Overview

Dataset statistics

Number of variables14
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory132.0 B

Variable types

Numeric14

Dataset

Description에너지수급 현황은 연간통계로서 우리나라에서 수입, 생산하여 공급된 에너지(1차에너지)와 에너지 형태로의 전환과정을 거쳐 최종적으로 소비자 단계에서 소비되는 에너지(최종에너지) 현황을 보여줌 2021년 데이터 이후 에너지밸런스를 변경하면서 일부 에너지제품의 분류가 변경되었습니다. (1)석유의 경우 기존의 밸런스에서는 석유제품의 정제생산을 일차에너지공급에 포함시켰으나 개정밸런스에서는 이를 전환부분으로 옮기면서 과거에 세 개의 제품으로 분류(에너지유, 비에너지유,LPG로의 구분)하였던 석유를 하나의 제품으로 변경하였습니다. (2) 과거에는 일차에너지공급에 열이 포함되지 않았으나 개정밸런스에서는 화학반응 열로 생산된 열이 일차에너지공급에 포함되면서 새롭게 추가 되었습니다.
URLhttps://www.data.go.kr/data/15051140/fileData.do

Alerts

연도 is highly overall correlated with 일차에너지공급석탄_소계 and 9 other fieldsHigh correlation
일차에너지공급석탄_소계 is highly overall correlated with 연도 and 10 other fieldsHigh correlation
일차에너지공급석탄_유연탄및기타 is highly overall correlated with 연도 and 10 other fieldsHigh correlation
일차에너지공급천연가스 is highly overall correlated with 연도 and 9 other fieldsHigh correlation
일차에너지공급석유 is highly overall correlated with 연도 and 10 other fieldsHigh correlation
일차에너지공급신재생및기타 is highly overall correlated with 연도 and 9 other fieldsHigh correlation
일차에너지공급수력 is highly overall correlated with 일차에너지공급석탄_소계 and 3 other fieldsHigh correlation
일차에너지공급열 is highly overall correlated with 연도 and 9 other fieldsHigh correlation
최종소비_산업 is highly overall correlated with 연도 and 10 other fieldsHigh correlation
최종소비_수송 is highly overall correlated with 연도 and 9 other fieldsHigh correlation
최종소비_가정 is highly overall correlated with 연도 and 9 other fieldsHigh correlation
최종소비_상업-공공 is highly overall correlated with 연도 and 9 other fieldsHigh correlation
연도 has unique valuesUnique
일차에너지공급석탄_소계 has unique valuesUnique
일차에너지공급석탄_무연탄 has unique valuesUnique
일차에너지공급석탄_유연탄및기타 has unique valuesUnique
일차에너지공급천연가스 has unique valuesUnique
일차에너지공급석유 has unique valuesUnique
일차에너지공급신재생및기타 has unique valuesUnique
일차에너지공급원자력 has unique valuesUnique
일차에너지공급수력 has unique valuesUnique
최종소비_산업 has unique valuesUnique
최종소비_수송 has unique valuesUnique
최종소비_가정 has unique valuesUnique
최종소비_상업-공공 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:11:42.574517
Analysis finished2023-12-12 18:12:04.114068
Duration21.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2010.5
Minimum2000
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T03:12:04.194673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile2001.05
Q12005.25
median2010.5
Q32015.75
95-th percentile2019.95
Maximum2021
Range21
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation6.4935866
Coefficient of variation (CV)0.0032298366
Kurtosis-1.2
Mean2010.5
Median Absolute Deviation (MAD)5.5
Skewness0
Sum44231
Variance42.166667
MonotonicityStrictly increasing
2023-12-13T03:12:04.318102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2000 1
 
4.5%
2012 1
 
4.5%
2021 1
 
4.5%
2020 1
 
4.5%
2019 1
 
4.5%
2018 1
 
4.5%
2017 1
 
4.5%
2016 1
 
4.5%
2015 1
 
4.5%
2014 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
2000 1
4.5%
2001 1
4.5%
2002 1
4.5%
2003 1
4.5%
2004 1
4.5%
2005 1
4.5%
2006 1
4.5%
2007 1
4.5%
2008 1
4.5%
2009 1
4.5%
ValueCountFrequency (%)
2021 1
4.5%
2020 1
4.5%
2019 1
4.5%
2018 1
4.5%
2017 1
4.5%
2016 1
4.5%
2015 1
4.5%
2014 1
4.5%
2013 1
4.5%
2012 1
4.5%

