Note
Go to the end to download the full example code. or to run this example in your browser via JupyterLite or Binder
AggJoiner on a credit fraud dataset#
Many problems involve tables whose entities have a one-to-many relationship.
To simplify aggregate-then-join operations for machine learning, we can include
the AggJoiner
in our pipeline.
In this example, we are tackling a fraudulent loan detection use case. Because fraud is rare, this dataset is extremely imbalanced, with a prevalence of around 1.4%.
The data consists of two distinct entities: e-commerce “baskets”, and “products”. Baskets can be tagged fraudulent (1) or not (0), and are essentially a list of products of variable size. Each basket is linked to at least one products, e.g. basket 1 can have product 1 and 2.

Our aim is to predict which baskets are fraudulent.
The products dataframe can be joined on the baskets dataframe using the basket_ID
column.
Each product has several attributes:
a category (marked by the column
"item"
),a model (
"model"
),a brand (
"make"
),a merchant code (
"goods_code"
),a price per unit (
"cash_price"
),a quantity selected in the basket (
"Nbr_of_prod_purchas"
)
from skrub import TableReport
from skrub.datasets import fetch_credit_fraud
bunch = fetch_credit_fraud()
products, baskets = bunch.products, bunch.baskets
TableReport(products)
basket_ID | item | cash_price | make | model | goods_code | Nbr_of_prod_purchas | |
---|---|---|---|---|---|---|---|
0 | 85517 | COMPUTERS | 889 | APPLE | 2020 APPLE MACBOOK AIR 13 3 RETINA DISPLAY M1 PROC | 239246776 | 1 |
1 | 51113 | COMPUTER PERIPHERALS ACCESSORIES | 409 | APPLE | APPLE WATCH SERIES 6 GPS 44MM SPACE GREY ALUMINIUM | 239001518 | 1 |
2 | 83008 | TELEVISIONS HOME CINEMA | 1399 | SAMSUNG | SAMSUNG QE75Q70A 2021 QLED HDR 4K ULTRA HD SMART T | 239842093 | 1 |
3 | 78712 | COMPUTERS | 689 | APPLE | 2020 APPLE IPAD AIR 10 9 A14 BIONIC PROCESSOR IOS | 239001422 | 1 |
4 | 78712 | COMPUTER PERIPHERALS ACCESSORIES | 119 | APPLE | APPLE PENCIL 2ND GENERATION 2018 MATTE WHITE | 237841896 | 1 |
163352 | 42613 | BEDROOM FURNITURE | 259 | SILENTNIGHT | SILENTNIGHT SLEEP GENIUS FULL HEIGHT HEADBOARD DOU | 236938439 | 1 |
163353 | 42613 | OUTDOOR FURNITURE | 949 | LG OUTDOOR | LG OUTDOOR BERGEN 2-SEAT GARDEN SIDE TABLE RECLINI | 239742814 | 1 |
163354 | 43567 | COMPUTERS | 1099 | APPLE | 2021 APPLE IPAD PRO 12 9 M1 PROCESSOR IOS WI-FI 25 | 240040978 | 1 |
163355 | 43567 | COMPUTERS | 2099 | APPLE | 2020 APPLE IMAC 27 ALL-IN-ONE INTEL CORE I7 8GB RA | 238923518 | 1 |
163356 | 68268 | TELEVISIONS HOME CINEMA | 799 | LG | LG OLED48A16LA 2021 OLED HDR 4K ULTRA HD SMART TV | 239866717 | 1 |
basket_ID
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 92,790 (56.8%)
- Mean ± Std
- 5.59e+04 ± 3.46e+04
- Median ± IQR
- 54,665 ± 61,275
- Min | Max
- 0 | 115,985
item
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 173 (0.1%)
Most frequent values
COMPUTERS
FULFILMENT CHARGE
COMPUTER PERIPHERALS ACCESSORIES
TELEVISIONS HOME CINEMA
WARRANTY
LIVING DINING FURNITURE
BEDROOM FURNITURE
SERVICE
TELEPHONES, FAX MACHINES & TWO-WAY RADIOS
COMPUTER PERIPHERALS & ACCESSORIES
['COMPUTERS', 'FULFILMENT CHARGE', 'COMPUTER PERIPHERALS ACCESSORIES', 'TELEVISIONS HOME CINEMA', 'WARRANTY', 'LIVING DINING FURNITURE', 'BEDROOM FURNITURE', 'SERVICE', 'TELEPHONES, FAX MACHINES & TWO-WAY RADIOS', 'COMPUTER PERIPHERALS & ACCESSORIES']
cash_price
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 1,594 (1.0%)
- Mean ± Std
- 701. ± 742.
- Median ± IQR
- 549 ± 1,029
- Min | Max
- 0 | 21,995
make
ObjectDType- Null values
- 1,273 (0.8%)
- Unique values
- 829 (0.5%)
Most frequent values
APPLE
RETAILER
LG
SAMSUNG
SONY
ANYDAY RETAILER
WEST ELM
SWOON
KETTLER
PANASONIC
['APPLE', 'RETAILER', 'LG', 'SAMSUNG', 'SONY', 'ANYDAY RETAILER', 'WEST ELM', 'SWOON', 'KETTLER', 'PANASONIC']
model
ObjectDType- Null values
- 1,273 (0.8%)
- Unique values
- 9,679 (5.9%)
Most frequent values
RETAILER
2020 APPLE MACBOOK AIR 13 3 RETINA DISPLAY M1 PROC
2020 APPLE MACBOOK PRO 13 TOUCH BAR M1 PROCESSOR 8
2021 APPLE MACBOOK PRO 14 M1 PRO PROCESSOR 16GB RA
APPLE PENCIL 2ND GENERATION 2018 MATTE WHITE
2020 APPLE IPAD AIR 10 9 A14 BIONIC PROCESSOR IOS
2021 APPLE IMAC 24 ALL-IN-ONE M1 PROCESSOR 8GB RAM
2021 APPLE IPAD PRO 11 M1 PROCESSOR IOS WI-FI 128G
2021 APPLE MACBOOK PRO 16 M1 PRO PROCESSOR 16GB RA
2021 APPLE IPAD PRO 12 9 M1 PROCESSOR IOS WI-FI 25
['RETAILER', '2020 APPLE MACBOOK AIR 13 3 RETINA DISPLAY M1 PROC', '2020 APPLE MACBOOK PRO 13 TOUCH BAR M1 PROCESSOR 8', '2021 APPLE MACBOOK PRO 14 M1 PRO PROCESSOR 16GB RA', 'APPLE PENCIL 2ND GENERATION 2018 MATTE WHITE', '2020 APPLE IPAD AIR 10 9 A14 BIONIC PROCESSOR IOS', '2021 APPLE IMAC 24 ALL-IN-ONE M1 PROCESSOR 8GB RAM', '2021 APPLE IPAD PRO 11 M1 PROCESSOR IOS WI-FI 128G', '2021 APPLE MACBOOK PRO 16 M1 PRO PROCESSOR 16GB RA', '2021 APPLE IPAD PRO 12 9 M1 PROCESSOR IOS WI-FI 25']
goods_code
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 14,880 (9.1%)
Most frequent values
FULFILMENT
239246776
239246779
237841896
239246778
239246782
240575990
236604736
240040984
240040978
['FULFILMENT', '239246776', '239246779', '237841896', '239246778', '239246782', '240575990', '236604736', '240040984', '240040978']
Nbr_of_prod_purchas
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 20 (< 0.1%)
- Mean ± Std
- 1.05 ± 0.427
- Median ± IQR
- 1 ± 0
- Min | Max
- 1 | 40
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
Column
|
Column name
|
dtype
|
Null values
|
Unique values
|
Mean
|
Std
|
Min
|
Median
|
Max
|
---|---|---|---|---|---|---|---|---|---|
0 | basket_ID | Int64DType | 0 (0.0%) | 92790 (56.8%) | 5.59e+04 | 3.46e+04 | 0 | 54,665 | 115,985 |
1 | item | ObjectDType | 0 (0.0%) | 173 (0.1%) | |||||
2 | cash_price | Int64DType | 0 (0.0%) | 1594 (1.0%) | 701. | 742. | 0 | 549 | 21,995 |
3 | make | ObjectDType | 1273 (0.8%) | 829 (0.5%) | |||||
4 | model | ObjectDType | 1273 (0.8%) | 9679 (5.9%) | |||||
5 | goods_code | ObjectDType | 0 (0.0%) | 14880 (9.1%) | |||||
6 | Nbr_of_prod_purchas | Int64DType | 0 (0.0%) | 20 (< 0.1%) | 1.05 | 0.427 | 1 | 1 | 40 |
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
basket_ID
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 92,790 (56.8%)
- Mean ± Std
- 5.59e+04 ± 3.46e+04
- Median ± IQR
- 54,665 ± 61,275
- Min | Max
- 0 | 115,985
item
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 173 (0.1%)
Most frequent values
COMPUTERS
FULFILMENT CHARGE
COMPUTER PERIPHERALS ACCESSORIES
TELEVISIONS HOME CINEMA
WARRANTY
LIVING DINING FURNITURE
BEDROOM FURNITURE
SERVICE
TELEPHONES, FAX MACHINES & TWO-WAY RADIOS
COMPUTER PERIPHERALS & ACCESSORIES
['COMPUTERS', 'FULFILMENT CHARGE', 'COMPUTER PERIPHERALS ACCESSORIES', 'TELEVISIONS HOME CINEMA', 'WARRANTY', 'LIVING DINING FURNITURE', 'BEDROOM FURNITURE', 'SERVICE', 'TELEPHONES, FAX MACHINES & TWO-WAY RADIOS', 'COMPUTER PERIPHERALS & ACCESSORIES']
cash_price
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 1,594 (1.0%)
- Mean ± Std
- 701. ± 742.
- Median ± IQR
- 549 ± 1,029
- Min | Max
- 0 | 21,995
make
ObjectDType- Null values
- 1,273 (0.8%)
- Unique values
- 829 (0.5%)
Most frequent values
APPLE
RETAILER
LG
SAMSUNG
SONY
ANYDAY RETAILER
WEST ELM
SWOON
KETTLER
PANASONIC
['APPLE', 'RETAILER', 'LG', 'SAMSUNG', 'SONY', 'ANYDAY RETAILER', 'WEST ELM', 'SWOON', 'KETTLER', 'PANASONIC']
model
ObjectDType- Null values
- 1,273 (0.8%)
- Unique values
- 9,679 (5.9%)
Most frequent values
RETAILER
2020 APPLE MACBOOK AIR 13 3 RETINA DISPLAY M1 PROC
2020 APPLE MACBOOK PRO 13 TOUCH BAR M1 PROCESSOR 8
2021 APPLE MACBOOK PRO 14 M1 PRO PROCESSOR 16GB RA
APPLE PENCIL 2ND GENERATION 2018 MATTE WHITE
2020 APPLE IPAD AIR 10 9 A14 BIONIC PROCESSOR IOS
2021 APPLE IMAC 24 ALL-IN-ONE M1 PROCESSOR 8GB RAM
2021 APPLE IPAD PRO 11 M1 PROCESSOR IOS WI-FI 128G
2021 APPLE MACBOOK PRO 16 M1 PRO PROCESSOR 16GB RA
2021 APPLE IPAD PRO 12 9 M1 PROCESSOR IOS WI-FI 25
['RETAILER', '2020 APPLE MACBOOK AIR 13 3 RETINA DISPLAY M1 PROC', '2020 APPLE MACBOOK PRO 13 TOUCH BAR M1 PROCESSOR 8', '2021 APPLE MACBOOK PRO 14 M1 PRO PROCESSOR 16GB RA', 'APPLE PENCIL 2ND GENERATION 2018 MATTE WHITE', '2020 APPLE IPAD AIR 10 9 A14 BIONIC PROCESSOR IOS', '2021 APPLE IMAC 24 ALL-IN-ONE M1 PROCESSOR 8GB RAM', '2021 APPLE IPAD PRO 11 M1 PROCESSOR IOS WI-FI 128G', '2021 APPLE MACBOOK PRO 16 M1 PRO PROCESSOR 16GB RA', '2021 APPLE IPAD PRO 12 9 M1 PROCESSOR IOS WI-FI 25']
goods_code
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 14,880 (9.1%)
Most frequent values
FULFILMENT
239246776
239246779
237841896
239246778
239246782
240575990
236604736
240040984
240040978
['FULFILMENT', '239246776', '239246779', '237841896', '239246778', '239246782', '240575990', '236604736', '240040984', '240040978']
Nbr_of_prod_purchas
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 20 (< 0.1%)
- Mean ± Std
- 1.05 ± 0.427
- Median ± IQR
- 1 ± 0
- Min | Max
- 1 | 40
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
Column 1 | Column 2 | Cramér's V | Pearson's Correlation |
---|---|---|---|
model | goods_code | 0.650 | |
item | make | 0.471 | |
cash_price | model | 0.403 | |
item | goods_code | 0.402 | |
item | model | 0.401 | |
item | cash_price | 0.324 | |
cash_price | goods_code | 0.316 | |
make | model | 0.300 | |
make | goods_code | 0.248 | |
cash_price | make | 0.238 | |
basket_ID | item | 0.167 | |
basket_ID | model | 0.154 | |
make | Nbr_of_prod_purchas | 0.144 | |
basket_ID | goods_code | 0.112 | |
item | Nbr_of_prod_purchas | 0.106 | |
basket_ID | make | 0.105 | |
basket_ID | cash_price | 0.0921 | 0.104 |
cash_price | Nbr_of_prod_purchas | 0.0666 | -0.0330 |
basket_ID | Nbr_of_prod_purchas | 0.0496 | -0.000404 |
goods_code | Nbr_of_prod_purchas | 0.0419 |
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ID | fraud_flag | |
---|---|---|
0 | 85517 | 0 |
1 | 51113 | 0 |
2 | 83008 | 0 |
3 | 78712 | 0 |
4 | 77846 | 0 |
92785 | 21243 | 0 |
92786 | 45891 | 0 |
92787 | 42613 | 0 |
92788 | 43567 | 0 |
92789 | 68268 | 0 |
ID
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 92,790 (100.0%)
- Mean ± Std
- 5.80e+04 ± 3.35e+04
- Median ± IQR
- 57,961 ± 58,085
- Min | Max
- 0 | 115,985
fraud_flag
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 2 (< 0.1%)
- Mean ± Std
- 0.0142 ± 0.118
- Median ± IQR
- 0 ± 0
- Min | Max
- 0 | 1
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
Column
|
Column name
|
dtype
|
Null values
|
Unique values
|
Mean
|
Std
|
Min
|
Median
|
Max
|
---|---|---|---|---|---|---|---|---|---|
0 | ID | Int64DType | 0 (0.0%) | 92790 (100.0%) | 5.80e+04 | 3.35e+04 | 0 | 57,961 | 115,985 |
1 | fraud_flag | Int64DType | 0 (0.0%) | 2 (< 0.1%) | 0.0142 | 0.118 | 0 | 0 | 1 |
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
ID
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 92,790 (100.0%)
- Mean ± Std
- 5.80e+04 ± 3.35e+04
- Median ± IQR
- 57,961 ± 58,085
- Min | Max
- 0 | 115,985
fraud_flag
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 2 (< 0.1%)
- Mean ± Std
- 0.0142 ± 0.118
- Median ± IQR
- 0 ± 0
- Min | Max
- 0 | 1
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
Column 1 | Column 2 | Cramér's V | Pearson's Correlation |
---|---|---|---|
ID | fraud_flag | 0.0884 | 0.0467 |
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Naive aggregation#
Let’s explore a naive solution first.
Note
Click here to skip this section and see the AggJoiner in action!
The first idea that comes to mind to merge these two tables is to aggregate the products attributes into lists, using their basket IDs.
products_grouped = products.groupby("basket_ID").agg(list)
TableReport(products_grouped)
basket_ID | item | cash_price | make | model | goods_code | Nbr_of_prod_purchas |
---|---|---|---|---|---|---|
0 | ['COMPUTERS', 'WARRANTY', 'FULFILMENT CHARGE'] | [1249, 35, 11] | ['APPLE', 'RETAILER', 'RETAILER'] | ['2021 APPLE IMAC 24 ALL-IN-ONE M1 PROCESSOR 8GB RAM', 'RETAILER', 'RETAILER'] | ['240040969', '236604727', 'FULFILMENT'] | [1, 1, 1] |
1 | ['OUTDOOR ACCESSORIES', 'OUTDOOR FURNITURE'] | [679, 369] | ['KETTLER', 'RETAILER'] | ['RETAILER', 'RETAILER'] | ['237874616', '238222170'] | [1, 1] |
2 | ['OUTDOOR FURNITURE', 'OUTDOOR FURNITURE'] | [1879, 110] | ['KETTLER', 'KETTLER'] | ['RETAILER', 'RETAILER'] | ['239482916', '235452317'] | [1, 1] |
4 | ['TELEPHONES, FAX MACHINES & TWO-WAY RADIOS', 'FULFILMENT CHARGE'] | [999, 0] | ['APPLE', 'RETAILER'] | ['APPLE IPHONE 12 PRO', 'RETAILER'] | ['239091969', 'FULFILMENT'] | [1, 1] |
5 | ['LIVING & DINING FURNITURE'] | [749] | ['RETAILER'] | ['RETAILER'] | ['238000174'] | [1] |
115981 | ['COMPUTERS'] | [1149] | ['APPLE'] | ['2021 APPLE IMAC 24 ALL-IN-ONE M1 PROCESSOR 8GB RAM'] | ['240040965'] | [1] |
115982 | ['COMPUTERS', 'FULFILMENT CHARGE'] | [1399, 7] | ['APPLE', 'RETAILER'] | ['2021 APPLE IPAD PRO 11 M1 PROCESSOR IOS WI-FI 1TB', 'RETAILER'] | ['240041001', 'FULFILMENT'] | [1, 1] |
115983 | ['COMPUTER PERIPHERALS ACCESSORIES'] | [439] | ['APPLE'] | ['APPLE WATCH SERIES 7 GPS CELLULAR 41MM BLUE ALUMIN'] | ['240376595'] | [1] |
115984 | ['COMPUTERS'] | [887] | ['APPLE'] | ['2020 APPLE MACBOOK AIR 13 3 RETINA DISPLAY M1 PROC'] | ['239246776'] | [1] |
115985 | ['COMPUTERS', 'FULFILMENT CHARGE'] | [569, 7] | ['APPLE', 'RETAILER'] | ['2022 APPLE IPAD AIR 10 9 M1 PROCESSOR IPADOS WI-FI', 'RETAILER'] | ['241017996', 'FULFILMENT'] | [1, 1] |
item
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 4,425 (4.8%)
Most frequent values
['COMPUTERS']
['COMPUTERS', 'FULFILMENT CHARGE']
['TELEVISIONS HOME CINEMA']
['COMPUTER PERIPHERALS ACCESSORIES']
['COMPUTERS', 'WARRANTY']
['LIVING DINING FURNITURE']
['TELEPHONES, FAX MACHINES & TWO-WAY RADIOS', 'FULFILMENT CHARGE']
['COMPUTER PERIPHERALS ACCESSORIES', 'FULFILMENT CHARGE']
['COMPUTERS', 'COMPUTER PERIPHERALS ACCESSORIES']
['COMPUTERS', 'WARRANTY', 'FULFILMENT CHARGE']
[['COMPUTERS'], ['COMPUTERS', 'FULFILMENT CHARGE'], ['TELEVISIONS HOME CINEMA'], ['COMPUTER PERIPHERALS ACCESSORIES'], ['COMPUTERS', 'WARRANTY'], ['LIVING DINING FURNITURE'], ['TELEPHONES, FAX MACHINES & TWO-WAY RADIOS', 'FULFILMENT CHARGE'], ['COMPUTER PERIPHERALS ACCESSORIES', 'FULFILMENT CHARGE'], ['COMPUTERS', 'COMPUTER PERIPHERALS ACCESSORIES'], ['COMPUTERS', 'WARRANTY', 'FULFILMENT CHARGE']]
cash_price
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 16,146 (17.4%)
Most frequent values
[949]
[889]
[369]
[399]
[1099]
[1187]
[899]
[999]
[1899]
[749]
[[949], [889], [369], [399], [1099], [1187], [899], [999], [1899], [749]]
make
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 3,862 (4.2%)
Most frequent values
['APPLE']
['APPLE', 'RETAILER']
['LG']
['APPLE', 'APPLE']
['SAMSUNG']
['LG', 'RETAILER']
['SONY']
['APPLE', 'APPLE', 'RETAILER']
['APPLE', 'RETAILER', 'RETAILER']
['RETAILER', 'RETAILER']
[['APPLE'], ['APPLE', 'RETAILER'], ['LG'], ['APPLE', 'APPLE'], ['SAMSUNG'], ['LG', 'RETAILER'], ['SONY'], ['APPLE', 'APPLE', 'RETAILER'], ['APPLE', 'RETAILER', 'RETAILER'], ['RETAILER', 'RETAILER']]
model
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 12,529 (13.5%)
Most frequent values
['2020 APPLE MACBOOK AIR 13 3 RETINA DISPLAY M1 PROC']
['2020 APPLE MACBOOK PRO 13 TOUCH BAR M1 PROCESSOR 8']
['2020 APPLE MACBOOK AIR 13 3 RETINA DISPLAY M1 PROC', 'RETAILER']
['2021 APPLE MACBOOK PRO 14 M1 PRO PROCESSOR 16GB RA']
['2020 APPLE IPAD AIR 10 9 A14 BIONIC PROCESSOR IOS']
['2020 APPLE MACBOOK PRO 13 TOUCH BAR M1 PROCESSOR 8', 'RETAILER']
['2020 APPLE MACBOOK AIR', 'RETAILER']
['LG OLED55C14LB 2021 OLED HDR 4K ULTRA HD SMART TV']
['2021 APPLE MACBOOK PRO 16 M1 PRO PROCESSOR 16GB RA']
['2021 APPLE IMAC 24 ALL-IN-ONE M1 PROCESSOR 8GB RAM']
[['2020 APPLE MACBOOK AIR 13 3 RETINA DISPLAY M1 PROC'], ['2020 APPLE MACBOOK PRO 13 TOUCH BAR M1 PROCESSOR 8'], ['2020 APPLE MACBOOK AIR 13 3 RETINA DISPLAY M1 PROC', 'RETAILER'], ['2021 APPLE MACBOOK PRO 14 M1 PRO PROCESSOR 16GB RA'], ['2020 APPLE IPAD AIR 10 9 A14 BIONIC PROCESSOR IOS'], ['2020 APPLE MACBOOK PRO 13 TOUCH BAR M1 PROCESSOR 8', 'RETAILER'], ['2020 APPLE MACBOOK AIR', 'RETAILER'], ['LG OLED55C14LB 2021 OLED HDR 4K ULTRA HD SMART TV'], ['2021 APPLE MACBOOK PRO 16 M1 PRO PROCESSOR 16GB RA'], ['2021 APPLE IMAC 24 ALL-IN-ONE M1 PROCESSOR 8GB RAM']]
goods_code
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 17,916 (19.3%)
Most frequent values
['239246776']
['239246779']
['239246778']
['239246776', 'FULFILMENT']
['239246782']
['240575990']
['239827061']
['239246779', 'FULFILMENT']
['240376619']
['240376608']
[['239246776'], ['239246779'], ['239246778'], ['239246776', 'FULFILMENT'], ['239246782'], ['240575990'], ['239827061'], ['239246779', 'FULFILMENT'], ['240376619'], ['240376608']]
Nbr_of_prod_purchas
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 812 (0.9%)
Most frequent values
[1]
[1, 1]
[1, 1, 1]
[1, 1, 1, 1]
[1, 1, 1, 1, 1]
[2]
[2, 1]
[1, 2]
[1, 1, 1, 1, 1, 1]
[1, 2, 1]
[[1], [1, 1], [1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1, 1], [2], [2, 1], [1, 2], [1, 1, 1, 1, 1, 1], [1, 2, 1]]
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
Column
|
Column name
|
dtype
|
Null values
|
Unique values
|
Mean
|
Std
|
Min
|
Median
|
Max
|
---|---|---|---|---|---|---|---|---|---|
0 | item | ObjectDType | 0 (0.0%) | 4425 (4.8%) | |||||
1 | cash_price | ObjectDType | 0 (0.0%) | 16146 (17.4%) | |||||
2 | make | ObjectDType | 0 (0.0%) | 3862 (4.2%) | |||||
3 | model | ObjectDType | 0 (0.0%) | 12529 (13.5%) | |||||
4 | goods_code | ObjectDType | 0 (0.0%) | 17916 (19.3%) | |||||
5 | Nbr_of_prod_purchas | ObjectDType | 0 (0.0%) | 812 (0.9%) |
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
item
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 4,425 (4.8%)
Most frequent values
['COMPUTERS']
['COMPUTERS', 'FULFILMENT CHARGE']
['TELEVISIONS HOME CINEMA']
['COMPUTER PERIPHERALS ACCESSORIES']
['COMPUTERS', 'WARRANTY']
['LIVING DINING FURNITURE']
['TELEPHONES, FAX MACHINES & TWO-WAY RADIOS', 'FULFILMENT CHARGE']
['COMPUTER PERIPHERALS ACCESSORIES', 'FULFILMENT CHARGE']
['COMPUTERS', 'COMPUTER PERIPHERALS ACCESSORIES']
['COMPUTERS', 'WARRANTY', 'FULFILMENT CHARGE']
[['COMPUTERS'], ['COMPUTERS', 'FULFILMENT CHARGE'], ['TELEVISIONS HOME CINEMA'], ['COMPUTER PERIPHERALS ACCESSORIES'], ['COMPUTERS', 'WARRANTY'], ['LIVING DINING FURNITURE'], ['TELEPHONES, FAX MACHINES & TWO-WAY RADIOS', 'FULFILMENT CHARGE'], ['COMPUTER PERIPHERALS ACCESSORIES', 'FULFILMENT CHARGE'], ['COMPUTERS', 'COMPUTER PERIPHERALS ACCESSORIES'], ['COMPUTERS', 'WARRANTY', 'FULFILMENT CHARGE']]
cash_price
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 16,146 (17.4%)
Most frequent values
[949]
[889]
[369]
[399]
[1099]
[1187]
[899]
[999]
[1899]
[749]
[[949], [889], [369], [399], [1099], [1187], [899], [999], [1899], [749]]
make
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 3,862 (4.2%)
Most frequent values
['APPLE']
['APPLE', 'RETAILER']
['LG']
['APPLE', 'APPLE']
['SAMSUNG']
['LG', 'RETAILER']
['SONY']
['APPLE', 'APPLE', 'RETAILER']
['APPLE', 'RETAILER', 'RETAILER']
['RETAILER', 'RETAILER']
[['APPLE'], ['APPLE', 'RETAILER'], ['LG'], ['APPLE', 'APPLE'], ['SAMSUNG'], ['LG', 'RETAILER'], ['SONY'], ['APPLE', 'APPLE', 'RETAILER'], ['APPLE', 'RETAILER', 'RETAILER'], ['RETAILER', 'RETAILER']]
model
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 12,529 (13.5%)
Most frequent values
['2020 APPLE MACBOOK AIR 13 3 RETINA DISPLAY M1 PROC']
['2020 APPLE MACBOOK PRO 13 TOUCH BAR M1 PROCESSOR 8']
['2020 APPLE MACBOOK AIR 13 3 RETINA DISPLAY M1 PROC', 'RETAILER']
['2021 APPLE MACBOOK PRO 14 M1 PRO PROCESSOR 16GB RA']
['2020 APPLE IPAD AIR 10 9 A14 BIONIC PROCESSOR IOS']
['2020 APPLE MACBOOK PRO 13 TOUCH BAR M1 PROCESSOR 8', 'RETAILER']
['2020 APPLE MACBOOK AIR', 'RETAILER']
['LG OLED55C14LB 2021 OLED HDR 4K ULTRA HD SMART TV']
['2021 APPLE MACBOOK PRO 16 M1 PRO PROCESSOR 16GB RA']
['2021 APPLE IMAC 24 ALL-IN-ONE M1 PROCESSOR 8GB RAM']
[['2020 APPLE MACBOOK AIR 13 3 RETINA DISPLAY M1 PROC'], ['2020 APPLE MACBOOK PRO 13 TOUCH BAR M1 PROCESSOR 8'], ['2020 APPLE MACBOOK AIR 13 3 RETINA DISPLAY M1 PROC', 'RETAILER'], ['2021 APPLE MACBOOK PRO 14 M1 PRO PROCESSOR 16GB RA'], ['2020 APPLE IPAD AIR 10 9 A14 BIONIC PROCESSOR IOS'], ['2020 APPLE MACBOOK PRO 13 TOUCH BAR M1 PROCESSOR 8', 'RETAILER'], ['2020 APPLE MACBOOK AIR', 'RETAILER'], ['LG OLED55C14LB 2021 OLED HDR 4K ULTRA HD SMART TV'], ['2021 APPLE MACBOOK PRO 16 M1 PRO PROCESSOR 16GB RA'], ['2021 APPLE IMAC 24 ALL-IN-ONE M1 PROCESSOR 8GB RAM']]
goods_code
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 17,916 (19.3%)
Most frequent values
['239246776']
['239246779']
['239246778']
['239246776', 'FULFILMENT']
['239246782']
['240575990']
['239827061']
['239246779', 'FULFILMENT']
['240376619']
['240376608']
[['239246776'], ['239246779'], ['239246778'], ['239246776', 'FULFILMENT'], ['239246782'], ['240575990'], ['239827061'], ['239246779', 'FULFILMENT'], ['240376619'], ['240376608']]
Nbr_of_prod_purchas
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 812 (0.9%)
Most frequent values
[1]
[1, 1]
[1, 1, 1]
[1, 1, 1, 1]
[1, 1, 1, 1, 1]
[2]
[2, 1]
[1, 2]
[1, 1, 1, 1, 1, 1]
[1, 2, 1]
[[1], [1, 1], [1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1, 1], [2], [2, 1], [1, 2], [1, 1, 1, 1, 1, 1], [1, 2, 1]]
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
Column 1 | Column 2 | Cramér's V | Pearson's Correlation |
---|---|---|---|
model | goods_code | 0.712 | |
item | make | 0.582 | |
make | Nbr_of_prod_purchas | 0.418 | |
item | Nbr_of_prod_purchas | 0.375 | |
item | model | 0.362 | |
cash_price | goods_code | 0.354 | |
cash_price | model | 0.335 | |
make | model | 0.303 | |
item | goods_code | 0.302 | |
item | cash_price | 0.290 | |
make | goods_code | 0.251 | |
cash_price | make | 0.199 | |
model | Nbr_of_prod_purchas | 0.191 | |
goods_code | Nbr_of_prod_purchas | 0.151 | |
cash_price | Nbr_of_prod_purchas | 0.142 |
Please enable javascript
The skrub table reports need javascript to display correctly. If you are displaying a report in a Jupyter notebook and you see this message, you may need to re-execute the cell or to trust the notebook (button on the top right or "File > Trust notebook").
