Overview

Dataset statistics

Number of variables14
Number of observations608
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory68.4 KiB
Average record size in memory115.2 B

Variable types

Categorical13
Text1

Dataset

Description한국전력공사의 판매전력량을 용도별(가정용, 공공용, 제조업 등), 행정구역별로 나타낸 데이터
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=3107

Alerts

통계표ID has constant value ""Constant
기관코드 has constant value ""Constant
수록주기 has constant value ""Constant
단위명 has constant value ""Constant
단위영문명 has constant value ""Constant
수록시점 has constant value ""Constant
통계표명 has constant value ""Constant
분류명1 has constant value ""Constant
수집날짜 has constant value ""Constant
항목 ID is highly overall correlated with 항목명High correlation
항목명 is highly overall correlated with 항목 IDHigh correlation
분류값 ID1 is highly overall correlated with 분류값 명1High correlation
분류값 명1 is highly overall correlated with 분류값 ID1High correlation

Reproduction

Analysis started2024-01-09 22:05:28.970581
Analysis finished2024-01-09 22:05:29.542247
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계표ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
DT_31002_A006
608 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDT_31002_A006
2nd rowDT_31002_A006
3rd rowDT_31002_A006
4th rowDT_31002_A006
5th rowDT_31002_A006

Common Values

ValueCountFrequency (%)
DT_31002_A006 608
100.0%

Length

2024-01-10T07:05:29.591816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:05:29.661736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
dt_31002_a006 608
100.0%

기관코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
310
608 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row310
2nd row310
3rd row310
4th row310
5th row310

Common Values

ValueCountFrequency (%)
310 608
100.0%

Length

2024-01-10T07:05:29.733833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:05:29.805210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
310 608
100.0%

수록주기
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
A
608 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
A 608
100.0%

Length

2024-01-10T07:05:29.877555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:05:29.949101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a 608
100.0%

항목명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
부산
 
32
충북
 
32
충남
 
32
대전
 
32
대구
 
32
Other values (14)
448 

Length

Max length2
Median length2
Mean length1.9473684
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산
2nd row충북
3rd row충남
4th row대전
5th row대구

Common Values

ValueCountFrequency (%)
부산 32
 
5.3%
충북 32
 
5.3%
충남 32
 
5.3%
대전 32
 
5.3%
대구 32
 
5.3%
개성 32
 
5.3%
강원 32
 
5.3%
광주 32
 
5.3%
경북 32
 
5.3%
경기 32
 
5.3%
Other values (9) 288
47.4%

Length

2024-01-10T07:05:30.023981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산 32
 
5.3%
경남 32
 
5.3%
계 32
 
5.3%
서울 32
 
5.3%
세종 32
 
5.3%
전남 32
 
5.3%
전북 32
 
5.3%
제주 32
 
5.3%
인천 32
 
5.3%
경기 32
 
5.3%
Other values (9) 288
47.4%

항목 ID
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
BUSAN
 
32
CHUNGBUK
 
32
CHUNGNAM
 
32
DAEJEON
 
32
DEAGU
 
32
Other values (14)
448 

Length

Max length9
Median length8
Mean length6.6842105
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBUSAN
2nd rowCHUNGBUK
3rd rowCHUNGNAM
4th rowDAEJEON
5th rowDEAGU

Common Values

ValueCountFrequency (%)
BUSAN 32
 
5.3%
CHUNGBUK 32
 
5.3%
CHUNGNAM 32
 
5.3%
DAEJEON 32
 
5.3%
DEAGU 32
 
5.3%
GAESEONG 32
 
5.3%
GANGWON 32
 
5.3%
GWANGJU 32
 
5.3%
GYEONGBUK 32
 
5.3%
GYEONGGI 32
 
5.3%
Other values (9) 288
47.4%

Length

2024-01-10T07:05:30.115559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
busan 32
 
5.3%
gyeongnam 32
 
5.3%
total 32
 
5.3%
seoul 32
 
5.3%
sejong 32
 
5.3%
jeonnam 32
 
5.3%
jeonbuk 32
 
5.3%
jeju 32
 
5.3%
incheon 32
 
5.3%
gyeonggi 32
 
5.3%
Other values (9) 288
47.4%

단위명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
MWh
608 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
MWh 608
100.0%

