
2011,39%,29%,5%
2014,70%,63%,40%",63
"LaptopCharacteristic,Laptop,Smartphone,Tablets
2011,39%,29%,5%
2014,70%,63%,40%",Tablets
"39.3Characteristic,Regular consumers*,Casual consumers**,Non-consumers
2015,16.4%,50.8%,32.8%
2010,17.8%,44.1%,38%
2005,20.7%,41.3%,38%
2000,23.8%,43.4%,32.8%
1998,25.5%,39.3%,35.2%
1995,27.9%,41.2%,30.9%
1990,30.2%,36.9%,32.9%
1985,41.5%,32.3%,26.2%
1980,50.7%,30.1%,19.2%",43.4
"Casual consumersCharacteristic,Regular consumers*,Casual consumers**,Non-consumers
2015,16.4%,50.8%,32.8%
2010,17.8%,44.1%,38%
2005,20.7%,41.3%,38%
2000,23.8%,43.4%,32.8%
1998,25.5%,39.3%,35.2%
1995,27.9%,41.2%,30.9%
1990,30.2%,36.9%,32.9%
1985,41.5%,32.3%,26.2%
1980,50.7%,30.1%,19.2%","[Casual consumers**, Non-consumers]"
"13Characteristic,Percentage of population
2019,10.7%
2018,10.3%
2017,10.7%
2016,10.2%
2015,11%
2014,11.5%
2013,11.8%
2012,11.2%
2011,12.2%
2010,13%
2009,11.7%
2008,12%
2007,12.1%
2006,11.4%
2005,11.2%
2004,12.1%
2003,11.7%
2002,12.5%
2001,12.1%
2000,11.6%",13
"10.8Characteristic,Percentage of population
2019,10.8%
2018,10.7%
2017,10.3%
2016,10.7%
2015,11%
2014,11.5%
2013,11.8%
2012,11.2%
2011,12.2%
2010,13%
2009,11.7%
2008,12%
2007,12.1%
2006,11.4%
2005,11.2%
2004,12.1%
2003,11.7%
2002,12.5%
2001,12.1%
2000,11.6%",10.57
"46.27Characteristic,Agriculture,Industry,Services
2020,21.28%,30.15%,48.57%
2019,21.71%,30.1%,48.2%
2018,22.31%,30.03%,47.66%
2017,22.78%,30.12%,47.1%
2016,23.1%,29.88%,47.02%
2015,25.59%,28.46%,45.96%
2014,28.35%,28.93%,42.72%
2013,29.25%,28.29%,42.46%
2012,29.71%,28.21%,42.08%
2011,29.26%,28.56%,42.18%
2010,31",31.01
"24.87Characteristic,Agriculture,Industry,Services
2020,21.28%,30.15%,48.57%
2019,21.71%,30.1%,48.2%
2018,22.31%,30.03%,47.66%
2017,22.78%,30.12%,47.1%
2016,23.1%,29.88%,47.02%
2015,25.59%,28.46%,45.96%
2014,28.35%,28.93%,42.72%
2013,29.25%,28.29%,42.46%
2012,29.71%,28.21%,42.08%
2011,29.26%,28.56%,42.18%
2010,31",9.66
"YesCharacteristic,Share of respondents
Yes,77%
No,16%
I don't know,7%",Yes
"23Characteristic,Share of respondents
Yes,77%
No,16%
I don't know,7%",23
"56Characteristic,Other,Games,Video and entertainment,Social and communication
2019,19%,9%,21%,50%
2018,19%,9%,20%,53%
2017,19%,9%,16%,56%
2016,20%,11%,13%,56%",56
"21Characteristic,Other,Games,Video and entertainment,Social and communication
2019,19%,9%,21%,50%
2018,19%,9%,20%,53%
2017,19%,9%,16%,56%
2016,20%,11%,13%,56%",6
"42Characteristic,Good value,Excellent value
Netflix,42%,36%
Hulu,38%,38%
Amazon Primt,38%,37%
""vMPD/""""Skinny Bundle"""""",24%,44%
Traditional pay-TV,12%,34%",12
"56Characteristic,Good value,Excellent value
Netflix,42%,36%
Hulu,38%,38%
Amazon Primt,38%,37%
""vMvpd""""""Skinny Bundle"",24%,44%
Traditional pay-TV,12%,34%",54
"LeaveCharacteristic,Remain,Leave
Christian,42%,58%
Muslim,70%,30%
Hindu,70%,30%
Jewish,46%,54%
Sikh,48%,52%
Buddhist,51%,49%",Leave
"47Characteristic,Remain,Leave
Christian,42%,58%
Muslim,70%,30%
Hindu,70%,30%
Jewish,46%,54%
Sikh,48%,52%
Buddhist,51%,49%",56
"[Facebook users, Twitter users]Characteristic,Trust the retailer less,Trust the retailer more
Online shoppers,55%,27%
Facebook users,55%,33%
Twitter users,52%,37%",Facebook users
"Facebook usersCharacteristic,Trust the retailer less,Trust the retailer more
Online shoppers,55%,27%
Facebook users,55%,33%
Twitter users,52%,37%",Online shoppers
"2014Characteristic,New Car Market,Used Car Market
2014,43.4,45.1