Then, we can expand all lists into columns, as if we were “flattening” the dataframe.
We end up with a products dataframe ready to be joined on the baskets dataframe, using
"basket_ID"
as the join key.
import pandas as pd
products_flatten = []
for col in products_grouped.columns:
cols = [f"{col}{idx}" for idx in range(24)]
products_flatten.append(pd.DataFrame(products_grouped[col].to_list(), columns=cols))
products_flatten = pd.concat(products_flatten, axis=1)
products_flatten.insert(0, "basket_ID", products_grouped.index)
TableReport(products_flatten)
basket_ID | item0 | item1 | item2 | item3 | item4 | item5 | item6 | item7 | item8 | item9 | item10 | item11 | item12 | item13 | item14 | item15 | item16 | item17 | item18 | item19 | item20 | item21 | item22 | item23 | cash_price0 | cash_price1 | cash_price2 | cash_price3 | cash_price4 | cash_price5 | cash_price6 | cash_price7 | cash_price8 | cash_price9 | cash_price10 | cash_price11 | cash_price12 | cash_price13 | cash_price14 | cash_price15 | cash_price16 | cash_price17 | cash_price18 | cash_price19 | cash_price20 | cash_price21 | cash_price22 | cash_price23 | make0 | make1 | make2 | make3 | make4 | make5 | make6 | make7 | make8 | make9 | make10 | make11 | make12 | make13 | make14 | make15 | make16 | make17 | make18 | make19 | make20 | make21 | make22 | make23 | model0 | model1 | model2 | model3 | model4 | model5 | model6 | model7 | model8 | model9 | model10 | model11 | model12 | model13 | model14 | model15 | model16 | model17 | model18 | model19 | model20 | model21 | model22 | model23 | goods_code0 | goods_code1 | goods_code2 | goods_code3 | goods_code4 | goods_code5 | goods_code6 | goods_code7 | goods_code8 | goods_code9 | goods_code10 | goods_code11 | goods_code12 | goods_code13 | goods_code14 | goods_code15 | goods_code16 | goods_code17 | goods_code18 | goods_code19 | goods_code20 | goods_code21 | goods_code22 | goods_code23 | Nbr_of_prod_purchas0 | Nbr_of_prod_purchas1 | Nbr_of_prod_purchas2 | Nbr_of_prod_purchas3 | Nbr_of_prod_purchas4 | Nbr_of_prod_purchas5 | Nbr_of_prod_purchas6 | Nbr_of_prod_purchas7 | Nbr_of_prod_purchas8 | Nbr_of_prod_purchas9 | Nbr_of_prod_purchas10 | Nbr_of_prod_purchas11 | Nbr_of_prod_purchas12 | Nbr_of_prod_purchas13 | Nbr_of_prod_purchas14 | Nbr_of_prod_purchas15 | Nbr_of_prod_purchas16 | Nbr_of_prod_purchas17 | Nbr_of_prod_purchas18 | Nbr_of_prod_purchas19 | Nbr_of_prod_purchas20 | Nbr_of_prod_purchas21 | Nbr_of_prod_purchas22 | Nbr_of_prod_purchas23 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 0 | COMPUTERS | WARRANTY | FULFILMENT CHARGE | 1249 | 35.0 | 11.0 | APPLE | RETAILER | RETAILER | 2021 APPLE IMAC 24 ALL-IN-ONE M1 PROCESSOR 8GB RAM | RETAILER | RETAILER | 240040969 | 236604727 | FULFILMENT | 1 | 1.0 | 1.0 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
1 | 1 | OUTDOOR ACCESSORIES | OUTDOOR FURNITURE | 679 | 369.0 | KETTLER | RETAILER | RETAILER | RETAILER | 237874616 | 238222170 | 1 | 1.0 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
2 | 2 | OUTDOOR FURNITURE | OUTDOOR FURNITURE | 1879 | 110.0 | KETTLER | KETTLER | RETAILER | RETAILER | 239482916 | 235452317 | 1 | 1.0 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
3 | 4 | TELEPHONES, FAX MACHINES & TWO-WAY RADIOS | FULFILMENT CHARGE | 999 | 0.0 | APPLE | RETAILER | APPLE IPHONE 12 PRO | RETAILER | 239091969 | FULFILMENT | 1 | 1.0 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
4 | 5 | LIVING & DINING FURNITURE | 749 | RETAILER | RETAILER | 238000174 | 1 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
92785 | 115981 | COMPUTERS | 1149 | APPLE | 2021 APPLE IMAC 24 ALL-IN-ONE M1 PROCESSOR 8GB RAM | 240040965 | 1 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
92786 | 115982 | COMPUTERS | FULFILMENT CHARGE | 1399 | 7.0 | APPLE | RETAILER | 2021 APPLE IPAD PRO 11 M1 PROCESSOR IOS WI-FI 1TB | RETAILER | 240041001 | FULFILMENT | 1 | 1.0 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
92787 | 115983 | COMPUTER PERIPHERALS ACCESSORIES | 439 | APPLE | APPLE WATCH SERIES 7 GPS CELLULAR 41MM BLUE ALUMIN | 240376595 | 1 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
92788 | 115984 | COMPUTERS | 887 | APPLE | 2020 APPLE MACBOOK AIR 13 3 RETINA DISPLAY M1 PROC | 239246776 | 1 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
92789 | 115985 | COMPUTERS | FULFILMENT CHARGE | 569 | 7.0 | APPLE | RETAILER | 2022 APPLE IPAD AIR 10 9 M1 PROCESSOR IPADOS WI-FI | RETAILER | 241017996 | FULFILMENT | 1 | 1.0 |
basket_ID
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 92,790 (100.0%)
- Mean ± Std
- 5.80e+04 ± 3.35e+04
- Median ± IQR
- 57,961 ± 58,085
- Min | Max
- 0 | 115,985
item0
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 134 (0.1%)
item1
ObjectDType- Null values
- 48,134 (51.9%)
- Unique values
- 137 (0.1%)
item2
ObjectDType- Null values
- 79,889 (86.1%)
- Unique values
- 125 (0.1%)
item3
ObjectDType- Null values
- 88,228 (95.1%)
- Unique values
- 124 (0.1%)
item4
ObjectDType- Null values
- 90,620 (97.7%)
- Unique values
- 107 (0.1%)
item5
ObjectDType- Null values
- 91,454 (98.6%)
- Unique values
- 97 (0.1%)
item6
ObjectDType- Null values
- 91,844 (99.0%)
- Unique values
- 91 (< 0.1%)
item7
ObjectDType- Null values
- 92,063 (99.2%)
- Unique values
- 89 (< 0.1%)
item8
ObjectDType- Null values
- 92,222 (99.4%)
- Unique values
- 82 (< 0.1%)
item9
ObjectDType- Null values
- 92,318 (99.5%)
- Unique values
- 71 (< 0.1%)
item10
ObjectDType- Null values
- 92,406 (99.6%)
- Unique values
- 70 (< 0.1%)
item11
ObjectDType- Null values
- 92,468 (99.7%)
- Unique values
- 62 (< 0.1%)
item12
ObjectDType- Null values
- 92,533 (99.7%)
- Unique values
- 60 (< 0.1%)
item13
ObjectDType- Null values
- 92,571 (99.8%)
- Unique values
- 57 (< 0.1%)
item14
ObjectDType- Null values
- 92,597 (99.8%)
- Unique values
- 55 (< 0.1%)
item15
ObjectDType- Null values
- 92,625 (99.8%)
- Unique values
- 44 (< 0.1%)
item16
ObjectDType- Null values
- 92,648 (99.8%)
- Unique values
- 46 (< 0.1%)
item17
ObjectDType- Null values
- 92,670 (99.9%)
- Unique values
- 41 (< 0.1%)
item18
ObjectDType- Null values
- 92,687 (99.9%)
- Unique values
- 37 (< 0.1%)
item19
ObjectDType- Null values
- 92,699 (99.9%)
- Unique values
- 33 (< 0.1%)
item20
ObjectDType- Null values
- 92,713 (99.9%)
- Unique values
- 30 (< 0.1%)
item21
ObjectDType- Null values
- 92,727 (99.9%)
- Unique values
- 24 (< 0.1%)
item22
ObjectDType- Null values
- 92,740 (99.9%)
- Unique values
- 22 (< 0.1%)
item23
ObjectDType- Null values
- 92,747 (100.0%)
- Unique values
- 22 (< 0.1%)
cash_price0
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 1,406 (1.5%)
- Mean ± Std
- 1.09e+03 ± 711.
- Median ± IQR
- 949 ± 700
- Min | Max
- 2 | 21,995
cash_price1
Float64DType- Null values
- 48,134 (51.9%)
- Unique values
- 867 (0.9%)
- Mean ± Std
- 192. ± 393.
- Median ± IQR
- 40.0 ± 132.
- Min | Max
- 0.00 | 6.50e+03
cash_price2
Float64DType- Null values
- 79,889 (86.1%)
- Unique values
- 645 (0.7%)
- Mean ± Std
- 193. ± 376.
- Median ± IQR
- 43.0 ± 182.
- Min | Max
- 0.00 | 6.00e+03
cash_price3
Float64DType- Null values
- 88,228 (95.1%)
- Unique values
- 463 (0.5%)
- Mean ± Std
- 176. ± 321.
- Median ± IQR
- 48.0 ± 179.
- Min | Max
- 0.00 | 5.20e+03
cash_price4
Float64DType- Null values
- 90,620 (97.7%)
- Unique values
- 357 (0.4%)
- Mean ± Std
- 196. ± 374.
- Median ± IQR
- 59.0 ± 183.
- Min | Max
- 0.00 | 4.25e+03
cash_price5
Float64DType- Null values
- 91,454 (98.6%)
- Unique values
- 273 (0.3%)
- Mean ± Std
- 162. ± 292.
- Median ± IQR
- 50.0 ± 164.
- Min | Max
- 0.00 | 3.00e+03
cash_price6
Float64DType- Null values
- 91,844 (99.0%)
- Unique values
- 230 (0.2%)
- Mean ± Std
- 145. ± 291.
- Median ± IQR
- 50.0 ± 120.
- Min | Max
- 0.00 | 4.20e+03
cash_price7
Float64DType- Null values
- 92,063 (99.2%)
- Unique values
- 179 (0.2%)
- Mean ± Std
- 131. ± 258.
- Median ± IQR
- 45.0 ± 104.
- Min | Max
- 0.00 | 3.00e+03
cash_price8
Float64DType- Null values
- 92,222 (99.4%)
- Unique values
- 177 (0.2%)
- Mean ± Std
- 133. ± 267.
- Median ± IQR
- 45.0 ± 111.
- Min | Max
- 0.00 | 2.40e+03
cash_price9
Float64DType- Null values
- 92,318 (99.5%)
- Unique values
- 147 (0.2%)
- Mean ± Std
- 112. ± 213.
- Median ± IQR
- 40.0 ± 80.0
- Min | Max
- 0.00 | 1.54e+03
cash_price10
Float64DType- Null values
- 92,406 (99.6%)
- Unique values
- 130 (0.1%)
- Mean ± Std
- 112. ± 251.
- Median ± IQR
- 32.0 ± 81.0
- Min | Max
- 0.00 | 3.20e+03
cash_price11
Float64DType- Null values
- 92,468 (99.7%)
- Unique values
- 120 (0.1%)
- Mean ± Std
- 103. ± 220.
- Median ± IQR
- 30.0 ± 67.0
- Min | Max
- 0.00 | 2.16e+03
cash_price12
Float64DType- Null values
- 92,533 (99.7%)
- Unique values
- 102 (0.1%)
- Mean ± Std
- 84.2 ± 141.
- Median ± IQR
- 29.0 ± 77.0
- Min | Max
- 0.00 | 899.
cash_price13
Float64DType- Null values
- 92,571 (99.8%)
- Unique values
- 97 (0.1%)
- Mean ± Std
- 111. ± 200.
- Median ± IQR
- 39.0 ± 95.0
- Min | Max
- 0.00 | 1.30e+03
cash_price14
Float64DType- Null values
- 92,597 (99.8%)
- Unique values
- 82 (< 0.1%)
- Mean ± Std
- 72.4 ± 106.
- Median ± IQR
- 35.0 ± 59.0
- Min | Max
- 0.00 | 599.
cash_price15
Float64DType- Null values
- 92,625 (99.8%)
- Unique values
- 72 (< 0.1%)
- Mean ± Std
- 98.2 ± 228.
- Median ± IQR
- 35.0 ± 64.0
- Min | Max
- 0.00 | 1.60e+03
cash_price16
Float64DType- Null values
- 92,648 (99.8%)
- Unique values
- 71 (< 0.1%)
- Mean ± Std
- 89.0 ± 177.
- Median ± IQR
- 30.0 ± 76.0
- Min | Max
- 0.00 | 1.55e+03
cash_price17
Float64DType- Null values
- 92,670 (99.9%)
- Unique values
- 67 (< 0.1%)
- Mean ± Std
- 84.0 ± 134.
- Median ± IQR
- 25.0 ± 84.0
- Min | Max
- 0.00 | 799.
cash_price18
Float64DType- Null values
- 92,687 (99.9%)
- Unique values
- 67 (< 0.1%)
- Mean ± Std
- 88.2 ± 142.
- Median ± IQR
- 36.0 ± 77.0
- Min | Max
- 0.00 | 999.
cash_price19
Float64DType- Null values
- 92,699 (99.9%)
- Unique values
- 50 (< 0.1%)
- Mean ± Std
- 79.6 ± 223.
- Median ± IQR
- 26.0 ± 42.0
- Min | Max
- 0.00 | 2.01e+03
cash_price20
Float64DType- Null values
- 92,713 (99.9%)
- Unique values
- 43 (< 0.1%)
- Mean ± Std
- 58.2 ± 88.8
- Median ± IQR
- 25.0 ± 45.0
- Min | Max
- 4.00 | 450.
cash_price21
Float64DType- Null values
- 92,727 (99.9%)
- Unique values
- 42 (< 0.1%)
- Mean ± Std
- 126. ± 342.
- Median ± IQR
- 28.0 ± 57.0
- Min | Max
- 0.00 | 2.09e+03
cash_price22
Float64DType- Null values
- 92,740 (99.9%)
- Unique values
- 41 (< 0.1%)
- Mean ± Std
- 109. ± 199.
- Median ± IQR
- 35.0 ± 78.0
- Min | Max
- 0.00 | 995.
cash_price23
Float64DType- Null values
- 92,747 (100.0%)
- Unique values
- 31 (< 0.1%)
- Mean ± Std
- 122. ± 264.
- Median ± IQR
- 20.0 ± 66.0
- Min | Max
- 4.00 | 1.04e+03
make0
ObjectDType- Null values
- 685 (0.7%)
- Unique values
- 425 (0.5%)
make1
ObjectDType- Null values
- 48,461 (52.2%)
- Unique values
- 416 (0.4%)
make2
ObjectDType- Null values
- 79,999 (86.2%)
- Unique values
- 357 (0.4%)
make3
ObjectDType- Null values
- 88,262 (95.1%)
- Unique values
- 308 (0.3%)
make4
ObjectDType- Null values
- 90,639 (97.7%)
- Unique values
- 265 (0.3%)
make5
ObjectDType- Null values
- 91,467 (98.6%)
- Unique values
- 205 (0.2%)
make6
ObjectDType- Null values
- 91,854 (99.0%)
- Unique values
- 186 (0.2%)
make7
ObjectDType- Null values
- 92,073 (99.2%)
- Unique values
- 165 (0.2%)
make8
ObjectDType- Null values
- 92,232 (99.4%)
- Unique values
- 142 (0.2%)
make9
ObjectDType- Null values
- 92,328 (99.5%)
- Unique values
- 126 (0.1%)
make10
ObjectDType- Null values
- 92,414 (99.6%)
- Unique values
- 107 (0.1%)
make11
ObjectDType- Null values
- 92,476 (99.7%)
- Unique values
- 100 (0.1%)
make12
ObjectDType- Null values
- 92,540 (99.7%)
- Unique values
- 81 (< 0.1%)
make13
ObjectDType- Null values
- 92,576 (99.8%)
- Unique values
- 73 (< 0.1%)
make14
ObjectDType- Null values
- 92,602 (99.8%)
- Unique values
- 69 (< 0.1%)
make15
ObjectDType- Null values
- 92,628 (99.8%)
- Unique values
- 61 (< 0.1%)
make16
ObjectDType- Null values
- 92,651 (99.9%)
- Unique values
- 49 (< 0.1%)
make17
ObjectDType- Null values
- 92,671 (99.9%)
- Unique values
- 42 (< 0.1%)
make18
ObjectDType- Null values
- 92,688 (99.9%)
- Unique values
- 44 (< 0.1%)
make19
ObjectDType- Null values
- 92,700 (99.9%)
- Unique values
- 37 (< 0.1%)
make20
ObjectDType- Null values
- 92,714 (99.9%)
- Unique values
- 30 (< 0.1%)
make21
ObjectDType- Null values
- 92,728 (99.9%)
- Unique values
- 23 (< 0.1%)
make22
ObjectDType- Null values
- 92,741 (99.9%)
- Unique values
- 25 (< 0.1%)
make23
ObjectDType- Null values
- 92,747 (100.0%)
- Unique values
- 19 (< 0.1%)
model0
ObjectDType- Null values
- 685 (0.7%)
- Unique values
- 3,782 (4.1%)
model1
ObjectDType- Null values
- 48,461 (52.2%)
- Unique values
- 3,242 (3.5%)
model2
ObjectDType- Null values
- 79,999 (86.2%)
- Unique values
- 2,344 (2.5%)
model3
ObjectDType- Null values
- 88,262 (95.1%)
- Unique values
- 1,611 (1.7%)
model4
ObjectDType- Null values
- 90,639 (97.7%)
- Unique values
- 1,093 (1.2%)
model5
ObjectDType- Null values
- 91,467 (98.6%)
- Unique values
- 756 (0.8%)
model6
ObjectDType- Null values
- 91,854 (99.0%)
- Unique values
- 601 (0.6%)
model7
ObjectDType- Null values
- 92,073 (99.2%)
- Unique values
- 472 (0.5%)
model8
ObjectDType- Null values
- 92,232 (99.4%)
- Unique values
- 377 (0.4%)
model9
ObjectDType- Null values
- 92,328 (99.5%)
- Unique values
- 333 (0.4%)
model10
ObjectDType- Null values
- 92,414 (99.6%)
- Unique values
- 265 (0.3%)
model11
ObjectDType- Null values
- 92,476 (99.7%)
- Unique values
- 219 (0.2%)
model12
ObjectDType- Null values
- 92,540 (99.7%)
- Unique values
- 179 (0.2%)
model13
ObjectDType- Null values
- 92,576 (99.8%)
- Unique values
- 154 (0.2%)
model14
ObjectDType- Null values
- 92,602 (99.8%)
- Unique values
- 139 (0.1%)
model15
ObjectDType- Null values
- 92,628 (99.8%)
- Unique values
- 123 (0.1%)
model16
ObjectDType- Null values
- 92,651 (99.9%)
- Unique values
- 106 (0.1%)
model17
ObjectDType- Null values
- 92,671 (99.9%)
- Unique values
- 87 (< 0.1%)
model18
ObjectDType- Null values
- 92,688 (99.9%)
- Unique values
- 81 (< 0.1%)
model19
ObjectDType- Null values
- 92,700 (99.9%)
- Unique values
- 75 (< 0.1%)
model20
ObjectDType- Null values
- 92,714 (99.9%)
- Unique values
- 63 (< 0.1%)
model21
ObjectDType- Null values
- 92,728 (99.9%)
- Unique values
- 55 (< 0.1%)
model22
ObjectDType- Null values
- 92,741 (99.9%)
- Unique values
- 45 (< 0.1%)
model23
ObjectDType- Null values
- 92,747 (100.0%)
- Unique values
- 42 (< 0.1%)
goods_code0
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 5,966 (6.4%)
goods_code1
ObjectDType- Null values
- 48,134 (51.9%)
- Unique values
- 4,728 (5.1%)
goods_code2
ObjectDType- Null values
- 79,889 (86.1%)
- Unique values
- 3,237 (3.5%)
goods_code3
ObjectDType- Null values
- 88,228 (95.1%)
- Unique values
- 2,118 (2.3%)
goods_code4
ObjectDType- Null values
- 90,620 (97.7%)
- Unique values
- 1,480 (1.6%)
goods_code5
ObjectDType- Null values
- 91,454 (98.6%)
- Unique values
- 1,006 (1.1%)
goods_code6
ObjectDType- Null values
- 91,844 (99.0%)
- Unique values
- 805 (0.9%)
goods_code7
ObjectDType- Null values
- 92,063 (99.2%)
- Unique values
- 628 (0.7%)
goods_code8
ObjectDType- Null values
- 92,222 (99.4%)
- Unique values
- 514 (0.6%)
goods_code9
ObjectDType- Null values
- 92,318 (99.5%)
- Unique values
- 426 (0.5%)
goods_code10
ObjectDType- Null values
- 92,406 (99.6%)
- Unique values
- 350 (0.4%)
goods_code11
ObjectDType- Null values
- 92,468 (99.7%)
- Unique values
- 282 (0.3%)
goods_code12
ObjectDType- Null values
- 92,533 (99.7%)
- Unique values
- 238 (0.3%)
goods_code13
ObjectDType- Null values
- 92,571 (99.8%)
- Unique values
- 205 (0.2%)
goods_code14
ObjectDType- Null values
- 92,597 (99.8%)
- Unique values
- 179 (0.2%)
goods_code15
ObjectDType- Null values
- 92,625 (99.8%)
- Unique values
- 156 (0.2%)
goods_code16
ObjectDType- Null values
- 92,648 (99.8%)
- Unique values
- 131 (0.1%)
goods_code17
ObjectDType- Null values
- 92,670 (99.9%)
- Unique values
- 109 (0.1%)
goods_code18
ObjectDType- Null values
- 92,687 (99.9%)
- Unique values
- 96 (0.1%)
goods_code19
ObjectDType- Null values
- 92,699 (99.9%)
- Unique values
- 85 (< 0.1%)
goods_code20
ObjectDType- Null values
- 92,713 (99.9%)
- Unique values
- 71 (< 0.1%)
goods_code21
ObjectDType- Null values
- 92,727 (99.9%)
- Unique values
- 59 (< 0.1%)
goods_code22
ObjectDType- Null values
- 92,740 (99.9%)
- Unique values
- 46 (< 0.1%)
goods_code23
ObjectDType- Null values
- 92,747 (100.0%)
- Unique values
- 42 (< 0.1%)
Nbr_of_prod_purchas0
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 16 (< 0.1%)
- Mean ± Std
- 1.03 ± 0.351
- Median ± IQR
- 1 ± 0
- Min | Max
- 1 | 40
Nbr_of_prod_purchas1
Float64DType- Null values
- 48,134 (51.9%)
- Unique values
- 13 (< 0.1%)
- Mean ± Std
- 1.04 ± 0.300
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 18.0
Nbr_of_prod_purchas2
Float64DType- Null values
- 79,889 (86.1%)
- Unique values
- 12 (< 0.1%)
- Mean ± Std
- 1.08 ± 0.464
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 16.0
Nbr_of_prod_purchas3
Float64DType- Null values
- 88,228 (95.1%)
- Unique values
- 14 (< 0.1%)
- Mean ± Std
- 1.15 ± 0.795
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 28.0
Nbr_of_prod_purchas4
Float64DType- Null values
- 90,620 (97.7%)
- Unique values
- 10 (< 0.1%)
- Mean ± Std
- 1.23 ± 0.824
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 15.0
Nbr_of_prod_purchas5
Float64DType- Null values
- 91,454 (98.6%)
- Unique values
- 9 (< 0.1%)
- Mean ± Std
- 1.26 ± 0.978
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 24.0
Nbr_of_prod_purchas6
Float64DType- Null values
- 91,844 (99.0%)
- Unique values
- 10 (< 0.1%)
- Mean ± Std
- 1.29 ± 0.905
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 16.0
Nbr_of_prod_purchas7
Float64DType- Null values
- 92,063 (99.2%)
- Unique values
- 10 (< 0.1%)
- Mean ± Std
- 1.33 ± 1.05
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 14.0
Nbr_of_prod_purchas8
Float64DType- Null values
- 92,222 (99.4%)
- Unique values
- 11 (< 0.1%)
- Mean ± Std
- 1.41 ± 1.27
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 18.0
Nbr_of_prod_purchas9
Float64DType- Null values
- 92,318 (99.5%)
- Unique values
- 7 (< 0.1%)
- Mean ± Std
- 1.36 ± 0.948
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 8.00
Nbr_of_prod_purchas10
Float64DType- Null values
- 92,406 (99.6%)
- Unique values
- 9 (< 0.1%)
- Mean ± Std
- 1.37 ± 1.11
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 12.0
Nbr_of_prod_purchas11
Float64DType- Null values
- 92,468 (99.7%)
- Unique values
- 7 (< 0.1%)
- Mean ± Std
- 1.32 ± 0.897
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 7.00
Nbr_of_prod_purchas12
Float64DType- Null values
- 92,533 (99.7%)
- Unique values
- 6 (< 0.1%)
- Mean ± Std
- 1.26 ± 0.823
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 10.0
Nbr_of_prod_purchas13
Float64DType- Null values
- 92,571 (99.8%)
- Unique values
- 6 (< 0.1%)
- Mean ± Std
- 1.36 ± 1.04
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 12.0
Nbr_of_prod_purchas14
Float64DType- Null values
- 92,597 (99.8%)
- Unique values
- 6 (< 0.1%)
- Mean ± Std
- 1.35 ± 0.951
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 6.00
Nbr_of_prod_purchas15
Float64DType- Null values