Length

2024-01-10T07:05:30.205880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:05:30.280414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mwh 608
100.0%

분류값 ID1
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
01
 
19
01_01
 
19
01_02
 
19
01_03
 
19
01_04
 
19
Other values (27)
513 

Length

Max length8
Median length8
Mean length7.25
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row01
2nd row01
3rd row01
4th row01
5th row01

Common Values

ValueCountFrequency (%)
01 19
 
3.1%
01_01 19
 
3.1%
01_02 19
 
3.1%
01_03 19
 
3.1%
01_04 19
 
3.1%
01_05 19
 
3.1%
01_07 19
 
3.1%
01_07_01 19
 
3.1%
01_07_02 19
 
3.1%
01_07_03 19
 
3.1%
Other values (22) 418
68.8%

Length

2024-01-10T07:05:30.377561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
01 19
 
3.1%
01_01 19
 
3.1%
01_07_24 19
 
3.1%
01_07_23 19
 
3.1%
01_07_22 19
 
3.1%
01_07_21 19
 
3.1%
01_07_20 19
 
3.1%
01_07_19 19
 
3.1%
01_07_18 19
 
3.1%
01_07_17 19
 
3.1%
Other values (22) 418
68.8%

단위영문명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
MWh
608 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
MWh 608
100.0%

Length

2024-01-10T07:05:30.477947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:05:30.549074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mwh 608
100.0%

수치값
Text

Distinct571
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-01-10T07:05:30.731568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.4194079
Min length1

Characters and Unicode

Total characters3295
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique569 ?
Unique (%)93.6%

Sample

1st row21493648
2nd row29412227
3rd row50259638
4th row10016877
5th row16039260
ValueCountFrequency (%)
37
 
6.1%
7 2
 
0.3%
10469 1
 
0.2%
45593 1
 
0.2%
790408 1
 
0.2%
152764 1
 
0.2%
3634607 1
 
0.2%
21493648 1
 
0.2%
2647 1
 
0.2%
1032633 1
 
0.2%
Other values (561) 561
92.3%
2024-01-10T07:05:31.060477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 464
14.1%
2 347
10.5%
3 332
10.1%
5 329
10.0%
4 316
9.6%
6 314
9.5%
9 299
9.1%
0 293
8.9%
7 291
8.8%
8 273
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3258
98.9%
Dash Punctuation 37
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 464
14.2%
2 347
10.7%
3 332
10.2%
5 329
10.1%
4 316
9.7%
6 314
9.6%
9 299
9.2%
0 293
9.0%
7 291
8.9%
8 273
8.4%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3295
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 464
14.1%
2 347
10.5%
3 332
10.1%
5 329
10.0%
4 316
9.6%
6 314
9.5%
9 299
9.1%
0 293
8.9%
7 291
8.8%
8 273
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3295
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 464
14.1%
2 347
10.5%
3 332
10.1%
5 329
10.0%
4 316
9.6%
6 314
9.5%
9 299
9.1%
0 293
8.9%
7 291
8.8%
8 273
8.3%

분류값 명1
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
합계
 
19
가정용
 
19
공공용
 
19
서비스업
 
19
농림어업
 
19
Other values (27)
513 

Length

Max length8
Median length4
Mean length3.59375
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
합계 19
 
3.1%
가정용 19
 
3.1%
공공용 19
 
3.1%
서비스업 19
 
3.1%
농림어업 19
 
3.1%
광업 19
 
3.1%
제조업(10차) 19
 
3.1%
식료품 19
 
3.1%
음료 19
 
3.1%
담배 19
 
3.1%
Other values (22) 418
68.8%

Length

2024-01-10T07:05:31.178208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
합계 19
 
3.1%
가정용 19
 
3.1%
기타제품 19
 
3.1%
가구 19
 
3.1%
기타운송 19
 
3.1%
자동차 19
 
3.1%
기타기계 19
 
3.1%
전기장비 19
 
3.1%
의료광학 19
 
3.1%
전자통신 19
 
3.1%
Other values (22) 418
68.8%

수록시점
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2022
608 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2022 608
100.0%

