cardiffnlp/databench · Datasets at Hugging Face

question string	answer string	type string	columns_used sequence	column_types sequence	sample_answer string	dataset string
Is the person with the highest net worth self-made?	True	boolean	[ "finalWorth", "selfMade" ]	[ "number[uint32]", "boolean" ]	False	001_Forbes
Does the youngest billionaire identify as male?	True	boolean	[ "age", "gender" ]	[ "number[UInt8]", "category" ]	True	001_Forbes
Is the city with the most billionaires in the United States?	True	boolean	[ "city", "country" ]	[ "category", "category" ]	True	001_Forbes
Is there a non-self-made billionaire in the top 5 ranks?	True	boolean	[ "rank", "selfMade" ]	[ "number[uint16]", "boolean" ]	False	001_Forbes
Does the oldest billionaire have a philanthropy score of 5?	False	boolean	[ "age", "philanthropyScore" ]	[ "number[UInt8]", "number[UInt8]" ]	False	001_Forbes
What is the age of the youngest billionaire?	19.0	number	[ "age" ]	[ "number[UInt8]" ]	32.0	001_Forbes
How many billionaires are there from the 'Technology' category?	343	number	[ "category" ]	[ "category" ]	0	001_Forbes
What's the total worth of billionaires in the 'Automotive' category?	583600	number	[ "category", "finalWorth" ]	[ "category", "number[uint32]" ]	0	001_Forbes
How many billionaires have a philanthropy score above 3?	25	number	[ "philanthropyScore" ]	[ "number[UInt8]" ]	0	001_Forbes
What's the rank of the wealthiest non-self-made billionaire?	3	number	[ "selfMade", "rank" ]	[ "boolean", "number[uint16]" ]	288	001_Forbes
Which category does the richest billionaire belong to?	Automotive	category	[ "finalWorth", "category" ]	[ "number[uint32]", "category" ]	Food & Beverage	001_Forbes
What's the country of origin of the oldest billionaire?	United States	category	[ "age", "country" ]	[ "number[UInt8]", "category" ]	United Kingdom	001_Forbes
What's the gender of the billionaire with the highest philanthropy score?	M	category	[ "philanthropyScore", "gender" ]	[ "number[UInt8]", "category" ]	M	001_Forbes
What's the source of wealth for the youngest billionaire?	drugstores	category	[ "age", "source" ]	[ "number[UInt8]", "category" ]	fintech	001_Forbes
What is the title of the billionaire with the lowest rank?	null	category	[ "rank", "title" ]	[ "number[uint16]", "category" ]	null	001_Forbes
List the top 3 countries with the most billionaires.	['United States', 'China', 'India']	list[category]	[ "country" ]	[ "category" ]	['United States', 'China', 'Brazil']	001_Forbes
List the top 5 sources of wealth for billionaires.	['real estate', 'investments', 'pharmaceuticals', 'diversified', 'software']	list[category]	[ "source" ]	[ "category" ]	['diversified', 'media, automotive', 'Semiconductor materials', 'WeWork', 'beverages']	001_Forbes
List the top 4 cities where the youngest billionaires live.	[nan, 'Los Angeles', 'Jiaozuo', 'Oslo']	list[category]	[ "age", "city" ]	[ "number[UInt8]", "category" ]	['San Francisco', 'New York', 'Wuhan', 'Bangalore']	001_Forbes
List the bottom 3 categories with the fewest billionaires.	['Logistics', 'Sports', 'Gambling & Casinos']	list[category]	[ "category" ]	[ "category" ]	['Service', 'Fashion & Retail', 'Manufacturing']	001_Forbes
List the bottom 2 countries with the least number of billionaires.	['Colombia', 'Andorra']	list[category]	[ "country" ]	[ "category" ]	['Canada', 'Egypt']	001_Forbes
List the top 5 ranks of billionaires who are not self-made.	[3, 10, 14, 16, 18]	list[number]	[ "selfMade", "rank" ]	[ "boolean", "number[uint16]" ]	[288, 296, 509, 523, 601]	001_Forbes
List the bottom 3 ages of billionaires who have a philanthropy score of 5.	[48.0, 83.0, 83.0]	list[number]	[ "philanthropyScore", "age" ]	[ "number[UInt8]", "number[UInt8]" ]	[]	001_Forbes
List the top 6 final worth values of billionaires in the 'Technology' category.	[171000, 129000, 111000, 107000, 106000, 91400]	list[number]	[ "category", "finalWorth" ]	[ "category", "number[uint32]" ]	[]	001_Forbes
List the bottom 4 ranks of female billionaires.	[14, 18, 21, 30]	list[number]	[ "gender", "rank" ]	[ "category", "number[uint16]" ]	[]	001_Forbes
List the top 2 final worth values of billionaires in the 'Automotive' category.	[219000, 44800]	list[number]	[ "category", "finalWorth" ]	[ "category", "number[uint32]" ]	[]	001_Forbes
Did any children below the age of 18 survive?	True	boolean	[ "Age", "Survived" ]	[ "number[UInt8]", "boolean" ]	True	002_Titanic
