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/15069492/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 23:53:16.511490
Analysis finished2023-12-12 23:53:17.104862
Duration0.59 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
10
10000 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10
2nd row10
3rd row10
4th row10
5th row10

Common Values

ValueCountFrequency (%)
10 10000
100.0%

Length

2023-12-13T08:53:17.152236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:53:17.215765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 10000
100.0%

1차본부
Categorical

CONSTANT 

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

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광주전남본부 10000
100.0%

Length

2023-12-13T08:53:17.281713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:53:17.348943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광주전남본부 10000
100.0%

2차순번
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
6546 
1
3454 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 6546
65.5%
1 3454
34.5%

Length

2023-12-13T08:53:17.426322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:53:17.513838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 6546
65.5%
1 3454
34.5%

2차사업소
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
여수지사
6546 
광주전남본부직할
3454 

Length

Max length8
Median length4
Mean length5.3816
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광주전남본부직할
2nd row여수지사
3rd row여수지사
4th row광주전남본부직할
5th row광주전남본부직할

Common Values

ValueCountFrequency (%)
여수지사 6546
65.5%
광주전남본부직할 3454
34.5%

Length

2023-12-13T08:53:17.595464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:53:17.672575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여수지사 6546
65.5%
광주전남본부직할 3454
34.5%

전산화번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T08:53:17.917558image/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 row9593X045
2nd row3377R861
3rd row3563E711
4th row0093Q461
5th row9495G702
ValueCountFrequency (%)
9593x045 1
 
< 0.1%
2677w961 1
 
< 0.1%
2874w511 1
 
< 0.1%
2875x503 1
 
< 0.1%
3477w942 1
 
< 0.1%
2962h813 1
 
< 0.1%
2767p581 1
 
< 0.1%
3463c261 1
 
< 0.1%
3561g541 1
 
< 0.1%
3464z731 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-13T08:53:18.261963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 10176
12.7%
9 10138
12.7%
2 9224
11.5%
1 8262
10.3%
7 7699
9.6%
6 7450
9.3%
4 5696
7.1%
5 5029
6.3%
0 3774
 
4.7%
8 3446
 
4.3%
Other values (16) 9106
11.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70894
88.6%
Uppercase Letter 9106
 
11.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H 677
 
7.4%
X 660
 
7.2%
W 641
 
7.0%
P 596
 
6.5%
Q 579
 
6.4%
C 573
 
6.3%
D 572
 
6.3%
G 570
 
6.3%
S 568
 
6.2%
Y 565
 
6.2%
Other values (6) 3105
34.1%
Decimal Number
ValueCountFrequency (%)
3 10176
14.4%
9 10138
14.3%
2 9224
13.0%
1 8262
11.7%
7 7699
10.9%
6 7450
10.5%
4 5696
8.0%
5 5029
7.1%
0 3774
 
5.3%
8 3446
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
Common 70894
88.6%
Latin 9106
 
11.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
H 677
 
7.4%
X 660
 
7.2%
W 641
 
7.0%
P 596
 
6.5%
Q 579
 
6.4%
C 573
 
6.3%
D 572
 
6.3%
G 570
 
6.3%
S 568
 
6.2%
Y 565
 
6.2%
Other values (6) 3105
34.1%
Common
ValueCountFrequency (%)
3 10176
14.4%
9 10138
14.3%
2 9224
13.0%
1 8262
11.7%
7 7699
10.9%
6 7450
10.5%
4 5696
8.0%
5 5029
7.1%
0 3774
 
5.3%
8 3446
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 10176
12.7%
9 10138
12.7%
2 9224
11.5%
1 8262
10.3%
7 7699
9.6%
6 7450
9.3%
4 5696
7.1%
5 5029
6.3%
0 3774
 
4.7%
8 3446
 
4.3%
Other values (16) 9106
11.4%

지역구분
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주택가
4180 
농어촌
3393 
<NA>
1869 
번화가
 
319
야외도로
 
238

Length

Max length4
Median length3
Mean length3.2106
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row주택가
2nd row농어촌
3rd row농어촌
4th row주택가
5th row주택가

Common Values

ValueCountFrequency (%)
주택가 4180
41.8%
농어촌 3393
33.9%
<NA> 1869
18.7%
번화가 319
 
3.2%
야외도로 238
 
2.4%
공란 1
 
< 0.1%

Length

2023-12-13T08:53:18.374046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:53:18.459406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주택가 4180
41.8%
농어촌 3393
33.9%
na 1869
18.7%
번화가 319
 
3.2%
야외도로 238
 
2.4%
공란 1
 
< 0.1%

Correlations

2023-12-13T08:53:18.519521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2차순번2차사업소지역구분
2차순번1.0001.0000.341
2차사업소1.0001.0000.341
지역구분0.3410.3411.000
2023-12-13T08:53:18.592386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역구분2차순번2차사업소
지역구분1.0000.4150.415
2차순번0.4151.0001.000
2차사업소0.4151.0001.000
2023-12-13T08:53:18.664026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2차순번2차사업소지역구분
2차순번1.0001.0000.415
2차사업소1.0001.0000.415
지역구분0.4150.4151.000

Missing values

2023-12-13T08:53:16.984597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:53:17.063610image/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
2530810광주전남본부1광주전남본부직할9593X045주택가
8508110광주전남본부2여수지사3377R861농어촌
5593410광주전남본부2여수지사3563E711농어촌
2715110광주전남본부1광주전남본부직할0093Q461주택가
2425810광주전남본부1광주전남본부직할9495G702주택가
10310광주전남본부1광주전남본부직할9792B173주택가
312510광주전남본부1광주전남본부직할9794P501주택가
7919910광주전남본부2여수지사3272S612주택가
1736010광주전남본부1광주전남본부직할0094Y221주택가
4600310광주전남본부2여수지사3374P931농어촌
1차순번1차본부2차순번2차사업소전산화번호지역구분
4920610광주전남본부2여수지사3463B501주택가
5747310광주전남본부2여수지사28671234농어촌
3757210광주전남본부2여수지사3564F111농어촌
927910광주전남본부1광주전남본부직할9794Q843주택가
5432710광주전남본부2여수지사34562352농어촌
8892610광주전남본부2여수지사2777A503<NA>
5599210광주전남본부2여수지사3564H593농어촌
3808310광주전남본부2여수지사2972H391농어촌
1529410광주전남본부1광주전남본부직할9596F931농어촌
589610광주전남본부1광주전남본부직할9793B713주택가