Overview

Dataset statistics

Number of variables16
Number of observations26
Missing cells4
Missing cells (%)1.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory149.1 B

Variable types

Numeric16

Dataset

Description국내 석유제품의 제품별 소비량(휘발유, 등유, 경유, 경질중유, 벙커C, 납사, 용제, 항공유, LPG, 아스팔트, 윤활유, 부생연료유, 기타제품) 단위 : 물량(천Bbl)
URLhttps://www.data.go.kr/data/15054604/fileData.do

Alerts

is highly overall correlated with 휘발유 and 12 other fieldsHigh correlation
휘발유 is highly overall correlated with and 11 other fieldsHigh correlation
등유 is highly overall correlated with and 11 other fieldsHigh correlation
경유 is highly overall correlated with and 9 other fieldsHigh correlation
경질중유 is highly overall correlated with and 11 other fieldsHigh correlation
중유 is highly overall correlated with and 10 other fieldsHigh correlation
벙커C유 is highly overall correlated with and 11 other fieldsHigh correlation
납사 is highly overall correlated with and 12 other fieldsHigh correlation
용제 is highly overall correlated with 윤활유 and 1 other fieldsHigh correlation
항공유 is highly overall correlated with and 10 other fieldsHigh correlation
LPG is highly overall correlated with and 12 other fieldsHigh correlation
윤활유 is highly overall correlated with and 3 other fieldsHigh correlation
기타제품 is highly overall correlated with and 11 other fieldsHigh correlation
부생연료유 is highly overall correlated with and 10 other fieldsHigh correlation
합계 is highly overall correlated with and 11 other fieldsHigh correlation
부생연료유 has 4 (15.4%) missing valuesMissing
has unique valuesUnique
휘발유 has unique valuesUnique
등유 has unique valuesUnique
경유 has unique valuesUnique
경질중유 has unique valuesUnique
중유 has unique valuesUnique
벙커C유 has unique valuesUnique
납사 has unique valuesUnique
용제 has unique valuesUnique
항공유 has unique valuesUnique
LPG has unique valuesUnique
아스팔트 has unique valuesUnique
윤활유 has unique valuesUnique
기타제품 has unique valuesUnique
합계 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:21:06.576287
Analysis finished2023-12-12 05:21:33.352867
Duration26.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables


Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2009.5
Minimum1997
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T14:21:33.418210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1997
5-th percentile1998.25
Q12003.25
median2009.5
Q32015.75
95-th percentile2020.75
Maximum2022
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.0038061853
Kurtosis-1.2
Mean2009.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum52247
Variance58.5
MonotonicityStrictly increasing
2023-12-12T14:21:33.892765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1997 1
 
3.8%
2011 1
 
3.8%
2022 1
 
3.8%
2021 1
 
3.8%
2020 1
 
3.8%
2019 1
 
3.8%
2018 1
 
3.8%
2017 1
 
3.8%
2016 1
 
3.8%
2015 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1997 1
3.8%
1998 1
3.8%
1999 1
3.8%
2000 1
3.8%
2001 1
3.8%
2002 1
3.8%
2003 1
3.8%
2004 1
3.8%
2005 1
3.8%
2006 1
3.8%
ValueCountFrequency (%)
2022 1
3.8%
2021 1
3.8%
2020 1
3.8%
2019 1
3.8%
2018 1
3.8%
2017 1
3.8%
2016 1
3.8%
2015 1
3.8%
2014 1
3.8%
2013 1
3.8%

휘발유
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70145.5
Minimum58151
Maximum88368
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T14:21:34.021601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum58151
5-th percentile59639.25
Q162551.75
median69252.5
Q378337
95-th percentile84343
Maximum88368
Range30217
Interquartile range (IQR)15785.25

Descriptive statistics

Standard deviation8963.8067
Coefficient of variation (CV)0.12778876
Kurtosis-1.06176
Mean70145.5
Median Absolute Deviation (MAD)7094
Skewness0.44292241
Sum1823783
Variance80349830
MonotonicityNot monotonic
2023-12-12T14:21:34.171515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
71358 1
 