Were there any passengers who paid a fare of more than $500?	True	boolean	[ "Fare" ]	[ "number[double]" ]	False	002_Titanic
Is every passenger's name unique?	True	boolean	[ "Name" ]	[ "text" ]	True	002_Titanic
Were there any female passengers in the 3rd class who survived?	True	boolean	[ "Sex", "Pclass", "Survived" ]	[ "category", "number[uint8]", "boolean" ]	True	002_Titanic
How many unique passenger classes are present in the dataset?	3	number	[ "Pclass" ]	[ "number[uint8]" ]	3	002_Titanic
What's the maximum age of the passengers?	80.0	number	[ "Age" ]	[ "number[UInt8]" ]	69.0	002_Titanic
How many passengers boarded without any siblings or spouses?	604	number	[ "Siblings_Spouses Aboard" ]	[ "number[uint8]" ]	12	002_Titanic
On average, how much fare did the passengers pay?	32.31	number	[ "Fare" ]	[ "number[double]" ]	23.096459999999997	002_Titanic
Which passenger class has the highest number of survivors?	1	category	[ "Pclass", "Survived" ]	[ "number[uint8]", "boolean" ]	3	002_Titanic
What's the most common gender among the survivors?	female	category	[ "Sex", "Survived" ]	[ "category", "boolean" ]	female	002_Titanic
Among those who survived, which fare range was the most common: (0-50, 50-100, 100-150, 150+)?	0-50	category	[ "Fare", "Survived" ]	[ "number[double]", "boolean" ]	0-50	002_Titanic
What's the most common age range among passengers: (0-18, 18-30, 30-50, 50+)?	18-30	category	[ "Age" ]	[ "number[UInt8]" ]	18-30	002_Titanic
Name the top 3 passenger classes by survival rate.	[1, 2, 3]	list[category]	[ "Pclass", "Survived" ]	[ "number[uint8]", "boolean" ]	[1, 3, 2]	002_Titanic
Could you list the bottom 3 fare ranges by number of survivors: (0-50, 50-100, 100-150, 150+)?	['50-100', '150+', '100-150']	list[category]	[ "Fare", "Survived" ]	[ "number[double]", "boolean" ]	[50-100, 150+, 100-150]	002_Titanic
What is the top 4 age ranges('30-50', '18-30', '0-18', '50+') with the highest number of survivors?	['30-50', '18-30', '0-18', '50+']	list[category]	[ "Age", "Survived" ]	[ "number[UInt8]", "boolean" ]	[30-50, 18-30, 0-18, 50+]	002_Titanic
What are the top 2 genders by average fare paid?	['female', 'male']	list[category]	[ "Sex", "Fare" ]	[ "category", "number[double]" ]	[female, male]	002_Titanic
What are the oldest 3 ages among the survivors?	[24.0, 22.0, 27.0]	list[number]	[ "Age", "Survived" ]	[ "number[UInt8]", "boolean" ]	[56.0, 47.0, 42.0]	002_Titanic
Which are the top 4 fares paid by survivors?	[13.0, 26.0, 7.75, 10.5]	list[number]	[ "Fare", "Survived" ]	[ "number[double]", "boolean" ]	[133.65, 39.0, 35.5, 30.5]	002_Titanic
Could you list the youngest 3 ages among the survivors?	[53.0, 55.0, 11.0]	list[number]	[ "Age", "Survived" ]	[ "number[UInt8]", "boolean" ]	[14.0, 24.0, 28.0]	002_Titanic
Which are the bottom 4 fares among those who didn't survive?	[90.0, 12.275, 9.35, 10.5167]	list[number]	[ "Fare", "Survived" ]	[ "number[double]", "boolean" ]	[13.0, 7.75, 11.5, 10.1708]	002_Titanic
Is the average age of the respondents above 30?	True	boolean	[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "a", "g", "e", "?", " ", "👶", "🏻", "👵", "🏻", "'", "]" ]	[ "number[uint8]" ]	True	003_Love
Are there more single individuals than married ones in the dataset?	True	boolean	[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "c", "i", "v", "i", "l", " ", "s", "t", "a", "t", "u", "s", "?", " ", "💍", "'", "]" ]	[ "category" ]	False	003_Love
Do the majority of respondents have a height greater than 170 cm?	True	boolean	[ "[", "W", "h", "a", "t", "'", "s", " ", "y", "o", "u", "r", " ", "h", "e", "i", "g", "h", "t", "?", " ", "i", "n", " ", "c", "m", " ", "📏", "]" ]	[ "number[uint8]" ]	True	003_Love
Is the most frequent hair color black?	False	boolean	[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "h", "a", "i", "r", " ", "c", "o", "l", "o", "r", "?", " ", "👩", "🦰", "👱", "🏽", "'", "]" ]	[ "category" ]	False	003_Love
How many unique nationalities are present in the dataset?	13	number	[ "[", "W", "h", "a", "t", "'", "s", " ", "y", "o", "u", "r", " ", "n", "a", "t", "i", "o", "n", "a", "l", "i", "t", "y", "?", "\"", "]", "\"" ]	[ "category" ]	1	003_Love
What is the average gross annual salary?	56332.81720430108	number	[ "[", "'", "G", "r", "o", "s", "s", " ", "a", "n", "n", "u", "a", "l", " ", "s", "a", "l", "a", "r", "y", " ", "(", "i", "n", " ", "e", "u", "r", "o", "s", ")", " ", "💸", "'", "]" ]	[ "number[UInt32]" ]	62710.0	003_Love
