Overview

Dataset statistics

Number of variables10
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory43.1 KiB
Average record size in memory88.3 B

Variable types

Categorical3
Numeric6
Text1

Dataset

Description샘플 데이터
Author서울시(스마트카드사)
URLhttps://bigdata.seoul.go.kr/data/selectSampleData.do?sample_data_seq=71

Alerts

시간(HOUR) has 6 (1.2%) zerosZeros
승차인원(GETON_CNT) has 10 (2.0%) zerosZeros
하차인원(GETOFF_CNT) has 16 (3.2%) zerosZeros

Reproduction

Analysis started2024-04-19 05:59:38.040694
Analysis finished2024-04-19 05:59:42.352207
Duration4.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년(YEAR)
Categorical

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2017
110 
2020
107 
2019
105 
2018
92 
2021
86 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2019
5th row2017

Common Values

ValueCountFrequency (%)
2017 110
22.0%
2020 107
21.4%
2019 105
21.0%
2018 92
18.4%
2021 86
17.2%

Length

2024-04-19T14:59:42.413765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:59:42.517451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 110
22.0%
2020 107
21.4%
2019 105
21.0%
2018 92
18.4%
2021 86
17.2%

월(MONTH)
Real number (ℝ)

Distinct12
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.096
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-19T14:59:42.631168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.448851
Coefficient of variation (CV)0.5657564
Kurtosis-1.2019072
Mean6.096
Median Absolute Deviation (MAD)3
Skewness0.10595067
Sum3048
Variance11.894573
MonotonicityNot monotonic
2024-04-19T14:59:42.738460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 55
11.0%
10 46
9.2%
2 46
9.2%
8 44
8.8%
3 44
8.8%
5 44
8.8%
4 42
8.4%
6 41
8.2%
7 40
8.0%
9 34
6.8%
Other values (2) 64
12.8%
ValueCountFrequency (%)
1 55
11.0%
2 46
9.2%
3 44
8.8%
4 42
8.4%
5 44
8.8%
6 41
8.2%
7 40
8.0%
8 44
8.8%
9 34
6.8%
10 46
9.2%
ValueCountFrequency (%)
12 33
6.6%
11 31
6.2%
10 46
9.2%
9 34
6.8%
8 44
8.8%
7 40
8.0%
6 41
8.2%
5 44
8.8%
4 42
8.4%
3 44
8.8%

일(DAY)
Real number (ℝ)

Distinct31
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.656
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-19T14:59:42.863653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q18
median16
Q323
95-th percentile29.05
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.5884333
Coefficient of variation (CV)0.54857136
Kurtosis-1.1905547
Mean15.656
Median Absolute Deviation (MAD)7.5
Skewness0.052968335
Sum7828
Variance73.761186
MonotonicityNot monotonic
2024-04-19T14:59:42.999503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
13 23
 
4.6%
14 23
 
4.6%
3 22
 
4.4%
7 22
 
4.4%
27 21
 
4.2%
22 20
 
4.0%
16 19
 
3.8%
19 19
 
3.8%
20 19
 
3.8%
6 19
 
3.8%
Other values (21) 293
58.6%
ValueCountFrequency (%)
1 9
1.8%
2 12
2.4%
3 22
4.4%
4 14
2.8%
5 17
3.4%
6 19
3.8%
7 22
4.4%
8 19
3.8%
9 18
3.6%
10 15
3.0%
ValueCountFrequency (%)
31 8
 
1.6%
30 17
3.4%
29 9
1.8%
28 17
3.4%
27 21
4.2%
26 9
1.8%
25 17
3.4%
24 18
3.6%
23 17
3.4%
22 20
4.0%

시간(HOUR)
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.14
Minimum0
Maximum23
Zeros6
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-19T14:59:43.133640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q110
median14
Q319
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)9

Descriptive statistics

Standard deviation5.3712289
Coefficient of variation (CV)0.3798606
Kurtosis-0.74833865
Mean14.14
Median Absolute Deviation (MAD)4
Skewness-0.18754257
Sum7070
Variance28.8501
MonotonicityNot monotonic
2024-04-19T14:59:43.236831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
13 38
 
