Overview

Dataset statistics

Number of variables11
Number of observations18759
Missing cells0
Missing cells (%)0.0%
Total size in memory1.6 MiB
Average record size in memory88.0 B

Variable types

Categorical9
Numeric2

Alerts

下单日期 has a high cardinality: 69 distinct valuesHigh cardinality
签收状态 is highly imbalanced (68.5%)Imbalance
客户来源 is highly imbalanced (53.6%)Imbalance

Reproduction

Analysis started2023-06-23 08:53:57.073636
Analysis finished2023-06-23 08:53:57.416653
Duration0.34 seconds
Software versionpandas-profiling v3.6.6
Download configurationconfig.json

Variables

回访人
Categorical

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size146.7 KiB
staff_A
1618 
staff_B
1613 
staff_C
1607 
staff_D
1599 
staff_E
1596 
Other values (9)
10726 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowstaff_A
2nd rowstaff_B
3rd rowstaff_C
4th rowstaff_D
5th rowstaff_E

Common Values

ValueCountFrequency (%)
staff_A 1618
8.6%
staff_B 1613
8.6%
staff_C 1607
8.6%
staff_D 1599
8.5%
staff_E 1596
8.5%
staff_F 1590
8.5%
staff_G 1589
8.5%
staff_H 1589
8.5%
staff_I 1585
8.4%
staff_J 1582
8.4%
Other values (4) 2791
14.9%

下单日期
Categorical

Distinct69
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size146.7 KiB
2023-03-31
 
398
2023-02-23
 
383
2023-03-08
 
364
2023-03-06
 
360
2023-03-20
 
357
Other values (64)
16897 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-03-01
2nd row2023-03-01
3rd row2023-03-01
4th row2023-03-01
5th row2023-03-01

Common Values

ValueCountFrequency (%)
2023-03-31 398
 
2.1%
2023-02-23 383
 
2.0%
2023-03-08 364
 
1.9%
2023-03-06 360
 
1.9%
2023-03-20 357
 
1.9%
2023-03-10 347
 
1.8%
2023-03-09 345
 
1.8%
2023-03-27 342
 
1.8%
2023-04-18 340
 
1.8%
2023-04-21 340
 
1.8%
Other values (59) 15183
80.9%

商品名称
Categorical

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size146.7 KiB
product_A
5002 
others[262]
4902 
product_B
3746 
product_C
1084 
product_D
1050 
Other values (5)
2975 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowproduct_A
2nd rowothers[262]
3rd rowothers[262]
4th rowproduct_F
5th rowproduct_A

Common Values

ValueCountFrequency (%)
product_A 5002
26.7%
others[262] 4902
26.1%
product_B 3746
20.0%
product_C 1084
 
5.8%
product_D 1050
 
5.6%
product_E 1048
 
5.6%
product_F 631
 
3.4%
product_G 475
 
2.5%
product_H 426
 
2.3%
product_I 395
 
2.1%

Common Values (Plot)

2023-06-23T16:53:57.689669image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

订单金额
Real number (ℝ)

Distinct365
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean158.6849752
Minimum0
Maximum1680
Zeros161
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size146.7 KiB
2023-06-23T16:53:58.074685image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile85
Q189
median169
Q3179
95-th percentile268
Maximum1680
Range1680
Interquartile range (IQR)90

Descriptive statistics

Standard deviation72.58462908
Coefficient of variation (CV)0.4574133687
Kurtosis31.35546115
Mean158.6849752
Median Absolute Deviation (MAD)37
Skewness2.885863171
Sum2976771.45
Variance5268.528378
MonotonicityNot monotonic
2023-06-23T16:53:58.434703image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
179 4979
26.5%
89 2642
14.1%
85 1264
 
6.7%
169 1057
 
5.6%
138 1035
 
5.5%
258 1019
 
5.4%
146 534
 
2.8%
155 420
 
2.2%
118 411
 
2.2%
115 378
 
2.0%
Other values (355) 5020
26.8%
ValueCountFrequency (%)
0 161
0.9%
7.3 2
 
< 0.1%
9.42 1
 
< 0.1%
10 12
 
0.1%
10.4 1
 
< 0.1%
ValueCountFrequency (%)
1680 1
< 0.1%
1453 1
< 0.1%
1134 1
< 0.1%
1075 1
< 0.1%
1057 1
< 0.1%

客户地址
Categorical

Distinct31
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size146.7 KiB
江苏省
1471 
山东省
1340 
辽宁省
 
1169
河南省
 
1164
河北省
 
1014
Other values (26)
12601 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row四川省
2nd row上海市
3rd row广西壮族自治区
4th row福建省
5th row湖南省

