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/15069477/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 20:28:29.854722
Analysis finished2023-12-12 20:28:30.502790
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
8
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row8
2nd row8
3rd row8
4th row8
5th row8

Common Values

ValueCountFrequency (%)
8 10000
100.0%

Length

2023-12-13T05:28:30.591297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:28:30.783575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8 10000
100.0%

1차본부
Categorical

CONSTANT 

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

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대전세종충남본부 10000
100.0%

Length

2023-12-13T05:28:30.910782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:28:31.003464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전세종충남본부 10000
100.0%

2차순번
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
6599 
1
3401 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 6599
66.0%
1 3401
34.0%

Length

2023-12-13T05:28:31.127084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:28:31.243251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 6599
66.0%
1 3401
34.0%

2차사업소
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
천안지사
6599 
대전세종충남본부직할
3401 

Length

Max length10
Median length4
Mean length6.0406
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대전세종충남본부직할
2nd row천안지사
3rd row천안지사
4th row대전세종충남본부직할
5th row천안지사

Common Values

ValueCountFrequency (%)
천안지사 6599
66.0%
대전세종충남본부직할 3401
34.0%

Length

2023-12-13T05:28:31.374420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:28:31.477906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
천안지사 6599
66.0%
대전세종충남본부직할 3401
34.0%

전산화번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T05:28:31.900104image/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 row1957Z593
2nd row0491B351
3rd row1279W921
4th row1857H712
5th row1280A894
ValueCountFrequency (%)
1957z593 1
 
< 0.1%
0589r652 1
 
< 0.1%
0684f801 1
 
< 0.1%
2155a812 1
 
< 0.1%
1956d722 1
 
< 0.1%
1783g562 1
 
< 0.1%
0378g662 1
 
< 0.1%
1582e291 1
 
< 0.1%
0786e602 1
 
< 0.1%
0685b461 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-13T05:28:32.515035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12726
15.9%
8 9601
12.0%
0 9046
11.3%
2 8036
10.0%
5 7114
8.9%
7 5492
6.9%
9 5042
 
6.3%
6 4801
 
6.0%
3 4384
 
5.5%
4 3787
 
4.7%
Other values (16) 9971
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70029
87.5%
Uppercase Letter 9971
 
12.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
G 679
 
6.8%
B 676
 
6.8%
Y 655
 
6.6%
W 650
 
6.5%
E 645
 
6.5%
Z 635
 
6.4%
F 634
 
6.4%
A 628
 
6.3%
H 623
 
6.2%
D 620
 
6.2%
Other values (6) 3526
35.4%
Decimal Number
ValueCountFrequency (%)
1 12726
18.2%
8 9601
13.7%
0 9046
12.9%
2 8036
11.5%
5 7114
10.2%
7 5492
7.8%
9 5042
 
7.2%
6 4801
 
6.9%
3 4384
 
6.3%
4 3787
 
5.4%

Most occurring scripts

ValueCountFrequency (%)
Common 70029
87.5%
Latin 9971
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
G 679
 
6.8%
B 676
 
6.8%
Y 655
 
6.6%
W 650
 
6.5%
E 645
 
6.5%
Z 635
 
6.4%
F 634
 
6.4%
A 628
 
6.3%
H 623
 
6.2%
D 620
 
6.2%
Other values (6) 3526
35.4%
Common
ValueCountFrequency (%)
1 12726
18.2%
8 9601
13.7%
0 9046
12.9%
2 8036
11.5%
5 7114
10.2%
7 5492
7.8%
9 5042
 
7.2%
6 4801
 
6.9%
3 4384
 
6.3%
4 3787
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12726
15.9%
8 9601
12.0%
0 9046
11.3%
2 8036
10.0%
5 7114
8.9%
7 5492
6.9%
9 5042
 
6.3%
6 4801
 
6.0%
3 4384
 
5.5%
4 3787
 
4.7%
Other values (16) 9971
12.5%

지역구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주택가
5700 
<NA>
2214 
농어촌
1924 
번화가
 
160
야외도로
 
2

Length

Max length4
Median length3
Mean length3.2216
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주택가 5700
57.0%
<NA> 2214
 
22.1%
농어촌 1924
 
19.2%
번화가 160
 
1.6%
야외도로 2
 
< 0.1%

Length

2023-12-13T05:28:32.688122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:28:32.813746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주택가 5700
57.0%
na 2214
 
22.1%
농어촌 1924
 
19.2%
번화가 160
 
1.6%
야외도로 2
 
< 0.1%

Correlations

2023-12-13T05:28:32.892548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2차순번2차사업소지역구분
2차순번1.0001.0000.284
2차사업소1.0001.0000.284
지역구분0.2840.2841.000
2023-12-13T05:28:32.990228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역구분2차순번2차사업소
지역구분1.0000.1890.189
2차순번0.1891.0001.000
2차사업소0.1891.0001.000
2023-12-13T05:28:33.086487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2차순번2차사업소지역구분
2차순번1.0001.0000.189
2차사업소1.0001.0000.189
지역구분0.1890.1891.000

Missing values

2023-12-13T05:28:30.287475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:28:30.435899image/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
103348대전세종충남본부1대전세종충남본부직할1957Z593주택가
688658대전세종충남본부2천안지사0491B351<NA>
665428대전세종충남본부2천안지사1279W921주택가
56458대전세종충남본부1대전세종충남본부직할1857H712주택가
935678대전세종충남본부2천안지사1280A894<NA>
787778대전세종충남본부2천안지사0481X983<NA>
911488대전세종충남본부2천안지사0888E431<NA>
205048대전세종충남본부1대전세종충남본부직할1958Y064번화가
256468대전세종충남본부1대전세종충남본부직할2156R691주택가
654188대전세종충남본부2천안지사0578Y521주택가
1차순번1차본부2차순번2차사업소전산화번호지역구분
658528대전세종충남본부2천안지사13813991주택가
299018대전세종충남본부1대전세종충남본부직할2360Q951<NA>
263408대전세종충남본부1대전세종충남본부직할1857R313<NA>
644648대전세종충남본부2천안지사0981Z201주택가
555688대전세종충남본부2천안지사0784P931주택가
471278대전세종충남본부2천안지사0578D082주택가
137358대전세종충남본부1대전세종충남본부직할1854D571주택가
608078대전세종충남본부2천안지사0692Z381주택가
430058대전세종충남본부2천안지사0583F415<NA>
755678대전세종충남본부2천안지사0885X081주택가