Overview

Dataset statistics

Number of variables8
Number of observations6451
Missing cells3328
Missing cells (%)6.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory447.4 KiB
Average record size in memory71.0 B

Variable types

Text1
Numeric7

Dataset

Description인천광역시 시내버스 정류장별 이용승객 현황으로 <br/>정류소명, 정류소아이디, 승차건수, 하차건수 등을 제공합니다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15048264&srcSe=7661IVAWM27C61E190

Alerts

총승차건수 is highly overall correlated with 총하차건수 and 4 other fieldsHigh correlation
총하차건수 is highly overall correlated with 총승차건수 and 4 other fieldsHigh correlation
승차건수(카드) is highly overall correlated with 총승차건수 and 4 other fieldsHigh correlation
하차건수(카드) is highly overall correlated with 총승차건수 and 4 other fieldsHigh correlation
승차건수(현금) is highly overall correlated with 총승차건수 and 4 other fieldsHigh correlation
일평균승하차건수 is highly overall correlated with 총승차건수 and 4 other fieldsHigh correlation
총승차건수 has 169 (2.6%) missing valuesMissing
총하차건수 has 160 (2.5%) missing valuesMissing
승차건수(카드) has 183 (2.8%) missing valuesMissing
하차건수(카드) has 160 (2.5%) missing valuesMissing
승차건수(현금) has 2656 (41.2%) missing valuesMissing
일평균승하차건수 has 514 (8.0%) zerosZeros

Reproduction

Analysis started2024-04-06 09:44:12.776981
Analysis finished2024-04-06 09:44:21.114848
Duration8.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

정류소명
Text

Distinct3757
Distinct (%)58.2%
Missing0
Missing (%)0.0%
Memory size50.5 KiB
2024-04-06T18:44:21.355464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length6.6595877
Min length2

Characters and Unicode

Total characters42961
Distinct characters628
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1532 ?
Unique (%)23.7%

Sample

1st row(구)국제여객터미널
2nd row(구)국제여객터미널
3rd row(구)시민회관사거리
4th row(구)시민회관사거리
5th row(주)경동세라믹스
ValueCountFrequency (%)
대동아파트 13
 
0.2%
현대아파트 12
 
0.2%
부대앞 11
 
0.2%
한국아파트 11
 
0.2%
입구 10
 
0.2%
쌍용아파트 9
 
0.1%
광명아파트 9
 
0.1%
풍림아파트 8
 
0.1%
신동아아파트 8
 
0.1%
뉴서울아파트 8
 
0.1%
Other values (3753) 6393
98.5%
2024-04-06T18:44:21.913066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 1104
 
2.6%
트 1059
 
2.5%
파 942
 
2.2%
리 882
 
2.1%
교 882
 
2.1%
동 830
 
1.9%
지 820
 
1.9%
구 803
 
1.9%
학 691
 
1.6%
마 535
 
1.2%
Other values (618) 34413
80.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39921
92.9%
Decimal Number 1270
 
3.0%
Close Punctuation 515
 
1.2%
Open Punctuation 515
 
1.2%
Uppercase Letter 327
 
0.8%
Other Punctuation 319
 
0.7%
Space Separator 51
 
0.1%
Lowercase Letter 37
 
0.1%
Dash Punctuation 5
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 1104
 
2.8%
트 1059
 
2.7%
파 942
 
2.4%
리 882
 
2.2%
교 882
 
2.2%
동 830
 
2.1%
지 820
 
2.1%
구 803
 
2.0%
학 691
 
1.7%
마 535
 
1.3%
Other values (568) 31373
78.6%
Uppercase Letter
ValueCountFrequency (%)
K 42
12.8%
S 40
12.2%
T 40
12.2%
C 31
9.5%
L 29
8.9%
G 27
8.3%
H 25
7.6%
A 17
 
5.2%
I 15
 
4.6%
B 14
 
4.3%
Other values (12) 47
14.4%
Decimal Number
ValueCountFrequency (%)
1 397
31.3%
2 296
23.3%
3 167
13.1%
0 100
 
