Overview

Dataset statistics

Number of variables21
Number of observations8399
Missing cells63
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory168.0 B

Variable types

CAT12
NUM9

Reproduction

Analysis started2020-09-04 08:59:34.891417
Analysis finished2020-09-04 09:00:02.160756
Duration27.27 seconds
Versionpandas-profiling v2.8.0
Command linepandas_profiling --config_file config.yaml [YOUR_FILE.csv]
Download configurationconfig.yaml

Warnings

Order Date has a high cardinality: 1418 distinct values High cardinality
Customer Name has a high cardinality: 795 distinct values High cardinality
Product Name has a high cardinality: 1263 distinct values High cardinality
Ship Date has a high cardinality: 1450 distinct values High cardinality
Order ID is highly correlated with Row IDHigh correlation
Row ID is highly correlated with Order IDHigh correlation
Region is highly correlated with ProvinceHigh correlation
Province is highly correlated with RegionHigh correlation
Product Sub-Category is highly correlated with Product CategoryHigh correlation
Product Category is highly correlated with Product Sub-CategoryHigh correlation
Row ID has unique values Unique
Discount has 756 (9.0%) zeros Zeros

Variables

Row ID
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct count8399
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4200.0
Minimum1
Maximum8399
Zeros0
Zeros (%)0.0%
Memory size65.6 KiB
2020-09-04T12:00:02.356849image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile420.9
Q12100.5
median4200
Q36299.5
95-th percentile7979.1
Maximum8399
Range8398
Interquartile range (IQR)4199

Descriptive statistics

Standard deviation2424.726789
Coefficient of variation (CV)0.5773159021
Kurtosis-1.2
Mean4200
Median Absolute Deviation (MAD)2100
Skewness0
Sum35275800
Variance5879300
2020-09-04T12:00:02.607877image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
20471< 0.1%
 
33711< 0.1%
 
74731< 0.1%
 
13301< 0.1%
 
33791< 0.1%
 
54321< 0.1%
 
74811< 0.1%
 
13381< 0.1%
 
33871< 0.1%
 
54401< 0.1%
 
Other values (8389)838999.9%
 
ValueCountFrequency (%) 
11< 0.1%
 
21< 0.1%
 
31< 0.1%
 
41< 0.1%
 
51< 0.1%
 
ValueCountFrequency (%) 
83991< 0.1%
 
83981< 0.1%
 
83971< 0.1%
 
83961< 0.1%
 
83951< 0.1%
 

Order ID
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count5496
Unique (%)65.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29965.179783307536
Minimum3
Maximum59973
Zeros0
Zeros (%)0.0%
Memory size65.6 KiB
2020-09-04T12:00:02.806250image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile2818
Q115011.5
median29857
Q344596
95-th percentile57061
Maximum59973
Range59970
Interquartile range (IQR)29584.5

Descriptive statistics

Standard deviation17260.88345
Coefficient of variation (CV)0.5760313661
Kurtosis-1.178316663
Mean29965.17978
Median Absolute Deviation (MAD)14778
Skewness0.00381089223
Sum251677545
Variance297938097.4
2020-09-04T12:00:03.025501image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
2413260.1%
 
4374560.1%
 
4845250.1%
 
1354050.1%
 
899550.1%
 
144450.1%
 
5878450.1%
 
3379750.1%
 
1206750.1%
 
1510950.1%
 
Other values (5486)834799.4%
 
ValueCountFrequency (%) 
31< 0.1%
 
61< 0.1%
 
324< 0.1%
 
352< 0.1%
 
361< 0.1%
 
ValueCountFrequency (%) 
599732< 0.1%
 
599713< 0.1%
 
599692< 0.1%
 
599431< 0.1%
 
599421< 0.1%
 

Order Date
Categorical

HIGH CARDINALITY

Distinct count1418
Unique (%)16.9%
Missing0
Missing (%)0.0%
Memory size65.6 KiB
9/15/2011
 
20
3/28/2012
 
20
12/12/2010
 
18
8/4/2010
 
17
11/19/2011
 
17
Other values (1413)
8307
ValueCountFrequency (%) 
9/15/2011200.2%
 
3/28/2012200.2%
 
12/12/2010180.2%
 
8/4/2010170.2%
 
11/19/2011170.2%
 
2/27/2010170.2%
 
4/20/2010170.2%
 
2/4/2009160.2%
 
10/30/2012160.2%
 
10/9/2010150.2%
 
Other values (1408)822697.9%
 
2020-09-04T12:00:03.404923image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.948803429
Min length8