3.8%
69574 1
 
3.8%
88368 1
 
3.8%
84874 1
 
3.8%
80965 1
 
3.8%
82750 1
 
3.8%
79683 1
 
3.8%
79616 1
 
3.8%
78926 1
 
3.8%
76570 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
58151 1
3.8%
59561 1
3.8%
59874 1
3.8%
60484 1
3.8%
61089 1
3.8%
62382 1
3.8%
62500 1
3.8%
62707 1
3.8%
62937 1
3.8%
63879 1
3.8%
ValueCountFrequency (%)
88368 1
3.8%
84874 1
3.8%
82750 1
3.8%
80965 1
3.8%
79683 1
3.8%
79616 1
3.8%
78926 1
3.8%
76570 1
3.8%
73473 1
3.8%
73416 1
3.8%

등유
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35047.538
Minimum15429
Maximum85025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T14:21:34.338142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15429
5-th percentile16062.75
Q118830.75
median26081.5
Q350428
95-th percentile75173.25
Maximum85025
Range69596
Interquartile range (IQR)31597.25

Descriptive statistics

Standard deviation21418.077
Coefficient of variation (CV)0.61111502
Kurtosis-0.19630319
Mean35047.538
Median Absolute Deviation (MAD)9193
Skewness1.0425191
Sum911236
Variance4.5873403 × 108
MonotonicityNot monotonic
2023-12-12T14:21:34.517303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
85025 1
 
3.8%
25430 1
 
3.8%
16008 1
 
3.8%
16813 1
 
3.8%
16964 1
 
3.8%
17127 1
 
3.8%
18875 1
 
3.8%
19006 1
 
3.8%
19060 1
 
3.8%
16227 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
15429 1
3.8%
16008 1
3.8%
16227 1
3.8%
16813 1
3.8%
16964 1
3.8%
17127 1
3.8%
18816 1
3.8%
18875 1
3.8%
19006 1
3.8%
19060 1
3.8%
ValueCountFrequency (%)
85025 1
3.8%
76928 1
3.8%
69909 1
3.8%
61707 1
3.8%
61457 1
3.8%
58464 1
3.8%
52874 1
3.8%
43090 1
3.8%
39392 1
3.8%
31450 1
3.8%

경유
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean146795.19
Minimum120372
Maximum171795
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T14:21:34.653363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum120372
5-th percentile126911.25
Q1134546.5
median143409.5
Q3163712
95-th percentile168406.25
Maximum171795
Range51423
Interquartile range (IQR)29165.5

Descriptive statistics

Standard deviation15370.378
Coefficient of variation (CV)0.10470628
Kurtosis-1.246644
Mean146795.19
Median Absolute Deviation (MAD)11171.5
Skewness0.25973575
Sum3816675
Variance2.3624852 × 108
MonotonicityNot monotonic
2023-12-12T14:21:34.786491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
166790 1
 
3.8%
134157 1
 
3.8%
163658 1
 
3.8%
166124 1
 
3.8%
163730 1
 
3.8%
171795 1
 
3.8%
167039 1
 
3.8%
168862 1
 
3.8%
166560 1
 
3.8%
156367 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
120372 1
3.8%
126072 1
3.8%
129429 1
3.8%
132168 1
3.8%
132308 1
3.8%
134157 1
3.8%
134513 1
3.8%
134647 1
3.8%
136725 1
3.8%
138045 1
3.8%
ValueCountFrequency (%)
171795 1
3.8%
168862 1
3.8%
167039 1
3.8%
166790 1
3.8%
166560 1
3.8%
166124 1
3.8%
163730 1
3.8%
163658 1
3.8%
156367 1
3.8%
145366 1
3.8%

경질중유
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2055.1538
Minimum1092
Maximum2966
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T14:21:34.908736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1092
5-th percentile1231.25
Q11584.75
median2062.5
Q32360.25
95-th percentile2923.5
Maximum2966
Range1874
Interquartile range (IQR)775.5

Descriptive statistics

Standard deviation554.22484
Coefficient of variation (CV)0.2696756
Kurtosis-1.0207453
Mean2055.1538
Median Absolute Deviation (MAD)467
Skewness0.060562929
Sum53434
Variance307165.18
MonotonicityNot monotonic
2023-12-12T14:21:35.037769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2760 1
 
3.8%
2213 1
 
3.8%
1092 1
 
3.8%
1158 1
 
3.8%
1457 1
 
3.8%
1617 1
 
3.8%
1467 1
 
3.8%
1574 1
 
3.8%
1642 1
 
3.8%
1569 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1092 1
3.8%
1158 1
3.8%
1451 1
3.8%
1457 1
3.8%
1467 1
3.8%
1569 1
3.8%
1574 1
3.8%
1617 1
3.8%
1642 1
3.8%
1683 1
3.8%
ValueCountFrequency (%)
2966 1
3.8%
2956 1
3.8%
2826 1
3.8%
2760 1
3.8%
2714 1
3.8%
2692 1
3.8%
2361 1
3.8%
2358 1
3.8%
2303 1
3.8%
2231 1
3.8%

