Overview

Dataset statistics

Number of variables5
Number of observations1104
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory43.3 KiB
Average record size in memory40.1 B

Variable types

Categorical3
Text2

Dataset

Description한국전력공사와 전력공급계약을 체결한 고객중 전문대학(85301),대학교(85302),대학원(85303) 산업분류코드 고객의 고객 호수 및 계약 전력데이터 입니다.
Author한국전력공사
URLhttps://www.data.go.kr/data/15125798/fileData.do

Reproduction

Analysis started2024-01-06 12:13:57.163099
Analysis finished2024-01-06 12:14:03.038377
Duration5.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년월
Categorical

Distinct23
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
2022-01
 
48
2022-02
 
48
2022-03
 
48
2022-04
 
48
2022-05
 
48
Other values (18)
864 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-01
2nd row2022-01
3rd row2022-01
4th row2022-01
5th row2022-01

Common Values

ValueCountFrequency (%)
2022-01 48
 
4.3%
2022-02 48
 
4.3%
2022-03 48
 
4.3%
2022-04 48
 
4.3%
2022-05 48
 
4.3%
2022-06 48
 
4.3%
2022-07 48
 
4.3%
2022-08 48
 
4.3%
2022-09 48
 
4.3%
2022-10 48
 
4.3%
Other values (13) 624
56.5%

Length

2024-01-06T12:14:03.280890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-01 48
 
4.3%
2023-01 48
 
4.3%
2023-10 48
 
4.3%
2023-09 48
 
4.3%
2023-08 48
 
4.3%
2023-07 48
 
4.3%
2023-06 48
 
4.3%
2023-05 48
 
4.3%
2023-04 48
 
4.3%
2023-03 48
 
4.3%
Other values (13) 624
56.5%

시도
Categorical

Distinct17
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
서울특별시
 
69
세종특별자치시
 
69
경상북도
 
69
대구광역시
 
69
대전광역시
 
69
Other values (12)
759 

Length

Max length7
Median length5
Mean length4.8541667
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원특별자치도
2nd row강원특별자치도
3rd row경기도
4th row경기도
5th row경기도

Common Values

ValueCountFrequency (%)
서울특별시 69
 
6.2%
세종특별자치시 69
 
6.2%
경상북도 69
 
6.2%
대구광역시 69
 
6.2%
대전광역시 69
 
6.2%
부산광역시 69
 
6.2%
경기도 69
 
6.2%
충청북도 69
 
6.2%
울산광역시 69
 
6.2%
인천광역시 69
 
6.2%
Other values (7) 414
37.5%

Length

2024-01-06T12:14:03.886916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 69
 
6.2%
세종특별자치시 69
 
6.2%
충청남도 69
 
6.2%
제주특별자치도 69
 
6.2%
전라북도 69
 
6.2%
전라남도 69
 
6.2%
인천광역시 69
 
6.2%
울산광역시 69
 
6.2%
충청북도 69
 
6.2%
경기도 69
 
6.2%
Other values (7) 414
37.5%

산업분류
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
85301 전문대학
391 
85302 대학교
391 
85303 대학원
322 

Length

Max length10
Median length9
Mean length9.3541667
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row85301 전문대학
2nd row85302 대학교
3rd row85301 전문대학
4th row85302 대학교
5th row85303 대학원

Common Values

ValueCountFrequency (%)
85301 전문대학 391
35.4%
85302 대학교 391
35.4%
85303 대학원 322
29.2%

Length

2024-01-06T12:14:04.466484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:14:04.907563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
85301 391
17.7%
전문대학 391
17.7%
85302 391
17.7%
대학교 391
17.7%
85303 322
14.6%
대학원 322
14.6%

고객호수
Text

Distinct68
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
2024-01-06T12:14:05.457668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.5833333
Min length2

Characters and Unicode

Total characters3956
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)1.1%

Sample

1st row20
2nd row75
3rd row42
4th row160
5th row13
ValueCountFrequency (%)
5호 345
23.8%
미만 345
23.8%
11 67
 
4.6%
17 49
 
3.4%
55 34
 
2.3%
7 31
 
2.1%
19 27
 
1.9%
6 26
 
1.8%
54 25
 
1.7%
9 25
 
1.7%
Other values (59) 475
32.8%
2024-01-06T12:14:06.700426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1104
27.9%
5 530
13.4%
1 392
 
9.9%
호 345
 
8.7%
미 345
 
8.7%
만 345
 
8.7%
7 182
 
4.6%
2 169
 
4.3%
6 158
 
4.0%
9 117
 
3.0%
Other values (4) 269
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1817
45.9%
Space Separator 1104
27.9%
Other Letter 1035
26.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 530
29.2%
1 392
21.6%
7 182
 
10.0%
2 169
 
9.3%
6 158
 
8.7%
9 117
 
6.4%
4 73
 
4.0%
0 72
 
4.0%
8 68
 
3.7%
3 56
 
3.1%
Other Letter
ValueCountFrequency (%)
호 345
33.3%
미 345
33.3%
만 345
33.3%
Space Separator
ValueCountFrequency (%)
1104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2921
73.8%
Hangul 1035
 
