question_id
stringlengths
64
64
category
stringclasses
1 value
turns
sequencelengths
1
1
ground_truth
stringlengths
2
3.05k
task
stringclasses
3 values
livebench_release_date
timestamp[s]
livebench_removal_date
stringclasses
1 value
d4ec8efff8fdcc6db682bb2c9dc2b5284ea7ca5d0f79663832e203e3d52bd125
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[13429383], [13428821], [13428264], [13429035], [13429397]] \n Classes: ['arrest' 'latitude' 'location_description' ':@computed_region_rpca_8um6'\n ':@computed_region_43wa_7qmu' 'updated_on' 'primary_type'\n ':@computed_region_awaf_s7ux' ':@computed_region_d9mm_jgwp' 'beat'\n ':@computed_region_vrxf_vc4k' ':@computed_region_6mkv_f3dw' 'longitude'\n 'domestic' 'description' 'y_coordinate' 'block' 'id' 'x_coordinate'\n 'year' ':@computed_region_bdys_3d7i' 'ward' 'location' 'district'\n 'fbi_code' ':@computed_region_8hcu_yrd4' 'date' 'iucr'\n ':@computed_region_d3ds_rm58' 'case_number' 'community_area'] \n Output: \n" ]
id
cta
2024-06-24T00:00:00
a0ef4e780ad34fa8a80b2ce6367a36c65899cfeb5e610e896857e49bc240e45e
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[1995], [1964], [1986], [2022], [1985]] \n Classes: ['Maize yield' 'code country' 'Year' 'country'] \n Output: \n" ]
Year
cta
2024-06-24T00:00:00
48dd183d63a78a751541e8d237cfbfaeeba2df8cd7f0d6fe58324d74aad9ff3b
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[2.947], [2.6497], [-2.0369], [-190.1799], [-18.7659]] \n Classes: ['REVS5m20' 'Beta252' 'Price1M' 'PVT6' 'ACD6' 'LossVariance60'\n 'InformationRatio20' 'REVS60' 'SharpeRatio120' 'VEMA5' 'Volumn3M'\n 'GainVariance60' 'EMV6' 'BackwardADJ' 'VSTD10' 'VOL240' 'RC24' 'Aroon'\n 'ROC6' 'UpRVI' 'SharpeRatio20' 'VOL60' 'RVI' 'Volumn1M' 'TreynorRatio60'\n 'VROC6' 'InformationRatio60' 'TVMA6' 'RSTR12' 'VEMA12' 'AD20' 'BollUp'\n 'CCI20' 'Ulcer5' 'RSTR504' 'minusDI' 'VMACD' 'RSI' 'DIFF' 'DAVOL20'\n 'ARBR' 'ADXR' 'STOA' 'GainLossVarianceRatio120' 'APBMA' 'DIZ' 'TVMA20'\n 'STOM' 'STOQ' 'AD6' 'EMA12' 'VOSC' 'ChaikinVolatility' 'SBM'\n 'MoneyFlow20' 'SharpeRatio60' 'CoppockCurve' 'BollDown' 'REVS120'\n 'CmraCNE5' 'BIAS60' 'Kurtosis20' 'REVS5m60' 'TreynorRatio20' 'DDNSR'\n 'trend' 'MA10Close' 'MA120' 'REVS5Indu1' 'DBCD' 'Beta20' 'Volatility'\n 'Alpha20' 'ADTM' 'TOBT' 'UOS' 'PLRC12' 'DASTD' 'AR' 'PVI' 'BR' 'Rank1M'\n 'Skewness' 'PEHist250' 'VR' 'EMA20' 'ILLIQUIDITY' 'MA10RegressCoeff12'\n 'MA10RegressCoeff6' 'Variance60' 'MAWVAD' 'BIAS5' 'Beta120' 'PLRC6'\n 'CCI5' 'VOL10' 'Variance20' 'AD' 'TRIX10' 'GainLossVarianceRatio60'\n 'KlingerOscillator' 'ChandeSD' 'TVSTD6' 'AroonDown' 'REVS10' 'MACD'\n 'MTMMA' 'PEHist20' 'OBV20' 'VOL120' 'DHILO' 'MA60' 'OBV6' 'MFI' 'PSY'\n 'ADX' 'ticker' 'KDJ_D' 'PEHist120' 'GainVariance20' 'CCI10' 'DDNCR'\n 'VOL5' 'DIF' 'BBIC' 'Alpha60' 'GainVariance120' 'AroonUp' 'VEMA10' 'EMA5'\n 'WVAD' 'Ulcer10' 'ATR6' 'LossVariance20' 'BBI' 'LossVariance120'\n 'EARNMOM' 'OBV' 'VEMA26' 'EMV14' 'ChaikinOscillator' 'TEMA10' 'TRIX5'\n 'Variance120' 'NVI' 'DAVOL10' 'VROC12' 'HSIGMA' 'SwingIndex' 'MTM'\n 'InformationRatio120' 'PEHist60' 'month' 'VSTD20' 'ATR14' 'Kurtosis120'\n 'RealizedVolatility' 'Hurst' 'REVS20Indu1' 'Beta60' 'DEA' 'KDJ_J' 'RC12'\n 'REVS5' 'BIAS10' 'Price1Y' 'VDEA' 'BullPower' 'HsigmaCNE5' 'EMA120'\n 'REVS250' 'MA5' 'EMA26' 'Price3M' 'VDIFF' 'CMRA' 'ChandeSU' 'MA20' 'SRMI'\n 'TVSTD20' 'REVS20' 'TEMA5' 'Kurtosis60' 'HBETA' 'TreynorRatio120'\n 'DownRVI' 'MA10' 'FiftyTwoWeekHigh' 'EMA10' 'DVRAT' 'BearPower' 'CCI88'\n 'JDQS20' 'MassIndex' 'CMO' 'EMA60' 'ASI' 'BIAS20' 'ARC' 'PVT12' 'ACD20'\n 'Elder' 'Alpha120' 'KDJ_K' 'DDI' 'ROC20' 'DAVOL5' 'CR20' 'VOL20' 'PVT'\n 'plusDI' 'GainLossVarianceRatio20' 'STM' 'RSTR24'] \n Output: \n" ]
ChaikinOscillator
cta
2024-06-24T00:00:00
567d5f634453da734fb7ceab3bbea4dd283ac19a125102fe9b533ca5e0e388e5
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[\"{'url': 'http://img.scoop.co.nz/stories/images/1701/325b73cba7c727ae495c.jpeg'}\"], [nan], [nan], [nan], [\"{'url': 'http://www.stuff.co.nz/content/dam/images/1/6/p/4/g/6/image.related.StuffLandscapeSixteenByNine.620x349.16otlx.png/1441253972454.jpg'}\"]] \n Classes: ['storm_name' 'event_id' 'injury_count' 'event_import_id'\n 'location_description' 'notes' 'submitted_date' 'landslide_setting'\n 'event_title' 'landslide_size' 'photo_link' 'source_link' 'latitude'\n 'event_import_source' 'gazeteer_closest_point' 'landslide_category'\n 'longitude' 'fatality_count' 'landslide_trigger' 'country_code'\n 'last_edited_date' 'event_date' 'gazeteer_distance' 'location_accuracy'\n 'source_name' 'event_description' 'admin_division_population'\n 'created_date' 'country_name' 'admin_division_name'] \n Output: \n" ]
photo_link
cta
2024-06-24T00:00:00
5c3dfa6b8c0ecd07ea0091b21fb237ade69bdce3c3a9cdeed307bee1e968ce2b
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[1995], [1964], [1986], [2022], [1985]] \n Classes: ['country' 'code country' 'Year' 'Maize yield'] \n Output: \n" ]
Year
cta
2024-06-24T00:00:00
051ed5edf44bb798385076a1260de95b272dd2e0f5167dc78e514ce434af3ef6