중유
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1118.8846
Minimum145
Maximum1793
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T14:21:35.173843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum145
5-th percentile170.5
Q1739
median1286.5
Q31550.5
95-th percentile1752.5
Maximum1793
Range1648
Interquartile range (IQR)811.5

Descriptive statistics

Standard deviation522.24487
Coefficient of variation (CV)0.4667549
Kurtosis-0.93211471
Mean1118.8846
Median Absolute Deviation (MAD)404.5
Skewness-0.54102801
Sum29091
Variance272739.71
MonotonicityNot monotonic
2023-12-12T14:21:35.313025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1615 1
 
3.8%
1280 1
 
3.8%
159 1
 
3.8%
145 1
 
3.8%
205 1
 
3.8%
431 1
 
3.8%
634 1
 
3.8%
722 1
 
3.8%
840 1
 
3.8%
787 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
145 1
3.8%
159 1
3.8%
205 1
3.8%
431 1
3.8%
634 1
3.8%
722 1
3.8%
723 1
3.8%
787 1
3.8%
840 1
3.8%
843 1
3.8%
ValueCountFrequency (%)
1793 1
3.8%
1768 1
3.8%
1706 1
3.8%
1636 1
3.8%
1622 1
3.8%
1615 1
3.8%
1563 1
3.8%
1513 1
3.8%
1510 1
3.8%
1436 1
3.8%

벙커C유
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70997.308
Minimum20933
Maximum160367
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T14:21:35.438637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20933
5-th percentile21730.75
Q134140.5
median63984
Q3105589.5
95-th percentile124951.25
Maximum160367
Range139434
Interquartile range (IQR)71449

Descriptive statistics

Standard deviation40484.74
Coefficient of variation (CV)0.57022923
Kurtosis-0.96764381
Mean70997.308
Median Absolute Deviation (MAD)32632.5
Skewness0.41140309
Sum1845930
Variance1.6390142 × 109
MonotonicityNot monotonic
2023-12-12T14:21:35.574171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
160367 1
 
3.8%
51505 1
 
3.8%
21658 1
 
3.8%
20933 1
 
3.8%
22111 1
 
3.8%
21949 1
 
3.8%
31620 1
 
3.8%
33522 1
 
3.8%
45000 1
 
3.8%
35996 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
20933 1
3.8%
21658 1
3.8%
21949 1
3.8%
22111 1
3.8%
31094 1
3.8%
31620 1
3.8%
33522 1
3.8%
35996 1
3.8%
43786 1
3.8%
45000 1
3.8%
ValueCountFrequency (%)
160367 1
3.8%
125319 1
3.8%
123848 1
3.8%
116907 1
3.8%
116271 1
3.8%
111361 1
3.8%
107130 1
3.8%
100968 1
3.8%
96359 1
3.8%
92912 1
3.8%

납사
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean334879.19
Minimum194918
Maximum458350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T14:21:35.728418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum194918
5-th percentile215122
Q1255030.5
median327220.5
Q3409423.25
95-th percentile451644.75
Maximum458350
Range263432
Interquartile range (IQR)154392.75

Descriptive statistics

Standard deviation87397.416
Coefficient of variation (CV)0.26098192
Kurtosis-1.4697093
Mean334879.19
Median Absolute Deviation (MAD)79978.5
Skewness-0.040167946
Sum8706859
Variance7.6383083 × 109
MonotonicityNot monotonic
2023-12-12T14:21:35.864497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
194918 1
 
3.8%
355192 1
 
3.8%
446832 1
 
3.8%
451807 1
 
3.8%
405266 1
 
3.8%
438614 1
 
3.8%
451158 1
 
3.8%
458350 1
 
3.8%
430091 1
 
3.8%
410809 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
194918 1
3.8%
213860 1
3.8%
218908 1
3.8%
229046 1
3.8%
233293 1
3.8%
245309 1
3.8%
252417 1
3.8%
262871 1
3.8%
273250 1
3.8%
287003 1
3.8%
ValueCountFrequency (%)
458350 1
3.8%
451807 1
3.8%
451158 1
3.8%
446832 1
3.8%
438614 1
3.8%
430091 1
3.8%
410809 1
3.8%
405266 1
3.8%
396344 1
3.8%
384606 1
3.8%