How many respondents wear glasses all the time?	0	number	[ "[", "'", "H", "o", "w", " ", "o", "f", "t", "e", "n", " ", "d", "o", " ", "y", "o", "u", " ", "w", "e", "a", "r", " ", "g", "l", "a", "s", "s", "e", "s", "?", " ", "👓", "'", "]" ]	[ "category" ]	0	003_Love
What's the median age of the respondents?	33.0	number	[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "a", "g", "e", "?", " ", "👶", "🏻", "👵", "🏻", "'", "]" ]	[ "number[uint8]" ]	32.5	003_Love
What is the most common level of studies achieved?	Master	category	[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "t", "h", "e", " ", "m", "a", "x", "i", "m", "u", "m", " ", "l", "e", "v", "e", "l", " ", "o", "f", " ", "s", "t", "u", "d", "i", "e", "s", " ", "y", "o", "u", " ", "h", "a", "v", "e", " ", "a", "c", "h", "i", "e", "v", "e", "d", "?", " ", "🎓", "'", "]" ]	[ "category" ]	Master	003_Love
Which body complexity has the least number of respondents?	Very thin	category	[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "b", "o", "d", "y", " ", "c", "o", "m", "p", "l", "e", "x", "i", "t", "y", "?", " ", "🏋", "️", "'", "]" ]	[ "category" ]	Obese	003_Love
What's the most frequent eye color?	Brown	category	[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "e", "y", "e", " ", "c", "o", "l", "o", "r", "?", " ", "👁", "️", "'", "]" ]	[ "category" ]	Brown	003_Love
Which sexual orientation has the highest representation?	Heterosexual	category	[ "[", "W", "h", "a", "t", "'", "s", " ", "y", "o", "u", "r", " ", "s", "e", "x", "u", "a", "l", " ", "o", "r", "i", "e", "n", "t", "a", "t", "i", "o", "n", "?", "\"", "]", "\"" ]	[ "category" ]	Heterosexual	003_Love
List the top 3 most common areas of knowledge.	['[Computer Science]', '[Business]', '[Enginering & Architecture]']	list[category]	[ "[", "'", "W", "h", "a", "t", " ", "a", "r", "e", "a", " ", "o", "f", " ", "k", "n", "o", "w", "l", "e", "d", "g", "e", " ", "i", "s", " ", "c", "l", "o", "s", "e", "r", " ", "t", "o", " ", "y", "o", "u", "?", "'", "]" ]	[ "list[category]" ]	['[Computer Science]', '[Business]', '[Enginering & Architecture]']	003_Love
List the bottom 3 hair lengths in terms of frequency.	['Medium', 'Long', 'Bald']	list[category]	[ "[", "'", "H", "o", "w", " ", "l", "o", "n", "g", " ", "i", "s", " ", "y", "o", "u", "r", " ", "h", "a", "i", "r", "?", " ", "💇", "🏻", "♀", "️", "💇", "🏽", "♂", "️", "'", "]" ]	[ "category" ]	['Short', 'Medium', 'Long']	003_Love
Name the top 5 civil statuses represented in the dataset.	['Single', 'Married', 'In a Relationship', 'In a Relationship Cohabiting', 'Divorced']	list[category]	[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "c", "i", "v", "i", "l", " ", "s", "t", "a", "t", "u", "s", "?", " ", "💍", "'", "]" ]	[ "category" ]	['Married', 'In a Relationship', 'In a Relationship Cohabiting', 'Single', 'Divorced']	003_Love
What are the 4 least common hair colors?	['Red', 'Other', 'White', 'Blue']	list[category]	[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "h", "a", "i", "r", " ", "c", "o", "l", "o", "r", "?", " ", "👩", "🦰", "👱", "🏽", "'", "]" ]	[ "category" ]	['Brown', 'Black']	003_Love
What are the top 4 maximum gross annual salaries?	[500000.0, 360000.0, 300000.0, 300000.0]	list[number]	[ "[", "'", "G", "r", "o", "s", "s", " ", "a", "n", "n", "u", "a", "l", " ", "s", "a", "l", "a", "r", "y", " ", "(", "i", "n", " ", "e", "u", "r", "o", "s", ")", " ", "💸", "'", "]" ]	[ "number[UInt32]" ]	[150000.0, 130000.0, 125000.0, 120000.0]	003_Love
Name the bottom 3 values for the happiness scale.	[2, 2, 2]	list[number]	[ "[", "'", "H", "a", "p", "p", "i", "n", "e", "s", "s", " ", "s", "c", "a", "l", "e", "'", "]" ]	[ "number[uint8]" ]	[7, 10, 6]	003_Love
What are the 5 highest ages present in the dataset?	[65, 62, 60, 60, 59]	list[number]	[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "a", "g", "e", "?", " ", "👶", "🏻", "👵", "🏻", "'", "]" ]	[ "number[uint8]" ]	[65, 60, 51, 50, 50]	003_Love
List the bottom 6 skin tone values based on frequency.	[2, 1, 6, 0, 7, 8]	list[number]	[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "s", "k", "i", "n", " ", "t", "o", "n", "e", "?", "'", "]" ]	[ "number[uint8]" ]	[3, 1, 6, 2, 7, 0]	003_Love
Are there any trips with a total distance greater than 30 miles?	False	boolean	[ "trip_distance" ]	[ "number[double]" ]	False	004_Taxi