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[5], [5], [2], [2], [4]] \n Classes: ['grade_level' 'father_profession' 'veggies_day' 'turkey_calories'\n 'type_sports' 'ideal_diet_coded' 'calories_scone' 'fav_cuisine'\n 'exercise' 'soup' 'drink' 'ethnic_food' 'healthy_feeling'\n 'waffle_calories' 'diet_current_coded' 'Gender' 'eating_changes_coded1'\n 'calories_chicken' 'cuisine' 'coffee' 'mother_education'\n 'comfort_food_reasons' 'fav_cuisine_coded' 'indian_food' 'vitamins'\n 'pay_meal_out' 'life_rewarding' 'mother_profession' 'weight'\n 'father_education' 'comfort_food' 'thai_food' 'self_perception_weight'\n 'income' 'employment' 'breakfast' 'healthy_meal' 'ideal_diet'\n 'marital_status' 'calories_day' 'GPA' 'eating_changes' 'greek_food'\n 'fav_food' 'parents_cook' 'tortilla_calories' 'fries' 'diet_current'\n 'italian_food' 'persian_food' 'cook' 'eating_changes_coded'\n 'meals_dinner_friend' 'on_off_campus' 'eating_out' 'sports'\n 'food_childhood' 'fruit_day' 'nutritional_check'\n 'comfort_food_reasons_coded' 'comfort_food_reasons_coded.1'] \n Output: \n" ]
nutritional_check
cta
2024-06-24T00:00:00
811f288b7c362542153770a32060519cf59d30d4c61368bb9abea3a56f873a09
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['RC'], ['CC'], ['CC'], ['TI'], ['TI']] \n Classes: ['titular' 'rangobeneficioconsolidadoasignado' 'pais'\n 'fechainscripcionbeneficiario' 'rangoultimobeneficioasignado'\n 'codigodepartamentoatencion' 'discapacidad' 'nombremunicipioatencion'\n 'tipodocumento' 'nombredepartamentoatencion' 'tipoasignacionbeneficio'\n 'rangoedad' 'tipobeneficio' 'etnia' 'codigomunicipioatencion'\n 'estadobeneficiario' 'fechaultimobeneficioasignado' 'tipopoblacion'\n 'nivelescolaridad' 'genero' 'cantidaddebeneficiarios' 'bancarizado'] \n Output: \n" ]
tipodocumento
cta
2024-06-24T00:00:00
3f7b12f0c920812c39c3217750021c9e9153c1934d4673e5aaf481be74f89aa9
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[41.509998], [57.52], [48.27], [48.119999], [40.880001]] \n Classes: ['Volume' 'High' 'Date' 'Low' 'Close' 'Open'] \n Output: \n" ]
Low
cta
2024-06-24T00:00:00
13ca9b1d4d1937587bd2cc18ac8804a4c57d5e9066a6d7501d2f06ab33119cb6
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['Thailand'], ['Vietnam'], ['Mexico'], ['Colombia'], ['Honduras']] \n Classes: ['Expiration' 'Acidity' 'Aroma' 'Balance' 'Clean.Cup' 'Processing.Method'\n 'Aftertaste' 'Harvest.Year' 'Variety' 'Moisture' 'Sweetness' 'Uniformity'\n 'Country.of.Origin' 'Continent.of.Origin' 'Quakers' 'Color' 'Flavor'\n 'Species' 'Body' 'Category.One.Defects' 'REC_ID' 'Category.Two.Defects'] \n Output: \n" ]
Country.of.Origin
cta
2024-06-24T00:00:00
f9bcb466e175b91a55ff30f1265ad410a93737012e3e6c8f288adcd3525f5d7e
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['Adobe InDesign CS4: Fundamentals'], ['Cisco CAPPS 8.0: Implementing Cisco Unity Express in CUCM Express Environment'], ['Consulting Skills 2: Marketing, Building, and Expanding'], ['Basic Features of Excel 2003'], ['Adobe_Presenter 10']] \n Classes: ['training_type' 'training_title' 'training_provider'\n 'training_description' 'target_audience'] \n Output: \n" ]
training_title
cta
2024-06-24T00:00:00
2cbf1cc153f0500650d2b4ce15643bc7319268df28b56624014250dc8fe28b07
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[232058], [4581], [80510], [183295], [232058]] \n Classes: ['quantity' 'species'] \n Output: \n" ]
quantity
cta
2024-06-24T00:00:00
f6239269d04fcfd9a96e904b2016c00b132487ce74c331d77b829d5cdb6f5df7
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['Authoritative'], [nan], ['In process'], ['Authoritative'], ['Authoritative']] \n Classes: ['data_set' 'publishing_status' 'source' 'data_collection_phase'\n 'description' 'sharing_permissions' 'primary_uses' 'update_frequency'\n 'category_search' 'format' 'date_added' 'downloadurl' 'principal_use'\n 'basis_url' 'dataurl' 'data_steward_notes' 'geojson' 'basisid'\n 'data_subcategory' 'data_category' 'data_steward' 'geometry' 'in_review'\n 'unit_of_analysis' 'date_published'] \n Output: \n" ]
publishing_status
cta
2024-06-24T00:00:00
60d902d2b18d8ed747f135fd78d13c2da523d6067ed3865723d5e34a99abdf61
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[1010], [4404], [1010], [1010], [1010]] \n Classes: ['longitude' 'latitude' 'ward' 'application_type' 'state' 'city'\n 'ward_precinct' 'police_district' 'license_status' 'license_start_date'\n 'license_number' 'location' 'license_id' 'conditional_approval' 'ssa'\n 'id' 'account_number' 'license_description' 'license_code' 'payment_date'\n 'site_number' 'business_activity' 'application_requirements_complete'\n 'doing_business_as_name' 'address' 'expiration_date'\n 'business_activity_id' 'date_issued' 'license_approved_for_issuance'\n 'precinct' 'zip_code' 'legal_name'] \n Output: \n" ]
license_code
cta
2024-06-24T00:00:00
76b0d923c1e41da8c302c906ce9b145c4f648e04442ee224d899de34e2a09c27
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[232058], [4581], [80510], [183295], [232058]] \n Classes: ['species' 'quantity'] \n Output: \n" ]
quantity
cta
2024-06-24T00:00:00
b75684697587c1ce05a1377916ae8da11e579e9e8a3d9e693a955a1dc8522f2e
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['POSSESS - HEROIN (WHITE)'], ['HARASSMENT BY ELECTRONIC MEANS'], ['ATTEMPT - AUTOMOBILE'], ['OVER $500'], ['POSSESS - CANNABIS MORE THAN 30 GRAMS']] \n Classes: ['latitude' 'case_' ':@computed_region_bdys_3d7i' 'arrest'\n ':@computed_region_6mkv_f3dw' 'ward' 'block' '_secondary_description'\n 'fbi_cd' '_location_description' 'longitude' 'beat' 'y_coordinate'\n '_primary_decsription' 'domestic' 'date_of_occurrence'\n ':@computed_region_43wa_7qmu' '_iucr' 'location'\n ':@computed_region_awaf_s7ux' 'x_coordinate'\n ':@computed_region_vrxf_vc4k'] \n Output: \n" ]
_secondary_description
