Overview

Dataset statistics

Number of variables9
Number of observations112
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.9 KiB
Average record size in memory81.2 B

Variable types

Categorical1
Text1
Numeric7

Dataset

Description부산교통공사_도시철도역별수송수입현황_20211231
Author부산교통공사
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3033569

Alerts

승차(명) is highly overall correlated with 승차 일평균(명) and 5 other fieldsHigh correlation
승차 일평균(명) is highly overall correlated with 승차(명) and 5 other fieldsHigh correlation
하차(명) is highly overall correlated with 승차(명) and 5 other fieldsHigh correlation
하차 일평균(명) is highly overall correlated with 승차(명) and 5 other fieldsHigh correlation
승차권(원) is highly overall correlated with 승차(명) and 5 other fieldsHigh correlation
카드승차권(원) is highly overall correlated with 승차(명) and 5 other fieldsHigh correlation
일평균(원) is highly overall correlated with 승차(명) and 5 other fieldsHigh correlation
승차(명) has unique valuesUnique
승차 일평균(명) has unique valuesUnique
하차(명) has unique valuesUnique
하차 일평균(명) has unique valuesUnique
승차권(원) has unique valuesUnique
카드승차권(원) has unique valuesUnique
일평균(원) has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:45:47.380950
Analysis finished2023-12-10 16:45:54.374715
Duration6.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

호선
Categorical

Distinct4
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2
43 
1
40 
3
16 
4
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 43
38.4%
1 40
35.7%
3 16
 
14.3%
4 13
 
11.6%

Length

2023-12-11T01:45:54.453155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:45:54.544252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 43
38.4%
1 40
35.7%
3 16
 
14.3%
4 13
 
11.6%

역명
Text

Distinct108
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-11T01:45:54.840184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length3
Mean length3.5446429
Min length3

Characters and Unicode

Total characters397
Distinct characters133
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)92.9%

Sample

1st row다대포해수욕장역
2nd row다대포항역
3rd row낫개역
4th row신장림역
5th row장림역
ValueCountFrequency (%)
연산역 2
 
1.8%
서면역 2
 
1.8%
덕천역 2
 
1.8%
동래역 2
 
1.8%
고촌역 1
 
0.9%
남양산역 1
 
0.9%
부산대양산캠퍼스역 1
 
0.9%
증산역 1
 
0.9%
호포역 1
 
0.9%
금곡역 1
 
0.9%
Other values (98) 98
87.5%
2023-12-11T01:45:55.269132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
역 112
28.2%
산 19
 
4.8%
대 16
 
4.0%
동 11
 
2.8%
부 9
 
2.3%
장 9
 
2.3%
포 8
 
2.0%
남 7
 
1.8%
서 6
 
1.5%
사 6
 
1.5%
Other values (123) 194
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 396
99.7%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 112
28.3%
산 19
 
4.8%
대 16
 
4.0%
동 11
 
2.8%
부 9
 
2.3%
장 9
 
2.3%
포 8
 
2.0%
남 7
 
1.8%
서 6
 
1.5%
사 6
 
1.5%
Other values (122) 193
48.7%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 396
99.7%
Common 1
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 112
28.3%
산 19
 
4.8%
대 16
 
4.0%
동 11
 
2.8%
부 9
 
2.3%
장 9
 
2.3%
포 8
 
2.0%
남 7
 
1.8%
서 6
 
1.5%
사 6
 
1.5%
Other values (122) 193
48.7%
Common
ValueCountFrequency (%)
· 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 396
99.7%
None 1
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
역 112
28.3%
산 19
 
4.8%
대 16
 
4.0%
동 11
 
2.8%
부 9
 
2.3%
장 9
 
2.3%
포 8
 
2.0%
남 7
 
1.8%
서 6
 
1.5%
사 6
 
1.5%
Other values (122) 193
48.7%
None
ValueCountFrequency (%)
· 1
100.0%

승차(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct112
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2267180.6
Minimum71300
Maximum9865580
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T01:45:55.426027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum71300
5-th percentile557294.2
Q11090586
median1752882
Q32964679.2
95-th percentile5329943.4
Maximum9865580
Range9794280
Interquartile range (IQR)1874093.2

Descriptive statistics

Standard deviation1652661.2
Coefficient of variation (CV)0.72894995
Kurtosis3.2772412
Mean2267180.6
Median Absolute Deviation (MAD)816710.5
Skewness1.5405875
Sum2.5392423 × 108
Variance2.731289 × 1012
MonotonicityNot monotonic
2023-12-11T01:45:55.555382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1556270 1
 
