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/15069493/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-12 22:53:01.365838
Analysis finished2023-12-12 22:53:02.018163
Duration0.65 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
14
10000 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row14
2nd row14
3rd row14
4th row14
5th row14

Common Values

ValueCountFrequency (%)
14 10000
100.0%

Length

2023-12-13T07:53:02.120504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:53:02.258167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
14 10000
100.0%

1차본부
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경남본부 10000
100.0%

Length

2023-12-13T07:53:02.352556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:53:02.467992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경남본부 10000
100.0%

2차순번
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
5421 
1
4579 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
2 5421
54.2%
1 4579
45.8%

Length

2023-12-13T07:53:02.574718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:53:02.693842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 5421
54.2%
1 4579
45.8%

2차사업소
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
진주지사
5421 
경남본부직할
4579 

Length

Max length6
Median length4
Mean length4.9158
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row진주지사
2nd row진주지사
3rd row경남본부직할
4th row경남본부직할
5th row진주지사

Common Values

ValueCountFrequency (%)
진주지사 5421
54.2%
경남본부직할 4579
45.8%

Length

2023-12-13T07:53:02.830778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:53:02.966152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진주지사 5421
54.2%
경남본부직할 4579
45.8%

전산화번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T07:53:03.343325image/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 row61972401
2nd row4496D144
3rd row8596Y132
4th row8596F581
5th row5893F643
ValueCountFrequency (%)
61972401 1
 
< 0.1%
65954452 1
 
< 0.1%
4496d271 1
 
< 0.1%
82023584 1
 
< 0.1%
8298f761 1
 
< 0.1%
6094y573 1
 
< 0.1%
8699p171 1
 
< 0.1%
8398q453 1
 
< 0.1%
58982104 1
 
< 0.1%
60972542 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-13T07:53:03.857506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 10891
13.6%
1 9187
11.5%
8 8466
10.6%
2 7824
9.8%
6 7373
9.2%
3 6701
8.4%
4 6519
8.1%
5 6340
7.9%
0 5628
7.0%
7 4222
 
5.3%
Other values (16) 6849
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73151
91.4%
Uppercase Letter 6849
 
8.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 464
 
6.8%
P 460
 
6.7%
D 448
 
6.5%
G 446
 
6.5%
Y 440
 
6.4%
H 437
 
6.4%
Z 437
 
6.4%
Q 437
 
6.4%
X 435
 
6.4%
W 424
 
6.2%
Other values (6) 2421
35.3%
Decimal Number
ValueCountFrequency (%)
9 10891
14.9%
1 9187
12.6%
8 8466
11.6%
2 7824
10.7%
6 7373
10.1%
3 6701
9.2%
4 6519
8.9%
5 6340
8.7%
0 5628
7.7%
7 4222
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
Common 73151
91.4%
Latin 6849
 
8.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 464
 
6.8%
P 460
 
6.7%
D 448
 
6.5%
G 446
 
6.5%
Y 440
 
6.4%
H 437
 
6.4%
Z 437
 
6.4%
Q 437
 
6.4%
X 435
 
6.4%
W 424
 
6.2%
Other values (6) 2421
35.3%
Common
ValueCountFrequency (%)
9 10891
14.9%
1 9187
12.6%
8 8466
11.6%
2 7824
10.7%
6 7373
10.1%
3 6701
9.2%
4 6519
8.9%
5 6340
8.7%
0 5628
7.7%
7 4222
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 10891
13.6%
1 9187
11.5%
8 8466
10.6%
2 7824
9.8%
6 7373
9.2%
3 6701
8.4%
4 6519
8.1%
5 6340
7.9%
0 5628
7.0%
7 4222
 
5.3%
Other values (16) 6849
8.6%

지역구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주택가
3375 
농어촌
3350 
<NA>
3074 
번화가
 
171
야외도로
 
30

Length

Max length4
Median length3
Mean length3.3104
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주택가 3375
33.8%
농어촌 3350
33.5%
<NA> 3074
30.7%
번화가 171
 
1.7%
야외도로 30
 
0.3%

Length

2023-12-13T07:53:04.010675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:53:04.128948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주택가 3375
33.8%
농어촌 3350
33.5%
na 3074
30.7%
번화가 171
 
1.7%
야외도로 30
 
0.3%

Correlations

2023-12-13T07:53:04.205175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2차순번2차사업소지역구분
2차순번1.0001.0000.349
2차사업소1.0001.0000.349
지역구분0.3490.3491.000
2023-12-13T07:53:04.294623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역구분2차순번2차사업소
지역구분1.0000.2330.233
2차순번0.2331.0001.000
2차사업소0.2331.0001.000
2023-12-13T07:53:04.418103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2차순번2차사업소지역구분
2차순번1.0001.0000.233
2차사업소1.0001.0000.233
지역구분0.2330.2331.000

Missing values

2023-12-13T07:53:01.805462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:53:01.948030image/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
5259814경남본부2진주지사61972401농어촌
8616014경남본부2진주지사4496D144농어촌
2964614경남본부1경남본부직할8596Y132번화가
1098414경남본부1경남본부직할8596F581주택가
4726214경남본부2진주지사5893F643<NA>
8283414경남본부2진주지사6094D313주택가
994814경남본부1경남본부직할8497A802주택가
6905914경남본부2진주지사6095Y361농어촌
8203414경남본부2진주지사6195H333농어촌
7015814경남본부2진주지사5893A012주택가
1차순번1차본부2차순번2차사업소전산화번호지역구분
722514경남본부1경남본부직할8597X943주택가
5201614경남본부2진주지사59901341<NA>
3812714경남본부1경남본부직할8802H051<NA>
585514경남본부1경남본부직할8696H941<NA>
2643214경남본부1경남본부직할8604S062농어촌
1669714경남본부1경남본부직할8602X991<NA>
5536114경남본부2진주지사5793H221주택가
3470914경남본부1경남본부직할8204P611농어촌
2410914경남본부1경남본부직할83994605<NA>
1188714경남본부1경남본부직할8695H321주택가