Datasets:

beamstation
/

all-restaurants-in-melbourne-florida-us-211295-211295

beam_id string	title string	category_main_group string	category_sub_group string	category string	categories string	address string	street string	city string	state string	borough string	neighborhood float64	postal_code int64	country string	address_verified bool	latitude float64	longitude float64	timezone string	phone string	price_level int64	business_status string	has_open_hours bool	has_price bool	census_place float64	verified_census_city bool	beam_location_name string	beam_state_code string	beam_country_code string	website_protocol string	website string	website_normalized string	website_domain string	website_domain_tld string	website_domain_age float64	website_domain_registered string	website_domain_expires string	website_domain_registrar string	emails_list string	emails_list_website_domain string	emails_count int64	emails_deliverable_count int64	emails_risky_count int64	description string	has_about bool	has_description bool	rating float64	reviews_total_count int64	reviews_per_rating string	service_options string	highlights string	popular_for string	accessibility string	offerings string	dining_options string	amenities string	atmosphere string	crowd string	planning string	payments string	children string	has_popular_times bool	has_website bool	has_email string	has_social bool	has_phone bool	socials_count int64	first_social_post_date string	last_social_post_date string	first_social_post_days float64	last_social_post_days float64	social_post_count float64	first_social_post_days_min float64	first_social_post_days_max float64	last_social_post_days_min float64	last_social_post_days_max float64	social_profile_instagram string	social_username_instagram string	social_profile_facebook string	social_username_facebook string	social_profile_twitter string	social_username_twitter string	social_profile_tiktok string	social_username_tiktok string	social_profile_linkedin string	social_username_linkedin string	social_profile_youtube string	social_username_youtube string	social_profile_github float64	social_username_github float64	social_profile_snapchat float64	social_username_snapchat float64	social_profile_pinterest string	social_username_pinterest string	instagram_followers float64	instagram_engagement_rate float64	instagram_engagement_rate_1m float64	instagram_engagement_rate_3m float64	instagram_engagement_rate_6m float64	instagram_engagement_rate_12m float64	instagram_post_count float64	tiktok_followers float64	tiktok_video_count float64	tiktok_heart_count float64	tiktok_engagement_rate float64	tiktok_engagement_rate_1m float64	tiktok_engagement_rate_3m float64	tiktok_engagement_rate_6m float64	tiktok_engagement_rate_12m float64	menu_link string	order_links string	reservation_link string	last_updated_at string	beam_cross_social_market_penetration float64	beam_cross_social_urgency float64	beam_cross_per_capita_engagement float64	beam_cross_market_saturation_lead float64	beam_cross_population_adjusted_rank float64	beam_cross_demand_gap_index float64	beam_rating_score float64	beam_review_confidence float64	beam_rating_health float64	sentiment_avg float64	sentiment_avg_30d float64	sentiment_avg_90d float64	sentiment_avg_180d float64	sentiment_avg_360d float64	sentiment_percentile_1km float64	sentiment_percentile_5km float64	sentiment_percentile_10km float64	sentiment_score_90d float64	sentiment_score_360d float64	sentiment_positive_pct_30d float64	sentiment_negative_pct_30d float64	sentiment_neutral_pct_30d float64	sentiment_positive_pct_90d float64	sentiment_negative_pct_90d float64	sentiment_neutral_pct_90d float64	sentiment_positive_pct_180d float64	sentiment_negative_pct_180d float64	sentiment_neutral_pct_180d float64	sentiment_positive_pct_360d float64	sentiment_negative_pct_360d float64	sentiment_neutral_pct_360d float64	sentiment_trend_30vs90d string	sentiment_trend_90vs360d string	sentiment_diff_30vs90d float64	sentiment_change_360d float64	sentiment_diff_90vs360d float64	sentiment_change_pct_360d float64	reviews_count_90d int64	reviews_count_180d int64	reviews_count_360d int64	review_growth_pct_180d float64	review_growth_pct_360d float64	review_growth_pct_90d float64	beam_score_overall float64	beam_popularity_percentile float64	beam_social_presence int64	beam_data_completeness int64	beam_price_value float64	beam_data_freshness float64	beam_rank_city_category int64	beam_rank_city_overall int64	beam_rank_city_reviews int64	beam_rank_state_category int64	beam_rank_state_overall int64	beam_rank_state_reviews int64	beam_rank_country_category int64	beam_rank_country_overall int64	beam_rank_country_reviews int64	beam_rank_place_global_category int64	beam_rank_category int64	beam_rank_competition_1km_category int64	beam_rank_competition_1km_total int64	beam_rank_competition_1km_reviews int64	beam_rank_competition_5km_category int64	beam_rank_competition_5km_total int64	beam_rank_competition_5km_reviews int64	beam_rank_competition_10km_category int64	beam_rank_competition_10km_total int64	beam_rank_competition_10km_reviews int64	beam_export_rank int64	total_city_category float64	total_city float64	total_state_category float64	total_state float64	total_country_category float64	total_country float64	total_category_global float64	beam_competitors_10km_competitive_strength float64	beam_competitors_10km_competitor_avg_sentiment_30d float64	beam_competitors_10km_competitor_avg_sentiment_90d float64	beam_competitors_10km_sentiment_diff_30d float64	beam_competitors_10km_sentiment_diff_90d float64	beam_competitors_1km_competitive_strength float64	beam_competitors_1km_competitor_avg_sentiment_30d float64	beam_competitors_1km_competitor_avg_sentiment_90d float64	beam_competitors_1km_sentiment_diff_30d float64	beam_competitors_1km_sentiment_diff_90d float64	beam_competitors_5km_competitive_strength float64	beam_competitors_5km_competitor_avg_sentiment_30d float64	beam_competitors_5km_competitor_avg_sentiment_90d float64	beam_competitors_5km_sentiment_diff_30d float64	beam_competitors_5km_sentiment_diff_90d float64	beam_competitors_10km_competitor_count int64	beam_competitors_1km_competitor_count int64	beam_competitors_5km_competitor_count int64	beam_competitors_1km_rank_by_score int64	beam_competitors_1km_rank_by_rating int64	beam_competitors_1km_rank_by_reviews int64	beam_competitors_1km_score_percentile float64	beam_competitors_1km_rating_percentile float64	beam_competitors_1km_reviews_percentile float64	beam_competitors_1km_health_percentile float64	beam_competitors_1km_sentiment_percentile float64	beam_competitors_1km_competitor_avg_score float64	beam_competitors_1km_competitor_avg_rating float64	beam_competitors_1km_competitor_avg_reviews int64	beam_competitors_1km_competitor_avg_health float64	beam_competitors_1km_competitor_avg_sentiment float64	beam_competitors_1km_score_diff float64	beam_competitors_1km_rating_diff float64	beam_competitors_1km_reviews_diff int64	beam_competitors_1km_health_diff float64	beam_competitors_1km_sentiment_diff float64	beam_competitors_5km_rank_by_score int64	beam_competitors_5km_rank_by_rating int64	beam_competitors_5km_rank_by_reviews int64	beam_competitors_5km_score_percentile float64	beam_competitors_5km_rating_percentile float64	beam_competitors_5km_reviews_percentile float64	beam_competitors_5km_health_percentile float64	beam_competitors_5km_sentiment_percentile float64	beam_competitors_5km_competitor_avg_score float64	beam_competitors_5km_competitor_avg_rating float64	beam_competitors_5km_competitor_avg_reviews int64	beam_competitors_5km_competitor_avg_health float64	beam_competitors_5km_competitor_avg_sentiment float64	beam_competitors_5km_score_diff float64	beam_competitors_5km_rating_diff float64	beam_competitors_5km_reviews_diff int64	beam_competitors_5km_health_diff float64	beam_competitors_5km_sentiment_diff float64	beam_competitors_10km_rank_by_score int64	beam_competitors_10km_rank_by_rating int64	beam_competitors_10km_rank_by_reviews int64	beam_competitors_10km_score_percentile float64	beam_competitors_1km_competitive_tier string	beam_competitors_10km_rating_percentile float64	beam_competitors_10km_reviews_percentile float64	beam_competitors_10km_health_percentile float64	beam_competitors_10km_sentiment_percentile float64	beam_competitors_5km_competitive_tier string	beam_competitors_10km_competitor_avg_score float64	beam_competitors_10km_competitor_avg_rating float64	beam_competitors_10km_competitor_avg_reviews int64	beam_competitors_10km_competitor_avg_health float64	beam_competitors_10km_competitive_tier string	beam_competitors_10km_competitor_avg_sentiment float64	beam_competitors_10km_score_diff float64	beam_competitors_10km_rating_diff float64	beam_competitors_10km_reviews_diff int64	beam_competitors_10km_health_diff float64	beam_competitors_10km_sentiment_diff float64	beam_competitors_1km_total_in_radius int64	beam_competitors_5km_total_in_radius int64	beam_competitors_10km_total_in_radius int64	beam_competitors_1km_avg_distance_m int64	beam_competitors_1km_closest_competitor_m int64	beam_competitors_1km_market_type string	beam_competitors_1km_review_share float64	beam_competitors_1km_density_per_sqkm float64	beam_competitors_1km_tier_below_40 float64	beam_competitors_1km_tier_40_59 float64	beam_competitors_1km_tier_60_79 float64	beam_competitors_1km_tier_80_100 float64	beam_competitors_5km_avg_distance_m int64	beam_competitors_5km_closest_competitor_m int64	beam_competitors_5km_market_type string	