2013,36.7,42.7
2012,32.3,38.1
2011,29.0,35.7
2010,28.7,35.0
2009,28.0,34.2
2008,28.1,32.4
2007,33.0,33.3
2006,32.4,33.9
2005,32.2,32.3
2004,32.4,30.0
2003,33.5,32.0",2014
"4.2Characteristic,New Car Market,Used Car Market
2014,43.4,45.1
2013,36.7,42.7
2012,32.3,38.1
2011,29.0,35.7
2010,28.7,35.0
2009,28.0,34.2
2008,28.1,32.4
2007,33.0,33.3
2006,32.4,33.9
2005,32.2,32.3
2004,32.4,30.0
2003,33.5,32.0",4.9
"AsiansCharacteristic,Hispa nics,White, non-Hispanic,African Americans,Asians
Once a week or more (net),33%,33%,28%,34%
Once a month or more (net),70%,76%,71%,70%",Asians
"110Characteristic,Hispanics,White, non-Hispanic,African Americans,Asians
Once a week or more (net),33%,33%,28%,34%
Once a month or more (net),70%,76%,71%,70%",104
"PDFCharacteristic,Market share
Office,70.79%
Browser,14.76%
Android,7.24%
Java,3.61%
Adobe Flash,2.53%
PDF,1.07%",PDF
"55.53Characteristic,Share of downloads
Office,70.79%
Browser,14.76%
Android,7.24%
Java,3.61%
Adobe Flash,2.53%
PDF,1.07%",85.55
"23Characteristic,18-19 years old,20-24 years
1992,9%,23%
2006,16%,28%
2013,21%,41%",23
"20Characteristic,18-19 years old,20-24 years
2013,21%,41%
2006,16%,28%
1992,9%,23%",20
"48.25Characteristic,0-14,15-64,65 and older
2019,42.47%,54.91%,2.62%
2018,43.09%,54.32%,2.58%
2017,43.68%,53.76%,2.55%
2016,44.27%,53.21%,2.52%
2015,44.88%,52.64%,2.48%
2014,45.64%,51.91%,2.45%
2013,46.39%,51.19%,2.42%
2012,47.09%,50.52%,2.39%
2011,47.7%,49.94%,2.35%
2010,48.18%,49.49%,2.33%
2009",48.25
"[42.47%, 54.91]Characteristic,0-14,15-64,65 and older
2019,42.47%,54.91%,2.62%
2018,43.09%,54.32%,2.58%
2017,43.68%,53.76%,2.55%
2016,44.27%,53.21%,2.52%
2015,44.88%,52.64%,2.48%
2014,45.64%,51.91%,2.45%
2013,46.39%,51.19%,2.42%
2012,47.09%,50.52%,2.39%
2011,47.7%,49.94%,2.35%
2010,48.18%,49.49%,2","[42.47, 54.91]"
"32.03Characteristic,Sales share
Retail,67.97%
Wholesale,32.03%",32.03
"35.94Characteristic,Market value
Retail,67.97%
Wholesale,32.03%",35.94
"2Characteristic,Share of respondents
Uncomfortable,38%
Moderately comfortable,24%
Comfortable,29%
Don't know,9%",2
"47Characteristic,Share of respondents
Uncomfortable,38%
Moderately comfortable,24%
Comfortable,29%
Don't know,9%",47
"10901Characteristic,Passenger movements in thousands
Dover,10901
Holyhead,1886
Portsmouth,1715
Hull,827
Harwich,691
Tyne,604",10901
"2478.5Characteristic,Passenger movements in thousands
Dover,10901
Holyhead,1886
Portsmouth,1715
Hull,827
Harwich,691
Tyne,604",5864
"Over 10.5 years, More than 10.5 years, 6.6 -10.5 years, 4.6 - 6.5 years, 2.6 - 4.5 years, 0 - 2.5 yearsCharacteristic,Price (as a 12 month total) in British pounds
""0 - 2.5 years"",140994
""2.6 - 4.5 years"",274713
""4.6 - 6.5 years"",156134
""6.6 - 10.5 years"",413077
More than 10.5 years,258081",6.6 - 10.5 years
"50604Price (as a 12 month total) in British pounds,Sold car age group
""0 - 2.5 years"",140994
""2.6 - 4.5 years"",274713
""4.6 - 6.5 years"",156134
""6.6 - 10.5 years"",413077
""More than 10.5 years"",258081",399075
"Connected medical deviceCharacteristic,Connected medical device,Other medical device
Today,66%,34%
In 5 years,58%,42%",Other medical device
"60.5Characteristic,Connected medical device,Other medical device
Today,66%,34%
In 5 years,58%,42%",62
"BlueCharacteristic,Grooms,Brides
2019,30.4,28.8
2018,30.2,28.5
2017,30.0,28.4
2016,30.3,28.3
2015,30.3,28.2
2014,30.2,28.2
2013,30.2,28.0
2012,30.1,28.0
2011,30.1,28.0
2010,30.0,27.7",blue
