task_id stringclasses 53
values | query stringclasses 53
values | answer stringlengths 1 139 | artifact_type stringclasses 6
values | artifact_scope stringclasses 4
values | query_cols listlengths 1 5 | artifact_reasoning_cols listlengths 0 8 | table dict | num_rows int64 10 1.13k | num_cols int64 5 20 | recovered_tables_transform_spec dict | base_data_num_tokens int64 1.94k 16.1k | base_data_token_bucket int64 2k 16k | perturbation_note stringclasses 257
values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 13 | bad-values | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 51 | 10 | {
"drop_rows": [
[
24
]
],
"overwrite_cells": [
[]
]
} | 4,032 | 4,000 | Introduced bad values in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 15 | outliers | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 70 | 20 | {
"drop_rows": [
[
31
]
],
"overwrite_cells": [
[]
]
} | 8,045 | 8,000 | Introduced large outliers in lpep_dropoff_datetime column for absurdly long trip durations |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 19 | bad-values | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 70 | 20 | {
"drop_rows": [
[
45
]
],
"overwrite_cells": [
[]
]
} | 8,045 | 8,000 | Introduced bad values in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 43 | inconsistent-commonsense-logic | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 141 | 20 | {
"drop_rows": [
[
65,
68,
105,
119
]
],
"overwrite_cells": [
[]
]
} | 15,962 | 16,000 | Introduced inconsistent logic in lpep_dropoff_datetime column and how it should be strictly after the lpep_pickup_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 8 | inconsistent-commonsense-logic | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 17 | 20 | {
"drop_rows": [
[
2
]
],
"overwrite_cells": [
[]
]
} | 2,008 | 2,000 | Introduced inconsistent logic in lpep_dropoff_datetime column and how it should be strictly after the lpep_pickup_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 11 | missingness | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 35 | 20 | {
"drop_rows": [
[
30
]
],
"overwrite_cells": [
[]
]
} | 4,019 | 4,000 | Introduced missingness in lpep_dropoff_datetime column so the LLM needs to remove the rows with missing values |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 103 | missingness | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 273 | 5 | {
"drop_rows": [
[
34,
60,
125,
128,
169,
174,
233,
240,
267
]
],
"overwrite_cells": [
[]
]
} | 16,003 | 16,000 | Introduced missingness in lpep_dropoff_datetime column so the LLM needs to remove the rows with missing values |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 8 | missingness | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 17 | 20 | {
"drop_rows": [
[
2
]
],
"overwrite_cells": [
[]
]
} | 2,008 | 2,000 | Introduced missingness in lpep_dropoff_datetime column so the LLM needs to remove the rows with missing values |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 14 | bad-values | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 67 | 5 | {
"drop_rows": [
[
50
]
],
"overwrite_cells": [
[]
]
} | 3,999 | 4,000 | Introduced bad values in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 11 | inconsistent-commonsense-logic | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 35 | 20 | {
"drop_rows": [
[
30
]
],
"overwrite_cells": [
[]
]
} | 4,019 | 4,000 | Introduced inconsistent logic in lpep_dropoff_datetime column and how it should be strictly after the lpep_pickup_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 103 | inconsistent-commonsense-logic | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 273 | 5 | {
"drop_rows": [
[
34,
60,
125,
128,
169,
174,
233,
240,
267
]
],
"overwrite_cells": [
[]
]
} | 16,003 | 16,000 | Introduced inconsistent logic in lpep_dropoff_datetime column and how it should be strictly after the lpep_pickup_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 10 | inconsistent-commonsense-logic | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 34 | 5 | {
"drop_rows": [
[
21
]
],
"overwrite_cells": [
[]
]
} | 2,015 | 2,000 | Introduced inconsistent logic in lpep_dropoff_datetime column and how it should be strictly after the lpep_pickup_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 7 | outliers | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 25 | 10 | {
"drop_rows": [
[
7
]
],
"overwrite_cells": [
[]
]
} | 1,965 | 2,000 | Introduced large outliers in lpep_dropoff_datetime column for absurdly long trip durations |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 6 | bad-values | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 25 | 10 | {
"drop_rows": [
[
8
]
],
"overwrite_cells": [
[]
]
} | 1,965 | 2,000 | Introduced bad values in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 84 | clean | clean | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 208 | 10 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 16,014 | 16,000 | |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 24 | inconsistent-commonsense-logic | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 103 | 10 | {
"drop_rows": [
[
22,
58
]
],
"overwrite_cells": [
[]