cta
2024-06-24T00:00:00
666f26a703b286a7d31f2f46070307d6aa9e9644fcc24482de85820bfe2ad341
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['ham'], ['spam'], ['ham'], ['ham'], ['spam']] \n Classes: ['email' 'label'] \n Output: \n" ]
label
cta
2024-06-24T00:00:00
c6e1c2339d66267100fd9c9851f6fb488e0e91054519c789bc30206a8bf0f175
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['STEAMFITTER'], ['POLICE OFFICER'], ['POLICE OFFICER'], ['POLICE OFFICER'], ['POLICE OFFICER']] \n Classes: ['typical_hours' 'name' 'department' 'full_or_part_time' 'annual_salary'\n 'salary_or_hourly' 'hourly_rate' 'job_titles'] \n Output: \n" ]
job_titles
cta
2024-06-24T00:00:00
ea6612af21a179810783dc4c8f39584a5f287099d46855b0b44b3d706ef349f7
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[0.16], [0.12], [0.125], [0.19], [0.115]] \n Classes: ['Height' 'Whole_weight' 'id' 'Length' 'Viscera_weight' 'Shucked_weight'\n 'Sex' 'Diameter' 'Rings' 'Shell_weight'] \n Output: \n" ]
Height
cta
2024-06-24T00:00:00
010107031fdf6e54fcac08ac186ff4f0a9018d887bf5920f921f14e80bd82633
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[1164437190.0], [1295752418.0], [nan], [1619502168.0], [1497385967.0]] \n Classes: ['provider_status' ':@computed_region_pqdx_y6mm' 'courses_available'\n 'geocoded_address' 'county' 'provider_name' 'order_label' 'zip'\n 'national_drug_code' 'provider_note' 'npi' 'state_code'\n 'last_report_date' 'address1' 'city' 'address2'] \n Output: \n" ]
npi
cta
2024-06-24T00:00:00
d3d910189e70e5e5edd9a3f76420da1e8a5578b966ceef1c3936fb6b8e456551
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[0], [5], [0], [0], [7]] \n Classes: ['inpatient_beds_used_7_day_sum' 'total_beds_7_day_avg'\n 'previous_day_admission_adult_covid_confirmed_7_day_coverage'\n 'total_patients_hospitalized_confirmed_influenza_and_covid_7_day_sum'\n 'total_pediatric_patients_hospitalized_confirmed_covid_7_day_coverage'\n 'total_staffed_pediatric_icu_beds_7_day_avg' 'collection_week'\n 'total_adult_patients_hospitalized_confirmed_covid_7_day_coverage'\n 'total_adult_patients_hospitalized_confirmed_covid_7_day_avg'\n 'icu_patients_confirmed_influenza_7_day_sum'\n 'previous_day_admission_adult_covid_suspected_70_79_7_day_sum'\n 'staffed_pediatric_icu_bed_occupancy_7_day_sum'\n 'previous_day_admission_pediatric_covid_suspected_7_day_coverage'\n 'total_staffed_adult_icu_beds_7_day_coverage'\n 'inpatient_beds_used_7_day_avg'\n 'icu_patients_confirmed_influenza_7_day_coverage'\n 'total_patients_hospitalized_confirmed_influenza_7_day_sum'\n 'previous_day_admission_adult_covid_suspected_50'\n 'icu_patients_confirmed_influenza_7_day_avg'\n 'all_pediatric_inpatient_bed_occupied_7_day_sum'\n 'previous_day_admission_pediatric_covid_confirmed_unknown_7_day_sum'\n 'all_adult_hospital_inpatient_bed_occupied_7_day_coverage'\n 'staffed_icu_adult_patients_confirmed_covid_7_day_coverage'\n ':@computed_region_pqdx_y6mm'\n 'previous_day_admission_adult_covid_suspected_18'\n 'total_adult_patients_hospitalized_confirmed_and_suspected_covid_7_day_coverage'\n 'inpatient_beds_used_covid_7_day_coverage'\n 'inpatient_beds_7_day_coverage' 'all_adult_hospital_beds_7_day_sum'\n 'total_pediatric_patients_hospitalized_confirmed_covid_7_day_sum'\n 'staffed_icu_pediatric_patients_confirmed_covid_7_day_avg'\n 'previous_day_admission_pediatric_covid_confirmed_0_4_7_day_sum'\n 'staffed_icu_adult_patients_confirmed_covid_7_day_sum'\n 'all_adult_hospital_inpatient_beds_7_day_coverage'\n 'previous_day_admission_adult_covid_suspected_unknown_7_day_sum'\n 'icu_beds_used_7_day_sum' 'total_icu_beds_7_day_sum'\n 'previous_day_admission_adult_covid_suspected_30' 'hhs_ids'\n 'total_patients_hospitalized_confirmed_influenza_and_covid_7_day_avg'\n 'staffed_icu_adult_patients_confirmed_and_suspected_covid_7_day_avg'\n 'all_adult_hospital_inpatient_bed_occupied_7_day_sum' 'city'\n 'previous_day_admission_adult_covid_suspected_60'\n 'icu_beds_used_7_day_avg'\n 'previous_day_admission_influenza_confirmed_7_day_sum'\n 'all_pediatric_inpatient_beds_7_day_coverage' 'inpatient_beds_7_day_avg'\n 'staffed_icu_pediatric_patients_confirmed_covid_7_day_sum'\n 'previous_day_admission_pediatric_covid_confirmed_7_day_sum'\n 'previous_day_admission_adult_covid_confirmed_60'\n 'all_adult_hospital_inpatient_beds_7_day_sum'\n 'staffed_icu_adult_patients_confirmed_and_suspected_covid_7_day_sum'\n 'state' 'previous_day_admission_adult_covid_suspected_40' 'is_corrected'\n 'hospital_subtype'\n 'total_patients_hospitalized_confirmed_influenza_and_covid_7_day_coverage'\n 'total_icu_beds_7_day_avg'\n 'total_patients_hospitalized_confirmed_influenza_7_day_avg'\n 'total_adult_patients_hospitalized_confirmed_and_suspected_covid_7_day_avg'\n 'staffed_pediatric_icu_bed_occupancy_7_day_coverage'\n 'all_pediatric_inpatient_bed_occupied_7_day_coverage'\n 'staffed_icu_adult_patients_confirmed_and_suspected_covid_7_day_coverage'\n 'all_adult_hospital_inpatient_bed_occupied_7_day_avg'\n 'previous_day_admission_adult_covid_suspected_7_day_coverage' 'fips_code'\n 'previous_day_admission_adult_covid_suspected_80' 'total_beds_7_day_sum'\n 'total_patients_hospitalized_confirmed_influenza_7_day_coverage'\n 'all_adult_hospital_beds_7_day_avg' 'zip' 'is_metro_micro'\n 'previous_day_admission_adult_covid_confirmed_80'\n 'staffed_pediatric_icu_bed_occupancy_7_day_avg'\n 'previous_day_admission_pediatric_covid_confirmed_5_11_7_day_sum'\n 