Were there any trips that cost more than $100 in total?	False	boolean	[ "total_amount" ]	[ "number[double]" ]	False	004_Taxi
Is there any trip with more than 6 passengers?	False	boolean	[ "passenger_count" ]	[ "number[uint8]" ]	False	004_Taxi
Did all the trips use a payment type of either 1 or 2?	False	boolean	[ "payment_type" ]	[ "number[uint8]" ]	True	004_Taxi
What is the maximum fare amount charged for a trip?	75.25	number	[ "fare_amount" ]	[ "number[double]" ]	85.0	004_Taxi
How many unique pickup locations are in the dataset?	96	number	[ "PULocationID" ]	[ "number[uint16]" ]	193	004_Taxi
What is the average tip amount given by passengers?	2.74	number	[ "tip_amount" ]	[ "number[double]" ]	1.5	004_Taxi
How many trips took place in the airport area?	99807	number	[ "Airport_fee" ]	[ "number[UInt8]" ]	194	004_Taxi
Which payment type is the most common in the dataset?	1	category	[ "payment_type" ]	[ "number[uint8]" ]	1	004_Taxi
Which vendor has the most trips recorded?	2	category	[ "VendorID" ]	[ "number[uint8]" ]	2	004_Taxi
What is the most common drop-off location?	236	category	[ "DOLocationID" ]	[ "number[uint16]" ]	161	004_Taxi
On which date did the first recorded trip occur?	2023-01-31	category	[ "tpep_pickup_datetime" ]	[ "date[ns", "UTC]" ]	2019-01-01 00:46:40	004_Taxi
Which are the top 3 most frequent pickup locations?	[161, 237, 236]	list[category]	[ "PULocationID" ]	[ "number[uint16]" ]	[237, 236, 161]	004_Taxi
Name the 4 most common rate codes used.	[1, 2, 5, 4]	list[category]	[ "RatecodeID" ]	[ "number[uint8]" ]	[1, 2, 5, 3]	004_Taxi
list the 2 most frequent store and forward flags.	['N', 'Y']	list[category]	[ "store_and_fwd_flag" ]	[ "category" ]	['N', 'Y']	004_Taxi
Identify the top 4 payment types used by frequency	[1, 2, 4, 3]	list[category]	[ "payment_type" ]	[ "number[uint8]" ]	[1, 2, 3]	004_Taxi
Report the 4 highest toll amounts paid.	[0, 0, 0, 0]	list[number]	[ "tolls_amount" ]	[ "number[uint8]" ]	[0, 0, 0, 0]	004_Taxi
list the top 3 longest trip distances	[19.83, 19.74, 19.68]	list[number]	[ "trip_distance" ]	[ "number[double]" ]	[8.32, 5.93, 2.8]	004_Taxi
Identify the 5 largest total amounts paid for trips.	[80.0, 80.0, 80.0, 80.0, 79.55]	list[number]	[ "total_amount" ]	[ "number[double]" ]	[45.8, 39.9, 33.2, 25.2, 24.87]	004_Taxi
Report the 6 highest fare amounts charged.	[75.25, 74.4, 73.0, 73.0, 73.0, 73.0]	list[number]	[ "fare_amount" ]	[ "number[double]" ]	[40.8, 28.9, 21.2, 17.0, 14.9, 13.5]	004_Taxi
Are there any complaints made in Brooklyn?	True	boolean	[ "borough" ]	[ "category" ]	True	005_NYC
Do any complaints have 'Dog' as a descriptor?	True	boolean	[ "descriptor" ]	[ "category" ]	False	005_NYC
Were there any complaints raised in April?	True	boolean	[ "month_name" ]	[ "category" ]	True	005_NYC
Is the Mayor's office of special enforcement one of the agencies handling complaints?	True	boolean	[ "agency" ]	[ "category" ]	False	005_NYC
How many complaints have been made in Queens?	23110	number	[ "borough" ]	[ "category" ]	0	005_NYC
What's the total number of unique agencies handling complaints?	22	number	[ "agency" ]	[ "category" ]	7	005_NYC
How many complaints were raised at midnight?	14811	number	[ "hour" ]	[ "number[uint8]" ]	2	005_NYC
How many unique descriptors are present in the dataset?	1131	number	[ "descriptor" ]	[ "category" ]	16	005_NYC
Which borough has the most complaints?	BROOKLYN	category	[ "borough" ]	[ "category" ]	QUEENS	005_NYC
Which month sees the highest number of complaints?	July	category	[ "month_name" ]	[ "category" ]	January	005_NYC
Which weekday has the least complaints?	Sunday	category	[ "weekday_name" ]	[ "category" ]	Thursday	005_NYC
Which agency is least frequently handling complaints?	ACS	category	[ "agency" ]	[ "category" ]	DOHMH	005_NYC
List the top 5 most frequent complaint types.	['Noise - Residential', 'HEAT/HOT WATER', 'Illegal Parking', 'Blocked Driveway', 'Street Condition']	list[category]	[ "complaint_type" ]	[ "category" ]	[HEAT/HOT WATER, Building/Use, Noise - Residential, General Construction/Plumbing, Air Quality]	005_NYC
Which 4 agencies handle the most complaints?	['NYPD', 'HPD', 'DOT', 'DSNY']	list[category]	[ "agency" ]	[ "category" ]	[NYPD, HPD, DOB, DSNY]	005_NYC
Name the 3 least frequent descriptors for complaints.	['Booting Company', 'Ready NY - Businesses', 'Animal']	list[category]	[ "descriptor" ]	[ "category" ]	[Structure - Outdoors, Air: Odor/Fumes, Restaurant (AD2), 12 Dead Animals]	005_NYC

