Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells26835
Missing cells (%)33.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory771.5 KiB
Average record size in memory79.0 B

Variable types

Numeric7
Text1

Dataset

Description기준_날짜,목적통행_패턴,총_승객수,총_승객수_일반,총_승객수_어린이,총_승객수_청소년,총_승객수_경로,총_승객수_장애인
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21216/S/1/datasetView.do

Alerts

총_승객수 is highly overall correlated with 총_승객수_일반 and 4 other fieldsHigh correlation
총_승객수_일반 is highly overall correlated with 총_승객수 and 4 other fieldsHigh correlation
총_승객수_어린이 is highly overall correlated with 총_승객수 and 4 other fieldsHigh correlation
총_승객수_청소년 is highly overall correlated with 총_승객수 and 4 other fieldsHigh correlation
총_승객수_경로 is highly overall correlated with 총_승객수 and 4 other fieldsHigh correlation
총_승객수_장애인 is highly overall correlated with 총_승객수 and 4 other fieldsHigh correlation
총_승객수_어린이 has 5576 (55.8%) missing valuesMissing
총_승객수_청소년 has 3976 (39.8%) missing valuesMissing
총_승객수_경로 has 8518 (85.2%) missing valuesMissing
총_승객수_장애인 has 8698 (87.0%) missing valuesMissing

Reproduction

Analysis started2024-04-06 13:11:01.206964
Analysis finished2024-04-06 13:11:12.710908
Duration11.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준_날짜
Real number (ℝ)

Distinct477
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20232245
Minimum20221208
Maximum20240401
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T22:11:12.832275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20221208
5-th percentile20230103
Q120230417
median20230821
Q320231213
95-th percentile20240311
Maximum20240401
Range19193
Interquartile range (IQR)796

Descriptive statistics

Standard deviation4553.154
Coefficient of variation (CV)0.00022504443
Kurtosis0.55253883
Mean20232245
Median Absolute Deviation (MAD)397
Skewness0.43937607
Sum2.0232245 × 1011
Variance20731211
MonotonicityNot monotonic
2024-04-06T22:11:13.123775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20231117 35
 
0.4%
20240315 34
 
0.3%
20230912 34
 
0.3%
20230817 33
 
0.3%
20231226 33
 
0.3%
20240213 32
 
0.3%
20230623 31
 
0.3%
20231126 31
 
0.3%
20240318 31
 
0.3%
20240106 31
 
0.3%
Other values (467) 9675
96.8%
ValueCountFrequency (%)
20221208 6
 
0.1%
20221209 30
0.3%
20221210 20
0.2%
20221211 13
0.1%
20221212 21
0.2%
20221213 23
0.2%
20221214 18
0.2%
20221215 21
0.2%
20221216 30
0.3%
20221217 24
0.2%
ValueCountFrequency (%)
20240401 27
0.3%
20240331 19
0.2%
20240330 15
0.1%
20240329 19
0.2%
20240328 30
0.3%
20240327 17
0.2%
20240326 25
0.2%
20240325 16
0.2%
20240324 20
0.2%
20240323 28
0.3%
Distinct240
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T22:11:13.347222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length42
Mean length36.5346
Min length5

Characters and Unicode

Total characters365346
Distinct characters16
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row①[지하철] → ②[버스] → ③[경기버스] → ④[지하철]
2nd row①[지하철] → ②[지하철] → ③[버스]
3rd row①[버스] → ②[지하철] → ③[경기버스] → ④[지하철]
4th row①[버스] → ②[지하철] → ③[경기버스] → ④[지하철] → ⑤[지하철]
5th row①[지하철] → ②[버스] → ③[지하철] → ④[경기버스] → ⑤[버스]
ValueCountFrequency (%)
34550
43.7%
④[버스 3663
 
4.6%
③[버스 3640
 
4.6%
②[버스 3583
 
4.5%
①[버스 3475
 
4.4%
②[경기버스 3420
 
4.3%
⑤[버스 3414
 
4.3%
①[경기버스 3412
 
4.3%
①[지하철 3113
 
3.9%
③[경기버스 3058
 
3.9%
Other values (5) 13772
 
17.4%
2024-04-06T22:11:13.727405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
69100
18.9%
[ 44550
12.2%
] 44550
12.2%
34550
9.5%
29946
8.2%
29946
8.2%
14604
 
