Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory566.4 KiB
Average record size in memory58.0 B

Variable types

Categorical5
Text1

Dataset

Description전국 전주전산화번호(전주번호)
Author한국전력공사
URLhttps://www.data.go.kr/data/15069426/fileData.do

Alerts

1차순번 has constant value ""Constant
1차본부 has constant value ""Constant
2차사업소 is highly overall correlated with 2차순번High correlation
2차순번 is highly overall correlated with 2차사업소High correlation
전산화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:59:25.621693
Analysis finished2023-12-12 22:59:26.457574
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

1차순번
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
9
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9
2nd row9
3rd row9
4th row9
5th row9

Common Values

ValueCountFrequency (%)
9 10000
100.0%

Length

2023-12-13T07:59:26.524923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:59:26.623120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9 10000
100.0%

1차본부
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
전북본부
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전북본부 10000
100.0%

Length

2023-12-13T07:59:26.739778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:59:26.835521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북본부 10000
100.0%

2차순번
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
8288 
4
1712 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row4
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 8288
82.9%
4 1712
 
17.1%

Length

2023-12-13T07:59:26.946773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:59:27.032819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 8288
82.9%
4 1712
 
17.1%

2차사업소
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
전북본부직할
8288 
익산지사
1712 

Length

Max length6
Median length6
Mean length5.6576
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전북본부직할
2nd row익산지사
3rd row전북본부직할
4th row전북본부직할
5th row전북본부직할

Common Values

ValueCountFrequency (%)
전북본부직할 8288
82.9%
익산지사 1712
 
17.1%

Length

2023-12-13T07:59:27.144979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:59:27.237295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북본부직할 8288
82.9%
익산지사 1712
 
17.1%

전산화번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T07:59:27.546489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters80000
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st row0432P762
2nd row9836W312
3rd row0730H863
4th row0534Y032
5th row1432F082
ValueCountFrequency (%)
0432p762 1
 
< 0.1%
0732f311 1
 
< 0.1%
0535h013 1
 
< 0.1%
0734s812 1
 
< 0.1%
1442a511 1
 
< 0.1%
0741b244 1
 
< 0.1%
0840z891 1
 
< 0.1%
1643b141 1
 
< 0.1%
0838z642 1
 
< 0.1%
1032r291 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-13T07:59:28.040252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 13031
16.3%
1 11629
14.5%
0 11010
13.8%
2 7240
9.0%
4 6331
7.9%
9 4786
 
6.0%
6 4113
 
5.1%
5 4005
 
5.0%
7 3964
 
5.0%
8 3958
 
4.9%
Other values (16) 9933
12.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70067
87.6%
Uppercase Letter 9933
 
12.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 696
 
7.0%
B 679
 
6.8%
A 650
 
6.5%
R 643
 
6.5%
Y 640
 
6.4%
W 640
 
6.4%
G 628
 
6.3%
C 619
 
6.2%
Z 618
 
6.2%
X 613
 
6.2%
Other values (6) 3507
35.3%
Decimal Number
ValueCountFrequency (%)
3 13031
18.6%
1 11629
16.6%
0 11010
15.7%
2 7240
10.3%
4 6331
9.0%
9 4786
 
6.8%
6 4113
 
5.9%
5 4005
 
5.7%
7 3964
 
5.7%
8 3958
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Common 70067
87.6%
Latin 9933
 
12.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 696
 
7.0%
B 679
 
6.8%
A 650
 
6.5%
R 643
 
6.5%
Y 640
 
6.4%
W 640
 
6.4%
G 628
 
6.3%
C 619
 
6.2%
Z 618
 
6.2%
X 613
 
6.2%
Other values (6) 3507
35.3%
Common
ValueCountFrequency (%)
3 13031
18.6%
1 11629
16.6%
0 11010
15.7%
2 7240
10.3%
4 6331
9.0%
9 4786
 
6.8%
6 4113
 
5.9%
5 4005
 
5.7%
7 3964
 
5.7%
8 3958
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 13031
16.3%
1 11629
14.5%
0 11010
13.8%
2 7240
9.0%
4 6331
7.9%
9 4786
 
6.0%
6 4113
 
5.1%
5 4005
 
5.0%
7 3964
 
5.0%
8 3958
 
4.9%
Other values (16) 9933
12.4%

지역구분
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
농어촌
4388 
<NA>
3360 
주택가
2188 
번화가
 
64

Length

Max length4
Median length3
Mean length3.336
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row주택가
2nd row주택가
3rd row<NA>
4th row<NA>
5th row주택가

Common Values

ValueCountFrequency (%)
농어촌 4388
43.9%
<NA> 3360
33.6%
주택가 2188
21.9%
번화가 64
 
0.6%

Length

2023-12-13T07:59:28.206260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:59:28.316613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농어촌 4388
43.9%
na 3360
33.6%
주택가 2188
21.9%
번화가 64
 
0.6%

Correlations

2023-12-13T07:59:28.385524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2차순번2차사업소지역구분
2차순번1.0001.0000.093
2차사업소1.0001.0000.093
지역구분0.0930.0931.000
2023-12-13T07:59:28.460944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역구분2차사업소2차순번
지역구분1.0000.1540.154
2차사업소0.1541.0001.000
2차순번0.1541.0001.000
2023-12-13T07:59:28.552643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2차순번2차사업소지역구분
2차순번1.0001.0000.154
2차사업소1.0001.0000.154
지역구분0.1540.1541.000

Missing values

2023-12-13T07:59:26.294796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:59:26.395545image/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

1차순번1차본부2차순번2차사업소전산화번호지역구분
514089전북본부1전북본부직할0432P762주택가
948409전북본부4익산지사9836W312주택가
184399전북본부1전북본부직할0730H863<NA>
647269전북본부1전북본부직할0534Y032<NA>
543769전북본부1전북본부직할1432F082주택가
676869전북본부1전북본부직할0940W911농어촌
31889전북본부1전북본부직할0631P651주택가
740849전북본부1전북본부직할0641Y254<NA>
937859전북본부4익산지사9945E871농어촌
492999전북본부1전북본부직할1042D641농어촌
1차순번1차본부2차순번2차사업소전산화번호지역구분
158509전북본부1전북본부직할0032B861주택가
716939전북본부1전북본부직할0931W882<NA>
866159전북본부4익산지사0441Q191<NA>
812669전북본부4익산지사9936B552주택가
177309전북본부1전북본부직할0729F521주택가
784299전북본부1전북본부직할1138P032<NA>
390089전북본부1전북본부직할1140W081주택가
695709전북본부1전북본부직할0434H772<NA>
804969전북본부4익산지사9734D571주택가
330699전북본부1전북본부직할0537D021농어촌