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=ZTO011TOTALCGITISSU

Alerts

MT has constant value ""Constant
201901 has constant value ""Constant
화장지티슈 has constant value ""Constant
1 has constant value ""Constant
전체.1 is highly overall correlated with 전체 and 1 other fieldsHigh correlation
20 is highly overall correlated with 전체 and 1 other fieldsHigh correlation
전체 is highly overall correlated with 전체.1 and 1 other fieldsHigh correlation
123 is highly overall correlated with 85 and 2 other fieldsHigh correlation
85 is highly overall correlated with 123 and 2 other fieldsHigh correlation
123.1 is highly overall correlated with 123 and 2 other fieldsHigh correlation
92 is highly overall correlated with 123 and 2 other fieldsHigh correlation
서울특별시 is highly overall correlated with 송파구High correlation
송파구 is highly overall correlated with 서울특별시High correlation

Reproduction

Analysis started2023-12-10 06:45:10.514030
Analysis finished2023-12-10 06:45:13.730844
Duration3.22 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

2023-12-10T15:45:13.813389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:45:13.965329image/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

2023-12-10T15:45:14.096996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:45:14.237359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201901 99
100.0%

123
Real number (ℝ)

HIGH CORRELATION 

Distinct79
Distinct (%)79.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192.67677
Minimum-1
Maximum5399
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)1.0%
Memory size1023.0 B
2023-12-10T15:45:14.422468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile18.9
Q172
median95
Q3136.5
95-th percentile342.3
Maximum5399
Range5400
Interquartile range (IQR)64.5

Descriptive statistics

Standard deviation577.99428
Coefficient of variation (CV)2.999813
Kurtosis70.194993
Mean192.67677
Median Absolute Deviation (MAD)28
Skewness8.1028009
Sum19075
Variance334077.38
MonotonicityNot monotonic
2023-12-10T15:45:14.646699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
89 4
 
4.0%
65 3
 
3.0%
71 3
 
3.0%
121 3
 
3.0%
96 3
 
3.0%
91 3
 
3.0%
116 2
 
2.0%
93 2
 
2.0%
95 2
 
2.0%
163 2
 
2.0%
Other values (69) 72
72.7%
ValueCountFrequency (%)
-1 1
1.0%
3 1
1.0%
13 1
1.0%
14 1
1.0%
18 1
1.0%
19 1
1.0%
34 1
1.0%
36 1
1.0%
46 1
1.0%
47 1
1.0%
ValueCountFrequency (%)
5399 1
1.0%
2287 1
1.0%
475 1
1.0%
440 1
1.0%
354 1
1.0%
341 1
1.0%
332 1
1.0%
331 1
1.0%
321 1
1.0%
264 1
1.0%

85
Real number (ℝ)

HIGH CORRELATION 

Distinct70
Distinct (%)70.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.85859
Minimum-100
Maximum1209
Zeros0
Zeros (%)0.0%
Negative2
Negative (%)2.0%
Memory size1023.0 B
2023-12-10T15:45:14.850000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-100
5-th percentile35
Q174.5
median91
Q3109.5
95-th percentile388
Maximum1209
Range1309
Interquartile range (IQR)35

Descriptive statistics

Standard deviation175.26586
Coefficient of variation (CV)1.3815846
Kurtosis23.005541
Mean126.85859
Median Absolute Deviation (MAD)17
Skewness4.5845391
Sum12559
Variance30718.123
MonotonicityNot monotonic
2023-12-10T15:45:15.054924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
89 4
 
4.0%
93 4
 
4.0%
77 4
 
4.0%
35 3
 
3.0%
82 3
 
3.0%
95 2
 
2.0%
103 2
 
2.0%
119 2
 
2.0%
55 2
 
2.0%
102 2
 
2.0%
Other values (60) 71
71.7%
ValueCountFrequency (%)
-100 1
 
1.0%
-1 1
 
1.0%
20 1
 
1.0%
35 3
3.0%
36 1
 
1.0%
37 1
 
1.0%
42 1
 
1.0%
48 1
 
1.0%
49 1
 
1.0%
50 1
 
1.0%
ValueCountFrequency (%)
1209 1
1.0%
1021 1
1.0%
821 1
1.0%
451 1
1.0%
424 1
1.0%
384 1
1.0%
266 1
1.0%
198 1
1.0%
172 1
1.0%
156 1
1.0%

123.1
Real number (ℝ)

HIGH CORRELATION 

Distinct79
Distinct (%)79.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192.67677
Minimum-1
Maximum5399
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)1.0%
Memory size1023.0 B
2023-12-10T15:45:15.274436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile18.9
Q172
median95
Q3136.5
95-th percentile342.3
Maximum5399
Range5400
Interquartile range (IQR)64.5

Descriptive statistics

Standard deviation577.99428
Coefficient of variation (CV)2.999813
Kurtosis70.194993
Mean192.67677
Median Absolute Deviation (MAD)28
Skewness8.1028009
Sum19075
Variance334077.38
MonotonicityNot monotonic
2023-12-10T15:45:15.507140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
89 4
 