]
} | 8,003 | 8,000 | Introduced inconsistent logic in lpep_dropoff_datetime column and how it should be strictly after the lpep_pickup_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 15 | clean | clean | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 67 | 5 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 3,999 | 4,000 | |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 11 | inconsistent-commonsense-logic | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 51 | 10 | {
"drop_rows": [
[
27
]
],
"overwrite_cells": [
[]
]
} | 4,032 | 4,000 | Introduced inconsistent logic in lpep_dropoff_datetime column and how it should be strictly after the lpep_pickup_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 11 | clean | clean | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 34 | 5 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 2,015 | 2,000 | |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 9 | missingness | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 25 | 10 | {
"drop_rows": [
[
2
]
],
"overwrite_cells": [
[]
]
} | 1,965 | 2,000 | Introduced missingness in lpep_dropoff_datetime column so the LLM needs to remove the rows with missing values |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 47 | clean | clean | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 141 | 20 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 15,962 | 16,000 | |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 8 | bad-values | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 17 | 20 | {
"drop_rows": [
[
4
]
],
"overwrite_cells": [
[]
]
} | 2,008 | 2,000 | Introduced bad values in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 42 | outliers | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 136 | 5 | {
"drop_rows": [
[
50,
80,
87,
110
]
],
"overwrite_cells": [
[]
]
} | 8,015 | 8,000 | Introduced large outliers in lpep_dropoff_datetime column for absurdly long trip durations |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 8 | outliers | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 17 | 20 | {
"drop_rows": [
[
11
]
],
"overwrite_cells": [
[]
]
} | 2,008 | 2,000 | Introduced large outliers in lpep_dropoff_datetime column for absurdly long trip durations |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 14 | inconsistent-commonsense-logic | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 67 | 5 | {
"drop_rows": [
[
54
]
],
"overwrite_cells": [
[]
]
} | 3,999 | 4,000 | Introduced inconsistent logic in lpep_dropoff_datetime column and how it should be strictly after the lpep_pickup_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 15 | inconsistent-commonsense-logic | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 70 | 20 | {
"drop_rows": [
[
34
]
],
"overwrite_cells": [
[]
]
} | 8,045 | 8,000 | Introduced inconsistent logic in lpep_dropoff_datetime column and how it should be strictly after the lpep_pickup_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 10 | bad-values | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 34 | 5 | {
"drop_rows": [
[
27
]
],
"overwrite_cells": [
[]
]
} | 2,015 | 2,000 | Introduced bad values in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 42 | missingness | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 136 | 5 | {
"drop_rows": [
[
65,
68,
106,
125
]
],
"overwrite_cells": [
[]
]
} | 8,015 | 8,000 | Introduced missingness in lpep_dropoff_datetime column so the LLM needs to remove the rows with missing values |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 15 | missingness | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 70 | 20 | {
"drop_rows": [
[
34
]
],
"overwrite_cells": [
[]
]
} | 8,045 | 8,000 | Introduced missingness in lpep_dropoff_datetime column so the LLM needs to remove the rows with missing values |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 43 | missingness | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 141 | 20 | {
"drop_rows": [
[
65,
68,
105,
119
]
],
"overwrite_cells": [
[]
]
} | 15,962 | 16,000 | Introduced missingness in lpep_dropoff_datetime column so the LLM needs to remove the rows with missing values |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 11 | bad-values | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 35 | 20 | {
"drop_rows": [
[
27
]
],
"overwrite_cells": [
[]
]
} | 4,019 | 4,000 | Introduced bad values in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 88 | outliers | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 273 | 5 | {
"drop_rows": [
[
7,
43,
50,
65,
68,
159,
162,
188,
247
]
],
"overwrite_cells": [
[]
]
} | 16,003 | 16,000 | Introduced large outliers in lpep_dropoff_datetime column for absurdly long trip durations |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 11 | outliers | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 35 | 20 | {
"drop_rows": [
[
31
]
],
"overwrite_cells": [
[]
]
} | 4,019 | 4,000 | Introduced large outliers in lpep_dropoff_datetime column for absurdly long trip durations |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 88 | bad-values | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 273 | 5 | {