beam_competitors_5km_review_share float64	beam_competitors_5km_density_per_sqkm float64	beam_competitors_5km_tier_below_40 float64	beam_competitors_5km_tier_40_59 float64	beam_competitors_5km_tier_60_79 float64	beam_competitors_5km_tier_80_100 float64	beam_competitors_10km_avg_distance_m int64	beam_competitors_10km_closest_competitor_m int64	beam_competitors_10km_market_type string	beam_competitors_10km_review_share float64	beam_competitors_10km_density_per_sqkm float64	beam_competitors_10km_tier_below_40 float64	beam_competitors_10km_tier_40_59 float64	beam_competitors_10km_tier_60_79 float64	beam_competitors_10km_tier_80_100 float64	beam_competitors_city_competitor_avg_sentiment_30d float64	beam_competitors_city_competitor_avg_sentiment_90d float64	beam_competitors_city_sentiment_diff_30d float64	beam_competitors_city_sentiment_diff_90d float64	beam_competitors_city_competitor_count int64	beam_competitors_city_total_in_city int64	beam_competitors_city_rank_by_score int64	beam_competitors_city_rank_by_rating int64	beam_competitors_city_rank_by_reviews int64	beam_competitors_city_score_percentile float64	beam_competitors_city_rating_percentile float64	beam_competitors_city_reviews_percentile float64	beam_competitors_city_health_percentile float64	beam_competitors_city_sentiment_percentile float64	beam_competitors_city_competitor_avg_score float64	beam_competitors_city_competitor_avg_rating float64	beam_competitors_city_competitor_avg_reviews int64	beam_competitors_city_competitor_avg_health float64	beam_competitors_city_competitor_avg_sentiment float64	beam_competitors_city_score_diff float64	beam_competitors_city_rating_diff float64	beam_competitors_city_reviews_diff int64	beam_competitors_city_health_diff float64	beam_competitors_city_sentiment_diff float64	beam_competitors_city_market_type string	beam_competitors_city_review_share float64	beam_competitors_city_density_per_sqkm float64	beam_competitors_city_tier_below_40 float64	beam_competitors_city_tier_60_79 float64	beam_competitors_city_tier_80_100 float64	beam_competitors_city_competitive_strength float64	beam_competitors_city_underserved_score float64	beam_competitors_city_competition_intensity float64	beam_competitors_state_competitor_avg_sentiment_30d float64	beam_competitors_state_competitor_avg_sentiment_90d float64	beam_competitors_state_sentiment_diff_30d float64	beam_competitors_state_sentiment_diff_90d float64	beam_competitors_state_competitor_count int64	beam_competitors_state_total_in_state int64	beam_competitors_state_rank_by_score int64	beam_competitors_state_rank_by_rating int64	beam_competitors_state_rank_by_reviews int64	beam_competitors_state_score_percentile float64	beam_competitors_state_rating_percentile float64	beam_competitors_state_reviews_percentile float64	beam_competitors_state_health_percentile float64	beam_competitors_state_sentiment_percentile float64	beam_competitors_state_competitor_avg_score float64	beam_competitors_state_competitor_avg_rating float64	beam_competitors_state_competitor_avg_reviews int64	beam_competitors_state_competitor_avg_health float64	beam_competitors_state_competitor_avg_sentiment float64	beam_competitors_state_score_diff float64	beam_competitors_state_rating_diff float64	beam_competitors_state_reviews_diff int64	beam_competitors_state_health_diff float64	beam_competitors_state_sentiment_diff float64	beam_competitors_state_market_type string	beam_competitors_state_review_share float64	beam_competitors_state_density_per_sqkm float64	beam_competitors_state_underserved_score float64	beam_competitors_state_competition_intensity float64	beam_competitors_state_competitive_strength float64	beam_competitors_country_competitor_avg_sentiment_30d float64	beam_competitors_country_competitor_avg_sentiment_90d float64	beam_competitors_country_sentiment_diff_30d float64	beam_competitors_country_sentiment_diff_90d float64	beam_competitors_country_competitor_count int64	beam_competitors_country_competitor_avg_score float64	beam_competitors_country_competitor_avg_rating float64	beam_competitors_country_competitor_avg_reviews int64	beam_competitors_country_competitor_avg_health float64	beam_competitors_country_competitor_avg_sentiment float64	beam_competitors_country_score_diff float64	beam_competitors_country_rating_diff float64	beam_competitors_country_reviews_diff int64	beam_competitors_country_sentiment_diff float64	beam_competitors_country_score_percentile float64	beam_competitors_country_rating_percentile float64	beam_competitors_country_reviews_percentile float64	beam_competitors_country_health_percentile float64	beam_competitors_country_sentiment_percentile float64	beam_competitors_country_rank_by_score int64	beam_competitors_country_competitive_strength float64	beam_competitors_country_health_diff float64	beam_competitors_country_rank_by_rating int64	beam_competitors_country_rank_by_reviews int64	beam_competitors_country_tier_40_59 float64	beam_competitors_country_tier_60_79 float64	beam_competitors_country_tier_80_100 float64	beam_competitors_country_tier_below_40 float64	beam_competitors_country_total_in_country int64	beam_competitors_city_siblings_competitor_count int64	beam_competitors_city_siblings_competitor_avg_score float64	beam_competitors_city_siblings_competitor_avg_rating float64	beam_competitors_city_siblings_competitor_avg_reviews int64	beam_competitors_city_siblings_competitor_avg_health float64	beam_competitors_city_siblings_competitor_avg_sentiment float64	beam_competitors_city_siblings_score_diff float64	beam_competitors_city_siblings_rating_diff float64	beam_competitors_city_siblings_reviews_diff int64	beam_competitors_city_siblings_sentiment_diff float64	beam_competitors_city_siblings_score_percentile float64	beam_competitors_city_siblings_rating_percentile float64	beam_competitors_city_siblings_reviews_percentile float64	beam_competitors_city_siblings_health_percentile float64	beam_competitors_city_siblings_sentiment_percentile float64	beam_competitors_city_siblings_rank_by_score int64	beam_competitors_city_siblings_competitor_avg_recommend_pct float64	beam_competitors_city_siblings_recommend_pct_diff float64	beam_competitors_city_siblings_recommend_pct_percentile float64	beam_competitors_city_siblings_total_siblings int64	beam_competitors_city_businesses_per_10k_pop float64	beam_competitors_city_population_per_business int64	beam_competitors_city_population_density int64	beam_competitors_city_reviews_per_capita float64	beam_competitors_city_reviews_per_10k_pop float64	beam_competitors_state_businesses_per_10k_pop float64	beam_competitors_state_population_per_business int64	beam_competitors_state_population_density int64	beam_competitors_state_reviews_per_capita float64	beam_competitors_state_reviews_per_10k_pop float64	beam_competitors_1km_hhi_contribution float64	beam_competitors_1km_hhi_minimum float64	beam_competitors_5km_hhi_contribution float64	beam_competitors_5km_hhi_minimum float64	beam_competitors_10km_hhi_contribution float64	beam_competitors_10km_hhi_minimum float64	beam_competitors_city_hhi_contribution float64	beam_competitors_city_hhi_minimum float64	beam_competitors_state_hhi_contribution float64	beam_competitors_state_hhi_minimum float64	beam_trends_score_30d_beam_score_overall float64	beam_trends_score_30d_beam_popularity_percentile float64	beam_trends_score_90d_beam_score_overall float64	beam_trends_score_90d_rating float64	beam_trends_score_90d_review_count int64	beam_trends_score_90d_beam_rating_health float64	beam_trends_score_90d_beam_popularity_percentile float64	beam_trends_competitive_1km_30d_strength_change float64	beam_trends_competitive_1km_30d_rank_change int64	beam_trends_competitive_1km_30d_percentile_change float64	beam_trends_competitive_1km_90d_strength_change float64	beam_trends_competitive_1km_90d_rank_change int64	beam_trends_competitive_1km_90d_percentile_change float64	beam_trends_competitive_5km_30d_strength_change float64	beam_trends_competitive_5km_30d_rank_change int64	beam_trends_competitive_5km_30d_percentile_change float64	beam_trends_competitive_5km_90d_strength_change float64	beam_trends_competitive_5km_90d_rank_change int64	beam_trends_competitive_5km_90d_percentile_change float64	beam_trends_competitive_10km_30d_strength_change float64	beam_trends_competitive_10km_30d_rank_change int64	beam_trends_competitive_10km_30d_percentile_change float64	beam_trends_competitive_10km_90d_strength_change float64	beam_trends_competitive_10km_90d_rank_change int64	beam_trends_competitive_10km_90d_percentile_change float64	beam_trends_competitive_city_30d_strength_change float64	beam_trends_competitive_city_30d_rank_change int64	beam_trends_competitive_city_30d_percentile_change float64	beam_trends_competitive_city_90d_strength_change float64	beam_trends_competitive_city_90d_rank_change int64	beam_trends_competitive_city_90d_percentile_change float64	beam_trends_competitive_state_30d_strength_change float64	beam_trends_competitive_state_30d_rank_change int64	beam_trends_competitive_state_30d_percentile_change float64	beam_trends_competitive_state_90d_strength_change float64	beam_trends_competitive_state_90d_rank_change int64	beam_trends_competitive_state_90d_percentile_change float64	beam_trends_sentiment_current_sentiment float64	beam_trends_sentiment_positive_ratio float64	beam_trends_sentiment_negative_ratio float64	beam_trends_sentiment_review_count int64	beam_trends_velocity_trend string	beam_velocity_reviews_per_day float64	beam_velocity_reviews_per_week float64	beam_velocity_reviews_per_month float64	beam_velocity_reviews_last_30d float64	beam_velocity_reviews_last_90d float64	beam_velocity_reviews_last_365d float64	beam_velocity_percentile_1km float64	beam_velocity_percentile_5km float64	beam_velocity_percentile_10km float64	beam_velocity_percentile_city float64	beam_velocity_percentile_state float64	beam_velocity_rank_1km float64	beam_velocity_rank_5km float64	beam_velocity_rank_10km float64	beam_velocity_rank_city float64	beam_velocity_rank_state float64	beam_velocity_trend string	beam_velocity_change_30d float64	beam_velocity_change_90d float64	beam_trends_sentiment_recommend_pct float64