Is the person with the highest net worth self-made?

True

boolean

[ "finalWorth", "selfMade" ]

[ "number[uint32]", "boolean" ]

False

001_Forbes

Does the youngest billionaire identify as male?

True

boolean

[ "age", "gender" ]

[ "number[UInt8]", "category" ]

True

001_Forbes

Is the city with the most billionaires in the United States?

True

boolean

[ "city", "country" ]

[ "category", "category" ]

True

001_Forbes

Is there a non-self-made billionaire in the top 5 ranks?

True

boolean

[ "rank", "selfMade" ]

[ "number[uint16]", "boolean" ]

False

001_Forbes

Does the oldest billionaire have a philanthropy score of 5?

False

boolean

[ "age", "philanthropyScore" ]

[ "number[UInt8]", "number[UInt8]" ]

False

001_Forbes

What is the age of the youngest billionaire?

19.0

number

[ "age" ]

[ "number[UInt8]" ]

32.0

001_Forbes

How many billionaires are there from the 'Technology' category?

343

number

[ "category" ]

0

001_Forbes

What's the total worth of billionaires in the 'Automotive' category?

583600

number

[ "category", "finalWorth" ]

[ "category", "number[uint32]" ]

0

001_Forbes

How many billionaires have a philanthropy score above 3?

25

number

[ "philanthropyScore" ]

[ "number[UInt8]" ]

0

001_Forbes

What's the rank of the wealthiest non-self-made billionaire?

3

number

[ "selfMade", "rank" ]

[ "boolean", "number[uint16]" ]

288

001_Forbes

Which category does the richest billionaire belong to?

Automotive

category

[ "finalWorth", "category" ]

[ "number[uint32]", "category" ]

Food & Beverage

001_Forbes

What's the country of origin of the oldest billionaire?

United States

category

[ "age", "country" ]

[ "number[UInt8]", "category" ]

United Kingdom

001_Forbes

What's the gender of the billionaire with the highest philanthropy score?

M

category

[ "philanthropyScore", "gender" ]

[ "number[UInt8]", "category" ]

M

001_Forbes

What's the source of wealth for the youngest billionaire?

drugstores

category

[ "age", "source" ]

[ "number[UInt8]", "category" ]

fintech

001_Forbes

What is the title of the billionaire with the lowest rank?

null

category

[ "rank", "title" ]

[ "number[uint16]", "category" ]

null

001_Forbes

List the top 3 countries with the most billionaires.

['United States', 'China', 'India']

list[category]

[ "country" ]

[ "category" ]

['United States', 'China', 'Brazil']

001_Forbes

List the top 5 sources of wealth for billionaires.

['real estate', 'investments', 'pharmaceuticals', 'diversified', 'software']

list[category]

[ "source" ]

[ "category" ]

['diversified', 'media, automotive', 'Semiconductor materials', 'WeWork', 'beverages']

001_Forbes

List the top 4 cities where the youngest billionaires live.

[nan, 'Los Angeles', 'Jiaozuo', 'Oslo']

list[category]

[ "age", "city" ]

[ "number[UInt8]", "category" ]

['San Francisco', 'New York', 'Wuhan', 'Bangalore']

001_Forbes

List the bottom 3 categories with the fewest billionaires.

['Logistics', 'Sports', 'Gambling & Casinos']

list[category]

[ "category" ]

['Service', 'Fashion & Retail', 'Manufacturing']

001_Forbes

List the bottom 2 countries with the least number of billionaires.

['Colombia', 'Andorra']

list[category]

[ "country" ]

[ "category" ]

['Canada', 'Egypt']

001_Forbes

List the top 5 ranks of billionaires who are not self-made.

[3, 10, 14, 16, 18]

list[number]

[ "selfMade", "rank" ]

[ "boolean", "number[uint16]" ]

[288, 296, 509, 523, 601]

001_Forbes

List the bottom 3 ages of billionaires who have a philanthropy score of 5.

[48.0, 83.0, 83.0]

list[number]

[ "philanthropyScore", "age" ]

[ "number[UInt8]", "number[UInt8]" ]

[]

001_Forbes

List the top 6 final worth values of billionaires in the 'Technology' category.

[171000, 129000, 111000, 107000, 106000, 91400]

list[number]

[ "category", "finalWorth" ]

[ "category", "number[uint32]" ]

[]

001_Forbes

List the bottom 4 ranks of female billionaires.

[14, 18, 21, 30]

list[number]

[ "gender", "rank" ]

[ "category", "number[uint16]" ]

[]

001_Forbes

List the top 2 final worth values of billionaires in the 'Automotive' category.

[219000, 44800]

list[number]

[ "category", "finalWorth" ]

[ "category", "number[uint32]" ]

[]

001_Forbes

Did any children below the age of 18 survive?

True

boolean

[ "Age", "Survived" ]

[ "number[UInt8]", "boolean" ]

True

002_Titanic

Were there any passengers who paid a fare of more than $500?

True

boolean

[ "Fare" ]

[ "number[double]" ]

False

002_Titanic

Is every passenger's name unique?

True

boolean

[ "Name" ]

[ "text" ]

True

002_Titanic

Were there any female passengers in the 3rd class who survived?

True

boolean

[ "Sex", "Pclass", "Survived" ]

[ "category", "number[uint8]", "boolean" ]

True

002_Titanic

How many unique passenger classes are present in the dataset?