"drop_rows": [
[
19,
27,
43,
160,
164,
169,
184,
243,
267
]
],
"overwrite_cells": [
[]
]
} | 16,003 | 16,000 | Introduced bad values in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 76 | inconsistent-commonsense-logic | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 208 | 10 | {
"drop_rows": [
[
3,
35,
44,
59,
68,
151,
171,
180
]
],
"overwrite_cells": [
[]
]
} | 16,014 | 16,000 | Introduced inconsistent logic in lpep_dropoff_datetime column and how it should be strictly after the lpep_pickup_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 24 | bad-values | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 103 | 10 | {
"drop_rows": [
[
31,
83
]
],
"overwrite_cells": [
[]
]
} | 8,003 | 8,000 | Introduced bad values in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 24 | outliers | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 103 | 10 | {
"drop_rows": [
[
21,
22
]
],
"overwrite_cells": [
[]
]
} | 8,003 | 8,000 | Introduced large outliers in lpep_dropoff_datetime column for absurdly long trip durations |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 11 | missingness | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 51 | 10 | {
"drop_rows": [
[
27
]
],
"overwrite_cells": [
[]
]
} | 4,032 | 4,000 | Introduced missingness in lpep_dropoff_datetime column so the LLM needs to remove the rows with missing values |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 11 | inconsistent-formatting | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 34 | 5 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[
{
"col": "lpep_dropoff_datetime",
"new_value": "21-04-07 01:10:AM -- ",
"row": 30
}
]
]
} | 2,015 | 2,000 | Introduced formatting inconsistencies in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 9 | inconsistent-commonsense-logic | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 25 | 10 | {
"drop_rows": [
[
2
]
],
"overwrite_cells": [
[]
]
} | 1,965 | 2,000 | Introduced inconsistent logic in lpep_dropoff_datetime column and how it should be strictly after the lpep_pickup_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 6 | clean | clean | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 17 | 20 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 2,008 | 2,000 | |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 43 | outliers | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 141 | 20 | {
"drop_rows": [
[
8,
21,
85,
92
]
],
"overwrite_cells": [
[]
]
} | 15,962 | 16,000 | Introduced large outliers in lpep_dropoff_datetime column for absurdly long trip durations |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 14 | missingness | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 67 | 5 | {
"drop_rows": [
[
54
]
],
"overwrite_cells": [
[]
]
} | 3,999 | 4,000 | Introduced missingness in lpep_dropoff_datetime column so the LLM needs to remove the rows with missing values |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 7 | inconsistent-formatting | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 25 | 10 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[
{
"col": "lpep_dropoff_datetime",
"new_value": "21-10-07 09:18:AM -- ",
"row": 7
}
]
]
} | 1,965 | 2,000 | Introduced formatting inconsistencies in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 84 | inconsistent-formatting | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 208 | 10 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[
{
"col": "lpep_dropoff_datetime",
"new_value": "21-09-24 17:33:PM -- ",
"row": 3
},
{
"col": "lpep_dropoff_datetime",
"new_value": "21-01-14 10:56:AM -- ",
"row": 67
},
{
"co... | 16,014 | 16,000 | Introduced formatting inconsistencies in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 42 | inconsistent-commonsense-logic | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 136 | 5 | {
"drop_rows": [
[
65,
68,
106,
125
]
],
"overwrite_cells": [
[]
]
} | 8,015 | 8,000 | Introduced inconsistent logic in lpep_dropoff_datetime column and how it should be strictly after the lpep_pickup_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 26 | clean | clean | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 103 | 10 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 8,003 | 8,000 | |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 76 | bad-values | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 208 | 10 | {
"drop_rows": [
[
19,
31,
32,
65,
77,
78,
103,
185
]
],
"overwrite_cells": [
[]
]
} | 16,014 | 16,000 | Introduced bad values in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 12 | inconsistent-formatting | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 51 | 10 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[
{
"col": "lpep_dropoff_datetime",
"new_value": "21-10-07 09:18:AM -- ",
"row": 7
}
]
]
} | 4,032 | 4,000 | Introduced formatting inconsistencies in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 14 | outliers | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 67 | 5 | {
"drop_rows": [
[
54
]
],
"overwrite_cells": [
[]
]