BB2G2XRS	Subway	Food and Drink	Restaurants	Sandwich shop	Sandwich shop, Caterer, Fast food restaurant, Takeout Restaurant, Restaurant	1500 S Babcock St, Melbourne, FL 32901	1500 S Babcock St	Melbourne	Florida	Magnolia Hgts	null	32,901	US	true	28.084882	-80.62196	America/New_York	(321) 72-***	2	OPERATIONAL	true	true	null	true	Melbourne	Florida	US	https	https://restaurants.subway.com/united-states/fl/melbourne/1500-s-babcock-st	restaurants.subway.com/united-states/fl/melbourne/1500-s-babcock-st	restaurants.subway.com	com	11,067	1996-01-17	2027-01-18	CSC Corporate Domains, Inc.	purchase_dataset@ipcoop.com	null	1	0	1	Casual counter-serve chain for build-your-own sandwiches & salads, with health-conscious options.	true	true	4.13	679	{"1": 59, "2": 26, "3": 73, "4": 168, "5": 421}	Delivery, Onsite services, Takeout, Dine-in	null	Breakfast, Lunch, Dinner, Solo dining	"Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible restroom, (...TRUNCATED)	Coffee, Comfort food, Healthy options, Late-night food, Quick bite, Vegetarian options	Breakfast, Lunch, Dinner, Catering, Counter service, Dessert	Restroom	Casual, Quiet	College students, Tourists	null	Credit cards, Debit cards, NFC mobile payments	Good for kids, Kids' menu	true	true	purchase_dataset@	true	true	5	2025-11-06	2026-02-25	182	71	36	182	182	71	71	https://www.instagram.com/subway	subway	https://www.facebook.com/subway	subway	https://twitter.com/subway	subway	null	null	https://www.linkedin.com/company/subway	subway	https://www.youtube.com/user/subway	subway	null	null	null	null	null	null	1,445,400	0.03	null	0.02	0.02	0.03	1,810	null	null	null	null	null	null	null	null	https://subway.com/en-us/restaurant/622-0/menu/?segment_code=0	null	null	2026-05-07T16:28:34.519290+00:00	2,237.46	0	14,372.15	194.8	201.8349	0.46	82.6	94.4	77.9	0.5458	null	0.7131	0.8478	0.7381	0.5556	0.3304	0.2556	85.7	86.9	null	null	null	81.82	9.09	9.09	94.64	3.57	1.79	89.41	9.41	1.18	stable	stable	null	-1.2	-0.025	-1.4	11	56	85	-60.7	-48.2	-100	70.6	9.5	64	100	85.9	56	138	519	179	16,786	59,570	21,850	183,106	941,735	247,599	196,863	138	12	28	8	61	113	63	110	134	85	284	null	null	null	null	null	null	null	0.2436	0.1971	0.6399	-0.1971	0.0732	0.5704	-0.0076	0.411	0.0076	0.3021	0.3813	0.1382	0.4841	-0.1382	0.229	133	27	112	12	18	8	0.5926	0.3704	0.7407	0.3704	0.5556	60.8	3.66	468	77.3	0.459	9.8	0.47	211	0.6	0.0868	61	90	63	0.4643	0.2054	0.4464	0.2321	0.3304	69.9	4.38	828	83.8	0.6107	0.7	-0.25	-149	-5.9	-0.0649	110	107	85	0.1805	Average	0.203	0.3684	0.203	0.2556	Below Average	75.2	4.39	986	84.4	Below Average	0.6548	-4.6	-0.26	-307	-6.5	-0.109	28	113	134	545	44	competitive	0.051	8.59	18.5	11.1	70.4	0	2,879	1,026	competitive	0.0073	1.43	1.8	7.1	81.3	9.8	6,915	5,014	competitive	0.0051	0.42	0	0	82.7	17.3	0.2014	0.6223	-0.2014	0.0908	131	132	119	116	80	0.0992	0.1221	0.3969	0.145	0.1679	75.7	4.45	929	86	0.6861	-5.1	-0.32	-250	-8.1	-0.1403	competitive	0.0055	1.01	0.8	77.1	22.1	0.1954	0.46	11.71	0.259	0.8413	-0.259	-0.1282	184	185	185	185	173	0	0	0.0652	0	0.0163	81.8	4.81	3,217	95.5	0.8766	-11.2	-0.68	-2,538	-17.6	-0.3308	competitive	0.0011	0.001	0.97	0.07	0.0196	0.064	0.2835	-0.064	0.4296	853,667	58.5	3.82	406	76.2	0.4631	12.1	0.31	273	0.0827	0.7619	0.3345	0.7689	0.4331	0.5231	200,344	0.6358	1.7	562,756	196,968	25.5	57.6	2.1	14.7	853,668	79	60	3.96	515	70.3	0.3831	10.6	0.17	164	0.1627	0.7051	0.4359	0.6538	0.5641	0.6026	24	63.45	23.09	0.7821	79	15.47	646	654	1.4368	14,367.84	0.09	117,055	116	0.0275	274.79	25.98	357.14	0.53	88.5	0.27	74.63	0.31	75.76	0.01	54.05	-1.6	-25.6	-10.2	0	6	0.2	-66.8	-0.14	136,115	-0.168	-68.14	245,033	-0.318	0.03	13,482	0	-67.93	223,731	-0.284	0.06	-25,509	0.049	-67.83	113,044	-0.146	-0.04	34	-0.058	-68.18	-94,246	-0.201	-0.03	3,871	-0.057	-68.11	-81,490	-0.108	0.5458	null	null	679	decelerating	0.1	0.7	3	3	28	92	0.774	0.779	0.779	0.952	0.717	186,454	197,394	196,667	1	448	decelerating	-0.4	null	86.54
X9ZKE8KD	JACQUELINES BAKERY & CAFÉ	Food and Drink	Restaurants	Restaurant	Restaurant	906 E New Haven Ave, Melbourne, FL 32901	906 E New Haven Ave	Melbourne	Florida	Camps Of Melbourne	null	32,901	US	true	28.078501	-80.605706	America/New_York	(321) 31-***	2	OPERATIONAL	true	true	null	true	Melbourne	Florida	US	https	https://jacquelinebakery.com	jacquelinebakery.com	jacquelinebakery.com	com	3,712	2016-03-08	2028-03-08	Wix.com Ltd.	purchase_dataset@jacquelinebakery.com	realdomain	1	1	0	null	true	false	4.34	1,098	{"1": 95, "2": 45, "3": 70, "4": 171, "5": 919}	Outdoor seating, Delivery, Onsite services, Takeout, Dine-in	Great coffee, Great dessert, Great tea selection, Serves local specialty	Breakfast, Lunch, Solo dining	"Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible restroom, (...TRUNCATED)	Coffee, Comfort food, Quick bite, Small plates	Breakfast, Brunch, Lunch, Dinner, Counter service, Dessert, Seating	Restroom, Wi-Fi	Casual, Cozy, Quiet, Trendy	Tourists	null	Credit cards, Debit cards, NFC mobile payments	Good for kids, High chairs	true	true	purchase_dataset@	true	true	5	2025-12-16	2026-02-13	142	83	24	142	142	83	83	https://www.instagram.com/jacquelines.bakery.suntree	jacquelines.bakery.suntree	https://www.facebook.com/jacquelines.bakery.downtown	jacquelines.bakery.downtown	https://twitter.com/suntreeseniors	suntreeseniors	null	null	https://www.linkedin.com/in/jacqueline-dittmore-1870b112a	jacqueline-dittmore-1870b112a	https://www.youtube.com/channel/ucjrvukplpd0z2v1yq6hyeiw	ucjrvukplpd0z2v1yq6hyeiw	null	null	null	null	null	null	484	1.41	null	1.61	1.41	1.41	560	null	null	null	null	null	null	null	null	https://jacquelinebakery.com/generalmenu	null	null	2026-05-07T16:04:11.577894+00:00	0.74	1	14,472.22	192.9	200.3058	0.46	86.8	100	82.7	0.6602	null	0.3714	0.266	0.5222	0.4634	0.4957	0.4961	68.6	76.1	null	null	null	81.82	18.18	0	66.04	24.53	9.43	77.78	17.09	5.13	stable	declining	null	-7.5	-0.1508	-9.9	11	53	117	-58.5	-62.4	-100	72.2	9.5	88	80	72.8	56	44	423	53	8,083	47,964	9,536	60,461	730,769	75,281	65,738	44	19	42	7	53	116	18	86	130	38	221	null	null	null	null	null	null	null	0.4923	0.1952	0.6154	-0.1952	-0.2443	0.5683	0.1635	0.4173	-0.1635	-0.0462	0.5713	0.1042	0.5247	-0.1042	-0.1536	129	41	115	19	30	7	0.561	0.2927	0.8537	0.2683	0.4634	63.3	4.1	655	84.3	0.623	8.9	0.24	443	-1.6	0.0372	53	79	18	0.5478	0.3217	0.8522	0.3391	0.4957	71	4.41	708	84.7	0.6289	1.2	-0.07	390	-2	0.0313	86	69	38	0.3411	Average	0.4729	0.7132	0.4186	0.4961	Average	74.1	4.36	1,012	83.7	Average	0.6282	-1.9	-0.02	86	-1	0.032	42	116	130	303	46	competitive	0.0393	13.05	14.6	12.2	58.5	14.6	3,662	1,410	competitive	0.0133	1.46	0.9	4.3	87	7.8	7,401	5,009	competitive	0.0083	0.41	0.8	0	84.5	14.7	0.203	0.6225	-0.203	-0.2514	130	131	101	91	32	0.2308	0.3077	0.7615	0.2923	0.3846	75.7	4.45	930	86	0.6855	-3.5	-0.11	168	-3.3	-0.0253	competitive	0.009	1	0.8	76.9	22.3	0.4131	0.46	11.62	0.2576	0.8381	-0.2576	-0.467	184	185	185	184	148	0	0.0054	0.2011	0	0.038	81.8	4.81	3,316	95.5	0.8765	-9.6	-0.47	-2,218	-12.8	-0.2163	competitive	0.0018	0.001	0.97	0.07	0.062	0.064	0.2835	-0.064	0.0876	853,667	58.5	3.82	406	76.2	0.4631	13.7	0.52	692	0.1971	0.8141	0.4849	0.9217	0.551	0.6711	156,005	0.7476	6.5	433,011	66,490	25.5	57.6	2.1	14.7	853,668	321	64	4.39	527	81.4	0.5615	8.2	-0.05	571	0.0987	0.6531	0.3281	0.8969	0.3969	0.5344	111	65.3	17.3	0.55	321	15.35	651	654	1.4271	14,271	0.09	117,055	116	0.0283	283.31	15.43	238.1	1.77	86.21	0.7	76.92	0.81	76.34	0.03	54.05	0.3	-27.3	-12.6	0.01	18	0.1	-84.4	-0.12	149,202	-0.19	-81.33	243,229	-0.319	0.04	-13,681	0.032	-81.31	202,284	-0.262	0.07	-19,944	0.044	-81.28	237,439	-0.311	-0.04	22	-0.034	-81.36	-31,097	-0.306	-0.01	2,373	-0.029	-81.22	-17,153	-0.203	0.6602	null	null	1,098	decelerating	0.03	0.23	1	1	27	127	0.481	0.488	0.49	0.238	0.324	354,748	377,618	375,705	15	1,226	decelerating	-0.5	null	82.6