4.0%
14604
 
4.0%
14604
 
4.0%
12171
 
3.3%
Other values (6) 56721
15.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 128046
35.0%
Space Separator 69100
18.9%
Open Punctuation 44550
 
12.2%
Close Punctuation 44550
 
12.2%
Other Number 44550
 
12.2%
Math Symbol 34550
 
9.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
29946
23.4%
29946
23.4%
14604
11.4%
14604
11.4%
14604
11.4%
12171
9.5%
12171
9.5%
Other Number
ValueCountFrequency (%)
10000
22.4%
9907
22.2%
9621
21.6%
8757
19.7%
6265
14.1%
Space Separator
ValueCountFrequency (%)
69100
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 44550
100.0%
Close Punctuation
ValueCountFrequency (%)
] 44550
100.0%
Math Symbol
ValueCountFrequency (%)
34550
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 237300
65.0%
Hangul 128046
35.0%

Most frequent character per script

Common
ValueCountFrequency (%)
69100
29.1%
[ 44550
18.8%
] 44550
18.8%
34550
14.6%
10000
 
4.2%
9907
 
4.2%
9621
 
4.1%
8757
 
3.7%
6265
 
2.6%
Hangul
ValueCountFrequency (%)
29946
23.4%
29946
23.4%
14604
11.4%
14604
11.4%
14604
11.4%
12171
9.5%
12171
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 158200
43.3%
Hangul 128046
35.0%
Enclosed Alphanum 44550
 
12.2%
Arrows 34550
 
9.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
69100
43.7%
[ 44550
28.2%
] 44550
28.2%
Arrows
ValueCountFrequency (%)
34550
100.0%
Hangul
ValueCountFrequency (%)
29946
23.4%
29946
23.4%
14604
11.4%
14604
11.4%
14604
11.4%
12171
9.5%
12171
9.5%
Enclosed Alphanum
ValueCountFrequency (%)
10000
22.4%
9907
22.2%
9621
21.6%
8757
19.7%
6265
14.1%

총_승객수
Real number (ℝ)

HIGH CORRELATION 

Distinct2052
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39343.241
Minimum1
Maximum5292943
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T22:11:13.945291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17
median27
Q3196
95-th percentile17633.25
Maximum5292943
Range5292942
Interquartile range (IQR)189

Descriptive statistics

Standard deviation341193.91
Coefficient of variation (CV)8.672237
Kurtosis152.92815
Mean39343.241
Median Absolute Deviation (MAD)25
Skewness11.885048
Sum3.9343241 × 108
Variance1.1641328 × 1011
MonotonicityNot monotonic
2024-04-06T22:11:14.196321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 611
 
6.1%
2 420
 
4.2%
3 356
 
3.6%
4 305
 
3.0%
5 305
 
3.0%
6 288
 
2.9%
7 254
 
2.5%
8 236
 
2.4%
10 235
 
2.4%
9 225
 
2.2%
Other values (2042) 6765
67.7%
ValueCountFrequency (%)
1 611
6.1%
2 420
4.2%
3 356
3.6%
4 305
3.0%
5 305
3.0%
6 288
2.9%
7 254
2.5%
8 236
 
2.4%
9 225
 
2.2%
10 235
 
2.4%
ValueCountFrequency (%)
5292943 1
< 0.1%
5188178 1
< 0.1%
5156190 1
< 0.1%
5115690 1
< 0.1%
5100240 1
< 0.1%
5061558 1
< 0.1%
5053563 1
< 0.1%
5049805 1
< 0.1%
5038379 1
< 0.1%
5035162 1
< 0.1%

총_승객수_일반
Real number (ℝ)

HIGH CORRELATION 

Distinct2029
Distinct (%)20.4%
Missing67
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean32038.66
Minimum1
Maximum4003565
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T22:11:14.474342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17
median25
Q3186
95-th percentile16902.4
Maximum4003565
Range4003564
Interquartile range (IQR)179

Descriptive statistics

Standard deviation263975.22
Coefficient of variation (CV)8.2392716
Kurtosis141.51423
Mean32038.66
Median Absolute Deviation (MAD)23
Skewness11.392606
Sum3.1824001 × 108
Variance6.9682917 × 1010
MonotonicityNot monotonic
2024-04-06T22:11:14.683908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 619
 