} | 3,999 | 4,000 | Introduced large outliers in lpep_dropoff_datetime column for absurdly long trip durations |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 16 | inconsistent-formatting | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 70 | 20 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[
{
"col": "lpep_dropoff_datetime",
"new_value": "21-10-09 01:44:AM -- ",
"row": 45
}
]
]
} | 8,045 | 8,000 | Introduced formatting inconsistencies in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 12 | clean | clean | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 35 | 20 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 4,019 | 4,000 | |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 97 | clean | clean | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 273 | 5 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 16,003 | 16,000 | |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 12 | inconsistent-formatting | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 35 | 20 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[
{
"col": "lpep_dropoff_datetime",
"new_value": "21-08-24 09:02:AM -- ",
"row": 34
}
]
]
} | 4,019 | 4,000 | Introduced formatting inconsistencies in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 46 | clean | clean | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 136 | 5 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 8,015 | 8,000 | |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 97 | inconsistent-formatting | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 273 | 5 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[
{
"col": "lpep_dropoff_datetime",
"new_value": "21-07-24 12:58:PM -- ",
"row": 68
},
{
"col": "lpep_dropoff_datetime",
"new_value": "21-06-10 16:37:PM -- ",
"row": 87
},
{
"c... | 16,003 | 16,000 | Introduced formatting inconsistencies in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 43 | bad-values | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 141 | 20 | {
"drop_rows": [
[
4,
22,
122,
128
]
],
"overwrite_cells": [
[]
]
} | 15,962 | 16,000 | Introduced bad values in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 16 | clean | clean | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 70 | 20 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 8,045 | 8,000 | |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 10 | outliers | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 34 | 5 | {
"drop_rows": [
[
31
]
],
"overwrite_cells": [
[]
]
} | 2,015 | 2,000 | Introduced large outliers in lpep_dropoff_datetime column for absurdly long trip durations |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 41 | bad-values | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 136 | 5 | {
"drop_rows": [
[
4,
14,
83,
87
]
],
"overwrite_cells": [
[]
]
} | 8,015 | 8,000 | Introduced bad values in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 12 | clean | clean | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 51 | 10 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 4,032 | 4,000 | |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 26 | inconsistent-formatting | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 103 | 10 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[
{
"col": "lpep_dropoff_datetime",
"new_value": "21-12-28 20:47:PM -- ",
"row": 85
},
{
"col": "lpep_dropoff_datetime",
"new_value": "21-11-20 21:11:PM -- ",
"row": 99
}
]
]
} | 8,003 | 8,000 | Introduced formatting inconsistencies in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 10 | missingness | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 34 | 5 | {
"drop_rows": [
[
21
]
],
"overwrite_cells": [
[]
]
} | 2,015 | 2,000 | Introduced missingness in lpep_dropoff_datetime column so the LLM needs to remove the rows with missing values |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 7 | clean | clean | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 25 | 10 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 1,965 | 2,000 | |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 46 | inconsistent-formatting | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount"
],
"rows": [
[
"239022",
"04/10/2021 11:11:55 AM",
"04/10/2021 11:18:14 AM",
"1.1",
"6.5"
],
[
"926728",
"11/27/2021 01:13:13 PM",
... | 136 | 5 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[
{
"col": "lpep_dropoff_datetime",
"new_value": "21-10-15 13:05:PM -- ",
"row": 27
},
{
"col": "lpep_dropoff_datetime",
"new_value": "21-12-27 12:52:PM -- ",
"row": 58
},
{
"c... | 8,015 | 8,000 | Introduced formatting inconsistencies in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 47 | inconsistent-formatting | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 141 | 20 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[
{
"col": "lpep_dropoff_datetime",
"new_value": "21-07-30 20:36:PM -- ",
"row": 22
},
{
"col": "lpep_dropoff_datetime",
"new_value": "21-12-17 16:53:PM -- ",
"row": 56
},
{
"c... | 15,962 | 16,000 | Introduced formatting inconsistencies in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 6 | inconsistent-formatting | single-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime"
] | {
"headers": [
"RideID",
"congestion_surcharge",
"DOLocationID",
"extra",
"start_month",
"tolls_amount",
