The dataset viewer is not available for this split.
Error code: InfoError
Exception: HfHubHTTPError
Message: 504 Server Error: Gateway Time-out for url: https://huggingface.co/api/datasets/beamstation/all-restaurants-in-murfreesboro-tennessee-us-175315/paths-info/00265c568f588f7744385938a1a39836157c4dfb
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 223, in compute_first_rows_from_streaming_response
info = get_dataset_config_info(path=dataset, config_name=config, token=hf_token)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 268, in get_dataset_config_info
builder = load_dataset_builder(
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1315, in load_dataset_builder
dataset_module = dataset_module_factory(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1207, in dataset_module_factory
raise e1 from None
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1182, in dataset_module_factory
).get_module()
^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 638, in get_module
patterns = get_data_patterns(base_path, download_config=self.download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/data_files.py", line 493, in get_data_patterns
return _get_data_files_patterns(resolver)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/data_files.py", line 268, in _get_data_files_patterns
data_files = pattern_resolver(pattern)
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/data_files.py", line 372, in resolve_pattern
for filepath, info in fs.glob(fs_pattern, detail=True, **glob_kwargs).items():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 521, in glob
return super().glob(path, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/fsspec/spec.py", line 604, in glob
allpaths = self.find(root, maxdepth=depth, withdirs=True, detail=True, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 556, in find
return super().find(
^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/fsspec/spec.py", line 495, in find
out[path] = self.info(path)
^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 719, in info
paths_info = self._api.get_paths_info(
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_api.py", line 3371, in get_paths_info
hf_raise_for_status(response)
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/utils/_http.py", line 482, in hf_raise_for_status
raise _format(HfHubHTTPError, str(e), response) from e
huggingface_hub.errors.HfHubHTTPError: 504 Server Error: Gateway Time-out for url: https://huggingface.co/api/datasets/beamstation/all-restaurants-in-murfreesboro-tennessee-us-175315/paths-info/00265c568f588f7744385938a1a39836157c4dfbNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
All Restaurants in Murfreesboro, Tennessee, US
Free sample dataset from BeamStation
All Restaurants in Murfreesboro, Tennessee, US
This dataset provides a complete export of every restaurant operating in Murfreesboro, Tennessee, containing 433 records. Updated weekly, it includes all available columns from the source, such as establishment name, address, cuisine type, contact information, hours of operation, and any additional profile fields offered by the data provider.
Ideal for local market analysts, food‑delivery platforms, urban planners, or researchers studying the restaurant landscape of a mid‑size Southeastern city, the file enables straightforward analysis of dining options, competitive benchmarking, and geographic distribution.
Access the dataset directly via the BeamStation portal: https://beamstation.com/datasets/175315/.
Because the refresh cadence is weekly, users can rely on relatively current information for time‑sensitive projects while still benefiting from a stable, downloadable format for offline work or integration into larger data pipelines.
Note: All figures presented here are derived solely from the dataset metadata.
Dataset Details
| Field | Value |
|---|---|
| Full dataset | 433 records |
| Sample size | 43 records |
| Location | Murfreesboro |
| 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-murfreesboro-tennessee-us-175315")
Get the Full Dataset
This is a free sample with masked email and phone data. The full dataset with 433 records and unmasked contact data is available at:
All Restaurants in Murfreesboro, Tennessee, US on BeamStation
License
This sample is provided for evaluation purposes under the BeamStation Terms of Service.
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