Overview

Dataset statistics

Number of variables13
Number of observations99
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.9 KiB
Average record size in memory112.3 B

Variable types

Categorical9
Numeric4

Dataset

DescriptionSample
Author(주)제로투원파트너스
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=ZTO011TOTALCGISTYLE

Alerts

MT has constant value ""Constant
201901 has constant value ""Constant
의류스타일러 has constant value ""Constant
1131 is highly overall correlated with 1131.1 and 1 other fieldsHigh correlation
365 is highly overall correlated with 193High correlation
1131.1 is highly overall correlated with 1131 and 1 other fieldsHigh correlation
193 is highly overall correlated with 1131 and 2 other fieldsHigh correlation
부산광역시 is highly overall correlated with 전체.2High correlation
전체.2 is highly overall correlated with 부산광역시High correlation
전체.1 is highly imbalanced (52.8%)Imbalance

Reproduction

Analysis started2023-12-10 06:28:30.724627
Analysis finished2023-12-10 06:28:34.246825
Duration3.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

MT
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
MT
99 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMT
2nd rowMT
3rd rowMT
4th rowMT
5th rowMT

Common Values

ValueCountFrequency (%)
MT 99
100.0%

Length

2023-12-10T15:28:34.363003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:28:34.546228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mt 99
100.0%

201901
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
201901
99 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201901
2nd row201901
3rd row201901
4th row201901
5th row201901

Common Values

ValueCountFrequency (%)
201901 99
100.0%

Length

2023-12-10T15:28:34.710761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:28:34.848064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201901 99
100.0%

1131
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)41.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean170.9697
Minimum9
Maximum1131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:28:35.012794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile17
Q154.5
median108
Q3195
95-th percentile500
Maximum1131
Range1122
Interquartile range (IQR)140.5

Descriptive statistics

Standard deviation199.48057
Coefficient of variation (CV)1.1667598
Kurtosis9.7588108
Mean170.9697
Median Absolute Deviation (MAD)74
Skewness2.7774085
Sum16926
Variance39792.499
MonotonicityNot monotonic
2023-12-10T15:28:35.277059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
108 4
 
4.0%
91 4
 
4.0%
30 4
 
4.0%
27 4
 
4.0%
22 3
 
3.0%
500 3
 
3.0%
62 3
 
3.0%
129 3
 
3.0%
195 3
 
3.0%
70 3
 
3.0%
Other values (31) 65
65.7%
ValueCountFrequency (%)
9 2
2.0%
13 2
2.0%
17 2
2.0%
22 3
3.0%
27 4
4.0%
30 4
4.0%
32 2
2.0%
34 2
2.0%
37 2
2.0%
53 2
2.0%
ValueCountFrequency (%)
1131 2
2.0%
628 2
2.0%
500 3
3.0%
479 3
3.0%
453 2
2.0%
317 2
2.0%
309 2
2.0%
277 2
2.0%
211 2
2.0%
208 2
2.0%

365
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)40.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.47475
Minimum12
Maximum498
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:28:35.496296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile16
Q150
median73
Q3114
95-th percentile446
Maximum498
Range486
Interquartile range (IQR)64

Descriptive statistics

Standard deviation118.54271
Coefficient of variation (CV)1.0446616
Kurtosis3.8384659
Mean113.47475
Median Absolute Deviation (MAD)26
Skewness2.1628824
Sum11234
Variance14052.374
MonotonicityNot monotonic
2023-12-10T15:28:35.735180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
63 7
 
7.1%
73 5
 
5.1%
115 4
 
4.0%
16 4
 
4.0%
48 3
 
3.0%
338 3
 
3.0%
151 3
 
3.0%
57 3
 
3.0%
91 3
 
3.0%
40 3
 
3.0%
Other values (30) 61
61.6%
ValueCountFrequency (%)
12 2
2.0%
15 2
2.0%
16 4
4.0%
23 2
2.0%
28 2
2.0%
37 2
2.0%
40 3
3.0%
44 2
2.0%
46 2
2.0%
48 3
3.0%
ValueCountFrequency (%)
498 2
2.0%
490 2
2.0%
446 2
2.0%
365 2
2.0%
338 3
3.0%
247 2
2.0%
162 2
2.0%
151 3
3.0%
119 2
2.0%
115 4
4.0%

1131.1
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)41.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean170.9697
Minimum9
Maximum1131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:28:36.312873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile17
Q154.5
median108
Q3195
95-th percentile500
Maximum1131
Range1122
Interquartile range (IQR)140.5

Descriptive statistics

Standard deviation199.48057
Coefficient of variation (CV)1.1667598
Kurtosis9.7588108
Mean170.9697
Median Absolute Deviation (MAD)74
Skewness2.7774085
Sum16926
Variance39792.499
MonotonicityNot monotonic
2023-12-10T15:28:36.497663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
108 4
 