Order Priority
Categorical

Distinct count5
Unique (%)0.1%
Missing0
Missing (%)0.0%
Memory size65.6 KiB
High
1768
Low
1720
Not Specified
1672
Medium
1631
Critical
1608
ValueCountFrequency (%) 
High176821.1%
 
Low172020.5%
 
Not Specified167219.9%
 
Medium163119.4%
 
Critical160819.1%
 
2020-09-04T12:00:03.652063image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length13
Median length6
Mean length6.7410406
Min length3

Order Quantity
Real number (ℝ≥0)

Distinct count50
Unique (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.571734730325037
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Memory size65.6 KiB
2020-09-04T12:00:03.892656image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q113
median26
Q338
95-th percentile48
Maximum50
Range49
Interquartile range (IQR)25

Descriptive statistics

Standard deviation14.48107111
Coefficient of variation (CV)0.5662920903
Kurtosis-1.208020269
Mean25.57173473
Median Absolute Deviation (MAD)13
Skewness-0.01731778213
Sum214777
Variance209.7014206
2020-09-04T12:00:04.029797image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
312022.4%
 
41962.3%
 
391952.3%
 
461932.3%
 
231922.3%
 
241922.3%
 
31892.3%
 
421892.3%
 
431842.2%
 
411832.2%
 
Other values (40)648477.2%
 
ValueCountFrequency (%) 
11652.0%
 
21521.8%
 
31892.3%
 
41962.3%
 
51662.0%
 
ValueCountFrequency (%) 
501822.2%
 
491361.6%
 
481722.0%
 
471662.0%
 
461932.3%
 

Sales
Real number (ℝ≥0)

Distinct count8153
Unique (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1775.8781788308133
Minimum2.24
Maximum89061.05
Zeros0
Zeros (%)0.0%
Memory size65.6 KiB
2020-09-04T12:00:04.197084image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2.24
5-th percentile34.178
Q1143.195
median449.42
Q31709.32
95-th percentile7844.335
Maximum89061.05
Range89058.81
Interquartile range (IQR)1566.125

Descriptive statistics

Standard deviation3585.050525
Coefficient of variation (CV)2.018748002
Kurtosis60.92837614
Mean1775.878179
Median Absolute Deviation (MAD)381.95
Skewness5.386982374
Sum14915600.82
Variance12852587.27
2020-09-04T12:00:04.357623image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
46.943< 0.1%
 
75.193< 0.1%
 
10.483< 0.1%
 
224.583< 0.1%
 
43.293< 0.1%
 
127.563< 0.1%
 
151.193< 0.1%
 
74.023< 0.1%
 
20.193< 0.1%
 
19.363< 0.1%
 
Other values (8143)836999.6%
 
ValueCountFrequency (%) 
2.241< 0.1%
 
3.21< 0.1%
 
3.231< 0.1%
 
3.411< 0.1%
 
3.421< 0.1%
 
ValueCountFrequency (%) 
89061.051< 0.1%
 
45923.761< 0.1%
 
41343.211< 0.1%
 
33367.851< 0.1%
 
29884.61< 0.1%
 

Discount
Real number (ℝ≥0)

ZEROS

Distinct count16
Unique (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04967138945112514
Minimum0.0
Maximum0.25
Zeros756
Zeros (%)9.0%
Memory size65.6 KiB
2020-09-04T12:00:04.545523image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.02
median0.05
Q30.08
95-th percentile0.1
Maximum0.25
Range0.25
Interquartile range (IQR)0.06

Descriptive statistics

Standard deviation0.0318230196
Coefficient of variation (CV)0.6406710172
Kurtosis-0.9594110633
Mean0.04967138945
Median Absolute Deviation (MAD)0.03
Skewness0.07391696254
Sum417.19
Variance0.001012704577
2020-09-04T12:00:04.685804image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.018069.6%
 
0.057869.4%
 
0.037799.3%
 
0.097789.3%
 
0.047709.2%
 
0.087659.1%
 
0.027659.1%
 
07569.0%
 
0.17458.9%
 
0.067348.7%
 
Other values (6)7158.5%
 
ValueCountFrequency (%) 
07569.0%
 
0.018069.6%
 
0.027659.1%
 
0.037799.3%
 
0.047709.2%
 
ValueCountFrequency (%) 
0.251< 0.1%
 
0.211< 0.1%
 
0.171< 0.1%
 
0.161< 0.1%
 
0.111< 0.1%
 

Ship Mode
Categorical

Distinct count3
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.6 KiB
Regular Air
6270
Delivery Truck
 