3

number

[ "Pclass" ]

[ "number[uint8]" ]

3

002_Titanic

What's the maximum age of the passengers?

80.0

number

[ "Age" ]

[ "number[UInt8]" ]

69.0

002_Titanic

How many passengers boarded without any siblings or spouses?

604

number

[ "Siblings_Spouses Aboard" ]

[ "number[uint8]" ]

12

002_Titanic

On average, how much fare did the passengers pay?

32.31

number

[ "Fare" ]

[ "number[double]" ]

23.096459999999997

002_Titanic

Which passenger class has the highest number of survivors?

1

category

[ "Pclass", "Survived" ]

[ "number[uint8]", "boolean" ]

3

002_Titanic

What's the most common gender among the survivors?

female

category

[ "Sex", "Survived" ]

[ "category", "boolean" ]

female

002_Titanic

Among those who survived, which fare range was the most common: (0-50, 50-100, 100-150, 150+)?

0-50

category

[ "Fare", "Survived" ]

[ "number[double]", "boolean" ]

0-50

002_Titanic

What's the most common age range among passengers: (0-18, 18-30, 30-50, 50+)?

18-30

category

[ "Age" ]

[ "number[UInt8]" ]

18-30

002_Titanic

Name the top 3 passenger classes by survival rate.

[1, 2, 3]

list[category]

[ "Pclass", "Survived" ]

[ "number[uint8]", "boolean" ]

[1, 3, 2]

002_Titanic

Could you list the bottom 3 fare ranges by number of survivors: (0-50, 50-100, 100-150, 150+)?

['50-100', '150+', '100-150']

list[category]

[ "Fare", "Survived" ]

[ "number[double]", "boolean" ]

[50-100, 150+, 100-150]

002_Titanic

What is the top 4 age ranges('30-50', '18-30', '0-18', '50+') with the highest number of survivors?

['30-50', '18-30', '0-18', '50+']

list[category]

[ "Age", "Survived" ]

[ "number[UInt8]", "boolean" ]

[30-50, 18-30, 0-18, 50+]

002_Titanic

What are the top 2 genders by average fare paid?

['female', 'male']

list[category]

[ "Sex", "Fare" ]

[ "category", "number[double]" ]

[female, male]

002_Titanic

What are the oldest 3 ages among the survivors?

[24.0, 22.0, 27.0]

list[number]

[ "Age", "Survived" ]

[ "number[UInt8]", "boolean" ]

[56.0, 47.0, 42.0]

002_Titanic

Which are the top 4 fares paid by survivors?

[13.0, 26.0, 7.75, 10.5]

list[number]

[ "Fare", "Survived" ]

[ "number[double]", "boolean" ]

[133.65, 39.0, 35.5, 30.5]

002_Titanic

Could you list the youngest 3 ages among the survivors?

[53.0, 55.0, 11.0]

list[number]

[ "Age", "Survived" ]

[ "number[UInt8]", "boolean" ]

[14.0, 24.0, 28.0]

002_Titanic

Which are the bottom 4 fares among those who didn't survive?

[90.0, 12.275, 9.35, 10.5167]

list[number]

[ "Fare", "Survived" ]

[ "number[double]", "boolean" ]

[13.0, 7.75, 11.5, 10.1708]

002_Titanic

Is the average age of the respondents above 30?

True

boolean

[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "a", "g", "e", "?", " ", "👶", "🏻", "👵", "🏻", "'", "]" ]

[ "number[uint8]" ]

True

003_Love

Are there more single individuals than married ones in the dataset?

True

boolean

[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "c", "i", "v", "i", "l", " ", "s", "t", "a", "t", "u", "s", "?", " ", "💍", "'", "]" ]

[ "category" ]

False

003_Love

Do the majority of respondents have a height greater than 170 cm?

True

boolean

[ "[", "W", "h", "a", "t", "'", "s", " ", "y", "o", "u", "r", " ", "h", "e", "i", "g", "h", "t", "?", " ", "i", "n", " ", "c", "m", " ", "📏", "]" ]

[ "number[uint8]" ]

True

003_Love

Is the most frequent hair color black?

False

boolean

[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "h", "a", "i", "r", " ", "c", "o", "l", "o", "r", "?", " ", "👩", "🦰", "👱", "🏽", "'", "]" ]

[ "category" ]

False

003_Love

How many unique nationalities are present in the dataset?

13

number

[ "[", "W", "h", "a", "t", "'", "s", " ", "y", "o", "u", "r", " ", "n", "a", "t", "i", "o", "n", "a", "l", "i", "t", "y", "?", "\"", "]", "\"" ]

[ "category" ]

1

003_Love

What is the average gross annual salary?

56332.81720430108

number

[ "[", "'", "G", "r", "o", "s", "s", " ", "a", "n", "n", "u", "a", "l", " ", "s", "a", "l", "a", "r", "y", " ", "(", "i", "n", " ", "e", "u", "r", "o", "s", ")", " ", "💸", "'", "]" ]

[ "number[UInt32]" ]

62710.0

003_Love

How many respondents wear glasses all the time?

0

number

[ "[", "'", "H", "o", "w", " ", "o", "f", "t", "e", "n", " ", "d", "o", " ", "y", "o", "u", " ", "w", "e", "a", "r", " ", "g", "l", "a", "s", "s", "e", "s", "?", " ", "👓", "'", "]" ]

[ "category" ]

0

003_Love

What's the median age of the respondents?