Common Values

ValueCountFrequency (%)
江苏省 1471
 
7.8%
山东省 1340
 
7.1%
辽宁省 1169
 
6.2%
河南省 1164
 
6.2%
河北省 1014
 
5.4%
广东省 913
 
4.9%
四川省 909
 
4.8%
湖北省 805
 
4.3%
黑龙江省 780
 
4.2%
湖南省 733
 
3.9%
Other values (21) 8461
45.1%

签收状态
Categorical

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size146.7 KiB
已签收
16134 
拒收
 
1094
派送中
 
726
在途中
 
329
已揽收
 
180
Other values (2)
 
296

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row已签收
2nd row已签收
3rd row已签收
4th row已签收
5th row已签收

Common Values

ValueCountFrequency (%)
已签收 16134
86.0%
拒收 1094
 
5.8%
派送中 726
 
3.9%
在途中 329
 
1.8%
已揽收 180
 
1.0%
退回 155
 
0.8%
141
 
0.8%

Common Values (Plot)

2023-06-23T16:53:58.832725image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

客户来源
Categorical

Distinct17
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size146.7 KiB
今日头条
10669 
客服转接
3522 
百度信息流
2230 
1340 
短信渠道
 
425
Other values (12)
 
573

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row今日头条
2nd row客服转接
3rd row客服转接
4th row客服转接
5th row今日头条

Common Values

ValueCountFrequency (%)
今日头条 10669
56.9%
客服转接 3522
 
18.8%
百度信息流 2230
 
11.9%
1340
 
7.1%
短信渠道 425
 
2.3%
微信（广告） 305
 
1.6%
400热线 91
 
0.5%
在线咨询-小6 83
 
0.4%
广告（老客） 22
 
0.1%
VIVO 21
 
0.1%
Other values (7) 51
 
0.3%

性别
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size146.7 KiB
男
14705 
女
2405 
未知
1649 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row男
2nd row男
3rd row男
4th row男
5th row男

Common Values

ValueCountFrequency (%)
男 14705
78.4%
女 2405
 
12.8%
未知 1649
 
8.8%

Common Values (Plot)

2023-06-23T16:53:59.226744image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

呼叫方式
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size146.7 KiB
去电
12966 
来电
4753 
未知
 
1040

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row去电
2nd row来电
3rd row来电
4th row来电
5th row去电

Common Values

ValueCountFrequency (%)
去电 12966
69.1%
来电 4753
 
25.3%
未知 1040
 
5.5%

Common Values (Plot)

2023-06-23T16:53:59.514848image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

回访日期
Categorical

Distinct48
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size146.7 KiB
2023-03-20
 
770
2023-03-17
 
709
2023-03-16
 
668
2023-04-07
 
589
2023-04-01
 
579
Other values (43)
15444 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-03-10
2nd row2023-03-10
3rd row2023-03-10
4th row2023-03-10
5th row2023-03-10

Common Values

ValueCountFrequency (%)
2023-03-20 770
 
4.1%
2023-03-17 709
 
3.8%
2023-03-16 668
 
3.6%
2023-04-07 589
 
3.1%
2023-04-01 579
 
3.1%
2023-03-21 558
 
3.0%
2023-04-27 556
 
3.0%
2023-04-03 552
 
2.9%
2023-04-25 543
 
2.9%
2023-03-13 531
 
2.8%
Other values (38) 12704
67.7%

下单时间
Real number (ℝ)

Distinct18
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.28695559
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size146.7 KiB
2023-06-23T16:53:59.804845image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q110
median14
Q316
95-th percentile18
Maximum23
Range22
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.204548143
Coefficient of variation (CV)0.2411800145
Kurtosis-1.005923739
Mean13.28695559
Median Absolute Deviation (MAD)3
Skewness0.07950220692
Sum249250
Variance10.2691288
MonotonicityNot monotonic
2023-06-23T16:54:00.060819image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
15 2369
12.6%
14 2353
12.5%
10 2266
12.1%
11 2230
11.9%
16 2136
11.4%
9 2052
10.9%
17 1527
8.1%
13 789
 
4.2%
18 776
 
4.1%
12 679
 
3.6%
Other values (8) 1582
8.4%
ValueCountFrequency (%)
1 2
 
< 0.1%
7 82
 
0.4%
8 626
 
3.3%
9 2052
10.9%
10 2266
12.1%
ValueCountFrequency (%)
23 12
 
0.1%
22 12
 
0.1%
21 25
 
0.1%
20 321
1.7%
19 502
2.7%