- 92,625 (99.8%)
- Unique values
- 6 (< 0.1%)
- Mean ± Std
- 1.29 ± 0.749
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 6.00
Nbr_of_prod_purchas16
Float64DType- Null values
- 92,648 (99.8%)
- Unique values
- 5 (< 0.1%)
- Mean ± Std
- 1.44 ± 1.43
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 12.0
Nbr_of_prod_purchas17
Float64DType- Null values
- 92,670 (99.9%)
- Unique values
- 7 (< 0.1%)
- Mean ± Std
- 1.47 ± 1.81
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 16.0
Nbr_of_prod_purchas18
Float64DType- Null values
- 92,687 (99.9%)
- Unique values
- 7 (< 0.1%)
- Mean ± Std
- 1.39 ± 1.17
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 7.00
Nbr_of_prod_purchas19
Float64DType- Null values
- 92,699 (99.9%)
- Unique values
- 5 (< 0.1%)
- Mean ± Std
- 1.33 ± 0.870
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 7.00
Nbr_of_prod_purchas20
Float64DType- Null values
- 92,713 (99.9%)
- Unique values
- 4 (< 0.1%)
- Mean ± Std
- 1.22 ± 0.529
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 4.00
Nbr_of_prod_purchas21
Float64DType- Null values
- 92,727 (99.9%)
- Unique values
- 5 (< 0.1%)
- Mean ± Std
- 1.38 ± 0.923
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 7.00
Nbr_of_prod_purchas22
Float64DType- Null values
- 92,740 (99.9%)
- Unique values
- 4 (< 0.1%)
- Mean ± Std
- 1.16 ± 0.548
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 4.00
Nbr_of_prod_purchas23
Float64DType- Null values
- 92,747 (100.0%)
- Unique values
- 3 (< 0.1%)
- Mean ± Std
- 1.37 ± 1.11
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 8.00
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
Column
|
Column name
|
dtype
|
Null values
|
Unique values
|
Mean
|
Std
|
Min
|
Median
|
Max
|
---|---|---|---|---|---|---|---|---|---|
0 | basket_ID | Int64DType | 0 (0.0%) | 92790 (100.0%) | 5.80e+04 | 3.35e+04 | 0 | 57,961 | 115,985 |
1 | item0 | ObjectDType | 0 (0.0%) | 134 (0.1%) | |||||
2 | item1 | ObjectDType | 48134 (51.9%) | 137 (0.1%) | |||||
3 | item2 | ObjectDType | 79889 (86.1%) | 125 (0.1%) | |||||
4 | item3 | ObjectDType | 88228 (95.1%) | 124 (0.1%) | |||||
5 | item4 | ObjectDType | 90620 (97.7%) | 107 (0.1%) | |||||
6 | item5 | ObjectDType | 91454 (98.6%) | 97 (0.1%) | |||||
7 | item6 | ObjectDType | 91844 (99.0%) | 91 (< 0.1%) | |||||
8 | item7 | ObjectDType | 92063 (99.2%) | 89 (< 0.1%) | |||||
9 | item8 | ObjectDType | 92222 (99.4%) | 82 (< 0.1%) | |||||
10 | item9 | ObjectDType | 92318 (99.5%) | 71 (< 0.1%) | |||||
11 | item10 | ObjectDType | 92406 (99.6%) | 70 (< 0.1%) | |||||
12 | item11 | ObjectDType | 92468 (99.7%) | 62 (< 0.1%) | |||||
13 | item12 | ObjectDType | 92533 (99.7%) | 60 (< 0.1%) | |||||
14 | item13 | ObjectDType | 92571 (99.8%) | 57 (< 0.1%) | |||||
15 | item14 | ObjectDType | 92597 (99.8%) | 55 (< 0.1%) | |||||
16 | item15 | ObjectDType | 92625 (99.8%) | 44 (< 0.1%) | |||||
17 | item16 | ObjectDType | 92648 (99.8%) | 46 (< 0.1%) | |||||
18 | item17 | ObjectDType | 92670 (99.9%) | 41 (< 0.1%) | |||||
19 | item18 | ObjectDType | 92687 (99.9%) | 37 (< 0.1%) | |||||
20 | item19 | ObjectDType | 92699 (99.9%) | 33 (< 0.1%) | |||||
21 | item20 | ObjectDType | 92713 (99.9%) | 30 (< 0.1%) | |||||
22 | item21 | ObjectDType | 92727 (99.9%) | 24 (< 0.1%) | |||||
23 | item22 | ObjectDType | 92740 (99.9%) | 22 (< 0.1%) | |||||
24 | item23 | ObjectDType | 92747 (100.0%) | 22 (< 0.1%) | |||||
25 | cash_price0 | Int64DType | 0 (0.0%) | 1406 (1.5%) | 1.09e+03 | 711. | 2 | 949 | 21,995 |
26 | cash_price1 | Float64DType | 48134 (51.9%) | 867 (0.9%) | 192. | 393. | 0.00 | 40.0 | 6.50e+03 |
27 | cash_price2 | Float64DType | 79889 (86.1%) | 645 (0.7%) | 193. | 376. | 0.00 | 43.0 | 6.00e+03 |
28 | cash_price3 | Float64DType | 88228 (95.1%) | 463 (0.5%) | 176. | 321. | 0.00 | 48.0 | 5.20e+03 |
29 | cash_price4 | Float64DType | 90620 (97.7%) | 357 (0.4%) | 196. | 374. | 0.00 | 59.0 | 4.25e+03 |
30 | cash_price5 | Float64DType | 91454 (98.6%) | 273 (0.3%) | 162. | 292. | 0.00 | 50.0 | 3.00e+03 |
31 | cash_price6 | Float64DType | 91844 (99.0%) | 230 (0.2%) | 145. | 291. | 0.00 | 50.0 | 4.20e+03 |
32 | cash_price7 | Float64DType | 92063 (99.2%) | 179 (0.2%) | 131. | 258. | 0.00 | 45.0 | 3.00e+03 |
33 | cash_price8 | Float64DType | 92222 (99.4%) | 177 (0.2%) | 133. | 267. | 0.00 | 45.0 | 2.40e+03 |
34 | cash_price9 | Float64DType | 92318 (99.5%) | 147 (0.2%) | 112. | 213. | 0.00 | 40.0 | 1.54e+03 |
35 | cash_price10 | Float64DType | 92406 (99.6%) | 130 (0.1%) | 112. | 251. | 0.00 | 32.0 | 3.20e+03 |
36 | cash_price11 | Float64DType | 92468 (99.7%) | 120 (0.1%) | 103. | 220. | 0.00 | 30.0 | 2.16e+03 |
37 | cash_price12 | Float64DType | 92533 (99.7%) | 102 (0.1%) | 84.2 | 141. | 0.00 | 29.0 | 899. |
38 | cash_price13 | Float64DType | 92571 (99.8%) | 97 (0.1%) | 111. | 200. | 0.00 | 39.0 | 1.30e+03 |
39 | cash_price14 | Float64DType | 92597 (99.8%) | 82 (< 0.1%) | 72.4 | 106. | 0.00 | 35.0 | 599. |
40 | cash_price15 | Float64DType | 92625 (99.8%) | 72 (< 0.1%) | 98.2 | 228. | 0.00 | 35.0 | 1.60e+03 |
41 | cash_price16 | Float64DType | 92648 (99.8%) | 71 (< 0.1%) | 89.0 | 177. | 0.00 | 30.0 | 1.55e+03 |
42 | cash_price17 | Float64DType | 92670 (99.9%) | 67 (< 0.1%) | 84.0 | 134. | 0.00 | 25.0 | 799. |
43 | cash_price18 | Float64DType | 92687 (99.9%) | 67 (< 0.1%) | 88.2 | 142. | 0.00 | 36.0 | 999. |
44 | cash_price19 | Float64DType | 92699 (99.9%) | 50 (< 0.1%) | 79.6 | 223. | 0.00 | 26.0 | 2.01e+03 |
45 | cash_price20 | Float64DType | 92713 (99.9%) | 43 (< 0.1%) | 58.2 | 88.8 | 4.00 | 25.0 | 450. |
46 | cash_price21 | Float64DType | 92727 (99.9%) | 42 (< 0.1%) | 126. | 342. | 0.00 | 28.0 | 2.09e+03 |
47 | cash_price22 | Float64DType | 92740 (99.9%) | 41 (< 0.1%) | 109. | 199. | 0.00 | 35.0 | 995. |
48 | cash_price23 | Float64DType | 92747 (100.0%) | 31 (< 0.1%) | 122. | 264. | 4.00 | 20.0 | 1.04e+03 |
49 | make0 | ObjectDType | 685 (0.7%) | 425 (0.5%) | |||||
50 | make1 | ObjectDType | 48461 (52.2%) | 416 (0.4%) | |||||
51 | make2 | ObjectDType | 79999 (86.2%) | 357 (0.4%) | |||||
52 | make3 | ObjectDType | 88262 (95.1%) | 308 (0.3%) | |||||
53 | make4 | ObjectDType | 90639 (97.7%) | 265 (0.3%) | |||||
54 | make5 | ObjectDType | 91467 (98.6%) | 205 (0.2%) | |||||
55 | make6 | ObjectDType | 91854 (99.0%) | 186 (0.2%) | |||||
56 | make7 | ObjectDType | 92073 (99.2%) | 165 (0.2%) | |||||
57 | make8 | ObjectDType | 92232 (99.4%) | 142 (0.2%) | |||||
58 | make9 | ObjectDType | 92328 (99.5%) | 126 (0.1%) | |||||
59 | make10 | ObjectDType | 92414 (99.6%) | 107 (0.1%) | |||||
60 | make11 | ObjectDType | 92476 (99.7%) | 100 (0.1%) | |||||
61 | make12 | ObjectDType | 92540 (99.7%) | 81 (< 0.1%) | |||||
62 | make13 | ObjectDType | 92576 (99.8%) | 73 (< 0.1%) | |||||
63 | make14 | ObjectDType | 92602 (99.8%) | 69 (< 0.1%) | |||||
64 | make15 | ObjectDType | 92628 (99.8%) | 61 (< 0.1%) | |||||
65 | make16 | ObjectDType | 92651 (99.9%) | 49 (< 0.1%) | |||||
66 | make17 | ObjectDType | 92671 (99.9%) | 42 (< 0.1%) | |||||
67 | make18 | ObjectDType | 92688 (99.9%) | 44 (< 0.1%) | |||||
68 | make19 | ObjectDType | 92700 (99.9%) | 37 (< 0.1%) | |||||
69 | make20 | ObjectDType | 92714 (99.9%) | 30 (< 0.1%) | |||||
70 | make21 | ObjectDType | 92728 (99.9%) | 23 (< 0.1%) | |||||
71 | make22 | ObjectDType | 92741 (99.9%) | 25 (< 0.1%) | |||||
72 | make23 | ObjectDType | 92747 (100.0%) | 19 (< 0.1%) | |||||
73 | model0 | ObjectDType | 685 (0.7%) | 3782 (4.1%) | |||||
74 | model1 | ObjectDType | 48461 (52.2%) | 3242 (3.5%) | |||||
75 | model2 | ObjectDType | 79999 (86.2%) | 2344 (2.5%) | |||||
76 | model3 | ObjectDType | 88262 (95.1%) | 1611 (1.7%) | |||||
77 | model4 | ObjectDType | 90639 (97.7%) | 1093 (1.2%) | |||||
78 | model5 | ObjectDType | 91467 (98.6%) | 756 (0.8%) | |||||
79 | model6 | ObjectDType | 91854 (99.0%) | 601 (0.6%) | |||||
80 | model7 | ObjectDType | 92073 (99.2%) | 472 (0.5%) | |||||
81 | model8 | ObjectDType | 92232 (99.4%) | 377 (0.4%) | |||||
82 | model9 | ObjectDType | 92328 (99.5%) | 333 (0.4%) | |||||
83 | model10 | ObjectDType | 92414 (99.6%) | 265 (0.3%) | |||||
84 | model11 | ObjectDType | 92476 (99.7%) | 219 (0.2%) | |||||
85 | model12 | ObjectDType | 92540 (99.7%) | 179 (0.2%) | |||||
86 | model13 | ObjectDType | 92576 (99.8%) | 154 (0.2%) | |||||
87 | model14 | ObjectDType | 92602 (99.8%) | 139 (0.1%) | |||||
88 | model15 | ObjectDType | 92628 (99.8%) | 123 (0.1%) | |||||
89 | model16 | ObjectDType | 92651 (99.9%) | 106 (0.1%) | |||||
90 | model17 | ObjectDType | 92671 (99.9%) | 87 (< 0.1%) | |||||
91 | model18 | ObjectDType | 92688 (99.9%) | 81 (< 0.1%) | |||||
92 | model19 | ObjectDType | 92700 (99.9%) | 75 (< 0.1%) | |||||
93 | model20 | ObjectDType | 92714 (99.9%) | 63 (< 0.1%) | |||||
94 | model21 | ObjectDType | 92728 (99.9%) | 55 (< 0.1%) | |||||
95 | model22 | ObjectDType | 92741 (99.9%) | 45 (< 0.1%) | |||||
96 | model23 | ObjectDType | 92747 (100.0%) | 42 (< 0.1%) | |||||
97 | goods_code0 | ObjectDType | 0 (0.0%) | 5966 (6.4%) | |||||
98 | goods_code1 | ObjectDType | 48134 (51.9%) | 4728 (5.1%) | |||||
99 | goods_code2 | ObjectDType | 79889 (86.1%) | 3237 (3.5%) | |||||
100 | goods_code3 | ObjectDType | 88228 (95.1%) | 2118 (2.3%) | |||||
101 | goods_code4 | ObjectDType | 90620 (97.7%) | 1480 (1.6%) | |||||
102 | goods_code5 | ObjectDType | 91454 (98.6%) | 1006 (1.1%) | |||||
103 | goods_code6 | ObjectDType | 91844 (99.0%) | 805 (0.9%) | |||||
104 | goods_code7 | ObjectDType | 92063 (99.2%) | 628 (0.7%) | |||||
105 | goods_code8 | ObjectDType | 92222 (99.4%) | 514 (0.6%) | |||||
106 | goods_code9 | ObjectDType | 92318 (99.5%) | 426 (0.5%) | |||||
107 | goods_code10 | ObjectDType | 92406 (99.6%) | 350 (0.4%) | |||||
108 | goods_code11 | ObjectDType | 92468 (99.7%) | 282 (0.3%) | |||||
109 | goods_code12 | ObjectDType | 92533 (99.7%) | 238 (0.3%) | |||||
110 | goods_code13 | ObjectDType | 92571 (99.8%) | 205 (0.2%) | |||||
111 | goods_code14 | ObjectDType | 92597 (99.8%) | 179 (0.2%) | |||||
112 | goods_code15 | ObjectDType | 92625 (99.8%) | 156 (0.2%) | |||||
113 | goods_code16 | ObjectDType | 92648 (99.8%) | 131 (0.1%) | |||||
114 | goods_code17 | ObjectDType | 92670 (99.9%) | 109 (0.1%) | |||||
115 | goods_code18 | ObjectDType | 92687 (99.9%) | 96 (0.1%) | |||||
116 | goods_code19 | ObjectDType | 92699 (99.9%) | 85 (< 0.1%) | |||||
117 | goods_code20 | ObjectDType | 92713 (99.9%) | 71 (< 0.1%) | |||||
118 | goods_code21 | ObjectDType | 92727 (99.9%) | 59 (< 0.1%) | |||||
119 | goods_code22 | ObjectDType | 92740 (99.9%) | 46 (< 0.1%) | |||||
120 | goods_code23 | ObjectDType | 92747 (100.0%) | 42 (< 0.1%) | |||||
121 | Nbr_of_prod_purchas0 | Int64DType | 0 (0.0%) | 16 (< 0.1%) | 1.03 | 0.351 | 1 | 1 | 40 |
122 | Nbr_of_prod_purchas1 | Float64DType | 48134 (51.9%) | 13 (< 0.1%) | 1.04 | 0.300 | 1.00 | 1.00 | 18.0 |
123 | Nbr_of_prod_purchas2 | Float64DType | 79889 (86.1%) | 12 (< 0.1%) | 1.08 | 0.464 | 1.00 | 1.00 | 16.0 |
124 | Nbr_of_prod_purchas3 | Float64DType | 88228 (95.1%) | 14 (< 0.1%) | 1.15 | 0.795 | 1.00 | 1.00 | 28.0 |
125 | Nbr_of_prod_purchas4 | Float64DType | 90620 (97.7%) | 10 (< 0.1%) | 1.23 | 0.824 | 1.00 | 1.00 | 15.0 |
126 | Nbr_of_prod_purchas5 | Float64DType | 91454 (98.6%) | 9 (< 0.1%) | 1.26 | 0.978 | 1.00 | 1.00 | 24.0 |
127 | Nbr_of_prod_purchas6 | Float64DType | 91844 (99.0%) | 10 (< 0.1%) | 1.29 | 0.905 | 1.00 | 1.00 | 16.0 |
128 | Nbr_of_prod_purchas7 | Float64DType | 92063 (99.2%) | 10 (< 0.1%) | 1.33 | 1.05 | 1.00 | 1.00 | 14.0 |
129 | Nbr_of_prod_purchas8 | Float64DType | 92222 (99.4%) | 11 (< 0.1%) | 1.41 | 1.27 | 1.00 | 1.00 | 18.0 |
130 | Nbr_of_prod_purchas9 | Float64DType | 92318 (99.5%) | 7 (< 0.1%) | 1.36 | 0.948 | 1.00 | 1.00 | 8.00 |
131 | Nbr_of_prod_purchas10 | Float64DType | 92406 (99.6%) | 9 (< 0.1%) | 1.37 | 1.11 | 1.00 | 1.00 | 12.0 |
132 | Nbr_of_prod_purchas11 | Float64DType | 92468 (99.7%) | 7 (< 0.1%) | 1.32 | 0.897 | 1.00 | 1.00 | 7.00 |
133 | Nbr_of_prod_purchas12 | Float64DType | 92533 (99.7%) | 6 (< 0.1%) | 1.26 | 0.823 | 1.00 | 1.00 | 10.0 |
134 | Nbr_of_prod_purchas13 | Float64DType | 92571 (99.8%) | 6 (< 0.1%) | 1.36 | 1.04 | 1.00 | 1.00 | 12.0 |
135 | Nbr_of_prod_purchas14 | Float64DType | 92597 (99.8%) | 6 (< 0.1%) | 1.35 | 0.951 | 1.00 | 1.00 | 6.00 |
136 | Nbr_of_prod_purchas15 | Float64DType | 92625 (99.8%) | 6 (< 0.1%) | 1.29 | 0.749 | 1.00 | 1.00 | 6.00 |
137 | Nbr_of_prod_purchas16 | Float64DType | 92648 (99.8%) | 5 (< 0.1%) | 1.44 | 1.43 | 1.00 | 1.00 | 12.0 |
138 | Nbr_of_prod_purchas17 | Float64DType | 92670 (99.9%) | 7 (< 0.1%) | 1.47 | 1.81 | 1.00 | 1.00 | 16.0 |
139 | Nbr_of_prod_purchas18 | Float64DType | 92687 (99.9%) | 7 (< 0.1%) | 1.39 | 1.17 | 1.00 | 1.00 | 7.00 |
140 | Nbr_of_prod_purchas19 | Float64DType | 92699 (99.9%) | 5 (< 0.1%) | 1.33 | 0.870 | 1.00 | 1.00 | 7.00 |
141 | Nbr_of_prod_purchas20 | Float64DType | 92713 (99.9%) | 4 (< 0.1%) | 1.22 | 0.529 | 1.00 | 1.00 | 4.00 |
142 | Nbr_of_prod_purchas21 | Float64DType | 92727 (99.9%) | 5 (< 0.1%) | 1.38 | 0.923 | 1.00 | 1.00 | 7.00 |
143 | Nbr_of_prod_purchas22 | Float64DType | 92740 (99.9%) | 4 (< 0.1%) | 1.16 | 0.548 | 1.00 | 1.00 | 4.00 |
144 | Nbr_of_prod_purchas23 | Float64DType | 92747 (100.0%) | 3 (< 0.1%) | 1.37 | 1.11 | 1.00 | 1.00 | 8.00 |
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
max_plot_columns
parameter.
basket_ID
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 92,790 (100.0%)
- Mean ± Std
- 5.80e+04 ± 3.35e+04
- Median ± IQR
- 57,961 ± 58,085
- Min | Max
- 0 | 115,985
item0
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 134 (0.1%)
item1
ObjectDType- Null values
- 48,134 (51.9%)
- Unique values
- 137 (0.1%)
item2
ObjectDType- Null values
- 79,889 (86.1%)
- Unique values
- 125 (0.1%)
item3
ObjectDType- Null values
- 88,228 (95.1%)
- Unique values
- 124 (0.1%)
item4
ObjectDType- Null values
- 90,620 (97.7%)
- Unique values
- 107 (0.1%)
item5
ObjectDType- Null values
- 91,454 (98.6%)
- Unique values
- 97 (0.1%)
item6
ObjectDType- Null values
- 91,844 (99.0%)
- Unique values
- 91 (< 0.1%)
item7
ObjectDType- Null values
- 92,063 (99.2%)
- Unique values
- 89 (< 0.1%)
item8
ObjectDType- Null values
- 92,222 (99.4%)
- Unique values
- 82 (< 0.1%)
item9
ObjectDType- Null values
- 92,318 (99.5%)
- Unique values
- 71 (< 0.1%)
item10
ObjectDType- Null values
- 92,406 (99.6%)
- Unique values
- 70 (< 0.1%)
item11
ObjectDType- Null values
- 92,468 (99.7%)
- Unique values
- 62 (< 0.1%)
item12
ObjectDType- Null values
- 92,533 (99.7%)
- Unique values
- 60 (< 0.1%)
item13
ObjectDType- Null values
- 92,571 (99.8%)
- Unique values
- 57 (< 0.1%)
item14
ObjectDType- Null values
- 92,597 (99.8%)
- Unique values
- 55 (< 0.1%)
item15
ObjectDType- Null values
- 92,625 (99.8%)
- Unique values
- 44 (< 0.1%)
item16
ObjectDType- Null values
- 92,648 (99.8%)
- Unique values
- 46 (< 0.1%)
item17
ObjectDType- Null values
- 92,670 (99.9%)
- Unique values
- 41 (< 0.1%)
item18
ObjectDType- Null values
- 92,687 (99.9%)
- Unique values
- 37 (< 0.1%)
item19
ObjectDType- Null values
- 92,699 (99.9%)
- Unique values
- 33 (< 0.1%)
item20
ObjectDType- Null values
- 92,713 (99.9%)
- Unique values
- 30 (< 0.1%)
item21
ObjectDType- Null values
- 92,727 (99.9%)
- Unique values
- 24 (< 0.1%)
item22
ObjectDType- Null values
- 92,740 (99.9%)
- Unique values
- 22 (< 0.1%)
item23
ObjectDType- Null values
- 92,747 (100.0%)
- Unique values
- 22 (< 0.1%)
cash_price0
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 1,406 (1.5%)
- Mean ± Std
- 1.09e+03 ± 711.
- Median ± IQR
- 949 ± 700
- Min | Max
- 2 | 21,995
cash_price1
Float64DType- Null values
- 48,134 (51.9%)
- Unique values
- 867 (0.9%)
- Mean ± Std
- 192. ± 393.
- Median ± IQR
- 40.0 ± 132.
- Min | Max
- 0.00 | 6.50e+03
cash_price2
Float64DType- Null values
- 79,889 (86.1%)
- Unique values
- 645 (0.7%)
- Mean ± Std
- 193. ± 376.
- Median ± IQR
- 43.0 ± 182.
- Min | Max
- 0.00 | 6.00e+03
cash_price3
Float64DType- Null values
- 88,228 (95.1%)
- Unique values
- 463 (0.5%)
- Mean ± Std
- 176. ± 321.
- Median ± IQR
- 48.0 ± 179.
- Min | Max
- 0.00 | 5.20e+03
cash_price4
Float64DType- Null values
- 90,620 (97.7%)
- Unique values
- 357 (0.4%)
- Mean ± Std
- 196. ± 374.
- Median ± IQR
- 59.0 ± 183.
- Min | Max
- 0.00 | 4.25e+03
cash_price5
Float64DType- Null values
- 91,454 (98.6%)
- Unique values
- 273 (0.3%)
- Mean ± Std
- 162. ± 292.
- Median ± IQR
- 50.0 ± 164.
- Min | Max
- 0.00 | 3.00e+03
cash_price6
Float64DType- Null values
- 91,844 (99.0%)
- Unique values
- 230 (0.2%)
- Mean ± Std
- 145. ± 291.
- Median ± IQR
- 50.0 ± 120.
- Min | Max
- 0.00 | 4.20e+03
cash_price7
Float64DType- Null values
- 92,063 (99.2%)
- Unique values
- 179 (0.2%)
- Mean ± Std
- 131. ± 258.
- Median ± IQR
- 45.0 ± 104.
- Min | Max
- 0.00 | 3.00e+03
cash_price8
Float64DType- Null values
- 92,222 (99.4%)
- Unique values
- 177 (0.2%)
- Mean ± Std
- 133. ± 267.
- Median ± IQR
- 45.0 ± 111.
- Min | Max
- 0.00 | 2.40e+03
cash_price9
Float64DType- Null values
- 92,318 (99.5%)
- Unique values
- 147 (0.2%)
- Mean ± Std
- 112. ± 213.
- Median ± IQR
- 40.0 ± 80.0
- Min | Max
- 0.00 | 1.54e+03
cash_price10
Float64DType- Null values
- 92,406 (99.6%)
- Unique values
- 130 (0.1%)
- Mean ± Std
- 112. ± 251.
- Median ± IQR
- 32.0 ± 81.0
- Min | Max
- 0.00 | 3.20e+03
cash_price11
Float64DType- Null values
- 92,468 (99.7%)
- Unique values
- 120 (0.1%)
- Mean ± Std
- 103. ± 220.
- Median ± IQR
- 30.0 ± 67.0
- Min | Max
- 0.00 | 2.16e+03
cash_price12
Float64DType- Null values
- 92,533 (99.7%)
- Unique values
- 102 (0.1%)
- Mean ± Std
- 84.2 ± 141.
- Median ± IQR
- 29.0 ± 77.0
- Min | Max
- 0.00 | 899.
cash_price13
Float64DType- Null values
- 92,571 (99.8%)
- Unique values
- 97 (0.1%)
- Mean ± Std
- 111. ± 200.
- Median ± IQR
- 39.0 ± 95.0
- Min | Max
- 0.00 | 1.30e+03
cash_price14
Float64DType- Null values
- 92,597 (99.8%)
- Unique values
- 82 (< 0.1%)
- Mean ± Std
- 72.4 ± 106.
- Median ± IQR
- 35.0 ± 59.0
- Min | Max
- 0.00 | 599.
cash_price15
Float64DType- Null values
- 92,625 (99.8%)
- Unique values
- 72 (< 0.1%)
- Mean ± Std
- 98.2 ± 228.
- Median ± IQR
- 35.0 ± 64.0
- Min | Max
- 0.00 | 1.60e+03
cash_price16
Float64DType- Null values
- 92,648 (99.8%)
- Unique values
- 71 (< 0.1%)
- Mean ± Std
- 89.0 ± 177.
- Median ± IQR
- 30.0 ± 76.0
- Min | Max
- 0.00 | 1.55e+03
cash_price17
Float64DType- Null values
- 92,670 (99.9%)
- Unique values
- 67 (< 0.1%)
- Mean ± Std
- 84.0 ± 134.
- Median ± IQR
- 25.0 ± 84.0
- Min | Max
- 0.00 | 799.
cash_price18
Float64DType- Null values
- 92,687 (99.9%)
- Unique values
- 67 (< 0.1%)
- Mean ± Std
- 88.2 ± 142.
- Median ± IQR
- 36.0 ± 77.0
- Min | Max
- 0.00 | 999.
cash_price19
Float64DType- Null values
- 92,699 (99.9%)
- Unique values
- 50 (< 0.1%)
- Mean ± Std
- 79.6 ± 223.
- Median ± IQR
- 26.0 ± 42.0
- Min | Max
- 0.00 | 2.01e+03
cash_price20
Float64DType- Null values
- 92,713 (99.9%)
- Unique values
- 43 (< 0.1%)
- Mean ± Std
- 58.2 ± 88.8
- Median ± IQR
- 25.0 ± 45.0
- Min | Max
- 4.00 | 450.
cash_price21
Float64DType- Null values
- 92,727 (99.9%)
- Unique values
- 42 (< 0.1%)
- Mean ± Std
- 126. ± 342.
- Median ± IQR
- 28.0 ± 57.0
- Min | Max
- 0.00 | 2.09e+03
cash_price22
Float64DType- Null values
- 92,740 (99.9%)
- Unique values
- 41 (< 0.1%)
- Mean ± Std
- 109. ± 199.