7.9%
4 87
 
6.9%
5 73
 
5.7%
6 49
 
3.9%
7 45
 
3.5%
9 30
 
2.4%
8 26
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
e 24
64.9%
s 4
 
10.8%
k 2
 
5.4%
f 1
 
2.7%
y 1
 
2.7%
t 1
 
2.7%
n 1
 
2.7%
i 1
 
2.7%
m 1
 
2.7%
g 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 275
86.2%
· 42
 
13.2%
, 2
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 515
100.0%
Open Punctuation
ValueCountFrequency (%)
( 515
100.0%
Space Separator
ValueCountFrequency (%)
51
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39921
92.9%
Common 2676
 
6.2%
Latin 364
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 1104
 
2.8%
트 1059
 
2.7%
파 942
 
2.4%
리 882
 
2.2%
교 882
 
2.2%
동 830
 
2.1%
지 820
 
2.1%
구 803
 
2.0%
학 691
 
1.7%
마 535
 
1.3%
Other values (568) 31373
78.6%
Latin
ValueCountFrequency (%)
K 42
11.5%
S 40
11.0%
T 40
11.0%
C 31
8.5%
L 29
 
8.0%
G 27
 
7.4%
H 25
 
6.9%
e 24
 
6.6%
A 17
 
4.7%
I 15
 
4.1%
Other values (22) 74
20.3%
Common
ValueCountFrequency (%)
) 515
19.2%
( 515
19.2%
1 397
14.8%
2 296
11.1%
. 275
10.3%
3 167
 
6.2%
0 100
 
3.7%
4 87
 
3.3%
5 73
 
2.7%
51
 
1.9%
Other values (8) 200
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39921
92.9%
ASCII 2998
 
7.0%
None 42
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 1104
 
2.8%
트 1059
 
2.7%
파 942
 
2.4%
리 882
 
2.2%
교 882
 
2.2%
동 830
 
2.1%
지 820
 
2.1%
구 803
 
2.0%
학 691
 
1.7%
마 535
 
1.3%
Other values (568) 31373
78.6%
ASCII
ValueCountFrequency (%)
) 515
17.2%
( 515
17.2%
1 397
13.2%
2 296
9.9%
. 275
9.2%
3 167
 
5.6%
0 100
 
3.3%
4 87
 
2.9%
5 73
 
2.4%
51
 
1.7%
Other values (39) 522
17.4%
None
ValueCountFrequency (%)
· 42
100.0%

정류소아이디
Real number (ℝ)

Distinct6438
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46978.475
Minimum11002
Maximum92076
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size56.8 KiB
2024-04-06T18:44:22.096365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11002
5-th percentile35302.5
Q138349.5
median40830
Q343518.5
95-th percentile90093.5
Maximum92076
Range81074
Interquartile range (IQR)5169

Descriptive statistics

Standard deviation17434.943
Coefficient of variation (CV)0.37112621
Kurtosis1.8423011
Mean46978.475
Median Absolute Deviation (MAD)2606
Skewness1.8234066
Sum3.0305814 × 108
Variance3.0397725 × 108
MonotonicityNot monotonic
2024-04-06T18:44:22.239705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35761 2
 
< 0.1%
35396 2
 
< 0.1%
35147 2
 
< 0.1%
35610 2
 
< 0.1%
35073 2
 
< 0.1%
35097 2
 
< 0.1%
35219 2
 
< 0.1%
35214 2
 
< 0.1%
35074 2
 
< 0.1%
35246 2
 
< 0.1%
Other values (6428) 6431
99.7%
ValueCountFrequency (%)
11002 1
< 0.1%
11013 1
< 0.1%
11014 1
< 0.1%
11015 1
< 0.1%
11020 1
< 0.1%
11021 1
< 0.1%
11187 1
< 0.1%
14001 1
< 0.1%
14002 1
< 0.1%
14149 1
< 0.1%
ValueCountFrequency (%)
92076 1
< 0.1%
92075 1
< 0.1%
92074 1
< 0.1%
92071 1
< 0.1%
92070 1
< 0.1%
92069 1
< 0.1%
92068 1
< 0.1%
92067 1
< 0.1%
92066 1
< 0.1%
92065 1
< 0.1%

총승차건수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3415
Distinct (%)54.4%
Missing169
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean3720.2813
Minimum1
Maximum166865
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size56.8 KiB
2024-04-06T18:44:22.427721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q173.25
median875.5
Q33908.5
95-th percentile15207.4
Maximum166865
Range166864
Interquartile range (IQR)3835.25