1146
Express Air
 
983
ValueCountFrequency (%) 
Regular Air627074.7%
 
Delivery Truck114613.6%
 
Express Air98311.7%
 
2020-09-04T12:00:04.962091image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length14
Median length11
Mean length11.40933444
Min length11

Profit
Real number (ℝ)

Distinct count7807
Unique (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean181.1844243362305
Minimum-14140.7
Maximum27220.69
Zeros0
Zeros (%)0.0%
Memory size65.6 KiB
2020-09-04T12:00:05.134678image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-14140.7
5-th percentile-592.439
Q1-83.315
median-1.5
Q3162.75
95-th percentile1542.309
Maximum27220.69
Range41361.39
Interquartile range (IQR)246.065

Descriptive statistics

Standard deviation1196.653371
Coefficient of variation (CV)6.604615026
Kurtosis67.34970524
Mean181.1844243
Median Absolute Deviation (MAD)104.33
Skewness3.647238938
Sum1521767.98
Variance1431979.291
2020-09-04T12:00:05.255824image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-969.0580.1%
 
11.6560.1%
 
-433.2960.1%
 
-528.6550.1%
 
-1331.5550.1%
 
-715.7850.1%
 
-505.9850.1%
 
-513.794< 0.1%
 
-66.874< 0.1%
 
0.354< 0.1%
 
Other values (7797)834799.4%
 
ValueCountFrequency (%) 
-14140.71< 0.1%
 
-125581< 0.1%
 
-11984.41< 0.1%
 
-11861.461< 0.1%
 
-11769.171< 0.1%
 
ValueCountFrequency (%) 
27220.691< 0.1%
 
14440.391< 0.1%
 
13340.261< 0.1%
 
12748.861< 0.1%
 
12606.811< 0.1%
 

Unit Price
Real number (ℝ≥0)

Distinct count751
Unique (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.34625907846171
Minimum0.99
Maximum6783.02
Zeros0
Zeros (%)0.0%
Memory size65.6 KiB
2020-09-04T12:00:05.425382image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0.99
5-th percentile2.88
Q16.48
median20.99
Q385.99
95-th percentile320.64
Maximum6783.02
Range6782.03
Interquartile range (IQR)79.51

Descriptive statistics

Standard deviation290.354383
Coefficient of variation (CV)3.249765418
Kurtosis271.1687334
Mean89.34625908
Median Absolute Deviation (MAD)17.01
Skewness14.12779334
Sum750419.23
Variance84305.66773
2020-09-04T12:00:05.616005image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
6.482643.1%
 
65.991922.3%
 
4.981361.6%
 
125.991151.4%
 
5.981021.2%
 
2.88811.0%
 
30.98730.9%
 
20.99730.9%
 
35.99700.8%
 
205.99660.8%
 
Other values (741)722786.0%
 
ValueCountFrequency (%) 
0.992< 0.1%
 
1.14100.1%
 
1.26130.2%
 
1.48120.1%
 
1.650.1%
 
ValueCountFrequency (%) 
6783.0270.1%
 
3502.1460.1%
 
3499.9970.1%
 
2550.1470.1%
 
2036.4860.1%
 

Shipping Cost
Real number (ℝ≥0)

Distinct count652
Unique (%)7.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.838556971067984
Minimum0.49
Maximum164.73
Zeros0
Zeros (%)0.0%
Memory size65.6 KiB
2020-09-04T12:00:05.788731image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0.49
5-th percentile0.8
Q13.3
median6.07
Q313.99
95-th percentile55.351
Maximum164.73
Range164.24
Interquartile range (IQR)10.69

Descriptive statistics

Standard deviation17.26405197
Coefficient of variation (CV)1.344703459
Kurtosis7.751587174
Mean12.83855697
Median Absolute Deviation (MAD)3.61
Skewness2.553800841
Sum107831.04
Variance298.0474903
2020-09-04T12:00:05.953668image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
19.993524.2%
 