- Median ± IQR
- 35.0 ± 78.0
- Min | Max
- 0.00 | 995.
cash_price23
Float64DType- Null values
- 92,747 (100.0%)
- Unique values
- 31 (< 0.1%)
- Mean ± Std
- 122. ± 264.
- Median ± IQR
- 20.0 ± 66.0
- Min | Max
- 4.00 | 1.04e+03
make0
ObjectDType- Null values
- 685 (0.7%)
- Unique values
- 425 (0.5%)
make1
ObjectDType- Null values
- 48,461 (52.2%)
- Unique values
- 416 (0.4%)
make2
ObjectDType- Null values
- 79,999 (86.2%)
- Unique values
- 357 (0.4%)
make3
ObjectDType- Null values
- 88,262 (95.1%)
- Unique values
- 308 (0.3%)
make4
ObjectDType- Null values
- 90,639 (97.7%)
- Unique values
- 265 (0.3%)
make5
ObjectDType- Null values
- 91,467 (98.6%)
- Unique values
- 205 (0.2%)
make6
ObjectDType- Null values
- 91,854 (99.0%)
- Unique values
- 186 (0.2%)
make7
ObjectDType- Null values
- 92,073 (99.2%)
- Unique values
- 165 (0.2%)
make8
ObjectDType- Null values
- 92,232 (99.4%)
- Unique values
- 142 (0.2%)
make9
ObjectDType- Null values
- 92,328 (99.5%)
- Unique values
- 126 (0.1%)
make10
ObjectDType- Null values
- 92,414 (99.6%)
- Unique values
- 107 (0.1%)
make11
ObjectDType- Null values
- 92,476 (99.7%)
- Unique values
- 100 (0.1%)
make12
ObjectDType- Null values
- 92,540 (99.7%)
- Unique values
- 81 (< 0.1%)
make13
ObjectDType- Null values
- 92,576 (99.8%)
- Unique values
- 73 (< 0.1%)
make14
ObjectDType- Null values
- 92,602 (99.8%)
- Unique values
- 69 (< 0.1%)
make15
ObjectDType- Null values
- 92,628 (99.8%)
- Unique values
- 61 (< 0.1%)
make16
ObjectDType- Null values
- 92,651 (99.9%)
- Unique values
- 49 (< 0.1%)
make17
ObjectDType- Null values
- 92,671 (99.9%)
- Unique values
- 42 (< 0.1%)
make18
ObjectDType- Null values
- 92,688 (99.9%)
- Unique values
- 44 (< 0.1%)
make19
ObjectDType- Null values
- 92,700 (99.9%)
- Unique values
- 37 (< 0.1%)
make20
ObjectDType- Null values
- 92,714 (99.9%)
- Unique values
- 30 (< 0.1%)
make21
ObjectDType- Null values
- 92,728 (99.9%)
- Unique values
- 23 (< 0.1%)
make22
ObjectDType- Null values
- 92,741 (99.9%)
- Unique values
- 25 (< 0.1%)
make23
ObjectDType- Null values
- 92,747 (100.0%)
- Unique values
- 19 (< 0.1%)
model0
ObjectDType- Null values
- 685 (0.7%)
- Unique values
- 3,782 (4.1%)
model1
ObjectDType- Null values
- 48,461 (52.2%)
- Unique values
- 3,242 (3.5%)
model2
ObjectDType- Null values
- 79,999 (86.2%)
- Unique values
- 2,344 (2.5%)
model3
ObjectDType- Null values
- 88,262 (95.1%)
- Unique values
- 1,611 (1.7%)
model4
ObjectDType- Null values
- 90,639 (97.7%)
- Unique values
- 1,093 (1.2%)
model5
ObjectDType- Null values
- 91,467 (98.6%)
- Unique values
- 756 (0.8%)
model6
ObjectDType- Null values
- 91,854 (99.0%)
- Unique values
- 601 (0.6%)
model7
ObjectDType- Null values
- 92,073 (99.2%)
- Unique values
- 472 (0.5%)
model8
ObjectDType- Null values
- 92,232 (99.4%)
- Unique values
- 377 (0.4%)
model9
ObjectDType- Null values
- 92,328 (99.5%)
- Unique values
- 333 (0.4%)
model10
ObjectDType- Null values
- 92,414 (99.6%)
- Unique values
- 265 (0.3%)
model11
ObjectDType- Null values
- 92,476 (99.7%)
- Unique values
- 219 (0.2%)
model12
ObjectDType- Null values
- 92,540 (99.7%)
- Unique values
- 179 (0.2%)
model13
ObjectDType- Null values
- 92,576 (99.8%)
- Unique values
- 154 (0.2%)
model14
ObjectDType- Null values
- 92,602 (99.8%)
- Unique values
- 139 (0.1%)
model15
ObjectDType- Null values
- 92,628 (99.8%)
- Unique values
- 123 (0.1%)
model16
ObjectDType- Null values
- 92,651 (99.9%)
- Unique values
- 106 (0.1%)
model17
ObjectDType- Null values
- 92,671 (99.9%)
- Unique values
- 87 (< 0.1%)
model18
ObjectDType- Null values
- 92,688 (99.9%)
- Unique values
- 81 (< 0.1%)
model19
ObjectDType- Null values
- 92,700 (99.9%)
- Unique values
- 75 (< 0.1%)
model20
ObjectDType- Null values
- 92,714 (99.9%)
- Unique values
- 63 (< 0.1%)
model21
ObjectDType- Null values
- 92,728 (99.9%)
- Unique values
- 55 (< 0.1%)
model22
ObjectDType- Null values
- 92,741 (99.9%)
- Unique values
- 45 (< 0.1%)
model23
ObjectDType- Null values
- 92,747 (100.0%)
- Unique values
- 42 (< 0.1%)
goods_code0
ObjectDType- Null values
- 0 (0.0%)
- Unique values
- 5,966 (6.4%)
goods_code1
ObjectDType- Null values
- 48,134 (51.9%)
- Unique values
- 4,728 (5.1%)
goods_code2
ObjectDType- Null values
- 79,889 (86.1%)
- Unique values
- 3,237 (3.5%)
goods_code3
ObjectDType- Null values
- 88,228 (95.1%)
- Unique values
- 2,118 (2.3%)
goods_code4
ObjectDType- Null values
- 90,620 (97.7%)
- Unique values
- 1,480 (1.6%)
goods_code5
ObjectDType- Null values
- 91,454 (98.6%)
- Unique values
- 1,006 (1.1%)
goods_code6
ObjectDType- Null values
- 91,844 (99.0%)
- Unique values
- 805 (0.9%)
goods_code7
ObjectDType- Null values
- 92,063 (99.2%)
- Unique values
- 628 (0.7%)
goods_code8
ObjectDType- Null values
- 92,222 (99.4%)
- Unique values
- 514 (0.6%)
goods_code9
ObjectDType- Null values
- 92,318 (99.5%)
- Unique values
- 426 (0.5%)
goods_code10
ObjectDType- Null values
- 92,406 (99.6%)
- Unique values
- 350 (0.4%)
goods_code11
ObjectDType- Null values
- 92,468 (99.7%)
- Unique values
- 282 (0.3%)
goods_code12
ObjectDType- Null values
- 92,533 (99.7%)
- Unique values
- 238 (0.3%)
goods_code13
ObjectDType- Null values
- 92,571 (99.8%)
- Unique values
- 205 (0.2%)
goods_code14
ObjectDType- Null values
- 92,597 (99.8%)
- Unique values
- 179 (0.2%)
goods_code15
ObjectDType- Null values
- 92,625 (99.8%)
- Unique values
- 156 (0.2%)
goods_code16
ObjectDType- Null values
- 92,648 (99.8%)
- Unique values
- 131 (0.1%)
goods_code17
ObjectDType- Null values
- 92,670 (99.9%)
- Unique values
- 109 (0.1%)
goods_code18
ObjectDType- Null values
- 92,687 (99.9%)
- Unique values
- 96 (0.1%)
goods_code19
ObjectDType- Null values
- 92,699 (99.9%)
- Unique values
- 85 (< 0.1%)
goods_code20
ObjectDType- Null values
- 92,713 (99.9%)
- Unique values
- 71 (< 0.1%)
goods_code21
ObjectDType- Null values
- 92,727 (99.9%)
- Unique values
- 59 (< 0.1%)
goods_code22
ObjectDType- Null values
- 92,740 (99.9%)
- Unique values
- 46 (< 0.1%)
goods_code23
ObjectDType- Null values
- 92,747 (100.0%)
- Unique values
- 42 (< 0.1%)
Nbr_of_prod_purchas0
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 16 (< 0.1%)
- Mean ± Std
- 1.03 ± 0.351
- Median ± IQR
- 1 ± 0
- Min | Max
- 1 | 40
Nbr_of_prod_purchas1
Float64DType- Null values
- 48,134 (51.9%)
- Unique values
- 13 (< 0.1%)
- Mean ± Std
- 1.04 ± 0.300
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 18.0
Nbr_of_prod_purchas2
Float64DType- Null values
- 79,889 (86.1%)
- Unique values
- 12 (< 0.1%)
- Mean ± Std
- 1.08 ± 0.464
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 16.0
Nbr_of_prod_purchas3
Float64DType- Null values
- 88,228 (95.1%)
- Unique values
- 14 (< 0.1%)
- Mean ± Std
- 1.15 ± 0.795
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 28.0
Nbr_of_prod_purchas4
Float64DType- Null values
- 90,620 (97.7%)
- Unique values
- 10 (< 0.1%)
- Mean ± Std
- 1.23 ± 0.824
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 15.0
Nbr_of_prod_purchas5
Float64DType- Null values
- 91,454 (98.6%)
- Unique values
- 9 (< 0.1%)
- Mean ± Std
- 1.26 ± 0.978
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 24.0
Nbr_of_prod_purchas6
Float64DType- Null values
- 91,844 (99.0%)
- Unique values
- 10 (< 0.1%)
- Mean ± Std
- 1.29 ± 0.905
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 16.0
Nbr_of_prod_purchas7
Float64DType- Null values
- 92,063 (99.2%)
- Unique values
- 10 (< 0.1%)
- Mean ± Std
- 1.33 ± 1.05
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 14.0
Nbr_of_prod_purchas8
Float64DType- Null values
- 92,222 (99.4%)
- Unique values
- 11 (< 0.1%)
- Mean ± Std
- 1.41 ± 1.27
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 18.0
Nbr_of_prod_purchas9
Float64DType- Null values
- 92,318 (99.5%)
- Unique values
- 7 (< 0.1%)
- Mean ± Std
- 1.36 ± 0.948
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 8.00
Nbr_of_prod_purchas10
Float64DType- Null values
- 92,406 (99.6%)
- Unique values
- 9 (< 0.1%)
- Mean ± Std
- 1.37 ± 1.11
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 12.0
Nbr_of_prod_purchas11
Float64DType- Null values
- 92,468 (99.7%)
- Unique values
- 7 (< 0.1%)
- Mean ± Std
- 1.32 ± 0.897
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 7.00
Nbr_of_prod_purchas12
Float64DType- Null values
- 92,533 (99.7%)
- Unique values
- 6 (< 0.1%)
- Mean ± Std
- 1.26 ± 0.823
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 10.0
Nbr_of_prod_purchas13
Float64DType- Null values
- 92,571 (99.8%)
- Unique values
- 6 (< 0.1%)
- Mean ± Std
- 1.36 ± 1.04
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 12.0
Nbr_of_prod_purchas14
Float64DType- Null values
- 92,597 (99.8%)
- Unique values
- 6 (< 0.1%)
- Mean ± Std
- 1.35 ± 0.951
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 6.00
Nbr_of_prod_purchas15
Float64DType- Null values
- 92,625 (99.8%)
- Unique values
- 6 (< 0.1%)
- Mean ± Std
- 1.29 ± 0.749
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 6.00
Nbr_of_prod_purchas16
Float64DType- Null values
- 92,648 (99.8%)
- Unique values
- 5 (< 0.1%)
- Mean ± Std
- 1.44 ± 1.43
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 12.0
Nbr_of_prod_purchas17
Float64DType- Null values
- 92,670 (99.9%)
- Unique values
- 7 (< 0.1%)
- Mean ± Std
- 1.47 ± 1.81
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 16.0
Nbr_of_prod_purchas18
Float64DType- Null values
- 92,687 (99.9%)
- Unique values
- 7 (< 0.1%)
- Mean ± Std
- 1.39 ± 1.17
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 7.00
Nbr_of_prod_purchas19
Float64DType- Null values
- 92,699 (99.9%)
- Unique values
- 5 (< 0.1%)
- Mean ± Std
- 1.33 ± 0.870
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 7.00
Nbr_of_prod_purchas20
Float64DType- Null values
- 92,713 (99.9%)
- Unique values
- 4 (< 0.1%)
- Mean ± Std
- 1.22 ± 0.529
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 4.00
Nbr_of_prod_purchas21
Float64DType- Null values
- 92,727 (99.9%)
- Unique values
- 5 (< 0.1%)
- Mean ± Std
- 1.38 ± 0.923
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 7.00
Nbr_of_prod_purchas22
Float64DType- Null values
- 92,740 (99.9%)
- Unique values
- 4 (< 0.1%)
- Mean ± Std
- 1.16 ± 0.548
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 4.00
Nbr_of_prod_purchas23
Float64DType- Null values
- 92,747 (100.0%)
- Unique values
- 3 (< 0.1%)
- Mean ± Std
- 1.37 ± 1.11
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 8.00
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
Column 1 | Column 2 | Cramér's V | Pearson's Correlation |
---|---|---|---|
item10 | item12 | 1.00 | |
item10 | item11 | 1.00 | |
Nbr_of_prod_purchas13 | Nbr_of_prod_purchas14 | 1.00 | 1.00 |
item10 | make14 | 1.00 | |
item10 | make12 | 1.00 | |
item10 | make11 | 1.00 | |
item10 | goods_code10 | 1.00 | |
item11 | item12 | 1.00 | |
item11 | cash_price11 | 1.00 | |
item11 | make12 | 1.00 | |
item11 | make11 | 1.00 | |
item11 | make14 | 1.00 | |
item11 | goods_code11 | 1.00 | |
item11 | goods_code10 | 1.00 | |
item12 | item14 | 1.00 | |
item12 | cash_price14 | 1.00 | |
item12 | cash_price13 | 1.00 | |
item12 | cash_price11 | 1.00 | |
item12 | make14 | 1.00 | |
item12 | make12 | 1.00 |
Please enable javascript
The skrub table reports need javascript to display correctly. If you are displaying a report in a Jupyter notebook and you see this message, you may need to re-execute the cell or to trust the notebook (button on the top right or "File > Trust notebook").
Look at the “Stats” section of the TableReport
above. Does anything strike you?
Not only did we create 144 columns, but most of these columns are filled with NaN, which is very inefficient for learning!
This is because each basket contains a variable number of products, up to 24, and we created one column for each product attribute, for each position (up to 24) in the dataframe.
Moreover, if we wanted to replace text columns with encodings, we would create
\(d \times 24 \times 2\) columns (encoding of dimensionality \(d\), for
24 products, for the "item"
and "make"
columns), which would explode the
memory usage.
AggJoiner#
Let’s now see how the AggJoiner
can help us solve this. We begin with splitting our
basket dataset in a training and testing set.
from sklearn.model_selection import train_test_split
X, y = baskets[["ID"]], baskets["fraud_flag"]
X_train, X_test, y_train, y_test = train_test_split(X, y, stratify=y, test_size=0.1)
X_train.shape, y_train.shape
((83511, 1), (83511,))
Before aggregating our product dataframe, we need to vectorize our categorical columns. To do so, we use:
MinHashEncoder
on “item” and “model” columns, because they both expose typos and text similarities.OrdinalEncoder
on “make” and “goods_code” columns, because they consist in orthogonal categories.
We bring this logic into a TableVectorizer
to vectorize these columns in a
single step.
See this example
for more details about these encoding choices.
from sklearn.preprocessing import OrdinalEncoder
from skrub import MinHashEncoder, TableVectorizer
vectorizer = TableVectorizer(
high_cardinality=MinHashEncoder(), # encode ["item", "model"]
specific_transformers=[
(OrdinalEncoder(), ["make", "goods_code"]),
],
)
products_transformed = vectorizer.fit_transform(products)
TableReport(products_transformed)
basket_ID | item_00 | item_01 | item_02 | item_03 | item_04 | item_05 | item_06 | item_07 | item_08 | item_09 | item_10 | item_11 | item_12 | item_13 | item_14 | item_15 | item_16 | item_17 | item_18 | item_19 | item_20 | item_21 | item_22 | item_23 | item_24 | item_25 | item_26 | item_27 | item_28 | item_29 | cash_price | make | model_00 | model_01 | model_02 | model_03 | model_04 | model_05 | model_06 | model_07 | model_08 | model_09 | model_10 | model_11 | model_12 | model_13 | model_14 | model_15 | model_16 | model_17 | model_18 | model_19 | model_20 | model_21 | model_22 | model_23 | model_24 | model_25 | model_26 | model_27 | model_28 | model_29 | goods_code | Nbr_of_prod_purchas | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 85517.0 | -2119082112.0 | -1621485056.0 | -1795710976.0 | -2069712512.0 | -2053898240.0 | -2061027200.0 | -1407719040.0 | -2003757696.0 | -1860201856.0 | -2064848000.0 | -1952196096.0 | -2143475584.0 | -1984537216.0 | -2097144064.0 | -1901156992.0 | -1890843008.0 | -2073910784.0 | -2043068544.0 | -1962807680.0 | -2026307840.0 | -2103297024.0 | -2053113984.0 | -2063595136.0 | -2083497856.0 | -2092638208.0 | -1687056128.0 | -1841633408.0 | -2118906752.0 | -2124841088.0 | -1926313216.0 | 889.0 | 30.0 | -2070114816.0 | -2140802048.0 | -2128763520.0 | -2114467200.0 | -2098292864.0 | -2101188736.0 | -2080134784.0 | -2123221504.0 | -2071984128.0 | -2089785728.0 | -2082095616.0 | -2065732480.0 | -2047006848.0 | -2096223104.0 | -2101725056.0 | -2028907008.0 | -2052252160.0 | -2127037184.0 | -2064700672.0 | -2141094144.0 | -2137696128.0 | -2143421952.0 | -2098587008.0 | -2146054400.0 | -2135834880.0 | -2113379200.0 | -2044705920.0 | -2053709824.0 | -2147119104.0 | -2110975872.0 | 11181.0 | 1.0 |
1 | 51113.0 | -2119082112.0 | -2092437504.0 | -2091895296.0 | -2096070400.0 | -2053898240.0 | -2069353216.0 | -2075299584.0 | -2009485056.0 | -2071984128.0 | -2089785728.0 | -2082897536.0 | -2143475584.0 | -2057488000.0 | -2097144064.0 | -2086916736.0 | -2124873472.0 | -2109534080.0 | -2043068544.0 | -2135823616.0 | -2132238720.0 | -2114070144.0 | -2143421952.0 | -2063595136.0 | -2083497856.0 | -2143897856.0 | -2021854080.0 | -1841633408.0 | -2118906752.0 | -2124841088.0 | -2115769728.0 | 409.0 | 30.0 | -2086969984.0 | -2140802048.0 | -2120533120.0 | -2123470592.0 | -2044521856.0 | -2138671360.0 | -2139137024.0 | -2121052800.0 | -2071984128.0 | -2070443776.0 | -2082769664.0 | -2129256192.0 | -2134113920.0 | -2114362496.0 | -2128111232.0 | -2143113472.0 | -2101461632.0 | -2138302592.0 | -2047586432.0 | -2137376000.0 | -2114070144.0 | -2085245184.0 | -2113314816.0 | -2087341184.0 | -2065861248.0 | -2100475776.0 | -2072272384.0 | -2114559744.0 | -2125133952.0 | -1987577088.0 | 10552.0 | 1.0 |
2 | 83008.0 | -2128259840.0 | -2095576448.0 | -2144445696.0 | -2020459392.0 | -2057084800.0 | -1876818048.0 | -2121499136.0 | -2114278400.0 | -2085140224.0 | -2064848000.0 | -2063490048.0 | -2143475584.0 | -2124267776.0 | -2096223104.0 | -1994766720.0 | -2008991360.0 | -2013149184.0 | -2127037184.0 | -2023255296.0 | -2128494592.0 | -2072412416.0 | -2141099136.0 | -2063595136.0 | -2134392832.0 | -2095952128.0 | -2111947648.0 | -2146418048.0 | -1724371712.0 | -2142947968.0 | -2066046208.0 | 1399.0 | 633.0 | -2140403968.0 | -2092437504.0 | -1949062784.0 | -2128161920.0 | -2145696768.0 | -2119088768.0 | -2138769792.0 | -2087540096.0 | -2124020992.0 | -2133883648.0 | -2129010944.0 | -2119972352.0 | -2075782528.0 | -2096223104.0 | -2140701696.0 | -2142510208.0 | -1969872000.0 | -2127037184.0 | -2053575552.0 | -2140361472.0 | -1990730368.0 | -2049603072.0 | -2092721792.0 | -2109808896.0 | -2135747968.0 | -2130675712.0 | -2106766080.0 | -2112450432.0 | -2071285888.0 | -2118983168.0 | 12038.0 | 1.0 |
3 | 78712.0 | -2119082112.0 | -1621485056.0 | -1795710976.0 | -2069712512.0 | -2053898240.0 | -2061027200.0 | -1407719040.0 | -2003757696.0 | -1860201856.0 | -2064848000.0 | -1952196096.0 | -2143475584.0 | -1984537216.0 | -2097144064.0 | -1901156992.0 | -1890843008.0 | -2073910784.0 | -2043068544.0 | -1962807680.0 | -2026307840.0 | -2103297024.0 | -2053113984.0 | -2063595136.0 | -2083497856.0 | -2092638208.0 | -1687056128.0 | -1841633408.0 | -2118906752.0 | -2124841088.0 | -1926313216.0 | 689.0 | 30.0 | -2107412224.0 | -2142073600.0 | -2128763520.0 | -2114467200.0 | -2101596928.0 | -2069353216.0 | -2084104064.0 | -2108259072.0 | -2125949440.0 | -2136905088.0 | -2081278208.0 | -2111496832.0 | -2124267776.0 | -2096223104.0 | -2100255360.0 | -2028907008.0 | -2063535744.0 | -2120063360.0 | -2115619584.0 | -2141094144.0 | -2098944768.0 | -2143421952.0 | -2140212608.0 | -1995871488.0 | -2135834880.0 | -2111947648.0 | -2136661760.0 | -2123857024.0 | -2144492544.0 | -2066046208.0 | 10513.0 | 1.0 |
4 | 78712.0 | -2119082112.0 | -2092437504.0 | -2091895296.0 | -2096070400.0 | -2053898240.0 | -2069353216.0 | -2075299584.0 | -2009485056.0 | -2071984128.0 | -2089785728.0 | -2082897536.0 | -2143475584.0 | -2057488000.0 | -2097144064.0 | -2086916736.0 | -2124873472.0 | -2109534080.0 | -2043068544.0 | -2135823616.0 | -2132238720.0 | -2114070144.0 | -2143421952.0 | -2063595136.0 | -2083497856.0 | -2143897856.0 | -2021854080.0 | -1841633408.0 | -2118906752.0 | -2124841088.0 | -2115769728.0 | 119.0 | 30.0 | -2123276160.0 | -2096499328.0 | -2120533120.0 | -2107973376.0 | -1991295488.0 | -2097416448.0 | -2139137024.0 | -2123221504.0 | -2124020992.0 | -2141934976.0 | -2094848640.0 | -2094566016.0 | -2124267776.0 | -2114362496.0 | -2100255360.0 | -2086078848.0 | -2056125312.0 | -2127037184.0 | -2064700672.0 | -2128494592.0 | -2137696128.0 | -2143421952.0 | -1873599616.0 | -2134392832.0 | -2065861248.0 | -2111947648.0 | -2106766080.0 | -2136393856.0 | -2044628224.0 | -2138674816.0 | 4925.0 | 1.0 |
163352 | 42613.0 | -1944860928.0 | -2140802048.0 | -2042012544.0 | -1952299136.0 | -1956562944.0 | -2115316480.0 | -1994253056.0 | -2003757696.0 | -2051230592.0 | -2128871936.0 | -1990878976.0 | -2143475584.0 | -1984537216.0 | -2073099648.0 | -1961043200.0 | -2101944064.0 | -2002543232.0 | -1877808256.0 | -1956121088.0 | -2140361472.0 | -2062128512.0 | -2112148992.0 | -2106278912.0 | -1786246784.0 | -2092638208.0 | -2135700096.0 | -2023483264.0 | -1849929088.0 | -1864043904.0 | -2078980864.0 | 259.0 | 658.0 | -1989880960.0 | -2018200832.0 | -1986772608.0 | -2121657216.0 | -1993879936.0 | -2101188736.0 | -2131974784.0 | -1985121152.0 | -2075421312.0 | -2106573056.0 | -2094848640.0 | -2094566016.0 | -2134113920.0 | -2124304256.0 | -2140701696.0 | -2137089792.0 | -2078441984.0 | -2145952512.0 | -2076997632.0 | -2121964032.0 | -1972271360.0 | -2141144576.0 | -2126553728.0 | -2146054400.0 | -2140792960.0 | -2088835584.0 | -2120271616.0 | -2146970240.0 | -2139479040.0 | -1972564480.0 | 2807.0 | 1.0 |
163353 | 42613.0 | -1944860928.0 | -2140802048.0 | -1811393152.0 | -2061610752.0 | -1956562944.0 | -2115316480.0 | -2002457600.0 | -2009485056.0 | -1993391616.0 | -2128871936.0 | -1990878976.0 | -2053293056.0 | -1834136064.0 | -1876119680.0 | -1613908224.0 | -2101944064.0 | -1430106496.0 | -2022489728.0 | -1986229760.0 | -2132238720.0 | -1876001536.0 | -2112148992.0 | -2106278912.0 | -1997466752.0 | -2025872896.0 | -2135700096.0 | -2023483264.0 | -2146970240.0 | -2009022592.0 | -2078980864.0 | 949.0 | 412.0 | -2144654336.0 | -2140802048.0 | -2120533120.0 | -2140173568.0 | -2059119744.0 | -2100804096.0 | -2097867008.0 | -2087686016.0 | -2124020992.0 | -2091307392.0 | -2119114880.0 | -2119972352.0 | -2085467136.0 | -2114362496.0 | -2140701696.0 | -2134924800.0 | -2059552384.0 | -2100255872.0 | -2051555584.0 | -2132238720.0 | -2044759680.0 | -2107845760.0 | -2098688896.0 | -2053801600.0 | -2128403712.0 | -2040432896.0 | -2106766080.0 | -2146970240.0 | -2092956800.0 | -2128906368.0 | 11464.0 | 1.0 |
163354 | 43567.0 | -2119082112.0 | -1621485056.0 | -1795710976.0 | -2069712512.0 | -2053898240.0 | -2061027200.0 | -1407719040.0 | -2003757696.0 | -1860201856.0 | -2064848000.0 | -1952196096.0 | -2143475584.0 | -1984537216.0 | -2097144064.0 | -1901156992.0 | -1890843008.0 | -2073910784.0 | -2043068544.0 | -1962807680.0 | -2026307840.0 | -2103297024.0 | -2053113984.0 | -2063595136.0 | -2083497856.0 | -2092638208.0 | -1687056128.0 | -1841633408.0 | -2118906752.0 | -2124841088.0 | -1926313216.0 | 1099.0 | 30.0 | -2123882240.0 | -2116824448.0 | -2120533120.0 | -2124229120.0 | -2113986816.0 | -2097663616.0 | -2139137024.0 | -2087540096.0 | -2124020992.0 | -2112236160.0 | -2097948544.0 | -2065732480.0 | -2124267776.0 | -2096223104.0 | -2100255360.0 | -2028907008.0 | -2141608832.0 | -2069449344.0 | -2039003264.0 | -2141094144.0 | -2098944768.0 | -2143421952.0 | -2046004608.0 | -1995871488.0 | -2065861248.0 | -2111947648.0 | -2106766080.0 | -2141457664.0 | -2139479040.0 | -2066606080.0 | 13080.0 | 1.0 |
