Overview

Dataset statistics

Number of variables15
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory139.4 B

Variable types

Numeric15

Dataset

Description부산항에서 처리되는 컨테이너화물의 연도별 물동량 통계 데이터를 제공합니다.- 부산항 컨테이너 부두- 단위 : TEU
Author부산항만공사
URLhttps://www.data.go.kr/data/15055478/fileData.do

Alerts

연도 is highly overall correlated with 전체 and 10 other fieldsHigh correlation
전체 is highly overall correlated with 연도 and 10 other fieldsHigh correlation
자성대부두 is highly overall correlated with 연도 and 3 other fieldsHigh correlation
신선대부두 is highly overall correlated with 연도 and 7 other fieldsHigh correlation
감만부두 is highly overall correlated with 우암부두 and 2 other fieldsHigh correlation
우암부두 is highly overall correlated with 감만부두 and 2 other fieldsHigh correlation
감천한진 is highly overall correlated with 감만부두 and 2 other fieldsHigh correlation
신감만부두 is highly overall correlated with 연도 and 6 other fieldsHigh correlation
일반부두(북항-감천) is highly overall correlated with 연도 and 8 other fieldsHigh correlation
신항1부두 is highly overall correlated with 연도 and 9 other fieldsHigh correlation
신항2부두 is highly overall correlated with 연도 and 8 other fieldsHigh correlation
신항3부두 is highly overall correlated with 연도 and 8 other fieldsHigh correlation
신항4부두 is highly overall correlated with 연도 and 7 other fieldsHigh correlation
신항5부두 is highly overall correlated with 연도 and 7 other fieldsHigh correlation
다목적부두등 is highly overall correlated with 연도 and 8 other fieldsHigh correlation
연도 has unique valuesUnique
전체 has unique valuesUnique
자성대부두 has unique valuesUnique
신선대부두 has unique valuesUnique
일반부두(북항-감천) has unique valuesUnique
감만부두 has 5 (16.7%) zerosZeros
우암부두 has 6 (20.0%) zerosZeros
감천한진 has 5 (16.7%) zerosZeros
신감만부두 has 9 (30.0%) zerosZeros
신항1부두 has 13 (43.3%) zerosZeros
신항2부두 has 14 (46.7%) zerosZeros
신항3부두 has 16 (53.3%) zerosZeros
신항4부두 has 17 (56.7%) zerosZeros
신항5부두 has 18 (60.0%) zerosZeros
다목적부두등 has 15 (50.0%) zerosZeros

Reproduction

Analysis started2023-12-12 04:28:36.246091
Analysis finished2023-12-12 04:29:02.616616
Duration26.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2007.5
Minimum1993
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T13:29:02.685324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1993
5-th percentile1994.45
Q12000.25
median2007.5
Q32014.75
95-th percentile2020.55
Maximum2022
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.0043852595
Kurtosis-1.2
Mean2007.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum60225
Variance77.5
MonotonicityStrictly increasing
2023-12-12T13:29:02.821455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1993 1
 
3.3%
2009 1
 
3.3%
2022 1
 
3.3%
2021 1
 
3.3%
2020 1
 
3.3%
2019 1
 
3.3%
2018 1
 
3.3%
2017 1
 
3.3%
2016 1
 
3.3%
2015 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1993 1
3.3%
1994 1
3.3%
1995 1
3.3%
1996 1
3.3%
1997 1
3.3%
1998 1
3.3%
1999 1
3.3%
2000 1
3.3%
2001 1
3.3%
2002 1
3.3%
ValueCountFrequency (%)
2022 1
3.3%
2021 1
3.3%
2020 1
3.3%
2019 1
3.3%
2018 1
3.3%
2017 1
3.3%
2016 1
3.3%
2015 1
3.3%
2014 1
3.3%
2013 1
3.3%

전체
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13089953
Minimum2975632
Maximum22706131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T13:29:02.982049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2975632
5-th percentile3824790.2
Q16805446.5
median12650477
Q319263042
95-th percentile22039408
Maximum22706131
Range19730499
Interquartile range (IQR)12457595

Descriptive statistics

Standard deviation6559338.5
Coefficient of variation (CV)0.50109718
Kurtosis-1.3705455
Mean13089953
Median Absolute Deviation (MAD)6536697
Skewness-0.042509518
Sum3.9269859 × 108
Variance4.3024921 × 1013
MonotonicityNot monotonic
2023-12-12T13:29:03.121697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
2975632 1
 