용제
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2094.5769
Minimum578
Maximum4753
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T14:21:36.024418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum578
5-th percentile732
Q11067.75
median1623.5
Q33118.5
95-th percentile4359.5
Maximum4753
Range4175
Interquartile range (IQR)2050.75

Descriptive statistics

Standard deviation1312.3534
Coefficient of variation (CV)0.62654819
Kurtosis-0.82157461
Mean2094.5769
Median Absolute Deviation (MAD)863
Skewness0.72525231
Sum54459
Variance1722271.4
MonotonicityNot monotonic
2023-12-12T14:21:36.137014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
785 1
 
3.8%
2877 1
 
3.8%
1403 1
 
3.8%
1585 1
 
3.8%
2154 1
 
3.8%
1728 1
 
3.8%
1614 1
 
3.8%
1742 1
 
3.8%
1633 1
 
3.8%
1388 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
578 1
3.8%
731 1
3.8%
735 1
3.8%
736 1
3.8%
785 1
3.8%
794 1
3.8%
1001 1
3.8%
1268 1
3.8%
1271 1
3.8%
1388 1
3.8%
ValueCountFrequency (%)
4753 1
3.8%
4380 1
3.8%
4298 1
3.8%
3894 1
3.8%
3879 1
3.8%
3330 1
3.8%
3199 1
3.8%
2877 1
3.8%
2703 1
3.8%
2154 1
3.8%

항공유
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26478.231
Minimum17290
Maximum39856
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T14:21:36.246455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17290
5-th percentile18267
Q120727
median25252
Q330295.25
95-th percentile38677
Maximum39856
Range22566
Interquartile range (IQR)9568.25

Descriptive statistics

Standard deviation6869.3941
Coefficient of variation (CV)0.25943554
Kurtosis-0.72179723
Mean26478.231
Median Absolute Deviation (MAD)5013.5
Skewness0.59511237
Sum688434
Variance47188576
MonotonicityNot monotonic
2023-12-12T14:21:36.371126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
19302 1
 
3.8%
28445 1
 
3.8%
25273 1
 
3.8%
21174 1
 
3.8%
21729 1
 
3.8%
38833 1
 
3.8%
39856 1
 
3.8%
38209 1
 
3.8%
36998 1
 
3.8%
34358 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
17290 1
3.8%
18231 1
3.8%
18375 1
3.8%
19302 1
3.8%
20057 1
3.8%
20073 1
3.8%
20578 1
3.8%
21174 1
3.8%
21225 1
3.8%
21729 1
3.8%
ValueCountFrequency (%)
39856 1
3.8%
38833 1
3.8%
38209 1
3.8%
36998 1
3.8%
34358 1
3.8%
31961 1
3.8%
30325 1
3.8%
30206 1
3.8%
28445 1
3.8%
28190 1
3.8%

LPG
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97703.308
Minimum67992
Maximum132789
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T14:21:36.495894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum67992
5-th percentile72969
Q188848.75
median94462
Q3106033.75
95-th percentile122954.75
Maximum132789
Range64797
Interquartile range (IQR)17185

Descriptive statistics

Standard deviation15835.587
Coefficient of variation (CV)0.16207831
Kurtosis-0.025842437
Mean97703.308
Median Absolute Deviation (MAD)9929.5
Skewness0.3452748
Sum2540286
Variance2.507658 × 108
MonotonicityNot monotonic
2023-12-12T14:21:36.605107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
71623 1
 
3.8%
99201 1
 
3.8%
132789 1
 
3.8%
123227 1
 
3.8%
121294 1
 
3.8%
122138 1
 
3.8%
109780 1
 
3.8%
105145 1
 
3.8%
108961 1
 
3.8%
89866 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
67992 1
3.8%
71623 1
3.8%
77007 1
3.8%
84377 1
3.8%
84688 1
3.8%
88432 1
3.8%
88606 1
3.8%
89577 1
3.8%
89866 1
3.8%
91415 1
3.8%
ValueCountFrequency (%)
132789 1
3.8%
123227 1
3.8%
122138 1
3.8%
121294 1
3.8%
109780 1
3.8%
108961 1
3.8%
106320 1
3.8%
105175 1
3.8%
105145 1
3.8%
101881 1
3.8%