163355 | 43567.0 | -2119082112.0 | -1621485056.0 | -1795710976.0 | -2069712512.0 | -2053898240.0 | -2061027200.0 | -1407719040.0 | -2003757696.0 | -1860201856.0 | -2064848000.0 | -1952196096.0 | -2143475584.0 | -1984537216.0 | -2097144064.0 | -1901156992.0 | -1890843008.0 | -2073910784.0 | -2043068544.0 | -1962807680.0 | -2026307840.0 | -2103297024.0 | -2053113984.0 | -2063595136.0 | -2083497856.0 | -2092638208.0 | -1687056128.0 | -1841633408.0 | -2118906752.0 | -2124841088.0 | -1926313216.0 | 2099.0 | 30.0 | -2119082112.0 | -2140802048.0 | -2144499584.0 | -2044493056.0 | -2119447424.0 | -2100804096.0 | -2122059776.0 | -2019972352.0 | -2124020992.0 | -2142483712.0 | -2065907072.0 | -2111503488.0 | -2116008832.0 | -2126917376.0 | -2131770240.0 | -2124873472.0 | -2044098560.0 | -2127037184.0 | -2115619584.0 | -2141094144.0 | -2103297024.0 | -2075032192.0 | -2021440512.0 | -2087341184.0 | -2136538112.0 | -2100475776.0 | -2106766080.0 | -2125088256.0 | -2050167424.0 | -2096222464.0 | 9971.0 | 1.0 |
163356 | 68268.0 | -2128259840.0 | -2095576448.0 | -2144445696.0 | -2020459392.0 | -2057084800.0 | -1876818048.0 | -2121499136.0 | -2114278400.0 | -2085140224.0 | -2064848000.0 | -2063490048.0 | -2143475584.0 | -2124267776.0 | -2096223104.0 | -1994766720.0 | -2008991360.0 | -2013149184.0 | -2127037184.0 | -2023255296.0 | -2128494592.0 | -2072412416.0 | -2141099136.0 | -2063595136.0 | -2134392832.0 | -2095952128.0 | -2111947648.0 | -2146418048.0 | -1724371712.0 | -2142947968.0 | -2066046208.0 | 799.0 | 411.0 | -2140403968.0 | -2092437504.0 | -2072778240.0 | -2124229120.0 | -2111208576.0 | -2119088768.0 | -2138769792.0 | -2087540096.0 | -2124020992.0 | -2133883648.0 | -2129010944.0 | -2139309824.0 | -2075782528.0 | -2096223104.0 | -2140701696.0 | -2134924800.0 | -2061275392.0 | -2138311808.0 | -2053575552.0 | -2140361472.0 | -1863376000.0 | -2049603072.0 | -2092721792.0 | -2109808896.0 | -2135747968.0 | -2135416576.0 | -2106766080.0 | -2103071232.0 | -2036068224.0 | -2138224128.0 | 12106.0 | 1.0 |
basket_ID
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 92,790 (56.8%)
- Mean ± Std
- 5.59e+04 ± 3.46e+04
- Median ± IQR
- 5.47e+04 ± 6.13e+04
- Min | Max
- 0.00 | 1.16e+05
item_00
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 73 (< 0.1%)
- Mean ± Std
- -2.03e+09 ± 1.55e+08
- Median ± IQR
- -2.12e+09 ± 1.82e+08
- Min | Max
- -2.15e+09 | -1.03e+09
item_01
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 47 (< 0.1%)
- Mean ± Std
- -1.91e+09 ± 2.66e+08
- Median ± IQR
- -2.06e+09 ± 4.74e+08
- Min | Max
- -2.14e+09 | -1.09e+09
item_02
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 59 (< 0.1%)
- Mean ± Std
- -1.98e+09 ± 1.84e+08
- Median ± IQR
- -2.09e+09 ± 3.25e+08
- Min | Max
- -2.14e+09 | -3.95e+08
item_03
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 55 (< 0.1%)
- Mean ± Std
- -2.06e+09 ± 8.12e+07
- Median ± IQR
- -2.07e+09 ± 4.98e+07
- Min | Max
- -2.15e+09 | -8.27e+08
item_04
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 64 (< 0.1%)
- Mean ± Std
- -2.02e+09 ± 6.44e+07
- Median ± IQR
- -2.05e+09 ± 8.00e+07
- Min | Max
- -2.15e+09 | -1.08e+09
item_05
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 62 (< 0.1%)
- Mean ± Std
- -1.99e+09 ± 2.15e+08
- Median ± IQR
- -2.06e+09 ± 2.47e+07
- Min | Max
- -2.14e+09 | -8.93e+08
item_06
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 70 (< 0.1%)
- Mean ± Std
- -1.76e+09 ± 3.83e+08
- Median ± IQR
- -1.99e+09 ± 6.68e+08
- Min | Max
- -2.14e+09 | -9.01e+07
item_07
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 62 (< 0.1%)
- Mean ± Std
- -1.97e+09 ± 1.41e+08
- Median ± IQR
- -2.00e+09 ± 7.90e+07
- Min | Max
- -2.14e+09 | -1.20e+09
item_08
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 65 (< 0.1%)
- Mean ± Std
- -1.98e+09 ± 1.06e+08
- Median ± IQR
- -2.02e+09 ± 2.12e+08
- Min | Max
- -2.15e+09 | -9.20e+08
item_09
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 67 (< 0.1%)
- Mean ± Std
- -2.01e+09 ± 2.29e+08
- Median ± IQR
- -2.06e+09 ± 8.91e+07
- Min | Max
- -2.14e+09 | 7.04e+08
item_10
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 61 (< 0.1%)
- Mean ± Std
- -2.02e+09 ± 7.99e+07
- Median ± IQR
- -2.04e+09 ± 1.31e+08
- Min | Max
- -2.14e+09 | 2.67e+07
item_11
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 59 (< 0.1%)
- Mean ± Std
- -2.10e+09 ± 1.06e+08
- Median ± IQR
- -2.14e+09 ± 4.89e+07
- Min | Max
- -2.14e+09 | -5.71e+08
item_12
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 59 (< 0.1%)
- Mean ± Std
- -2.04e+09 ± 8.53e+07
- Median ± IQR
- -2.06e+09 ± 1.31e+08
- Min | Max
- -2.14e+09 | -1.05e+09
item_13
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 58 (< 0.1%)
- Mean ± Std
- -2.04e+09 ± 1.49e+08
- Median ± IQR
- -2.10e+09 ± 9.61e+07
- Min | Max
- -2.15e+09 | -1.14e+09
item_14
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 61 (< 0.1%)
- Mean ± Std
- -1.98e+09 ± 1.51e+08
- Median ± IQR
- -1.99e+09 ± 2.24e+08
- Min | Max
- -2.15e+09 | -5.50e+08
item_15
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 63 (< 0.1%)
- Mean ± Std
- -1.99e+09 ± 1.23e+08
- Median ± IQR
- -2.01e+09 ± 2.11e+08
- Min | Max
- -2.15e+09 | -8.00e+08
item_16
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 68 (< 0.1%)
- Mean ± Std
- -2.03e+09 ± 1.06e+08
- Median ± IQR
- -2.06e+09 ± 5.51e+07
- Min | Max
- -2.15e+09 | -6.04e+08
item_17
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 56 (< 0.1%)
- Mean ± Std
- -2.04e+09 ± 9.05e+07
- Median ± IQR
- -2.04e+09 ± 8.40e+07
- Min | Max
- -2.15e+09 | -1.13e+09
item_18
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 70 (< 0.1%)
- Mean ± Std
- -2.00e+09 ± 8.97e+07
- Median ± IQR
- -1.96e+09 ± 1.24e+08
- Min | Max
- -2.14e+09 | -9.75e+08
item_19
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 51 (< 0.1%)
- Mean ± Std
- -2.06e+09 ± 1.03e+08
- Median ± IQR
- -2.08e+09 ± 1.06e+08
- Min | Max
- -2.15e+09 | -5.72e+08
item_20
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 58 (< 0.1%)
- Mean ± Std
- -2.01e+09 ± 3.00e+08
- Median ± IQR
- -2.10e+09 ± 4.17e+07
- Min | Max
- -2.14e+09 | -5.10e+06
item_21
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 66 (< 0.1%)
- Mean ± Std
- -2.05e+09 ± 1.02e+08
- Median ± IQR
- -2.05e+09 ± 1.18e+08
- Min | Max
- -2.14e+09 | -8.74e+08
item_22
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 57 (< 0.1%)
- Mean ± Std
- -1.99e+09 ± 1.43e+08
- Median ± IQR
- -2.06e+09 ± 2.10e+08
- Min | Max
- -2.14e+09 | -7.91e+08
item_23
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 63 (< 0.1%)
- Mean ± Std
- -2.05e+09 ± 1.32e+08
- Median ± IQR
- -2.08e+09 ± 3.95e+07
- Min | Max
- -2.15e+09 | -7.27e+08
item_24
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 63 (< 0.1%)
- Mean ± Std
- -2.01e+09 ± 1.54e+08
- Median ± IQR
- -2.09e+09 ± 1.82e+08
- Min | Max
- -2.14e+09 | -5.03e+08
item_25
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 68 (< 0.1%)
- Mean ± Std
- -1.90e+09 ± 2.07e+08
- Median ± IQR
- -1.83e+09 ± 4.25e+08
- Min | Max
- -2.14e+09 | -8.07e+08
item_26
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 73 (< 0.1%)
- Mean ± Std
- -1.94e+09 ± 1.31e+08
- Median ± IQR
- -1.84e+09 ± 1.83e+08
- Min | Max
- -2.15e+09 | -1.36e+09
item_27
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 67 (< 0.1%)
- Mean ± Std
- -2.00e+09 ± 1.70e+08
- Median ± IQR
- -2.12e+09 ± 1.69e+08
- Min | Max
- -2.15e+09 | -9.92e+08
item_28
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 76 (< 0.1%)
- Mean ± Std
- -2.05e+09 ± 1.21e+08
- Median ± IQR
- -2.12e+09 ± 1.78e+08
- Min | Max
- -2.15e+09 | -9.07e+08
item_29
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 58 (< 0.1%)
- Mean ± Std
- -1.99e+09 ± 1.22e+08
- Median ± IQR
- -1.97e+09 ± 1.53e+08
- Min | Max
- -2.15e+09 | -1.07e+09
cash_price
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 1,594 (1.0%)
- Mean ± Std
- 701. ± 742.
- Median ± IQR
- 549. ± 1.03e+03
- Min | Max
- 0.00 | 2.20e+04
make
Float64DType- Null values
- 1,273 (0.8%)
- Unique values
- 829 (0.5%)
- Mean ± Std
- 303. ± 281.
- Median ± IQR
- 176. ± 572.
- Min | Max
- 0.00 | 828.
model_00
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 478 (0.3%)
- Mean ± Std
- -1.95e+09 ± 2.69e+08
- Median ± IQR
- -2.07e+09 ± 4.85e+08
- Min | Max
- -2.15e+09 | 0.00
model_01
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 347 (0.2%)
- Mean ± Std
- -2.09e+09 ± 2.04e+08
- Median ± IQR
- -2.14e+09 ± 4.84e+07
- Min | Max
- -2.15e+09 | 0.00
model_02
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 337 (0.2%)
- Mean ± Std
- -2.07e+09 ± 1.93e+08
- Median ± IQR
- -2.12e+09 ± 1.19e+08
- Min | Max
- -2.15e+09 | 4.22e+07
model_03
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 341 (0.2%)
- Mean ± Std
- -2.05e+09 ± 1.98e+08
- Median ± IQR
- -2.11e+09 ± 1.72e+08
- Min | Max
- -2.15e+09 | 0.00
model_04
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 432 (0.3%)
- Mean ± Std
- -2.02e+09 ± 1.96e+08
- Median ± IQR
- -2.04e+09 ± 1.24e+08
- Min | Max
- -2.15e+09 | 0.00
model_05
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 335 (0.2%)
- Mean ± Std
- -2.09e+09 ± 1.88e+08
- Median ± IQR
- -2.10e+09 ± 1.81e+07
- Min | Max
- -2.15e+09 | 8.95e+08
model_06
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 329 (0.2%)
- Mean ± Std
- -1.89e+09 ± 3.76e+08
- Median ± IQR
- -2.08e+09 ± 7.94e+08
- Min | Max
- -2.15e+09 | 0.00
model_07
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 365 (0.2%)
- Mean ± Std
- -2.02e+09 ± 2.03e+08
- Median ± IQR
- -2.09e+09 ± 2.12e+08
- Min | Max
- -2.15e+09 | 0.00
model_08
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 430 (0.3%)
- Mean ± Std
- -1.98e+09 ± 2.33e+08
- Median ± IQR
- -2.07e+09 ± 3.38e+08
- Min | Max
- -2.15e+09 | 0.00
model_09
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 280 (0.2%)
- Mean ± Std
- -2.00e+09 ± 2.35e+08
- Median ± IQR
- -2.09e+09 ± 3.62e+08
- Min | Max
- -2.15e+09 | 0.00
model_10
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 386 (0.2%)
- Mean ± Std
- -2.07e+09 ± 1.92e+08
- Median ± IQR
- -2.09e+09 ± 1.59e+07
- Min | Max
- -2.15e+09 | 1.05e+09
model_11
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 346 (0.2%)
- Mean ± Std
- -2.08e+09 ± 1.89e+08
- Median ± IQR
- -2.10e+09 ± 5.25e+07
- Min | Max
- -2.15e+09 | 2.73e+08
model_12
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 471 (0.3%)
- Mean ± Std
- -1.96e+09 ± 2.38e+08
- Median ± IQR
- -2.05e+09 ± 3.79e+08
- Min | Max
- -2.15e+09 | 0.00
model_13
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 377 (0.2%)
- Mean ± Std
- -2.08e+09 ± 1.87e+08
- Median ± IQR
- -2.10e+09 ± 0.00
- Min | Max
- -2.15e+09 | 0.00
model_14
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 311 (0.2%)
- Mean ± Std
- -2.07e+09 ± 1.95e+08
- Median ± IQR
- -2.10e+09 ± 1.45e+08
- Min | Max
- -2.15e+09 | 9.05e+07
model_15
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 355 (0.2%)
- Mean ± Std
- -2.04e+09 ± 1.96e+08
- Median ± IQR
- -2.03e+09 ± 1.38e+08
- Min | Max
- -2.15e+09 | 3.49e+08
model_16
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 448 (0.3%)
- Mean ± Std
- -1.93e+09 ± 2.72e+08
- Median ± IQR
- -2.05e+09 ± 4.76e+08
- Min | Max
- -2.15e+09 | 0.00
model_17
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 413 (0.3%)
- Mean ± Std
- -1.82e+09 ± 4.59e+08
- Median ± IQR
- -2.11e+09 ± 1.00e+09
- Min | Max
- -2.15e+09 | 4.20e+08
model_18
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 396 (0.2%)
- Mean ± Std
- -2.04e+09 ± 1.88e+08
- Median ± IQR
- -2.05e+09 ± 7.62e+07
- Min | Max
- -2.15e+09 | 1.57e+09
model_19
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 255 (0.2%)
- Mean ± Std
- -2.09e+09 ± 1.93e+08
- Median ± IQR
- -2.14e+09 ± 1.15e+08
- Min | Max
- -2.15e+09 | 2.29e+08
model_20
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 415 (0.3%)
- Mean ± Std
- -2.00e+09 ± 2.37e+08
- Median ± IQR
- -2.10e+09 ± 3.54e+08
- Min | Max
- -2.15e+09 | 0.00
model_21
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 315 (0.2%)
- Mean ± Std
- -2.09e+09 ± 1.93e+08
- Median ± IQR
- -2.11e+09 ± 5.59e+07
- Min | Max
- -2.15e+09 | 1.15e+09
model_22
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 398 (0.2%)
- Mean ± Std
- -1.91e+09 ± 2.86e+08
- Median ± IQR
- -2.03e+09 ± 5.39e+08
- Min | Max
- -2.15e+09 | 6.53e+08
model_23
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 447 (0.3%)
- Mean ± Std
- -1.94e+09 ± 2.88e+08
- Median ± IQR
- -2.08e+09 ± 5.43e+08
- Min | Max
- -2.15e+09 | 9.93e+08
model_24
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 369 (0.2%)
- Mean ± Std
- -2.05e+09 ± 1.94e+08
- Median ± IQR
- -2.07e+09 ± 1.49e+08
- Min | Max
- -2.15e+09 | 0.00
model_25
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 369 (0.2%)
- Mean ± Std
- -1.99e+09 ± 2.45e+08
- Median ± IQR
- -2.10e+09 ± 3.83e+08
- Min | Max
- -2.15e+09 | 0.00
model_26
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 395 (0.2%)
- Mean ± Std
- -2.06e+09 ± 1.98e+08
- Median ± IQR
- -2.09e+09 ± 4.59e+07
- Min | Max
- -2.15e+09 | 1.14e+09
model_27
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 332 (0.2%)
- Mean ± Std
- -2.08e+09 ± 1.91e+08
- Median ± IQR
- -2.09e+09 ± 5.01e+07
- Min | Max
- -2.15e+09 | 1.20e+09
model_28
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 406 (0.2%)
- Mean ± Std
- -2.08e+09 ± 1.96e+08
- Median ± IQR
- -2.10e+09 ± 3.57e+07
- Min | Max
- -2.15e+09 | 4.59e+08
model_29
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 433 (0.3%)
- Mean ± Std
- -1.99e+09 ± 2.00e+08
- Median ± IQR
- -2.00e+09 ± 1.77e+08
- Min | Max
- -2.15e+09 | 1.17e+09
goods_code
Float64DType- Null values
- 0 (0.0%)
- Unique values
- 14,880 (9.1%)
- Mean ± Std
- 1.06e+04 ± 4.22e+03
- Median ± IQR
- 1.12e+04 ± 5.37e+03
- Min | Max
- 0.00 | 1.49e+04
Nbr_of_prod_purchas
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 20 (< 0.1%)
- Mean ± Std
- 1.05 ± 0.427
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 40.0
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
Column
|
Column name
|
dtype
|
Null values
|
Unique values
|
Mean
|
Std
|
Min
|
Median
|
Max
|
---|---|---|---|---|---|---|---|---|---|
0 | basket_ID | Float32DType | 0 (0.0%) | 92790 (56.8%) | 5.59e+04 | 3.46e+04 | 0.00 | 5.47e+04 | 1.16e+05 |
1 | item_00 | Float32DType | 0 (0.0%) | 73 (< 0.1%) | -2.03e+09 | 1.55e+08 | -2.15e+09 | -2.12e+09 | -1.03e+09 |
2 | item_01 | Float32DType | 0 (0.0%) | 47 (< 0.1%) | -1.91e+09 | 2.66e+08 | -2.14e+09 | -2.06e+09 | -1.09e+09 |
3 | item_02 | Float32DType | 0 (0.0%) | 59 (< 0.1%) | -1.98e+09 | 1.84e+08 | -2.14e+09 | -2.09e+09 | -3.95e+08 |
4 | item_03 | Float32DType | 0 (0.0%) | 55 (< 0.1%) | -2.06e+09 | 8.12e+07 | -2.15e+09 | -2.07e+09 | -8.27e+08 |
5 | item_04 | Float32DType | 0 (0.0%) | 64 (< 0.1%) | -2.02e+09 | 6.44e+07 | -2.15e+09 | -2.05e+09 | -1.08e+09 |
6 | item_05 | Float32DType | 0 (0.0%) | 62 (< 0.1%) | -1.99e+09 | 2.15e+08 | -2.14e+09 | -2.06e+09 | -8.93e+08 |
7 | item_06 | Float32DType | 0 (0.0%) | 70 (< 0.1%) | -1.76e+09 | 3.83e+08 | -2.14e+09 | -1.99e+09 | -9.01e+07 |
8 | item_07 | Float32DType | 0 (0.0%) | 62 (< 0.1%) | -1.97e+09 | 1.41e+08 | -2.14e+09 | -2.00e+09 | -1.20e+09 |
9 | item_08 | Float32DType | 0 (0.0%) | 65 (< 0.1%) | -1.98e+09 | 1.06e+08 | -2.15e+09 | -2.02e+09 | -9.20e+08 |
10 | item_09 | Float32DType | 0 (0.0%) | 67 (< 0.1%) | -2.01e+09 | 2.29e+08 | -2.14e+09 | -2.06e+09 | 7.04e+08 |
11 | item_10 | Float32DType | 0 (0.0%) | 61 (< 0.1%) | -2.02e+09 | 7.99e+07 | -2.14e+09 | -2.04e+09 | 2.67e+07 |
12 | item_11 | Float32DType | 0 (0.0%) | 59 (< 0.1%) | -2.10e+09 | 1.06e+08 | -2.14e+09 | -2.14e+09 | -5.71e+08 |
13 | item_12 | Float32DType | 0 (0.0%) | 59 (< 0.1%) | -2.04e+09 | 8.53e+07 | -2.14e+09 | -2.06e+09 | -1.05e+09 |
14 | item_13 | Float32DType | 0 (0.0%) | 58 (< 0.1%) | -2.04e+09 | 1.49e+08 | -2.15e+09 | -2.10e+09 | -1.14e+09 |
15 | item_14 | Float32DType | 0 (0.0%) | 61 (< 0.1%) | -1.98e+09 | 1.51e+08 | -2.15e+09 | -1.99e+09 | -5.50e+08 |
16 | item_15 | Float32DType | 0 (0.0%) | 63 (< 0.1%) | -1.99e+09 | 1.23e+08 | -2.15e+09 | -2.01e+09 | -8.00e+08 |
17 | item_16 | Float32DType | 0 (0.0%) | 68 (< 0.1%) | -2.03e+09 | 1.06e+08 | -2.15e+09 | -2.06e+09 | -6.04e+08 |
18 | item_17 | Float32DType | 0 (0.0%) | 56 (< 0.1%) | -2.04e+09 | 9.05e+07 | -2.15e+09 | -2.04e+09 | -1.13e+09 |
19 | item_18 | Float32DType | 0 (0.0%) | 70 (< 0.1%) | -2.00e+09 | 8.97e+07 | -2.14e+09 | -1.96e+09 | -9.75e+08 |
20 | item_19 | Float32DType | 0 (0.0%) | 51 (< 0.1%) | -2.06e+09 | 1.03e+08 | -2.15e+09 | -2.08e+09 | -5.72e+08 |
21 | item_20 | Float32DType | 0 (0.0%) | 58 (< 0.1%) | -2.01e+09 | 3.00e+08 | -2.14e+09 | -2.10e+09 | -5.10e+06 |
22 | item_21 | Float32DType | 0 (0.0%) | 66 (< 0.1%) | -2.05e+09 | 1.02e+08 | -2.14e+09 | -2.05e+09 | -8.74e+08 |
23 | item_22 | Float32DType | 0 (0.0%) | 57 (< 0.1%) | -1.99e+09 | 1.43e+08 | -2.14e+09 | -2.06e+09 | -7.91e+08 |
24 | item_23 | Float32DType | 0 (0.0%) | 63 (< 0.1%) | -2.05e+09 | 1.32e+08 | -2.15e+09 | -2.08e+09 | -7.27e+08 |
25 | item_24 | Float32DType | 0 (0.0%) | 63 (< 0.1%) | -2.01e+09 | 1.54e+08 | -2.14e+09 | -2.09e+09 | -5.03e+08 |
26 | item_25 | Float32DType | 0 (0.0%) | 68 (< 0.1%) | -1.90e+09 | 2.07e+08 | -2.14e+09 | -1.83e+09 | -8.07e+08 |
27 | item_26 | Float32DType | 0 (0.0%) | 73 (< 0.1%) | -1.94e+09 | 1.31e+08 | -2.15e+09 | -1.84e+09 | -1.36e+09 |
28 | item_27 | Float32DType | 0 (0.0%) | 67 (< 0.1%) | -2.00e+09 | 1.70e+08 | -2.15e+09 | -2.12e+09 | -9.92e+08 |
29 | item_28 | Float32DType | 0 (0.0%) | 76 (< 0.1%) | -2.05e+09 | 1.21e+08 | -2.15e+09 | -2.12e+09 | -9.07e+08 |
30 | item_29 | Float32DType | 0 (0.0%) | 58 (< 0.1%) | -1.99e+09 | 1.22e+08 | -2.15e+09 | -1.97e+09 | -1.07e+09 |
31 | cash_price | Float32DType | 0 (0.0%) | 1594 (1.0%) | 701. | 742. | 0.00 | 549. | 2.20e+04 |
32 | make | Float64DType | 1273 (0.8%) | 829 (0.5%) | 303. | 281. | 0.00 | 176. | 828. |
33 | model_00 | Float32DType | 0 (0.0%) | 478 (0.3%) | -1.95e+09 | 2.69e+08 | -2.15e+09 | -2.07e+09 | 0.00 |
34 | model_01 | Float32DType | 0 (0.0%) | 347 (0.2%) | -2.09e+09 | 2.04e+08 | -2.15e+09 | -2.14e+09 | 0.00 |
35 | model_02 | Float32DType | 0 (0.0%) | 337 (0.2%) | -2.07e+09 | 1.93e+08 | -2.15e+09 | -2.12e+09 | 4.22e+07 |
36 | model_03 | Float32DType | 0 (0.0%) | 341 (0.2%) | -2.05e+09 | 1.98e+08 | -2.15e+09 | -2.11e+09 | 0.00 |
37 | model_04 | Float32DType | 0 (0.0%) | 432 (0.3%) | -2.02e+09 | 1.96e+08 | -2.15e+09 | -2.04e+09 | 0.00 |
38 | model_05 | Float32DType | 0 (0.0%) | 335 (0.2%) | -2.09e+09 | 1.88e+08 | -2.15e+09 | -2.10e+09 | 8.95e+08 |
39 | model_06 | Float32DType | 0 (0.0%) | 329 (0.2%) | -1.89e+09 | 3.76e+08 | -2.15e+09 | -2.08e+09 | 0.00 |
40 | model_07 | Float32DType | 0 (0.0%) | 365 (0.2%) | -2.02e+09 | 2.03e+08 | -2.15e+09 | -2.09e+09 | 0.00 |
41 | model_08 | Float32DType | 0 (0.0%) | 430 (0.3%) | -1.98e+09 | 2.33e+08 | -2.15e+09 | -2.07e+09 | 0.00 |
42 | model_09 | Float32DType | 0 (0.0%) | 280 (0.2%) | -2.00e+09 | 2.35e+08 | -2.15e+09 | -2.09e+09 | 0.00 |
43 | model_10 | Float32DType | 0 (0.0%) | 386 (0.2%) | -2.07e+09 | 1.92e+08 | -2.15e+09 | -2.09e+09 | 1.05e+09 |
44 | model_11 | Float32DType | 0 (0.0%) | 346 (0.2%) | -2.08e+09 | 1.89e+08 | -2.15e+09 | -2.10e+09 | 2.73e+08 |
45 | model_12 | Float32DType | 0 (0.0%) | 471 (0.3%) | -1.96e+09 | 2.38e+08 | -2.15e+09 | -2.05e+09 | 0.00 |
46 | model_13 | Float32DType | 0 (0.0%) | 377 (0.2%) | -2.08e+09 | 1.87e+08 | -2.15e+09 | -2.10e+09 | 0.00 |
47 | model_14 | Float32DType | 0 (0.0%) | 311 (0.2%) | -2.07e+09 | 1.95e+08 | -2.15e+09 | -2.10e+09 | 9.05e+07 |
48 | model_15 | Float32DType | 0 (0.0%) | 355 (0.2%) | -2.04e+09 | 1.96e+08 | -2.15e+09 | -2.03e+09 | 3.49e+08 |
49 | model_16 | Float32DType | 0 (0.0%) | 448 (0.3%) | -1.93e+09 | 2.72e+08 | -2.15e+09 | -2.05e+09 | 0.00 |
50 | model_17 | Float32DType | 0 (0.0%) | 413 (0.3%) | -1.82e+09 | 4.59e+08 | -2.15e+09 | -2.11e+09 | 4.20e+08 |
51 | model_18 | Float32DType | 0 (0.0%) | 396 (0.2%) | -2.04e+09 | 1.88e+08 | -2.15e+09 | -2.05e+09 | 1.57e+09 |
52 | model_19 | Float32DType | 0 (0.0%) | 255 (0.2%) | -2.09e+09 | 1.93e+08 | -2.15e+09 | -2.14e+09 | 2.29e+08 |
53 | model_20 | Float32DType | 0 (0.0%) | 415 (0.3%) | -2.00e+09 | 2.37e+08 | -2.15e+09 | -2.10e+09 | 0.00 |
54 | model_21 | Float32DType | 0 (0.0%) | 315 (0.2%) | -2.09e+09 | 1.93e+08 | -2.15e+09 | -2.11e+09 | 1.15e+09 |
55 | model_22 | Float32DType | 0 (0.0%) | 398 (0.2%) | -1.91e+09 | 2.86e+08 | -2.15e+09 | -2.03e+09 | 6.53e+08 |
56 | model_23 | Float32DType | 0 (0.0%) | 447 (0.3%) | -1.94e+09 | 2.88e+08 | -2.15e+09 | -2.08e+09 | 9.93e+08 |
57 | model_24 | Float32DType | 0 (0.0%) | 369 (0.2%) | -2.05e+09 | 1.94e+08 | -2.15e+09 | -2.07e+09 | 0.00 |
58 | model_25 | Float32DType | 0 (0.0%) | 369 (0.2%) | -1.99e+09 | 2.45e+08 | -2.15e+09 | -2.10e+09 | 0.00 |
59 | model_26 | Float32DType | 0 (0.0%) | 395 (0.2%) | -2.06e+09 | 1.98e+08 | -2.15e+09 | -2.09e+09 | 1.14e+09 |
60 | model_27 | Float32DType | 0 (0.0%) | 332 (0.2%) | -2.08e+09 | 1.91e+08 | -2.15e+09 | -2.09e+09 | 1.20e+09 |
61 | model_28 | Float32DType | 0 (0.0%) | 406 (0.2%) | -2.08e+09 | 1.96e+08 | -2.15e+09 | -2.10e+09 | 4.59e+08 |
62 | model_29 | Float32DType | 0 (0.0%) | 433 (0.3%) | -1.99e+09 | 2.00e+08 | -2.15e+09 | -2.00e+09 | 1.17e+09 |
63 | goods_code | Float64DType | 0 (0.0%) | 14880 (9.1%) | 1.06e+04 | 4.22e+03 | 0.00 | 1.12e+04 | 1.49e+04 |
64 | Nbr_of_prod_purchas | Float32DType | 0 (0.0%) | 20 (< 0.1%) | 1.05 | 0.427 | 1.00 | 1.00 | 40.0 |
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
max_plot_columns
parameter.
