Overview

Dataset statistics

Number of variables6
Number of observations27
Missing cells16
Missing cells (%)9.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory58.9 B

Variable types

Numeric6

Dataset

Description"95년부터 "21년도의 연도별 유형별 집단에너지 연료사용량 정보로, 지역냉난방, 산업단지, 병행사업자의 연료 등의 내용을 제공합니다. -연도,지역난방_연료사용량(TOE),산업단지_연료사용량(TOE),병행_연료사용량(TOE),국내_에너지_총사용량(천TOE),집단에너지_부문_에너지_사용비율(%)
Author산업통상자원부
URLhttps://www.data.go.kr/data/15054436/fileData.do

Alerts

연도 is highly overall correlated with 지역난방_연료사용량 and 4 other fieldsHigh correlation
지역난방_연료사용량 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
산업단지_연료사용량 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
병행_연료사용량 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
국내_에너지_총사용량 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
집단에너지_부문_에너지_사용비율 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
병행_연료사용량 has 16 (59.3%) missing valuesMissing
연도 has unique valuesUnique
지역난방_연료사용량 has unique valuesUnique
산업단지_연료사용량 has unique valuesUnique
국내_에너지_총사용량 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:08:31.031343
Analysis finished2023-12-12 07:08:34.927991
Duration3.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2008
Minimum1995
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T16:08:34.979774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1995
5-th percentile1996.3
Q12001.5
median2008
Q32014.5
95-th percentile2019.7
Maximum2021
Range26
Interquartile range (IQR)13

Descriptive statistics

Standard deviation7.9372539
Coefficient of variation (CV)0.0039528157
Kurtosis-1.2
Mean2008
Median Absolute Deviation (MAD)7
Skewness0
Sum54216
Variance63
MonotonicityStrictly increasing
2023-12-12T16:08:35.122505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1995 1
 
3.7%
1996 1
 
3.7%
2021 1
 
3.7%
2020 1
 
3.7%
2019 1
 
3.7%
2018 1
 
3.7%
2017 1
 
3.7%
2016 1
 
3.7%
2015 1
 
3.7%
2014 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1995 1
3.7%
1996 1
3.7%
1997 1
3.7%
1998 1
3.7%
1999 1
3.7%
2000 1
3.7%
2001 1
3.7%
2002 1
3.7%
2003 1
3.7%
2004 1
3.7%
ValueCountFrequency (%)
2021 1
3.7%
2020 1
3.7%
2019 1
3.7%
2018 1
3.7%
2017 1
3.7%
2016 1
3.7%
2015 1
3.7%
2014 1
3.7%
2013 1
3.7%
2012 1
3.7%

지역난방_연료사용량
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2957703.1
Minimum523696
Maximum6804005
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T16:08:35.276249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum523696
5-th percentile648431.4
Q11757894
median2236294
Q34177092.5
95-th percentile6179344.9
Maximum6804005
Range6280309
Interquartile range (IQR)2419198.5

Descriptive statistics

Standard deviation1843648.2
Coefficient of variation (CV)0.62333782
Kurtosis-0.68127962
Mean2957703.1
Median Absolute Deviation (MAD)1459137
Skewness0.58667897
Sum79857984
Variance3.3990387 × 1012
MonotonicityNot monotonic
2023-12-12T16:08:35.380230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2744016 1
 
3.7%
523696 1
 
3.7%
6186118 1
 
3.7%
5615777 1
 
3.7%
6163541 1
 
3.7%
6804005 1
 
3.7%
4651558 1
 
3.7%
4460661 1
 
3.7%
3962489 1
 
3.7%
3925475 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
523696 1
3.7%
641502 1
3.7%
664600 1
3.7%
777157 1
3.7%
1087464 1
3.7%
1539786 1
3.7%
1720088 1
3.7%
1795700 1
3.7%
1813994 1
3.7%
1816007 1
3.7%
ValueCountFrequency (%)
6804005 1
3.7%
6186118 1
3.7%
6163541 1
3.7%
5615777 1
3.7%
4651558 1
3.7%
4460661 1
3.7%
4268752 1
3.7%
4085433 1
3.7%
3962489 1
3.7%
3925475 1
3.7%

산업단지_연료사용량
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5596731.6
Minimum1841472
Maximum9144176
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T16:08:35.503368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1841472
5-th percentile2519101.8
Q14687659
median5192929
Q36492943.5
95-th percentile8515109.6
Maximum9144176
Range7302704
Interquartile range (IQR)1805284.5