PXZKSGHM	Hemingway's Tavern	Food and Drink	Restaurants	American restaurant	American restaurant, Bar, Restaurant	1800 W Hibiscus Blvd # 115, Melbourne, FL 32901	1800 W Hibiscus Blvd # 115	Melbourne	Florida	null	null	32,901	US	true	28.086404	-80.651823	America/New_York	(321) 80-***	2	OPERATIONAL	true	true	null	true	Melbourne	Florida	US	https	https://hemingwaystavern.com	hemingwaystavern.com	hemingwaystavern.com	com	4,035	2015-04-20	2035-09-22	GoDaddy.com, LLC	purchase_dataset@ldeateries.com	null	1	1	0	"Chill eatery inspired by writer Ernest Hemingway with eclectic meals, happy hours & outdoor seating(...TRUNCATED)	true	true	4.57	1,067	{"1": 92, "2": 65, "3": 214, "4": 773, "5": 3591}	Outdoor seating, Curbside pickup, Delivery, Onsite services, Takeout, Dine-in	"Fast service, Great beer selection, Great cocktails, Great coffee, Great dessert, Great wine list, (...TRUNCATED)	Breakfast, Lunch, Dinner, Solo dining	"Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible restroom, (...TRUNCATED)	"Alcohol, Beer, Cocktails, Coffee, Comfort food, Happy hour drinks, Happy hour food, Hard liquor, He(...TRUNCATED)	Breakfast, Brunch, Lunch, Dinner, Catering, Counter service, Dessert, Seating, Table service	Bar onsite, Gender-neutral restroom, Restroom, Wi-Fi	Casual, Cozy, Trendy	College students, Family-friendly, Groups, Tourists	Brunch reservations recommended, Accepts reservations	Credit cards, Debit cards, NFC mobile payments	Good for kids, High chairs, Kids' menu	true	true	purchase_dataset@	true	true	4	2022-01-19	2026-02-24	1,569	72	33	1,569	1,569	72	72	https://www.instagram.com/hemingwaystavern	hemingwaystavern	https://www.facebook.com/hemingwaystavern	hemingwaystavern	null	null	https://www.tiktok.com/@hemingways_tavern	hemingways_tavern	null	null	https://www.youtube.com/channel/uc6ulcvvqsu2nkyv3jrhsfbq	uc6ulcvvqsu2nkyv3jrhsfbq	null	null	null	null	null	null	3,716	0.95	null	0.83	0.95	0.95	1,127	50	3	63	2.18	null	null	null	null	https://hemingwaystavern.com/menus	null	null	2026-05-07T16:02:53.546531+00:00	5.75	0.2	14,634.24	232.4	201.8349	0.46	91.4	100	89.5	0.7879	null	0.6	0.842	0.8258	0.8438	0.8559	0.7669	80	91.3	null	null	null	80	20	0	93.18	6.82	0	92.06	7.54	0.4	stable	declining	null	-11.3	-0.2258	-12.4	5	88	252	-88.6	-92.1	-100	78.1	9.5	80	100	88	56	55	276	66	9,176	31,466	10,981	72,255	454,400	90,902	78,453	55	6	33	11	18	119	22	33	134	44	123	null	null	null	null	null	null	null	0.712	0.1543	0.6257	-0.1543	0.1243	0.7782	0.1771	0.2088	-0.1771	0.5412	0.8076	0.1349	0.5113	-0.1349	0.2387	133	32	118	6	8	11	0.8438	0.7813	0.6875	0.7813	0.8438	61.4	4.01	826	73.7	0.4287	16.7	0.56	241	15.8	0.3592	18	33	22	0.8559	0.7288	0.822	0.7288	0.8559	70.9	4.36	758	83.5	0.6071	7.2	0.21	309	6	0.1808	33	43	44	0.7594	Strong	0.6842	0.6767	0.6917	0.7669	Market Leader	74.3	4.38	920	84.2	Strong	0.6502	3.8	0.19	147	5.3	0.1377	33	119	134	704	43	competitive	0.0388	10.19	9.4	34.4	43.8	12.5	3,347	1,067	competitive	0.0118	1.5	0.8	3.4	89	6.8	7,318	5,024	competitive	0.0086	0.42	0.8	0	85.7	13.5	0.2014	0.622	-0.2014	0.128	131	132	44	49	40	0.6718	0.6336	0.7023	0.6412	0.7176	75.6	4.45	926	86	0.6842	2.5	0.12	141	3.5	0.1037	competitive	0.0087	1.01	0.8	77.1	22.1	0.6695	0.46	11.7	0.2601	0.8399	-0.2601	-0.0899	183	184	151	174	148	0.1803	0.0546	0.1967	0.0601	0.0874	81.8	4.81	3,196	95.5	0.877	-3.7	-0.24	-2,129	-6	-0.0891	competitive	0.0018	0.001	0.98	0.07	0.1475	0.064	0.2835	-0.064	0.4665	853,667	58.5	3.82	406	76.2	0.4631	19.6	0.75	661	0.3248	0.958	0.6807	0.9068	0.7613	0.857	34,607	0.8595	13.3	265,845	79,040	25.5	57.6	2.1	14.7	853,668	321	64	4.39	527	81.4	0.5615	14.1	0.18	540	0.2264	0.8688	0.5719	0.8656	0.6625	0.7688	42	65.3	24.02	0.7563	321	15.47	646	654	1.4322	14,322.02	0.08	117,695	116	0.0272	271.57	15.04	303.03	1.39	84.03	0.75	74.63	0.76	75.76	0.03	54.35	1.2	-17.9	-9.1	0	44	-0.1	-79.7	-0.02	95,983	-0.11	-91.85	370,769	-0.49	0.05	-10,178	0.029	-91.73	250,035	-0.326	0.05	-27,815	0.052	-91.67	243,064	-0.323	-0.02	-4	0.016	-91.5	-1,102	-0.077	-0.01	-687	0.015	-91.48	1,490	-0.045	0.7879	null	null	1,067	decelerating	0.03	0.23	1	1	32	278	0.481	0.488	0.49	0.625	0.312	354,748	377,618	375,705	7	810	decelerating	-0.54	null	89.32
RMJF7TDT	Wendy's	Food and Drink	Restaurants	Fast food restaurant	Fast food restaurant, Hamburger restaurant, Restaurant	950 N Wickham Rd, Melbourne, FL 32935	950 N Wickham Rd	Melbourne	Florida	null	null	32,935	US	true	28.122755	-80.672127	America/New_York	(321) 62-***	2	OPERATIONAL	true	true	null	true	Melbourne	Florida	US	https	https://locations.wendys.com/united-states/fl/melbourne/950-n-wickham-rd	locations.wendys.com/united-states/fl/melbourne/950-n-wickham-rd	locations.wendys.com	com	11,114	1995-12-01	2026-11-30	MarkMonitor, Inc.	null	null	0	0	0	Fast-food burger chain serving sides such as chili & baked potatoes.	true	true	3.53	1,013	{"1": 211, "2": 78, "3": 197, "4": 299, "5": 477}	Delivery, Drive-through, Onsite services, Takeout, Dine-in	null	Breakfast, Lunch, Dinner, Solo dining	Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible restroom	Coffee, Late-night food, Quick bite	Breakfast, Lunch, Dinner, Counter service, Dessert, Seating	Restroom, Wi-Fi	Casual	Family-friendly, Groups	null	Credit cards, Debit cards, NFC mobile payments	Good for kids, Has changing table(s), High chairs, Kids' menu	true	true	purchase_dataset@	true	true	3	null	null	null	null	null	null	null	null	null	null	null	https://www.facebook.com/wendys22006northernblvd	wendys22006northernblvd	https://twitter.com/wendys	wendys	null	null	https://www.linkedin.com/company/wendys-international	wendys-international	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	https://order.wendys.com/us/en/national/menu?site=menu&lang=en_us%2F%3Futm_source%3Dyext	null	null	2026-05-07T15:44:52.134998+00:00	0	4.4	14,448.03	294	203.3639	0.45	70.6	100	59.5	0.2181	null	-0.3333	-0.076	-0.0202	0.1724	0.1048	0.0079	33.3	49	null	null	null	33.33	66.67	0	42.86	47.62	9.52	47.69	46.15	6.15	stable	declining	null	-15.7	-0.3131	-32	3	21	65	-71.4	-81.5	-100	55.8	9.5	32	80	44.8	56	90	635	109	11,299	75,928	13,906	100,855	1,246,111	131,369	109,103	90	24	30	6	97	106	27	126	127	60	347	null	null	null	null	null	null	null	0.1627	0.1631	0.6011	-0.1631	-0.9344	0.3724	0.1355	0.3302	-0.1355	-0.6635	0.2743	0.1293	0.4864	-0.1293	-0.8197	126	29	105	24	26	6	0.2069	0.1379	0.8276	0.1379	0.1724	62.8	3.74	507	75.3	0.4589	-7	-0.21	506	-15.8	-0.2408	97	101	27	0.0857	0.0476	0.7524	0.0571	0.1048	67.7	4.35	620	83.1	0.6056	-11.9	-0.82	393	-23.6	-0.3875	126	127	60	0.0079	Below Average	0	0.5317	0	0.0079	Below Average	75	4.43	970	85.6	Emerging	0.6667	-19.2	-0.9	43	-26.1	-0.4486	30	106	127	408	79	competitive	0.0645	9.23	10.3	17.2	69	3.4	3,378	1,005	competitive	0.0153	1.34	1.9	13.3	79	5.7	7,683	5,001	competitive	0.0082	0.4	0.8	0	79.4	19.8	0.1999	0.623	-0.1999	-0.9563	132	133	132	133	59	0.0076	0	0.5606	0	0	75.6	4.45	927	86	0.685	-19.8	-0.92	86	-26.5	-0.4669	competitive	0.0082	1.02	0.8	77.3	22	0.1712	0.45	11.78	0.2632	0.8369	-0.2632	-1.1702	182	183	183	183	153	0	0	0.1648	0	0.0055	81.8	4.81	3,223	95.5	0.8765	-26	-1.28	-2,210	-36	-0.6584	competitive	0.0017	0.001	0.98	0.07	0.0494	0.064	0.2835	-0.064	-0.6168	853,667	58.5	3.82	406	76.2	0.4631	-2.7	-0.29	607	-0.245	0.2981	0.11	0.8718	0.1942	0.2399	597,414	0.4138	-16.7	758,016	109,014	25.5	57.6	2.1	14.7	853,668	79	60	3.96	515	70.3	0.3831	-4.2	-0.43	498	-0.165	0.2436	0.1923	0.7692	0.3077	0.3077	59	63.45	8.13	0.4231	79	15.59	642	654	1.4448	14,448.03	0.08	118,342	116	0.0272	272.34	41.58	333.33	2.35	94.34	0.68	78.74	0.67	75.19	0.03	54.64	3.9	-17.9	-14.4	0	8	-0.2	-77.5	-0.08	15,324	-0.007	-56.44	-19,519	0.041	0.07	-53,131	0.091	-56.54	121,707	-0.139	0	55,110	-0.06	-56.42	-41,062	0.068	0.01	4	0.031	-56.86	-289,843	-0.415	0	2,054	0.002	-56.82	-250,075	-0.341	0.2181	null	null	1,013	decelerating	0.03	0.23	1	1	7	70	0.481	0.488	0.49	0.317	0.239	354,748	377,618	375,705	20	2,934	decelerating	-0.14	null	71.58
QMP8EQPK	Firehouse Subs FIT Melbourne	Food and Drink	Restaurants	Sandwich shop	Sandwich shop	150 W University Blvd, Melbourne, FL 32901	150 W University Blvd	Melbourne	Florida	null	null	32,901	US	true	28.064499	-80.623116	America/New_York	null	2	CLOSED_TEMPORARILY	false	true	null	true	Melbourne	Florida	US	https	https://firehousesubs.com	firehousesubs.com	firehousesubs.com	com	10,031	1998-11-18	2027-11-17	CSC Corporate Domains, Inc.	null	null	0	0	0	null	true	false	4.71	7	{"1": 0, "2": 0, "3": 1, "4": 0, "5": 10}	Takeout	null	Lunch, Dinner, Solo dining	"Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible restroom, (...TRUNCATED)	Comfort food, Quick bite	Lunch, Dinner, Dessert	Restroom	Casual	College students, Tourists	null	Credit cards, Debit cards, NFC mobile payments	Good for kids, Kids' menu	false	true	purchase_dataset@	false	false	0	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	https://firehousesubs.com/our-food	null	null	2026-05-07T15:08:17.203892+00:00	0	6.6	14,400.67	1,168	201.8349	0.46	94.2	30.1	85.7	0.5961	null	null	0.0721	0.6907	1	0.4355	0.373	null	84.5	null	null	null	null	null	null	0	0	100	66.67	0	33.33	stable	stable	null	null	null	null	0	1	3	-100	-100	null	48.8	9.5	8	40	63.2	56	354	191	619	44,882	22,421	77,030	662,942	314,003	1,251,937	714,475	354	5	6	6	125	125	125	126	127	127	73	null	null	null	null	null	null	null	0.2722	0.1597	0.5708	-0.1597	-0.5708	0.38	-0.0569	0.0888	0.0569	-0.0888	0.2564	0.1737	0.5705	-0.1737	-0.5705	126	5	124	5	1	6	0.2	1	0	0.8	1	56.7	3.9	257	71.5	0.3256	-7.9	0.81	-250	14.2	0.2705	125	19	125	0	0.8548	0	0.5645	0.4355	73.4	4.35	992	83.2	0.6023	-24.6	0.36	-985	2.5	-0.0062	126	14	127	0.0079	Below Average	0.8968	0	0.5238	0.373	Below Average	73.2	4.37	854	83.8	Below Average	0.6313	-24.4	0.34	-847	1.9	-0.0352	6	125	127	379	208	concentrated	0.0054	1.59	0	80	20	0	3,219	1,454	competitive	0.0001	1.58	0	2.4	87.9	9.7	7,449	5,001	competitive	0.0001	0.4	0.8	0	85.7	13.5	0.2014	0.6206	-0.2014	-0.6206	131	132	131	21	132	0.0076	0.8473	0	0.4122	0.2519	75.7	4.45	931	86	0.6853	-26.9	0.26	-924	-0.3	-0.0892	competitive	0.0001	1.01	0.8	77.1	22.1	0.2572	0.46	11.71	0.2552	0.8359	-0.2552	-0.8359	183	184	184	157	184	0	0.1475	0	0.0273	0.0164	81.8	4.81	3,212	95.5	0.877	-33	-0.1	-3,205	-9.8	-0.2809	competitive	0	0.001	0.98	0.07	0.0443	0.064	0.2835	-0.064	-0.2835	853,667	58.5	3.82	406	76.2	0.4631	-9.7	0.89	-399	0.133	0.1912	0.7749	0.1582	0.6401	0.583	689,740	0.3564	9.5	187,223	713,458	25.5	57.6	2.1	14.7	853,668	79	60	3.96	515	70.3	0.3831	-11.2	0.75	-508	0.213	0.1923	0.8077	0.1667	0.7564	0.6923	64	63.45	22.26	0.7308	79	15.47	646	654	1.4401	14,400.67	0.08	117,695	116	0.0273	272.92	0.29	1,666.67	0	80	0	78.74	0	75.76	0	54.35	-6.7	-27.9	-0.8	0	0	0	-6.3	0.03	2,729	0.026	-34.61	-47,560	0.102	0.02	20,365	-0.019	-34.23	-482,353	0.66	0.05	-17,163	0.041	-34.53	-321,848	0.456	-0.06	47	-0.06	-34.59	-687,768	0.013	-0.07	10,141	-0.136	-34.47	-645,567	0.044	0.5961	null	null	7	decelerating	0.03	0.23	1	1	3	5	0.481	0.488	0.49	0.381	0.36	354,748	377,618	375,705	8	908	stable	-0.04	null	85.71