basket_ID
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 92,790 (56.8%)
- Mean ± Std
- 5.59e+04 ± 3.46e+04
- Median ± IQR
- 5.47e+04 ± 6.13e+04
- Min | Max
- 0.00 | 1.16e+05
item_00
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 73 (< 0.1%)
- Mean ± Std
- -2.03e+09 ± 1.55e+08
- Median ± IQR
- -2.12e+09 ± 1.82e+08
- Min | Max
- -2.15e+09 | -1.03e+09
item_01
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 47 (< 0.1%)
- Mean ± Std
- -1.91e+09 ± 2.66e+08
- Median ± IQR
- -2.06e+09 ± 4.74e+08
- Min | Max
- -2.14e+09 | -1.09e+09
item_02
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 59 (< 0.1%)
- Mean ± Std
- -1.98e+09 ± 1.84e+08
- Median ± IQR
- -2.09e+09 ± 3.25e+08
- Min | Max
- -2.14e+09 | -3.95e+08
item_03
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 55 (< 0.1%)
- Mean ± Std
- -2.06e+09 ± 8.12e+07
- Median ± IQR
- -2.07e+09 ± 4.98e+07
- Min | Max
- -2.15e+09 | -8.27e+08
item_04
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 64 (< 0.1%)
- Mean ± Std
- -2.02e+09 ± 6.44e+07
- Median ± IQR
- -2.05e+09 ± 8.00e+07
- Min | Max
- -2.15e+09 | -1.08e+09
item_05
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 62 (< 0.1%)
- Mean ± Std
- -1.99e+09 ± 2.15e+08
- Median ± IQR
- -2.06e+09 ± 2.47e+07
- Min | Max
- -2.14e+09 | -8.93e+08
item_06
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 70 (< 0.1%)
- Mean ± Std
- -1.76e+09 ± 3.83e+08
- Median ± IQR
- -1.99e+09 ± 6.68e+08
- Min | Max
- -2.14e+09 | -9.01e+07
item_07
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 62 (< 0.1%)
- Mean ± Std
- -1.97e+09 ± 1.41e+08
- Median ± IQR
- -2.00e+09 ± 7.90e+07
- Min | Max
- -2.14e+09 | -1.20e+09
item_08
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 65 (< 0.1%)
- Mean ± Std
- -1.98e+09 ± 1.06e+08
- Median ± IQR
- -2.02e+09 ± 2.12e+08
- Min | Max
- -2.15e+09 | -9.20e+08
item_09
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 67 (< 0.1%)
- Mean ± Std
- -2.01e+09 ± 2.29e+08
- Median ± IQR
- -2.06e+09 ± 8.91e+07
- Min | Max
- -2.14e+09 | 7.04e+08
item_10
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 61 (< 0.1%)
- Mean ± Std
- -2.02e+09 ± 7.99e+07
- Median ± IQR
- -2.04e+09 ± 1.31e+08
- Min | Max
- -2.14e+09 | 2.67e+07
item_11
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 59 (< 0.1%)
- Mean ± Std
- -2.10e+09 ± 1.06e+08
- Median ± IQR
- -2.14e+09 ± 4.89e+07
- Min | Max
- -2.14e+09 | -5.71e+08
item_12
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 59 (< 0.1%)
- Mean ± Std
- -2.04e+09 ± 8.53e+07
- Median ± IQR
- -2.06e+09 ± 1.31e+08
- Min | Max
- -2.14e+09 | -1.05e+09
item_13
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 58 (< 0.1%)
- Mean ± Std
- -2.04e+09 ± 1.49e+08
- Median ± IQR
- -2.10e+09 ± 9.61e+07
- Min | Max
- -2.15e+09 | -1.14e+09
item_14
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 61 (< 0.1%)
- Mean ± Std
- -1.98e+09 ± 1.51e+08
- Median ± IQR
- -1.99e+09 ± 2.24e+08
- Min | Max
- -2.15e+09 | -5.50e+08
item_15
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 63 (< 0.1%)
- Mean ± Std
- -1.99e+09 ± 1.23e+08
- Median ± IQR
- -2.01e+09 ± 2.11e+08
- Min | Max
- -2.15e+09 | -8.00e+08
item_16
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 68 (< 0.1%)
- Mean ± Std
- -2.03e+09 ± 1.06e+08
- Median ± IQR
- -2.06e+09 ± 5.51e+07
- Min | Max
- -2.15e+09 | -6.04e+08
item_17
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 56 (< 0.1%)
- Mean ± Std
- -2.04e+09 ± 9.05e+07
- Median ± IQR
- -2.04e+09 ± 8.40e+07
- Min | Max
- -2.15e+09 | -1.13e+09
item_18
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 70 (< 0.1%)
- Mean ± Std
- -2.00e+09 ± 8.97e+07
- Median ± IQR
- -1.96e+09 ± 1.24e+08
- Min | Max
- -2.14e+09 | -9.75e+08
item_19
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 51 (< 0.1%)
- Mean ± Std
- -2.06e+09 ± 1.03e+08
- Median ± IQR
- -2.08e+09 ± 1.06e+08
- Min | Max
- -2.15e+09 | -5.72e+08
item_20
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 58 (< 0.1%)
- Mean ± Std
- -2.01e+09 ± 3.00e+08
- Median ± IQR
- -2.10e+09 ± 4.17e+07
- Min | Max
- -2.14e+09 | -5.10e+06
item_21
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 66 (< 0.1%)
- Mean ± Std
- -2.05e+09 ± 1.02e+08
- Median ± IQR
- -2.05e+09 ± 1.18e+08
- Min | Max
- -2.14e+09 | -8.74e+08
item_22
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 57 (< 0.1%)
- Mean ± Std
- -1.99e+09 ± 1.43e+08
- Median ± IQR
- -2.06e+09 ± 2.10e+08
- Min | Max
- -2.14e+09 | -7.91e+08
item_23
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 63 (< 0.1%)
- Mean ± Std
- -2.05e+09 ± 1.32e+08
- Median ± IQR
- -2.08e+09 ± 3.95e+07
- Min | Max
- -2.15e+09 | -7.27e+08
item_24
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 63 (< 0.1%)
- Mean ± Std
- -2.01e+09 ± 1.54e+08
- Median ± IQR
- -2.09e+09 ± 1.82e+08
- Min | Max
- -2.14e+09 | -5.03e+08
item_25
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 68 (< 0.1%)
- Mean ± Std
- -1.90e+09 ± 2.07e+08
- Median ± IQR
- -1.83e+09 ± 4.25e+08
- Min | Max
- -2.14e+09 | -8.07e+08
item_26
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 73 (< 0.1%)
- Mean ± Std
- -1.94e+09 ± 1.31e+08
- Median ± IQR
- -1.84e+09 ± 1.83e+08
- Min | Max
- -2.15e+09 | -1.36e+09
item_27
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 67 (< 0.1%)
- Mean ± Std
- -2.00e+09 ± 1.70e+08
- Median ± IQR
- -2.12e+09 ± 1.69e+08
- Min | Max
- -2.15e+09 | -9.92e+08
item_28
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 76 (< 0.1%)
- Mean ± Std
- -2.05e+09 ± 1.21e+08
- Median ± IQR
- -2.12e+09 ± 1.78e+08
- Min | Max
- -2.15e+09 | -9.07e+08
item_29
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 58 (< 0.1%)
- Mean ± Std
- -1.99e+09 ± 1.22e+08
- Median ± IQR
- -1.97e+09 ± 1.53e+08
- Min | Max
- -2.15e+09 | -1.07e+09
cash_price
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 1,594 (1.0%)
- Mean ± Std
- 701. ± 742.
- Median ± IQR
- 549. ± 1.03e+03
- Min | Max
- 0.00 | 2.20e+04
make
Float64DType- Null values
- 1,273 (0.8%)
- Unique values
- 829 (0.5%)
- Mean ± Std
- 303. ± 281.
- Median ± IQR
- 176. ± 572.
- Min | Max
- 0.00 | 828.
model_00
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 478 (0.3%)
- Mean ± Std
- -1.95e+09 ± 2.69e+08
- Median ± IQR
- -2.07e+09 ± 4.85e+08
- Min | Max
- -2.15e+09 | 0.00
model_01
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 347 (0.2%)
- Mean ± Std
- -2.09e+09 ± 2.04e+08
- Median ± IQR
- -2.14e+09 ± 4.84e+07
- Min | Max
- -2.15e+09 | 0.00
model_02
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 337 (0.2%)
- Mean ± Std
- -2.07e+09 ± 1.93e+08
- Median ± IQR
- -2.12e+09 ± 1.19e+08
- Min | Max
- -2.15e+09 | 4.22e+07
model_03
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 341 (0.2%)
- Mean ± Std
- -2.05e+09 ± 1.98e+08
- Median ± IQR
- -2.11e+09 ± 1.72e+08
- Min | Max
- -2.15e+09 | 0.00
model_04
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 432 (0.3%)
- Mean ± Std
- -2.02e+09 ± 1.96e+08
- Median ± IQR
- -2.04e+09 ± 1.24e+08
- Min | Max
- -2.15e+09 | 0.00
model_05
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 335 (0.2%)
- Mean ± Std
- -2.09e+09 ± 1.88e+08
- Median ± IQR
- -2.10e+09 ± 1.81e+07
- Min | Max
- -2.15e+09 | 8.95e+08
model_06
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 329 (0.2%)
- Mean ± Std
- -1.89e+09 ± 3.76e+08
- Median ± IQR
- -2.08e+09 ± 7.94e+08
- Min | Max
- -2.15e+09 | 0.00
model_07
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 365 (0.2%)
- Mean ± Std
- -2.02e+09 ± 2.03e+08
- Median ± IQR
- -2.09e+09 ± 2.12e+08
- Min | Max
- -2.15e+09 | 0.00
model_08
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 430 (0.3%)
- Mean ± Std
- -1.98e+09 ± 2.33e+08
- Median ± IQR
- -2.07e+09 ± 3.38e+08
- Min | Max
- -2.15e+09 | 0.00
model_09
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 280 (0.2%)
- Mean ± Std
- -2.00e+09 ± 2.35e+08
- Median ± IQR
- -2.09e+09 ± 3.62e+08
- Min | Max
- -2.15e+09 | 0.00
model_10
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 386 (0.2%)
- Mean ± Std
- -2.07e+09 ± 1.92e+08
- Median ± IQR
- -2.09e+09 ± 1.59e+07
- Min | Max
- -2.15e+09 | 1.05e+09
model_11
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 346 (0.2%)
- Mean ± Std
- -2.08e+09 ± 1.89e+08
- Median ± IQR
- -2.10e+09 ± 5.25e+07
- Min | Max
- -2.15e+09 | 2.73e+08
model_12
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 471 (0.3%)
- Mean ± Std
- -1.96e+09 ± 2.38e+08
- Median ± IQR
- -2.05e+09 ± 3.79e+08
- Min | Max
- -2.15e+09 | 0.00
model_13
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 377 (0.2%)
- Mean ± Std
- -2.08e+09 ± 1.87e+08
- Median ± IQR
- -2.10e+09 ± 0.00
- Min | Max
- -2.15e+09 | 0.00
model_14
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 311 (0.2%)
- Mean ± Std
- -2.07e+09 ± 1.95e+08
- Median ± IQR
- -2.10e+09 ± 1.45e+08
- Min | Max
- -2.15e+09 | 9.05e+07
model_15
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 355 (0.2%)
- Mean ± Std
- -2.04e+09 ± 1.96e+08
- Median ± IQR
- -2.03e+09 ± 1.38e+08
- Min | Max
- -2.15e+09 | 3.49e+08
model_16
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 448 (0.3%)
- Mean ± Std
- -1.93e+09 ± 2.72e+08
- Median ± IQR
- -2.05e+09 ± 4.76e+08
- Min | Max
- -2.15e+09 | 0.00
model_17
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 413 (0.3%)
- Mean ± Std
- -1.82e+09 ± 4.59e+08
- Median ± IQR
- -2.11e+09 ± 1.00e+09
- Min | Max
- -2.15e+09 | 4.20e+08
model_18
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 396 (0.2%)
- Mean ± Std
- -2.04e+09 ± 1.88e+08
- Median ± IQR
- -2.05e+09 ± 7.62e+07
- Min | Max
- -2.15e+09 | 1.57e+09
model_19
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 255 (0.2%)
- Mean ± Std
- -2.09e+09 ± 1.93e+08
- Median ± IQR
- -2.14e+09 ± 1.15e+08
- Min | Max
- -2.15e+09 | 2.29e+08
model_20
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 415 (0.3%)
- Mean ± Std
- -2.00e+09 ± 2.37e+08
- Median ± IQR
- -2.10e+09 ± 3.54e+08
- Min | Max
- -2.15e+09 | 0.00
model_21
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 315 (0.2%)
- Mean ± Std
- -2.09e+09 ± 1.93e+08
- Median ± IQR
- -2.11e+09 ± 5.59e+07
- Min | Max
- -2.15e+09 | 1.15e+09
model_22
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 398 (0.2%)
- Mean ± Std
- -1.91e+09 ± 2.86e+08
- Median ± IQR
- -2.03e+09 ± 5.39e+08
- Min | Max
- -2.15e+09 | 6.53e+08
model_23
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 447 (0.3%)
- Mean ± Std
- -1.94e+09 ± 2.88e+08
- Median ± IQR
- -2.08e+09 ± 5.43e+08
- Min | Max
- -2.15e+09 | 9.93e+08
model_24
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 369 (0.2%)
- Mean ± Std
- -2.05e+09 ± 1.94e+08
- Median ± IQR
- -2.07e+09 ± 1.49e+08
- Min | Max
- -2.15e+09 | 0.00
model_25
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 369 (0.2%)
- Mean ± Std
- -1.99e+09 ± 2.45e+08
- Median ± IQR
- -2.10e+09 ± 3.83e+08
- Min | Max
- -2.15e+09 | 0.00
model_26
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 395 (0.2%)
- Mean ± Std
- -2.06e+09 ± 1.98e+08
- Median ± IQR
- -2.09e+09 ± 4.59e+07
- Min | Max
- -2.15e+09 | 1.14e+09
model_27
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 332 (0.2%)
- Mean ± Std
- -2.08e+09 ± 1.91e+08
- Median ± IQR
- -2.09e+09 ± 5.01e+07
- Min | Max
- -2.15e+09 | 1.20e+09
model_28
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 406 (0.2%)
- Mean ± Std
- -2.08e+09 ± 1.96e+08
- Median ± IQR
- -2.10e+09 ± 3.57e+07
- Min | Max
- -2.15e+09 | 4.59e+08
model_29
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 433 (0.3%)
- Mean ± Std
- -1.99e+09 ± 2.00e+08
- Median ± IQR
- -2.00e+09 ± 1.77e+08
- Min | Max
- -2.15e+09 | 1.17e+09
goods_code
Float64DType- Null values
- 0 (0.0%)
- Unique values
- 14,880 (9.1%)
- Mean ± Std
- 1.06e+04 ± 4.22e+03
- Median ± IQR
- 1.12e+04 ± 5.37e+03
- Min | Max
- 0.00 | 1.49e+04
Nbr_of_prod_purchas
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 20 (< 0.1%)
- Mean ± Std
- 1.05 ± 0.427
- Median ± IQR
- 1.00 ± 0.00
- Min | Max
- 1.00 | 40.0
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
Column 1 | Column 2 | Cramér's V | Pearson's Correlation |
---|---|---|---|
model_06 | model_22 | 0.913 | 0.959 |
model_14 | model_21 | 0.866 | 0.919 |
model_09 | model_22 | 0.866 | 0.949 |
model_09 | model_27 | 0.866 | 0.663 |
model_05 | model_09 | 0.866 | 0.699 |
model_21 | model_27 | 0.866 | 0.929 |
model_00 | model_09 | 0.865 | 0.964 |
model_24 | model_28 | 0.856 | 0.890 |
model_07 | model_09 | 0.851 | 0.916 |
item_03 | item_09 | 0.850 | 0.623 |
model_02 | model_06 | 0.850 | 0.623 |
model_02 | model_18 | 0.850 | 0.961 |
model_09 | model_12 | 0.844 | 0.956 |
model_22 | model_27 | 0.838 | 0.516 |
model_19 | model_27 | 0.837 | 0.882 |
model_21 | model_22 | 0.832 | 0.591 |
model_00 | model_22 | 0.829 | 0.965 |
model_05 | model_27 | 0.829 | 0.946 |
model_02 | model_14 | 0.826 | 0.947 |
model_02 | model_11 | 0.823 | 0.906 |
Please enable javascript
The skrub table reports need javascript to display correctly. If you are displaying a report in a Jupyter notebook and you see this message, you may need to re-execute the cell or to trust the notebook (button on the top right or "File > Trust notebook").
Our objective is now to aggregate this vectorized product dataframe by
"basket_ID"
, then to merge it on the baskets dataframe, still on
the "basket_ID"
.

AggJoiner
can help us achieve exactly this. We need to pass the product dataframe as
an auxiliary table argument to AggJoiner
in __init__
. The aux_key
argument
represent both the columns used to groupby on, and the columns used to join on.
The basket dataframe is our main table, and we indicate the columns to join on with
main_key
. Note that we pass the main table during fit
, and we discuss the
limitations of this design in the conclusion at the bottom of this notebook.
The minimum (“min”) is the most appropriate operation to aggregate encodings from
MinHashEncoder
, for reasons that are out of the scope of this notebook.
from skrub import AggJoiner
from skrub import _selectors as s
# Skrub selectors allow us to select columns using regexes, which reduces
# the boilerplate.
minhash_cols_query = s.glob("item*") | s.glob("model*")
minhash_cols = s.select(products_transformed, minhash_cols_query).columns
agg_joiner = AggJoiner(
aux_table=products_transformed,
aux_key="basket_ID",
main_key="ID",
cols=minhash_cols,
operations=["min"],
)
baskets_products = agg_joiner.fit_transform(baskets)
TableReport(baskets_products)
ID | fraud_flag | item_00_min | item_01_min | item_02_min | item_03_min | item_04_min | item_05_min | item_06_min | item_07_min | item_08_min | item_09_min | item_10_min | item_11_min | item_12_min | item_13_min | item_14_min | item_15_min | item_16_min | item_17_min | item_18_min | item_19_min | item_20_min | item_21_min | item_22_min | item_23_min | item_24_min | item_25_min | item_26_min | item_27_min | item_28_min | item_29_min | model_00_min | model_01_min | model_02_min | model_03_min | model_04_min | model_05_min | model_06_min | model_07_min | model_08_min | model_09_min | model_10_min | model_11_min | model_12_min | model_13_min | model_14_min | model_15_min | model_16_min | model_17_min | model_18_min | model_19_min | model_20_min | model_21_min | model_22_min | model_23_min | model_24_min | model_25_min | model_26_min | model_27_min | model_28_min | model_29_min | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 85517 | 0 | -2119082112.0 | -1621485056.0 | -1795710976.0 | -2069712512.0 | -2053898240.0 | -2061027200.0 | -1407719040.0 | -2003757696.0 | -1860201856.0 | -2064848000.0 | -1952196096.0 | -2143475584.0 | -1984537216.0 | -2097144064.0 | -1901156992.0 | -1890843008.0 | -2073910784.0 | -2043068544.0 | -1962807680.0 | -2026307840.0 | -2103297024.0 | -2053113984.0 | -2063595136.0 | -2083497856.0 | -2092638208.0 | -1687056128.0 | -1841633408.0 | -2118906752.0 | -2124841088.0 | -1926313216.0 | -2070114816.0 | -2140802048.0 | -2128763520.0 | -2114467200.0 | -2098292864.0 | -2101188736.0 | -2080134784.0 | -2123221504.0 | -2071984128.0 | -2089785728.0 | -2082095616.0 | -2065732480.0 | -2047006848.0 | -2096223104.0 | -2101725056.0 | -2028907008.0 | -2052252160.0 | -2127037184.0 | -2064700672.0 | -2141094144.0 | -2137696128.0 | -2143421952.0 | -2098587008.0 | -2146054400.0 | -2135834880.0 | -2113379200.0 | -2044705920.0 | -2053709824.0 | -2147119104.0 | -2110975872.0 |
1 | 51113 | 0 | -2119082112.0 | -2092437504.0 | -2091895296.0 | -2096070400.0 | -2053898240.0 | -2069353216.0 | -2075299584.0 | -2009485056.0 | -2071984128.0 | -2089785728.0 | -2082897536.0 | -2143475584.0 | -2057488000.0 | -2097144064.0 | -2086916736.0 | -2124873472.0 | -2109534080.0 | -2043068544.0 | -2135823616.0 | -2132238720.0 | -2114070144.0 | -2143421952.0 | -2063595136.0 | -2083497856.0 | -2143897856.0 | -2021854080.0 | -1841633408.0 | -2118906752.0 | -2124841088.0 | -2115769728.0 | -2086969984.0 | -2140802048.0 | -2120533120.0 | -2123470592.0 | -2044521856.0 | -2138671360.0 | -2139137024.0 | -2121052800.0 | -2071984128.0 | -2070443776.0 | -2082769664.0 | -2129256192.0 | -2134113920.0 | -2114362496.0 | -2128111232.0 | -2143113472.0 | -2101461632.0 | -2138302592.0 | -2047586432.0 | -2137376000.0 | -2114070144.0 | -2085245184.0 | -2113314816.0 | -2087341184.0 | -2065861248.0 | -2100475776.0 | -2072272384.0 | -2114559744.0 | -2125133952.0 | -1987577088.0 |
2 | 83008 | 0 | -2128259840.0 | -2095576448.0 | -2144445696.0 | -2020459392.0 | -2057084800.0 | -1876818048.0 | -2121499136.0 | -2114278400.0 | -2085140224.0 | -2064848000.0 | -2063490048.0 | -2143475584.0 | -2124267776.0 | -2096223104.0 | -1994766720.0 | -2008991360.0 | -2013149184.0 | -2127037184.0 | -2023255296.0 | -2128494592.0 | -2072412416.0 | -2141099136.0 | -2063595136.0 | -2134392832.0 | -2095952128.0 | -2111947648.0 | -2146418048.0 | -1724371712.0 | -2142947968.0 | -2066046208.0 | -2140403968.0 | -2092437504.0 | -1949062784.0 | -2128161920.0 | -2145696768.0 | -2119088768.0 | -2138769792.0 | -2087540096.0 | -2124020992.0 | -2133883648.0 | -2129010944.0 | -2119972352.0 | -2075782528.0 | -2096223104.0 | -2140701696.0 | -2142510208.0 | -1969872000.0 | -2127037184.0 | -2053575552.0 | -2140361472.0 | -1990730368.0 | -2049603072.0 | -2092721792.0 | -2109808896.0 | -2135747968.0 | -2130675712.0 | -2106766080.0 | -2112450432.0 | -2071285888.0 | -2118983168.0 |
3 | 78712 | 0 | -2119082112.0 | -2092437504.0 | -2091895296.0 | -2096070400.0 | -2053898240.0 | -2069353216.0 | -2075299584.0 | -2009485056.0 | -2071984128.0 | -2089785728.0 | -2082897536.0 | -2143475584.0 | -2057488000.0 | -2097144064.0 | -2086916736.0 | -2124873472.0 | -2109534080.0 | -2043068544.0 | -2135823616.0 | -2132238720.0 | -2114070144.0 | -2143421952.0 | -2063595136.0 | -2083497856.0 | -2143897856.0 | -2021854080.0 | -1841633408.0 | -2118906752.0 | -2124841088.0 | -2115769728.0 | -2123276160.0 | -2142073600.0 | -2128763520.0 | -2114467200.0 | -2101596928.0 | -2097416448.0 | -2139137024.0 | -2123221504.0 | -2125949440.0 | -2141934976.0 | -2094848640.0 | -2111496832.0 | -2124267776.0 | -2114362496.0 | -2100255360.0 | -2086078848.0 | -2063535744.0 | -2127037184.0 | -2115619584.0 | -2141094144.0 | -2137696128.0 | -2143421952.0 | -2140212608.0 | -2134392832.0 | -2135834880.0 | -2111947648.0 | -2136661760.0 | -2136393856.0 | -2144492544.0 | -2138674816.0 |
4 | 77846 | 0 | -2128259840.0 | -2095576448.0 | -2144445696.0 | -2020459392.0 | -2057084800.0 | -1876818048.0 | -2121499136.0 | -2114278400.0 | -2085140224.0 | -2064848000.0 | -2063490048.0 | -2143475584.0 | -2124267776.0 | -2096223104.0 | -1994766720.0 | -2008991360.0 | -2013149184.0 | -2127037184.0 | -2023255296.0 | -2128494592.0 | -2072412416.0 | -2141099136.0 | -2063595136.0 | -2134392832.0 | -2095952128.0 | -2111947648.0 | -2146418048.0 | -1724371712.0 | -2142947968.0 | -2066046208.0 | -2140403968.0 | -2092437504.0 | -2119336064.0 | -2053140480.0 | -2135153152.0 | -2146440832.0 | -2138769792.0 | -2123107200.0 | -2124020992.0 | -2133883648.0 | -2129010944.0 | -2105794432.0 | -2075782528.0 | -2096223104.0 | -2140701696.0 | -2109362432.0 | -2048629632.0 | -2138311808.0 | -2095718400.0 | -2140361472.0 | -1985099264.0 | -2106305152.0 | -2092721792.0 | -2109808896.0 | -2135834880.0 | -2134814464.0 | -2107277056.0 | -2103071232.0 | -2061058944.0 | -1995298944.0 |
92785 | 21243 | 0 | -2119082112.0 | -2092437504.0 | -2143066240.0 | -2121657216.0 | -2053898240.0 | -2085764736.0 | -2075299584.0 | -2009485056.0 | -2071984128.0 | -2089785728.0 | -2094848640.0 | -2143475584.0 | -2116008832.0 | -2097144064.0 | -2140701696.0 | -2124873472.0 | -2109534080.0 | -2135849344.0 | -2135823616.0 | -2135224192.0 | -2144071552.0 | -2143421952.0 | -2063595136.0 | -2083497856.0 | -2143897856.0 | -2021854080.0 | -2024828928.0 | -2118906752.0 | -2124841088.0 | -2115769728.0 | -2144654336.0 | -2140802048.0 | -2044098176.0 | -2136874880.0 | -2145696768.0 | -2138671360.0 | -2139137024.0 | -2141810816.0 | -2071899904.0 | -2124734848.0 | -2094848640.0 | -2101789312.0 | -2143261440.0 | -2114362496.0 | -2143952384.0 | -2130466304.0 | -2065807616.0 | -2088192384.0 | -2121673472.0 | -2137376000.0 | -2126369408.0 | -2087510656.0 | -2079609728.0 | -2025875840.0 | -2131045376.0 | -2113189120.0 | -2088567296.0 | -2092952704.0 | -2147119104.0 | -2132383744.0 |
92786 | 45891 | 0 | -2119082112.0 | -1621485056.0 | -1795710976.0 | -2069712512.0 | -2053898240.0 | -2061027200.0 | -1407719040.0 | -2003757696.0 | -1860201856.0 | -2064848000.0 | -1952196096.0 | -2143475584.0 | -1984537216.0 | -2097144064.0 | -1901156992.0 | -1890843008.0 | -2073910784.0 | -2043068544.0 | -1962807680.0 | -2026307840.0 | -2103297024.0 | -2053113984.0 | -2063595136.0 | -2083497856.0 | -2092638208.0 | -1687056128.0 | -1841633408.0 | -2118906752.0 | -2124841088.0 | -1926313216.0 | -2070114816.0 | -2140802048.0 | -2128763520.0 | -2114467200.0 | -2098292864.0 | -2101188736.0 | -2080134784.0 | -2123221504.0 | -2071984128.0 | -2089785728.0 | -2082095616.0 | -2065732480.0 | -2047006848.0 | -2096223104.0 | -2101725056.0 | -2028907008.0 | -2052252160.0 | -2127037184.0 | -2064700672.0 | -2141094144.0 | -2137696128.0 | -2143421952.0 | -2098587008.0 | -2146054400.0 | -2135834880.0 | -2113379200.0 | -2044705920.0 | -2053709824.0 | -2147119104.0 | -2110975872.0 |