Descriptive statistics

Standard deviation8666.774
Coefficient of variation (CV)2.3296018
Kurtosis98.062929
Mean3720.2813
Median Absolute Deviation (MAD)863.5
Skewness7.7703155
Sum23370807
Variance75112971
MonotonicityNot monotonic
2024-04-06T18:44:22.604378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 99
 
1.5%
3 72
 
1.1%
2 67
 
1.0%
4 63
 
1.0%
5 51
 
0.8%
12 48
 
0.7%
6 46
 
0.7%
15 45
 
0.7%
8 44
 
0.7%
22 43
 
0.7%
Other values (3405) 5704
88.4%
(Missing) 169
 
2.6%
ValueCountFrequency (%)
1 99
1.5%
2 67
1.0%
3 72
1.1%
4 63
1.0%
5 51
0.8%
6 46
0.7%
7 33
 
0.5%
8 44
0.7%
9 41
0.6%
10 38
 
0.6%
ValueCountFrequency (%)
166865 1
< 0.1%
165753 1
< 0.1%
158398 1
< 0.1%
143214 1
< 0.1%
131019 1
< 0.1%
107944 1
< 0.1%
103692 1
< 0.1%
101955 1
< 0.1%
91436 1
< 0.1%
91210 1
< 0.1%

총하차건수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3493
Distinct (%)55.5%
Missing160
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean3532.9638
Minimum1
Maximum156090
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size56.8 KiB
2024-04-06T18:44:22.831033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q190
median1012
Q33794
95-th percentile14342
Maximum156090
Range156089
Interquartile range (IQR)3704

Descriptive statistics

Standard deviation7804.6121
Coefficient of variation (CV)2.2090836
Kurtosis83.352485
Mean3532.9638
Median Absolute Deviation (MAD)994
Skewness7.1892962
Sum22225875
Variance60911971
MonotonicityNot monotonic
2024-04-06T18:44:23.027650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 89
 
1.4%
2 68
 
1.1%
3 62
 
1.0%
5 55
 
0.9%
4 43
 
0.7%
10 42
 
0.7%
8 42
 
0.7%
9 39
 
0.6%
6 37
 
0.6%
12 35
 
0.5%
Other values (3483) 5779
89.6%
(Missing) 160
 
2.5%
ValueCountFrequency (%)
1 89
1.4%
2 68
1.1%
3 62
1.0%
4 43
0.7%
5 55
0.9%
6 37
0.6%
7 31
 
0.5%
8 42
0.7%
9 39
0.6%
10 42
0.7%
ValueCountFrequency (%)
156090 1
< 0.1%
135085 1
< 0.1%
121709 1
< 0.1%
115546 1
< 0.1%
110231 1
< 0.1%
107576 1
< 0.1%
90560 1
< 0.1%
86908 1
< 0.1%
77374 1
< 0.1%
76558 1
< 0.1%

승차건수(카드)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3385
Distinct (%)54.0%
Missing183
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean3710.1878
Minimum1
Maximum166349
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size56.8 KiB
2024-04-06T18:44:23.256776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q171
median874
Q33903
95-th percentile15110.25
Maximum166349
Range166348
Interquartile range (IQR)3832

Descriptive statistics

Standard deviation8645.5693
Coefficient of variation (CV)2.3302242
Kurtosis98.304709
Mean3710.1878
Median Absolute Deviation (MAD)862
Skewness7.7803509
Sum23255457
Variance74745869
MonotonicityNot monotonic
2024-04-06T18:44:23.400432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 103
 
1.6%
3 78
 
1.2%
2 78
 
1.2%
4 58
 
0.9%
5 49
 
0.8%
6 48
 
0.7%
12 46
 
0.7%
15 45
 
0.7%
14 43
 
0.7%
10 42
 
0.7%
Other values (3375) 5678
88.0%
(Missing) 183
 
2.8%
ValueCountFrequency (%)
1 103
1.6%
2 78
1.2%
3 78
1.2%
4 58
0.9%
5 49
0.8%
6 48
0.7%
7 41
 
0.6%
8 41
 
0.6%
9 38
 
0.6%
10 42
0.7%
ValueCountFrequency (%)
166349 1
< 0.1%
165634 1
< 0.1%
157869 1
< 0.1%
143214 1
< 0.1%
130546 1
< 0.1%
107592 1
< 0.1%
103240 1
< 0.1%
101781 1
< 0.1%
91356 1
< 0.1%
91014 1
< 0.1%