"PULocationID",
"RatecodeID",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"payment_type",
"mta_tax",
"store_and_fwd_... | 17 | 20 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[
{
"col": "lpep_dropoff_datetime",
"new_value": "21-10-07 09:18:AM -- ",
"row": 7
}
]
]
} | 2,008 | 2,000 | Introduced formatting inconsistencies in lpep_dropoff_datetime column |
nyc-green-taxis | How many trips in the dataset occurred during the top 5 pickup hours (hours of the day) with the highest average trip duration?
Trip duration is defined as the difference between drop-off and pickup timestamps. | 76 | outliers | connected-multi-column | [
"lpep_pickup_datetime",
"lpep_dropoff_datetime"
] | [
"lpep_dropoff_datetime",
"lpep_pickup_datetime"
] | {
"headers": [
"RideID",
"payment_type",
"lpep_pickup_datetime",
"lpep_dropoff_datetime",
"trip_distance",
"fare_amount",
"extra",
"mta_tax",
"tolls_amount",
"store_and_fwd_flag"
],
"rows": [
[
"239022",
"2.0",
"04/10/2021 11:11:55 AM",
"04/10/20... | 208 | 10 | {
"drop_rows": [
[
11,
25,
46,
68,
95,
141,
144,
192
]
],
"overwrite_cells": [
[]
]
} | 16,014 | 16,000 | Introduced large outliers in lpep_dropoff_datetime column for absurdly long trip durations |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 51 | clean | clean | [
"Diagnosis_Date"
] | [] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Primary_Physician",
"Comorbidities",
"Height",
"Cancer_Type",
"Smoking_Status",
"Emirate",
"Gender",
"Outcome",
"Cancer_Stage",
"Treatment_Type",
... | 98 | 20 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 7,979 | 8,000 | |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 15 | inconsistent-commonsense-logic | connected-multi-column | [
"Diagnosis_Date"
] | [
"Diagnosis_Date",
"Treatment_Start_Date"
] | {
"headers": [
"Patient_ID",
"Primary_Physician",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Comorbidities",
"Height",
"Cancer_Type"
],
"rows": [
[
"PAT000001",
"Dr. VO41",
"2020-11-30",
"2020-10-11",
"69... | 38 | 10 | {
"drop_rows": [
[
15
]
],
"overwrite_cells": [
[
{
"col": "Patient_ID",
"new_value": "PAT000001",
"row": 0
},
{
"col": "Primary_Physician",
"new_value": "Dr. VO41",
"row": 0
},
{
"col": "Diagnosis_Date",
... | 2,001 | 2,000 | Introduced an inconsistency in the Diagnosis_Date column where it is after the Treatment_Start_Date. Should drop this record. |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 109 | inconsistent-commonsense-logic | connected-multi-column | [
"Diagnosis_Date"
] | [
"Diagnosis_Date",
"Treatment_Start_Date"
] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality"
],
"rows": [
[
"PAT000001",
"2020-11-30",
"2020-12-04",
"69",
"Emirati"
],
[
"PAT000002",
"2015-10-10",
"2015-11-05",
"32",
"Emira... | 219 | 5 | {
"drop_rows": [
[
11,
26,
46,
58,
81,
88,
94,
102,
111,
115,
133,
196
]
],
"overwrite_cells": [
[]
]
} | 7,991 | 8,000 | Introduced an inconsistency in the Diagnosis_Date column where it is after the Treatment_Start_Date. Should drop this record. |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 37 | clean | clean | [
"Diagnosis_Date"
] | [] | {
"headers": [
"Patient_ID",
"Primary_Physician",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Comorbidities",
"Height",
"Cancer_Type"
],
"rows": [
[
"PAT000001",
"Dr. VO41",
"2020-11-30",
"2020-12-04",
"69... | 76 | 10 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 3,995 | 4,000 | |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 164 | inconsistent-formatting | naive-multi-column | [
"Diagnosis_Date"
] | [
"Diagnosis_Date",
"Treatment_Start_Date"
] | {
"headers": [
"Patient_ID",
"Primary_Physician",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Comorbidities",
"Height",
"Cancer_Type"
],
"rows": [
[
"PAT000001",
"Dr. VO41",
"2020-11-30",
"2020-12-04",
"69... | 300 | 10 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[
{
"col": "Treatment_Start_Date",
"new_value": null,
"row": 10
},
{
"col": "Treatment_Start_Date",
"new_value": null,
"row": 12
},
{
"col": "Treatment_Start_Date",
"ne... | 15,987 | 16,000 | Introduced formatting inconsistencies in Diagnosis_Date and Treatment_Start_Date columns |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 99 | inconsistent-commonsense-logic | connected-multi-column | [
"Diagnosis_Date"
] | [
"Diagnosis_Date",
"Treatment_Start_Date"
] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Primary_Physician",
"Comorbidities",
"Height",
"Cancer_Type",
"Smoking_Status",
"Emirate",
"Gender",
"Outcome",
"Cancer_Stage",
"Treatment_Type",
... | 197 | 20 | {
"drop_rows": [
[
15,
34,
35,
66,
90,
115,
124,
151,
153,
191
]
],
"overwrite_cells": [
[
{
"col": "Patient_ID",
"new_value": "PAT000012",
"row": 11
},
{
"col": "Diagnosis_Date",
"new... | 16,035 | 16,000 | Introduced an inconsistency in the Diagnosis_Date column where it is after the Treatment_Start_Date. Should drop this record. |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 62 | clean | clean | [
"Diagnosis_Date"
] | [] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality"
],
"rows": [
[
"PAT000001",
"2020-11-30",
"2020-12-04",
"69",
"Emirati"
],
[
"PAT000002",
"2015-10-10",
"2015-11-05",
"32",