8UX2RNW4	Long Doggers	Food and Drink	Restaurants	American restaurant	American restaurant	890 N Miramar Ave, Indialantic, FL 32903	890 N Miramar Ave	Melbourne	Florida	Melbourne Beach	null	32,903	US	true	28.098442	-80.569286	America/New_York	(321) 72-***	2	null	true	true	null	true	Melbourne	Florida	US	https	https://longdoggers.com	longdoggers.com	longdoggers.com	com	10,354	1997-12-31	2027-12-30	TLDS L.L.C. d/b/a SRSPlus	null	null	0	0	0	Laid-back American eatery dispensing wings, burgers & beer in beachy digs with outdoor seats.	true	true	4.5	1,025	{"1": 50, "2": 49, "3": 125, "4": 457, "5": 1890}	Outdoor seating, Curbside pickup, Delivery, Drive-through, Onsite services, Takeout, Dine-in	Fast service, Great beer selection, Serves local specialty, Sports	Lunch, Dinner, Solo dining	"Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible restroom, (...TRUNCATED)	"Alcohol, Beer, Coffee, Comfort food, Happy hour drinks, Happy hour food, Healthy options, Late-nigh(...TRUNCATED)	Lunch, Dinner, Catering, Counter service, Dessert, Seating, Table service	Bar onsite, Restroom, Wi-Fi	Casual, Cozy, Trendy	College students, Family-friendly, Groups, Tourists	null	Credit cards, Debit cards, NFC mobile payments	Good for kids, High chairs, Kids' menu	true	true	purchase_dataset@	true	true	5	2024-10-24	2026-02-23	560	73	66	560	560	73	73	https://www.instagram.com/longdoggerssatellite	longdoggerssatellite	https://www.facebook.com/longdoggers	longdoggers	https://twitter.com/long_doggers	long_doggers	https://www.tiktok.com/@ldsatellitebeach	ldsatellitebeach	https://www.linkedin.com/company/long-doggers	long-doggers	null	null	null	null	null	null	null	null	3,528	1.24	null	1.6	1.24	1.24	2,032	1,008	29	1,389	4.89	null	3.49	3.81	4.71	https://longdoggers.com/menus	null	null	2026-05-07T14:52:43.380183+00:00	5.46	0.2	15,027.57	193.9	201.8349	0.46	90	100	88	0.7725	null	1	0.8175	0.7618	0.6429	0.7172	0.7258	100	88.1	null	null	null	100	0	0	91.84	8.16	0	88.89	10.46	0.65	stable	improving	null	11.9	0.2382	13.5	3	49	153	-87.8	-92.2	-100	77.7	9.5	100	80	96.4	56	85	324	103	10,955	36,441	13,413	94,918	535,367	122,495	102,776	85	7	29	7	17	100	29	32	125	55	156	null	null	null	null	null	null	null	0.6508	0.1739	0.587	-0.1739	0.413	0.6893	0.0695	0.4232	-0.0695	0.5768	0.696	0.1407	0.4324	-0.1407	0.5676	124	28	99	7	16	7	0.7857	0.4643	0.7857	0.5	0.6429	66.6	4.29	508	83.1	0.6052	11.1	0.21	517	4.9	0.1673	17	52	29	0.8384	0.4848	0.7172	0.4949	0.7172	64.9	4.25	563	84.7	0.603	12.8	0.25	462	3.3	0.1695	32	50	55	0.75	Strong	0.6048	0.5645	0.5968	0.7258	Strong	73.1	4.37	947	83.5	Strong	0.6187	4.6	0.13	78	4.5	0.1538	29	100	125	641	41	competitive	0.0672	8.91	7.1	14.3	71.4	7.1	4,156	1,069	competitive	0.0181	1.26	9.1	16.2	61.6	13.1	7,520	5,023	competitive	0.0087	0.39	0	4	83.9	12.1	0.2014	0.6201	-0.2014	0.3799	131	132	49	62	57	0.6336	0.5344	0.5725	0.5649	0.687	75.6	4.45	926	86	0.6843	2.1	0.05	99	2	0.0882	competitive	0.0084	1.01	0.8	77.1	22.1	0.5855	0.46	11.7	0.2561	0.8381	-0.2561	0.1619	184	185	157	179	154	0.1522	0.0326	0.1685	0.0326	0.0707	81.8	4.81	3,191	95.5	0.8769	-4.1	-0.31	-2,166	-7.5	-0.1044	competitive	0.0017	0.001	0.97	0.07	0.1212	0.064	0.2835	-0.064	0.7165	853,667	58.5	3.82	406	76.2	0.4631	19.2	0.68	619	0.3094	0.952	0.6206	0.8787	0.7154	0.8368	39,660	0.8306	11.8	313,297	102,936	25.5	57.6	2.1	14.7	853,668	321	64	4.39	527	81.4	0.5615	13.7	0.11	498	0.211	0.8469	0.4938	0.8031	0.6031	0.75	47	65.3	22.6	0.7063	321	15.47	646	654	1.4327	14,326.98	0.09	117,055	116	0.0273	272.62	45.13	344.83	3.26	100	0.75	80	0.7	75.76	0.03	54.05	3	0	-5.2	0	3	0	-79.6	-0.03	11,256	-0.01	-89.22	69,969	-0.091	-0.05	26,412	-0.01	-89.6	474,029	-0.61	0.07	-13,796	0.037	-89.31	275,645	-0.36	-0.06	30	-0.056	-89.19	-33,681	-0.148	-0.04	2,925	-0.046	-89.14	-26,156	-0.091	0.7725	null	null	1,025	decelerating	0.23	1.63	7	7	36	185	0.816	0.822	0.822	0.778	0.56	142,983	148,636	148,433	4	585	decelerating	-0.44	null	87.9
TGUJ5Y4J	Eve La Cubanita	Food and Drink	Restaurants	Cuban restaurant	Cuban restaurant, Coffee shop, Latin American restaurant, Sandwich shop, Spanish restaurant	2001 S Harbor City Blvd, Melbourne, FL 32901	2001 S Harbor City Blvd	Melbourne	Florida	null	null	32,901	US	true	28.078675	-80.602572	America/New_York	(407) 92-***	2	OPERATIONAL	true	true	null	true	Melbourne	Florida	US	null	null	null	null	null	null	null	null	null	null	null	0	0	0	null	true	false	5	80	{"1": 0, "2": 0, "3": 0, "4": 0, "5": 119}	Outdoor seating, Curbside pickup, Onsite services, Takeout, Dine-in	Serves local specialty	Lunch, Dinner, Solo dining	Wheelchair accessible entrance, Wheelchair accessible parking lot	Alcohol, Coffee, Comfort food, Late-night food, Quick bite, Small plates	Breakfast, Lunch, Dinner, Catering, Counter service, Dessert, Seating	Bar onsite, Restroom	Casual, Quiet	null	null	Credit cards, Debit cards	null	false	false	purchase_dataset@	false	true	0	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	2026-05-07T11:29:26.534799+00:00	0	6.1	14,400.67	1,167.3	201.8349	0.46	100	63.6	100	0.8745	null	0.8416	0.7493	0.8745	0.8378	0.9478	0.9612	92.1	93.7	null	null	null	100	0	0	96.77	0	3.23	98.75	0	1.25	stable	stable	null	-1.6	-0.0329	-1.7	5	31	80	-67.7	-75	-100	64.8	9.5	8	30	87.8	56	309	5	483	36,648	221	57,065	529,646	1,639	871,187	568,690	309	26	38	28	103	116	109	125	130	128	3	null	null	null	null	null	null	null	0.3202	0.1973	0.5991	-0.1973	0.2425	0.5108	0.1812	0.4138	-0.1812	0.4278	0.3635	0.1042	0.5395	-0.1042	0.3021	129	37	115	26	1	28	0.3243	1	0.2703	1	0.8378	64.7	4.27	706	85.2	0.6503	0.1	0.73	-626	14.8	0.2242	103	1	109	0.113	1	0.0609	1	0.9478	71.4	4.43	700	85.2	0.634	-6.6	0.57	-620	14.8	0.2405	125	1	128	0.0388	Average	1	0.0155	1	0.9612	Below Average	74.1	4.36	1,013	83.6	Below Average	0.6208	-9.3	0.64	-933	16.4	0.2537	38	116	130	372	0	competitive	0.0031	11.78	10.8	13.5	59.5	16.2	3,665	1,080	competitive	0.001	1.46	0.9	3.5	87.8	7.8	7,474	5,071	competitive	0.0006	0.41	0.8	0	84.5	14.7	0.2014	0.6206	-0.2014	0.221	131	132	129	1	130	0.0229	1	0.0153	1	0.9313	75.7	4.45	931	86	0.6853	-10.9	0.55	-851	14	0.1892	competitive	0.0007	1.01	0.8	77.1	22.1	0.3138	0.46	11.71	0.2552	0.8359	-0.2552	0.0057	183	184	184	1	184	0	1	0	1	0.3388	81.8	4.81	3,212	95.5	0.877	-17	0.19	-3,132	4.5	-0.0025	competitive	0.0001	0.001	0.98	0.07	0.3	0.064	0.2835	-0.064	0.5581	853,667	58.5	3.82	406	76.2	0.4631	6.3	1.18	-326	0.4114	0.5581	0.8662	0.3315	0.9376	0.9424	374,263	0.5825	23.8	74,545	569,352	25.5	57.6	2.1	14.7	853,668	321	64	4.39	527	81.4	0.5615	0.8	0.61	-447	0.313	0.3594	0.8594	0.2469	0.9281	0.9031	206	65.3	12.62	0.4344	321	15.47	646	654	1.4401	14,400.67	0.08	117,695	116	0.0273	272.92	0.09	263.16	0.01	86.21	0	76.92	0	75.76	0	54.35	-0.4	-40	5	0	6	0	-22.7	-0.07	107,604	-0.136	-50.33	-261,835	0.372	0.03	898	0.011	-50.49	-269,729	0.377	0.07	-24,142	0.05	-50.68	-201,204	0.291	0	-2	0.033	-50.73	-530,479	0.016	-0.01	231	0.023	-50.67	-504,216	0.151	0.8745	null	null	80	decelerating	0.03	0.23	1	1	20	80	0.481	0.488	0.49	0.4	0.338	354,748	377,618	375,705	4	375	decelerating	-0.34	null	77.92
X8Q6PB5M	Mustard's Famous Hot Dogs	Food and Drink	Restaurants	Hot dog restaurant	Hot dog restaurant, Fast food restaurant	415 E New Haven Ave, Melbourne, FL 32901, United States	415 E New Haven Ave	Melbourne	Florida	null	null	32,901	US	true	28.07839	-80.613553	America/New_York	+1 321-9-**	2	OPERATIONAL	true	true	null	true	Melbourne	Florida	US	http	http://mustardslaststand.us	mustardslaststand.us	mustardslaststand.us	us	5,425	2011-06-30	2026-06-29	GoDaddy.com, LLC	purchase_dataset@mustardsfamoushotdogs.com, purchase_dataset@mustardslaststand.us	realdomain	2	2	0	"Quick-serve hot dogs & fries are the focus of this joint with a quirky eat-in space & outdoor seats(...TRUNCATED)	true	true	4.58	1,049	{"1": 59, "2": 27, "3": 108, "4": 424, "5": 2132}	Outdoor seating, Drive-through, On-site services, Takeaway, Dine-in	Fast service, Serves local specialty	Lunch, Dinner, Solo dining	"Wheelchair-accessible car park, Wheelchair-accessible entrance, Wheelchair-accessible seating, Whee(...TRUNCATED)	Alcohol, Beer, Comfort food, Quick bite, Small plates	Lunch, Dinner, Counter service, Dessert, Seating	Toilet	Casual, Cosy, Trendy	Family friendly, Groups, Tourists, University students	null	Credit cards, Debit cards, NFC mobile payments	Good for kids, High chairs, Kids' menu	true	true	purchase_dataset@	true	true	4	2024-03-15	2026-01-22	783	105	24	783	783	105	105	https://www.instagram.com/mustardslaststand	mustardslaststand	https://www.facebook.com/mustardslast	mustardslast	https://twitter.com/biggus_doggus	biggus_doggus	null	null	https://www.linkedin.com/company/mustards-last-stand	mustards-last-stand	null	null	null	null	null	null	null	null	1,307	11.19	null	null	2.22	3.44	103	null	null	null	null	null	null	null	null	https://places.singleplatform.com/mustards-last-stand-4/menu	null	null	2026-05-07T11:28:43.438467+00:00	2.02	0.5	15,927.02	232.7	201.8349	0.46	91.6	100	90.7	0.5119	null	0.5196	0.5396	0.5537	0.2703	0.2564	0.2214	76	77.7	null	null	null	83.33	0	16.67	89.19	5.41	5.41	92.38	4.76	2.86	stable	stable	null	-1.7	-0.0341	-2.2	6	37	105	-67.6	-77.1	-100	75.7	9.5	92	100	66.8	56	68	268	82	9,959	30,759	12,058	81,381	443,270	103,551	88,246	68	14	38	11	35	118	33	52	132	53	120	null	null	null	null	null	null	