6.2%
2 431
 
4.3%
3 372
 
3.7%
5 328
 
3.3%
4 305
 
3.0%
6 293
 
2.9%
7 255
 
2.5%
8 242
 
2.4%
10 241
 
2.4%
9 220
 
2.2%
Other values (2019) 6627
66.3%
ValueCountFrequency (%)
1 619
6.2%
2 431
4.3%
3 372
3.7%
4 305
3.0%
5 328
3.3%
6 293
2.9%
7 255
2.5%
8 242
 
2.4%
9 220
 
2.2%
10 241
 
2.4%
ValueCountFrequency (%)
4003565 1
< 0.1%
3937918 1
< 0.1%
3934877 1
< 0.1%
3883238 1
< 0.1%
3872134 1
< 0.1%
3866369 1
< 0.1%
3851243 1
< 0.1%
3834080 1
< 0.1%
3809387 1
< 0.1%
3771697 1
< 0.1%

총_승객수_어린이
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct700
Distinct (%)15.8%
Missing5576
Missing (%)55.8%
Infinite0
Infinite (%)0.0%
Mean1963.3836
Minimum1
Maximum118248
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T22:11:14.944252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q324
95-th percentile5795.65
Maximum118248
Range118247
Interquartile range (IQR)23

Descriptive statistics

Standard deviation11506.285
Coefficient of variation (CV)5.8604364
Kurtosis56.493506
Mean1963.3836
Median Absolute Deviation (MAD)2
Skewness7.3667746
Sum8686009
Variance1.3239459 × 108
MonotonicityNot monotonic
2024-04-06T22:11:15.215935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1377
 
13.8%
2 534
 
5.3%
3 334
 
3.3%
4 211
 
2.1%
5 128
 
1.3%
6 87
 
0.9%
7 83
 
0.8%
8 65
 
0.7%
19 53
 
0.5%
12 47
 
0.5%
Other values (690) 1505
 
15.0%
(Missing) 5576
55.8%
ValueCountFrequency (%)
1 1377
13.8%
2 534
 
5.3%
3 334
 
3.3%
4 211
 
2.1%
5 128
 
1.3%
6 87
 
0.9%
7 83
 
0.8%
8 65
 
0.7%
9 42
 
0.4%
10 35
 
0.4%
ValueCountFrequency (%)
118248 1
< 0.1%
115928 1
< 0.1%
113894 1
< 0.1%
112886 1
< 0.1%
112757 1
< 0.1%
112075 1
< 0.1%
111739 1
< 0.1%
109367 1
< 0.1%
107835 1
< 0.1%
107797 1
< 0.1%

총_승객수_청소년
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct868
Distinct (%)14.4%
Missing3976
Missing (%)39.8%
Infinite0
Infinite (%)0.0%
Mean2415.7258
Minimum1
Maximum181820
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T22:11:15.428593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median4
Q335
95-th percentile3387.85
Maximum181820
Range181819
Interquartile range (IQR)34

Descriptive statistics

Standard deviation15210.059
Coefficient of variation (CV)6.296269
Kurtosis67.819142
Mean2415.7258
Median Absolute Deviation (MAD)3
Skewness8.0532694
Sum14552332
Variance2.313459 × 108
MonotonicityNot monotonic
2024-04-06T22:11:16.158726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1563
 
15.6%
2 708
 
7.1%
3 432
 
4.3%
4 321
 
3.2%
5 245
 
2.5%
6 206
 
2.1%
7 160
 
1.6%
8 126
 
1.3%
9 111
 
1.1%
12 76
 
0.8%
Other values (858) 2076
20.8%
(Missing) 3976
39.8%
ValueCountFrequency (%)
1 1563
15.6%
2 708
7.1%
3 432
 
4.3%
4 321
 
3.2%
5 245
 
2.5%
6 206
 
2.1%
7 160
 
1.6%
8 126
 
1.3%
9 111
 
1.1%
10 75
 
0.8%
ValueCountFrequency (%)
181820 1
< 0.1%
178970 1
< 0.1%
177917 1
< 0.1%
168001 1
< 0.1%
166933 1
< 0.1%
163597 1
< 0.1%
160691 1
< 0.1%
159178 1
< 0.1%
157353 1
< 0.1%
156793 1
< 0.1%

