Overview

Dataset statistics

Number of variables3
Number of observations28
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory888.0 B
Average record size in memory31.7 B

Variable types

Numeric3

Dataset

Description상업용 에너지소비량 대비 일반용 도시가스 수요 비중은 총 상업용 에너지소비량에서 도시가스 소비량이 차지하는 비중을 나타낸다. 상기 비중은 총 에너지에서 도시가스 소비량의 비중을 보여주기에 에너지원 믹스를 파악할 수 있다. 또한 이는 미시전망모형에서 총에너지수요전망에서 도시가스 수요전망치를 산출하는데 이용된다.
Author한국가스공사
URLhttps://www.data.go.kr/data/15102802/fileData.do

Alerts

순번 is highly overall correlated with 연도 and 1 other fieldsHigh correlation
연도 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
가스비중 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
순번 has unique valuesUnique
연도 has unique valuesUnique
가스비중 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:32:11.433866
Analysis finished2023-12-12 03:32:12.954079
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.5
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-12T12:32:13.054644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.35
Q17.75
median14.5
Q321.25
95-th percentile26.65
Maximum28
Range27
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation8.2259751
Coefficient of variation (CV)0.56730863
Kurtosis-1.2
Mean14.5
Median Absolute Deviation (MAD)7
Skewness0
Sum406
Variance67.666667
MonotonicityStrictly increasing
2023-12-12T12:32:13.259695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 1
 
3.6%
16 1
 
3.6%
28 1
 
3.6%
27 1
 
3.6%
26 1
 
3.6%
25 1
 
3.6%
24 1
 
3.6%
23 1
 
3.6%
22 1
 
3.6%
21 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
1 1
3.6%
2 1
3.6%
3 1
3.6%
4 1
3.6%
5 1
3.6%
6 1
3.6%
7 1
3.6%
8 1
3.6%
9 1
3.6%
10 1
3.6%
ValueCountFrequency (%)
28 1
3.6%
27 1
3.6%
26 1
3.6%
25 1
3.6%
24 1
3.6%
23 1
3.6%
22 1
3.6%
21 1
3.6%
20 1
3.6%
19 1
3.6%

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2006.5
Minimum1993
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-12T12:32:13.455360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1993
5-th percentile1994.35
Q11999.75
median2006.5
Q32013.25
95-th percentile2018.65
Maximum2020
Range27
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation8.2259751
Coefficient of variation (CV)0.0040996637
Kurtosis-1.2
Mean2006.5
Median Absolute Deviation (MAD)7
Skewness0
Sum56182
Variance67.666667
MonotonicityStrictly increasing
2023-12-12T12:32:13.679097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1993 1
 
3.6%
2008 1
 
3.6%
2020 1
 
3.6%
2019 1
 
3.6%
2018 1
 
3.6%
2017 1
 
3.6%
2016 1
 
3.6%
2015 1
 
3.6%
2014 1
 
3.6%
2013 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
1993 1
3.6%
1994 1
3.6%
1995 1
3.6%
1996 1
3.6%
1997 1
3.6%
1998 1
3.6%
1999 1
3.6%
2000 1
3.6%
2001 1
3.6%
2002 1
3.6%
ValueCountFrequency (%)
2020 1
3.6%
2019 1
3.6%
2018 1
3.6%
2017 1
3.6%
2016 1
3.6%
2015 1
3.6%
2014 1
3.6%
2013 1
3.6%
2012 1
3.6%
2011 1
3.6%

가스비중
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.15591166
Minimum0.060599762
Maximum0.19941405
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-12T12:32:13.873637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.060599762
5-th percentile0.066794134
Q10.14357305
median0.17520042
Q30.1826069
95-th percentile0.19224713
Maximum0.19941405
Range0.13881428
Interquartile range (IQR)0.039033845

Descriptive statistics

Standard deviation0.042088287
Coefficient of variation (CV)0.26994957
Kurtosis0.27850626
Mean0.15591166
Median Absolute Deviation (MAD)0.009930326
Skewness-1.2912128
Sum4.3655266
Variance0.0017714239
MonotonicityNot monotonic
2023-12-12T12:32:14.074853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.060599762 1
 
3.6%
0.186625924 1
 
3.6%
0.170231587 1
 
3.6%
0.179255254 1
 
3.6%
0.181377277 1
 
3.6%
0.177371112 1
 
3.6%
0.173120373 1
 
3.6%
0.169715723 1
 
3.6%
0.177696456 1
 
3.6%
0.182105646 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
0.060599762 1
3.6%
0.062191286 1
3.6%
0.075342279 1
3.6%
0.092689749 1
3.6%
0.097261943 1
3.6%
0.112341726 1
3.6%
0.120211391 1
3.6%
0.15136027 1
3.6%
0.161243331 1
3.6%
0.169696708 1
3.6%
ValueCountFrequency (%)
0.199414045 1
3.6%
0.194828499 1
3.6%
0.187453157 1
3.6%
0.186625924 1
3.6%
0.185148607 1
3.6%
0.185112876 1
3.6%
0.184110643 1
3.6%
0.182105646 1
3.6%
0.181377277 1
3.6%
0.179255254 1
3.6%

Interactions

2023-12-12T12:32:12.312113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:32:11.539558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:32:11.930958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:32:12.442921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:32:11.659703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:32:12.055315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:32:12.581789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:32:11.789447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:32:12.178038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:32:14.197738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번연도가스비중
순번1.0001.0000.644
연도1.0001.0000.617
가스비중0.6440.6171.000
2023-12-12T12:32:14.331863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번연도가스비중
순번1.0001.0000.579
연도1.0001.0000.579
가스비중0.5790.5791.000

Missing values

2023-12-12T12:32:12.772946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:32:12.909443image/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

순번연도가스비중
0119930.0606
1219940.062191
2319950.075342
3419960.09269
4519970.097262
5619980.112342
6719990.120211
7820000.15136
8920010.161243
91020020.169697
순번연도가스비중
181920110.17862
192020120.17697
202120130.182106
212220140.177696
222320150.169716
232420160.17312
242520170.177371
252620180.181377
262720190.179255
272820200.170232