일차에너지공급석탄_소계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69210.773
Minimum43143
Maximum90965
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T03:12:04.501255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum43143
5-th percentile45945.45
Q153321.5
median75995.5
Q382669.5
95-th percentile89549.1
Maximum90965
Range47822
Interquartile range (IQR)29348

Descriptive statistics

Standard deviation15913.273
Coefficient of variation (CV)0.2299248
Kurtosis-1.5000995
Mean69210.773
Median Absolute Deviation (MAD)10061.5
Skewness-0.32285035
Sum1522637
Variance2.5323225 × 108
MonotonicityNot monotonic
2023-12-13T03:12:04.619770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
43143 1
 
4.5%
79059 1
 
4.5%
76968 1
 
4.5%
75983 1
 
4.5%
85048 1
 
4.5%
90965 1
 
4.5%
89786 1
 
4.5%
83989 1
 
4.5%
83650 1
 
4.5%
82764 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
43143 1
4.5%
45838 1
4.5%
47987 1
4.5%
49135 1
4.5%
51886 1
4.5%
52975 1
4.5%
54361 1
4.5%
58149 1
4.5%
64925 1
4.5%
67094 1
4.5%
ValueCountFrequency (%)
90965 1
4.5%
89786 1
4.5%
85048 1
4.5%
83989 1
4.5%
83650 1
4.5%
82764 1
4.5%
82386 1
4.5%
80538 1
4.5%
79059 1
4.5%
76968 1
4.5%

일차에너지공급석탄_무연탄
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4770.3182
Minimum3074
Maximum6796
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T03:12:04.772794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3074
5-th percentile3608.4
Q14058
median4787.5
Q35308.25
95-th percentile5991.7
Maximum6796
Range3722
Interquartile range (IQR)1250.25

Descriptive statistics

Standard deviation918.31649
Coefficient of variation (CV)0.19250634
Kurtosis-0.29222065
Mean4770.3182
Median Absolute Deviation (MAD)712.5
Skewness0.18330209
Sum104947
Variance843305.18
MonotonicityNot monotonic
2023-12-13T03:12:04.908801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
3074 1
 
4.5%
5021 1
 
4.5%
3683 1
 
4.5%
3605 1
 
4.5%
3956 1
 
4.5%
4644 1
 
4.5%
4109 1
 
4.5%
5348 1
 
4.5%
5189 1
 
4.5%
4867 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
3074 1
4.5%
3605 1
4.5%
3673 1
4.5%
3683 1
4.5%
3956 1
4.5%
4041 1
4.5%
4109 1
4.5%
4287 1
4.5%
4529 1
4.5%
4644 1
4.5%
ValueCountFrequency (%)
6796 1
4.5%
5998 1
4.5%
5872 1
4.5%
5673 1
4.5%
5560 1
4.5%
5348 1
4.5%
5189 1
4.5%
5174 1
4.5%
5140 1
4.5%
5021 1
4.5%

일차에너지공급석탄_유연탄및기타
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64440.318
Minimum40069
Maximum86321
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T03:12:05.075447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40069
5-th percentile42254.05
Q148497
median71193.5
Q377320.5
95-th percentile85447.75
Maximum86321
Range46252
Interquartile range (IQR)28823.5

Descriptive statistics

Standard deviation15667.909
Coefficient of variation (CV)0.2431383
Kurtosis-1.5614704
Mean64440.318
Median Absolute Deviation (MAD)11020
Skewness-0.25421273
Sum1417687
Variance2.4548339 × 108
MonotonicityNot monotonic
2023-12-13T03:12:05.241861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
40069 1
 