아스팔트
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10562.385
Minimum8383
Maximum12484
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T14:21:36.721543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8383
5-th percentile9332.25
Q110162.75
median10513
Q310997
95-th percentile11885.5
Maximum12484
Range4101
Interquartile range (IQR)834.25

Descriptive statistics

Standard deviation867.94834
Coefficient of variation (CV)0.082173522
Kurtosis0.9326644
Mean10562.385
Median Absolute Deviation (MAD)417.5
Skewness-0.081817689
Sum274622
Variance753334.33
MonotonicityNot monotonic
2023-12-12T14:21:36.826904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
11958 1
 
3.8%
10413 1
 
3.8%
8383 1
 
3.8%
9450 1
 
3.8%
10054 1
 
3.8%
10540 1
 
3.8%
10658 1
 
3.8%
11637 1
 
3.8%
11461 1
 
3.8%
10195 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
8383 1
3.8%
9293 1
3.8%
9450 1
3.8%
9851 1
3.8%
9927 1
3.8%
10054 1
3.8%
10152 1
3.8%
10195 1
3.8%
10289 1
3.8%
10296 1
3.8%
ValueCountFrequency (%)
12484 1
3.8%
11958 1
3.8%
11668 1
3.8%
11637 1
3.8%
11461 1
3.8%
11115 1
3.8%
11033 1
3.8%
10889 1
3.8%
10813 1
3.8%
10677 1
3.8%

윤활유
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4334.3846
Minimum2821
Maximum8030
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T14:21:36.946604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2821
5-th percentile3223
Q13647.25
median3972.5
Q34741.75
95-th percentile7005
Maximum8030
Range5209
Interquartile range (IQR)1094.5

Descriptive statistics

Standard deviation1197.4697
Coefficient of variation (CV)0.27627213
Kurtosis4.297027
Mean4334.3846
Median Absolute Deviation (MAD)547.5
Skewness1.950077
Sum112694
Variance1433933.6
MonotonicityNot monotonic
2023-12-12T14:21:37.085297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
3740 1
 
3.8%
3409 1
 
3.8%
7594 1
 
3.8%
8030 1
 
3.8%
4593 1
 
3.8%
4764 1
 
3.8%
4675 1
 
3.8%
4893 1
 
3.8%
4000 1
 
3.8%
3945 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
2821 1
3.8%
3168 1
3.8%
3388 1
3.8%
3409 1
3.8%
3452 1
3.8%
3570 1
3.8%
3636 1
3.8%
3681 1
3.8%
3693 1
3.8%
3740 1
3.8%
ValueCountFrequency (%)
8030 1
3.8%
7594 1
3.8%
5238 1
3.8%
4966 1
3.8%
4900 1
3.8%
4893 1
3.8%
4764 1
3.8%
4675 1
3.8%
4593 1
3.8%
4504 1
3.8%

기타제품
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12457.038
Minimum3659
Maximum32543
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T14:21:37.205223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3659
5-th percentile3840
Q16399
median7588
Q316407.5
95-th percentile29809
Maximum32543
Range28884
Interquartile range (IQR)10008.5

Descriptive statistics

Standard deviation8365.927
Coefficient of variation (CV)0.67158234
Kurtosis0.3116074
Mean12457.038
Median Absolute Deviation (MAD)3919
Skewness1.0085419
Sum323883
Variance69988735
MonotonicityNot monotonic
2023-12-12T14:21:37.324903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
3659 1
 
3.8%
15700 1
 
3.8%
32543 1
 
3.8%
31385 1
 
3.8%
25081 1
 
3.8%
18111 1
 
3.8%
16139 1
 
3.8%
15077 1
 
3.8%
16497 1
 
3.8%
15745 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
3659 1
3.8%
3679 1
3.8%
4323 1
3.8%
4330 1
3.8%
4958 1
3.8%
5992 1
3.8%
6315 1
3.8%
6651 1
3.8%
6826 1
3.8%
6862 1
3.8%
ValueCountFrequency (%)
32543 1
3.8%
31385 1
3.8%
25081 1
3.8%
20420 1
3.8%
18929 1
3.8%
18111 1
3.8%
16497 1
3.8%
16139 1
3.8%
15745 1
3.8%
15700 1
3.8%

부생연료유
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)100.0%
Missing4
Missing (%)15.4%
Infinite0
Infinite (%)0.0%
Mean2165.4091
Minimum916
Maximum3027
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T14:21:37.450391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum916
5-th percentile1467.5
Q11635
median2235
Q32552.75
95-th percentile2954.45
Maximum3027
Range2111
Interquartile range (IQR)917.75