"19.6Characteristic,Grooms,Brides
2019,30.4,28.8
2018,30.2,28.5
2017,30.0,28.4
2016,30.3,28.3
2015,30.3,28.2
2014,30.2,28.2
2013,30.2,28.0
2012,30.1,28.0
2011,30.1,28.0
2010,30.0,27.7",2.7
"Helps me identify trending productsCharacteristic,Strongly agree,Somewhat agree,Neither agree nor disagree,Somewhat disagree,Strongly disagree
""Increases my purchasing confidence"",30%,43%,22%,32%,-
""Improves customer feedback"",30%,41%,25%,32%,-
""Is more interesting than content created by the brand"",26%,39%,29%,42%,-
""Creates a more authentic shopping experience"",24%,43%,28%,32%,-
""Encourages me to engage with a brand"",19%,42%,-,-,62%
Helps me identify trending products,16%,32%,40%,9%,-",Helps me identify trending products
"39Characteristic,Strongly agree,Somewhat agree,Neither agree nor disagree,Somewhat disagree,Strongly disagree
""Increases my purchasing confidence"",30%,43%,22%,32%,-
""Improves customer feedback"",30%,41%,25%,32%,-
""Is more interesting than content created by the brand"",26%,39%,29%,42%,-
""Creates a more authentic shopping experience"",24%,43%,28%,32%,-
""Encourages me to engage with a brand"",19%,42%,32%,62%,-
""Helps me identify trending products"",16%,32%,40%,9%,3",29.33
"SameCharacteristic,Share of respondents
Same,54%
More,24%
Less,22%",Same
"46Characteristic,Share of respondents
Same,54%
More,24%
Less,22%",46
"11.8Characteristic,Percentage of population
2019,11.8%
2018,12.8%
2017,13.3%
2016,14.3%
2015,15.4%
2014,16.4%
2013,16.8%
2012,17%
2011,16.6%
2010,15.8%
2009,14.2%
2008,13.3%
2007,12.4%
2006,13.2%
2005,13.3%
2004,13.4%
2003,13%
2002,13%
2001,12.8%
2000,13.7%",11.8
"2.5Characteristic,Percentage of population
2019,11.8%
2018,12.8%
2017,13.3%
2016,14.3%
2015,15.3%
2014,16.4%
2013,16.8%
2012,16.9%
2011,17%
2010,15.8%
2009,14.2%
2008,13.3%
2007,12.4%
2006,13.6%
2005,13.3%
2004,13.6%
2003,13.4%
2002,13%
2001,12.8%
2000,13.7%",5.2
"EuropeCharacteristic,Number of personal trips in millions
Europe,19.3
Africa,2.0
Americas,1.8
Asia and Oceania,1.4",Europe
"YesCharacteristic,Number of personal trips in millions
Europe,19.3
Africa,2.0
Americas,1.8
Asia and Oceania,1.4",Yes
"61 years and olderCharacteristic,18 to 29 years,30 to 45 years,46 to 60 years,61 years and older
""I use it regularly"",11%,6%,5%,1%
""I use it occasionally"",14%,8%,4%,1%
""I have used it once"",13%,5%,3%
""I can imagine using it"",42%,52%,53%
""I won't use it"",21%,20%,29%,36%",61 years and older
"19Characteristic,18 to 29 years,30 to 45 years,46 to 60 years,61 years and older
I use it regularly,11%,5%,6%,1%
I use it occasionally,14%,8%,4%,1%
I have used it once,13%,11%,5%,3%
I can imagine using it,42%,52%,53%,56%
I won't use it,21%,20%,29%,36%",32
"40-59 yearsCharacteristic,Men,Women
Below 1 year of age,1%,0.9%
1-5 years,4.9%,4.6%
6-14 years,8.3%,7.7%
15-17 years,2.9%,2.6%
18-20 years,3.2%,2.9%
21-24 years,4.8%,4.2%
25-39 years,19.9%,18.3%
40-59 years,28.9%,27.9%
60-64 years,6.8%,6.8%
65 years and older,19.3%,24.1%",40-59 years
"6.88Characteristic,Men,Women
Below 1 year of age,1%,0.9%
1-5 years,4.9%,4.6%
6-14 years,8.3%,7.7%
15-17 years,2.9%,2.6%
18-20 years,3.2%,2.9%
21-24 years,4.8%,4.2%
25-39 years,19.9%,18.3%
40-59 years,28.9%,27.9%
60-64 years,6.8%,6.8%
65 years and older,19.3%,24.1%",0.6
"5Characteristic,Share of respondents
0 - 5%,21%
5 - 10%,41%
10 - 15%,21%
15 - 20%,12%
More than 20%,5%",5
"64Characteristic,Share of respondents