0.9%
2528491 1
 
0.9%
1453888 1
 
0.9%
1861635 1
 
0.9%
1042668 1
 
0.9%
645007 1
 
0.9%
1346543 1
 
0.9%
399892 1
 
0.9%
775891 1
 
0.9%
507230 1
 
0.9%
Other values (102) 102
91.1%
ValueCountFrequency (%)
71300 1
0.9%
207504 1
0.9%
218998 1
0.9%
399892 1
0.9%
507230 1
0.9%
522928 1
0.9%
585412 1
0.9%
638402 1
0.9%
639897 1
0.9%
645007 1
0.9%
ValueCountFrequency (%)
9865580 1
0.9%
6815621 1
0.9%
6038274 1
0.9%
5535387 1
0.9%
5425413 1
0.9%
5398573 1
0.9%
5273792 1
0.9%
5145104 1
0.9%
5078465 1
0.9%
5021969 1
0.9%

승차 일평균(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct112
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6211.4911
Minimum195
Maximum27029
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T01:45:55.677167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum195
5-th percentile1527.05
Q12987.5
median4802.5
Q38122.5
95-th percentile14602.9
Maximum27029
Range26834
Interquartile range (IQR)5135

Descriptive statistics

Standard deviation4527.8291
Coefficient of variation (CV)0.72894399
Kurtosis3.2772531
Mean6211.4911
Median Absolute Deviation (MAD)2238
Skewness1.5405973
Sum695687
Variance20501236
MonotonicityNot monotonic
2023-12-11T01:45:55.814283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4264 1
 
0.9%
6927 1
 
0.9%
3983 1
 
0.9%
5100 1
 
0.9%
2857 1
 
0.9%
1767 1
 
0.9%
3689 1
 
0.9%
1096 1
 
0.9%
2126 1
 
0.9%
1390 1
 
0.9%
Other values (102) 102
91.1%
ValueCountFrequency (%)
195 1
0.9%
569 1
0.9%
600 1
0.9%
1096 1
0.9%
1390 1
0.9%
1433 1
0.9%
1604 1
0.9%
1749 1
0.9%
1753 1
0.9%
1767 1
0.9%
ValueCountFrequency (%)
27029 1
0.9%
18673 1
0.9%
16543 1
0.9%
15165 1
0.9%
14864 1
0.9%
14791 1
0.9%
14449 1
0.9%
14096 1
0.9%
13914 1
0.9%
13759 1
0.9%

하차(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct112
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2260560.3
Minimum54968
Maximum11240735
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T01:45:55.943703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54968
5-th percentile540704.75
Q11057124.8
median1729765.5
Q32906701.5
95-th percentile5482536.2
Maximum11240735
Range11185767
Interquartile range (IQR)1849576.8

Descriptive statistics

Standard deviation1756187.3
Coefficient of variation (CV)0.7768814
Kurtosis5.4601806
Mean2260560.3
Median Absolute Deviation (MAD)777379.5
Skewness1.8781018
Sum2.5318276 × 108
Variance3.0841937 × 1012
MonotonicityNot monotonic
2023-12-11T01:45:56.342173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1276300 1
 
0.9%
2808641 1
 
0.9%
1402682 1
 
0.9%
1857036 1
 
0.9%
1016297 1
 
0.9%
602537 1
 
0.9%
1448972 1
 
0.9%
511497 1
 
0.9%
640485 1
 
0.9%
415125 1
 
0.9%
Other values (102) 102
91.1%
ValueCountFrequency (%)
54968 1
0.9%
163002 1
0.9%
203806 1
0.9%
415125 1
0.9%
511497 1
0.9%
531770 1
0.9%
548015 1
0.9%
602537 1
0.9%
612164 1
0.9%
627500 1
0.9%
ValueCountFrequency (%)
11240735 1
0.9%
7300816 1
0.9%
6220246 1
0.9%
5573582 1
0.9%
5537313 1
0.9%
5490586 1
0.9%
5475950 1
0.9%
5262697 1
0.9%
5228972 1
0.9%
5138567 1
0.9%

하차 일평균(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct112
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6193.3393
Minimum151
Maximum30797
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T01:45:56.555838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum151
5-th percentile1481.2
Q12896.5
median4739
Q37964
95-th percentile15021
Maximum30797
Range30646
Interquartile range (IQR)5067.5

Descriptive statistics

Standard deviation4811.5224
Coefficient of variation (CV)0.77688661
Kurtosis5.4603012
Mean6193.3393
Median Absolute Deviation (MAD)2129.5
Skewness1.8781132
Sum693654
Variance23150748
MonotonicityNot monotonic
2023-12-11T01:45:56.693297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3497 1
 
