Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)< 0.1%
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/15069501/fileData.do

Alerts

1차순번 has constant value ""Constant
1차본부 has constant value ""Constant
Dataset has 1 (< 0.1%) duplicate rowsDuplicates
2차순번 is highly overall correlated with 2차사업소High correlation
2차사업소 is highly overall correlated with 2차순번High correlation

Reproduction

Analysis started2023-12-12 11:55:21.216568
Analysis finished2023-12-12 11:55:21.980535
Duration0.76 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
5
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5 10000
100.0%

Length

2023-12-12T20:55:22.050185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:55:22.163548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 10000
100.0%

1차본부
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기본부 10000
100.0%

Length

2023-12-12T20:55:22.263210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:55:22.363236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기본부 10000
100.0%

2차순번
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
3929 
2
2685 
1
1972 
4
1414 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row3
4th row3
5th row4

Common Values

ValueCountFrequency (%)
3 3929
39.3%
2 2685
26.9%
1 1972
19.7%
4 1414
 
14.1%

Length

2023-12-12T20:55:22.496337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:55:22.635375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3929
39.3%
2 2685
26.9%
1 1972
19.7%
4 1414
 
14.1%

2차사업소
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
안산지사
3929 
안양지사
2685 
경기본부직할
1972 
성남지사
1414 

Length

Max length6
Median length4
Mean length4.3944
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기본부직할
2nd row경기본부직할
3rd row안산지사
4th row안산지사
5th row성남지사

Common Values

ValueCountFrequency (%)
안산지사 3929
39.3%
안양지사 2685
26.9%
경기본부직할 1972
19.7%
성남지사 1414
 
14.1%

Length

2023-12-12T20:55:22.783481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:55:22.928189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안산지사 3929
39.3%
안양지사 2685
26.9%
경기본부직할 1972
19.7%
성남지사 1414
 
14.1%

전산화번호
Text

Distinct9999
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:55:23.344547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters80000
Distinct characters27
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

Unique9998 ?
Unique (%)> 99.9%

Sample

1st row9811H782
2nd row0309W672
3rd row9011F155
4th row9113D095
5th row0215W813
ValueCountFrequency (%)
9414f862 2
 
< 0.1%
9111c181 1
 
< 0.1%
0012r021 1
 
< 0.1%
9013q624 1
 
< 0.1%
9212e143 1
 
< 0.1%
0819q401 1
 
< 0.1%
0011a102 1
 
< 0.1%
9910a481 1
 
< 0.1%
9715w991 1
 
< 0.1%
0619h081 1
 
< 0.1%
Other values (9989) 9989
99.9%
2023-12-12T20:55:23.927746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18007
22.5%
9 9471
11.8%
0 8319
10.4%
2 7158
 
8.9%
3 5860
 
7.3%
8 5000
 
6.2%
4 4692
 
5.9%
7 4129
 
5.2%
6 4027
 
5.0%
5 3332
 
4.2%
Other values (17) 10005
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69995
87.5%
Uppercase Letter 10005
 
12.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
W 754
 
7.5%
S 712
 
7.1%
Q 702
 
7.0%
X 660
 
6.6%
H 657
 
6.6%
E 633
 
6.3%
Y 626
 
6.3%
P 620
 
6.2%
G 612
 
6.1%
Z 609
 
6.1%
Other values (7) 3420
34.2%
Decimal Number
ValueCountFrequency (%)
1 18007
25.7%
9 9471
13.5%
0 8319
11.9%
2 7158
 
10.2%
3 5860
 
8.4%
8 5000
 
7.1%
4 4692
 
6.7%
7 4129
 
5.9%
6 4027
 
5.8%
5 3332
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common 69995
87.5%
Latin 10005
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
W 754
 
7.5%
S 712
 
7.1%
Q 702
 
7.0%
X 660
 
6.6%
H 657
 
6.6%
E 633
 
6.3%
Y 626
 
6.3%
P 620
 
6.2%
G 612
 
6.1%
Z 609
 
6.1%
Other values (7) 3420
34.2%
Common
ValueCountFrequency (%)
1 18007
25.7%
9 9471
13.5%
0 8319
11.9%
2 7158
 
10.2%
3 5860
 
8.4%
8 5000
 
7.1%
4 4692
 
6.7%
7 4129
 
5.9%
6 4027
 
5.8%
5 3332
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18007
22.5%
9 9471
11.8%
0 8319
10.4%
2 7158
 
8.9%
3 5860
 
7.3%
8 5000
 
6.2%
4 4692
 
5.9%
7 4129
 
5.2%
6 4027
 
5.0%
5 3332
 
4.2%
Other values (17) 10005
12.5%

지역구분
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주택가
4664 
<NA>
4332 
농어촌
760 
번화가
 
244

Length

Max length4
Median length3
Mean length3.4332
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주택가 4664
46.6%
<NA> 4332
43.3%
농어촌 760
 
7.6%
번화가 244
 
2.4%

Length

2023-12-12T20:55:24.147237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:55:24.275022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주택가 4664
46.6%
na 4332
43.3%
농어촌 760
 
7.6%
번화가 244
 
2.4%

Correlations

2023-12-12T20:55:24.350457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2차순번2차사업소지역구분
2차순번1.0001.0000.110
2차사업소1.0001.0000.110
지역구분0.1100.1101.000
2023-12-12T20:55:24.480416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2차순번지역구분2차사업소
2차순번1.0000.1031.000
지역구분0.1031.0000.103
2차사업소1.0000.1031.000
2023-12-12T20:55:24.623473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2차순번2차사업소지역구분
2차순번1.0001.0000.103
2차사업소1.0001.0000.103
지역구분0.1030.1031.000

Missing values

2023-12-12T20:55:21.763012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:55:21.915643image/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
179695경기본부1경기본부직할9811H782<NA>
105535경기본부1경기본부직할0309W672주택가
739625경기본부3안산지사9011F155주택가
768655경기본부3안산지사9113D095주택가
931565경기본부4성남지사0215W813농어촌
888615경기본부4성남지사0618C253주택가
722385경기본부3안산지사9511C321<NA>
450865경기본부3안산지사8812D004<NA>
154315경기본부1경기본부직할9912G341주택가
666735경기본부3안산지사9411W942주택가
1차순번1차본부2차순번2차사업소전산화번호지역구분
95865경기본부1경기본부직할0210Z401<NA>
747485경기본부3안산지사9314A222주택가
189295경기본부1경기본부직할0011C465<NA>
248465경기본부2안양지사9714X501주택가
21585경기본부1경기본부직할0010S172<NA>
683215경기본부3안산지사8912F291주택가
330445경기본부2안양지사9712E021주택가
225805경기본부2안양지사9715F281번화가
286285경기본부2안양지사9616D632주택가
370885경기본부2안양지사9612D952농어촌

Duplicate rows

Most frequently occurring

1차순번1차본부2차순번2차사업소전산화번호지역구분# duplicates
05경기본부3안산지사9414F862<NA>2