Overview

Dataset statistics

Number of variables12
Number of observations99
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.9 KiB
Average record size in memory102.3 B

Variable types

Categorical10
Numeric2

Dataset

DescriptionSample
Author(주)제로투원파트너스
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=ZTO010BSICGIPROCESS

Alerts

MT has constant value ""Constant
가공유 has constant value ""Constant
전체 has constant value ""Constant
전체.1 has constant value ""Constant
2 has constant value ""Constant
남양유업 초코에몽 has constant value ""Constant
201805 is highly overall correlated with 50High correlation
50 is highly overall correlated with 201805High correlation
광주광역시 is highly overall correlated with 동구High correlation
동구 is highly overall correlated with 광주광역시High correlation
7 has 1 (1.0%) zerosZeros

Reproduction

Analysis started2023-12-10 06:36:07.449504
Analysis finished2023-12-10 06:36:09.752008
Duration2.3 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

2023-12-10T15:36:09.949319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:36:10.122402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mt 99
100.0%

201805
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
201805
58 
201802
41 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201805
2nd row201805
3rd row201805
4th row201805
5th row201805

Common Values

ValueCountFrequency (%)
201805 58
58.6%
201802 41
41.4%

Length

2023-12-10T15:36:10.372467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:36:10.514984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201805 58
58.6%
201802 41
41.4%

65
Real number (ℝ)

Distinct75
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93.545455
Minimum15
Maximum273
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:36:10.703999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile42.5
Q161
median82
Q3112.5
95-th percentile198.4
Maximum273
Range258
Interquartile range (IQR)51.5

Descriptive statistics

Standard deviation49.679436
Coefficient of variation (CV)0.53107269
Kurtosis2.3300182
Mean93.545455
Median Absolute Deviation (MAD)23
Skewness1.4877434
Sum9261
Variance2468.0464
MonotonicityNot monotonic
2023-12-10T15:36:10.931226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
78 3
 
3.0%
70 3
 
3.0%
95 3
 
3.0%
82 3
 
3.0%
83 3
 
3.0%
56 3
 
3.0%
51 2
 
2.0%
64 2
 
2.0%
44 2
 
2.0%
100 2
 
2.0%
Other values (65) 73
73.7%
ValueCountFrequency (%)
15 1
1.0%
22 1
1.0%
35 1
1.0%
36 1
1.0%
38 1
1.0%
43 1
1.0%
44 2
2.0%
45 1
1.0%
46 1
1.0%
47 1
1.0%
ValueCountFrequency (%)
273 1
1.0%
252 1
1.0%
234 1
1.0%
224 1
1.0%
202 1
1.0%
198 1
1.0%
179 2
2.0%
176 1
1.0%
175 1
1.0%
164 1
1.0%

7
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)29.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.242424
Minimum0
Maximum100
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:36:11.192257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median8
Q313.5
95-th percentile37
Maximum100
Range100
Interquartile range (IQR)9.5

Descriptive statistics

Standard deviation15.672731
Coefficient of variation (CV)1.2801984
Kurtosis18.826756
Mean12.242424
Median Absolute Deviation (MAD)4
Skewness3.8944671
Sum1212
Variance245.63451
MonotonicityNot monotonic
2023-12-10T15:36:11.403543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
7 11
 
11.1%
4 9
 
9.1%
8 8
 
8.1%
2 7
 
7.1%
5 6
 
6.1%
6 6
 
6.1%
1 5
 
5.1%
10 4
 
4.0%
17 4
 
4.0%
3 4
 
4.0%
Other values (19) 35
35.4%
ValueCountFrequency (%)
0 1
 
1.0%
1 5
5.1%
2 7
7.1%
3 4
 
4.0%
4 9
9.1%
5 6
6.1%
6 6
6.1%
7 11
11.1%
8 8
8.1%
9 4
 
4.0%
ValueCountFrequency (%)
100 2
2.0%
45 1
1.0%
38 1
1.0%
37 2
2.0%
34 1
1.0%
33 1
1.0%
32 1
1.0%
25 2
2.0%
24 2
2.0%
21 1
1.0%

가공유
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가공유 99
100.0%

Length

2023-12-10T15:36:12.122684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:36:12.382980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가공유 99
100.0%

전체
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전체 99
100.0%

Length

2023-12-10T15:36:12.623100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:36:12.856690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 99
100.0%

전체.1
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전체 99
100.0%

Length

2023-12-10T15:36:13.008145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:36:13.146200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 99
100.0%

2
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2
99 

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 99
100.0%

Length

2023-12-10T15:36:13.304376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:36:13.503780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 99
100.0%

50
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
40
33 
50
30 
60
28 
30
8 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row50
2nd row50
3rd row50
4th row50
5th row50

Common Values

ValueCountFrequency (%)
40 33
33.3%
50 30
30.3%
60 28
28.3%
30 8
 
8.1%

Length

2023-12-10T15:36:13.662008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:36:13.854155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
40 33
33.3%
50 30
30.3%
60 28
28.3%
30 8
 
8.1%

광주광역시
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size924.0 B
경기도
15 
충청남도
14 
서울특별시
12 
대전광역시
8 
부산광역시
8 
Other values (10)
42 

Length

Max length5
Median length4
Mean length4.2525253
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row대전광역시
2nd row대전광역시
3rd row대전광역시
4th row울산광역시
5th row울산광역시