Descriptive statistics

Standard deviation1903242.7
Coefficient of variation (CV)0.34006324
Kurtosis-0.36858624
Mean5596731.6
Median Absolute Deviation (MAD)1217646
Skewness0.13438762
Sum1.5111175 × 108
Variance3.6223327 × 1012
MonotonicityNot monotonic
2023-12-12T16:08:35.616760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1841472 1
 
3.7%
2232468 1
 
3.7%
9144176 1
 
3.7%
8269457 1
 
3.7%
8546303 1
 
3.7%
8442325 1
 
3.7%
8325386 1
 
3.7%
7691621 1
 
3.7%
6410575 1
 
3.7%
6206670 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1841472 1
3.7%
2232468 1
3.7%
3187914 1
3.7%
3600456 1
3.7%
3918818 1
3.7%
4515971 1
3.7%
4670027 1
3.7%
4705291 1
3.7%
4833116 1
3.7%
4844271 1
3.7%
ValueCountFrequency (%)
9144176 1
3.7%
8546303 1
3.7%
8442325 1
3.7%
8325386 1
3.7%
8269457 1
3.7%
7691621 1
3.7%
6559034 1
3.7%
6426853 1
3.7%
6410575 1
3.7%
6206670 1
3.7%

병행_연료사용량
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)100.0%
Missing16
Missing (%)59.3%
Infinite0
Infinite (%)0.0%
Mean846105.45
Minimum232572
Maximum1368913
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T16:08:35.714038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum232572
5-th percentile232589
Q1284143.5
median1261800
Q31347985.5
95-th percentile1363659
Maximum1368913
Range1136341
Interquartile range (IQR)1063842

Descriptive statistics

Standard deviation552500.36
Coefficient of variation (CV)0.65299231
Kurtosis-2.4115327
Mean846105.45
Median Absolute Deviation (MAD)107113
Skewness-0.20652053
Sum9307160
Variance3.0525664 × 1011
MonotonicityNot monotonic
2023-12-12T16:08:35.808622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
232606 1
 
3.7%
232572 1
 
3.7%
319814 1
 
3.7%
289613 1
 
3.7%
278674 1
 
3.7%
1261800 1
 
3.7%
1368913 1
 
3.7%
1340741 1
 
3.7%
1355230 1
 
3.7%
1268792 1
 
3.7%
(Missing) 16
59.3%
ValueCountFrequency (%)
232572 1
3.7%
232606 1
3.7%
278674 1
3.7%
289613 1
3.7%
319814 1
3.7%
1261800 1
3.7%
1268792 1
3.7%
1340741 1
3.7%
1355230 1
3.7%
1358405 1
3.7%
ValueCountFrequency (%)
1368913 1
3.7%
1358405 1
3.7%
1355230 1
3.7%
1340741 1
3.7%
1268792 1
3.7%
1261800 1
3.7%
319814 1
3.7%
289613 1
3.7%
278674 1
3.7%
232606 1
3.7%

국내_에너지_총사용량
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean241833.59
Minimum150437
Maximum306123
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T16:08:35.904992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum150437
5-th percentile165428
Q1203522.5
median240752
Q3284050.5
95-th percentile304815.2
Maximum306123
Range155686
Interquartile range (IQR)80528

Descriptive statistics

Standard deviation49221.54
Coefficient of variation (CV)0.20353475
Kurtosis-1.2135416
Mean241833.59
Median Absolute Deviation (MAD)42343
Skewness-0.28741741
Sum6529507
Variance2.42276 × 109
MonotonicityNot monotonic
2023-12-12T16:08:36.002698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
150437 1
 
3.7%
165212 1
 
3.7%
305252 1
 
3.7%
290835 1
 
3.7%
303796 1
 
3.7%
306123 1
 
3.7%
301088 1
 
3.7%
295678 1
 
3.7%
286181 1
 
3.7%
281920 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
150437 1
3.7%
165212 1
3.7%
165932 1
3.7%
180638 1
3.7%
181363 1
3.7%
192887 1
3.7%
198409 1
3.7%
208636 1
3.7%
215067 1
3.7%
220238 1
3.7%
ValueCountFrequency (%)
306123 1
3.7%
305252 1
3.7%
303796 1
3.7%
301088 1
3.7%
295678 1
3.7%
290835 1
3.7%
286181 1
3.7%
281920 1
3.7%
280165 1
3.7%
277646 1
3.7%