92787 | 42613 | 0 | -1944860928.0 | -2140802048.0 | -2042012544.0 | -2061610752.0 | -1956562944.0 | -2115316480.0 | -2002457600.0 | -2009485056.0 | -2051230592.0 | -2128871936.0 | -1990878976.0 | -2143475584.0 | -1984537216.0 | -2073099648.0 | -1961043200.0 | -2101944064.0 | -2002543232.0 | -2022489728.0 | -1986229760.0 | -2140361472.0 | -2062128512.0 | -2112148992.0 | -2106278912.0 | -1997466752.0 | -2092638208.0 | -2135700096.0 | -2023483264.0 | -2146970240.0 | -2009022592.0 | -2078980864.0 | -2144654336.0 | -2140802048.0 | -2120533120.0 | -2140173568.0 | -2082763776.0 | -2118896512.0 | -2131974784.0 | -2120086912.0 | -2124020992.0 | -2106573056.0 | -2119114880.0 | -2143740544.0 | -2134113920.0 | -2131891200.0 | -2143952384.0 | -2137089792.0 | -2078441984.0 | -2145952512.0 | -2086298112.0 | -2140361472.0 | -2126369408.0 | -2141144576.0 | -2126553728.0 | -2146054400.0 | -2140792960.0 | -2130675712.0 | -2120271616.0 | -2146970240.0 | -2139479040.0 | -2128906368.0 |
92788 | 43567 | 0 | -2119082112.0 | -1621485056.0 | -1795710976.0 | -2069712512.0 | -2053898240.0 | -2061027200.0 | -1407719040.0 | -2003757696.0 | -1860201856.0 | -2064848000.0 | -1952196096.0 | -2143475584.0 | -1984537216.0 | -2097144064.0 | -1901156992.0 | -1890843008.0 | -2073910784.0 | -2043068544.0 | -1962807680.0 | -2026307840.0 | -2103297024.0 | -2053113984.0 | -2063595136.0 | -2083497856.0 | -2092638208.0 | -1687056128.0 | -1841633408.0 | -2118906752.0 | -2124841088.0 | -1926313216.0 | -2123882240.0 | -2140802048.0 | -2144499584.0 | -2124229120.0 | -2119447424.0 | -2100804096.0 | -2139137024.0 | -2087540096.0 | -2124020992.0 | -2142483712.0 | -2097948544.0 | -2111503488.0 | -2124267776.0 | -2126917376.0 | -2131770240.0 | -2124873472.0 | -2141608832.0 | -2127037184.0 | -2115619584.0 | -2141094144.0 | -2103297024.0 | -2143421952.0 | -2046004608.0 | -2087341184.0 | -2136538112.0 | -2111947648.0 | -2106766080.0 | -2141457664.0 | -2139479040.0 | -2096222464.0 |
92789 | 68268 | 0 | -2128259840.0 | -2095576448.0 | -2144445696.0 | -2020459392.0 | -2057084800.0 | -1876818048.0 | -2121499136.0 | -2114278400.0 | -2085140224.0 | -2064848000.0 | -2063490048.0 | -2143475584.0 | -2124267776.0 | -2096223104.0 | -1994766720.0 | -2008991360.0 | -2013149184.0 | -2127037184.0 | -2023255296.0 | -2128494592.0 | -2072412416.0 | -2141099136.0 | -2063595136.0 | -2134392832.0 | -2095952128.0 | -2111947648.0 | -2146418048.0 | -1724371712.0 | -2142947968.0 | -2066046208.0 | -2140403968.0 | -2092437504.0 | -2072778240.0 | -2124229120.0 | -2111208576.0 | -2119088768.0 | -2138769792.0 | -2087540096.0 | -2124020992.0 | -2133883648.0 | -2129010944.0 | -2139309824.0 | -2075782528.0 | -2096223104.0 | -2140701696.0 | -2134924800.0 | -2061275392.0 | -2138311808.0 | -2053575552.0 | -2140361472.0 | -1863376000.0 | -2049603072.0 | -2092721792.0 | -2109808896.0 | -2135747968.0 | -2135416576.0 | -2106766080.0 | -2103071232.0 | -2036068224.0 | -2138224128.0 |
ID
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 92,790 (100.0%)
- Mean ± Std
- 5.80e+04 ± 3.35e+04
- Median ± IQR
- 57,961 ± 58,085
- Min | Max
- 0 | 115,985
fraud_flag
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 2 (< 0.1%)
- Mean ± Std
- 0.0142 ± 0.118
- Median ± IQR
- 0 ± 0
- Min | Max
- 0 | 1
item_00_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 50 (< 0.1%)
- Mean ± Std
- -2.11e+09 ± 4.90e+07
- Median ± IQR
- -2.12e+09 ± 0.00
- Min | Max
- -2.15e+09 | -1.04e+09
item_01_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 37 (< 0.1%)
- Mean ± Std
- -1.96e+09 ± 2.15e+08
- Median ± IQR
- -2.09e+09 ± 4.74e+08
- Min | Max
- -2.14e+09 | -1.12e+09
item_02_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 47 (< 0.1%)
- Mean ± Std
- -2.02e+09 ± 1.52e+08
- Median ± IQR
- -2.09e+09 ± 3.47e+08
- Min | Max
- -2.14e+09 | -6.79e+08
item_03_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 37 (< 0.1%)
- Mean ± Std
- -2.08e+09 ± 4.41e+07
- Median ± IQR
- -2.08e+09 ± 5.19e+07
- Min | Max
- -2.15e+09 | -8.27e+08
item_04_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 44 (< 0.1%)
- Mean ± Std
- -2.04e+09 ± 3.26e+07
- Median ± IQR
- -2.05e+09 ± 0.00
- Min | Max
- -2.15e+09 | -1.08e+09
item_05_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 44 (< 0.1%)
- Mean ± Std
- -2.05e+09 ± 7.20e+07
- Median ± IQR
- -2.07e+09 ± 2.47e+07
- Min | Max
- -2.14e+09 | -8.93e+08
item_06_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 55 (< 0.1%)
- Mean ± Std
- -1.86e+09 ± 3.09e+08
- Median ± IQR
- -2.03e+09 ± 6.68e+08
- Min | Max
- -2.14e+09 | -5.96e+08
item_07_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 44 (< 0.1%)
- Mean ± Std
- -2.02e+09 ± 5.24e+07
- Median ± IQR
- -2.00e+09 ± 1.36e+07
- Min | Max
- -2.14e+09 | -1.20e+09
item_08_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 48 (< 0.1%)
- Mean ± Std
- -2.00e+09 ± 9.91e+07
- Median ± IQR
- -2.02e+09 ± 2.12e+08
- Min | Max
- -2.15e+09 | -1.46e+09
item_09_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 42 (< 0.1%)
- Mean ± Std
- -2.08e+09 ± 4.46e+07
- Median ± IQR
- -2.06e+09 ± 2.49e+07
- Min | Max
- -2.14e+09 | 7.04e+08
item_10_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 43 (< 0.1%)
- Mean ± Std
- -2.04e+09 ± 6.49e+07
- Median ± IQR
- -2.06e+09 ± 1.43e+08
- Min | Max
- -2.14e+09 | -1.07e+09
item_11_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 32 (< 0.1%)
- Mean ± Std
- -2.14e+09 ± 2.30e+07
- Median ± IQR
- -2.14e+09 ± 0.00
- Min | Max
- -2.14e+09 | -1.23e+09
item_12_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 36 (< 0.1%)
- Mean ± Std
- -2.06e+09 ± 6.49e+07
- Median ± IQR
- -2.09e+09 ± 1.31e+08
- Min | Max
- -2.14e+09 | -1.05e+09
item_13_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 42 (< 0.1%)
- Mean ± Std
- -2.09e+09 ± 3.74e+07
- Median ± IQR
- -2.10e+09 ± 0.00
- Min | Max
- -2.15e+09 | -1.16e+09
item_14_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 50 (< 0.1%)
- Mean ± Std
- -2.02e+09 ± 1.28e+08
- Median ± IQR
- -2.09e+09 ± 2.40e+08
- Min | Max
- -2.15e+09 | -9.70e+08
item_15_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 43 (< 0.1%)
- Mean ± Std
- -2.02e+09 ± 9.49e+07
- Median ± IQR
- -2.03e+09 ± 2.34e+08
- Min | Max
- -2.15e+09 | -8.00e+08
item_16_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 51 (< 0.1%)
- Mean ± Std
- -2.07e+09 ± 6.56e+07
- Median ± IQR
- -2.07e+09 ± 4.37e+07
- Min | Max
- -2.15e+09 | -1.34e+09
item_17_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 42 (< 0.1%)
- Mean ± Std
- -2.07e+09 ± 6.55e+07
- Median ± IQR
- -2.04e+09 ± 9.28e+07
- Min | Max
- -2.15e+09 | -1.33e+09
item_18_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 50 (< 0.1%)
- Mean ± Std
- -2.03e+09 ± 7.36e+07
- Median ± IQR
- -2.02e+09 ± 1.73e+08
- Min | Max
- -2.14e+09 | -1.56e+09
item_19_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 35 (< 0.1%)
- Mean ± Std
- -2.09e+09 ± 5.63e+07
- Median ± IQR
- -2.13e+09 ± 1.09e+08
- Min | Max
- -2.15e+09 | -1.01e+09
item_20_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 37 (< 0.1%)
- Mean ± Std
- -2.10e+09 ± 6.33e+07
- Median ± IQR
- -2.10e+09 ± 4.08e+07
- Min | Max
- -2.14e+09 | -5.10e+06
item_21_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 45 (< 0.1%)
- Mean ± Std
- -2.09e+09 ± 5.48e+07
- Median ± IQR
- -2.11e+09 ± 8.80e+07
- Min | Max
- -2.14e+09 | -8.74e+08
item_22_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 37 (< 0.1%)
- Mean ± Std
- -2.07e+09 ± 2.29e+07
- Median ± IQR
- -2.06e+09 ± 0.00
- Min | Max
- -2.14e+09 | -7.91e+08
item_23_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 41 (< 0.1%)
- Mean ± Std
- -2.09e+09 ± 4.68e+07
- Median ± IQR
- -2.08e+09 ± 2.15e+07
- Min | Max
- -2.15e+09 | -7.27e+08
item_24_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 38 (< 0.1%)
- Mean ± Std
- -2.10e+09 ± 4.13e+07
- Median ± IQR
- -2.09e+09 ± 3.31e+06
- Min | Max
- -2.14e+09 | -5.35e+08
item_25_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 51 (< 0.1%)
- Mean ± Std
- -1.94e+09 ± 1.84e+08
- Median ± IQR
- -2.02e+09 ± 4.25e+08
- Min | Max
- -2.14e+09 | -9.00e+08
item_26_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 54 (< 0.1%)
- Mean ± Std
- -1.97e+09 ± 1.27e+08
- Median ± IQR
- -2.02e+09 ± 2.60e+08
- Min | Max
- -2.15e+09 | -1.45e+09
item_27_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 42 (< 0.1%)
- Mean ± Std
- -2.06e+09 ± 1.30e+08
- Median ± IQR
- -2.12e+09 ± 4.35e+06
- Min | Max
- -2.15e+09 | -9.92e+08
item_28_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 53 (< 0.1%)
- Mean ± Std
- -2.12e+09 ± 5.25e+07
- Median ± IQR
- -2.12e+09 ± 0.00
- Min | Max
- -2.15e+09 | -1.14e+09
item_29_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 38 (< 0.1%)
- Mean ± Std
- -2.02e+09 ± 8.10e+07
- Median ± IQR
- -2.07e+09 ± 1.85e+08
- Min | Max
- -2.15e+09 | -1.19e+09
model_00_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 250 (0.3%)
- Mean ± Std
- -2.06e+09 ± 2.03e+08
- Median ± IQR
- -2.09e+09 ± 5.38e+07
- Min | Max
- -2.15e+09 | 0.00
model_01_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 140 (0.2%)
- Mean ± Std
- -2.10e+09 ± 1.91e+08
- Median ± IQR
- -2.14e+09 ± 4.84e+07
- Min | Max
- -2.15e+09 | 0.00
model_02_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 162 (0.2%)
- Mean ± Std
- -2.10e+09 ± 1.85e+08
- Median ± IQR
- -2.12e+09 ± 8.23e+06
- Min | Max
- -2.15e+09 | 4.22e+07
model_03_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 188 (0.2%)
- Mean ± Std
- -2.09e+09 ± 1.86e+08
- Median ± IQR
- -2.12e+09 ± 9.76e+06
- Min | Max
- -2.15e+09 | 0.00
model_04_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 263 (0.3%)
- Mean ± Std
- -2.05e+09 ± 1.91e+08
- Median ± IQR
- -2.10e+09 ± 9.02e+07
- Min | Max
- -2.15e+09 | 0.00
model_05_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 151 (0.2%)
- Mean ± Std
- -2.09e+09 ± 1.82e+08
- Median ± IQR
- -2.10e+09 ± 1.83e+07
- Min | Max
- -2.15e+09 | 0.00
model_06_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 180 (0.2%)
- Mean ± Std
- -2.07e+09 ± 2.22e+08
- Median ± IQR
- -2.12e+09 ± 5.97e+07
- Min | Max
- -2.15e+09 | 0.00
model_07_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 200 (0.2%)
- Mean ± Std
- -2.07e+09 ± 1.89e+08
- Median ± IQR
- -2.09e+09 ± 3.57e+07
- Min | Max
- -2.15e+09 | 0.00
model_08_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 212 (0.2%)
- Mean ± Std
- -2.06e+09 ± 2.02e+08
- Median ± IQR
- -2.09e+09 ± 5.20e+07
- Min | Max
- -2.15e+09 | 0.00
model_09_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 166 (0.2%)
- Mean ± Std
- -2.08e+09 ± 1.91e+08
- Median ± IQR
- -2.11e+09 ± 4.71e+07
- Min | Max
- -2.15e+09 | 0.00
model_10_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 205 (0.2%)
- Mean ± Std
- -2.08e+09 ± 1.86e+08
- Median ± IQR
- -2.09e+09 ± 1.52e+07
- Min | Max
- -2.15e+09 | 1.05e+09
model_11_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 155 (0.2%)
- Mean ± Std
- -2.09e+09 ± 1.83e+08
- Median ± IQR
- -2.11e+09 ± 1.82e+07
- Min | Max
- -2.15e+09 | 0.00
model_12_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 274 (0.3%)
- Mean ± Std
- -2.05e+09 ± 2.03e+08
- Median ± IQR
- -2.10e+09 ± 7.73e+07
- Min | Max
- -2.15e+09 | 0.00
model_13_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 161 (0.2%)
- Mean ± Std
- -2.09e+09 ± 1.81e+08
- Median ± IQR
- -2.10e+09 ± 1.81e+07
- Min | Max
- -2.15e+09 | 0.00
model_14_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 139 (0.1%)
- Mean ± Std
- -2.10e+09 ± 1.85e+08
- Median ± IQR
- -2.13e+09 ± 4.04e+07
- Min | Max
- -2.15e+09 | 0.00
model_15_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 171 (0.2%)
- Mean ± Std
- -2.07e+09 ± 1.89e+08
- Median ± IQR
- -2.11e+09 ± 1.06e+08
- Min | Max
- -2.15e+09 | 0.00
model_16_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 253 (0.3%)
- Mean ± Std
- -2.03e+09 ± 2.07e+08
- Median ± IQR
- -2.06e+09 ± 4.92e+07
- Min | Max
- -2.15e+09 | 0.00
model_17_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 204 (0.2%)
- Mean ± Std
- -2.07e+09 ± 2.44e+08
- Median ± IQR
- -2.13e+09 ± 1.38e+07
- Min | Max
- -2.15e+09 | 0.00
model_18_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 208 (0.2%)
- Mean ± Std
- -2.06e+09 ± 1.82e+08
- Median ± IQR
- -2.06e+09 ± 6.80e+07
- Min | Max
- -2.15e+09 | 0.00
model_19_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 94 (0.1%)
- Mean ± Std
- -2.12e+09 ± 1.85e+08
- Median ± IQR
- -2.14e+09 ± 3.72e+06
- Min | Max
- -2.15e+09 | 0.00
model_20_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 228 (0.2%)
- Mean ± Std
- -2.08e+09 ± 2.01e+08
- Median ± IQR
- -2.13e+09 ± 3.88e+07
- Min | Max
- -2.15e+09 | 0.00
model_21_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 140 (0.2%)
- Mean ± Std
- -2.10e+09 ± 1.88e+08
- Median ± IQR
- -2.14e+09 ± 3.71e+07
- Min | Max
- -2.15e+09 | 1.15e+09
model_22_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 230 (0.2%)
- Mean ± Std
- -2.04e+09 ± 2.04e+08
- Median ± IQR
- -2.08e+09 ± 7.71e+07
- Min | Max
- -2.15e+09 | 6.53e+08
model_23_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 242 (0.3%)
- Mean ± Std
- -2.07e+09 ± 2.10e+08
- Median ± IQR
- -2.11e+09 ± 7.93e+07
- Min | Max
- -2.15e+09 | 9.93e+08
model_24_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 182 (0.2%)
- Mean ± Std
- -2.09e+09 ± 1.86e+08
- Median ± IQR
- -2.14e+09 ± 7.00e+07
- Min | Max
- -2.15e+09 | 0.00
model_25_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 183 (0.2%)
- Mean ± Std
- -2.08e+09 ± 1.92e+08
- Median ± IQR
- -2.11e+09 ± 1.71e+07
- Min | Max
- -2.15e+09 | 0.00
model_26_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 200 (0.2%)
- Mean ± Std
- -2.07e+09 ± 1.89e+08
- Median ± IQR
- -2.09e+09 ± 2.95e+07
- Min | Max
- -2.15e+09 | 1.34e+08
model_27_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 134 (0.1%)
- Mean ± Std
- -2.08e+09 ± 1.85e+08
- Median ± IQR
- -2.10e+09 ± 6.32e+07
- Min | Max
- -2.15e+09 | 0.00
model_28_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 194 (0.2%)
- Mean ± Std
- -2.10e+09 ± 1.89e+08
- Median ± IQR
- -2.13e+09 ± 3.58e+07
- Min | Max
- -2.15e+09 | 2.58e+08
model_29_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 253 (0.3%)
- Mean ± Std
- -2.03e+09 ± 1.93e+08
- Median ± IQR
- -2.07e+09 ± 1.46e+08
- Min | Max
- -2.15e+09 | 2.92e+08
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
Column
|
Column name
|
dtype
|
Null values
|
Unique values
|
Mean
|
Std
|
Min
|
Median
|
Max
|
---|---|---|---|---|---|---|---|---|---|
0 | ID | Int64DType | 0 (0.0%) | 92790 (100.0%) | 5.80e+04 | 3.35e+04 | 0 | 57,961 | 115,985 |
1 | fraud_flag | Int64DType | 0 (0.0%) | 2 (< 0.1%) | 0.0142 | 0.118 | 0 | 0 | 1 |
2 | item_00_min | Float32DType | 0 (0.0%) | 50 (< 0.1%) | -2.11e+09 | 4.90e+07 | -2.15e+09 | -2.12e+09 | -1.04e+09 |
3 | item_01_min | Float32DType | 0 (0.0%) | 37 (< 0.1%) | -1.96e+09 | 2.15e+08 | -2.14e+09 | -2.09e+09 | -1.12e+09 |
4 | item_02_min | Float32DType | 0 (0.0%) | 47 (< 0.1%) | -2.02e+09 | 1.52e+08 | -2.14e+09 | -2.09e+09 | -6.79e+08 |
5 | item_03_min | Float32DType | 0 (0.0%) | 37 (< 0.1%) | -2.08e+09 | 4.41e+07 | -2.15e+09 | -2.08e+09 | -8.27e+08 |
6 | item_04_min | Float32DType | 0 (0.0%) | 44 (< 0.1%) | -2.04e+09 | 3.26e+07 | -2.15e+09 | -2.05e+09 | -1.08e+09 |
7 | item_05_min | Float32DType | 0 (0.0%) | 44 (< 0.1%) | -2.05e+09 | 7.20e+07 | -2.14e+09 | -2.07e+09 | -8.93e+08 |
8 | item_06_min | Float32DType | 0 (0.0%) | 55 (< 0.1%) | -1.86e+09 | 3.09e+08 | -2.14e+09 | -2.03e+09 | -5.96e+08 |
9 | item_07_min | Float32DType | 0 (0.0%) | 44 (< 0.1%) | -2.02e+09 | 5.24e+07 | -2.14e+09 | -2.00e+09 | -1.20e+09 |
10 | item_08_min | Float32DType | 0 (0.0%) | 48 (< 0.1%) | -2.00e+09 | 9.91e+07 | -2.15e+09 | -2.02e+09 | -1.46e+09 |
11 | item_09_min | Float32DType | 0 (0.0%) | 42 (< 0.1%) | -2.08e+09 | 4.46e+07 | -2.14e+09 | -2.06e+09 | 7.04e+08 |
12 | item_10_min | Float32DType | 0 (0.0%) | 43 (< 0.1%) | -2.04e+09 | 6.49e+07 | -2.14e+09 | -2.06e+09 | -1.07e+09 |
13 | item_11_min | Float32DType | 0 (0.0%) | 32 (< 0.1%) | -2.14e+09 | 2.30e+07 | -2.14e+09 | -2.14e+09 | -1.23e+09 |
14 | item_12_min | Float32DType | 0 (0.0%) | 36 (< 0.1%) | -2.06e+09 | 6.49e+07 | -2.14e+09 | -2.09e+09 | -1.05e+09 |
15 | item_13_min | Float32DType | 0 (0.0%) | 42 (< 0.1%) | -2.09e+09 | 3.74e+07 | -2.15e+09 | -2.10e+09 | -1.16e+09 |
16 | item_14_min | Float32DType | 0 (0.0%) | 50 (< 0.1%) | -2.02e+09 | 1.28e+08 | -2.15e+09 | -2.09e+09 | -9.70e+08 |
17 | item_15_min | Float32DType | 0 (0.0%) | 43 (< 0.1%) | -2.02e+09 | 9.49e+07 | -2.15e+09 | -2.03e+09 | -8.00e+08 |
18 | item_16_min | Float32DType | 0 (0.0%) | 51 (< 0.1%) | -2.07e+09 | 6.56e+07 | -2.15e+09 | -2.07e+09 | -1.34e+09 |
19 | item_17_min | Float32DType | 0 (0.0%) | 42 (< 0.1%) | -2.07e+09 | 6.55e+07 | -2.15e+09 | -2.04e+09 | -1.33e+09 |
20 | item_18_min | Float32DType | 0 (0.0%) | 50 (< 0.1%) | -2.03e+09 | 7.36e+07 | -2.14e+09 | -2.02e+09 | -1.56e+09 |
21 | item_19_min | Float32DType | 0 (0.0%) | 35 (< 0.1%) | -2.09e+09 | 5.63e+07 | -2.15e+09 | -2.13e+09 | -1.01e+09 |
22 | item_20_min | Float32DType | 0 (0.0%) | 37 (< 0.1%) | -2.10e+09 | 6.33e+07 | -2.14e+09 | -2.10e+09 | -5.10e+06 |
23 | item_21_min | Float32DType | 0 (0.0%) | 45 (< 0.1%) | -2.09e+09 | 5.48e+07 | -2.14e+09 | -2.11e+09 | -8.74e+08 |
24 | item_22_min | Float32DType | 0 (0.0%) | 37 (< 0.1%) | -2.07e+09 | 2.29e+07 | -2.14e+09 | -2.06e+09 | -7.91e+08 |
25 | item_23_min | Float32DType | 0 (0.0%) | 41 (< 0.1%) | -2.09e+09 | 4.68e+07 | -2.15e+09 | -2.08e+09 | -7.27e+08 |
26 | item_24_min | Float32DType | 0 (0.0%) | 38 (< 0.1%) | -2.10e+09 | 4.13e+07 | -2.14e+09 | -2.09e+09 | -5.35e+08 |
27 | item_25_min | Float32DType | 0 (0.0%) | 51 (< 0.1%) | -1.94e+09 | 1.84e+08 | -2.14e+09 | -2.02e+09 | -9.00e+08 |
28 | item_26_min | Float32DType | 0 (0.0%) | 54 (< 0.1%) | -1.97e+09 | 1.27e+08 | -2.15e+09 | -2.02e+09 | -1.45e+09 |
29 | item_27_min | Float32DType | 0 (0.0%) | 42 (< 0.1%) | -2.06e+09 | 1.30e+08 | -2.15e+09 | -2.12e+09 | -9.92e+08 |
30 | item_28_min | Float32DType | 0 (0.0%) | 53 (< 0.1%) | -2.12e+09 | 5.25e+07 | -2.15e+09 | -2.12e+09 | -1.14e+09 |
31 | item_29_min | Float32DType | 0 (0.0%) | 38 (< 0.1%) | -2.02e+09 | 8.10e+07 | -2.15e+09 | -2.07e+09 | -1.19e+09 |
32 | model_00_min | Float32DType | 0 (0.0%) | 250 (0.3%) | -2.06e+09 | 2.03e+08 | -2.15e+09 | -2.09e+09 | 0.00 |
33 | model_01_min | Float32DType | 0 (0.0%) | 140 (0.2%) | -2.10e+09 | 1.91e+08 | -2.15e+09 | -2.14e+09 | 0.00 |
34 | model_02_min | Float32DType | 0 (0.0%) | 162 (0.2%) | -2.10e+09 | 1.85e+08 | -2.15e+09 | -2.12e+09 | 4.22e+07 |
35 | model_03_min | Float32DType | 0 (0.0%) | 188 (0.2%) | -2.09e+09 | 1.86e+08 | -2.15e+09 | -2.12e+09 | 0.00 |
36 | model_04_min | Float32DType | 0 (0.0%) | 263 (0.3%) | -2.05e+09 | 1.91e+08 | -2.15e+09 | -2.10e+09 | 0.00 |
37 | model_05_min | Float32DType | 0 (0.0%) | 151 (0.2%) | -2.09e+09 | 1.82e+08 | -2.15e+09 | -2.10e+09 | 0.00 |
38 | model_06_min | Float32DType | 0 (0.0%) | 180 (0.2%) | -2.07e+09 | 2.22e+08 | -2.15e+09 | -2.12e+09 | 0.00 |
39 | model_07_min | Float32DType | 0 (0.0%) | 200 (0.2%) | -2.07e+09 | 1.89e+08 | -2.15e+09 | -2.09e+09 | 0.00 |
40 | model_08_min | Float32DType | 0 (0.0%) | 212 (0.2%) | -2.06e+09 | 2.02e+08 | -2.15e+09 | -2.09e+09 | 0.00 |
41 | model_09_min | Float32DType | 0 (0.0%) | 166 (0.2%) | -2.08e+09 | 1.91e+08 | -2.15e+09 | -2.11e+09 | 0.00 |
42 | model_10_min | Float32DType | 0 (0.0%) | 205 (0.2%) | -2.08e+09 | 1.86e+08 | -2.15e+09 | -2.09e+09 | 1.05e+09 |
43 | model_11_min | Float32DType | 0 (0.0%) | 155 (0.2%) | -2.09e+09 | 1.83e+08 | -2.15e+09 | -2.11e+09 | 0.00 |
44 | model_12_min | Float32DType | 0 (0.0%) | 274 (0.3%) | -2.05e+09 | 2.03e+08 | -2.15e+09 | -2.10e+09 | 0.00 |
45 | model_13_min | Float32DType | 0 (0.0%) | 161 (0.2%) | -2.09e+09 | 1.81e+08 | -2.15e+09 | -2.10e+09 | 0.00 |
46 | model_14_min | Float32DType | 0 (0.0%) | 139 (0.1%) | -2.10e+09 | 1.85e+08 | -2.15e+09 | -2.13e+09 | 0.00 |
47 | model_15_min | Float32DType | 0 (0.0%) | 171 (0.2%) | -2.07e+09 | 1.89e+08 | -2.15e+09 | -2.11e+09 | 0.00 |
48 | model_16_min | Float32DType | 0 (0.0%) | 253 (0.3%) | -2.03e+09 | 2.07e+08 | -2.15e+09 | -2.06e+09 | 0.00 |
49 | model_17_min | Float32DType | 0 (0.0%) | 204 (0.2%) | -2.07e+09 | 2.44e+08 | -2.15e+09 | -2.13e+09 | 0.00 |
50 | model_18_min | Float32DType | 0 (0.0%) | 208 (0.2%) | -2.06e+09 | 1.82e+08 | -2.15e+09 | -2.06e+09 | 0.00 |
51 | model_19_min | Float32DType | 0 (0.0%) | 94 (0.1%) | -2.12e+09 | 1.85e+08 | -2.15e+09 | -2.14e+09 | 0.00 |
52 | model_20_min | Float32DType | 0 (0.0%) | 228 (0.2%) | -2.08e+09 | 2.01e+08 | -2.15e+09 | -2.13e+09 | 0.00 |
53 | model_21_min | Float32DType | 0 (0.0%) | 140 (0.2%) | -2.10e+09 | 1.88e+08 | -2.15e+09 | -2.14e+09 | 1.15e+09 |
54 | model_22_min | Float32DType | 0 (0.0%) | 230 (0.2%) | -2.04e+09 | 2.04e+08 | -2.15e+09 | -2.08e+09 | 6.53e+08 |
55 | model_23_min | Float32DType | 0 (0.0%) | 242 (0.3%) | -2.07e+09 | 2.10e+08 | -2.15e+09 | -2.11e+09 | 9.93e+08 |
56 | model_24_min | Float32DType | 0 (0.0%) | 182 (0.2%) | -2.09e+09 | 1.86e+08 | -2.15e+09 | -2.14e+09 | 0.00 |
57 | model_25_min | Float32DType | 0 (0.0%) | 183 (0.2%) | -2.08e+09 | 1.92e+08 | -2.15e+09 | -2.11e+09 | 0.00 |
58 | model_26_min | Float32DType | 0 (0.0%) | 200 (0.2%) | -2.07e+09 | 1.89e+08 | -2.15e+09 | -2.09e+09 | 1.34e+08 |
59 | model_27_min | Float32DType | 0 (0.0%) | 134 (0.1%) | -2.08e+09 | 1.85e+08 | -2.15e+09 | -2.10e+09 | 0.00 |
60 | model_28_min | Float32DType | 0 (0.0%) | 194 (0.2%) | -2.10e+09 | 1.89e+08 | -2.15e+09 | -2.13e+09 | 2.58e+08 |
61 | model_29_min | Float32DType | 0 (0.0%) | 253 (0.3%) | -2.03e+09 | 1.93e+08 | -2.15e+09 | -2.07e+09 | 2.92e+08 |
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
max_plot_columns
parameter.