3.3%
11980611 1
 
3.3%
22078195 1
 
3.3%
22706131 1
 
3.3%
21823996 1
 
3.3%
21992001 1
 
3.3%
21662573 1
 
3.3%
20493477 1
 
3.3%
19456293 1
 
3.3%
19468725 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
2975632 1
3.3%
3574925 1
3.3%
4130181 1
3.3%
4374246 1
3.3%
4811377 1
3.3%
5311660 1
3.3%
5655694 1
3.3%
6382899 1
3.3%
8073089 1
3.3%
9453689 1
3.3%
ValueCountFrequency (%)
22706131 1
3.3%
22078195 1
3.3%
21992001 1
3.3%
21823996 1
3.3%
21662573 1
3.3%
20493477 1
3.3%
19468725 1
3.3%
19456293 1
3.3%
18683287 1
3.3%
17686099 1
3.3%

자성대부두
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1643121.4
Minimum896746
Maximum2274710
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T13:29:03.275569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum896746
5-th percentile1075688.7
Q11375665.8
median1594899.5
Q31922268.5
95-th percentile2173909.7
Maximum2274710
Range1377964
Interquartile range (IQR)546602.75

Descriptive statistics

Standard deviation368422.8
Coefficient of variation (CV)0.22422128
Kurtosis-0.88179593
Mean1643121.4
Median Absolute Deviation (MAD)315488.5
Skewness-0.14957908
Sum49293643
Variance1.3573536 × 1011
MonotonicityNot monotonic
2023-12-12T13:29:03.418033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1049244 1
 
3.3%
1897899 1
 
3.3%
1917869 1
 
3.3%
1982803 1
 
3.3%
1826714 1
 
3.3%
1923735 1
 
3.3%
1926182 1
 
3.3%
2073695 1
 
3.3%
1867428 1
 
3.3%
1729414 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
896746 1
3.3%
1049244 1
3.3%
1108010 1
3.3%
1195849 1
3.3%
1245793 1
3.3%
1272333 1
3.3%
1286489 1
3.3%
1366534 1
3.3%
1403061 1
3.3%
1476998 1
3.3%
ValueCountFrequency (%)
2274710 1
3.3%
2212526 1
3.3%
2126712 1
3.3%
2103012 1
3.3%
2073695 1
3.3%
1982803 1
3.3%
1926182 1
3.3%
1923735 1
3.3%
1917869 1
3.3%
1897899 1
3.3%

신선대부두
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1888639.8
Minimum944722
Maximum2688014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T13:29:03.557568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum944722
5-th percentile1065247.8
Q11320702.8
median2005392
Q32365000.8
95-th percentile2617566.7
Maximum2688014
Range1743292
Interquartile range (IQR)1044298

Descriptive statistics

Standard deviation563121.64
Coefficient of variation (CV)0.29816255
Kurtosis-1.3457341
Mean1888639.8
Median Absolute Deviation (MAD)397070.5
Skewness-0.3665085
Sum56659193
Variance3.1710598 × 1011
MonotonicityNot monotonic
2023-12-12T13:29:03.696489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
944722 1
 
3.3%
2655760 1
 
3.3%
2341909 1
 
3.3%
2376489 1
 
3.3%
2307478 1
 
3.3%
2404009 1
 
3.3%
2490203 1
 
3.3%
2260708 1
 
3.3%
1954293 1
 
3.3%
2015853 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
944722 1
3.3%
1056435 1
3.3%
1076019 1
3.3%
1077149 1
3.3%
1091600 1
3.3%
1169493 1
3.3%
1216891 1
3.3%
1319812 1
3.3%
1323375 1
3.3%
1528338 1
3.3%
ValueCountFrequency (%)
2688014 1
3.3%
2655760 1
3.3%
2570886 1
3.3%
2490203 1
3.3%
2404009 1
3.3%
2400916 1
3.3%
2376489 1
3.3%
2372698 1
3.3%
2341909 1
3.3%
2307478 1
3.3%

감만부두
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1490617.5
Minimum0
Maximum2862254
Zeros5
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T13:29:03.818624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11144958.8
median1481800
Q32041745.2
95-th percentile2789241.5
Maximum2862254
Range2862254
Interquartile range (IQR)896786.5