'previous_day_admission_adult_covid_suspected_20'\n 'total_staffed_pediatric_icu_beds_7_day_sum'\n 'previous_day_admission_adult_covid_confirmed_30_39_7_day_sum'\n 'geocoded_hospital_address' 'all_adult_hospital_beds_7_day_coverage'\n 'staffed_icu_adult_patients_confirmed_covid_7_day_avg'\n 'icu_beds_used_7_day_coverage'\n 'previous_day_admission_adult_covid_confirmed_40_49_7_day_sum'\n 'inpatient_beds_used_covid_7_day_sum'\n 'previous_day_covid_ed_visits_7_day_sum'\n 'all_adult_hospital_inpatient_beds_7_day_avg'\n 'previous_day_admission_adult_covid_suspected_7_day_sum'\n 'previous_day_admission_adult_covid_confirmed_70'\n 'inpatient_beds_used_7_day_coverage'\n 'inpatient_beds_used_covid_7_day_avg'\n 'total_pediatric_patients_hospitalized_confirmed_and_suspected_covid_7_day_avg'\n 'all_pediatric_inpatient_beds_7_day_sum'\n 'staffed_adult_icu_bed_occupancy_7_day_avg' 'ccn'\n 'total_adult_patients_hospitalized_confirmed_and_suspected_covid_7_day_sum'\n 'all_pediatric_inpatient_beds_7_day_avg'\n 'previous_day_admission_adult_covid_confirmed_18_19_7_day_sum'\n 'previous_day_admission_pediatric_covid_confirmed_12_17_7_day_sum'\n 'previous_day_total_ed_visits_7_day_sum'\n 'staffed_adult_icu_bed_occupancy_7_day_sum'\n 'staffed_adult_icu_bed_occupancy_7_day_coverage'\n 'previous_day_admission_adult_covid_confirmed_50'\n 'previous_day_admission_adult_covid_confirmed_7_day_sum'\n 'total_beds_7_day_coverage'\n 'total_pediatric_patients_hospitalized_confirmed_and_suspected_covid_7_day_coverage'\n 'total_adult_patients_hospitalized_confirmed_covid_7_day_sum'\n 'total_staffed_pediatric_icu_beds_7_day_coverage' 'hospital_name'\n 'previous_day_admission_adult_covid_confirmed_20_29_7_day_sum'\n 'all_pediatric_inpatient_bed_occupied_7_day_avg'\n 'previous_day_admission_pediatric_covid_confirmed_7_day_coverage'\n 'staffed_icu_pediatric_patients_confirmed_covid_7_day_coverage'\n 'total_pediatric_patients_hospitalized_confirmed_covid_7_day_avg'\n 'previous_day_admission_pediatric_covid_suspected_7_day_sum'\n 'total_staffed_adult_icu_beds_7_day_sum'\n 'previous_day_admission_adult_covid_confirmed_unknown_7_day_sum'\n 'address' 'total_staffed_adult_icu_beds_7_day_avg' 'hospital_pk'\n 'total_icu_beds_7_day_coverage'\n 'total_pediatric_patients_hospitalized_confirmed_and_suspected_covid_7_day_sum'\n 'inpatient_beds_7_day_sum'] \n Output: \n" ]
previous_day_admission_adult_covid_confirmed_7_day_coverage
cta
2024-06-24T00:00:00
090b4fb6f42c01d28d3dd382ee3b06c9596078e719d863eb53fe16bc1a0ca910
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['2015-08-06 12:07:40'], ['2015-08-01 07:12:04'], ['2015-08-27 19:44:02'], ['2015-08-20 04:14:52'], ['2015-08-03 04:24:42']] \n Classes: ['time' 'temp' 'light' 'power' 'dust' 'humidity' 'CO2'] \n Output: \n" ]
time
cta
2024-06-24T00:00:00
fb965026ca12eae296ee0e5a21c0f7f2691e7f27a829c7d6b69b3d659257222a
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[nan], [nan], [nan], [nan], [nan]] \n Classes: ['potassium_extractable' 'carbon_total' 'nitrogen_total'\n 'sodium_extractable' 'ph' 'carbon_organic' 'copper_extractable'\n 'horizon_upper' 'phosphorus_extractable' 'end_date' 'iron_extractable'\n 'aluminium_extractable' 'manganese_extractable' 'latitude'\n 'boron_extractable' 'electrical_conductivity' 'magnesium_extractable'\n 'longitude' 'zinc_extractable' 'start_date' 'calcium_extractable'\n 'source' 'sulphur_extractable' 'horizon_lower'] \n Output: \n" ]
zinc_extractable
cta
2024-06-24T00:00:00
602d69fbe97264184593d70751ac8421a674ccc32daa16d0a251266d600e41b6
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[40.0], [nan], [nan], [nan], [nan]] \n Classes: ['annual_salary' 'department' 'salary_or_hourly' 'typical_hours'\n 'hourly_rate' 'name' 'job_titles' 'full_or_part_time'] \n Output: \n" ]
typical_hours
cta
2024-06-24T00:00:00
710e9427be77576c22d1e45a519a3e25c804d22150ca272b321b7c6916bb08c7
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['UNKNOWN INVENTORY'], ['UNKNOWN INVENTORY'], ['ACTIVE'], ['ACTIVE'], ['ACTIVE']] \n Classes: ['courses_available' 'provider_status' 'address1'\n ':@computed_region_pqdx_y6mm' 'county' 'npi' 'provider_note'\n 'national_drug_code' 'address2' 'last_report_date' 'geocoded_address'\n 'zip' 'state_code' 'order_label' 'city' 'provider_name'] \n Output: \n" ]
provider_status
cta
2024-06-24T00:00:00
901488c5b80e759ac79c75455b21b7680ecd546d5529c76483a65dd96a3dab82
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['Eucrite-mmict'], ['L6'], ['Stone-uncl'], ['H5'], ['L5']] \n Classes: ['id' 'geolocation' 'fall' 'reclat' 'name' 'reclong' 'mass'\n ':@computed_region_cbhk_fwbd' 'year' 'nametype' 'recclass'\n ':@computed_region_nnqa_25f4'] \n Output: \n" ]
recclass
cta
2024-06-24T00:00:00
2a096cf1746e2653f40f60879ceed7f994e888a06a029a143dc3b160040e756f
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[1.1405], [1.0535], [0.5805], [1.3905], [0.569]] \n Classes: ['Shucked_weight' 'Viscera_weight' 'Length' 'Rings' 'Whole_weight'\n 'Diameter' 'Shell_weight' 'id' 'Height' 'Sex'] \n Output: \n" ]
Whole_weight
cta
2024-06-24T00:00:00
5f2869cd7e61c776c9b5ceb1ee3f92fd09cb1b636d76bf32e573d6a8a8faced0
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[7.3], [0.0], [36.4], [21.2], [24.7]] \n Classes: ['RVAL3' 'RVAL1' 'WL2' 'RVAL2' 'VAL1' 'VAL3' 'WL3' 'WL1' 'VAL2'\n 'DeviceTimeStamp'] \n Output: \n" ]
WL3
cta