null	0.6382	0.186	0.6088	-0.186	-0.0679	0.6648	0.1407	0.3912	-0.1407	0.1497	0.712	0.1234	0.5598	-0.1234	-0.0189	131	37	117	14	15	11	0.6486	0.6216	0.7297	0.6757	0.2703	61.9	4.05	681	83.6	0.596	13.8	0.53	368	7.1	-0.0841	35	36	33	0.7094	0.7009	0.7265	0.7607	0.2564	71.9	4.35	804	82.9	0.6025	3.8	0.23	245	7.8	-0.0906	52	39	53	0.6107	Strong	0.7099	0.6031	0.7481	0.2214	Strong	74.2	4.38	975	84.3	Average	0.6409	1.5	0.2	74	6.4	-0.129	38	118	132	657	41	competitive	0.04	11.78	18.9	10.8	54.1	16.2	3,530	1,015	competitive	0.011	1.49	0	3.4	89.7	6.8	7,398	5,022	competitive	0.0081	0.42	0.8	0	84	15.3	0.2014	0.6236	-0.2014	-0.0827	131	132	71	46	49	0.4656	0.6565	0.6336	0.6947	0.1221	75.6	4.45	926	85.9	0.6863	0.1	0.13	123	4.8	-0.1744	competitive	0.0086	1.01	0.8	77.1	22.1	0.5733	0.46	11.7	0.259	0.84	-0.259	-0.2991	184	185	179	173	152	0.0326	0.0652	0.1793	0.087	0.0109	81.8	4.81	3,238	95.5	0.8764	-6.1	-0.23	-2,189	-4.8	-0.3645	competitive	0.0018	0.001	0.97	0.07	0.0864	0.064	0.2835	-0.064	0.2574	853,667	58.5	3.82	406	76.2	0.4631	17.2	0.76	643	0.0488	0.9125	0.6886	0.8955	0.7963	0.4859	72,702	0.8402	14.5	259,565	88,620	25.5	57.6	2.1	14.7	853,668	79	60	3.96	515	70.3	0.3831	15.7	0.62	534	0.1288	0.8718	0.7436	0.8333	0.8462	0.5128	10	63.45	-20.65	0.2051	79	15.47	646	654	1.4324	14,324.15	0.09	117,055	116	0.0277	276.65	15.99	263.16	1.22	84.75	0.66	75.76	0.74	75.76	0.03	54.05	3	0	-11.4	0	10	0	-81.3	-0.18	234,919	-0.303	-93.47	345,471	-0.457	0.04	-20,745	0.04	-93.39	196,907	-0.258	0.06	-12,846	0.034	-93.37	265,458	-0.351	-0.1	84	-0.187	-93.28	-757	-0.266	-0.06	8,926	-0.15	-93.25	10,329	-0.191	0.5119	null	null	1,049	decelerating	0.33	2.33	10	10	39	137	0.892	0.896	0.896	1	0.843	87,059	90,435	90,390	1	8	decelerating	0.06	null	42.8
VJU48DHS	Firehouse Subs Post	Food and Drink	Restaurants	Sandwich shop	Sandwich shop, Caterer	4100 N Wickham Rd #107, Melbourne, FL 32935	4100 N Wickham Rd #107	Melbourne	Florida	null	null	32,935	US	true	28.17287	-80.67379	America/New_York	(321) 75-***	2	OPERATIONAL	true	true	null	true	Melbourne	Florida	US	https	https://firehousesubs.com	firehousesubs.com	firehousesubs.com	com	10,031	1998-11-18	2027-11-17	CSC Corporate Domains, Inc.	"purchase_dataset@whopper.com, purchase_dataset@firehousesubs.com, purchase_dataset@firehousesubs.co(...TRUNCATED)	realdomain	10	0	10	Counter-serve sandwich chain offering made-to-order hot & cold subs, plus a variety of hot sauces.	true	true	4.11	352	{"1": 45, "2": 14, "3": 22, "4": 62, "5": 224}	Delivery, Onsite services, Takeout, Dine-in	null	Lunch, Dinner, Solo dining	"Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible restroom, (...TRUNCATED)	Comfort food, Healthy options, Quick bite, Vegetarian options	Lunch, Dinner, Catering, Counter service, Dessert, Seating	Restroom	Casual, Quiet	College students, Family-friendly, Groups, Tourists	null	Credit cards, Debit cards, NFC mobile payments	Good for kids, High chairs, Kids' menu	true	true	purchase_dataset@	true	true	6	2023-09-25	2026-02-13	955	83	87	955	955	83	83	https://www.instagram.com/firehousesubs	firehousesubs	https://www.facebook.com/firehousesubs	firehousesubs	https://twitter.com/firehousesubs	firehousesubs	https://www.tiktok.com/@firehousesubs	firehousesubs	https://www.linkedin.com/company/firehouse-subs	firehouse-subs	https://www.youtube.com/firehousesubs	firehousesubs	null	null	null	null	null	null	108,753	0.18	null	0.13	0.18	0.18	979	43,847	70	951,376	0.11	null	null	1.7	1.27	https://order.firehousesubs.com/menu?store-number=37	null	null	2026-05-07T11:02:01.863301+00:00	168.35	0	14,432.39	167	201.8349	0.46	82.2	84.9	77.8	0.5314	null	1	0.7131	0.7384	0.5	0.4167	0.248	100	86.9	null	null	null	100	0	0	87.5	12.5	0	87.5	12.5	0	stable	improving	null	13.1	0.2616	15.1	1	16	32	-87.5	-87.5	-100	71.4	9.5	72	100	95	56	213	528	292	24,973	60,540	34,739	316,157	959,129	456,631	338,865	213	10	23	15	28	85	45	84	126	93	290	null	null	null	null	null	null	null	0.2592	0.166	0.5103	-0.166	0.4897	0.4682	0.108	0.3667	-0.108	0.6333	0.5107	0.1133	0.4051	-0.1133	0.5949	125	22	84	10	14	15	0.5909	0.4091	0.3636	0.4091	0.5	67	3.97	534	76.9	0.4953	4.4	0.14	-182	0.9	0.0361	28	58	45	0.6786	0.3214	0.4762	0.3333	0.4167	62.3	3.83	468	79.2	0.5153	9.1	0.28	-116	-1.4	0.0161	84	107	93	0.336	Average	0.152	0.264	0.168	0.248	Average	73.5	4.41	821	85	Below Average	0.6444	-2.1	-0.3	-469	-7.2	-0.113	23	85	126	388	18	competitive	0.0291	7	4.5	18.2	63.6	13.6	3,431	1,026	competitive	0.0089	1.07	15.5	9.5	71.4	3.6	7,757	5,027	competitive	0.0034	0.4	0	0.8	85.6	13.6	0.2014	0.6201	-0.2014	0.3799	131	132	111	118	112	0.1603	0.1069	0.1527	0.1374	0.1603	75.7	4.45	931	86	0.6862	-4.3	-0.34	-579	-8.2	-0.1548	competitive	0.0029	1.01	0.8	77.1	22.1	0.142	0.46	11.71	0.2635	0.8394	-0.2635	0.1606	183	184	184	184	181	0	0	0.0164	0	0.0109	81.9	4.81	3,226	95.5	0.8772	-10.5	-0.7	-2,874	-17.7	-0.3458	competitive	0.0006	0.001	0.98	0.07	0.0049	0.064	0.2835	-0.064	0.7165	853,667	58.5	3.82	406	76.2	0.4631	12.9	0.29	-54	0.0683	0.7884	0.3236	0.6023	0.4296	0.5071	177,844	0.5931	1.6	572,479	338,901	25.5	57.6	2.1	14.7	853,668	79	60	3.96	515	70.3	0.3831	11.4	0.15	-163	0.1483	0.7436	0.4231	0.4872	0.5513	0.5769	21	63.45	19.98	0.641	79	15.47	646	654	1.4406	14,406.46	0.08	117,695	116	0.0274	274.07	8.45	434.78	0.79	117.65	0.12	79.37	0.08	75.76	0	54.35	-2.5	-33.3	-5	0	3	-0.1	-50.2	-0.05	20,477	-0.023	-58.58	-55,102	0.083	-0.04	56,038	-0.044	-59.09	434,479	-0.548	0.07	-18,602	0.043	-58.69	140,837	-0.174	0	-9	0.037	-58.96	-176,555	-0.158	-0.03	-374	0.021	-59	-161,806	-0.046	0.5314	null	null	352	decelerating	0.03	0.23	1	1	7	35	0.481	0.488	0.49	0.381	0.36	354,748	377,618	375,705	8	908	decelerating	-0.07	null	83.43
9XNX34SW	Firehouse Subs Eau Gallie Blvd	Food and Drink	Restaurants	Sandwich shop	Sandwich shop, Caterer, Restaurant	981 E Eau Gallie Blvd B, Indian Harbour Beach, FL 32937	981 E Eau Gallie Blvd B	Melbourne	Florida	null	null	32,937	US	true	28.13705	-80.58324	America/New_York	(321) 24-***	2	null	true	true	null	true	Melbourne	Florida	US	https	https://firehousesubs.com	firehousesubs.com	firehousesubs.com	com	10,031	1998-11-18	2027-11-17	CSC Corporate Domains, Inc.	"purchase_dataset@whopper.com, purchase_dataset@firehousesubs.com, purchase_dataset@firehousesubs.co(...TRUNCATED)	realdomain	11	0	11	Counter-serve sandwich chain offering made-to-order hot & cold subs, plus a variety of hot sauces.	true	true	4.19	197	{"1": 23, "2": 4, "3": 13, "4": 25, "5": 134}	Delivery, Onsite services, Takeout, Dine-in	null	Lunch, Solo dining	"Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible restroom, (...TRUNCATED)	Comfort food, Quick bite	Lunch, Catering, Counter service, Dessert, Seating	Restroom	Casual	Tourists	null	Credit cards, Debit cards, NFC mobile payments	Good for kids, High chairs, Kids' menu	true	true	purchase_dataset@	true	true	7	2023-09-25	2026-02-13	955	83	87	955	955	83	83	https://www.instagram.com/firehousesubs	firehousesubs	https://www.facebook.com/firehousesubs	firehousesubs	https://twitter.com/firehousesubs	firehousesubs	https://www.tiktok.com/@firehousesubs	firehousesubs	https://www.linkedin.com/company/firehouse-subs	firehouse-subs	https://www.youtube.com/firehousesubs	firehousesubs	null	null	null	null	https://www.pinterest.com/firehousesubskingstowne	firehousesubskingstowne	108,753	0.18	null	0.13	0.18	0.18	979	43,847	70	951,376	0.11	null	null	1.7	1.27	https://order.firehousesubs.com/menu?store-number=1683	null	null	2026-05-07T10:46:36.474289+00:00	168.35	0	14,450.72	146.2	201.8349	0.46	83.8	76.6	79.2	0.5808	null	1	0.3333	0.3913	0.4783	0.4074	0.2698	100	69.6	null	null	null	100	0	0	66.67	33.33	0	69.57	30.43	0	stable	improving	null	30.4	0.6087	43.7	3	12	23	-50	-47.8	-100	71.7	9.5	80	100	95.2	56	262	499	370	30,809	57,025	44,761	418,373	893,582	633,939	448,196	262	9	24	12	33	82	52	92	127	122	270	null	null	null	null	null	null	null	0.1778	0.1823	0.5937	-0.1823	0.4063	0.5087	0.0962	0.374	-0.0962	0.626	0.4383	0.1084	0.441	-0.1084	0.559	126	23	81	9	17	12	0.6522	0.3043	0.5217	0.3478	0.4783	63.9	4.06	580	79	0.5071	7.8	0.13	-383	0.2	0.0737	33	59	52	0.6049	0.284	0.3704	0.284	0.4074	63.2	4.04	496	81.4	0.5749	8.5	0.15	-299	-2.2	0.0059	92	104	122	0.2778	Average	0.1825	0.0397	0.2063	0.2698	Average	74.9	4.41	902	84.9	Emerging	0.6495	-3.2	-0.22	-705	-5.7	-0.0687	24	82	127	356	9	competitive	0.0146	7.32	13	17.4	60.9	8.7	3,227	1,056	competitive	0.0049	1.03	14.8	9.9	64.2	11.1	7,841	5,122	competitive	0.0017	0.4	0	0.8	80.2	19	0.2014	0.6201	-0.2014	0.3799	131	132	105	111	126	0.2061	0.1603	0.0458	0.1832	0.229	75.7	4.45	932	86	0.6858	-4	-0.26	-735	-6.8	-0.105	competitive	0.0016	1.01	0.8	77.1	22.1	0.1443	0.46	11.71	0.2575	0.8374	-0.2575	0.1626	183	184	184	184	182	0	0	0.0109	0	0.0164	81.8	4.81	3,202	95.5	0.8771	-10.1	-0.62	-3,005	-16.3	-0.2963	competitive	0.0003	0.001	0.98	0.07	0.0033	0.064	0.2835	-0.064	0.7165	853,667	58.5	3.82	406	76.2	0.4631	13.2	0.37	-209	0.1177	0.7982	0.3719	0.4739	0.4604	0.5642	169,449	0.573	3	530,764	448,259	25.5	57.6	2.1	14.7	853,668	79	60	3.96	515	70.3	0.3831	11.7	0.23	-318	0.1977	0.7692	0.5	0.3846	0.6282	0.641	19	63.45	20.65	0.6923	79	15.47	646	654	1.4425	14,424.76	0.08	117,695	116	0.0272	272.02	2.12	416.67	0.24	121.95	0.03	78.74	0.03	75.76	0	54.35	-2.4	-27.9	-2.4	0.01	4	0.4	-37.3	-0.09	90,549	-0.112	-53.31	13,834	-0.006	-0.05	33,012	-0.017	-53.8	318,996	-0.396	0.05	4,851	0.009	-53.44	6,109	0.003	-0.06	68	-0.135	-53.75	-237,288	-0.041	-0.07	6,682	-0.107	-53.7	-224,357	0.055	0.5808	null	null	197	decelerating	0.03	0.23	1	1	4	23	0.481	0.488	0.49	0.381	0.36	354,748	377,618	375,705	8	908	decelerating	-0.1	null	84.1

