Overview

Dataset statistics

Number of variables3
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory312.5 KiB
Average record size in memory32.0 B

Variable types

Categorical2
Text1

Dataset

Description한국전력공사에서 제공하는 경기북부 지역 전주전산화번호(전주번호)입니다. 해당데이터는 1차 본부명, 2차 사업소 명, 전산화 번호로 이루어져 있습니다.
URLhttps://www.data.go.kr/data/15069500/fileData.do

Alerts

본부명 has constant value ""Constant
전산화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:59:21.751781
Analysis finished2023-12-12 19:59:22.126864
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

본부명
Categorical

CONSTANT 

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

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기북부본부 10000
100.0%

Length

2023-12-13T04:59:22.276804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:59:22.416891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기북부본부 10000
100.0%

사업소명
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
포천지사
3100 
고양지사
2803 
경기북부본부직할
2418 
동두천지사
1672 
파주지사
 
6

Length

Max length8
Median length4
Mean length5.1344
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row고양지사
2nd row경기북부본부직할
3rd row포천지사
4th row고양지사
5th row포천지사

Common Values

ValueCountFrequency (%)
포천지사 3100
31.0%
고양지사 2803
28.0%
경기북부본부직할 2418
24.2%
동두천지사 1672
16.7%
파주지사 6
 
0.1%
연천지사 1
 
< 0.1%

Length

2023-12-13T04:59:22.578949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:59:22.712811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
포천지사 3100
31.0%
고양지사 2803
28.0%
경기북부본부직할 2418
24.2%
동두천지사 1672
16.7%
파주지사 6
 
0.1%
연천지사 1
 
< 0.1%

전산화번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T04:59:23.026255image/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

Unique10000 ?
Unique (%)100.0%

Sample

1st row9636X241
2nd row0439H933
3rd row0841P581
4th row8831F271
5th row1247R401
ValueCountFrequency (%)
9636x241 1
 
< 0.1%
0839c051 1
 
< 0.1%
9940q941 1
 
< 0.1%
9939f361 1
 
< 0.1%
0844a621 1
 
< 0.1%
9434q542 1
 
< 0.1%
0044b341 1
 
< 0.1%
8930a281 1
 
< 0.1%
9940f551 1
 
< 0.1%
9734w202 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-13T04:59:23.466143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11935
14.9%
3 10043
12.6%
0 8491
10.6%
4 8154
10.2%
2 8016
10.0%
9 7552
9.4%
5 4795
6.0%
8 4250
 
5.3%
7 3464
 
4.3%
6 3455
 
4.3%
Other values (17) 9845
12.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70155
87.7%
Uppercase Letter 9845
 
12.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
W 680
 
6.9%
G 677
 
6.9%
Q 658
 
6.7%
Y 656
 
6.7%
Z 646
 
6.6%
P 633
 
6.4%
B 628
 
6.4%
C 622
 
6.3%
D 621
 
6.3%
X 617
 
6.3%
Other values (7) 3407
34.6%
Decimal Number
ValueCountFrequency (%)
1 11935
17.0%
3 10043
14.3%
0 8491
12.1%
4 8154
11.6%
2 8016
11.4%
9 7552
10.8%
5 4795
6.8%
8 4250
 
6.1%
7 3464
 
4.9%
6 3455
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
Common 70155
87.7%
Latin 9845
 
12.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
W 680
 
6.9%
G 677
 
6.9%
Q 658
 
6.7%
Y 656
 
6.7%
Z 646
 
6.6%
P 633
 
6.4%
B 628
 
6.4%
C 622
 
6.3%
D 621
 
6.3%
X 617
 
6.3%
Other values (7) 3407
34.6%
Common
ValueCountFrequency (%)
1 11935
17.0%
3 10043
14.3%
0 8491
12.1%
4 8154
11.6%
2 8016
11.4%
9 7552
10.8%
5 4795
6.8%
8 4250
 
6.1%
7 3464
 
4.9%
6 3455
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11935
14.9%
3 10043
12.6%
0 8491
10.6%
4 8154
10.2%
2 8016
10.0%
9 7552
9.4%
5 4795
6.0%
8 4250
 
5.3%
7 3464
 
4.3%
6 3455
 
4.3%
Other values (17) 9845
12.3%

Missing values

2023-12-13T04:59:21.965672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:59:22.066470image/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

본부명사업소명전산화번호
49495경기북부본부고양지사9636X241
17584경기북부본부경기북부본부직할0439H933
79438경기북부본부포천지사0841P581
36990경기북부본부고양지사8831F271
66311경기북부본부포천지사1247R401
61534경기북부본부동두천지사0042Q093
93571경기북부본부포천지사0641F892
20273경기북부본부경기북부본부직할9941C261
5206경기북부본부경기북부본부직할0233G071
51239경기북부본부동두천지사0041A521
본부명사업소명전산화번호
68932경기북부본부포천지사0548Z871
14198경기북부본부경기북부본부직할0336D873
17575경기북부본부경기북부본부직할0439H813
93310경기북부본부포천지사1245B411
17956경기북부본부경기북부본부직할0038E821
86078경기북부본부포천지사0948E161
76076경기북부본부포천지사0641B961
34150경기북부본부고양지사9234Y771
26864경기북부본부고양지사9033Y334
1505경기북부본부경기북부본부직할0536E771