Descriptive statistics

Standard deviation555.54741
Coefficient of variation (CV)0.2565554
Kurtosis-0.41553778
Mean2165.4091
Median Absolute Deviation (MAD)475.5
Skewness-0.4266355
Sum47639
Variance308632.92
MonotonicityNot monotonic
2023-12-12T14:21:37.589492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2227 1
 
3.8%
1515 1
 
3.8%
1465 1
 
3.8%
1577 1
 
3.8%
1551 1
 
3.8%
1604 1
 
3.8%
1728 1
 
3.8%
2531 1
 
3.8%
2425 1
 
3.8%
2215 1
 
3.8%
Other values (12) 12
46.2%
(Missing) 4
 
15.4%
ValueCountFrequency (%)
916 1
3.8%
1465 1
3.8%
1515 1
3.8%
1551 1
3.8%
1577 1
3.8%
1604 1
3.8%
1728 1
3.8%
2163 1
3.8%
2173 1
3.8%
2215 1
3.8%
ValueCountFrequency (%)
3027 1
3.8%
2962 1
3.8%
2811 1
3.8%
2719 1
3.8%
2702 1
3.8%
2560 1
3.8%
2531 1
3.8%
2425 1
3.8%
2277 1
3.8%
2248 1
3.8%

합계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean816500.85
Minimum670278
Maximum947275
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T14:21:37.711397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum670278
5-th percentile725381.75
Q1761526.75
median794612
Q3871946
95-th percentile939604.75
Maximum947275
Range276997
Interquartile range (IQR)110419.25

Descriptive statistics

Standard deviation78716.883
Coefficient of variation (CV)0.096407595
Kurtosis-0.83388016
Mean816500.85
Median Absolute Deviation (MAD)38127.5
Skewness0.41680161
Sum21229022
Variance6.1963477 × 109
MonotonicityNot monotonic
2023-12-12T14:21:37.827467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
793900 1
 
3.8%
801644 1
 
3.8%
947275 1
 
3.8%
938170 1
 
3.8%
877179 1
 
3.8%
931946 1
 
3.8%
934802 1
 
3.8%
940083 1
 
3.8%
924200 1
 
3.8%
856247 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
670278 1
3.8%
719657 1
3.8%
742556 1
3.8%
743668 1
3.8%
752329 1
3.8%
760640 1
3.8%
761080 1
3.8%
762867 1
3.8%
762940 1
3.8%
765520 1
3.8%
ValueCountFrequency (%)
947275 1
3.8%
940083 1
3.8%
938170 1
3.8%
934802 1
3.8%
931946 1
3.8%
924200 1
3.8%
877179 1
3.8%
856247 1
3.8%
827680 1
3.8%
825200 1
3.8%