총_승객수_경로
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct537
Distinct (%)36.2%
Missing8518
Missing (%)85.2%
Infinite0
Infinite (%)0.0%
Mean28777.163
Minimum1
Maximum943701
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T22:11:16.413624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median16
Q3381.75
95-th percentile99304.9
Maximum943701
Range943700
Interquartile range (IQR)377.75

Descriptive statistics

Standard deviation140798.3
Coefficient of variation (CV)4.8927096
Kurtosis29.243184
Mean28777.163
Median Absolute Deviation (MAD)15
Skewness5.5104774
Sum42647755
Variance1.9824162 × 1010
MonotonicityNot monotonic
2024-04-06T22:11:16.622300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 124
 
1.2%
2 122
 
1.2%
3 109
 
1.1%
4 57
 
0.6%
5 44
 
0.4%
7 40
 
0.4%
8 36
 
0.4%
6 33
 
0.3%
12 32
 
0.3%
10 30
 
0.3%
Other values (527) 855
 
8.6%
(Missing) 8518
85.2%
ValueCountFrequency (%)
1 124
1.2%
2 122
1.2%
3 109
1.1%
4 57
0.6%
5 44
 
0.4%
6 33
 
0.3%
7 40
 
0.4%
8 36
 
0.4%
9 25
 
0.2%
10 30
 
0.3%
ValueCountFrequency (%)
943701 1
< 0.1%
920748 1
< 0.1%
911153 1
< 0.1%
906790 1
< 0.1%
899238 1
< 0.1%
899113 1
< 0.1%
896646 1
< 0.1%
893677 1
< 0.1%
893199 1
< 0.1%
890873 1
< 0.1%

총_승객수_장애인
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct397
Distinct (%)30.5%
Missing8698
Missing (%)87.0%
Infinite0
Infinite (%)0.0%
Mean6464.7197
Minimum1
Maximum158274
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T22:11:16.852848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median8
Q3156.5
95-th percentile50533.2
Maximum158274
Range158273
Interquartile range (IQR)154.5

Descriptive statistics

Standard deviation25455.025
Coefficient of variation (CV)3.9375295
Kurtosis20.398487
Mean6464.7197
Median Absolute Deviation (MAD)7
Skewness4.5599143
Sum8417065
Variance6.4795827 × 108
MonotonicityNot monotonic
2024-04-06T22:11:17.187524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 221
 
2.2%
2 122
 
1.2%
3 99
 
1.0%
4 69
 
0.7%
5 58
 
0.6%
6 42
 
0.4%
8 29
 
0.3%
7 24
 
0.2%
9 22
 
0.2%
10 20
 
0.2%
Other values (387) 596
 
6.0%
(Missing) 8698
87.0%
ValueCountFrequency (%)
1 221
2.2%
2 122
1.2%
3 99
1.0%
4 69
 
0.7%
5 58
 
0.6%
6 42
 
0.4%
7 24
 
0.2%
8 29
 
0.3%
9 22
 
0.2%
10 20
 
0.2%
ValueCountFrequency (%)
158274 1
< 0.1%
155889 1
< 0.1%
154774 1
< 0.1%
151933 1
< 0.1%
150848 1
< 0.1%
150303 1
< 0.1%
150196 1
< 0.1%
149165 1
< 0.1%
149010 1
< 0.1%
148993 1
< 0.1%