Descriptive statistics

Standard deviation882541.13
Coefficient of variation (CV)0.59206413
Kurtosis-0.56858875
Mean1490617.5
Median Absolute Deviation (MAD)423672
Skewness-0.27126249
Sum44718524
Variance7.7887884 × 1011
MonotonicityNot monotonic
2023-12-12T13:29:03.936033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 5
 
16.7%
1840908 1
 
3.3%
1424086 1
 
3.3%
1498394 1
 
3.3%
1509062 1
 
3.3%
1444404 1
 
3.3%
1287910 1
 
3.3%
1286369 1
 
3.3%
1171826 1
 
3.3%
1132395 1
 
3.3%
Other values (16) 16
53.3%
ValueCountFrequency (%)
0 5
16.7%
772922 1
 
3.3%
1132395 1
 
3.3%
1136003 1
 
3.3%
1171826 1
 
3.3%
1203322 1
 
3.3%
1286369 1
 
3.3%
1287910 1
 
3.3%
1424086 1
 
3.3%
1444404 1
 
3.3%
ValueCountFrequency (%)
2862254 1
3.3%
2842801 1
3.3%
2723780 1
3.3%
2722509 1
3.3%
2558774 1
3.3%
2546451 1
3.3%
2261533 1
3.3%
2081462 1
3.3%
1922595 1
3.3%
1888349 1
3.3%

우암부두
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean278218.83
Minimum0
Maximum640339
Zeros6
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T13:29:04.079267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1381.25
median288928
Q3544392
95-th percentile596672.4
Maximum640339
Range640339
Interquartile range (IQR)544010.75

Descriptive statistics

Standard deviation260340.81
Coefficient of variation (CV)0.93574116
Kurtosis-1.887872
Mean278218.83
Median Absolute Deviation (MAD)283602
Skewness0.028027542
Sum8346565
Variance6.777734 × 1010
MonotonicityNot monotonic
2023-12-12T13:29:04.191563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 6
 
20.0%
298465 1
 
3.3%
232 1
 
3.3%
329 1
 
3.3%
1476 1
 
3.3%
538 1
 
3.3%
2465 1
 
3.3%
2718 1
 
3.3%
46862 1
 
3.3%
514920 1
 
3.3%
Other values (15) 15
50.0%
ValueCountFrequency (%)
0 6
20.0%
232 1
 
3.3%
329 1
 
3.3%
538 1
 
3.3%
1476 1
 
3.3%
2465 1
 
3.3%
2718 1
 
3.3%
46862 1
 
3.3%
255543 1
 
3.3%
279391 1
 
3.3%
ValueCountFrequency (%)
640339 1
3.3%
612489 1
3.3%
577341 1
3.3%
569922 1
3.3%
564739 1
3.3%
551938 1
3.3%
549889 1
3.3%
548090 1
3.3%
533298 1
3.3%
531298 1
3.3%

감천한진
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean167263.37
Minimum0
Maximum574822
Zeros5
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T13:29:04.298142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1480.5
median1867.5
Q3415032
95-th percentile552534.65
Maximum574822
Range574822
Interquartile range (IQR)414551.5

Descriptive statistics

Standard deviation231877.11
Coefficient of variation (CV)1.3862994
Kurtosis-1.222434
Mean167263.37
Median Absolute Deviation (MAD)1867.5
Skewness0.8278232
Sum5017901
Variance5.3766992 × 1010
MonotonicityNot monotonic
2023-12-12T13:29:04.409164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 5
 
16.7%
187 1
 
3.3%
518 1
 
3.3%
1012 1
 
3.3%
1855 1
 
3.3%
1427 1
 
3.3%
624 1
 
3.3%
1146 1
 
3.3%
1880 1
 
3.3%
3234 1
 
3.3%
Other values (16) 16
53.3%
ValueCountFrequency (%)
0 5
16.7%
187 1
 
3.3%
264 1
 
3.3%
468 1
 
3.3%
518 1
 
3.3%
624 1
 
3.3%
1012 1
 
3.3%
1146 1
 
3.3%
1186 1
 
3.3%
1427 1
 
3.3%
ValueCountFrequency (%)
574822 1
3.3%
556154 1
3.3%
548111 1
3.3%
512285 1
3.3%
504269 1
3.3%
503697 1
3.3%
497701 1
3.3%
432972 1
3.3%
361212 1
3.3%
308671 1
3.3%

신감만부두
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean731529.2
Minimum0
Maximum1250148
Zeros9
Zeros (%)30.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T13:29:04.519999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median992490.5
Q31134114.5
95-th percentile1235110.8
Maximum1250148
Range1250148
Interquartile range (IQR)1134114.5