4.0%
65 3
 
3.0%
71 3
 
3.0%
121 3
 
3.0%
96 3
 
3.0%
91 3
 
3.0%
116 2
 
2.0%
93 2
 
2.0%
95 2
 
2.0%
163 2
 
2.0%
Other values (69) 72
72.7%
ValueCountFrequency (%)
-1 1
1.0%
3 1
1.0%
13 1
1.0%
14 1
1.0%
18 1
1.0%
19 1
1.0%
34 1
1.0%
36 1
1.0%
46 1
1.0%
47 1
1.0%
ValueCountFrequency (%)
5399 1
1.0%
2287 1
1.0%
475 1
1.0%
440 1
1.0%
354 1
1.0%
341 1
1.0%
332 1
1.0%
331 1
1.0%
321 1
1.0%
264 1
1.0%

화장지티슈
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
화장지티슈 99
100.0%

Length

2023-12-10T15:45:15.682371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:45:15.815617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화장지티슈 99
100.0%

전체
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
63 
기타위생지용품
36 

Length

Max length7
Median length2
Mean length3.8181818
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전체 63
63.6%
기타위생지용품 36
36.4%

Length

2023-12-10T15:45:15.947786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:45:16.076948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 63
63.6%
기타위생지용품 36
36.4%

전체.1
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
63 
기타위생지용품
36 

Length

Max length7
Median length2
Mean length3.8181818
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전체 63
63.6%
기타위생지용품 36
36.4%

Length

2023-12-10T15:45:16.531456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:45:16.679013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 63
63.6%
기타위생지용품 36
36.4%

1
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
1
99 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 99
100.0%

Length

2023-12-10T15:45:16.825573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:45:16.959696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 99
100.0%

20
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
20
32 
30
31 
50
22 
60
13 
40
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
20 32
32.3%
30 31
31.3%
50 22
22.2%
60 13
13.1%
40 1
 
1.0%

Length

2023-12-10T15:45:17.113161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:45:17.258782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20 32
32.3%
30 31
31.3%
50 22
22.2%
60 13
13.1%
40 1
 
1.0%

서울특별시
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
경기도
25 
서울특별시
15 
부산광역시
13 
전라북도
10 
인천광역시
9 
Other values (7)
27 

Length

Max length5
Median length4
Mean length4.1818182
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 25
25.3%
서울특별시 15
15.2%
부산광역시 13
13.1%
전라북도 10
 
10.1%
인천광역시 9
 
9.1%
대구광역시 6
 
6.1%
충청북도 6
 
6.1%
전라남도 5
 
5.1%
경상남도 4
 
4.0%
대전광역시 2
 
2.0%
Other values (2) 4
 
4.0%

Length

2023-12-10T15:45:17.443907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 25
25.3%
서울특별시 15
15.2%
부산광역시 13
13.1%
전라북도 10
 
10.1%
인천광역시 9
 
9.1%
대구광역시 6
 
6.1%
충청북도 6
 
6.1%
전라남도 5
 
5.1%
경상남도 4
 
4.0%
대전광역시 2
 
2.0%
Other values (2) 4
 
4.0%

송파구
Categorical

HIGH CORRELATION 

Distinct33
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
23 
중구
7 
연수구
 
4
의정부시
 
4
남양주시
 
4
Other values (28)
57 

Length

Max length4
Median length3
Mean length2.7575758
Min length2

Unique

Unique7 ?
Unique (%)7.1%

Sample

1st row전체
2nd row중구
3rd row동구
4th row동래구
5th row사상구

Common Values

ValueCountFrequency (%)
전체 23
23.2%
중구 7
 
7.1%
연수구 4
 
4.0%
의정부시 4
 
4.0%
남양주시 4
 
4.0%
오산시 4
 
4.0%
청주시 4
 
4.0%
안양시 3
 
3.0%
익산시 3
 
3.0%
노원구 3
 
3.0%
Other values (23) 40
40.4%

Length

2023-12-10T15:45:17.651197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 23
23.2%
중구 7
 
7.1%
연수구 4
 
4.0%
의정부시 4
 
4.0%
남양주시 4
 
4.0%
오산시 4
 
4.0%
청주시 4
 
4.0%
송파구 3
 
3.0%
노원구 3
 
3.0%
익산시 3
 
3.0%
Other values (23) 40
40.4%

92
Real number (ℝ)

HIGH CORRELATION 

Distinct65
Distinct (%)65.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.0202
Minimum-1
Maximum298
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)1.0%
Memory size1023.0 B
2023-12-10T15:45:17.851054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile44.5
Q181.5
median94
Q3109.5
95-th percentile173
Maximum298
Range299
Interquartile range (IQR)28

Descriptive statistics

Standard deviation42.344549
Coefficient of variation (CV)0.42335996
Kurtosis6.5179426
Mean100.0202
Median Absolute Deviation (MAD)15
Skewness1.6544391
Sum9902
Variance1793.0608
MonotonicityNot monotonic
2023-12-10T15:45:18.057652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
92 5
 