0 - 5%,21%
5 - 10%,41%
10 - 15%,21%
15 - 20%,12%
More than 20%,5%",46
"ChineseCharacteristic,Number of live births in thousands
Chinese,22.99
Malays,7.82
Indians,4.25
Others,4.21",Chinese
"18.4Characteristic,Number of live births in thousands
Chinese,22.99
Malays,7.82
Indians,4.25
Others,4.21",12.03
"CashCharacteristic,How consumers can pay,How providers receive payments
Cash,44%,46%
Account,19%,85%
Mobile,52%,54%
PayPal,33%,15%
Debit/credit card,78%,0%",Mobile
"0.120833333Characteristic,How consumers can pay,How providers receive payments
Cash,44%,46%
Account,19%,85%
Mobile,52%,54%
PayPal,33%,15%
Debit/credit card,78%,0%",2.315
"CompatibilityCharacteristic,Very concerned,Somewhat concerned,Slightly concerned,Not at all concerned
High prices,44%,33%,17%,5%
""Hacking/ cybersecurity"",48%,26%,18%,8%
Reliability,38%,32%,20%,11%
Compatibility,30%,38%,21%,12%
""Technology becoming outdated"",24%,37%,26%,13%
Difficulty managing,20%,34%,26%,20%",Very concerned
"52Characteristic,Very concerned,Somewhat concerned,Slightly concerned,Not at all concerned
High prices,44%,33%,17%,5%
""Hacking/cybersecurity"",48%,26%,18%,8%
Reliability,38%,32%,20%,11%
Compatibility,30%,38%,21%,12%
""Technology becoming outdated"",24%,37%,26%,13%
Difficulty managing,20%,34%,26%,20%",101
"80Characteristic,Domestic visitor,Foreign visitor
2017,80%,20%
2016,79.4%,20.6%
2015,80.9%,19.1%
2014,79.4%,20.6%
2013,79.8%,20.2%",20
"2Characteristic,Domestic visitor,Foreign visitor
2017,80%,20%
2016,79.4%,20.6%
2015,80.9%,19.1%
2014,79.4%,20.6%
2013,79.8%,20.2%",4
"Rx eyeglassesCharacteristic,Share sold online
Rx eyeglasses,9.3%
Plano sunglasses,8.3%",Rx eyeglasses
"17.6Characteristic,Share sold online
Rxeyeglasses,9.3%
Piano sunglasses,8.3%",17.6
"FemaleCharacteristic,Share of coaches
Male,73.5%
Female,26.5%",Female
"47Characteristic,Distribution of respondents
Male,73.5%
Female,26.5%",47
"PhilippinesCharacteristic,Number of cases in thousands
Quezon City,106.71
Cavite,72.34
City of Manila,66.88
Laguna,58.31
Rizal,55.57",Philippines
"42.03Characteristic,Number of cases in thousands
Quezon City,106.71
Cavite,72.34
City of Manila,66.88
Laguna,58.31
Rizal,55.57",51.14
"70Characteristic,2008,2009,2010
""Last week of November"",92,69,79
""1st week of December"",95,75,66
""2nd week of December"",94,73,66
""3rd week of December"",93,74,77
""4th week of December"",68,70,85",68
"86.5Characteristic,2008,2009,2010
""Last week of November"",92,69,79
""1st week of December"",95,75,66
""2nd week of December"",94,73,66
""3rd week of December"",93,74,77
""4th week of December"",68,70,85",74.6
"C1Characteristic,More than 10 times a day,2-10 times a day,Once a day,Less often than daily
AB,19%,42%,14%,25%
C1,24%,40%,19%,16%
C2,25%,41%,17%,17%
DE,34%,38%,14%,14%",2-10 times a day
"16Characteristic,More than 10 times a day,2-10 times a day,Once a day,Less often than daily
AB,19%,42%,14%,25%
C1,24%,40%,19%,16%
C2,25%,41%,17%,17%
DE,34%,38%,14%,14%",25
"2013***Characteristic,2013****,2014
Films or music,50%,73%
""Electronic books, magazines, newspapers or e-learning material"",52%,61%
""Computer software, computer and video games or software upgrades"",66%,91%",2013
"62.5Characteristic,2013***,2014
""Films or music"",50%,73%
""Electronic books, magazines, newspapers or e-learning material"",52%,61%
""Computer software, computer and video games or software upgrades"",66%,91%",56