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All Restaurants in Melbourne, Florida, US

Free sample dataset from BeamStation

The dataset All Restaurants in Melbourne, Florida, US provides a weekly refreshed export of every food‑service establishment listed for the city of Melbourne. It contains 414 records, each record representing a single restaurant profile with all available columns such as name, address, cuisine type, contact information, hours of operation, and any additional attributes supplied by the source. This comprehensive snapshot is useful for local analysts, market researchers, and developers who need up‑to‑date location‑based data for competitive analysis, site‑selection modeling, or building directory applications. Because the file is refreshed every week, users can rely on it to reflect recent openings, closures, or changes in details without having to scrape multiple sources. Access the dataset directly via the provided URL to integrate the latest Melbourne restaurant information into your workflow.

Dataset Details

Field	Value
Full dataset	414 records
Sample size	41 records
Location	Melbourne
Category	Restaurants
Updated	weekly
Format	CSV
Columns	beam_id, title, category_main_group, category_sub_group, category, categories, address, street, city, state, ... (498 total)

Column List

#	Column
1	`beam_id`
2	`title`
3	`category_main_group`
4	`category_sub_group`
5	`category`
6	`categories`
7	`address`
8	`street`
9	`city`
10	`state`
11	`borough`
12	`neighborhood`
13	`postal_code`
14	`country`
15	`address_verified`
16	`latitude`
17	`longitude`
18	`timezone`
19	`phone`
20	`price_level`
21	`business_status`
22	`has_open_hours`
23	`has_price`
24	`census_place`
25	`verified_census_city`
26	`beam_location_name`
27	`beam_state_code`
28	`beam_country_code`
29	`website_protocol`
30	`website`
31	`website_normalized`
32	`website_domain`
33	`website_domain_tld`
34	`website_domain_age`
35	`website_domain_registered`
36	`website_domain_expires`
37	`website_domain_registrar`
38	`emails_list`
39	`emails_list_website_domain`
40	`emails_count`
41	`emails_deliverable_count`
42	`emails_risky_count`
43	`description`
44	`has_about`
45	`has_description`
46	`rating`
47	`reviews_total_count`
48	`reviews_per_rating`
49	`service_options`
50	`highlights`
51	`popular_for`
52	`accessibility`
53	`offerings`
54	`dining_options`
55	`amenities`
56	`atmosphere`
57	`crowd`
58	`planning`
59	`payments`
60	`children`
61	`has_popular_times`
62	`has_website`
63	`has_email`
64	`has_social`
65	`has_phone`
66	`socials_count`
67	`first_social_post_date`
68	`last_social_post_date`
69	`first_social_post_days`
70	`last_social_post_days`
71	`social_post_count`
72	`first_social_post_days_min`
73	`first_social_post_days_max`
74	`last_social_post_days_min`
75	`last_social_post_days_max`
76	`social_profile_instagram`
77	`social_username_instagram`
78	`social_profile_facebook`
79	`social_username_facebook`
80	`social_profile_twitter`
81	`social_username_twitter`
82	`social_profile_tiktok`
83	`social_username_tiktok`
84	`social_profile_linkedin`
85	`social_username_linkedin`
86	`social_profile_youtube`
87	`social_username_youtube`
88	`social_profile_github`
89	`social_username_github`
90	`social_profile_snapchat`
91	`social_username_snapchat`
92	`social_profile_pinterest`
93	`social_username_pinterest`
94	`instagram_followers`
95	`instagram_engagement_rate`
96	`instagram_engagement_rate_1m`
97	`instagram_engagement_rate_3m`
98	`instagram_engagement_rate_6m`
99	`instagram_engagement_rate_12m`
100	`instagram_post_count`
101	`tiktok_followers`
102	`tiktok_video_count`
103	`tiktok_heart_count`
104	`tiktok_engagement_rate`
105	`tiktok_engagement_rate_1m`
106	`tiktok_engagement_rate_3m`
107	`tiktok_engagement_rate_6m`
108	`tiktok_engagement_rate_12m`
109	`menu_link`
110	`order_links`
111	`reservation_link`
112	`last_updated_at`
113	`beam_cross_social_market_penetration`
114	`beam_cross_velocity_quality`
115	`beam_cross_social_urgency`
116	`beam_cross_per_capita_engagement`
117	`beam_cross_market_saturation_lead`
118	`beam_cross_population_adjusted_rank`
119	`beam_cross_demand_gap_index`
120	`beam_rating_score`
121	`beam_review_confidence`
122	`beam_rating_health`
123	`sentiment_avg`
124	`sentiment_avg_30d`
125	`sentiment_avg_90d`
126	`sentiment_avg_180d`
127	`sentiment_avg_360d`
128	`sentiment_percentile_1km`
129	`sentiment_percentile_5km`
130	`sentiment_percentile_10km`
131	`sentiment_score_90d`
132	`sentiment_score_360d`
133	`sentiment_positive_pct_30d`
134	`sentiment_negative_pct_30d`
135	`sentiment_neutral_pct_30d`
136	`sentiment_positive_pct_90d`
137	`sentiment_negative_pct_90d`
138	`sentiment_neutral_pct_90d`
139	`sentiment_positive_pct_180d`
140	`sentiment_negative_pct_180d`
141	`sentiment_neutral_pct_180d`
142	`sentiment_positive_pct_360d`
143	`sentiment_negative_pct_360d`
144	`sentiment_neutral_pct_360d`
145	`sentiment_trend_30vs90d`
146	`sentiment_trend_90vs360d`
147	`sentiment_diff_30vs90d`
148	`sentiment_change_360d`
149	`sentiment_diff_90vs360d`
150	`sentiment_change_pct_360d`
151	`reviews_count_30d`
152	`reviews_count_90d`
153	`reviews_count_180d`
154	`reviews_count_360d`
155	`review_growth_pct_180d`
156	`review_growth_pct_360d`
157	`review_growth_pct_90d`
158	`beam_score_overall`
159	`beam_popularity_percentile`
160	`beam_social_presence`
161	`beam_data_completeness`
162	`beam_price_value`
163	`beam_data_freshness`
164	`beam_rank_city_category`
165	`beam_rank_city_overall`
166	`beam_rank_city_reviews`
167	`beam_rank_state_category`
168	`beam_rank_state_overall`
169	`beam_rank_state_reviews`
170	`beam_rank_country_category`
171	`beam_rank_country_overall`
172	`beam_rank_country_reviews`
173	`beam_rank_place_global_category`
174	`beam_rank_category`
175	`beam_rank_competition_1km_category`
176	`beam_rank_competition_1km_total`
177	`beam_rank_competition_1km_reviews`
178	`beam_rank_competition_5km_category`
179	`beam_rank_competition_5km_total`
180	`beam_rank_competition_5km_reviews`
181	`beam_rank_competition_10km_category`
182	`beam_rank_competition_10km_total`
183	`beam_rank_competition_10km_reviews`
184	`beam_export_rank`
185	`total_city_category`
186	`total_city`
187	`total_state_category`
188	`total_state`
189	`total_country_category`
190	`total_country`
191	`total_category_global`
192	`beam_competitors_10km_competitive_strength`
193	`beam_competitors_10km_competitor_avg_sentiment_30d`
194	`beam_competitors_10km_competitor_avg_sentiment_90d`
195	`beam_competitors_10km_sentiment_diff_30d`
196	`beam_competitors_10km_sentiment_diff_90d`
197	`beam_competitors_1km_competitive_strength`
198	`beam_competitors_1km_competitor_avg_sentiment_30d`
199	`beam_competitors_1km_competitor_avg_sentiment_90d`
200	`beam_competitors_1km_sentiment_diff_30d`
201	`beam_competitors_1km_sentiment_diff_90d`
202	`beam_competitors_5km_competitive_strength`
203	`beam_competitors_5km_competitor_avg_sentiment_30d`
204	`beam_competitors_5km_competitor_avg_sentiment_90d`
205	`beam_competitors_5km_sentiment_diff_30d`
206	`beam_competitors_5km_sentiment_diff_90d`
207	`beam_competitors_10km_competitor_count`
208	`beam_competitors_1km_competitor_count`
209	`beam_competitors_5km_competitor_count`
210	`beam_competitors_1km_rank_by_score`
211	`beam_competitors_1km_rank_by_rating`
212	`beam_competitors_1km_rank_by_reviews`
213	`beam_competitors_1km_score_percentile`
214	`beam_competitors_1km_rating_percentile`
215	`beam_competitors_1km_reviews_percentile`
216	`beam_competitors_1km_health_percentile`
217	`beam_competitors_1km_sentiment_percentile`
218	`beam_competitors_1km_competitor_avg_score`
219	`beam_competitors_1km_competitor_avg_rating`
220	`beam_competitors_1km_competitor_avg_reviews`
221	`beam_competitors_1km_competitor_avg_health`
222	`beam_competitors_1km_competitor_avg_sentiment`
223	`beam_competitors_1km_score_diff`
224	`beam_competitors_1km_rating_diff`
225	`beam_competitors_1km_reviews_diff`
226	`beam_competitors_1km_health_diff`
227	`beam_competitors_1km_sentiment_diff`
228	`beam_competitors_5km_rank_by_score`
229	`beam_competitors_5km_rank_by_rating`
230	`beam_competitors_5km_rank_by_reviews`
231	`beam_competitors_5km_score_percentile`
232	`beam_competitors_5km_rating_percentile`
233	`beam_competitors_5km_reviews_percentile`
234	`beam_competitors_5km_health_percentile`
235	`beam_competitors_5km_sentiment_percentile`
236	`beam_competitors_5km_competitor_avg_score`
237	`beam_competitors_5km_competitor_avg_rating`
238	`beam_competitors_5km_competitor_avg_reviews`
239	`beam_competitors_5km_competitor_avg_health`
240	`beam_competitors_5km_competitor_avg_sentiment`
241	`beam_competitors_5km_score_diff`
242	`beam_competitors_5km_rating_diff`
243	`beam_competitors_5km_reviews_diff`
244	`beam_competitors_5km_health_diff`
245	`beam_competitors_5km_sentiment_diff`
246	`beam_competitors_10km_rank_by_score`
247	`beam_competitors_10km_rank_by_rating`
248	`beam_competitors_10km_rank_by_reviews`
249	`beam_competitors_10km_score_percentile`
250	`beam_competitors_1km_competitive_tier`
251	`beam_competitors_10km_rating_percentile`
252	`beam_competitors_10km_reviews_percentile`
253	`beam_competitors_10km_health_percentile`
254	`beam_competitors_10km_sentiment_percentile`
255	`beam_competitors_5km_competitive_tier`
256	`beam_competitors_10km_competitor_avg_score`
257	`beam_competitors_10km_competitor_avg_rating`
258	`beam_competitors_10km_competitor_avg_reviews`
259	`beam_competitors_10km_competitor_avg_health`
260	`beam_competitors_10km_competitive_tier`
261	`beam_competitors_10km_competitor_avg_sentiment`
262	`beam_competitors_10km_score_diff`
263	`beam_competitors_10km_rating_diff`
264	`beam_competitors_10km_reviews_diff`
265	`beam_competitors_10km_health_diff`
266	`beam_competitors_10km_sentiment_diff`
267	`beam_competitors_1km_total_in_radius`
268	`beam_competitors_5km_total_in_radius`
269	`beam_competitors_10km_total_in_radius`
270	`beam_competitors_1km_avg_distance_m`
271	`beam_competitors_1km_closest_competitor_m`
272	`beam_competitors_1km_market_type`
273	`beam_competitors_1km_review_share`
274	`beam_competitors_1km_density_per_sqkm`
275	`beam_competitors_1km_tier_below_40`
276	`beam_competitors_1km_tier_40_59`
277	`beam_competitors_1km_tier_60_79`
278	`beam_competitors_1km_tier_80_100`
279	`beam_competitors_5km_avg_distance_m`
280	`beam_competitors_5km_closest_competitor_m`
281	`beam_competitors_5km_market_type`
282	`beam_competitors_5km_review_share`
283	`beam_competitors_5km_density_per_sqkm`
284	`beam_competitors_5km_tier_below_40`
285	`beam_competitors_5km_tier_40_59`
