Overview

Dataset statistics

Number of variables5
Number of observations324
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.7 KiB
Average record size in memory43.4 B

Variable types

Categorical2
DateTime1
Numeric2

Dataset

Description각 년도별 지역본부의 용도별(발전공급,도시가스공급)가스 공급량을 보여주는 자료이며, 각 지역본부 별 가스공급 점유율을 표시한 자료 입니다.
Author한국가스공사
URLhttps://www.data.go.kr/data/15049902/fileData.do

Alerts

발전 공급량 is highly overall correlated with 도시가스 공급량 and 1 other fieldsHigh correlation
도시가스 공급량 is highly overall correlated with 발전 공급량High correlation
지역본부 is highly overall correlated with 발전 공급량High correlation
발전 공급량 has unique valuesUnique
도시가스 공급량 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:21:25.538508
Analysis finished2023-12-12 01:21:26.385965
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Categorical

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2021
108 
2020
108 
2019
108 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 108
33.3%
2020 108
33.3%
2019 108
33.3%

Length

2023-12-12T10:21:26.457816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:21:26.573754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 108
33.3%
2020 108
33.3%
2019 108
33.3%

월
Date

Distinct12
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
Minimum1900-01-01 00:00:00
Maximum1900-01-12 00:00:00
2023-12-12T10:21:26.683139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:21:26.832587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

지역본부
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
서울
36 
인천
36 
경기
36 
강원
36 
대전.충청
36 
Other values (4)
144 

Length

Max length5
Median length2
Mean length3.3333333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울
2nd row인천
3rd row경기
4th row강원
5th row대전.충청

Common Values

ValueCountFrequency (%)
서울 36
11.1%
인천 36
11.1%
경기 36
11.1%
강원 36
11.1%
대전.충청 36
11.1%
전북 36
11.1%
광주.전남 36
11.1%
대구.경북 36
11.1%
부산.경남 36
11.1%

Length

2023-12-12T10:21:27.044515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:21:27.218237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울 36
11.1%
인천 36
11.1%
경기 36
11.1%
강원 36
11.1%
대전.충청 36
11.1%
전북 36
11.1%
광주.전남 36
11.1%
대구.경북 36
11.1%
부산.경남 36
11.1%

발전 공급량
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct324
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean206028.82
Minimum0
Maximum707668
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-12T10:21:27.434309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile31259.6
Q171335.75
median141744
Q3325825.25
95-th percentile499767.7
Maximum707668
Range707668
Interquartile range (IQR)254489.5

Descriptive statistics

Standard deviation161250.58
Coefficient of variation (CV)0.78266033
Kurtosis-0.20548771
Mean206028.82
Median Absolute Deviation (MAD)103335.5
Skewness0.80359972
Sum66753338
Variance2.6001751 × 1010
MonotonicityNot monotonic
2023-12-12T10:21:27.635626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
575358 1
 
0.3%
128360 1
 
0.3%
121011 1
 
0.3%
137942 1
 
0.3%
50950 1
 
0.3%
50916 1
 
0.3%
582009 1
 
0.3%
283613 1
 
0.3%
481915 1
 
0.3%
340353 1
 
0.3%
Other values (314) 314
96.9%
ValueCountFrequency (%)
0 1
0.3%
4213 1
0.3%
7290 1
0.3%
15751 1
0.3%
15950 1
0.3%
18461 1
0.3%
18705 1
0.3%
21560 1
0.3%
21698 1
0.3%
22171 1
0.3%
ValueCountFrequency (%)
707668 1
0.3%
695456 1
0.3%
663121 1
0.3%
642568 1
0.3%
634403 1
0.3%
598908 1
0.3%
582009 1
0.3%
575358 1
0.3%
572595 1
0.3%
571203 1
0.3%

도시가스 공급량
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct324
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean172021.77
Minimum29644
Maximum762786
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-12T10:21:27.855276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum29644
5-th percentile45685.35
Q180340.5
median134626
Q3207516.25
95-th percentile459982.1
Maximum762786
Range733142
Interquartile range (IQR)127175.75

Descriptive statistics

Standard deviation132832.34
Coefficient of variation (CV)0.77218335
Kurtosis3.31325
Mean172021.77
Median Absolute Deviation (MAD)60407.5
Skewness1.7679241
Sum55735052
Variance1.7644432 × 1010
MonotonicityNot monotonic
2023-12-12T10:21:28.074681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
762786 1
 
0.3%
98803 1
 
0.3%
147409 1
 
0.3%
154113 1
 
0.3%
254187 1
 
0.3%
84015 1
 
0.3%
475745 1
 
0.3%
195911 1
 
0.3%
715200 1
 
0.3%
480425 1
 
0.3%
Other values (314) 314
96.9%
ValueCountFrequency (%)
29644 1
0.3%
29813 1
0.3%
30474 1
0.3%
30624 1
0.3%
30787 1
0.3%
31199 1
0.3%
32453 1
0.3%
33343 1
0.3%
33813 1
0.3%
33929 1
0.3%
ValueCountFrequency (%)
762786 1
0.3%
715200 1
0.3%
658929 1
0.3%
653209 1
0.3%
617690 1
0.3%
610990 1
0.3%
577470 1
0.3%
550733 1
0.3%
540276 1
0.3%
539311 1
0.3%

Interactions

2023-12-12T10:21:25.975388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:21:25.765374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:21:26.077007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:21:25.874799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:21:28.206813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도월지역본부발전 공급량도시가스 공급량
년도1.0000.0000.0000.0000.000
월0.0001.0000.0000.1070.476
지역본부0.0000.0001.0000.8060.570
발전 공급량0.0000.1070.8061.0000.777
도시가스 공급량0.0000.4760.5700.7771.000
2023-12-12T10:21:28.325469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도지역본부
년도1.0000.000
지역본부0.0001.000
2023-12-12T10:21:28.429207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발전 공급량도시가스 공급량년도지역본부
발전 공급량1.0000.5620.0000.536
도시가스 공급량0.5621.0000.0000.303
년도0.0000.0001.0000.000
지역본부0.5360.3030.0001.000

Missing values

2023-12-12T10:21:26.223025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:21:26.347684image/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

년도월지역본부발전 공급량도시가스 공급량
020211900-01-01서울575358762786
120211900-01-01인천386926206023
220211900-01-01경기707668527063
320211900-01-01강원5050399133
420211900-01-01대전.충청54035270644
520211900-01-01전북172058173628
620211900-01-01광주.전남151396166871
720211900-01-01대구.경북102758294160
820211900-01-01부산.경남340489550733
920211900-01-02서울430898540276
년도월지역본부발전 공급량도시가스 공급량
31420191900-01-11부산.경남253400321868
31520191900-01-12서울548381617690
31620191900-01-12인천392322171463
31720191900-01-12경기663121425593
31820191900-01-12강원3236879168
31920191900-01-12대전.충청51232227829
32020191900-01-12전북118902135803
32120191900-01-12광주.전남154075134686
32220191900-01-12대구.경북102552245961
32320191900-01-12부산.경남285271429269