Descriptive statistics

Standard deviation509821.38
Coefficient of variation (CV)0.69692554
Kurtosis-1.4156294
Mean731529.2
Median Absolute Deviation (MAD)205697
Skewness-0.67913107
Sum21945876
Variance2.5991784 × 1011
MonotonicityNot monotonic
2023-12-12T13:29:04.630679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 9
30.0%
1032732 1
 
3.3%
890661 1
 
3.3%
1016701 1
 
3.3%
1033422 1
 
3.3%
1008637 1
 
3.3%
970504 1
 
3.3%
943275 1
 
3.3%
1069650 1
 
3.3%
1110635 1
 
3.3%
Other values (12) 12
40.0%
ValueCountFrequency (%)
0 9
30.0%
481202 1
 
3.3%
745564 1
 
3.3%
890661 1
 
3.3%
943275 1
 
3.3%
970504 1
 
3.3%
976344 1
 
3.3%
1008637 1
 
3.3%
1016701 1
 
3.3%
1032732 1
 
3.3%
ValueCountFrequency (%)
1250148 1
3.3%
1240864 1
3.3%
1228079 1
3.3%
1210767 1
3.3%
1185608 1
3.3%
1165837 1
3.3%
1144670 1
3.3%
1141941 1
3.3%
1110635 1
3.3%
1098635 1
3.3%

일반부두(북항-감천)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1372875.7
Minimum166895
Maximum2873705
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T13:29:04.821960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum166895
5-th percentile213043.7
Q1597025.5
median1116703
Q32329615.2
95-th percentile2795760.8
Maximum2873705
Range2706810
Interquartile range (IQR)1732589.8

Descriptive statistics

Standard deviation961980.93
Coefficient of variation (CV)0.70070503
Kurtosis-1.4535795
Mean1372875.7
Median Absolute Deviation (MAD)688065.5
Skewness0.35591829
Sum41186272
Variance9.2540732 × 1011
MonotonicityNot monotonic
2023-12-12T13:29:05.016524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
981617 1
 
3.3%
893887 1
 
3.3%
255386 1
 
3.3%
287905 1
 
3.3%
166895 1
 
3.3%
178400 1
 
3.3%
320429 1
 
3.3%
447729 1
 
3.3%
527801 1
 
3.3%
596629 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
166895 1
3.3%
178400 1
3.3%
255386 1
3.3%
287905 1
3.3%
320429 1
3.3%
447729 1
3.3%
527801 1
3.3%
596629 1
3.3%
598215 1
3.3%
603117 1
3.3%
ValueCountFrequency (%)
2873705 1
3.3%
2809502 1
3.3%
2778966 1
3.3%
2718937 1
3.3%
2699951 1
3.3%
2677673 1
3.3%
2641250 1
3.3%
2435093 1
3.3%
2013182 1
3.3%
1823860 1
3.3%

신항1부두
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean981023.4
Minimum0
Maximum2743856
Zeros13
Zeros (%)43.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T13:29:05.160269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median573390
Q32158346
95-th percentile2715544.9
Maximum2743856
Range2743856
Interquartile range (IQR)2158346

Descriptive statistics

Standard deviation1094337.8
Coefficient of variation (CV)1.1155063
Kurtosis-1.3929879
Mean981023.4
Median Absolute Deviation (MAD)573390
Skewness0.5749088
Sum29430702
Variance1.1975752 × 1012
MonotonicityNot monotonic
2023-12-12T13:29:05.359710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 13
43.3%
2420860 1
 
3.3%
2684136 1
 
3.3%
2737054 1
 
3.3%
2743856 1
 
3.3%
2295359 1
 
3.3%
2477785 1
 
3.3%
2689256 1
 
3.3%
2418702 1
 
3.3%
1712729 1
 
3.3%
Other values (8) 8
26.7%
ValueCountFrequency (%)
0 13
43.3%
237714 1
 
3.3%
445520 1
 
3.3%
701260 1
 
3.3%
928205 1
 
3.3%
969203 1
 
3.3%
1001523 1
 
3.3%
1220233 1
 
3.3%
1712729 1
 
3.3%
1747307 1
 
3.3%
ValueCountFrequency (%)
2743856 1
3.3%
2737054 1
3.3%
2689256 1
3.3%
2684136 1
3.3%
2477785 1
3.3%
2420860 1
3.3%
2418702 1
3.3%
2295359 1
3.3%
1747307 1
3.3%
1712729 1
3.3%