4.5%
74038 1
 
4.5%
73285 1
 
4.5%
72377 1
 
4.5%
81092 1
 
4.5%
86321 1
 
4.5%
85677 1
 
4.5%
78640 1
 
4.5%
78462 1
 
4.5%
77897 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
40069 1
4.5%
42165 1
4.5%
43946 1
4.5%
44606 1
4.5%
47599 1
4.5%
48267 1
4.5%
49187 1
4.5%
52589 1
4.5%
59052 1
4.5%
61420 1
4.5%
ValueCountFrequency (%)
86321 1
4.5%
85677 1
4.5%
81092 1
4.5%
78640 1
4.5%
78462 1
4.5%
77897 1
4.5%
75591 1
4.5%
75397 1
4.5%
74038 1
4.5%
73285 1
4.5%

일차에너지공급천연가스
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39992.364
Minimum19722
Maximum59622
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T03:12:05.390556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19722
5-th percentile19945.7
Q130781.25
median42819.5
Q349306.5
95-th percentile55032.85
Maximum59622
Range39900
Interquartile range (IQR)18525.25

Descriptive statistics

Standard deviation12327.2
Coefficient of variation (CV)0.30823885
Kurtosis-1.2273616
Mean39992.364
Median Absolute Deviation (MAD)9959.5
Skewness-0.21868177
Sum879832
Variance1.5195986 × 108
MonotonicityNot monotonic
2023-12-13T03:12:05.552239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
19743 1
 
4.5%
49554 1
 
4.5%
59622 1
 
4.5%
53947 1
 
4.5%
53875 1
 
4.5%
55090 1
 
4.5%
48564 1
 
4.5%
45524 1
 
4.5%
43958 1
 
4.5%
47409 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
19722 1
4.5%
19743 1
4.5%
23797 1
4.5%
24272 1
4.5%
27827 1
4.5%
30367 1
4.5%
32024 1
4.5%
33792 1
4.5%
34665 1
4.5%
35138 1
4.5%
ValueCountFrequency (%)
59622 1
4.5%
55090 1
4.5%
53947 1
4.5%
53875 1
4.5%
51943 1
4.5%
49554 1
4.5%
48564 1
4.5%
47409 1
4.5%
47318 1
4.5%
45524 1
4.5%

일차에너지공급석유
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101304.14
Minimum88431
Maximum116067
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T03:12:05.706622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum88431
5-th percentile89594.3
Q192604
median100707
Q3107574
95-th percentile115404.75
Maximum116067
Range27636
Interquartile range (IQR)14970

Descriptive statistics

Standard deviation9507.7262
Coefficient of variation (CV)0.093853287
Kurtosis-1.1601282
Mean101304.14
Median Absolute Deviation (MAD)8014
Skewness0.30177147
Sum2228691
Variance90396858
MonotonicityNot monotonic
2023-12-13T03:12:06.163763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
90804 1
 
4.5%
102833 1
 
4.5%
115204 1
 
4.5%
107970 1
 
4.5%
115408 1
 
4.5%
114450 1
 
4.5%
116067 1
 
4.5%
115343 1
 
4.5%
106386 1
 
4.5%
100792 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
88431 1
4.5%
89590 1
4.5%
89676 1
4.5%
90213 1
4.5%
90804 1
4.5%
92515 1
4.5%
92871 1
4.5%
96511 1
4.5%
100177 1
4.5%
100303 1
4.5%
ValueCountFrequency (%)
116067 1
4.5%
115408 1
4.5%
115343 1
4.5%
115204 1
4.5%
114450 1
4.5%
107970 1
4.5%
106386 1
4.5%
102833 1
4.5%
101306 1
4.5%
101219 1
4.5%

일차에너지공급신재생및기타
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5521
Minimum1135
Maximum14373
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T03:12:06.300935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1135
5-th percentile1414.45
Q12091.75
median4128
Q38059.5
95-th percentile12570.8
Maximum14373
Range13238
Interquartile range (IQR)5967.75

Descriptive statistics

Standard deviation4101.3958
Coefficient of variation (CV)0.74287192
Kurtosis-0.55891969
Mean5521
Median Absolute Deviation (MAD)2420
Skewness0.83629472
Sum121462
Variance16821448
MonotonicityNot monotonic
2023-12-13T03:12:06.461273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1135 1
 