33.0

number

[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "a", "g", "e", "?", " ", "👶", "🏻", "👵", "🏻", "'", "]" ]

[ "number[uint8]" ]

32.5

003_Love

What is the most common level of studies achieved?

Master

category

[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "t", "h", "e", " ", "m", "a", "x", "i", "m", "u", "m", " ", "l", "e", "v", "e", "l", " ", "o", "f", " ", "s", "t", "u", "d", "i", "e", "s", " ", "y", "o", "u", " ", "h", "a", "v", "e", " ", "a", "c", "h", "i", "e", "v", "e", "d", "?", " ", "🎓", "'", "]" ]

[ "category" ]

Master

003_Love

Which body complexity has the least number of respondents?

Very thin

category

[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "b", "o", "d", "y", " ", "c", "o", "m", "p", "l", "e", "x", "i", "t", "y", "?", " ", "🏋", "️", "'", "]" ]

[ "category" ]

Obese

003_Love

What's the most frequent eye color?

Brown

category

[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "e", "y", "e", " ", "c", "o", "l", "o", "r", "?", " ", "👁", "️", "'", "]" ]

[ "category" ]

Brown

003_Love

Which sexual orientation has the highest representation?

Heterosexual

category

[ "[", "W", "h", "a", "t", "'", "s", " ", "y", "o", "u", "r", " ", "s", "e", "x", "u", "a", "l", " ", "o", "r", "i", "e", "n", "t", "a", "t", "i", "o", "n", "?", "\"", "]", "\"" ]

[ "category" ]

Heterosexual

003_Love

List the top 3 most common areas of knowledge.

['[Computer Science]', '[Business]', '[Enginering & Architecture]']

list[category]

[ "[", "'", "W", "h", "a", "t", " ", "a", "r", "e", "a", " ", "o", "f", " ", "k", "n", "o", "w", "l", "e", "d", "g", "e", " ", "i", "s", " ", "c", "l", "o", "s", "e", "r", " ", "t", "o", " ", "y", "o", "u", "?", "'", "]" ]

[ "list[category]" ]

['[Computer Science]', '[Business]', '[Enginering & Architecture]']

003_Love

List the bottom 3 hair lengths in terms of frequency.

['Medium', 'Long', 'Bald']

list[category]

[ "[", "'", "H", "o", "w", " ", "l", "o", "n", "g", " ", "i", "s", " ", "y", "o", "u", "r", " ", "h", "a", "i", "r", "?", " ", "💇", "🏻", "♀", "️", "💇", "🏽", "♂", "️", "'", "]" ]

[ "category" ]

['Short', 'Medium', 'Long']

003_Love

Name the top 5 civil statuses represented in the dataset.

['Single', 'Married', 'In a Relationship', 'In a Relationship Cohabiting', 'Divorced']

list[category]

[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "c", "i", "v", "i", "l", " ", "s", "t", "a", "t", "u", "s", "?", " ", "💍", "'", "]" ]

[ "category" ]

['Married', 'In a Relationship', 'In a Relationship Cohabiting', 'Single', 'Divorced']

003_Love

What are the 4 least common hair colors?

['Red', 'Other', 'White', 'Blue']

list[category]

[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "h", "a", "i", "r", " ", "c", "o", "l", "o", "r", "?", " ", "👩", "🦰", "👱", "🏽", "'", "]" ]

[ "category" ]

['Brown', 'Black']

003_Love

What are the top 4 maximum gross annual salaries?

[500000.0, 360000.0, 300000.0, 300000.0]

list[number]

[ "[", "'", "G", "r", "o", "s", "s", " ", "a", "n", "n", "u", "a", "l", " ", "s", "a", "l", "a", "r", "y", " ", "(", "i", "n", " ", "e", "u", "r", "o", "s", ")", " ", "💸", "'", "]" ]

[ "number[UInt32]" ]

[150000.0, 130000.0, 125000.0, 120000.0]

003_Love

Name the bottom 3 values for the happiness scale.

[2, 2, 2]

list[number]

[ "[", "'", "H", "a", "p", "p", "i", "n", "e", "s", "s", " ", "s", "c", "a", "l", "e", "'", "]" ]

[ "number[uint8]" ]

[7, 10, 6]

003_Love

What are the 5 highest ages present in the dataset?

[65, 62, 60, 60, 59]

list[number]

[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "a", "g", "e", "?", " ", "👶", "🏻", "👵", "🏻", "'", "]" ]

[ "number[uint8]" ]

[65, 60, 51, 50, 50]

003_Love

List the bottom 6 skin tone values based on frequency.

[2, 1, 6, 0, 7, 8]

list[number]

[ "[", "'", "W", "h", "a", "t", " ", "i", "s", " ", "y", "o", "u", "r", " ", "s", "k", "i", "n", " ", "t", "o", "n", "e", "?", "'", "]" ]

[ "number[uint8]" ]

[3, 1, 6, 2, 7, 0]

003_Love

Are there any trips with a total distance greater than 30 miles?

False

boolean

[ "trip_distance" ]

[ "number[double]" ]

False

004_Taxi

Were there any trips that cost more than $100 in total?

False

boolean

[ "total_amount" ]

[ "number[double]" ]

False

004_Taxi

Is there any trip with more than 6 passengers?

False

boolean

[ "passenger_count" ]

[ "number[uint8]" ]

False

004_Taxi

Did all the trips use a payment type of either 1 or 2?