ID
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 92,790 (100.0%)
- Mean ± Std
- 5.80e+04 ± 3.35e+04
- Median ± IQR
- 57,961 ± 58,085
- Min | Max
- 0 | 115,985
fraud_flag
Int64DType- Null values
- 0 (0.0%)
- Unique values
- 2 (< 0.1%)
- Mean ± Std
- 0.0142 ± 0.118
- Median ± IQR
- 0 ± 0
- Min | Max
- 0 | 1
item_00_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 50 (< 0.1%)
- Mean ± Std
- -2.11e+09 ± 4.90e+07
- Median ± IQR
- -2.12e+09 ± 0.00
- Min | Max
- -2.15e+09 | -1.04e+09
item_01_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 37 (< 0.1%)
- Mean ± Std
- -1.96e+09 ± 2.15e+08
- Median ± IQR
- -2.09e+09 ± 4.74e+08
- Min | Max
- -2.14e+09 | -1.12e+09
item_02_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 47 (< 0.1%)
- Mean ± Std
- -2.02e+09 ± 1.52e+08
- Median ± IQR
- -2.09e+09 ± 3.47e+08
- Min | Max
- -2.14e+09 | -6.79e+08
item_03_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 37 (< 0.1%)
- Mean ± Std
- -2.08e+09 ± 4.41e+07
- Median ± IQR
- -2.08e+09 ± 5.19e+07
- Min | Max
- -2.15e+09 | -8.27e+08
item_04_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 44 (< 0.1%)
- Mean ± Std
- -2.04e+09 ± 3.26e+07
- Median ± IQR
- -2.05e+09 ± 0.00
- Min | Max
- -2.15e+09 | -1.08e+09
item_05_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 44 (< 0.1%)
- Mean ± Std
- -2.05e+09 ± 7.20e+07
- Median ± IQR
- -2.07e+09 ± 2.47e+07
- Min | Max
- -2.14e+09 | -8.93e+08
item_06_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 55 (< 0.1%)
- Mean ± Std
- -1.86e+09 ± 3.09e+08
- Median ± IQR
- -2.03e+09 ± 6.68e+08
- Min | Max
- -2.14e+09 | -5.96e+08
item_07_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 44 (< 0.1%)
- Mean ± Std
- -2.02e+09 ± 5.24e+07
- Median ± IQR
- -2.00e+09 ± 1.36e+07
- Min | Max
- -2.14e+09 | -1.20e+09
item_08_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 48 (< 0.1%)
- Mean ± Std
- -2.00e+09 ± 9.91e+07
- Median ± IQR
- -2.02e+09 ± 2.12e+08
- Min | Max
- -2.15e+09 | -1.46e+09
item_09_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 42 (< 0.1%)
- Mean ± Std
- -2.08e+09 ± 4.46e+07
- Median ± IQR
- -2.06e+09 ± 2.49e+07
- Min | Max
- -2.14e+09 | 7.04e+08
item_10_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 43 (< 0.1%)
- Mean ± Std
- -2.04e+09 ± 6.49e+07
- Median ± IQR
- -2.06e+09 ± 1.43e+08
- Min | Max
- -2.14e+09 | -1.07e+09
item_11_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 32 (< 0.1%)
- Mean ± Std
- -2.14e+09 ± 2.30e+07
- Median ± IQR
- -2.14e+09 ± 0.00
- Min | Max
- -2.14e+09 | -1.23e+09
item_12_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 36 (< 0.1%)
- Mean ± Std
- -2.06e+09 ± 6.49e+07
- Median ± IQR
- -2.09e+09 ± 1.31e+08
- Min | Max
- -2.14e+09 | -1.05e+09
item_13_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 42 (< 0.1%)
- Mean ± Std
- -2.09e+09 ± 3.74e+07
- Median ± IQR
- -2.10e+09 ± 0.00
- Min | Max
- -2.15e+09 | -1.16e+09
item_14_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 50 (< 0.1%)
- Mean ± Std
- -2.02e+09 ± 1.28e+08
- Median ± IQR
- -2.09e+09 ± 2.40e+08
- Min | Max
- -2.15e+09 | -9.70e+08
item_15_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 43 (< 0.1%)
- Mean ± Std
- -2.02e+09 ± 9.49e+07
- Median ± IQR
- -2.03e+09 ± 2.34e+08
- Min | Max
- -2.15e+09 | -8.00e+08
item_16_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 51 (< 0.1%)
- Mean ± Std
- -2.07e+09 ± 6.56e+07
- Median ± IQR
- -2.07e+09 ± 4.37e+07
- Min | Max
- -2.15e+09 | -1.34e+09
item_17_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 42 (< 0.1%)
- Mean ± Std
- -2.07e+09 ± 6.55e+07
- Median ± IQR
- -2.04e+09 ± 9.28e+07
- Min | Max
- -2.15e+09 | -1.33e+09
item_18_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 50 (< 0.1%)
- Mean ± Std
- -2.03e+09 ± 7.36e+07
- Median ± IQR
- -2.02e+09 ± 1.73e+08
- Min | Max
- -2.14e+09 | -1.56e+09
item_19_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 35 (< 0.1%)
- Mean ± Std
- -2.09e+09 ± 5.63e+07
- Median ± IQR
- -2.13e+09 ± 1.09e+08
- Min | Max
- -2.15e+09 | -1.01e+09
item_20_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 37 (< 0.1%)
- Mean ± Std
- -2.10e+09 ± 6.33e+07
- Median ± IQR
- -2.10e+09 ± 4.08e+07
- Min | Max
- -2.14e+09 | -5.10e+06
item_21_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 45 (< 0.1%)
- Mean ± Std
- -2.09e+09 ± 5.48e+07
- Median ± IQR
- -2.11e+09 ± 8.80e+07
- Min | Max
- -2.14e+09 | -8.74e+08
item_22_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 37 (< 0.1%)
- Mean ± Std
- -2.07e+09 ± 2.29e+07
- Median ± IQR
- -2.06e+09 ± 0.00
- Min | Max
- -2.14e+09 | -7.91e+08
item_23_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 41 (< 0.1%)
- Mean ± Std
- -2.09e+09 ± 4.68e+07
- Median ± IQR
- -2.08e+09 ± 2.15e+07
- Min | Max
- -2.15e+09 | -7.27e+08
item_24_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 38 (< 0.1%)
- Mean ± Std
- -2.10e+09 ± 4.13e+07
- Median ± IQR
- -2.09e+09 ± 3.31e+06
- Min | Max
- -2.14e+09 | -5.35e+08
item_25_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 51 (< 0.1%)
- Mean ± Std
- -1.94e+09 ± 1.84e+08
- Median ± IQR
- -2.02e+09 ± 4.25e+08
- Min | Max
- -2.14e+09 | -9.00e+08
item_26_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 54 (< 0.1%)
- Mean ± Std
- -1.97e+09 ± 1.27e+08
- Median ± IQR
- -2.02e+09 ± 2.60e+08
- Min | Max
- -2.15e+09 | -1.45e+09
item_27_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 42 (< 0.1%)
- Mean ± Std
- -2.06e+09 ± 1.30e+08
- Median ± IQR
- -2.12e+09 ± 4.35e+06
- Min | Max
- -2.15e+09 | -9.92e+08
item_28_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 53 (< 0.1%)
- Mean ± Std
- -2.12e+09 ± 5.25e+07
- Median ± IQR
- -2.12e+09 ± 0.00
- Min | Max
- -2.15e+09 | -1.14e+09
item_29_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 38 (< 0.1%)
- Mean ± Std
- -2.02e+09 ± 8.10e+07
- Median ± IQR
- -2.07e+09 ± 1.85e+08
- Min | Max
- -2.15e+09 | -1.19e+09
model_00_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 250 (0.3%)
- Mean ± Std
- -2.06e+09 ± 2.03e+08
- Median ± IQR
- -2.09e+09 ± 5.38e+07
- Min | Max
- -2.15e+09 | 0.00
model_01_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 140 (0.2%)
- Mean ± Std
- -2.10e+09 ± 1.91e+08
- Median ± IQR
- -2.14e+09 ± 4.84e+07
- Min | Max
- -2.15e+09 | 0.00
model_02_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 162 (0.2%)
- Mean ± Std
- -2.10e+09 ± 1.85e+08
- Median ± IQR
- -2.12e+09 ± 8.23e+06
- Min | Max
- -2.15e+09 | 4.22e+07
model_03_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 188 (0.2%)
- Mean ± Std
- -2.09e+09 ± 1.86e+08
- Median ± IQR
- -2.12e+09 ± 9.76e+06
- Min | Max
- -2.15e+09 | 0.00
model_04_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 263 (0.3%)
- Mean ± Std
- -2.05e+09 ± 1.91e+08
- Median ± IQR
- -2.10e+09 ± 9.02e+07
- Min | Max
- -2.15e+09 | 0.00
model_05_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 151 (0.2%)
- Mean ± Std
- -2.09e+09 ± 1.82e+08
- Median ± IQR
- -2.10e+09 ± 1.83e+07
- Min | Max
- -2.15e+09 | 0.00
model_06_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 180 (0.2%)
- Mean ± Std
- -2.07e+09 ± 2.22e+08
- Median ± IQR
- -2.12e+09 ± 5.97e+07
- Min | Max
- -2.15e+09 | 0.00
model_07_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 200 (0.2%)
- Mean ± Std
- -2.07e+09 ± 1.89e+08
- Median ± IQR
- -2.09e+09 ± 3.57e+07
- Min | Max
- -2.15e+09 | 0.00
model_08_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 212 (0.2%)
- Mean ± Std
- -2.06e+09 ± 2.02e+08
- Median ± IQR
- -2.09e+09 ± 5.20e+07
- Min | Max
- -2.15e+09 | 0.00
model_09_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 166 (0.2%)
- Mean ± Std
- -2.08e+09 ± 1.91e+08
- Median ± IQR
- -2.11e+09 ± 4.71e+07
- Min | Max
- -2.15e+09 | 0.00
model_10_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 205 (0.2%)
- Mean ± Std
- -2.08e+09 ± 1.86e+08
- Median ± IQR
- -2.09e+09 ± 1.52e+07
- Min | Max
- -2.15e+09 | 1.05e+09
model_11_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 155 (0.2%)
- Mean ± Std
- -2.09e+09 ± 1.83e+08
- Median ± IQR
- -2.11e+09 ± 1.82e+07
- Min | Max
- -2.15e+09 | 0.00
model_12_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 274 (0.3%)
- Mean ± Std
- -2.05e+09 ± 2.03e+08
- Median ± IQR
- -2.10e+09 ± 7.73e+07
- Min | Max
- -2.15e+09 | 0.00
model_13_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 161 (0.2%)
- Mean ± Std
- -2.09e+09 ± 1.81e+08
- Median ± IQR
- -2.10e+09 ± 1.81e+07
- Min | Max
- -2.15e+09 | 0.00
model_14_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 139 (0.1%)
- Mean ± Std
- -2.10e+09 ± 1.85e+08
- Median ± IQR
- -2.13e+09 ± 4.04e+07
- Min | Max
- -2.15e+09 | 0.00
model_15_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 171 (0.2%)
- Mean ± Std
- -2.07e+09 ± 1.89e+08
- Median ± IQR
- -2.11e+09 ± 1.06e+08
- Min | Max
- -2.15e+09 | 0.00
model_16_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 253 (0.3%)
- Mean ± Std
- -2.03e+09 ± 2.07e+08
- Median ± IQR
- -2.06e+09 ± 4.92e+07
- Min | Max
- -2.15e+09 | 0.00
model_17_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 204 (0.2%)
- Mean ± Std
- -2.07e+09 ± 2.44e+08
- Median ± IQR
- -2.13e+09 ± 1.38e+07
- Min | Max
- -2.15e+09 | 0.00
model_18_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 208 (0.2%)
- Mean ± Std
- -2.06e+09 ± 1.82e+08
- Median ± IQR
- -2.06e+09 ± 6.80e+07
- Min | Max
- -2.15e+09 | 0.00
model_19_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 94 (0.1%)
- Mean ± Std
- -2.12e+09 ± 1.85e+08
- Median ± IQR
- -2.14e+09 ± 3.72e+06
- Min | Max
- -2.15e+09 | 0.00
model_20_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 228 (0.2%)
- Mean ± Std
- -2.08e+09 ± 2.01e+08
- Median ± IQR
- -2.13e+09 ± 3.88e+07
- Min | Max
- -2.15e+09 | 0.00
model_21_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 140 (0.2%)
- Mean ± Std
- -2.10e+09 ± 1.88e+08
- Median ± IQR
- -2.14e+09 ± 3.71e+07
- Min | Max
- -2.15e+09 | 1.15e+09
model_22_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 230 (0.2%)
- Mean ± Std
- -2.04e+09 ± 2.04e+08
- Median ± IQR
- -2.08e+09 ± 7.71e+07
- Min | Max
- -2.15e+09 | 6.53e+08
model_23_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 242 (0.3%)
- Mean ± Std
- -2.07e+09 ± 2.10e+08
- Median ± IQR
- -2.11e+09 ± 7.93e+07
- Min | Max
- -2.15e+09 | 9.93e+08
model_24_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 182 (0.2%)
- Mean ± Std
- -2.09e+09 ± 1.86e+08
- Median ± IQR
- -2.14e+09 ± 7.00e+07
- Min | Max
- -2.15e+09 | 0.00
model_25_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 183 (0.2%)
- Mean ± Std
- -2.08e+09 ± 1.92e+08
- Median ± IQR
- -2.11e+09 ± 1.71e+07
- Min | Max
- -2.15e+09 | 0.00
model_26_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 200 (0.2%)
- Mean ± Std
- -2.07e+09 ± 1.89e+08
- Median ± IQR
- -2.09e+09 ± 2.95e+07
- Min | Max
- -2.15e+09 | 1.34e+08
model_27_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 134 (0.1%)
- Mean ± Std
- -2.08e+09 ± 1.85e+08
- Median ± IQR
- -2.10e+09 ± 6.32e+07
- Min | Max
- -2.15e+09 | 0.00
model_28_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 194 (0.2%)
- Mean ± Std
- -2.10e+09 ± 1.89e+08
- Median ± IQR
- -2.13e+09 ± 3.58e+07
- Min | Max
- -2.15e+09 | 2.58e+08
model_29_min
Float32DType- Null values
- 0 (0.0%)
- Unique values
- 253 (0.3%)
- Mean ± Std
- -2.03e+09 ± 1.93e+08
- Median ± IQR
- -2.07e+09 ± 1.46e+08
- Min | Max
- -2.15e+09 | 2.92e+08
No columns match the selected filter: . You can change the column filter in the dropdown menu above.
Column 1 | Column 2 | Cramér's V | Pearson's Correlation |
---|---|---|---|
model_15_min | model_21_min | 1.00 | 0.946 |
model_01_min | model_02_min | 1.00 | 0.951 |
model_02_min | model_04_min | 1.00 | 0.936 |
model_02_min | model_03_min | 1.00 | 0.975 |
model_02_min | model_21_min | 1.00 | 0.958 |
model_02_min | model_22_min | 1.00 | 0.891 |
model_02_min | model_23_min | 1.00 | 0.895 |
model_02_min | model_19_min | 1.00 | 0.984 |
model_02_min | model_20_min | 1.00 | 0.919 |
model_06_min | model_21_min | 1.00 | 0.817 |
model_03_min | model_10_min | 1.00 | 0.946 |
model_02_min | model_07_min | 1.00 | 0.953 |
model_02_min | model_14_min | 1.00 | 0.978 |
model_01_min | model_03_min | 1.00 | 0.947 |
model_02_min | model_10_min | 1.00 | 0.946 |
model_02_min | model_27_min | 1.00 | 0.969 |
model_02_min | model_08_min | 1.00 | 0.912 |
model_02_min | model_06_min | 1.00 | 0.856 |
model_01_min | model_21_min | 1.00 | 0.954 |
model_02_min | model_15_min | 1.00 | 0.944 |
Please enable javascript
The skrub table reports need javascript to display correctly. If you are displaying a report in a Jupyter notebook and you see this message, you may need to re-execute the cell or to trust the notebook (button on the top right or "File > Trust notebook").
Now that we understand how to use the AggJoiner
, we can now assemble our pipeline by
chaining two AggJoiner
together:
the first one to deal with the
MinHashEncoder
vectors as we just sawthe second one to deal with the all the other columns
For the second AggJoiner
, we use the mean, standard deviation, minimum and maximum
operations to extract a representative summary of each distribution.
DropCols
is another skrub transformer which removes the “ID” column, which doesn’t
bring any information after the joining operation.
from scipy.stats import loguniform, randint
from sklearn.ensemble import HistGradientBoostingClassifier
from sklearn.pipeline import make_pipeline
from skrub import DropCols
model = make_pipeline(
AggJoiner(
aux_table=products_transformed,
aux_key="basket_ID",
main_key="ID",
cols=minhash_cols,
operations=["min"],
),
AggJoiner(
aux_table=products_transformed,
aux_key="basket_ID",
main_key="ID",
cols=["make", "goods_code", "cash_price", "Nbr_of_prod_purchas"],
operations=["sum", "mean", "std", "min", "max"],
),
DropCols(["ID"]),
HistGradientBoostingClassifier(),
)
model
Pipeline(steps=[('aggjoiner-1', AggJoiner(aux_key='basket_ID', aux_table= basket_ID item_00 ... goods_code Nbr_of_prod_purchas 0 85517.0 -2.119082e+09 ... 11181.0 1.0 1 51113.0 -2.119082e+09 ... 10552.0 1.0 2 83008.0 -2.128260e+09 ... 12038.0 1.0 3 78712.0 -2.119082e+09 ... 10513.0 1.0 4 78712.0 -2.119082e+09 ... 4925.0 1.0 ... ... ... ... ... ... 163352 42613.0 -1.944861e+09 ... 2807.0 1.0 163353... 163354 43567.0 -2.119082e+09 ... 13080.0 1.0 163355 43567.0 -2.119082e+09 ... 9971.0 1.0 163356 68268.0 -2.128260e+09 ... 12106.0 1.0 [163357 rows x 65 columns], cols=['make', 'goods_code', 'cash_price', 'Nbr_of_prod_purchas'], main_key='ID', operations=['sum', 'mean', 'std', 'min', 'max'])), ('dropcols', DropCols(cols=['ID'])), ('histgradientboostingclassifier', HistGradientBoostingClassifier())])In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
Pipeline(steps=[('aggjoiner-1', AggJoiner(aux_key='basket_ID', aux_table= basket_ID item_00 ... goods_code Nbr_of_prod_purchas 0 85517.0 -2.119082e+09 ... 11181.0 1.0 1 51113.0 -2.119082e+09 ... 10552.0 1.0 2 83008.0 -2.128260e+09 ... 12038.0 1.0 3 78712.0 -2.119082e+09 ... 10513.0 1.0 4 78712.0 -2.119082e+09 ... 4925.0 1.0 ... ... ... ... ... ... 163352 42613.0 -1.944861e+09 ... 2807.0 1.0 163353... 163354 43567.0 -2.119082e+09 ... 13080.0 1.0 163355 43567.0 -2.119082e+09 ... 9971.0 1.0 163356 68268.0 -2.128260e+09 ... 12106.0 1.0 [163357 rows x 65 columns], cols=['make', 'goods_code', 'cash_price', 'Nbr_of_prod_purchas'], main_key='ID', operations=['sum', 'mean', 'std', 'min', 'max'])), ('dropcols', DropCols(cols=['ID'])), ('histgradientboostingclassifier', HistGradientBoostingClassifier())])
AggJoiner(aux_key='basket_ID', aux_table= basket_ID item_00 ... goods_code Nbr_of_prod_purchas 0 85517.0 -2.119082e+09 ... 11181.0 1.0 1 51113.0 -2.119082e+09 ... 10552.0 1.0 2 83008.0 -2.128260e+09 ... 12038.0 1.0 3 78712.0 -2.119082e+09 ... 10513.0 1.0 4 78712.0 -2.119082e+09 ... 4925.0 1.0 ... ... ... ... ... ... 163352 42613.0 -1.944861e+09 ... 2807.0 1.0 163353 42613.0 -1.944861e+09 ... 11464.0 1... 'model_00', 'model_01', 'model_02', 'model_03', 'model_04', 'model_05', 'model_06', 'model_07', 'model_08', 'model_09', 'model_10', 'model_11', 'model_12', 'model_13', 'model_14', 'model_15', 'model_16', 'model_17', 'model_18', 'model_19', 'model_20', 'model_21', 'model_22', 'model_23', 'model_24', 'model_25', 'model_26', 'model_27', 'model_28', 'model_29'], dtype='object'), main_key='ID', operations=['min'])
AggJoiner(aux_key='basket_ID', aux_table= basket_ID item_00 ... goods_code Nbr_of_prod_purchas 0 85517.0 -2.119082e+09 ... 11181.0 1.0 1 51113.0 -2.119082e+09 ... 10552.0 1.0 2 83008.0 -2.128260e+09 ... 12038.0 1.0 3 78712.0 -2.119082e+09 ... 10513.0 1.0 4 78712.0 -2.119082e+09 ... 4925.0 1.0 ... ... ... ... ... ... 163352 42613.0 -1.944861e+09 ... 2807.0 1.0 163353 42613.0 -1.944861e+09 ... 11464.0 1.0 163354 43567.0 -2.119082e+09 ... 13080.0 1.0 163355 43567.0 -2.119082e+09 ... 9971.0 1.0 163356 68268.0 -2.128260e+09 ... 12106.0 1.0 [163357 rows x 65 columns], cols=['make', 'goods_code', 'cash_price', 'Nbr_of_prod_purchas'], main_key='ID', operations=['sum', 'mean', 'std', 'min', 'max'])
DropCols(cols=['ID'])
HistGradientBoostingClassifier()
We tune the hyper-parameters of the HistGradientBoostingClassifier
to get a good performance.
from time import time
from sklearn.model_selection import RandomizedSearchCV
param_distributions = dict(
histgradientboostingclassifier__learning_rate=loguniform(1e-3, 1),
histgradientboostingclassifier__max_depth=randint(3, 9),
histgradientboostingclassifier__max_leaf_nodes=[None, 10, 30, 60, 90],
histgradientboostingclassifier__max_iter=randint(50, 500),
)
tic = time()
search = RandomizedSearchCV(
model,
param_distributions,
scoring="neg_log_loss",
refit=False,
n_iter=10,
cv=3,
verbose=1,
).fit(X_train, y_train)
print(f"This operation took {time() - tic:.1f}s")
Fitting 3 folds for each of 10 candidates, totalling 30 fits
This operation took 80.2s
The best hyper parameters are:
histgradientboostingclassifier__learning_rate 0.116547
histgradientboostingclassifier__max_depth 5.000000
histgradientboostingclassifier__max_iter 423.000000
histgradientboostingclassifier__max_leaf_nodes 90.000000
dtype: float64
To benchmark our performance, we plot the log loss of our model on the test set against the log loss of a dummy model that always output the observed probability of the two classes.
As this dataset is extremely imbalanced, this dummy model should be a good baseline.
The vertical bar represents one standard deviation around the mean of the cross validation log-loss.
import seaborn as sns
from matplotlib import pyplot as plt
from sklearn.dummy import DummyClassifier
from sklearn.metrics import log_loss
results = search.cv_results_
best_idx = search.best_index_
log_loss_model_mean = -results["mean_test_score"][best_idx]
log_loss_model_std = results["std_test_score"][best_idx]
dummy = DummyClassifier(strategy="prior").fit(X_train, y_train)
y_proba_dummy = dummy.predict_proba(X_test)
log_loss_dummy = log_loss(y_true=y_test, y_pred=y_proba_dummy)
fig, ax = plt.subplots()
ax.bar(
height=[log_loss_model_mean, log_loss_dummy],
x=["AggJoiner model", "Dummy"],
color=["C0", "C4"],
)
for container in ax.containers:
ax.bar_label(container, padding=4)
ax.vlines(
x="AggJoiner model",
ymin=log_loss_model_mean - log_loss_model_std,
ymax=log_loss_model_mean + log_loss_model_std,
linestyle="-",
linewidth=1,
color="k",
)
sns.despine()
ax.set_title("Log loss (lower is better)")

Text(0.5, 1.0, 'Log loss (lower is better)')
Conclusion#
With AggJoiner
, you can bring the aggregation and joining operations within a
sklearn pipeline, and train models more efficiently.
One known limitation of both the AggJoiner
and Joiner
is that the auxiliary data
to join is passed during the __init__
method instead of the fit
method, and
is therefore fixed once the model has been trained.
This limitation causes two main issues:
1. Bigger model serialization: Since the dataset has to be pickled along with the model, it can result in a massive file size on disk.
2. Inflexibility with new, unseen data in a production environment: To use new
auxiliary data, you would need to replace the auxiliary table in the AggJoiner
that
was used during fit
with the updated data, which is a rather hacky approach.
These limitations will be addressed later in skrub.
Total running time of the script: (2 minutes 45.820 seconds)