4.5%
4867 1
 
4.5%
14373 1
 
4.5%
12625 1
 
4.5%
11541 1
 
4.5%
11009 1
 
4.5%
9959 1
 
4.5%
8261 1
 
4.5%
7455 1
 
4.5%
6636 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
1135 1
4.5%
1407 1
4.5%
1556 1
4.5%
1796 1
4.5%
1946 1
4.5%
2051 1
4.5%
2214 1
4.5%
2569 1
4.5%
2917 1
4.5%
3447 1
4.5%
ValueCountFrequency (%)
14373 1
4.5%
12625 1
4.5%
11541 1
4.5%
11009 1
4.5%
9959 1
4.5%
8261 1
4.5%
7455 1
4.5%
6636 1
4.5%
5442 1
4.5%
4867 1
4.5%

일차에너지공급원자력
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32093.5
Minimum27241
Maximum37187
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T03:12:06.601326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27241
5-th percentile28053.2
Q130818
median32183
Q333559
95-th percentile36598.5
Maximum37187
Range9946
Interquartile range (IQR)2741

Descriptive statistics

Standard deviation2563.3937
Coefficient of variation (CV)0.079872674
Kurtosis-0.077899177
Mean32093.5
Median Absolute Deviation (MAD)1463
Skewness0.012425338
Sum706057
Variance6570987
MonotonicityNot monotonic
2023-12-13T03:12:06.752502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
27241 1
 
4.5%
31719 1
 
4.5%
33657 1
 
4.5%
34119 1
 
4.5%
31079 1
 
4.5%
28437 1
 
4.5%
31615 1
 
4.5%
34181 1
 
4.5%
34765 1
 
4.5%
33002 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
27241 1
4.5%
28033 1
4.5%
28437 1
4.5%
29283 1
4.5%
29776 1
4.5%
30731 1
4.5%
31079 1
4.5%
31615 1
4.5%
31719 1
4.5%
31771 1
4.5%
ValueCountFrequency (%)
37187 1
4.5%
36695 1
4.5%
34765 1
4.5%
34181 1
4.5%
34119 1
4.5%
33657 1
4.5%
33265 1
4.5%
33002 1
4.5%
32679 1
4.5%
32456 1
4.5%

일차에너지공급수력
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean777.36364
Minimum454
Maximum1226
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T03:12:06.901439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum454
5-th percentile581.05
Q1606.25
median789
Q3896.25
95-th percentile1078
Maximum1226
Range772
Interquartile range (IQR)290

Descriptive statistics

Standard deviation192.34853
Coefficient of variation (CV)0.247437
Kurtosis-0.12453848
Mean777.36364
Median Absolute Deviation (MAD)155.5
Skewness0.52717861
Sum17102
Variance36997.957
MonotonicityNot monotonic
2023-12-13T03:12:07.053690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1002 1
 
4.5%
838 1
 
4.5%
651 1
 
4.5%
826 1
 
4.5%
594 1
 
4.5%
719 1
 
4.5%
601 1
 
4.5%
603 1
 
4.5%
454 1
 
4.5%
581 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
454 1
4.5%
581 1
4.5%
582 1
4.5%
594 1
4.5%
601 1
4.5%
603 1
4.5%
616 1
4.5%
651 1
4.5%
660 1
4.5%
719 1
4.5%
ValueCountFrequency (%)
1226 1
4.5%
1082 1
4.5%
1002 1
4.5%
989 1
4.5%
919 1
4.5%
906 1
4.5%
867 1
4.5%
838 1
4.5%
826 1
4.5%
808 1
4.5%

일차에너지공급열
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.363636
Minimum10
Maximum135
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T03:12:07.216344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile12.05
Q116.25
median57.5
Q3103
95-th percentile126.9
Maximum135
Range125
Interquartile range (IQR)86.75