2024-06-24T00:00:00
25461ebb72e6daae6d0dc5815dcde9cd3fb2cf5150fe435f336775b00b45336d
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[22.656668], [19.917999], [23.328667], [20.456667], [92.657333]] \n Classes: ['date' 'price'] \n Output: \n" ]
price
cta
2024-06-24T00:00:00
a435d97ba2ea930c89581870ce3bdc86e96e6399ce7fc3ef7ed19bf88f3771a6
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['2023-11-16T00:00:00.000'], ['2022-06-16T00:00:00.000'], ['2020-09-04T00:00:00.000'], ['2023-03-01T00:00:00.000'], ['2023-11-09T00:00:00.000']] \n Classes: ['unidad' 'vigenciahasta' 'vigenciadesde' 'valor'] \n Output: \n" ]
vigenciahasta
cta
2024-06-24T00:00:00
3a3c5b4774627ce2884a00d76ebda25faae4b9ac1e76da7ae81513a08531af21
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[1039372], [1603137], [2845332], [1193999], [3335438]] \n Classes: ['gis_council_district' 'sprinkler' 'building_type' 'latest_action_date'\n 'zoning_dist1' 'boiler' 'gis_bin' 'existingno_of_stories' 'mechanical'\n 'doc__' 'adult_estab' 'withdrawal_flag' 'paid' 'assigned'\n 'pre__filing_date' 'horizontal_enlrgmt' 'applicant_s_last_name'\n 'job_no_good_count' 'owner_s_business_name' 'owner_sphone__'\n 'existing_height' 'borough' 'total_est__fee' 'block'\n 'proposed_dwelling_units' 'street_name' 'gis_nta_name' 'equipment'\n 'job_s1_no' 'other' 'owner_s_last_name' 'fully_paid' 'zoning_dist3'\n 'special_district_1' 'owner_type' 'applicant_professional_title'\n 'plumbing' 'owner_s_first_name' 'existing_dwelling_units'\n 'community___board' 'house__' 'fuel_storage' 'job_status_descrp'\n 'dobrundate' 'total_construction_floor_area' 'site_fill'\n 'proposed_zoning_sqft' 'other_description' 'vertical_enlrgmt'\n 'job_status' 'efiling_filed' 'professional_cert' 'fee_status'\n 'gis_longitude' 'proposed_no_of_stories' 'little_e'\n 'enlargement_sq_footage' 'special_district_2' 'street_frontage'\n 'zoning_dist2' 'standpipe' 'signoff_date' 'building_class'\n 'fully_permitted' 'bin__' 'applicant_s_first_name' 'landmarked'\n 'proposed_height' 'special_action_status' 'gis_census_tract'\n 'existing_occupancy' 'cluster' 'applicant_license__' 'gis_latitude'\n 'loft_board' 'special_action_date' 'fire_suppression' 'city_owned'\n 'pc_filed' 'job_type' 'fuel_burning' 'job_description' 'lot' 'curb_cut'\n 'approved' 'non_profit' 'existing_zoning_sqft' 'initial_cost'\n 'proposed_occupancy' 'fire_alarm' 'job__'] \n Output: \n" ]
job_s1_no
cta
2024-06-24T00:00:00
71fb9aae0aa1fd2fd7b0a41ffa1c2235cd23ab372bb1d1d039e7ebf150aad656
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['Bahary'], ['CHAN'], ['CHANG'], ['SIDERIS'], ['EARLY']] \n Classes: ['fuel_storage' 'landmarked' 'existing_dwelling_units' 'mechanical'\n 'plumbing' 'applicant_s_first_name' 'professional_cert' 'house__'\n 'zoning_dist1' 'boiler' 'job_status' 'existingno_of_stories' 'fee_status'\n 'lot' 'fire_suppression' 'pre__filing_date' 'block' 'proposed_occupancy'\n 'special_district_2' 'gis_nta_name' 'special_action_date'\n 'existing_occupancy' 'total_est__fee' 'proposed_no_of_stories'\n 'street_frontage' 'signoff_date' 'horizontal_enlrgmt' 'job_s1_no'\n 'proposed_height' 'community___board' 'initial_cost' 'street_name'\n 'owner_s_last_name' 'vertical_enlrgmt' 'borough' 'job_no_good_count'\n 'equipment' 'doc__' 'curb_cut' 'building_type' 'building_class'\n 'dobrundate' 'pc_filed' 'applicant_professional_title'\n 'enlargement_sq_footage' 'fully_paid' 'job_type' 'approved'\n 'zoning_dist3' 'standpipe' 'job_description' 'bin__' 'fully_permitted'\n 'sprinkler' 'proposed_zoning_sqft' 'non_profit' 'cluster'\n 'proposed_dwelling_units' 'other_description' 'latest_action_date'\n 'owner_s_first_name' 'gis_longitude' 'assigned' 'fuel_burning'\n 'efiling_filed' 'other' 'owner_sphone__' 'loft_board' 'existing_height'\n 'site_fill' 'special_action_status' 'city_owned' 'owner_type'\n 'fire_alarm' 'special_district_1' 'job__' 'little_e'\n 'gis_council_district' 'adult_estab' 'withdrawal_flag' 'gis_bin'\n 'applicant_license__' 'owner_s_business_name' 'paid' 'gis_census_tract'\n 'gis_latitude' 'existing_zoning_sqft' 'total_construction_floor_area'\n 'zoning_dist2' 'applicant_s_last_name' 'job_status_descrp'] \n Output: \n" ]
applicant_s_last_name
cta
2024-06-24T00:00:00
178c1f72e05a48d00980e3f21a6a33eb66c2c5fd87d78b72a92d4423cf3b3e40
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[0.0], [0.0], [0.0], [0.1426607705384305], [0.0]] \n Classes: ['freq_4' 'freq_3' 'freq_5' 'freq_6' 'freq_2' 'Areas' 'freq_1'] \n Output: \n" ]
freq_3
cta
2024-06-24T00:00:00
842cec572ddb0d7d642abdc3919a6b340a6787b4128d37184ad9d69095bdf875
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['%'], ['%'], ['%'], ['%'], ['%']] \n Classes: ['notes' 'on_track' 'measure_type' 'fiscal_year' 'priority_measure'\n 'data_type' 'budget_book' 'date' 'reporting_frequency' 'key_measure'\n 'program_name' 'id' 'active' 'target_met' 'measure_target'\n 'measure_value' 'org_number' 'dept_name' 'measure_value_type'\n 'measure_name' 'measure_id'] \n Output: \n" ]
measure_value_type
cta
2024-06-24T00:00:00
9ed22ed7d6c73a08f9522684d4996821054dde714067e644bf8225fe9f2817ff
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[1.31], [2900.0], [24.71], [466.0], [28.1]] \n Classes: ['reclat' 'fall' 'year' 'GeoLocation' 'recclass' 'nametype' 'id'\n 'mass (g)' 'reclong' 'name'] \n Output: \n" ]
mass (g)
cta
2024-06-24T00:00:00
6674aadb0c124d37c4b10b3a8fb1fef68aa6e697c6c8b315f07244721921136f