Interactions

2023-12-12T14:21:31.193922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:07.333082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:08.829148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:10.602089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:12.043342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:13.530345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:15.450701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:17.074404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:18.770276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:20.369764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:21.743420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:23.390035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:24.953299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:26.403499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:28.328519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:29.641913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:31.292531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:07.464813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:08.970726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:10.684663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:12.119466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:13.614339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:15.549248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:17.168693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:18.860380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:20.432330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:21.847804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:23.491905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:25.044263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:26.484482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:28.398627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:29.716938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:31.384281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:07.562565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:09.068147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:10.763009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:12.212927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:13.989805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:15.633615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:17.284846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:18.955363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:20.506298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:21.947819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:23.608603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:25.156843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:26.629572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:28.478931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:29.812255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:31.482947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:07.662325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:09.181250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:10.843718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:12.309143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:14.090606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:15.772048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:17.394571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:19.092056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:20.585637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:22.035727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:23.715018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:25.267836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:26.758291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:28.561370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:29.894974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:31.587980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:07.740016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:09.280232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:10.920607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:12.391069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:14.188448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:15.878362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:17.511820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:19.195995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:20.680702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:22.127228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:23.799137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:25.360797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:27.235399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:28.639022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:30.009270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:31.702916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:07.834326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:09.395140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:11.009416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:12.508647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:14.310296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:15.975452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:17.625154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:19.309010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:20.765673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:22.273813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:23.909493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:25.463442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:27.360704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:28.728793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:30.136299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:31.844798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:07.914446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:09.500089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:11.112457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:12.643197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:14.416346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:16.076841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:17.742985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:19.392505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:20.851646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:22.369140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:24.010916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:25.552869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:27.456320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:28.827809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:30.246870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:31.982048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:08.032382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:09.611132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:11.231429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:12.760493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:14.524708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:16.184028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:17.846437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:19.487033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:20.951746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:22.470314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:24.108362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:25.639666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:27.547848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:28.911623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:30.327778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:32.076044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:08.120134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:09.713284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:11.343688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:12.849889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:14.625657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:16.279797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:17.957749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:19.578300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:21.119637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:22.559366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:24.207377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:25.746163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:27.630875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:28.986829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:30.400532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:32.165936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:08.194864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:09.808245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:11.427847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:12.929878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:14.718082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:16.370614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:18.074121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:19.657252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:21.184749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:22.652184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:24.304695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:25.836546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:27.724643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:29.057340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:30.494123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:32.271622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:08.273438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:09.913533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:11.509056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:13.005486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:14.828099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:16.477252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:18.180524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:19.727961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:21.257696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:22.757351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:24.393517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:25.925793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:27.810580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:29.130973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:30.611470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:32.405893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:08.356364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:10.007041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:11.598200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:13.086497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:14.939535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:16.583091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:18.278486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:19.798580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:21.339320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:22.876318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:24.494403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:26.020669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:27.910714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:29.212943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:30.703725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:32.489808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:08.434658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:10.085362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:11.676608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:13.155392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:15.042024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:16.670353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:18.372423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:19.859365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:21.413511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:22.972846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:24.593741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:26.091600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:27.988655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:29.301051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:30.782371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:32.598730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:08.514647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:10.236282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:11.784111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:13.238681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:15.157155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:16.779284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:18.467038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:19.936950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:21.498637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:23.068324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:24.689651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:26.173751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:28.087217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:29.381801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:30.876075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:32.735797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:08.591578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:10.404195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:11.869810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:13.331293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:15.250255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:16.878605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:18.567238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:20.003600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:21.575849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:23.168089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:24.789705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:26.251683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:28.178511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:29.462095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:30.986252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:32.852259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:08.708051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:10.514538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:11.953927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:13.433422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:15.347371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:16.981142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:18.655029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:20.298760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:21.654315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:23.280440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:24.863737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:26.327174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:28.248937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:29.554794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:21:31.070990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:21:37.936777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
휘발유등유경유경질중유중유벙커C유납사용제항공유LPG아스팔트윤활유기타제품부생연료유합계
1.0000.8960.6600.8280.7940.7420.8860.9560.7280.7950.8080.6600.8770.8110.7520.819
휘발유0.8961.0000.0000.6740.8860.6750.7500.8940.5740.7400.7100.6620.7270.7360.8560.696
등유0.6600.0001.0000.6060.3510.0000.9170.8600.7220.0000.8630.0000.6850.0000.6460.592
경유0.8280.6740.6061.0000.7250.5960.5790.6780.5830.8030.6530.1530.5690.7290.7420.747
경질중유0.7940.8860.3510.7251.0000.4880.7200.5880.8280.8490.2610.4580.6110.7490.7560.533
중유0.7420.6750.0000.5960.4881.0000.0450.3330.2960.7430.7350.0000.0000.5600.5610.297
벙커C유0.8860.7500.9170.5790.7200.0451.0000.8600.8540.7180.9130.4130.3260.3000.8360.666
납사0.9560.8940.8600.6780.5880.3330.8601.0000.7970.7850.7060.0000.8570.6330.6980.857
용제0.7280.5740.7220.5830.8280.2960.8540.7971.0000.6740.5830.5490.5640.5720.0000.744
항공유0.7950.7400.0000.8030.8490.7430.7180.7850.6741.0000.0000.0000.4040.2270.4380.802
LPG0.8080.7100.8630.6530.2610.7350.9130.7060.5830.0001.0000.0000.8200.6340.4380.741
아스팔트0.6600.6620.0000.1530.4580.0000.4130.0000.5490.0000.0001.0000.0000.3800.4160.000
윤활유0.8770.7270.6850.5690.6110.0000.3260.8570.5640.4040.8200.0001.0000.5390.7570.690
기타제품0.8110.7360.0000.7290.7490.5600.3000.6330.5720.2270.6340.3800.5391.0000.8060.698
부생연료유0.7520.8560.6460.7420.7560.5610.8360.6980.0000.4380.4380.4160.7570.8061.0000.706
합계0.8190.6960.5920.7470.5330.2970.6660.8570.7440.8020.7410.0000.6900.6980.7061.000
2023-12-12T14:21:38.110385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
휘발유등유경유경질중유중유벙커C유납사용제항공유LPG아스팔트윤활유기타제품부생연료유합계
1.0000.837-0.9440.634-0.933-0.856-0.9740.9760.1820.7330.865-0.2510.5230.956-0.6220.918
휘발유0.8371.000-0.7740.634-0.805-0.909-0.8190.815-0.2440.5540.679-0.2560.3510.781-0.7440.884
등유-0.944-0.7741.000-0.5590.9480.8250.963-0.917-0.091-0.737-0.7120.353-0.364-0.9540.532-0.852
경유0.6340.634-0.5591.000-0.575-0.458-0.5800.6580.1520.5260.5040.1360.4910.543-0.2110.789
경질중유-0.933-0.8050.948-0.5751.0000.8830.962-0.908-0.071-0.669-0.7310.348-0.433-0.9230.600-0.839
중유-0.856-0.9090.825-0.4580.8831.0000.880-0.8320.240-0.538-0.6640.405-0.282-0.8190.784-0.798
벙커C유-0.974-0.8190.963-0.5800.9620.8801.000-0.947-0.130-0.713-0.8030.333-0.446-0.9550.630-0.875
납사0.9760.815-0.9170.658-0.908-0.832-0.9471.0000.1850.8030.829-0.1600.5090.903-0.5730.932
용제0.182-0.244-0.0910.152-0.0710.240-0.1300.1851.0000.2600.4280.3370.5280.1200.5520.080
항공유0.7330.554-0.7370.526-0.669-0.538-0.7130.8030.2601.0000.5900.1650.2430.679-0.1850.735
LPG0.8650.679-0.7120.504-0.731-0.664-0.8030.8290.4280.5901.000-0.0820.6790.776-0.5380.778
아스팔트-0.251-0.2560.3530.1360.3480.4050.333-0.1600.3370.165-0.0821.0000.074-0.3340.305-0.088
윤활유0.5230.351-0.3640.491-0.433-0.282-0.4460.5090.5280.2430.6790.0741.0000.382-0.2170.456
기타제품0.9560.781-0.9540.543-0.923-0.819-0.9550.9030.1200.6790.776-0.3340.3821.000-0.5470.845
부생연료유-0.622-0.7440.532-0.2110.6000.7840.630-0.5730.552-0.185-0.5380.305-0.217-0.5471.000-0.558
합계0.9180.884-0.8520.789-0.839-0.798-0.8750.9320.0800.7350.778-0.0880.4560.845-0.5581.000