0.9%
7695 1
 
0.9%
3843 1
 
0.9%
5088 1
 
0.9%
2784 1
 
0.9%
1651 1
 
0.9%
3970 1
 
0.9%
1401 1
 
0.9%
1755 1
 
0.9%
1137 1
 
0.9%
Other values (102) 102
91.1%
ValueCountFrequency (%)
151 1
0.9%
447 1
0.9%
558 1
0.9%
1137 1
0.9%
1401 1
0.9%
1457 1
0.9%
1501 1
0.9%
1651 1
0.9%
1677 1
0.9%
1719 1
0.9%
ValueCountFrequency (%)
30797 1
0.9%
20002 1
0.9%
17042 1
0.9%
15270 1
0.9%
15171 1
0.9%
15043 1
0.9%
15003 1
0.9%
14418 1
0.9%
14326 1
0.9%
14078 1
0.9%

승차권(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct112
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74942869
Minimum1333050
Maximum2.7034023 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T01:45:56.862962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1333050
5-th percentile12144058
Q135453912
median62145615
Q31.0670759 × 108
95-th percentile1.8275339 × 108
Maximum2.7034023 × 108
Range2.6900718 × 108
Interquartile range (IQR)71253680

Descriptive statistics

Standard deviation55245408
Coefficient of variation (CV)0.73716698
Kurtosis1.5960266
Mean74942869
Median Absolute Deviation (MAD)31042130
Skewness1.2572678
Sum8.3936013 × 109
Variance3.0520552 × 1015
MonotonicityNot monotonic
2023-12-11T01:45:57.031587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36035410 1
 
0.9%
216357450 1
 
0.9%
40810650 1
 
0.9%
101608000 1
 
0.9%
77935740 1
 
0.9%
35707100 1
 
0.9%
67513850 1
 
0.9%
12827510 1
 
0.9%
29751900 1
 
0.9%
19405350 1
 
0.9%
Other values (102) 102
91.1%
ValueCountFrequency (%)
1333050 1
0.9%
3902100 1
0.9%
5292210 1
0.9%
5466200 1
0.9%
9424400 1
0.9%
11818100 1
0.9%
12410750 1
0.9%
12648500 1
0.9%
12827510 1
0.9%
14066630 1
0.9%
ValueCountFrequency (%)
270340230 1
0.9%
241770730 1
0.9%
238613400 1
0.9%
216357450 1
0.9%
208810350 1
0.9%
194378670 1
0.9%
173241800 1
0.9%
170372350 1
0.9%
147019750 1
0.9%
146111720 1
0.9%

카드승차권(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct112
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.664669 × 109
Minimum30305984
Maximum8.1127078 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T01:45:57.232373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30305984
5-th percentile2.6214399 × 108
Q17.2861145 × 108
median1.2923565 × 109
Q32.326301 × 109
95-th percentile4.1412586 × 109
Maximum8.1127078 × 109
Range8.0824018 × 109
Interquartile range (IQR)1.5976895 × 109

Descriptive statistics

Standard deviation1.3547231 × 109
Coefficient of variation (CV)0.81380927
Kurtosis4.463814
Mean1.664669 × 109
Median Absolute Deviation (MAD)6.7953408 × 108
Skewness1.7785565
Sum1.8644293 × 1011
Variance1.8352747 × 1018
MonotonicityNot monotonic
2023-12-11T01:45:57.440368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
902300798 1
 
0.9%
2695046653 1
 
0.9%
848654753 1
 
0.9%
1472013112 1
 
0.9%
937859677 1
 
0.9%
555059887 1
 
0.9%
1160936113 1
 
0.9%
216093554 1
 
0.9%
451574229 1
 
0.9%
290270433 1
 
0.9%
Other values (102) 102
91.1%
ValueCountFrequency (%)
30305984 1
0.9%
80026955 1
0.9%
148302500 1
0.9%
213993079 1
0.9%
216093554 1
0.9%
244843598 1
0.9%
276298861 1
0.9%
290270433 1
0.9%
337898224 1
0.9%
346900985 1
0.9%
ValueCountFrequency (%)
8112707757 1
0.9%
5846863122 1
0.9%
5135213053 1
0.9%
4911105007 1
0.9%
4906631574 1
0.9%
4176527396 1
0.9%
4112402401 1
0.9%
3882658250 1
0.9%
3706006126 1
0.9%
3649066360 1
0.9%

일평균(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct112
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4766060.1
Minimum86682
Maximum22967255
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T01:45:57.613537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum86682
5-th percentile751474.1
Q12090303
median3650749
Q36791083.2
95-th percentile11860077
Maximum22967255
Range22880573
Interquartile range (IQR)4700780.2

Descriptive statistics

Standard deviation3842208.2
Coefficient of variation (CV)0.80616027
Kurtosis4.3196077
Mean4766060.1
Median Absolute Deviation (MAD)1832324.5
Skewness1.7487912
Sum5.3379873 × 108
Variance1.4762564 × 1013
MonotonicityNot monotonic
2023-12-11T01:45:57.758206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2570784 1
 