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[\"This program includes funding to implement improvements to the Caltrain/High-Speed Rail Corridor. Improvements include grade separations funded by Santa Clara County's Measure B and San Mateo County's Measure A, as well as future grade separations and other modernization improvements within the Bay Area's urban core that serve the dual purpose of connecting High Speed Rail to the Bay Area and improving the Caltrain system.\"], [\"This program includes funding to implement other programmatic investments to enhance local transit frequency, capacity and reliability. This program generally implements county, transit agency, and other local programs and initiatives to make bus and light rail travel faster and more reliable. Improvements include fleet and facilities expansions; transit corridor improvements; and transit station improvements. Example investments include implementation of SFMTA's bus and facility expansion (Core Capacity) and Parkmerced Transportation Improvements; and Santa Clara County's High-Capacity Transit Corridors program, SR-85 Corridor Improvements, and Downtown Coordinated Area Plan and Transit Center Improvements.\"], ['This program includes funding to implement interchange improvements at I-680/SR-12, Redwood Pkwy and Lagoon Valley Rd.'], ['This program includes funding to implement improvements to existing Caltrain rail service between San Francisco and San Jose, including frequency upgrades (8 trains per hour per direction in peak).'], ['This program includes funding to implement new rapid bus service along E 14th St/Mission St/Fremont Blvd between the San Leandro and Warm Springs BART stations. Improvements include frequency upgrades (10 minute peak headways for Route 10 and 20 minute peak headways for Route 99), dedicated lanes and mobility hubs at BART stations.']] \n Classes: ['open_period' 'title' 'plan_strategy' 'county' 'rtpid' 'scope'\n 'funding_millions_yoe'] \n Output: \n" ]
scope
cta
2024-06-24T00:00:00
cc82520bd9c7eeb5f06c9f7ebf1dd59b89bfd90d91080f88d49bd069250152e5
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['Your trial period has ended. Upgrade to a premium plan for unlimited access.'], [\"You've won a shopping spree! Click here to claim your voucher.\"], [\"We're excited to announce our upcoming webinar series. Register now to reserve your spot!\"], [\"Your order is confirmed. You'll receive a confirmation email shortly with the details.\"], ['Your Netflix subscription has expired. Click here to renew now!']] \n Classes: ['label' 'email'] \n Output: \n" ]
email
cta
2024-06-24T00:00:00
ae6113bfce471464f03e7ff173b9a9e13a8bb431439c41d82100097c5d61dd7d
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['Pre-PQ Process'], ['Pre-PQ Process'], ['Pre-PQ Process'], ['Pre-PQ Process'], ['Pre-PQ Process']] \n Classes: ['scheduled_delivery_date' 'line_item_value' 'sub_classification'\n 'freight_cost_usd' 'weight_kilograms' 'dosage_form' 'pack_price'\n 'po_sent_to_vendor_date' 'pq_first_sent_to_client_date' 'pq'\n 'delivery_recorded_date' 'dosage' 'fulfill_via' 'po_so'\n 'first_line_designation' 'brand' 'asn_dn' 'unit_of_measure_per_pack'\n 'unit_price' 'id' 'line_item_insurance_usd' 'vendor' 'vendor_inco_term'\n 'manufacturing_site' 'product_group' 'project_code' 'line_item_quantity'\n 'item_description' 'country' 'managed_by' 'delivered_to_client_date'\n 'shipment_mode' 'molecule_test_type'] \n Output: \n" ]
pq
cta
2024-06-24T00:00:00
5d098d85a099630e19fe3b715500589f0face5dafeffdf9cb3c23f5259600aa3
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[\"Revise the text with vivid descriptions and an upbeat, celebratory tone to capture the festival's triumph and community spirit.\"], ['Revise the text into a haiku format, with a syllable structure of 5-7-5 in each line, while maintaining the essence of observing nature through binoculars.'], ['Revise the text into a more casual and friendly tone.'], ['Revise the text to have a more poetic and nostalgic tone.'], ['Revise the text with an exaggerated, poetic style while retaining the core meaning.']] \n Classes: ['id' 'original_text' 'rewritten_text' 'rewrite_prompt'] \n Output: \n" ]
rewrite_prompt
cta
2024-06-24T00:00:00
cea94c94a9f19381ae78825923b0c72cf9f16907bd0213bea6beca953a70b085
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['Snoring'], ['Whistling respiration'], ['Asthmatic respiration'], ['Irregular respiration'], ['Hot breath']] \n Classes: ['Remedy' 'Final_remedy' 'Symptom' 'RemedyStrength' 'Part_of_remedy'] \n Output: \n" ]
Symptom
cta
2024-06-24T00:00:00
43b7ccbcb6eef8606b1b0aaf4c1c858948f75df49caa0589f74a107a9eaf1ea8
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['ham'], ['spam'], ['ham'], ['ham'], ['spam']] \n Classes: ['label' 'email'] \n Output: \n" ]
label
cta
2024-06-24T00:00:00
bb6b6f851602827f90538249a5eb7dffa6755060c85a51cd16b13500bbaf57d1
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[271], [271], [271], [271], [271]] \n Classes: ['active' 'key_measure' 'priority_measure' 'measure_value_type'\n 'measure_target' 'measure_type' 'reporting_frequency' 'dept_name'\n 'program_name' 'org_number' 'id' 'fiscal_year' 'date' 'on_track'\n 'measure_name' 'measure_id' 'target_met' 'budget_book' 'data_type'\n 'measure_value'] \n Output: \n" ]
measure_id
cta
2024-06-24T00:00:00