4.0%
91 4
 
4.0%
30 4
 
4.0%
27 4
 
4.0%
22 3
 
3.0%
500 3
 
3.0%
62 3
 
3.0%
129 3
 
3.0%
195 3
 
3.0%
70 3
 
3.0%
Other values (31) 65
65.7%
ValueCountFrequency (%)
9 2
2.0%
13 2
2.0%
17 2
2.0%
22 3
3.0%
27 4
4.0%
30 4
4.0%
32 2
2.0%
34 2
2.0%
37 2
2.0%
53 2
2.0%
ValueCountFrequency (%)
1131 2
2.0%
628 2
2.0%
500 3
3.0%
479 3
3.0%
453 2
2.0%
317 2
2.0%
309 2
2.0%
277 2
2.0%
211 2
2.0%
208 2
2.0%

의류스타일러
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
의류스타일러
99 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row의류스타일러
2nd row의류스타일러
3rd row의류스타일러
4th row의류스타일러
5th row의류스타일러

Common Values

ValueCountFrequency (%)
의류스타일러 99
100.0%

Length

2023-12-10T15:28:36.711392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:28:36.857143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의류스타일러 99
100.0%

전체
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
의류스타일러
55 
전체
44 

Length

Max length6
Median length6
Mean length4.2222222
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전체
2nd row전체
3rd row전체
4th row전체
5th row전체

Common Values

ValueCountFrequency (%)
의류스타일러 55
55.6%
전체 44
44.4%

Length

2023-12-10T15:28:37.041795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:28:37.204619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의류스타일러 55
55.6%
전체 44
44.4%

전체.1
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
89 
의류스타일러
10 

Length

Max length6
Median length2
Mean length2.4040404
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전체
2nd row전체
3rd row전체
4th row전체
5th row전체

Common Values

ValueCountFrequency (%)
전체 89
89.9%
의류스타일러 10
 
10.1%

Length

2023-12-10T15:28:37.418825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:28:37.616698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 89
89.9%
의류스타일러 10
 
10.1%

2
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2
59 
1
40 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 59
59.6%
1 40
40.4%

Length

2023-12-10T15:28:37.789160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:28:37.958328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 59
59.6%
1 40
40.4%

20
Categorical

Distinct5
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
30
33 
40
26 
50
20 
20
12 
60
8 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20
2nd row20
3rd row30
4th row30
5th row30

Common Values

ValueCountFrequency (%)
30 33
33.3%
40 26
26.3%
50 20
20.2%
20 12
 
12.1%
60 8
 
8.1%

Length

2023-12-10T15:28:38.128994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:28:38.299882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 33
33.3%
40 26
26.3%
50 20
20.2%
20 12
 
12.1%
60 8
 
8.1%

부산광역시
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
경기도
36 
부산광역시
19 
인천광역시
14 
서울특별시
13 
대구광역시
8 
Other values (2)
9 

Length

Max length5
Median length5
Mean length4.1818182
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인천광역시
2nd row경기도
3rd row서울특별시
4th row부산광역시
5th row인천광역시

Common Values

ValueCountFrequency (%)
경기도 36
36.4%
부산광역시 19
19.2%
인천광역시 14
 
14.1%
서울특별시 13
 
13.1%
대구광역시 8
 
8.1%
전라북도 7
 
7.1%
충청북도 2
 
2.0%

Length

2023-12-10T15:28:38.523477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:28:38.742477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 36
36.4%
부산광역시 19
19.2%
인천광역시 14
 
14.1%
서울특별시 13
 
13.1%
대구광역시 8
 
8.1%
전라북도 7
 
7.1%
충청북도 2
 
2.0%

전체.2
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
66 
송파구
11 
부천시
9 
안양시
 
5
익산시
 
2
Other values (3)
 
6

Length

Max length3
Median length2
Mean length2.3333333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전체
2nd row전체
3rd row송파구
4th row전체
5th row전체

Common Values

ValueCountFrequency (%)
전체 66
66.7%
송파구 11
 
11.1%
부천시 9
 
9.1%
안양시 5
 
5.1%
익산시 2
 
2.0%
노원구 2
 
2.0%
청주시 2
 
2.0%
사상구 2
 
2.0%

Length

2023-12-10T15:28:38.991823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:28:39.189862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 66
66.7%
송파구 11
 
11.1%
부천시 9
 
9.1%
안양시 5
 
5.1%
익산시 2
 
2.0%
노원구 2
 
2.0%
청주시 2
 
2.0%
사상구 2
 
2.0%

193
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)39.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.060606
Minimum11
Maximum193
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:28:39.401321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile17
Q131
median51
Q384
95-th percentile131
Maximum193
Range182
Interquartile range (IQR)53

Descriptive statistics

Standard deviation37.802877
Coefficient of variation (CV)0.60912839
Kurtosis1.3679871
Mean62.060606
Median Absolute Deviation (MAD)24
Skewness1.0872375
Sum6144
Variance1429.0575
MonotonicityNot monotonic
2023-12-10T15:28:39.625947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
30 5
 
