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=ZTO010BSICGIWATER

Alerts

MT has constant value ""Constant
물 has constant value ""Constant
전체 has constant value ""Constant
전체.1 has constant value ""Constant
2 has constant value ""Constant
농심 백산수 has constant value ""Constant
201802 is highly overall correlated with 30High correlation
30 is highly overall correlated with 201802High correlation
206 is highly overall correlated with 9High correlation
9 is highly overall correlated with 206High correlation
경상남도 is highly overall correlated with 합천군High correlation
합천군 is highly overall correlated with 경상남도High correlation

Reproduction

Analysis started2023-12-10 06:41:39.100352
Analysis finished2023-12-10 06:41:40.661481
Duration1.56 second
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

2023-12-10T15:41:40.761524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:41:40.880307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mt 99
100.0%

201802
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
201802
75 
201806
24 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201802
2nd row201802
3rd row201802
4th row201802
5th row201802

Common Values

ValueCountFrequency (%)
201802 75
75.8%
201806 24
 
24.2%

Length

2023-12-10T15:41:41.023055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:41:41.169085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201802 75
75.8%
201806 24
 
24.2%

206
Real number (ℝ)

HIGH CORRELATION 

Distinct77
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.858586
Minimum3
Maximum261
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:41:41.322312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile21.5
Q150
median74
Q399
95-th percentile182.6
Maximum261
Range258
Interquartile range (IQR)49

Descriptive statistics

Standard deviation51.383514
Coefficient of variation (CV)0.62771075
Kurtosis2.6133194
Mean81.858586
Median Absolute Deviation (MAD)25
Skewness1.4707739
Sum8104
Variance2640.2655
MonotonicityNot monotonic
2023-12-10T15:41:41.552747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74 4
 
4.0%
29 3
 
3.0%
76 3
 
3.0%
53 3
 
3.0%
47 2
 
2.0%
88 2
 
2.0%
77 2
 
2.0%
66 2
 
2.0%
71 2
 
2.0%
41 2
 
2.0%
Other values (67) 74
74.7%
ValueCountFrequency (%)
3 1
 
1.0%
10 1
 
1.0%
11 1
 
1.0%
16 1
 
1.0%
17 1
 
1.0%
22 1
 
1.0%
24 1
 
1.0%
28 1
 
1.0%
29 3
3.0%
30 1
 
1.0%
ValueCountFrequency (%)
261 1
1.0%
256 1
1.0%
244 1
1.0%
209 1
1.0%
197 1
1.0%
181 1
1.0%
179 1
1.0%
173 1
1.0%
163 1
1.0%
137 1
1.0%

9
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.525253
Minimum1
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:41:41.737408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15.5
median8
Q311
95-th percentile24.9
Maximum70
Range69
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation11.257962
Coefficient of variation (CV)1.0696144
Kurtosis14.906259
Mean10.525253
Median Absolute Deviation (MAD)3
Skewness3.5657638
Sum1042
Variance126.7417
MonotonicityNot monotonic
2023-12-10T15:41:41.914944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
7 11
11.1%
6 11
11.1%
8 10
10.1%
10 9
 
9.1%
4 7
 
7.1%
1 7
 
7.1%
11 6
 
6.1%
5 5
 
5.1%
9 5
 
5.1%
3 4
 
4.0%
Other values (16) 24
24.2%
ValueCountFrequency (%)
1 7
7.1%
2 2
 
2.0%
3 4
 
4.0%
4 7
7.1%
5 5
5.1%
6 11
11.1%
7 11
11.1%
8 10
10.1%
9 5
5.1%
10 9
9.1%
ValueCountFrequency (%)
70 1
 
1.0%
66 1
 
1.0%
55 1
 
1.0%
34 1
 
1.0%
33 1
 
1.0%
24 1
 
1.0%
23 1
 
1.0%
21 2
2.0%
18 3
3.0%
17 1
 
1.0%

물
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
물 99
100.0%

Length

2023-12-10T15:41:42.128031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:41:42.250650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물 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

2023-12-10T15:41:42.393363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:41:42.506967image/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

2023-12-10T15:41:42.631954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:41:42.751792image/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

2023-12-10T15:41:42.882667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:41:42.990836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 99
100.0%

30
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
40
43 
50
32 
20
24 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row40
2nd row40
3rd row40
4th row40
5th row40

Common Values

ValueCountFrequency (%)
40 43
43.4%
50 32
32.3%
20 24
24.2%

Length

2023-12-10T15:41:43.087443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:41:43.210297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
40 43
43.4%
50 32
32.3%
20 24
24.2%

경상남도
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size924.0 B
서울특별시
17 
부산광역시
16 
경기도
15 
인천광역시
9 
대전광역시
7 
Other values (10)
35 

Length

Max length5
Median length5
Mean length4.4343434
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 17
17.2%
부산광역시 16
16.2%
경기도 15
15.2%
인천광역시 9
9.1%
대전광역시 7
7.1%
대구광역시 6
 