2c40553d646d1f2d657f5f982f49b9ca64dfd6e1b675965830c419412c6076c1
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[3296], [3016], [1938], [3055], [3139]] \n Classes: ['CarName' 'symboling' 'enginetype' 'carlength' 'peakrpm' 'wheelbase'\n 'fuelsystem' 'stroke' 'curbweight' 'cylindernumber' 'citympg'\n 'aspiration' 'doornumber' 'enginelocation' 'carbody' 'boreratio'\n 'drivewheel' 'enginesize' 'horsepower' 'highwaympg' 'carheight' 'price'\n 'car_ID' 'compressionratio' 'carwidth' 'fueltype'] \n Output: \n" ]
curbweight
cta
2024-06-24T00:00:00
2cf1d19bf1e2c876de558ca796e1f48a65342d6927b11970b750152085d50ec7
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['2023-11-16T00:00:00.000'], ['2022-06-16T00:00:00.000'], ['2020-09-04T00:00:00.000'], ['2023-03-01T00:00:00.000'], ['2023-11-09T00:00:00.000']] \n Classes: ['valor' 'vigenciadesde' 'vigenciahasta' 'unidad'] \n Output: \n" ]
vigenciahasta
cta
2024-06-24T00:00:00
9c74edf111b76d22e29f59efc87f353419396850fea9cecb6d1f3535d7370cea
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['DK2'], ['GB'], ['FI'], ['HU'], ['HU']] \n Classes: ['fecha_actualizacion' 'hora' 'bandera' 'origen_dato' 'sistema'\n 'Unnamed: 0' 'tipo_moneda' 'fecha' 'precio'] \n Output: \n" ]
sistema
cta
2024-06-24T00:00:00
537b9002304148b4aef6f995c3012d9ae159196ab216bfb6fa7ef40f5585cddb
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[232058], [4581], [80510], [183295], [232058]] \n Classes: ['quantity' 'species'] \n Output: \n" ]
quantity
cta
2024-06-24T00:00:00
7a5f7b3b6f5972d4a6c9a42a1e3f6cd73e2f8cb7cb57685a964ff9d6cd43a03d
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[860], [1294], [1130], [1095], [3092]] \n Classes: ['description' 'latitudes' 'military_base_name' 'longtitudes' 'Unnamed: 0'\n 'coordinates'] \n Output: \n" ]
Unnamed: 0
cta
2024-06-24T00:00:00
aaa722230f998bcba4bfe53b5843b770a09c16203c4de187c1b810c8167b6471
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['70.443.997'], ['10.899.999'], ['20.280.795'], ['0'], ['1.2041']] \n Classes: ['Year' 'code country' 'Maize yield' 'country'] \n Output: \n" ]
Maize yield
cta
2024-06-24T00:00:00
58223a1f18c3cda82967cc3ba7d24813209e41470aee583167ee938ae01d3d21
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[nan], [0.0], [0.0], [nan], [nan]] \n Classes: ['deaths_covid_coverage'\n 'previous_week_therapeutic_a_casirivimab_imdevimab_courses_used'\n 'total_pediatric_patients_hospitalized_confirmed_covid'\n 'previous_day_admission_adult_covid_suspected_80_coverage'\n 'previous_day_admission_pediatric_covid_suspected_coverage'\n 'previous_day_admission_adult_covid_confirmed_60_69'\n 'previous_day_admission_adult_covid_confirmed_coverage'\n 'previous_day_admission_adult_covid_confirmed_30_39'\n 'inpatient_beds_utilization_denominator'\n 'previous_day_admission_adult_covid_confirmed_20_29_coverage'\n 'critical_staffing_shortage_today_not_reported'\n 'critical_staffing_shortage_anticipated_within_week_not_reported'\n 'previous_day_admission_pediatric_covid_confirmed_5_11'\n 'total_adult_patients_hospitalized_confirmed_covid'\n 'previous_day_admission_pediatric_covid_suspected'\n 'previous_day_deaths_covid_and_influenza'\n 'previous_day_admission_influenza_confirmed_coverage'\n 'previous_day_admission_adult_covid_confirmed_40_49'\n 'inpatient_beds_used_covid'\n 'previous_day_admission_pediatric_covid_confirmed_5_11_coverage'\n 'staffed_icu_pediatric_patients_confirmed_covid'\n 'previous_day_admission_adult_covid_confirmed_50_59_coverage'\n 'adult_icu_bed_utilization_coverage'\n 'total_patients_hospitalized_confirmed_influenza_and_covid_coverage'\n 'inpatient_beds_used_coverage' 'inpatient_bed_covid_utilization_coverage'\n 'total_staffed_pediatric_icu_beds'\n 'on_hand_supply_therapeutic_c_bamlanivimab_etesevimab_courses'\n 'all_pediatric_inpatient_bed_occupied_coverage'\n 'previous_day_admission_adult_covid_suspected_50_59_coverage'\n 'total_staffed_pediatric_icu_beds_coverage'\n 'adult_icu_bed_covid_utilization'\n 'previous_day_admission_pediatric_covid_confirmed_unknown'\n 'previous_day_admission_adult_covid_suspected_70_79'\n 'total_patients_hospitalized_confirmed_influenza_coverage'\n 'previous_day_admission_adult_covid_suspected_unknown'\n 'previous_day_admission_adult_covid_confirmed_70_79'\n 'previous_day_admission_adult_covid_confirmed_60_69_coverage'\n 'staffed_adult_icu_bed_occupancy_coverage'\n 'staffed_pediatric_icu_bed_occupancy'\n 'previous_week_therapeutic_c_bamlanivimab_etesevimab_courses_used'\n 'previous_day_deaths_influenza_coverage'\n 'previous_day_admission_adult_covid_suspected_70_79_coverage'\n 'previous_day_admission_adult_covid_suspected_unknown_coverage'\n 'previous_day_admission_pediatric_covid_confirmed_0_4_coverage'\n 'previous_day_admission_adult_covid_suspected_80_'\n 'on_hand_supply_therapeutic_a_casirivimab_imdevimab_courses'\n 'staffed_icu_adult_patients_confirmed_covid_coverage'\n 'previous_day_admission_adult_covid_confirmed_20_29'\n 'inpatient_beds_utilization_coverage'\n 'total_patients_hospitalized_confirmed_influenza_and_covid'\n 'previous_day_deaths_influenza' 'all_pediatric_inpatient_beds'\n 'all_pediatric_inpatient_bed_occupied'\n 'total_pediatric_patients_hospitalized_confirmed_and_suspected_covid_coverage'\n 'total_patients_hospitalized_confirmed_influenza'\n 'previous_day_admission_pediatric_covid_confirmed'\n 'percent_of_inpatients_with_covid_numerator'\n 