5.1%
29 5
 
5.1%
85 5
 
5.1%
50 4
 
4.0%
82 4
 
4.0%
34 4
 
4.0%
41 3
 
3.0%
25 3
 
3.0%
43 3
 
3.0%
75 3
 
3.0%
Other values (29) 60
60.6%
ValueCountFrequency (%)
11 2
 
2.0%
12 2
 
2.0%
17 2
 
2.0%
18 2
 
2.0%
22 2
 
2.0%
24 2
 
2.0%
25 3
3.0%
29 5
5.1%
30 5
5.1%
32 2
 
2.0%
ValueCountFrequency (%)
193 2
2.0%
137 2
2.0%
131 2
2.0%
118 2
2.0%
115 2
2.0%
112 2
2.0%
106 2
2.0%
105 2
2.0%
99 2
2.0%
90 2
2.0%

Interactions

2023-12-10T15:28:33.204534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:28:31.538316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:28:32.109170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:28:32.611141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:28:33.340836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:28:31.677226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:28:32.237101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:28:32.743581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:28:33.497656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:28:31.808675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:28:32.362339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:28:32.876081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:28:33.629544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:28:31.935972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:28:32.473141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:28:33.035244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:28:39.799234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
11313651131.1전체전체.1220부산광역시전체.2193
11311.0000.8851.0000.0000.2010.3960.4290.6210.0000.758
3650.8851.0000.8850.0000.0000.2680.4950.5220.0000.837
1131.11.0000.8851.0000.0000.2010.3960.4290.6210.0000.758
전체0.0000.0000.0001.0000.3790.0000.0000.0000.0000.000
전체.10.2010.0000.2010.3791.0000.3400.2590.0000.0000.138
20.3960.2680.3960.0000.3401.0000.0000.1110.0720.306
200.4290.4950.4290.0000.2590.0001.0000.2970.3070.559
부산광역시0.6210.5220.6210.0000.0000.1110.2971.0000.8220.396
전체.20.0000.0000.0000.0000.0000.0720.3070.8221.0000.649
1930.7580.8370.7580.0000.1380.3060.5590.3960.6491.000
2023-12-10T15:28:39.988045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
220전체.1부산광역시전체전체.2
21.0000.0000.2210.1130.0000.045
200.0001.0000.3100.1910.0000.189
전체.10.2210.3101.0000.0000.2470.000
부산광역시0.1130.1910.0001.0000.0000.621
전체0.0000.0000.2470.0001.0000.000
전체.20.0450.1890.0000.6210.0001.000
2023-12-10T15:28:40.177112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
11313651131.1193전체전체.1220부산광역시전체.2
11311.0000.4201.0000.5710.0000.2080.4130.2880.2570.000
3650.4201.0000.4200.7010.0000.0000.2560.3060.3040.000
1131.11.0000.4201.0000.5710.0000.2080.4130.2880.2570.000
1930.5710.7010.5711.0000.0000.0970.2210.3790.2220.265
전체0.0000.0000.0000.0001.0000.2470.0000.0000.0000.000
전체.10.2080.0000.2080.0970.2471.0000.2210.3100.0000.000
20.4130.2560.4130.2210.0000.2211.0000.0000.1130.045
200.2880.3060.2880.3790.0000.3100.0001.0000.1910.189
부산광역시0.2570.3040.2570.2220.0000.0000.1130.1911.0000.621
전체.20.0000.0000.0000.2650.0000.0000.0450.1890.6211.000

Missing values

2023-12-10T15:28:33.851010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:28:34.135345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

MT20190111313651131.1의류스타일러전체전체.1220부산광역시전체.2193
0MT20190112948129의류스타일러전체전체220인천광역시전체25
1MT20190150051500의류스타일러전체전체220경기도전체29
2MT20190147963479의류스타일러전체전체230서울특별시송파구75
3MT201901147338147의류스타일러전체전체230부산광역시전체42
4MT201901180151180의류스타일러전체전체230인천광역시전체48
5MT201901705770의류스타일러전체전체230경기도전체43
6MT20190119591195의류스타일러전체전체230경기도안양시85
7MT201901224022의류스타일러전체전체230경기도부천시30
8MT201901627362의류스타일러전체전체230전라북도전체41
9MT201901108115108의류스타일러전체전체230전라북도익산시34
MT20190111313651131.1의류스타일러전체전체.1220부산광역시전체.2193
89MT20190111313651131의류스타일러의류스타일러의류스타일러220부산광역시전체193
90MT20190112948129의류스타일러의류스타일러의류스타일러220인천광역시전체25
91MT20190150051500의류스타일러의류스타일러의류스타일러220경기도전체29
92MT20190147963479의류스타일러의류스타일러의류스타일러230서울특별시송파구75
93MT201901147338147의류스타일러의류스타일러의류스타일러230부산광역시전체42
94MT201901180151180의류스타일러의류스타일러의류스타일러230인천광역시전체48
95MT201901705770의류스타일러의류스타일러의류스타일러230경기도전체43
96MT20190119591195의류스타일러의류스타일러의류스타일러230경기도안양시85
97MT201901224022의류스타일러의류스타일러의류스타일러230경기도부천시30
98MT201901627362의류스타일러의류스타일러의류스타일러230전라북도전체41