"Emira... | 110 | 5 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 4,016 | 4,000 | |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 16 | clean | clean | [
"Diagnosis_Date"
] | [] | {
"headers": [
"Patient_ID",
"Primary_Physician",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Comorbidities",
"Height",
"Cancer_Type"
],
"rows": [
[
"PAT000001",
"Dr. VO41",
"2020-11-30",
"2020-12-04",
"69... | 38 | 10 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 2,001 | 2,000 | |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 95 | bad-values | naive-multi-column | [
"Diagnosis_Date"
] | [
"Diagnosis_Date",
"Treatment_Start_Date"
] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Primary_Physician",
"Comorbidities",
"Height",
"Cancer_Type",
"Smoking_Status",
"Emirate",
"Gender",
"Outcome",
"Cancer_Stage",
"Treatment_Type",
... | 197 | 20 | {
"drop_rows": [
[
15,
34,
35,
48,
49,
66,
90,
115,
124,
151,
153,
169,
189,
190
]
],
"overwrite_cells": [
[
{
"col": "Patient_ID",
"new_value": "PAT000012",
"row": 11
},
{
... | 16,035 | 16,000 | Introduced bad values in Diagnosis_Date and Treatment_Start_Date columns (no month). Need to be dropped. |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 25 | inconsistent-formatting | naive-multi-column | [
"Diagnosis_Date"
] | [
"Diagnosis_Date",
"Treatment_Start_Date"
] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality"
],
"rows": [
[
"PAT000001",
"2020-11-30",
"2020-12-04",
"69",
"Emirati"
],
[
"PAT000002",
"2015-10-10",
"2015-11-05",
"32",
"Emira... | 55 | 5 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[
{
"col": "Treatment_Start_Date",
"new_value": null,
"row": 2
},
{
"col": "Treatment_Start_Date",
"new_value": null,
"row": 9
},
{
"col": "Treatment_Start_Date",
"new_... | 2,015 | 2,000 | Introduced formatting inconsistencies in Diagnosis_Date and Treatment_Start_Date columns |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 105 | missingness | naive-multi-column | [
"Diagnosis_Date"
] | [
"Age",
"Nationality",
"Treatment_Start_Date",
"Diagnosis_Date"
] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Primary_Physician",
"Comorbidities",
"Height",
"Cancer_Type",
"Smoking_Status",
"Emirate",
"Gender",
"Outcome",
"Cancer_Stage",
"Treatment_Type",
... | 197 | 20 | {
"drop_rows": [
[
15,
99,
109,
163
]
],
"overwrite_cells": [
[
{
"col": "Nationality",
"new_value": null,
"row": 11
},
{
"col": "Patient_ID",
"new_value": "PAT000014",
"row": 13
},
{
"col": "... | 16,035 | 16,000 | Introduced missingness in, Age, Nationality and Treatment_Start_Date columns. |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 46 | inconsistent-commonsense-logic | connected-multi-column | [
"Diagnosis_Date"
] | [
"Diagnosis_Date",
"Treatment_Start_Date"
] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Primary_Physician",
"Comorbidities",
"Height",
"Cancer_Type",
"Smoking_Status",
"Emirate",
"Gender",
"Outcome",
"Cancer_Stage",
"Treatment_Type",
... | 98 | 20 | {
"drop_rows": [
[
36,
53,
83,
89,
93
]
],
"overwrite_cells": [
[
{
"col": "Patient_ID",
"new_value": "PAT000029",
"row": 28
},
{
"col": "Diagnosis_Date",
"new_value": "2017-07-14",
"row": 28
},
... | 7,979 | 8,000 | Introduced an inconsistency in the Diagnosis_Date column where it is after the Treatment_Start_Date. Should drop this record. |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 34 | inconsistent-commonsense-logic | connected-multi-column | [
"Diagnosis_Date"
] | [
"Diagnosis_Date",
"Treatment_Start_Date"
] | {
"headers": [
"Patient_ID",
"Primary_Physician",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Comorbidities",
"Height",
"Cancer_Type"
],
"rows": [
[
"PAT000001",
"Dr. VO41",
"2020-11-30",
"2020-12-04",
"69... | 76 | 10 | {
"drop_rows": [
[
15,
36,
51
]
],
"overwrite_cells": [
[
{
"col": "Patient_ID",
"new_value": "PAT000012",
"row": 11
},
{
"col": "Primary_Physician",
"new_value": "Dr. NS1",
"row": 11
},
{
"col": "D... | 3,995 | 4,000 | Introduced an inconsistency in the Diagnosis_Date column where it is after the Treatment_Start_Date. Should drop this record. |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 60 | missingness | naive-multi-column | [
"Diagnosis_Date"
] | [
"Age",
"Nationality",
"Treatment_Start_Date",
"Diagnosis_Date"
] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality"
],
"rows": [
[
"PAT000001",
"2020-11-30",
"2020-12-04",
"69",
""
],
[
"PAT000002",
"2015-10-10",
"2015-11-05",
"32",
"Emirati"
... | 110 | 5 | {
"drop_rows": [
[
26,
43
]
],
"overwrite_cells": [
[
{
"col": "Nationality",
"new_value": null,
"row": 0
},
{
"col": "Treatment_Start_Date",
"new_value": null,
"row": 82
},
{
"col": "Treatment_Start_Date... | 4,016 | 4,000 | Introduced missingness in, Age, Nationality and Treatment_Start_Date columns. |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 109 | clean | clean | [
"Diagnosis_Date"
] | [] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Primary_Physician",
"Comorbidities",
"Height",
"Cancer_Type",
"Smoking_Status",
"Emirate",
"Gender",
"Outcome",
"Cancer_Stage",
"Treatment_Type",
... | 197 | 20 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 16,035 | 16,000 | |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 141 | bad-values | naive-multi-column | [