Interactions

2024-04-06T22:11:10.703840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:02.442137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:03.735183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:04.941512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:06.332925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:07.927971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:09.447064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:10.913642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:02.589765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:03.914371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:05.138017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:06.497931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:08.135477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:09.640963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:11.070494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:02.763021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:04.061667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:05.325893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:07.008405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:08.390841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:09.804084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:11.294393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:02.994744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:04.249922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:05.552271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:07.221826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:08.634930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:10.002774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:11.487370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:03.160028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:04.447367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:05.734666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:07.391358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:08.892539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:10.203307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:11.670064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:03.357416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:04.626277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:05.942269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:07.572032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:09.068858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:10.408877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:11.835600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:03.528434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:04.740010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:06.138027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:07.739802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:09.237791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:11:10.546841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T22:11:17.382105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준_날짜총_승객수총_승객수_일반총_승객수_어린이총_승객수_청소년총_승객수_경로총_승객수_장애인
기준_날짜1.0000.0280.0070.0850.0550.0980.170
총_승객수0.0281.0000.9870.8120.8140.9090.892
총_승객수_일반0.0070.9871.0000.8060.8390.9410.939
총_승객수_어린이0.0850.8120.8061.0000.8940.7870.819
총_승객수_청소년0.0550.8140.8390.8941.0000.8340.762
총_승객수_경로0.0980.9090.9410.7870.8341.0000.953
총_승객수_장애인0.1700.8920.9390.8190.7620.9531.000
2024-04-06T22:11:17.555504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준_날짜총_승객수총_승객수_일반총_승객수_어린이총_승객수_청소년총_승객수_경로총_승객수_장애인
기준_날짜1.000-0.012-0.0140.012-0.021-0.0080.074
총_승객수-0.0121.0000.9990.8940.9200.9480.907
총_승객수_일반-0.0140.9991.0000.8910.9150.9440.903
총_승객수_어린이0.0120.8940.8911.0000.9020.9170.888
총_승객수_청소년-0.0210.9200.9150.9021.0000.9170.893
총_승객수_경로-0.0080.9480.9440.9170.9171.0000.911
총_승객수_장애인0.0740.9070.9030.8880.8930.9111.000

Missing values

2024-04-06T22:11:12.090477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T22:11:12.396353image/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.
2024-04-06T22:11:12.602607image/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

기준_날짜목적통행_패턴총_승객수총_승객수_일반총_승객수_어린이총_승객수_청소년총_승객수_경로총_승객수_장애인
3681420231019①[지하철] → ②[버스] → ③[경기버스] → ④[지하철]7472<NA>2<NA><NA>
2184920231227①[지하철] → ②[지하철] → ③[버스]53134863152298<NA><NA>
309520240319①[버스] → ②[지하철] → ③[경기버스] → ④[지하철]114107<NA>7<NA><NA>
1811620240112①[버스] → ②[지하철] → ③[경기버스] → ④[지하철] → ⑤[지하철]44<NA><NA><NA><NA>
2790120231128①[지하철] → ②[버스] → ③[지하철] → ④[경기버스] → ⑤[버스]87<NA>1<NA><NA>
8416120230228①[버스] → ②[지하철] → ③[버스] → ④[지하철]739709822<NA><NA>
4571620230907①[지하철] → ②[경기버스] → ③[지하철] → ④[경기버스] → ⑤[지하철]65<NA>1<NA><NA>
9238720230117①[버스] → ②[버스] → ③[경기버스] → ④[지하철]10097<NA>3<NA><NA>
7010520230511①[지하철] → ②[경기버스] → ③[버스] → ④[버스] → ⑤[지하철]44<NA><NA><NA><NA>
3025020231118①[경기버스] → ②[지하철] → ③[버스] → ④[경기버스] → ⑤[지하철]1111<NA><NA><NA><NA>
기준_날짜목적통행_패턴총_승객수총_승객수_일반총_승객수_어린이총_승객수_청소년총_승객수_경로총_승객수_장애인
6664720230529①[경기버스] → ②[버스] → ③[버스] → ④[버스] → ⑤[지하철]22202<NA><NA><NA>
903020240221①[지하철] → ②[경기버스] → ③[경기버스] → ④[지하철] → ⑤[버스]4747<NA><NA><NA><NA>
419120240314①[경기버스] → ②[경기버스] → ③[버스] → ④[지하철] → ⑤[버스]353311<NA><NA>
6913320230516①[지하철] → ②[경기버스] → ③[지하철] → ④[경기버스] → ⑤[버스]33<NA><NA><NA><NA>
8657820230215①[버스] → ②[경기버스] → ③[경기버스] → ④[지하철] → ⑤[버스]1513<NA>2<NA><NA>
9490220230104①[버스] → ②[버스] → ③[버스] → ④[버스] → ⑤[지하철]26725737<NA><NA>
7919620230325①[경기버스] → ②[지하철] → ③[버스] → ④[지하철] → ⑤[버스]5352<NA>1<NA><NA>
5179720230810①[버스] → ②[지하철] → ③[버스] → ④[지하철] → ⑤[지하철]1313<NA><NA><NA><NA>
965120240219①[경기버스] → ②[지하철] → ③[경기버스] → ④[지하철]12511825<NA><NA>
9304120230113①[경기버스] → ②[경기버스] → ③[경기버스] → ④[지하철] → ⑤[버스]6663<NA>3<NA><NA>