'inpatient_beds_used_covid_coverage'\n 'previous_day_admission_pediatric_covid_confirmed_unknown_coverage'\n 'previous_day_admission_pediatric_covid_confirmed_0_4'\n 'percent_of_inpatients_with_covid_coverage'\n 'hospital_onset_covid_coverage' 'icu_patients_confirmed_influenza'\n 'previous_day_admission_adult_covid_suspected'\n 'adult_icu_bed_utilization_denominator'\n 'total_pediatric_patients_hospitalized_confirmed_covid_coverage'\n 'previous_day_admission_adult_covid_suspected_60_69_coverage'\n 'previous_day_admission_adult_covid_confirmed_30_39_coverage'\n 'total_adult_patients_hospitalized_confirmed_and_suspected_covid'\n 'inpatient_beds_utilization_numerator'\n 'previous_day_admission_adult_covid_confirmed_18_19'\n 'critical_staffing_shortage_today_yes'\n 'previous_day_admission_adult_covid_suspected_20_29' 'state'\n 'staffed_icu_pediatric_patients_confirmed_covid_coverage'\n 'previous_day_admission_influenza_confirmed'\n 'previous_day_admission_adult_covid_suspected_30_39_coverage'\n 'deaths_covid' 'staffed_icu_adult_patients_confirmed_and_suspected_covid'\n 'staffed_adult_icu_bed_occupancy' 'inpatient_bed_covid_utilization'\n 'staffed_icu_adult_patients_confirmed_covid'\n 'adult_icu_bed_covid_utilization_coverage'\n 'total_pediatric_patients_hospitalized_confirmed_and_suspected_covid'\n 'previous_day_admission_adult_covid_suspected_40_49_coverage'\n 'on_hand_supply_therapeutic_b_bamlanivimab_courses'\n 'previous_day_admission_adult_covid_confirmed_80'\n 'adult_icu_bed_covid_utilization_denominator'\n 'previous_week_therapeutic_b_bamlanivimab_courses_used'\n 'staffed_icu_adult_patients_confirmed_and_suspected_covid_coverage'\n 'previous_day_admission_adult_covid_suspected_40_49'\n 'previous_day_admission_adult_covid_confirmed_70_79_coverage'\n 'inpatient_bed_covid_utilization_denominator' 'inpatient_beds_used'\n 'date' 'previous_day_admission_adult_covid_suspected_18_19'\n 'hospital_onset_covid' 'percent_of_inpatients_with_covid'\n 'percent_of_inpatients_with_covid_denominator'\n 'total_adult_patients_hospitalized_confirmed_covid_coverage'\n 'total_staffed_adult_icu_beds' 'inpatient_beds_utilization'\n 'previous_day_admission_adult_covid_confirmed_unknown_coverage'\n 'previous_day_deaths_covid_and_influenza_coverage'\n 'icu_patients_confirmed_influenza_coverage'\n 'previous_day_admission_adult_covid_confirmed_unknown'\n 'previous_day_admission_adult_covid_confirmed'\n 'inpatient_bed_covid_utilization_numerator'\n 'total_staffed_adult_icu_beds_coverage'\n 'all_pediatric_inpatient_beds_coverage'\n 'total_adult_patients_hospitalized_confirmed_and_suspected_covid_coverage'\n 'adult_icu_bed_covid_utilization_numerator'\n 'staffed_pediatric_icu_bed_occupancy_coverage'\n 'previous_day_admission_pediatric_covid_confirmed_12_17'\n 'previous_day_admission_adult_covid_confirmed_80_coverage'\n 'previous_day_admission_adult_covid_suspected_18_19_coverage'\n 'previous_day_admission_adult_covid_suspected_coverage'\n 'previous_day_admission_adult_covid_suspected_50_59'\n 'previous_day_admission_pediatric_covid_confirmed_coverage'\n 'previous_day_admission_adult_covid_suspected_30_39'\n 'critical_staffing_shortage_anticipated_within_week_no'\n 'inpatient_beds_coverage'\n 'previous_day_admission_adult_covid_confirmed_50_59'\n 'previous_day_admission_adult_covid_suspected_20_29_coverage'\n 'previous_day_admission_adult_covid_confirmed_18_19_coverage'\n 'critical_staffing_shortage_today_no'\n 'previous_day_admission_adult_covid_confirmed_40_49_coverage'\n 'adult_icu_bed_utilization_numerator' 'inpatient_beds'\n 'critical_staffing_shortage_anticipated_within_week_yes'\n 'previous_day_admission_adult_covid_suspected_60_69'\n 'adult_icu_bed_utilization'\n 'previous_day_admission_pediatric_covid_confirmed_12_17_coverage'] \n Output: \n" ]
previous_week_therapeutic_c_bamlanivimab_etesevimab_courses_used
cta
2024-06-24T00:00:00
0e035026e0e096f6275c4e0699603f502f04d6c9904bc938b46df4dc6300116b
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [[-72.99889], [50.35], [21.11073], [0.0], [-76.18333]] \n Classes: ['year' 'id' 'fall' 'nametype' 'recclass' 'mass (g)' 'reclat'\n 'GeoLocation' 'name' 'reclong'] \n Output: \n" ]
reclat
cta
2024-06-24T00:00:00
1845745b3354782800cff1a055131c3e64c58719dced8d96d69083ab210e0391
data_analysis
[ "Pick the column's class based on the provided column sample. Choose exactly one of the listed classes. Please respond only with the name of the class. \n Column sample: [['Lamivudine 10mg/ml [Epivir], oral solution, Bottle, 240 ml'], ['Stavudine 20mg, capsules, 60 Caps'], ['Tenofovir Disoproxil Fumarate 300mg, tablets, 30 Tabs'], ['Didanosine 25mg [Videx], chewable tablets, 60 Tabs'], ['Lamivudine 10mg/ml, oral solution, Bottle, 240 ml']] \n Classes: ['dosage_form' 'manufacturing_site' 'pack_price' 'asn_dn'\n 'sub_classification' 'line_item_value' 'id' 'molecule_test_type'\n 'freight_cost_usd' 'item_description' 'country' 'po_sent_to_vendor_date'\n 'delivery_recorded_date' 'fulfill_via' 'scheduled_delivery_date'\n 'delivered_to_client_date' 'po_so' 'product_group' 'dosage'\n 'project_code' 'unit_of_measure_per_pack' 'line_item_quantity' 'brand'\n 'first_line_designation' 'pq' 'shipment_mode' 'managed_by'\n 'vendor_inco_term' 'line_item_insurance_usd' 'weight_kilograms' 'vendor'\n 'pq_first_sent_to_client_date' 'unit_price'] \n Output: \n" ]
item_description
cta
2024-06-24T00:00:00