집단에너지_부문_에너지_사용비율
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5203704
Minimum1.67
Maximum5.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T16:08:36.105483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.67
5-th percentile2.248
Q12.825
median3.26
Q33.925
95-th percentile5.381
Maximum5.47
Range3.8
Interquartile range (IQR)1.1

Descriptive statistics

Standard deviation1.0301922
Coefficient of variation (CV)0.29263745
Kurtosis-0.39683005
Mean3.5203704
Median Absolute Deviation (MAD)0.48
Skewness0.60650377
Sum95.05
Variance1.061296
MonotonicityNot monotonic
2023-12-12T16:08:36.222983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2.98 2
 
7.4%
3.05 1
 
3.7%
2.77 1
 
3.7%
5.47 1
 
3.7%
5.21 1
 
3.7%
5.29 1
 
3.7%
5.42 1
 
3.7%
4.76 1
 
3.7%
4.82 1
 
3.7%
3.72 1
 
3.7%
Other values (16) 16
59.3%
ValueCountFrequency (%)
1.67 1
3.7%
2.11 1
3.7%
2.57 1
3.7%
2.59 1
3.7%
2.77 1
3.7%
2.78 1
3.7%
2.8 1
3.7%
2.85 1
3.7%
2.98 2
7.4%
3.05 1
3.7%
ValueCountFrequency (%)
5.47 1
3.7%
5.42 1
3.7%
5.29 1
3.7%
5.21 1
3.7%
4.82 1
3.7%
4.76 1
3.7%
3.98 1
3.7%
3.87 1
3.7%
3.72 1
3.7%
3.7 1
3.7%

Interactions

2023-12-12T16:08:34.289797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:31.239261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:31.922731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:32.557014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:33.177216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:33.754944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:34.367320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:31.336236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:32.036098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:32.655427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:33.269035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:33.855887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:34.446689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:31.455062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:32.149945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:32.765061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:33.373047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:33.952857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:34.530787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:31.564749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:32.244262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:32.880902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:33.484079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:34.041214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:34.608050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:31.678454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:32.338686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:32.989439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:33.576961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:34.123747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:34.691166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:31.796655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:32.452353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:33.087045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:33.661116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:08:34.203749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:08:36.555316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도지역난방_연료사용량산업단지_연료사용량병행_연료사용량국내_에너지_총사용량집단에너지_부문_에너지_사용비율
연도1.0000.8910.7941.0000.8840.822
지역난방_연료사용량0.8911.0000.8241.0000.9600.835
산업단지_연료사용량0.7940.8241.0001.0000.9040.962
병행_연료사용량1.0001.0001.0001.0000.9331.000
국내_에너지_총사용량0.8840.9600.9040.9331.0000.877
집단에너지_부문_에너지_사용비율0.8220.8350.9621.0000.8771.000
2023-12-12T16:08:36.644974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도지역난방_연료사용량산업단지_연료사용량병행_연료사용량국내_에너지_총사용량집단에너지_부문_에너지_사용비율
연도1.0000.9150.8930.8360.9910.811
지역난방_연료사용량0.9151.0000.8270.8180.9160.844
산업단지_연료사용량0.8930.8271.0000.8820.8940.940
병행_연료사용량0.8360.8180.8821.0000.8640.791
국내_에너지_총사용량0.9910.9160.8940.8641.0000.810
집단에너지_부문_에너지_사용비율0.8110.8440.9400.7910.8101.000

Missing values

2023-12-12T16:08:34.803940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:08:34.892217image/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

연도지역난방_연료사용량산업단지_연료사용량병행_연료사용량국내_에너지_총사용량집단에너지_부문_에너지_사용비율
0199527440161841472<NA>1504373.05
119965236962232468<NA>1652121.67
219976415023187914<NA>1806382.11
319986646003600456<NA>1659322.57
419997771573918818<NA>1813632.59
5200010874644844271<NA>1928873.07
6200115397865357959<NA>1984093.48
7200217200885192929<NA>2086363.31
8200318139945202116<NA>2150673.26
9200417957005040968<NA>2202383.1
연도지역난방_연료사용량산업단지_연료사용량병행_연료사용량국내_에너지_총사용량집단에너지_부문_에너지_사용비율
172012408543364268532325722776463.87
182013426875265590343198142801653.98
192014392547562066702896132819203.7
202015396248964105752786742861813.72
2120164460661769162112618002956784.82
2220174651558832538613689133010884.76
2320186804005844232513407413061235.42
2420196163541854630313552303037965.29
2520205615777826945712687922908355.21
2620216186118914417613584053052525.47