26.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1104
37.8%
5 530
18.1%
1 392
 
13.4%
7 182
 
6.2%
2 169
 
5.8%
6 158
 
5.4%
9 117
 
4.0%
4 73
 
2.5%
0 72
 
2.5%
8 68
 
2.3%
Hangul
ValueCountFrequency (%)
호 345
33.3%
미 345
33.3%
만 345
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2921
73.8%
Hangul 1035
 
26.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1104
37.8%
5 530
18.1%
1 392
 
13.4%
7 182
 
6.2%
2 169
 
5.8%
6 158
 
5.4%
9 117
 
4.0%
4 73
 
2.5%
0 72
 
2.5%
8 68
 
2.3%
Hangul
ValueCountFrequency (%)
호 345
33.3%
미 345
33.3%
만 345
33.3%

계약전력합계
Text

Distinct174
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
2024-01-06T12:14:07.500088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.5099638
Min length4

Characters and Unicode

Total characters6083
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)5.7%

Sample

1st row28750
2nd row119578
3rd row150490
4th row374554
5th row8285
ValueCountFrequency (%)
5호미만 345
31.2%
24002 23
 
2.1%
17900 23
 
2.1%
26347 23
 
2.1%
7636 23
 
2.1%
36428 23
 
2.1%
20306 22
 
2.0%
39330 22
 
2.0%
8317 20
 
1.8%
28750 20
 
1.8%
Other values (164) 560
50.7%
2024-01-06T12:14:08.908783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
759
12.5%
5 641
10.5%
2 554
9.1%
3 500
 
8.2%
0 492
 
8.1%
9 378
 
6.2%
1 373
 
6.1%
6 357
 
5.9%
호 345
 
5.7%
미 345
 
5.7%
Other values (4) 1339
22.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4289
70.5%
Other Letter 1035
 
17.0%
Space Separator 759
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 641
14.9%
2 554
12.9%
3 500
11.7%
0 492
11.5%
9 378
8.8%
1 373
8.7%
6 357
8.3%
7 336
7.8%
4 334
7.8%
8 324
7.6%
Other Letter
ValueCountFrequency (%)
호 345
33.3%
미 345
33.3%
만 345
33.3%
Space Separator
ValueCountFrequency (%)
759
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5048
83.0%
Hangul 1035
 
17.0%

Most frequent character per script

Common
ValueCountFrequency (%)
759
15.0%
5 641
12.7%
2 554
11.0%
3 500
9.9%
0 492
9.7%
9 378
7.5%
1 373
7.4%
6 357
7.1%
7 336
6.7%
4 334
6.6%
Hangul
ValueCountFrequency (%)
호 345
33.3%
미 345
33.3%
만 345
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5048
83.0%
Hangul 1035
 
17.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
759
15.0%
5 641
12.7%
2 554
11.0%
3 500
9.9%
0 492
9.7%
9 378
7.5%
1 373
7.4%
6 357
7.1%
7 336
6.7%
4 334
6.6%
Hangul
ValueCountFrequency (%)
호 345
33.3%
미 345
33.3%
만 345
33.3%

Correlations

2024-01-06T12:14:09.211589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월시도산업분류고객호수
년월1.0000.0000.0000.000
시도0.0001.0000.2250.975
산업분류0.0000.2251.0000.973
고객호수0.0000.9750.9731.000
2024-01-06T12:14:09.569202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
산업분류시도년월
산업분류1.0000.1220.000
시도0.1221.0000.000
년월0.0000.0001.000
2024-01-06T12:14:09.973827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월시도산업분류
년월1.0000.0000.000
시도0.0001.0000.122
산업분류0.0000.1221.000

Missing values

2024-01-06T12:14:02.307599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-06T12:14:02.770785image/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

년월시도산업분류고객호수계약전력합계
02022-01강원특별자치도85301 전문대학2028750
12022-01강원특별자치도85302 대학교75119578
22022-01경기도85301 전문대학42150490
32022-01경기도85302 대학교160374554
42022-01경기도85303 대학원138285
52022-01경상남도85301 전문대학2438925
62022-01경상남도85302 대학교6699683
72022-01경상북도85301 전문대학2638349
82022-01경상북도85302 대학교77244930
92022-01경상북도85303 대학원5호 미만5호미만
년월시도산업분류고객호수계약전력합계
10942023-11전라북도85303 대학원5호 미만5호미만
10952023-11제주특별자치도85301 전문대학5호 미만5호미만
10962023-11제주특별자치도85302 대학교1924659
10972023-11제주특별자치도85303 대학원5호 미만5호미만
10982023-11충청남도85301 전문대학1139330
10992023-11충청남도85302 대학교88222787
11002023-11충청남도85303 대학원67636
11012023-11충청북도85301 전문대학5호 미만5호미만
11022023-11충청북도85302 대학교62143048
11032023-11충청북도85303 대학원5호 미만5호미만