0.9%
7976450 1
 
0.9%
2436892 1
 
0.9%
4311291 1
 
0.9%
2783001 1
 
0.9%
1618540 1
 
0.9%
3365616 1
 
0.9%
627181 1
 
0.9%
1318702 1
 
0.9%
848427 1
 
0.9%
Other values (102) 102
91.1%
ValueCountFrequency (%)
86682 1
0.9%
229943 1
0.9%
421284 1
0.9%
600782 1
0.9%
627181 1
0.9%
703183 1
0.9%
790985 1
0.9%
848427 1
0.9%
976234 1
0.9%
976723 1
0.9%
ValueCountFrequency (%)
22967255 1
0.9%
16421597 1
0.9%
14421978 1
0.9%
14117468 1
0.9%
13975371 1
0.9%
12014624 1
0.9%
11733629 1
0.9%
11010043 1
0.9%
10628077 1
0.9%
10345206 1
0.9%

Interactions

2023-12-11T01:45:53.333553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:47.815553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:48.747990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:49.920211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:50.748627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:51.586995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:52.448049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:53.445324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:47.934735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:48.873941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:50.025869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:50.864973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:51.691074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:52.596396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:53.576400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:48.054245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:49.317457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:50.129887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:50.967641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:51.784092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:52.735437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:53.711288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:48.170499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:49.434042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:50.240950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:51.109799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:51.915398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:52.851671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:53.821033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:48.294945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:49.555477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:50.364956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:51.238449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:52.046621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:52.975280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:53.921160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:48.466662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:49.703940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:50.488410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:51.357111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:52.170119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:53.075487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:54.041281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:48.611149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:49.826304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:50.638998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:51.477396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:52.324729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:45:53.202744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:45:57.906854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호선승차(명)승차 일평균(명)하차(명)하차 일평균(명)승차권(원)카드승차권(원)일평균(원)
호선1.0000.6810.6810.5740.5740.5800.4650.465
승차(명)0.6811.0001.0000.9820.9820.8070.8930.893
승차 일평균(명)0.6811.0001.0000.9820.9820.8070.8930.893
하차(명)0.5740.9820.9821.0001.0000.8170.9150.915
하차 일평균(명)0.5740.9820.9821.0001.0000.8170.9150.915
승차권(원)0.5800.8070.8070.8170.8171.0000.8250.825
카드승차권(원)0.4650.8930.8930.9150.9150.8251.0001.000
일평균(원)0.4650.8930.8930.9150.9150.8251.0001.000
2023-12-11T01:45:58.081168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
승차(명)승차 일평균(명)하차(명)하차 일평균(명)승차권(원)카드승차권(원)일평균(원)호선
승차(명)1.0001.0000.9910.9910.8630.9770.9760.363
승차 일평균(명)1.0001.0000.9910.9910.8630.9770.9760.363
하차(명)0.9910.9911.0001.0000.8670.9730.9720.289
하차 일평균(명)0.9910.9911.0001.0000.8670.9730.9720.289
승차권(원)0.8630.8630.8670.8671.0000.8960.9020.387
카드승차권(원)0.9770.9770.9730.9730.8961.0001.0000.316
일평균(원)0.9760.9760.9720.9720.9021.0001.0000.316
호선0.3630.3630.2890.2890.3870.3160.3161.000

Missing values

2023-12-11T01:45:54.173044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:45:54.319605image/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

호선역명승차(명)승차 일평균(명)하차(명)하차 일평균(명)승차권(원)카드승차권(원)일평균(원)
01다대포해수욕장역1556270426412763003497360354109023007982570784
11다대포항역1058643290012122663321390940007142427222063936
21낫개역14979384104154137642236412468010318495203002669
31신장림역101366727779426782583427426407134640802071799
41장림역104157428549620942636355070007786858142230665
51동매역1265656346811350643110343378109152100302601501
61신평역20482845612208119057026960571015048216224313500
71하단역553538715165507885013915136007560388265825011010043
81당리역19353735302205402456275569094012285183343518382
91사하역1361333373012084513311471864309316996702681880
호선역명승차(명)승차 일평균(명)하차(명)하차 일평균(명)승차권(원)카드승차권(원)일평균(원)
1024충렬사역968342265310019662745166354003911156731117126
1034명장역95745426239250922534229228004824914851384697
1044서동역7220781978756928207418605550337898224976723
1054금사역585412160453177014579424400346900985976234
1064반여농산물시장역671970184169223018975292210213993079600782
1074석대역713001955496815113330503030598486682
1084영산대역88278024198677032377510780005828373231736754
1094동부산대학역81130422237655332097285116004437820361293955
1104고촌역207504569163002447390210080026955229943
1114안평역6398971753627500171912410750276298861790985