286	`beam_competitors_5km_tier_60_79`
287	`beam_competitors_5km_tier_80_100`
288	`beam_competitors_10km_avg_distance_m`
289	`beam_competitors_10km_closest_competitor_m`
290	`beam_competitors_10km_market_type`
291	`beam_competitors_10km_review_share`
292	`beam_competitors_10km_density_per_sqkm`
293	`beam_competitors_10km_tier_below_40`
294	`beam_competitors_10km_tier_40_59`
295	`beam_competitors_10km_tier_60_79`
296	`beam_competitors_10km_tier_80_100`
297	`beam_competitors_city_competitor_avg_sentiment_30d`
298	`beam_competitors_city_competitor_avg_sentiment_90d`
299	`beam_competitors_city_sentiment_diff_30d`
300	`beam_competitors_city_sentiment_diff_90d`
301	`beam_competitors_city_competitor_count`
302	`beam_competitors_city_total_in_city`
303	`beam_competitors_city_rank_by_score`
304	`beam_competitors_city_rank_by_rating`
305	`beam_competitors_city_rank_by_reviews`
306	`beam_competitors_city_score_percentile`
307	`beam_competitors_city_rating_percentile`
308	`beam_competitors_city_reviews_percentile`
309	`beam_competitors_city_health_percentile`
310	`beam_competitors_city_sentiment_percentile`
311	`beam_competitors_city_competitor_avg_score`
312	`beam_competitors_city_competitor_avg_rating`
313	`beam_competitors_city_competitor_avg_reviews`
314	`beam_competitors_city_competitor_avg_health`
315	`beam_competitors_city_competitor_avg_sentiment`
316	`beam_competitors_city_score_diff`
317	`beam_competitors_city_rating_diff`
318	`beam_competitors_city_reviews_diff`
319	`beam_competitors_city_health_diff`
320	`beam_competitors_city_sentiment_diff`
321	`beam_competitors_city_market_type`
322	`beam_competitors_city_review_share`
323	`beam_competitors_city_density_per_sqkm`
324	`beam_competitors_city_tier_below_40`
325	`beam_competitors_city_tier_40_59`
326	`beam_competitors_city_tier_60_79`
327	`beam_competitors_city_tier_80_100`
328	`beam_competitors_city_competitive_strength`
329	`beam_competitors_city_underserved_score`
330	`beam_competitors_city_competition_intensity`
331	`beam_competitors_state_competitor_avg_sentiment_30d`
332	`beam_competitors_state_competitor_avg_sentiment_90d`
333	`beam_competitors_state_sentiment_diff_30d`
334	`beam_competitors_state_sentiment_diff_90d`
335	`beam_competitors_state_competitor_count`
336	`beam_competitors_state_total_in_state`
337	`beam_competitors_state_rank_by_score`
338	`beam_competitors_state_rank_by_rating`
339	`beam_competitors_state_rank_by_reviews`
340	`beam_competitors_state_score_percentile`
341	`beam_competitors_state_rating_percentile`
342	`beam_competitors_state_reviews_percentile`
343	`beam_competitors_state_health_percentile`
344	`beam_competitors_state_sentiment_percentile`
345	`beam_competitors_state_competitor_avg_score`
346	`beam_competitors_state_competitor_avg_rating`
347	`beam_competitors_state_competitor_avg_reviews`
348	`beam_competitors_state_competitor_avg_health`
349	`beam_competitors_state_competitor_avg_sentiment`
350	`beam_competitors_state_score_diff`
351	`beam_competitors_state_rating_diff`
352	`beam_competitors_state_reviews_diff`
353	`beam_competitors_state_health_diff`
354	`beam_competitors_state_sentiment_diff`
355	`beam_competitors_state_market_type`
356	`beam_competitors_state_review_share`
357	`beam_competitors_state_density_per_sqkm`
358	`beam_competitors_state_underserved_score`
359	`beam_competitors_state_competition_intensity`
360	`beam_competitors_state_competitive_strength`
361	`beam_competitors_country_competitor_avg_sentiment_30d`
362	`beam_competitors_country_competitor_avg_sentiment_90d`
363	`beam_competitors_country_sentiment_diff_30d`
364	`beam_competitors_country_sentiment_diff_90d`
365	`beam_competitors_country_competitor_count`
366	`beam_competitors_country_competitor_avg_score`
367	`beam_competitors_country_competitor_avg_rating`
368	`beam_competitors_country_competitor_avg_reviews`
369	`beam_competitors_country_competitor_avg_health`
370	`beam_competitors_country_competitor_avg_sentiment`
371	`beam_competitors_country_score_diff`
372	`beam_competitors_country_rating_diff`
373	`beam_competitors_country_reviews_diff`
374	`beam_competitors_country_sentiment_diff`
375	`beam_competitors_country_score_percentile`
376	`beam_competitors_country_rating_percentile`
377	`beam_competitors_country_reviews_percentile`
378	`beam_competitors_country_health_percentile`
379	`beam_competitors_country_sentiment_percentile`
380	`beam_competitors_country_rank_by_score`
381	`beam_competitors_country_competitive_strength`
382	`beam_competitors_country_health_diff`
383	`beam_competitors_country_rank_by_rating`
384	`beam_competitors_country_rank_by_reviews`
385	`beam_competitors_country_tier_40_59`
386	`beam_competitors_country_tier_60_79`
387	`beam_competitors_country_tier_80_100`
388	`beam_competitors_country_tier_below_40`
389	`beam_competitors_country_total_in_country`
390	`beam_competitors_city_siblings_competitor_count`
391	`beam_competitors_city_siblings_competitor_avg_score`
392	`beam_competitors_city_siblings_competitor_avg_rating`
393	`beam_competitors_city_siblings_competitor_avg_reviews`
394	`beam_competitors_city_siblings_competitor_avg_health`
395	`beam_competitors_city_siblings_competitor_avg_sentiment`
396	`beam_competitors_city_siblings_score_diff`
397	`beam_competitors_city_siblings_rating_diff`
398	`beam_competitors_city_siblings_reviews_diff`
399	`beam_competitors_city_siblings_sentiment_diff`
400	`beam_competitors_city_siblings_score_percentile`
401	`beam_competitors_city_siblings_rating_percentile`
402	`beam_competitors_city_siblings_reviews_percentile`
403	`beam_competitors_city_siblings_health_percentile`
404	`beam_competitors_city_siblings_sentiment_percentile`
405	`beam_competitors_city_siblings_rank_by_score`
406	`beam_competitors_city_siblings_competitor_avg_recommend_pct`
407	`beam_competitors_city_siblings_recommend_pct_diff`
408	`beam_competitors_city_siblings_recommend_pct_percentile`
409	`beam_competitors_city_siblings_total_siblings`
410	`beam_competitors_city_businesses_per_10k_pop`
411	`beam_competitors_city_population_per_business`
412	`beam_competitors_city_population_density`
413	`beam_competitors_city_reviews_per_capita`
414	`beam_competitors_city_reviews_per_10k_pop`
415	`beam_competitors_state_businesses_per_10k_pop`
416	`beam_competitors_state_population_per_business`
417	`beam_competitors_state_population_density`
418	`beam_competitors_state_reviews_per_capita`
419	`beam_competitors_state_reviews_per_10k_pop`
420	`beam_competitors_1km_hhi_contribution`
421	`beam_competitors_1km_hhi_minimum`
422	`beam_competitors_5km_hhi_contribution`
423	`beam_competitors_5km_hhi_minimum`
424	`beam_competitors_10km_hhi_contribution`
425	`beam_competitors_10km_hhi_minimum`
426	`beam_competitors_city_hhi_contribution`
427	`beam_competitors_city_hhi_minimum`
428	`beam_competitors_state_hhi_contribution`
429	`beam_competitors_state_hhi_minimum`
430	`beam_trends_score_30d_beam_score_overall`
431	`beam_trends_score_30d_rating`
432	`beam_trends_score_30d_review_count`
433	`beam_trends_score_30d_beam_rating_health`
434	`beam_trends_score_30d_beam_popularity_percentile`
435	`beam_trends_score_90d_beam_score_overall`
436	`beam_trends_score_90d_rating`
437	`beam_trends_score_90d_review_count`
438	`beam_trends_score_90d_beam_rating_health`
439	`beam_trends_score_90d_beam_popularity_percentile`
440	`beam_trends_competitive_1km_30d_strength_change`
441	`beam_trends_competitive_1km_30d_rank_change`
442	`beam_trends_competitive_1km_30d_percentile_change`
443	`beam_trends_competitive_1km_90d_strength_change`
444	`beam_trends_competitive_1km_90d_rank_change`
445	`beam_trends_competitive_1km_90d_percentile_change`
446	`beam_trends_competitive_5km_30d_strength_change`
447	`beam_trends_competitive_5km_30d_rank_change`
448	`beam_trends_competitive_5km_30d_percentile_change`
449	`beam_trends_competitive_5km_90d_strength_change`
450	`beam_trends_competitive_5km_90d_rank_change`
451	`beam_trends_competitive_5km_90d_percentile_change`
452	`beam_trends_competitive_10km_30d_strength_change`
453	`beam_trends_competitive_10km_30d_rank_change`
454	`beam_trends_competitive_10km_30d_percentile_change`
455	`beam_trends_competitive_10km_90d_strength_change`
456	`beam_trends_competitive_10km_90d_rank_change`
457	`beam_trends_competitive_10km_90d_percentile_change`
458	`beam_trends_competitive_city_30d_strength_change`
459	`beam_trends_competitive_city_30d_rank_change`
460	`beam_trends_competitive_city_30d_percentile_change`
461	`beam_trends_competitive_city_90d_strength_change`
462	`beam_trends_competitive_city_90d_rank_change`
463	`beam_trends_competitive_city_90d_percentile_change`
464	`beam_trends_competitive_state_30d_strength_change`
465	`beam_trends_competitive_state_30d_rank_change`
466	`beam_trends_competitive_state_30d_percentile_change`
467	`beam_trends_competitive_state_90d_strength_change`
468	`beam_trends_competitive_state_90d_rank_change`
469	`beam_trends_competitive_state_90d_percentile_change`
470	`beam_trends_sentiment_current_sentiment`
471	`beam_trends_sentiment_positive_ratio`
472	`beam_trends_sentiment_negative_ratio`
473	`beam_trends_sentiment_review_count`
474	`beam_trends_velocity_reviews_per_day`
475	`beam_trends_velocity_reviews_per_month`
476	`beam_trends_velocity_percentile_city`
477	`beam_trends_velocity_percentile_state`
478	`beam_trends_velocity_trend`
479	`beam_velocity_reviews_per_day`
480	`beam_velocity_reviews_per_week`
481	`beam_velocity_reviews_per_month`
482	`beam_velocity_reviews_last_30d`
483	`beam_velocity_reviews_last_90d`
484	`beam_velocity_reviews_last_365d`
485	`beam_velocity_percentile_1km`
486	`beam_velocity_percentile_5km`
487	`beam_velocity_percentile_10km`
488	`beam_velocity_percentile_city`
489	`beam_velocity_percentile_state`
490	`beam_velocity_rank_1km`
491	`beam_velocity_rank_5km`
492	`beam_velocity_rank_10km`
493	`beam_velocity_rank_city`
494	`beam_velocity_rank_state`
495	`beam_velocity_trend`
496	`beam_velocity_change_30d`
497	`beam_velocity_change_90d`
498	`beam_trends_sentiment_recommend_pct`

Usage

from datasets import load_dataset
ds = load_dataset("beamstation/all-restaurants-in-melbourne-florida-us-211295")

Get the Full Dataset

This is a free sample with masked email and phone data. The full dataset with 414 records and unmasked contact data is available at:

All Restaurants in Melbourne, Florida, US on BeamStation

License

This sample is provided for evaluation purposes under the BeamStation Terms of Service.

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