Missing values

2023-12-12T14:21:33.010220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:21:33.261596image/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

휘발유등유경유경질중유중유벙커C유납사용제항공유LPG아스팔트윤활유기타제품부생연료유합계
0199771358850251667902760161516036719491878519302716231195837403659<NA>793900
119986108961457120372223112841071302138605781729067992985128214323<NA>670278
2199963879769281260722826151311627121890873518375770071029631683679<NA>719657
3200062382699091294292966143612531922904673618231846881028937954330<NA>742556
4200162707617071321682714151012384823329379420073843771103335704958916743668
520026407858464138045295616361169072453091271200579141510350382759922560762867
620036048452874145366269217681113612524172703205788860610550407966512811762940
720045815143090143799230317061009682628713894212258843211668433368623027752329
82005595613939214252923611793963592732504380250589166810486496663152962761080
92006598743145014243323581622929122870034753252319345110813368172202719765520
휘발유등유경유경질중유중유벙커C유납사용제항공유LPG아스팔트윤활유기타제품부생연료유합계
16201373416188161430201683897437863842487313032593057106773388189292227825200
17201473473154291448401451723310943963441001319618957792933636204202215821457
182015765701622715636715697873599641080913883435889866101953945157452425856247
1920167892619060166560164284045000430091163336998108961114614000164972531924200
2020177961619006168862157472233522458350174238209105145116374893150771728940083
2120187968318875167039146763431620451158161439856109780106584675161391604934802
2220198275017127171795161743121949438614172838833122138105404764181111551931946
2320208096516964163730145720522111405266215421729121294100544593250811577877179
242021848741681316612411581452093345180715852117412322794508030313851465938170
252022883681600816365810921592165844683214032527313278983837594325431515947275