신항2부두
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1874548.1
Minimum0
Maximum5501091
Zeros14
Zeros (%)46.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T13:29:05.503317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median355717
Q34195966.2
95-th percentile5019918
Maximum5501091
Range5501091
Interquartile range (IQR)4195966.2

Descriptive statistics

Standard deviation2166163.9
Coefficient of variation (CV)1.1555659
Kurtosis-1.6487836
Mean1874548.1
Median Absolute Deviation (MAD)355717
Skewness0.47507883
Sum56236442
Variance4.692266 × 1012
MonotonicityNot monotonic
2023-12-12T13:29:05.644599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 14
46.7%
133657 1
 
3.3%
4827307 1
 
3.3%
5086577 1
 
3.3%
4837172 1
 
3.3%
5501091 1
 
3.3%
4938446 1
 
3.3%
4531302 1
 
3.3%
4626435 1
 
3.3%
4296221 1
 
3.3%
Other values (7) 7
23.3%
ValueCountFrequency (%)
0 14
46.7%
133657 1
 
3.3%
577777 1
 
3.3%
797687 1
 
3.3%
2389324 1
 
3.3%
3218770 1
 
3.3%
3280017 1
 
3.3%
3299457 1
 
3.3%
3895202 1
 
3.3%
4296221 1
 
3.3%
ValueCountFrequency (%)
5501091 1
3.3%
5086577 1
3.3%
4938446 1
3.3%
4837172 1
3.3%
4827307 1
3.3%
4626435 1
3.3%
4531302 1
3.3%
4296221 1
3.3%
3895202 1
3.3%
3299457 1
3.3%

신항3부두
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1086749
Minimum0
Maximum2954267
Zeros16
Zeros (%)53.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T13:29:05.813504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32425880.5
95-th percentile2869098.2
Maximum2954267
Range2954267
Interquartile range (IQR)2425880.5

Descriptive statistics

Standard deviation1241650.3
Coefficient of variation (CV)1.1425364
Kurtosis-1.7972946
Mean1086749
Median Absolute Deviation (MAD)0
Skewness0.37386781
Sum32602470
Variance1.5416954 × 1012
MonotonicityNot monotonic
2023-12-12T13:29:06.008936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 16
53.3%
923731 1
 
3.3%
1553155 1
 
3.3%
2018283 1
 
3.3%
2442636 1
 
3.3%
2375614 1
 
3.3%
2467741 1
 
3.3%
2555966 1
 
3.3%
1925545 1
 
3.3%
2219402 1
 
3.3%
Other values (5) 5
 
16.7%
ValueCountFrequency (%)
0 16
53.3%
923731 1
 
3.3%
1553155 1
 
3.3%
1925545 1
 
3.3%
2018283 1
 
3.3%
2219402 1
 
3.3%
2375614 1
 
3.3%
2442636 1
 
3.3%
2467741 1
 
3.3%
2555966 1
 
3.3%
ValueCountFrequency (%)
2954267 1
3.3%
2939071 1
3.3%
2783576 1
3.3%
2770535 1
3.3%
2672948 1
3.3%
2555966 1
3.3%
2467741 1
3.3%
2442636 1
3.3%
2375614 1
3.3%
2219402 1
3.3%

신항4부두
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean896447.9
Minimum0
Maximum2552383
Zeros17
Zeros (%)56.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T13:29:06.219441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32100038
95-th percentile2360514.2
Maximum2552383
Range2552383
Interquartile range (IQR)2100038

Descriptive statistics

Standard deviation1080132.4
Coefficient of variation (CV)1.2049026
Kurtosis-1.8237278
Mean896447.9
Median Absolute Deviation (MAD)0
Skewness0.44018977
Sum26893437
Variance1.1666861 × 1012
MonotonicityNot monotonic
2023-12-12T13:29:06.367245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 17
56.7%
837088 1
 