Descriptive statistics

Standard deviation45.668104
Coefficient of variation (CV)0.76929425
Kurtosis-1.3659164
Mean59.363636
Median Absolute Deviation (MAD)42.5
Skewness0.4605215
Sum1306
Variance2085.5758
MonotonicityNot monotonic
2023-12-13T03:12:07.360909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
68 3
 
13.6%
14 2
 
9.1%
10 1
 
4.5%
124 1
 
4.5%
73 1
 
4.5%
66 1
 
4.5%
127 1
 
4.5%
117 1
 
4.5%
125 1
 
4.5%
113 1
 
4.5%
Other values (9) 9
40.9%
ValueCountFrequency (%)
10 1
4.5%
12 1
4.5%
13 1
4.5%
14 2
9.1%
16 1
4.5%
17 1
4.5%
19 1
4.5%
20 1
4.5%
38 1
4.5%
49 1
4.5%
ValueCountFrequency (%)
135 1
 
4.5%
127 1
 
4.5%
125 1
 
4.5%
124 1
 
4.5%
117 1
 
4.5%
113 1
 
4.5%
73 1
 
4.5%
68 3
13.6%
66 1
 
4.5%
49 1
 
4.5%

최종소비_산업
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108643.14
Minimum80963
Maximum133776
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T03:12:07.534294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum80963
5-th percentile81847.7
Q190087.75
median114447.5
Q3123795.75
95-th percentile130923.85
Maximum133776
Range52813
Interquartile range (IQR)33708

Descriptive statistics

Standard deviation18750.801
Coefficient of variation (CV)0.17259076
Kurtosis-1.7002798
Mean108643.14
Median Absolute Deviation (MAD)16329.5
Skewness-0.16643204
Sum2390149
Variance3.5159255 × 108
MonotonicityNot monotonic
2023-12-13T03:12:07.697714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
80963 1
 
4.5%
118914 1
 
4.5%
133776 1
 
4.5%
124003 1
 
4.5%
129223 1
 
4.5%
130769 1
 
4.5%
130932 1
 
4.5%
127696 1
 
4.5%
123174 1
 
4.5%
122898 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
80963 1
4.5%
81673 1
4.5%
85167 1
4.5%
86646 1
4.5%
88125 1
4.5%
89370 1
4.5%
92241 1
4.5%
96978 1
4.5%
98110 1
4.5%
98532 1
4.5%
ValueCountFrequency (%)
133776 1
4.5%
130932 1
4.5%
130769 1
4.5%
129223 1
4.5%
127696 1
4.5%
124003 1
4.5%
123174 1
4.5%
122898 1
4.5%
121318 1
4.5%
119660 1
4.5%

최종소비_수송
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31751.227
Minimum25007
Maximum37194
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T03:12:07.853066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25007
5-th percentile26315.1
Q129799.25
median31013
Q334687
95-th percentile36617.25
Maximum37194
Range12187
Interquartile range (IQR)4887.75

Descriptive statistics

Standard deviation3421.4757
Coefficient of variation (CV)0.10775885
Kurtosis-0.67458562
Mean31751.227
Median Absolute Deviation (MAD)1923
Skewness0.00067455692
Sum698527
Variance11706496
MonotonicityNot monotonic
2023-12-13T03:12:07.996659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
25007 1
 
4.5%
31502 1
 
4.5%
36636 1
 
4.5%
34746 1
 
4.5%
37194 1
 
4.5%
36227 1
 
4.5%
36261 1
 
4.5%
36030 1
 
4.5%
34510 1
 
4.5%
32407 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
25007 1
4.5%
26226 1
4.5%
28008 1
4.5%
29002 1
4.5%
29178 1
4.5%
29730 1
4.5%
30007 1
4.5%
30389 1
4.5%
30496 1
4.5%
30928 1
4.5%
ValueCountFrequency (%)
37194 1
4.5%
36636 1
4.5%
36261 1
4.5%
36227 1
4.5%
36030 1
4.5%
34746 1
4.5%
34510 1
4.5%
32407 1
4.5%
32017 1
4.5%
31502 1
4.5%

최종소비_가정
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19709.182
Minimum16284
Maximum22940
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T03:12:08.154553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16284
5-th percentile17058.55
Q118880.25
median19683.5
Q320673.75
95-th percentile22343.9
Maximum22940
Range6656
Interquartile range (IQR)1793.5