"Diagnosis_Date"
] | [
"Diagnosis_Date",
"Treatment_Start_Date"
] | {
"headers": [
"Patient_ID",
"Primary_Physician",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Comorbidities",
"Height",
"Cancer_Type"
],
"rows": [
[
"PAT000001",
"Dr. VO41",
"2020-11-30",
"2020-12-04",
"69... | 300 | 10 | {
"drop_rows": [
[
34,
35,
49,
53,
65,
66,
76,
105,
106,
107,
125,
161,
162,
189,
190,
207,
208,
243,
250,
252,
273,
282,
297
]
],
"overwrite_cells": [
[
{
... | 15,987 | 16,000 | Introduced bad values in Diagnosis_Date and Treatment_Start_Date columns (no month). Need to be dropped. |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 9 | clean | clean | [
"Diagnosis_Date"
] | [] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Primary_Physician",
"Comorbidities",
"Height",
"Cancer_Type",
"Smoking_Status",
"Emirate",
"Gender",
"Outcome",
"Cancer_Stage",
"Treatment_Type",
... | 24 | 20 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 1,991 | 2,000 | |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 24 | missingness | naive-multi-column | [
"Diagnosis_Date"
] | [
"Age",
"Nationality",
"Treatment_Start_Date",
"Diagnosis_Date"
] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality"
],
"rows": [
[
"PAT000001",
"2020-11-30",
"2020-12-04",
"69",
"Emirati"
],
[
"PAT000002",
"2015-10-10",
"2015-11-05",
"32",
"Emira... | 55 | 5 | {
"drop_rows": [
[
4
]
],
"overwrite_cells": [
[
{
"col": "Treatment_Start_Date",
"new_value": null,
"row": 12
},
{
"col": "Nationality",
"new_value": null,
"row": 21
},
{
"col": "Age",
"new_value": nul... | 2,015 | 2,000 | Introduced missingness in, Age, Nationality and Treatment_Start_Date columns. |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 104 | bad-values | naive-multi-column | [
"Diagnosis_Date"
] | [
"Diagnosis_Date",
"Treatment_Start_Date"
] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality"
],
"rows": [
[
"PAT000001",
"2020-11-30",
"2020-12-04",
"69",
"Emirati"
],
[
"PAT000002",
"2015-10-10",
"2015-11-05",
"32",
"Emira... | 219 | 5 | {
"drop_rows": [
[
11,
26,
46,
58,
71,
81,
88,
94,
102,
111,
115,
129,
133,
135,
154,
174,
196
]
],
"overwrite_cells": [
[]
]
} | 7,991 | 8,000 | Introduced bad values in Diagnosis_Date and Treatment_Start_Date columns (no month). Need to be dropped. |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 148 | inconsistent-commonsense-logic | connected-multi-column | [
"Diagnosis_Date"
] | [
"Diagnosis_Date",
"Treatment_Start_Date"
] | {
"headers": [
"Patient_ID",
"Primary_Physician",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Comorbidities",
"Height",
"Cancer_Type"
],
"rows": [
[
"PAT000001",
"Dr. VO41",
"2020-11-30",
"2020-12-04",
"69... | 300 | 10 | {
"drop_rows": [
[
36,
50,
53,
65,
66,
99,
108,
125,
163,
189,
190,
207,
243,
251,
273,
298
]
],
"overwrite_cells": [
[
{
"col": "Patient_ID",
"new_value": "PAT000036",
"row": ... | 15,987 | 16,000 | Introduced an inconsistency in the Diagnosis_Date column where it is after the Treatment_Start_Date. Should drop this record. |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 74 | inconsistent-commonsense-logic | connected-multi-column | [
"Diagnosis_Date"
] | [
"Diagnosis_Date",
"Treatment_Start_Date"
] | {
"headers": [
"Patient_ID",
"Primary_Physician",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Comorbidities",
"Height",
"Cancer_Type"
],
"rows": [
[
"PAT000001",
"Dr. VO41",
"2020-11-30",
"2020-10-22",
"69... | 151 | 10 | {
"drop_rows": [
[
15,
36,
49,
50,
64,
66,
76,
109
]
],
"overwrite_cells": [
[
{
"col": "Patient_ID",
"new_value": "PAT000001",
"row": 0
},
{
"col": "Primary_Physician",
"new_value": "Dr. VO41",
... | 7,996 | 8,000 | Introduced an inconsistency in the Diagnosis_Date column where it is after the Treatment_Start_Date. Should drop this record. |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 157 | missingness | naive-multi-column | [
"Diagnosis_Date"
] | [
"Age",
"Nationality",
"Treatment_Start_Date",
"Diagnosis_Date"
] | {
"headers": [
"Patient_ID",
"Primary_Physician",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Comorbidities",
"Height",
"Cancer_Type"
],
"rows": [
[
"PAT000001",
"Dr. VO41",
"2020-11-30",
"2020-12-04",
"69... | 300 | 10 | {
"drop_rows": [
[
109,
115,
153,
191,
207,
271,
272
]
],
"overwrite_cells": [
[
{
"col": "Treatment_Start_Date",
"new_value": null,
"row": 28
},
{
"col": "Nationality",
"new_value": null,
"row"... | 15,987 | 16,000 | Introduced missingness in, Age, Nationality and Treatment_Start_Date columns. |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 62 | inconsistent-formatting | naive-multi-column | [
"Diagnosis_Date"
] | [
"Diagnosis_Date",
"Treatment_Start_Date"
] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality"
],
"rows": [
[
"PAT000001",
"dt==November-30-2020",
"2020-12-04",
"69",
"Emirati"
],
[
"PAT000002",
"2015-10-10",
"2015-11-05",
"32",
... | 110 | 5 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[
{
"col": "Diagnosis_Date",
"new_value": "dt==November-30-2020",
"row": 0
},
{
"col": "Treatment_Start_Date",
"new_value": null,
"row": 5
},
{
"col": "Diagnosis_Date",