8.993213.8%
 
1.992472.9%
 
0.51902.3%
 
0.991441.7%
 
41431.7%
 
1.491381.6%
 
0.71381.6%
 
24.491321.6%
 
2.991241.5%
 
Other values (642)647077.0%
 
ValueCountFrequency (%) 
0.49340.4%
 
0.51902.3%
 
0.71381.6%
 
0.71220.3%
 
0.731< 0.1%
 
ValueCountFrequency (%) 
164.731< 0.1%
 
154.121< 0.1%
 
147.122< 0.1%
 
143.711< 0.1%
 
1301< 0.1%
 

Customer Name
Categorical

HIGH CARDINALITY

Distinct count795
Unique (%)9.5%
Missing0
Missing (%)0.0%
Memory size65.6 KiB
Darren Budd
 
41
Ed Braxton
 
38
Brad Thomas
 
35
Carlos Soltero
 
33
Patrick Jones
 
30
Other values (790)
8222
ValueCountFrequency (%) 
Darren Budd410.5%
 
Ed Braxton380.5%
 
Brad Thomas350.4%
 
Carlos Soltero330.4%
 
Patrick Jones300.4%
 
Tony Sayre290.3%
 
Lena Creighton280.3%
 
Joy Smith280.3%
 
Jack O'Briant280.3%
 
Giulietta Dortch280.3%
 
Other values (785)808196.2%
 
2020-09-04T12:00:06.201430image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length22
Median length13
Mean length12.86712704
Min length7

Province
Categorical

HIGH CORRELATION

Distinct count13
Unique (%)0.2%
Missing0
Missing (%)0.0%
Memory size65.6 KiB
Ontario
1826
British Columbia
1126
Saskachewan
913
Alberta
865
Manitoba
793
Other values (8)
2876
ValueCountFrequency (%) 
Ontario182621.7%
 
British Columbia112613.4%
 
Saskachewan91310.9%
 
Alberta86510.3%
 
Manitoba7939.4%
 
Quebec7819.3%
 
Yukon5426.5%
 
Nova Scotia4645.5%
 
Northwest Territories3944.7%
 
New Brunswick3233.8%
 
Other values (3)3724.4%
 
2020-09-04T12:00:06.476377image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length21
Median length8
Mean length9.997618764
Min length5

Region
Categorical

HIGH CORRELATION

Distinct count8
Unique (%)0.1%
Missing0
Missing (%)0.0%
Memory size65.6 KiB
West
1991
Ontario
1826
Prarie
1706
Atlantic
1080
Quebec
781
Other values (3)
1015
ValueCountFrequency (%) 
West199123.7%
 
Ontario182621.7%
 
Prarie170620.3%
 
Atlantic108012.9%
 
Quebec7819.3%
 
Yukon5426.5%
 
Northwest Territories3944.7%
 
Nunavut790.9%
 
2020-09-04T12:00:06.819876image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length21
Median length6
Mean length6.649005834
Min length4

Customer Segment
Categorical

Distinct count4
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.6 KiB
Corporate
3076
Home Office
2032
Consumer
1649
Small Business
1642
ValueCountFrequency (%) 
Corporate307636.6%
 
Home Office203224.2%
 
Consumer164919.6%
 
Small Business164219.5%
 
2020-09-04T12:00:07.175335image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length14
Median length9
Mean length10.26503155
Min length8

Product Category
Categorical

HIGH CORRELATION

Distinct count3
Unique (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.6 KiB
Office Supplies
4610
Technology
2065
Furniture
1724
ValueCountFrequency (%) 
Office Supplies461054.9%
 
Technology206524.6%
 
Furniture172420.5%
 
2020-09-04T12:00:07.512042image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length15
Median length15
Mean length12.5391118
Min length9

Product Sub-Category
Categorical

HIGH CORRELATION

Distinct count17
Unique (%)0.2%
Missing0
Missing (%)0.0%
Memory size65.6 KiB
Paper
1225
Binders and Binder Accessories
915
Telephones and Communication
883
Office Furnishings
788
Computer Peripherals
 
758
Other values (12)
3830
ValueCountFrequency (%) 
Paper122514.6%
 
Binders and Binder Accessories91510.9%
 
Telephones and Communication88310.5%
 
Office Furnishings7889.4%
 
Computer Peripherals7589.0%
 
Pens & Art Supplies6337.5%
 
Storage & Organization5466.5%
 
Appliances4345.2%
 
Chairs & Chairmats3864.6%
 
Tables3614.3%
 
Other values (7)147017.5%
 
2020-09-04T12:00:07.757748image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length30
Median length18
Mean length17.08096202
Min length5