3.3%
1576779 1
 
3.3%
1988675 1
 
3.3%
2391890 1
 
3.3%
2552383 1
 
3.3%
2320661 1
 
3.3%
2322166 1
 
3.3%
2069198 1
 
3.3%
2061131 1
 
3.3%
Other values (4) 4
 
13.3%
ValueCountFrequency (%)
0 17
56.7%
837088 1
 
3.3%
1576779 1
 
3.3%
1988675 1
 
3.3%
2061131 1
 
3.3%
2069198 1
 
3.3%
2110318 1
 
3.3%
2167478 1
 
3.3%
2237903 1
 
3.3%
2257767 1
 
3.3%
ValueCountFrequency (%)
2552383 1
3.3%
2391890 1
3.3%
2322166 1
3.3%
2320661 1
3.3%
2257767 1
3.3%
2237903 1
3.3%
2167478 1
3.3%
2110318 1
3.3%
2069198 1
3.3%
2061131 1
3.3%

신항5부두
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean629254.9
Minimum0
Maximum2433623
Zeros18
Zeros (%)60.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T13:29:06.516831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31294591.2
95-th percentile2294834.6
Maximum2433623
Range2433623
Interquartile range (IQR)1294591.2

Descriptive statistics

Standard deviation918153.56
Coefficient of variation (CV)1.4591123
Kurtosis-0.77142706
Mean629254.9
Median Absolute Deviation (MAD)0
Skewness0.98897434
Sum18877647
Variance8.4300596 × 1011
MonotonicityNot monotonic
2023-12-12T13:29:06.676899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 18
60.0%
21 1
 
3.3%
459969 1
 
3.3%
1099366 1
 
3.3%
1305610 1
 
3.3%
1261535 1
 
3.3%
1541859 1
 
3.3%
1940079 1
 
3.3%
2269682 1
 
3.3%
2119075 1
 
3.3%
Other values (3) 3
 
10.0%
ValueCountFrequency (%)
0 18
60.0%
21 1
 
3.3%
459969 1
 
3.3%
1099366 1
 
3.3%
1261535 1
 
3.3%
1305610 1
 
3.3%
1541859 1
 
3.3%
1940079 1
 
3.3%
2119075 1
 
3.3%
2131414 1
 
3.3%
ValueCountFrequency (%)
2433623 1
3.3%
2315414 1
3.3%
2269682 1
3.3%
2131414 1
3.3%
2119075 1
3.3%
1940079 1
3.3%
1541859 1
3.3%
1305610 1
3.3%
1261535 1
3.3%
1099366 1
3.3%

다목적부두등
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44637.767
Minimum0
Maximum371986
Zeros15
Zeros (%)50.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T13:29:06.815417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median40.5
Q332243.75
95-th percentile215334.8
Maximum371986
Range371986
Interquartile range (IQR)32243.75

Descriptive statistics

Standard deviation88635.922
Coefficient of variation (CV)1.9856711
Kurtosis5.9939975
Mean44637.767
Median Absolute Deviation (MAD)40.5
Skewness2.4481226
Sum1339133
Variance7.8563267 × 109
MonotonicityNot monotonic
2023-12-12T13:29:06.984275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 15
50.0%
26242 1
 
3.3%
371986 1
 
3.3%
226808 1
 
3.3%
201312 1
 
3.3%
164481 1
 
3.3%
147666 1
 
3.3%
30782 1
 
3.3%
22604 1
 
3.3%
81 1
 
3.3%
Other values (6) 6
 
20.0%
ValueCountFrequency (%)
0 15
50.0%
81 1
 
3.3%
214 1
 
3.3%
4460 1
 
3.3%
8869 1
 
3.3%
22604 1
 
3.3%
26242 1
 
3.3%
30782 1
 
3.3%
32731 1
 
3.3%
49734 1
 
3.3%
ValueCountFrequency (%)
371986 1
3.3%
226808 1
3.3%
201312 1
3.3%
164481 1
3.3%
147666 1
3.3%
51163 1
3.3%
49734 1
3.3%
32731 1
3.3%
30782 1
3.3%
26242 1
3.3%