Length

2024-01-10T07:05:31.279857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:05:31.354301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 608
100.0%

통계표명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
행정구역별 용도별 판매전력량
608 

Length

Max length15
Median length15
Mean length15
Min length15

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row행정구역별 용도별 판매전력량
2nd row행정구역별 용도별 판매전력량
3rd row행정구역별 용도별 판매전력량
4th row행정구역별 용도별 판매전력량
5th row행정구역별 용도별 판매전력량

Common Values

ValueCountFrequency (%)
행정구역별 용도별 판매전력량 608
100.0%

Length

2024-01-10T07:05:31.430127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:05:31.502266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
행정구역별 608
33.3%
용도별 608
33.3%
판매전력량 608
33.3%

분류명1
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
용도별
608 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용도별 608
100.0%

Length

2024-01-10T07:05:31.574867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:05:31.646061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용도별 608
100.0%

수집날짜
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
20231109
608 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20231109
2nd row20231109
3rd row20231109
4th row20231109
5th row20231109

Common Values

ValueCountFrequency (%)
20231109 608
100.0%

Length

2024-01-10T07:05:31.717730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:05:31.786637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20231109 608
100.0%

Correlations

2024-01-10T07:05:31.832472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
항목명항목 ID분류값 ID1분류값 명1
항목명1.0001.0000.0000.000
항목 ID1.0001.0000.0000.000
분류값 ID10.0000.0001.0001.000
분류값 명10.0000.0001.0001.000
2024-01-10T07:05:31.904502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
항목 ID항목명분류값 ID1분류값 명1
항목 ID1.0001.0000.0000.000
항목명1.0001.0000.0000.000
분류값 ID10.0000.0001.0001.000
분류값 명10.0000.0001.0001.000
2024-01-10T07:05:31.984839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
항목명항목 ID분류값 ID1분류값 명1
항목명1.0001.0000.0000.000
항목 ID1.0001.0000.0000.000
분류값 ID10.0000.0001.0001.000
분류값 명10.0000.0001.0001.000

Missing values

2024-01-10T07:05:29.352252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:05:29.487709image/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

통계표ID기관코드수록주기항목명항목 ID단위명분류값 ID1단위영문명수치값분류값 명1수록시점통계표명분류명1수집날짜
0DT_31002_A006310A부산BUSANMWh01MWh21493648합계2022행정구역별 용도별 판매전력량용도별20231109
1DT_31002_A006310A충북CHUNGBUKMWh01MWh29412227합계2022행정구역별 용도별 판매전력량용도별20231109
2DT_31002_A006310A충남CHUNGNAMMWh01MWh50259638합계2022행정구역별 용도별 판매전력량용도별20231109
3DT_31002_A006310A대전DAEJEONMWh01MWh10016877합계2022행정구역별 용도별 판매전력량용도별20231109
4DT_31002_A006310A대구DEAGUMWh01MWh16039260합계2022행정구역별 용도별 판매전력량용도별20231109
5DT_31002_A006310A개성GAESEONGMWh01MWh-합계2022행정구역별 용도별 판매전력량용도별20231109
6DT_31002_A006310A강원GANGWONMWh01MWh17325520합계2022행정구역별 용도별 판매전력량용도별20231109
7DT_31002_A006310A광주GWANGJUMWh01MWh9116871합계2022행정구역별 용도별 판매전력량용도별20231109
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598DT_31002_A006310A경기GYEONGGIMWh01_07_25MWh15791산업기계2022행정구역별 용도별 판매전력량용도별20231109
599DT_31002_A006310A경남GYEONGNAMMWh01_07_25MWh10469산업기계2022행정구역별 용도별 판매전력량용도별20231109
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605DT_31002_A006310A서울SEOULMWh01_07_25MWh1476산업기계2022행정구역별 용도별 판매전력량용도별20231109
606DT_31002_A006310A계TOTALMWh01_07_25MWh80369산업기계2022행정구역별 용도별 판매전력량용도별20231109
607DT_31002_A006310A울산ULSANMWh01_07_25MWh1058산업기계2022행정구역별 용도별 판매전력량용도별20231109