하차건수(카드)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3493
Distinct (%)55.5%
Missing160
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean3532.9638
Minimum1
Maximum156090
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size56.8 KiB
2024-04-06T18:44:23.531606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q190
median1012
Q33794
95-th percentile14342
Maximum156090
Range156089
Interquartile range (IQR)3704

Descriptive statistics

Standard deviation7804.6121
Coefficient of variation (CV)2.2090836
Kurtosis83.352485
Mean3532.9638
Median Absolute Deviation (MAD)994
Skewness7.1892962
Sum22225875
Variance60911971
MonotonicityNot monotonic
2024-04-06T18:44:23.693367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 89
 
1.4%
2 68
 
1.1%
3 62
 
1.0%
5 55
 
0.9%
4 43
 
0.7%
10 42
 
0.7%
8 42
 
0.7%
9 39
 
0.6%
6 37
 
0.6%
12 35
 
0.5%
Other values (3483) 5779
89.6%
(Missing) 160
 
2.5%
ValueCountFrequency (%)
1 89
1.4%
2 68
1.1%
3 62
1.0%
4 43
0.7%
5 55
0.9%
6 37
0.6%
7 31
 
0.5%
8 42
0.7%
9 39
0.6%
10 42
0.7%
ValueCountFrequency (%)
156090 1
< 0.1%
135085 1
< 0.1%
121709 1
< 0.1%
115546 1
< 0.1%
110231 1
< 0.1%
107576 1
< 0.1%
90560 1
< 0.1%
86908 1
< 0.1%
77374 1
< 0.1%
76558 1
< 0.1%

승차건수(현금)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct229
Distinct (%)6.0%
Missing2656
Missing (%)41.2%
Infinite0
Infinite (%)0.0%
Mean30.395257
Minimum1
Maximum1881
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size56.8 KiB
2024-04-06T18:44:23.836115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median11
Q333
95-th percentile119.3
Maximum1881
Range1880
Interquartile range (IQR)29

Descriptive statistics

Standard deviation60.611415
Coefficient of variation (CV)1.9941077
Kurtosis249.50121
Mean30.395257
Median Absolute Deviation (MAD)9
Skewness10.738585
Sum115350
Variance3673.7436
MonotonicityNot monotonic
2024-04-06T18:44:23.971267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 349
 
5.4%
2 309
 
4.8%
3 231
 
3.6%
4 195
 
3.0%
6 158
 
2.4%
5 130
 
2.0%
7 125
 
1.9%
8 110
 
1.7%
9 106
 
1.6%
11 101
 
1.6%
Other values (219) 1981
30.7%
(Missing) 2656
41.2%
ValueCountFrequency (%)
1 349
5.4%
2 309
4.8%
3 231
3.6%
4 195
3.0%
5 130
 
2.0%
6 158
2.4%
7 125
 
1.9%
8 110
 
1.7%
9 106
 
1.6%
10 95
 
1.5%
ValueCountFrequency (%)
1881 1
< 0.1%
691 1
< 0.1%
647 1
< 0.1%
625 1
< 0.1%
601 1
< 0.1%
573 1
< 0.1%
529 1
< 0.1%
516 1
< 0.1%
473 1
< 0.1%
463 2
< 0.1%

일평균승하차건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1050
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean235.13223
Minimum0
Maximum10765
Zeros514
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size56.8 KiB
2024-04-06T18:44:24.129701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median74
Q3262
95-th percentile946
Maximum10765
Range10765
Interquartile range (IQR)255

Descriptive statistics

Standard deviation513.20351
Coefficient of variation (CV)2.1826166
Kurtosis95.904369
Mean235.13223
Median Absolute Deviation (MAD)73
Skewness7.6311013
Sum1516838
Variance263377.84
MonotonicityNot monotonic
2024-04-06T18:44:24.280320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 514
 
8.0%
1 377
 
5.8%
2 248
 
3.8%
3 154
 
2.4%
4 117
 
1.8%
5 95
 
1.5%
6 84
 
1.3%
7 73
 
1.1%
10 60
 
0.9%
9 56
 
0.9%
Other values (1040) 4673
72.4%
ValueCountFrequency (%)
0 514
8.0%
1 377
5.8%
2 248
3.8%
3 154
 