Interactions

2023-12-12T13:29:00.406420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:36.734835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:38.491975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:40.405299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:42.388077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:43.994821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:45.215484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:46.344955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:48.514947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:50.406161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:52.037428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:53.411965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:55.562765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:57.435402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:59.010564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:00.506433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:36.865304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:38.594948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:40.854382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:42.487902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:44.069268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:45.287161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:46.742419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:48.632275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:50.506793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:52.117317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:53.557807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:55.669749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:57.531891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:59.091665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:00.654979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:36.966996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:38.706563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:40.978124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:42.609109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:44.153600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:45.372850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:46.843115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:48.776673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:50.622026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:52.206547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:53.723258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:55.809690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:57.644201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:59.184403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:00.766017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:37.071828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:38.828696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:41.083107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:42.712636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:44.239857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:45.451024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:46.984094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:48.921789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:50.734665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:52.324146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:54.169972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:55.948086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:57.763297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:59.298965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:00.863396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:37.213616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:38.963279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:41.196820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:42.831872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:44.333006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:45.528684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:47.125896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:49.087264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:50.853826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:52.432672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:54.295033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:56.077442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:57.860156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:59.397009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:01.226223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:37.342921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:39.097660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:41.329918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:42.957047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:44.418521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:45.610793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:47.231472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:49.206475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:50.980447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:52.525968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:54.459341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:56.222553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:57.949560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:59.482851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:01.326933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:37.447979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:39.234444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:41.422394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:43.058902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:44.498381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:45.681994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:47.351370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:49.329440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:51.128198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:52.609664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:54.550525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:56.354782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:58.104066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:59.571904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:01.421033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:37.569547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:39.361353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:41.545417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:43.165310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:44.578052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:45.753136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:47.574233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:49.464174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:51.238824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:52.691248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:54.651687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:56.461087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:58.214565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:59.658101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:01.519301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:37.703321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:39.479004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:41.655246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:43.291551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:44.655556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:45.827552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:47.694612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:49.587749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:51.340825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:52.771370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:54.780912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:56.589046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:58.305284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:59.771188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:01.622186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:37.814467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:39.626621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:41.776822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:43.403851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:44.730180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:45.900045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:47.827448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:49.698634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:51.436525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:52.853420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:54.901339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:56.715854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:58.410295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:59.860141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:01.732810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:37.929816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:39.761202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:41.876575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:43.516108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:44.805320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:45.981718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:47.955394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:49.817844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:51.541148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:52.938901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:54.990209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:56.839937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:58.525914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:59.943459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:01.844222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:38.023498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:39.896693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:41.983325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:43.614184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:44.898395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:46.051820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:48.072233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:49.934839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:51.649298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:53.020642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:55.077730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:56.946559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:58.635132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:00.046793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:01.941489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:38.129261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:39.997931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:42.091672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:43.706026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:44.979167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:46.124223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:48.178886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:50.031366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:51.740561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:53.102759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:55.202723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:57.082426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:58.760770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:00.137430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:02.063869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:38.239704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:40.119293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:42.198306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:43.812068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:45.047888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:46.194158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:48.273165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:50.137902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:51.847223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:53.186841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:55.319431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:57.200235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:58.843376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:00.231432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:02.171994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:38.343989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:40.269165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:42.287969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:43.901550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:45.126771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:46.264227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:48.391141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:50.264149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:51.942563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:53.273108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:55.438457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:57.319519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:58.922688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:29:00.317482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:29:07.141037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도전체자성대부두신선대부두감만부두우암부두감천한진신감만부두일반부두(북항-감천)신항1부두신항2부두신항3부두신항4부두신항5부두다목적부두등
연도1.0000.9290.5930.5790.6850.6400.5390.7390.8960.7410.8470.7270.8090.6420.546
전체0.9291.0000.3300.8720.7760.8290.7960.7870.8360.7580.6880.8130.8630.5750.000
자성대부두0.5930.3301.0000.6480.5570.4490.4040.2940.6010.0000.0000.0000.0000.2550.000
신선대부두0.5790.8720.6481.0000.5700.7800.0000.8370.7000.2960.0000.3590.2120.2370.000
감만부두0.6850.7760.5570.5701.0000.7770.7780.7640.6810.2620.7490.6150.6280.5270.000
우암부두0.6400.8290.4490.7800.7771.0000.9520.6720.3940.0000.0000.0000.3320.0000.000
감천한진0.5390.7960.4040.0000.7780.9521.0000.0000.6600.0000.0000.0000.0000.0000.000
신감만부두0.7390.7870.2940.8370.7640.6720.0001.0000.3810.5830.4690.3070.6030.3220.000
일반부두(북항-감천)0.8960.8360.6010.7000.6810.3940.6600.3811.0000.5570.7500.7730.7250.0000.000
신항1부두0.7410.7580.0000.2960.2620.0000.0000.5830.5571.0000.8700.8410.9430.9170.497
신항2부두0.8470.6880.0000.0000.7490.0000.0000.4690.7500.8701.0000.9610.8660.7710.847
신항3부두0.7270.8130.0000.3590.6150.0000.0000.3070.7730.8410.9611.0000.8920.8520.574
신항4부두0.8090.8630.0000.2120.6280.3320.0000.6030.7250.9430.8660.8921.0000.8530.482
신항5부두0.6420.5750.2550.2370.5270.0000.0000.3220.0000.9170.7710.8520.8531.0000.798
다목적부두등0.5460.0000.0000.0000.0000.0000.0000.0000.0000.4970.8470.5740.4820.7981.000
2023-12-12T13:29:07.713219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도전체자성대부두신선대부두감만부두우암부두감천한진신감만부두일반부두(북항-감천)신항1부두신항2부두신항3부두신항4부두신항5부두다목적부두등
연도1.0000.9960.5620.7630.209-0.0290.0230.582-0.7070.9440.9410.9010.8410.8840.921
전체0.9961.0000.5740.7560.214-0.0300.0360.587-0.6890.9400.9370.8930.8400.8820.910
자성대부두0.5620.5741.0000.6450.4860.1270.3310.554-0.0740.4990.4290.2710.1760.3090.315
신선대부두0.7630.7560.6451.0000.4520.3290.0770.795-0.4140.6870.7070.6440.4560.4950.663
감만부두0.2090.2140.4860.4521.0000.7420.7330.5550.445-0.000-0.049-0.118-0.214-0.194-0.063
우암부두-0.029-0.0300.1270.3290.7421.0000.5160.5690.480-0.198-0.221-0.247-0.245-0.397-0.203
감천한진0.0230.0360.3310.0770.7330.5161.0000.2900.596-0.152-0.211-0.314-0.299-0.311-0.295
신감만부두0.5820.5870.5540.7950.5550.5690.2901.000-0.1270.5230.4840.3970.3860.2470.426
일반부두(북항-감천)-0.707-0.689-0.074-0.4140.4450.4800.596-0.1271.000-0.811-0.862-0.901-0.826-0.873-0.886
신항1부두0.9440.9400.4990.687-0.000-0.198-0.1520.523-0.8111.0000.9630.9140.8530.9000.939
신항2부두0.9410.9370.4290.707-0.049-0.221-0.2110.484-0.8620.9631.0000.9520.8830.9250.963
신항3부두0.9010.8930.2710.644-0.118-0.247-0.3140.397-0.9010.9140.9521.0000.9020.9360.969
신항4부두0.8410.8400.1760.456-0.214-0.245-0.2990.386-0.8260.8530.8830.9021.0000.9060.891
신항5부두0.8840.8820.3090.495-0.194-0.397-0.3110.247-0.8730.9000.9250.9360.9061.0000.930
다목적부두등0.9210.9100.3150.663-0.063-0.203-0.2950.426-0.8860.9390.9630.9690.8910.9301.000