... | 4,016 | 4,000 | Introduced formatting inconsistencies in Diagnosis_Date and Treatment_Start_Date columns |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 19 | inconsistent-commonsense-logic | connected-multi-column | [
"Diagnosis_Date"
] | [
"Diagnosis_Date",
"Treatment_Start_Date"
] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Primary_Physician",
"Comorbidities",
"Height",
"Cancer_Type",
"Smoking_Status",
"Emirate",
"Gender",
"Outcome",
"Cancer_Stage",
"Treatment_Type",
... | 49 | 20 | {
"drop_rows": [
[
15,
47
]
],
"overwrite_cells": [
[
{
"col": "Patient_ID",
"new_value": "PAT000001",
"row": 0
},
{
"col": "Diagnosis_Date",
"new_value": "2020-11-30",
"row": 0
},
{
"col": "Treatment_Sta... | 3,991 | 4,000 | Introduced an inconsistency in the Diagnosis_Date column where it is after the Treatment_Start_Date. Should drop this record. |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 221 | inconsistent-commonsense-logic | connected-multi-column | [
"Diagnosis_Date"
] | [
"Diagnosis_Date",
"Treatment_Start_Date"
] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality"
],
"rows": [
[
"PAT000001",
"2020-11-30",
"2020-12-04",
"69",
"Emirati"
],
[
"PAT000002",
"2015-10-10",
"2015-11-05",
"32",
"Emira... | 439 | 5 | {
"drop_rows": [
[
20,
24,
35,
47,
53,
66,
70,
90,
119,
151,
185,
197,
210,
230,
260,
272,
283,
312,
317,
343,
346,
356,
375,
376
]
],
"overwrite_cells": [
[]... | 16,008 | 16,000 | Introduced an inconsistency in the Diagnosis_Date column where it is after the Treatment_Start_Date. Should drop this record. |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 164 | clean | clean | [
"Diagnosis_Date"
] | [] | {
"headers": [
"Patient_ID",
"Primary_Physician",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Comorbidities",
"Height",
"Cancer_Type"
],
"rows": [
[
"PAT000001",
"Dr. VO41",
"2020-11-30",
"2020-12-04",
"69... | 300 | 10 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 15,987 | 16,000 | |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 25 | clean | clean | [
"Diagnosis_Date"
] | [] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality"
],
"rows": [
[
"PAT000001",
"2020-11-30",
"2020-12-04",
"69",
"Emirati"
],
[
"PAT000002",
"2015-10-10",
"2015-11-05",
"32",
"Emira... | 55 | 5 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 2,015 | 2,000 | |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 82 | clean | clean | [
"Diagnosis_Date"
] | [] | {
"headers": [
"Patient_ID",
"Primary_Physician",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Comorbidities",
"Height",
"Cancer_Type"
],
"rows": [
[
"PAT000001",
"Dr. VO41",
"2020-11-30",
"2020-12-04",
"69... | 151 | 10 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 7,996 | 8,000 | |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 8 | inconsistent-commonsense-logic | connected-multi-column | [
"Diagnosis_Date"
] | [
"Diagnosis_Date",
"Treatment_Start_Date"
] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Primary_Physician",
"Comorbidities",
"Height",
"Cancer_Type",
"Smoking_Status",
"Emirate",
"Gender",
"Outcome",
"Cancer_Stage",
"Treatment_Type",
... | 24 | 20 | {
"drop_rows": [
[
22
]
],
"overwrite_cells": [
[
{
"col": "Patient_ID",
"new_value": "PAT000022",
"row": 21
},
{
"col": "Diagnosis_Date",
"new_value": "2020-11-03",
"row": 21
},
{
"col": "Treatment_Start_Date"... | 1,991 | 2,000 | Introduced an inconsistency in the Diagnosis_Date column where it is after the Treatment_Start_Date. Should drop this record. |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 109 | inconsistent-formatting | naive-multi-column | [
"Diagnosis_Date"
] | [
"Diagnosis_Date",
"Treatment_Start_Date"
] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Primary_Physician",
"Comorbidities",
"Height",
"Cancer_Type",
"Smoking_Status",
"Emirate",
"Gender",
"Outcome",
"Cancer_Stage",
"Treatment_Type",
... | 197 | 20 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[
{
"col": "Diagnosis_Date",
"new_value": "Date= 13/02/2018 -",
"row": 2
},
{
"col": "Diagnosis_Date",
"new_value": "dt==November-09-2015",
"row": 11
},
{
"col": "Diagnosis_Dat... | 16,035 | 16,000 | Introduced formatting inconsistencies in Diagnosis_Date and Treatment_Start_Date columns |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 21 | clean | clean | [
"Diagnosis_Date"
] | [] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality",
"Death_Date",
"Primary_Physician",
"Comorbidities",
"Height",
"Cancer_Type",
"Smoking_Status",
"Emirate",
"Gender",
"Outcome",
"Cancer_Stage",
"Treatment_Type",
... | 49 | 20 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 3,991 | 4,000 | |
uae-cancer-patient | How many patients were diagnosed in the second half of the year (months June - December)? | 245 | clean | clean | [
"Diagnosis_Date"
] | [] | {
"headers": [
"Patient_ID",
"Diagnosis_Date",
"Treatment_Start_Date",
"Age",
"Nationality"
],
"rows": [
[
"PAT000001",
"2020-11-30",
"2020-12-04",
"69",
"Emirati"
],
[
"PAT000002",
"2015-10-10",
"2015-11-05",
"32",
"Emira... | 439 | 5 | {
"drop_rows": [
[]
],
"overwrite_cells": [
[]
]
} | 16,008 | 16,000 |
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