6.1%
충청남도 6
 
6.1%
울산광역시 5
 
5.1%
강원도 4
 
4.0%
충청북도 4
 
4.0%
Other values (5) 10
10.1%

Length

2023-12-10T15:41:43.371161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 17
17.2%
부산광역시 16
16.2%
경기도 15
15.2%
인천광역시 9
9.1%
대전광역시 7
7.1%
대구광역시 6
 
6.1%
충청남도 6
 
6.1%
울산광역시 5
 
5.1%
강원도 4
 
4.0%
충청북도 4
 
4.0%
Other values (5) 10
10.1%

합천군
Categorical

HIGH CORRELATION 

Distinct42
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
8 
서구
 
6
계양구
 
3
금정구
 
3
광진구
 
3
Other values (37)
76 

Length

Max length4
Median length3
Mean length2.8787879
Min length2

Unique

Unique16 ?
Unique (%)16.2%

Sample

1st row전체
2nd row종로구
3rd row성동구
4th row광진구
5th row구로구

Common Values

ValueCountFrequency (%)
전체 8
 
8.1%
서구 6
 
6.1%
계양구 3
 
3.0%
금정구 3
 
3.0%
광진구 3
 
3.0%
구로구 3
 
3.0%
성동구 3
 
3.0%
연제구 3
 
3.0%
해운대구 3
 
3.0%
달성군 3
 
3.0%
Other values (32) 61
61.6%

Length

2023-12-10T15:41:43.554770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 8
 
8.1%
서구 6
 
6.1%
사하구 3
 
3.0%
유성구 3
 
3.0%
충주시 3
 
3.0%
안성시 3
 
3.0%
용인시 3
 
3.0%
의왕시 3
 
3.0%
종로구 3
 
3.0%
동두천시 3
 
3.0%
Other values (32) 61
61.6%

농심 백산수
Categorical

CONSTANT 

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

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row농심 백산수
2nd row농심 백산수
3rd row농심 백산수
4th row농심 백산수
5th row농심 백산수

Common Values

ValueCountFrequency (%)
농심 백산수 99
100.0%

Length

2023-12-10T15:41:43.770378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:41:43.935262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농심 99
50.0%
백산수 99
50.0%

Interactions

2023-12-10T15:41:39.907653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:41:39.629251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:41:40.053028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:41:39.761554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:41:44.033919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
201802206930경상남도합천군
2018021.0000.3220.0511.0000.0000.000
2060.3221.0000.5890.4000.3790.000
90.0510.5891.0000.1440.2210.563
301.0000.4000.1441.0000.0000.000
경상남도0.0000.3790.2210.0001.0000.990
합천군0.0000.0000.5630.0000.9901.000
2023-12-10T15:41:44.145380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
20180230경상남도합천군
2018021.0000.9950.0000.000
300.9951.0000.0000.000
경상남도0.0000.0001.0000.729
합천군0.0000.0000.7291.000
2023-12-10T15:41:44.256410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
206920180230경상남도합천군
2061.0000.5590.3080.1840.1540.000
90.5591.0000.0470.0910.0890.185
2018020.3080.0471.0000.9950.0000.000
300.1840.0910.9951.0000.0000.000
경상남도0.1540.0890.0000.0001.0000.729
합천군0.0000.1850.0000.0000.7291.000

Missing values

2023-12-10T15:41:40.292058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:41:40.563945image/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

MT2018022069물전체전체.1230경상남도합천군농심 백산수
0MT201802547물전체전체240서울특별시전체농심 백산수
1MT201802866물전체전체240서울특별시종로구농심 백산수
2MT201802567물전체전체240서울특별시성동구농심 백산수
3MT201802766물전체전체240서울특별시광진구농심 백산수
4MT2018026910물전체전체240서울특별시구로구농심 백산수
5MT20180212214물전체전체240서울특별시관악구농심 백산수
6MT20180211533물전체전체240부산광역시영도구농심 백산수
7MT201802855물전체전체240부산광역시해운대구농심 백산수
8MT2018021037물전체전체240부산광역시사하구농심 백산수
9MT20180210823물전체전체240부산광역시금정구농심 백산수
MT2018022069물전체전체.1230경상남도합천군농심 백산수
89MT20180613717물전체전체220대전광역시서구농심 백산수
90MT201806774물전체전체220대전광역시유성구농심 백산수
91MT20180613318물전체전체220울산광역시남구농심 백산수
92MT2018061263물전체전체220경기도동두천시농심 백산수
93MT201806918물전체전체220경기도안산시농심 백산수
94MT201806534물전체전체220경기도의왕시농심 백산수
95MT201806473물전체전체220경기도용인시농심 백산수
96MT2018069610물전체전체220경기도안성시농심 백산수
97MT2018069811물전체전체220강원도전체농심 백산수
98MT201806534물전체전체220충청북도충주시농심 백산수