False

boolean

[ "payment_type" ]

[ "number[uint8]" ]

True

004_Taxi

What is the maximum fare amount charged for a trip?

75.25

number

[ "fare_amount" ]

[ "number[double]" ]

85.0

004_Taxi

How many unique pickup locations are in the dataset?

96

number

[ "PULocationID" ]

[ "number[uint16]" ]

193

004_Taxi

What is the average tip amount given by passengers?

2.74

number

[ "tip_amount" ]

[ "number[double]" ]

1.5

004_Taxi

How many trips took place in the airport area?

99807

number

[ "Airport_fee" ]

[ "number[UInt8]" ]

194

004_Taxi

Which payment type is the most common in the dataset?

1

category

[ "payment_type" ]

[ "number[uint8]" ]

1

004_Taxi

Which vendor has the most trips recorded?

2

category

[ "VendorID" ]

[ "number[uint8]" ]

2

004_Taxi

What is the most common drop-off location?

236

category

[ "DOLocationID" ]

[ "number[uint16]" ]

161

004_Taxi

On which date did the first recorded trip occur?

2023-01-31

category

[ "tpep_pickup_datetime" ]

[ "date[ns", "UTC]" ]

2019-01-01 00:46:40

004_Taxi

Which are the top 3 most frequent pickup locations?

[161, 237, 236]

list[category]

[ "PULocationID" ]

[ "number[uint16]" ]

[237, 236, 161]

004_Taxi

Name the 4 most common rate codes used.

[1, 2, 5, 4]

list[category]

[ "RatecodeID" ]

[ "number[uint8]" ]

[1, 2, 5, 3]

004_Taxi

list the 2 most frequent store and forward flags.

['N', 'Y']

list[category]

[ "store_and_fwd_flag" ]

[ "category" ]

['N', 'Y']

004_Taxi

Identify the top 4 payment types used by frequency

[1, 2, 4, 3]

list[category]

[ "payment_type" ]

[ "number[uint8]" ]

[1, 2, 3]

004_Taxi

Report the 4 highest toll amounts paid.

[0, 0, 0, 0]

list[number]

[ "tolls_amount" ]

[ "number[uint8]" ]

[0, 0, 0, 0]

004_Taxi

list the top 3 longest trip distances

[19.83, 19.74, 19.68]

list[number]

[ "trip_distance" ]

[ "number[double]" ]

[8.32, 5.93, 2.8]

004_Taxi

Identify the 5 largest total amounts paid for trips.

[80.0, 80.0, 80.0, 80.0, 79.55]

list[number]

[ "total_amount" ]

[ "number[double]" ]

[45.8, 39.9, 33.2, 25.2, 24.87]

004_Taxi

Report the 6 highest fare amounts charged.

[75.25, 74.4, 73.0, 73.0, 73.0, 73.0]

list[number]

[ "fare_amount" ]

[ "number[double]" ]

[40.8, 28.9, 21.2, 17.0, 14.9, 13.5]

004_Taxi

Are there any complaints made in Brooklyn?

True

boolean

[ "borough" ]

[ "category" ]

True

005_NYC

Do any complaints have 'Dog' as a descriptor?

True

boolean

[ "descriptor" ]

[ "category" ]

False

005_NYC

Were there any complaints raised in April?

True

boolean

[ "month_name" ]

[ "category" ]

True

005_NYC

Is the Mayor's office of special enforcement one of the agencies handling complaints?

True

boolean

[ "agency" ]

[ "category" ]

False

005_NYC

How many complaints have been made in Queens?

23110

number

[ "borough" ]

[ "category" ]

0

005_NYC

What's the total number of unique agencies handling complaints?

22

number

[ "agency" ]

[ "category" ]

7

005_NYC

How many complaints were raised at midnight?

14811

number

[ "hour" ]

[ "number[uint8]" ]

2

005_NYC

How many unique descriptors are present in the dataset?

1131

number

[ "descriptor" ]

[ "category" ]

16

005_NYC

Which borough has the most complaints?

BROOKLYN

category

[ "borough" ]

[ "category" ]

QUEENS

005_NYC

Which month sees the highest number of complaints?

July

category

[ "month_name" ]

[ "category" ]

January

005_NYC

Which weekday has the least complaints?

Sunday

category

[ "weekday_name" ]

[ "category" ]

Thursday

005_NYC

Which agency is least frequently handling complaints?

ACS

category

[ "agency" ]

[ "category" ]

DOHMH

005_NYC

List the top 5 most frequent complaint types.

['Noise - Residential', 'HEAT/HOT WATER', 'Illegal Parking', 'Blocked Driveway', 'Street Condition']

list[category]

[ "complaint_type" ]

[ "category" ]

[HEAT/HOT WATER, Building/Use, Noise - Residential, General Construction/Plumbing, Air Quality]

005_NYC

Which 4 agencies handle the most complaints?

['NYPD', 'HPD', 'DOT', 'DSNY']

list[category]

[ "agency" ]

[ "category" ]

[NYPD, HPD, DOB, DSNY]

005_NYC

Name the 3 least frequent descriptors for complaints.

['Booting Company', 'Ready NY - Businesses', 'Animal']

list[category]

[ "descriptor" ]

[ "category" ]

[Structure - Outdoors, Air: Odor/Fumes, Restaurant (AD2), 12 Dead Animals]

005_NYC