Descriptive statistics

Standard deviation1707.2959
Coefficient of variation (CV)0.086624391
Kurtosis-0.28553367
Mean19709.182
Median Absolute Deviation (MAD)931
Skewness-0.036271122
Sum433602
Variance2914859.2
MonotonicityNot monotonic
2023-12-13T03:12:08.332424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
16284 1
 
4.5%
20407 1
 
4.5%
22940 1
 
4.5%
22356 1
 
4.5%
21466 1
 
4.5%
22114 1
 
4.5%
20918 1
 
4.5%
20140 1
 
4.5%
18971 1
 
4.5%
18905 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
16284 1
4.5%
17020 1
4.5%
17791 1
4.5%
17877 1
4.5%
18064 1
4.5%
18872 1
4.5%
18905 1
4.5%
18971 1
4.5%
19347 1
4.5%
19349 1
4.5%
ValueCountFrequency (%)
22940 1
4.5%
22356 1
4.5%
22114 1
4.5%
21466 1
4.5%
20918 1
4.5%
20733 1
4.5%
20496 1
4.5%
20407 1
4.5%
20185 1
4.5%
20140 1
4.5%

최종소비_상업-공공
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21691.818
Minimum18671
Maximum24890
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T03:12:08.505577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18671
5-th percentile18739.6
Q120346
median21725.5
Q322925.25
95-th percentile24308.85
Maximum24890
Range6219
Interquartile range (IQR)2579.25

Descriptive statistics

Standard deviation1822.5048
Coefficient of variation (CV)0.084018076
Kurtosis-1.000335
Mean21691.818
Median Absolute Deviation (MAD)1345.5
Skewness-0.078702779
Sum477220
Variance3321523.9
MonotonicityNot monotonic
2023-12-13T03:12:08.662998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
18704 1
 
4.5%
22948 1
 
4.5%
23189 1
 
4.5%
22668 1
 
4.5%
23850 1
 
4.5%
24890 1
 
4.5%
24333 1
 
4.5%
23686 1
 
4.5%
22692 1
 
4.5%
21679 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
18671 1
4.5%
18704 1
4.5%
19416 1
4.5%
19625 1
4.5%
19745 1
4.5%
20312 1
4.5%
20448 1
4.5%
20879 1
4.5%
21005 1
4.5%
21297 1
4.5%
ValueCountFrequency (%)
24890 1
4.5%
24333 1
4.5%
23850 1
4.5%
23686 1
4.5%
23189 1
4.5%
22948 1
4.5%
22857 1
4.5%
22692 1
4.5%
22668 1
4.5%
22554 1
4.5%