2.4%
4 117
 
1.8%
5 95
 
1.5%
6 84
 
1.3%
7 73
 
1.1%
8 51
 
0.8%
9 56
 
0.9%
ValueCountFrequency (%)
10765 1
< 0.1%
9131 1
< 0.1%
8830 1
< 0.1%
8041 1
< 0.1%
7798 1
< 0.1%
6656 1
< 0.1%
6495 1
< 0.1%
5852 1
< 0.1%
5536 1
< 0.1%
5371 1
< 0.1%

Interactions

2024-04-06T18:44:19.799727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:14.255435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:15.228266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:16.009533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:16.916308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:17.872122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:18.700297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:19.907732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:14.442023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:15.343336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:16.121693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:17.042250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:17.998906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:19.104822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:20.034590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:14.571254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:15.451711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:16.230968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:17.179137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:18.111631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:19.250488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:20.178967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:14.689041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:15.561752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:16.349591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:17.321541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:18.222800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:19.372915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:20.305268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:14.807897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:15.665578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:16.466930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:17.457497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:18.360175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:19.473331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:20.443854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:14.964328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:15.778648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:16.597018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:17.605038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:18.494568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:19.579420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:20.574897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:15.106406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:15.903343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:16.763680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:17.750681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:18.600475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:44:19.697901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T18:44:24.663484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정류소아이디총승차건수총하차건수승차건수(카드)하차건수(카드)승차건수(현금)일평균승하차건수
정류소아이디1.0000.0930.1280.0930.1280.0480.098
총승차건수0.0931.0000.8901.0000.8900.5560.951
총하차건수0.1280.8901.0000.8901.0000.6810.967
승차건수(카드)0.0931.0000.8901.0000.8900.5560.951
하차건수(카드)0.1280.8901.0000.8901.0000.6810.967
승차건수(현금)0.0480.5560.6810.5560.6811.0000.697
일평균승하차건수0.0980.9510.9670.9510.9670.6971.000
2024-04-06T18:44:24.794834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정류소아이디총승차건수총하차건수승차건수(카드)하차건수(카드)승차건수(현금)일평균승하차건수
정류소아이디1.000-0.368-0.372-0.367-0.372-0.269-0.420
총승차건수-0.3681.0000.7670.9990.7670.7010.932
총하차건수-0.3720.7671.0000.7651.0000.5540.931
승차건수(카드)-0.3670.9990.7651.0000.7650.6910.931
하차건수(카드)-0.3720.7671.0000.7651.0000.5540.931
승차건수(현금)-0.2690.7010.5540.6910.5541.0000.668
일평균승하차건수-0.4200.9320.9310.9310.9310.6681.000

Missing values

2024-04-06T18:44:20.731241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T18:44:20.862721image/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.
2024-04-06T18:44:21.020244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

정류소명정류소아이디총승차건수총하차건수승차건수(카드)하차건수(카드)승차건수(현금)일평균승하차건수
0(구)국제여객터미널350513313871013872347
1(구)국제여객터미널350521755341720343559
2(구)시민회관사거리37319471942526470542526141574
3(구)시민회관사거리37326912101892791014189271963671
4(주)경동세라믹스891464313842538615
5(주)경인양행앞42096985836985836<NA>60
6(주)경인양행앞420971678361016783610<NA>176
7(주)대한특수금속39050108183108183<NA>38
8(주)두남391351795317953<NA>7
9(주)세모입구(린나이코리아)375851458180414581804<NA>108
정류소명정류소아이디총승차건수총하차건수승차건수(카드)하차건수(카드)승차건수(현금)일평균승하차건수
6441힐스테이트푸르지오주안373001381215365137331536579972
6442힐스테이트푸르지오주안아파트37680758676817572768114508
6443힐스테이트학익37022549548215428482167343
6444힐스테이트학익3702344827702447477028406
6445힐스테이트학익104동앞37669135218981339189813108
6446힐스테이트학익104동앞3767022234995222249951240
6447힐캐슬프라자393291105916016109961601663902
6448힐캐슬프라자39331171679487170599487108888
6449힘찬병원40891545974825431748228431
6450힘찬병원40892428629914261299125242