Common Values

ValueCountFrequency (%)
경기도 15
15.2%
충청남도 14
14.1%
서울특별시 12
12.1%
대전광역시 8
8.1%
부산광역시 8
8.1%
울산광역시 7
7.1%
경상남도 7
7.1%
충청북도 5
 
5.1%
전라남도 5
 
5.1%
인천광역시 5
 
5.1%
Other values (5) 13
13.1%

Length

2023-12-10T15:36:14.050543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 15
15.2%
충청남도 14
14.1%
서울특별시 12
12.1%
대전광역시 8
8.1%
부산광역시 8
8.1%
울산광역시 7
7.1%
경상남도 7
7.1%
충청북도 5
 
5.1%
전라남도 5
 
5.1%
인천광역시 5
 
5.1%
Other values (5) 13
13.1%

동구
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
8 
서구
 
4
용인시
 
3
남구
 
3
동구
 
3
Other values (40)
78 

Length

Max length4
Median length3
Mean length2.8484848
Min length2

Unique

Unique10 ?
Unique (%)10.1%

Sample

1st row서구
2nd row유성구
3rd row대덕구
4th row중구
5th row남구

Common Values

ValueCountFrequency (%)
전체 8
 
8.1%
서구 4
 
4.0%
용인시 3
 
3.0%
남구 3
 
3.0%
동구 3
 
3.0%
동두천시 3
 
3.0%
안산시 3
 
3.0%
중구 3
 
3.0%
안성시 3
 
3.0%
충주시 3
 
3.0%
Other values (35) 63
63.6%

Length

2023-12-10T15:36:14.345171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 8
 
8.1%
서구 4
 
4.0%
중구 3
 
3.0%
유성구 3
 
3.0%
아산시 3
 
3.0%
충주시 3
 
3.0%
안성시 3
 
3.0%
의왕시 3
 
3.0%
안산시 3
 
3.0%
동두천시 3
 
3.0%
Other values (35) 63
63.6%

남양유업 초코에몽
Categorical

CONSTANT 

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

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남양유업 초코에몽
2nd row남양유업 초코에몽
3rd row남양유업 초코에몽
4th row남양유업 초코에몽
5th row남양유업 초코에몽

Common Values

ValueCountFrequency (%)
남양유업 초코에몽 99
100.0%

Length

2023-12-10T15:36:14.808534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:36:15.072931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남양유업 99
50.0%
초코에몽 99
50.0%

Interactions

2023-12-10T15:36:08.364063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:08.098639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:08.593623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:36:08.208993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:36:15.211163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
20180565750광주광역시동구
2018051.0000.2630.1981.0000.0000.000
650.2631.0000.5750.3150.0000.550
70.1980.5751.0000.4390.5710.868
501.0000.3150.4391.0000.6070.000
광주광역시0.0000.0000.5710.6071.0000.997
동구0.0000.5500.8680.0000.9971.000
2023-12-10T15:36:15.499562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
201805동구광주광역시50
2018051.0000.0000.0000.990
동구0.0001.0000.7120.000
광주광역시0.0000.7121.0000.367
500.9900.0000.3671.000
2023-12-10T15:36:15.686697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
65720180550광주광역시동구
651.0000.4020.1910.1850.0000.156
70.4021.0000.1770.2900.3070.473
2018050.1910.1771.0000.9900.0000.000
500.1850.2900.9901.0000.3670.000
광주광역시0.0000.3070.0000.3671.0000.712
동구0.1560.4730.0000.0000.7121.000

Missing values

2023-12-10T15:36:08.967770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:36:09.600054image/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

MT201805657가공유전체전체.1250광주광역시동구남양유업 초코에몽
0MT2018058510가공유전체전체250대전광역시서구남양유업 초코에몽
1MT201805704가공유전체전체250대전광역시유성구남양유업 초코에몽
2MT20180515325가공유전체전체250대전광역시대덕구남양유업 초코에몽
3MT2018058734가공유전체전체250울산광역시중구남양유업 초코에몽
4MT201805957가공유전체전체250울산광역시남구남양유업 초코에몽
5MT20180535100가공유전체전체250울산광역시동구남양유업 초코에몽
6MT201805431가공유전체전체250경기도동두천시남양유업 초코에몽
7MT201805824가공유전체전체250경기도안산시남양유업 초코에몽
8MT2018051205가공유전체전체250경기도의왕시남양유업 초코에몽
9MT201805865가공유전체전체250경기도용인시남양유업 초코에몽
MT201805657가공유전체전체.1250광주광역시동구남양유업 초코에몽
89MT2018029514가공유전체전체240경기도안산시남양유업 초코에몽
90MT201802647가공유전체전체240경기도의왕시남양유업 초코에몽
91MT201802717가공유전체전체240경기도용인시남양유업 초코에몽
92MT2018026913가공유전체전체240경기도안성시남양유업 초코에몽
93MT201802707가공유전체전체240강원도전체남양유업 초코에몽
94MT2018026013가공유전체전체240강원도정선군남양유업 초코에몽
95MT2018026120가공유전체전체240충청북도충주시남양유업 초코에몽
96MT201802667가공유전체전체240충청북도진천군남양유업 초코에몽
97MT2018028411가공유전체전체240충청남도전체남양유업 초코에몽
98MT201802596가공유전체전체240충청남도아산시남양유업 초코에몽