Product Name
Categorical

HIGH CARDINALITY

Distinct count1263
Unique (%)15.0%
Missing0
Missing (%)0.0%
Memory size65.6 KiB
Global High-Back Leather Tilter, Burgundy
 
24
Master Giant Foot® Doorstop, Safety Yellow
 
22
Bevis 36 x 72 Conference Tables
 
22
Fiskars® Softgrip Scissors
 
22
BoxOffice By Design Rectangular and Half-Moon Meeting Room Tables
 
22
Other values (1258)
8287
ValueCountFrequency (%) 
Global High-Back Leather Tilter, Burgundy240.3%
 
Master Giant Foot® Doorstop, Safety Yellow220.3%
 
Bevis 36 x 72 Conference Tables220.3%
 
Fiskars® Softgrip Scissors220.3%
 
BoxOffice By Design Rectangular and Half-Moon Meeting Room Tables220.3%
 
Wilson Jones Hanging View Binder, White, 1"210.3%
 
StarTAC 7760200.2%
 
80 Minute CD-R Spindle, 100/Pack - Staples200.2%
 
Peel & Seel® Recycled Catalog Envelopes, Brown190.2%
 
Office Star - Mid Back Dual function Ergonomic High Back Chair with 2-Way Adjustable Arms190.2%
 
Other values (1253)818897.5%
 
2020-09-04T12:00:07.993270image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length98
Median length34
Mean length34.35170854
Min length3
Distinct count7
Unique (%)0.1%
Missing0
Missing (%)0.0%
Memory size65.6 KiB
Small Box
4347
Wrap Bag
1168
Small Pack
956
Jumbo Drum
 
624
Jumbo Box
 
532
Other values (2)
 
772
ValueCountFrequency (%) 
Small Box434751.8%
 
Wrap Bag116813.9%
 
Small Pack95611.4%
 
Jumbo Drum6247.4%
 
Jumbo Box5326.3%
 
Large Box4064.8%
 
Medium Box3664.4%
 
2020-09-04T12:00:08.456771image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length10
Median length9
Mean length9.092630075
Min length8

Product Base Margin
Real number (ℝ≥0)

Distinct count51
Unique (%)0.6%
Missing63
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.5125131957773512
Minimum0.35
Maximum0.85
Zeros0
Zeros (%)0.0%
Memory size65.6 KiB
2020-09-04T12:00:08.811721image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0.35
5-th percentile0.36
Q10.38
median0.52
Q30.59
95-th percentile0.78
Maximum0.85
Range0.5
Interquartile range (IQR)0.21

Descriptive statistics

Standard deviation0.1355889411
Coefficient of variation (CV)0.2645569758
Kurtosis-0.6608702254
Mean0.5125131958
Median Absolute Deviation (MAD)0.12
Skewness0.5593995872
Sum4272.31
Variance0.01838436095
2020-09-04T12:00:09.416011image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.377619.1%
 
0.386788.1%
 
0.366287.5%
 
0.594975.9%
 
0.394825.7%
 
0.564595.5%
 
0.574595.5%
 
0.44084.9%
 
0.583874.6%
 
0.553143.7%
 
Other values (41)326338.8%
 
ValueCountFrequency (%) 
0.352623.1%
 
0.366287.5%
 
0.377619.1%
 
0.386788.1%
 
0.394825.7%
 
ValueCountFrequency (%) 
0.85360.4%
 
0.84250.3%
 
0.83831.0%
 
0.82320.4%
 
0.81730.9%
 

Ship Date
Categorical

HIGH CARDINALITY

Distinct count1450
Unique (%)17.3%
Missing0
Missing (%)0.0%
Memory size65.6 KiB
5/21/2011
 
19
4/11/2009
 
16
3/30/2012
 
16
10/9/2009
 
16
5/9/2012
 
15
Other values (1445)
8317
ValueCountFrequency (%) 
5/21/2011190.2%
 
4/11/2009160.2%
 
3/30/2012160.2%
 
10/9/2009160.2%
 
5/9/2012150.2%
 
10/4/2012150.2%
 
3/28/2009150.2%
 
4/15/2012140.2%
 
8/16/2009140.2%
 
5/27/2012140.2%
 
Other values (1440)824598.2%
 
2020-09-04T12:00:10.368260image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.9495178
Min length8

Interactions

2020-09-04T11:59:42.771227image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-04T11:59:43.074705image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-04T11:59:43.305895image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-04T11:59:43.479833image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-04T11:59:43.657881image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-09-04T11:59:43.847739image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/