5.1%
89 4
 
4.0%
94 4
 
4.0%
83 4
 
4.0%
73 3
 
3.0%
104 3
 
3.0%
102 3
 
3.0%
109 2
 
2.0%
110 2
 
2.0%
101 2
 
2.0%
Other values (55) 67
67.7%
ValueCountFrequency (%)
-1 1
1.0%
13 1
1.0%
17 1
1.0%
27 1
1.0%
31 1
1.0%
46 1
1.0%
61 1
1.0%
63 1
1.0%
66 1
1.0%
67 1
1.0%
ValueCountFrequency (%)
298 1
1.0%
267 1
1.0%
199 1
1.0%
179 1
1.0%
173 2
2.0%
166 1
1.0%
160 1
1.0%
153 1
1.0%
150 1
1.0%
146 1
1.0%

Interactions

2023-12-10T15:45:12.799559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:11.157419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:11.738152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:12.271394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:12.935646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:11.285596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:11.892424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:12.392142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:13.055971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:11.435528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:12.014559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:12.518750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:13.158003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:11.582309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:12.152035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:12.649152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:45:18.241580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
12385123.1전체전체.120서울특별시송파구92
1231.0000.7701.0000.0000.0000.0000.7180.7640.924
850.7701.0000.7700.2840.2840.6790.4870.6350.703
123.11.0000.7701.0000.0000.0000.0000.7180.7640.924
전체0.0000.2840.0001.0000.9991.0000.0000.0000.371
전체.10.0000.2840.0000.9991.0001.0000.0000.0000.371
200.0000.6790.0001.0001.0001.0000.2130.0000.394
서울특별시0.7180.4870.7180.0000.0000.2131.0000.9640.326
송파구0.7640.6350.7640.0000.0000.0000.9641.0000.775
920.9240.7030.9240.3710.3710.3940.3260.7751.000
2023-12-10T15:45:18.442273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전체.1송파구서울특별시20전체
전체.11.0000.0000.0000.9840.978
송파구0.0001.0000.6640.0000.000
서울특별시0.0000.6641.0000.1090.000
200.9840.0000.1091.0000.984
전체0.9780.0000.0000.9841.000
2023-12-10T15:45:18.608009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
12385123.192전체전체.120서울특별시송파구
1231.0000.6591.0000.5680.0000.0000.0000.4150.415
850.6591.0000.6590.5760.2050.2050.4950.2220.253
123.11.0000.6591.0000.5680.0000.0000.0000.4150.415
920.5680.5760.5681.0000.3570.3570.2330.1380.352
전체0.0000.2050.0000.3571.0000.9780.9840.0000.000
전체.10.0000.2050.0000.3570.9781.0000.9840.0000.000
200.0000.4950.0000.2330.9840.9841.0000.1090.000
서울특별시0.4150.2220.4150.1380.0000.0000.1091.0000.664
송파구0.4150.2530.4150.3520.0000.0000.0000.6641.000

Missing values

2023-12-10T15:45:13.327153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:45:13.639775image/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

MT20190112385123.1화장지티슈전체전체.1120서울특별시송파구92
0MT201901989598화장지티슈전체전체120부산광역시전체89
1MT20190112183121화장지티슈전체전체120부산광역시중구89
2MT201901539910215399화장지티슈전체전체120부산광역시동구298
3MT201901607460화장지티슈전체전체120부산광역시동래구69
4MT201901135101135화장지티슈전체전체120부산광역시사상구104
5MT201901125107125화장지티슈전체전체120대구광역시전체102
6MT201901346534화장지티슈전체전체120대구광역시달서구31
7MT20190112192121화장지티슈전체전체120인천광역시전체92
8MT201901545454화장지티슈전체전체120인천광역시연수구66
9MT201901331115331화장지티슈전체전체120대전광역시중구63
MT20190112385123.1화장지티슈전체전체.1120서울특별시송파구92
89MT201901149155149화장지티슈기타위생지용품기타위생지용품160대구광역시전체166
90MT2019016514265화장지티슈기타위생지용품기타위생지용품160인천광역시전체109
91MT201901182018화장지티슈기타위생지용품기타위생지용품160인천광역시연수구81
92MT20190111478114화장지티슈기타위생지용품기타위생지용품160경기도전체105
93MT201901440821440화장지티슈기타위생지용품기타위생지용품160경기도의정부시136
94MT201901955995화장지티슈기타위생지용품기타위생지용품160경기도남양주시72
95MT201901475137475화장지티슈기타위생지용품기타위생지용품160경기도오산시173
96MT201901363536화장지티슈기타위생지용품기타위생지용품160충청북도청주시83
97MT201901145103145화장지티슈기타위생지용품기타위생지용품160전라북도전체67
98MT201901111138111화장지티슈기타위생지용품기타위생지용품160전라남도전체150