Interactions

2023-12-13T03:12:02.272134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:43.071603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:44.662207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:46.214276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:48.014525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:49.234881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:50.790827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:52.183167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:53.753750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:54.992111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:56.251901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:57.552695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:58.829321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:00.587869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:02.366505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:43.173316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:44.765742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:46.313593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:48.094690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:49.366202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:50.906493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:52.274477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:53.828360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:55.072513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:56.328510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:57.645333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:58.935439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:00.701131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:02.455553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:43.281591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:44.877242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:46.412570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:48.167085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:49.467844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:50.995025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:52.372242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:53.903079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:55.162480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:56.406838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:57.731057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:59.325349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:00.811959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:02.558096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:43.397117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:45.003784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:46.544489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:48.245718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:49.592834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:51.091985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:52.484666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:53.994724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:55.252080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:56.496648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:57.815627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:59.456348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:00.935268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:02.667106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:43.496885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:45.112537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:46.656222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:48.315807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:49.689778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:51.206726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:52.592268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:54.065353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:55.332762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:56.574535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:57.907287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:59.540542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:01.060650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:02.768863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:43.617188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:45.230401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:47.134276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:48.428958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:49.797088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:51.322031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:52.702263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:54.148360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:55.421297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:56.664973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:58.007849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:59.646773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:01.181234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:02.861247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:43.699028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:45.345446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:47.236536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:48.511181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:49.890603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:51.415653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:52.793230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:54.226736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:55.507894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:56.742221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:58.088130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:59.746774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:01.314446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:02.952614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:43.828393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:45.441240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:47.341439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:48.610642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:50.010082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:51.502049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:52.879400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:54.326753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:55.595235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:56.832276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:58.173108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:59.840766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:01.445784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:03.049546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:43.937135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:45.561576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:47.421047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:48.689284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:50.102381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:51.594238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:52.964244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:54.418015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:55.694175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:56.923982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:58.252316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:59.955436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:01.578510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:03.164175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:44.040165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:45.666573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:47.527166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:48.777569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:50.212284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:51.709140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:53.056118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:54.543448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:55.789273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:57.026229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:58.348266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:00.078441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:01.717434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:03.254507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:44.155407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:45.757891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:47.621319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:48.865234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:50.338444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:51.797769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:53.420510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:54.622867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:55.886307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:57.127232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:58.445509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:00.190669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:01.833780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:03.344375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:44.264501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:45.864486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:47.718764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:48.950828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:50.450815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:51.877367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:53.501606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:54.697206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:55.987528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:57.242507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:58.528832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:00.287712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:01.948243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:03.433900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:44.379190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:45.971268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:47.809172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:49.036840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:50.558133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:51.954810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:53.588424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:54.792169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:56.075065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:57.345594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:58.613962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:00.379626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:02.071247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:03.551368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:44.515786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:46.091628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:47.915562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:49.134938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:50.674192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:52.054600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:53.677825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:54.892234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:56.163457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:57.451739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:11:58.722168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:00.485228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:02.165746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:12:08.805089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도일차에너지공급석탄_소계일차에너지공급석탄_무연탄일차에너지공급석탄_유연탄및기타일차에너지공급천연가스일차에너지공급석유일차에너지공급신재생및기타일차에너지공급원자력일차에너지공급수력일차에너지공급열최종소비_산업최종소비_수송최종소비_가정최종소비_상업-공공
연도1.0000.9200.6400.8410.6320.6030.8940.7650.0000.6150.8750.7290.7310.906
일차에너지공급석탄_소계0.9201.0000.4460.9640.6330.6490.0000.7140.2740.7640.7380.6120.7590.829
일차에너지공급석탄_무연탄0.6400.4461.0000.0000.2340.0000.4410.0000.7140.2110.7990.7220.5490.663
일차에너지공급석탄_유연탄및기타0.8410.9640.0001.0000.8910.8030.7620.4340.7540.5990.9090.6570.6560.876
일차에너지공급천연가스0.6320.6330.2340.8911.0000.4860.7960.0000.6980.0000.9110.5930.6330.824
일차에너지공급석유0.6030.6490.0000.8030.4861.0000.7270.2010.0000.7780.7560.8960.2520.400
일차에너지공급신재생및기타0.8940.0000.4410.7620.7960.7271.0000.0000.0000.8610.7620.6600.6430.803
일차에너지공급원자력0.7650.7140.0000.4340.0000.2010.0001.0000.3630.0000.3220.6110.9290.715
일차에너지공급수력0.0000.2740.7140.7540.6980.0000.0000.3631.0000.0000.0000.0000.6040.843
일차에너지공급열0.6150.7640.2110.5990.0000.7780.8610.0000.0001.0000.5980.1800.5930.374
최종소비_산업0.8750.7380.7990.9090.9110.7560.7620.3220.0000.5981.0000.9100.3240.836
최종소비_수송0.7290.6120.7220.6570.5930.8960.6600.6110.0000.1800.9101.0000.5800.615
최종소비_가정0.7310.7590.5490.6560.6330.2520.6430.9290.6040.5930.3240.5801.0000.832
최종소비_상업-공공0.9060.8290.6630.8760.8240.4000.8030.7150.8430.3740.8360.6150.8321.000
2023-12-13T03:12:09.023592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도일차에너지공급석탄_소계일차에너지공급석탄_무연탄일차에너지공급석탄_유연탄및기타일차에너지공급천연가스일차에너지공급석유일차에너지공급신재생및기타일차에너지공급원자력일차에너지공급수력일차에너지공급열최종소비_산업최종소비_수송최종소비_가정최종소비_상업-공공
연도1.0000.8700.0080.8810.9540.8940.9990.249-0.4760.7500.9830.9750.8540.904
일차에너지공급석탄_소계0.8701.0000.2580.9990.8350.8450.8690.132-0.5090.8100.9180.9100.7100.920
일차에너지공급석탄_무연탄0.0080.2581.0000.2370.025-0.0380.0050.305-0.0310.2410.0580.0240.0570.147
일차에너지공급석탄_유연탄및기타0.8810.9990.2371.0000.8450.8540.8800.139-0.5060.8210.9240.9160.7140.918
일차에너지공급천연가스0.9540.8350.0250.8451.0000.8420.9530.119-0.3080.7350.9310.9250.8810.875
일차에너지공급석유0.8940.845-0.0380.8540.8421.0000.896-0.047-0.5230.7430.9060.8960.6780.903
일차에너지공급신재생및기타0.9990.8690.0050.8800.9530.8961.0000.241-0.4730.7570.9820.9740.8460.906
일차에너지공급원자력0.2490.1320.3050.1390.119-0.0470.2411.0000.0130.2620.2200.2330.2380.090
일차에너지공급수력-0.476-0.509-0.031-0.506-0.308-0.523-0.4730.0131.000-0.274-0.504-0.491-0.153-0.409
일차에너지공급열0.7500.8100.2410.8210.7350.7430.7570.262-0.2741.0000.7750.7380.5810.757
최종소비_산업0.9830.9180.0580.9240.9310.9060.9820.220-0.5040.7751.0000.9820.8370.931
최종소비_수송0.9750.9100.0240.9160.9250.8960.9740.233-0.4910.7380.9821.0000.8340.918
최종소비_가정0.8540.7100.0570.7140.8810.6780.8460.238-0.1530.5810.8370.8341.0000.823
최종소비_상업-공공0.9040.9200.1470.9180.8750.9030.9060.090-0.4090.7570.9310.9180.8231.000