Missing values

2023-12-12T13:29:02.335865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:29:02.531269image/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

연도전체자성대부두신선대부두감만부두우암부두감천한진신감만부두일반부두(북항-감천)신항1부두신항2부두신항3부두신항4부두신항5부두다목적부두등
01993297563210492449447220000981617000000
1199435749251245793107714900001251789000000
2199541301811403061116949300001557545000000
3199643742461518585121689100001638770000000
419974811377160533113233750298465001584206000000
5199853116601108010109160077292225554330867101774914000000
6199956556948967461056435120332231411936121201823860000000
72000638289911958491076019150635627939115863302013182000000
82001807308912723331319812192259544770443297202677673000000
9200294536891534637152833822615335024605042694812022641250000000
연도전체자성대부두신선대부두감만부두우암부두감천한진신감만부두일반부두(북항-감천)신항1부두신항2부두신항3부두신항4부두신항5부두다목적부두등
2020131768609913665341744861146520651492026410327325982151747307329945723756142391890109936649734
2120141868328714769982190665113600346862257911856086781771712729389520224677412552383130561032731
222015194687251729414201585311323952718323411106355966292420860429622125559662320661126153522604
232016194562931867428195429311718262465188010696505278012418702462643519255452322166154185926242
2420172049347720736952260708128636953811469432754477292689256453130222194022069198194007930782
25201821662573192618224902031287910147662497050432042924777854938446277053520611312269682147666
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272020218239961826714230747815090622321855103342216689527438564837172295426721103182131414201312
2820212270613119828032376489149839401012101670128790527370545086577293907122379032315414226808
29202222078195191786923419091424086051889066125538626841364827307267294822577672433623371986