Missing values

2023-12-13T03:12:03.727349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:12:04.000024image/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

연도일차에너지공급석탄_소계일차에너지공급석탄_무연탄일차에너지공급석탄_유연탄및기타일차에너지공급천연가스일차에너지공급석유일차에너지공급신재생및기타일차에너지공급원자력일차에너지공급수력일차에너지공급열최종소비_산업최종소비_수송최종소비_가정최종소비_상업-공공
0200043143307440069197439080411352724110021080963250071628418704
120014583836734216519722902131407280335821381673262261702018671
220024798740414394623797925151556297768081485167280081779119416
3200349135452944606242729287117963241812262086646290021787720448
4200451886428747599278278967620513267910821988125291781806420312
520055297547084826730367884311946366959191289370297301975419625
620065436151744918732024895902214371878671792241309281961319745
7200758149556052589346651012192569307317811496978304961887220879
820086492558725905233792965112917324566603898110300071934721005
9200967094567361420351381003033447317716164998532303891934921297
연도일차에너지공급석탄_소계일차에너지공급석탄_무연탄일차에너지공급석탄_유연탄및기타일차에너지공급천연가스일차에너지공급석유일차에너지공급신재생및기타일차에너지공급원자력일차에너지공급수력일차에너지공급열최종소비_산업최종소비_수송최종소비_가정최종소비_상업-공공
1220127905950217403849554102833486731719838124118914315022040722948
1320138053851407539751943101306544229283906113121318320172018521772
142014827644867778974740910079266363300258168122898324071890521679
1520158365051897846243958106386745534765454125123174345101897122692
1620168398953487864045524115343826134181603117127696360302014023686
1720178978641098567748564116067995931615601127130932362612091824333
1820189096546448632155090114450110092843771968130769362272211424890
1920198504839568109253875115408115413107959466129223371942146623850
2020207598336057237753947107970126253411982673124003347462235622668
2120217696836837328559622115204143733365765168133776366362294023189