7.6%
20 33
 
6.6%
14 32
 
6.4%
12 32
 
6.4%
11 30
 
6.0%
15 29
 
5.8%
16 27
 
5.4%
19 26
 
5.2%
17 26
 
5.2%
21 26
 
5.2%
Other values (11) 201
40.2%
ValueCountFrequency (%)
0 6
 
1.2%
4 3
 
0.6%
5 21
4.2%
6 10
 
2.0%
7 25
5.0%
8 22
4.4%
9 24
4.8%
10 21
4.2%
11 30
6.0%
12 32
6.4%
ValueCountFrequency (%)
23 21
4.2%
22 26
5.2%
21 26
5.2%
20 33
6.6%
19 26
5.2%
18 22
4.4%
17 26
5.2%
16 27
5.4%
15 29
5.8%
14 32
6.4%

분_30분단위(HALF_HOUR)
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
30
261 
0
239 

Length

Max length2
Median length2
Mean length1.522
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
30 261
52.2%
0 239
47.8%

Length

2024-04-19T14:59:43.353488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:59:43.449352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 261
52.2%
0 239
47.8%

역ID(STATION_ID)
Real number (ℝ)

Distinct268
Distinct (%)53.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2100.254
Minimum150
Maximum4712
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-19T14:59:43.551509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum150
5-th percentile206
Q1336.75
median2558
Q32744.25
95-th percentile4135.05
Maximum4712
Range4562
Interquartile range (IQR)2407.5

Descriptive statistics

Standard deviation1421.9777
Coefficient of variation (CV)0.67705033
Kurtosis-1.1416592
Mean2100.254
Median Absolute Deviation (MAD)267.5
Skewness-0.10000278
Sum1050127
Variance2022020.5
MonotonicityNot monotonic
2024-04-19T14:59:43.708005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
419 6
 
1.2%
4708 5
 
1.0%
2733 5
 
1.0%
432 5
 
1.0%
2513 5
 
1.0%
152 4
 
0.8%
221 4
 
0.8%
2640 4
 
0.8%
4712 4
 
0.8%
2561 4
 
0.8%
Other values (258) 454
90.8%
ValueCountFrequency (%)
150 2
0.4%
152 4
0.8%
153 1
 
0.2%
154 1
 
0.2%
156 1
 
0.2%
157 1
 
0.2%
158 4
0.8%
159 2
0.4%
201 1
 
0.2%
202 1
 
0.2%
ValueCountFrequency (%)
4712 4
0.8%
4711 1
 
0.2%
4710 1
 
0.2%
4709 1
 
0.2%
4708 5
1.0%
4707 1
 
0.2%
4706 2
 
0.4%
4705 3
0.6%
4702 2
 
0.4%
4137 3
0.6%

호선명(LINE_NM)
Categorical

Distinct11
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
5호선
87 
7호선
79 
2호선
78 
6호선
58 
3호선
45 
Other values (6)
153 

Length

Max length8
Median length3
Mean length3.25
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6호선
2nd row2호선
3rd row4호선
4th row5호선
5th row4호선

Common Values

ValueCountFrequency (%)
5호선 87
17.4%
7호선 79
15.8%
2호선 78
15.6%
6호선 58
11.6%
3호선 45
9.0%
4호선 42
8.4%
9호선 42
8.4%
8호선 24
 
4.8%
9호선2~3단계 19
 
3.8%
우이신설선 15
 
3.0%

Length

2024-04-19T14:59:43.950896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5호선 87
17.4%
7호선 79
15.8%
2호선 78
15.6%
6호선 58
11.6%
3호선 45
9.0%
4호선 42
8.4%
9호선 42
8.4%
8호선 24
 
4.8%
9호선2~3단계 19
 
3.8%
우이신설선 15
 
3.0%

역명(STATION_NM)
Text

Distinct233
Distinct (%)46.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-19T14:59:44.233902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length4.066
Min length2

Characters and Unicode

Total characters2033
Distinct characters234
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)19.2%

Sample

1st row마곡
2nd row응암
3rd row구산
4th row개화
5th row화랑대(서울여대입구)
ValueCountFrequency (%)
종로3가 9
 
1.8%
보문 8
 
1.6%
신설동 7
 
1.4%
고속터미널 6
 
1.2%
공덕 6
 
1.2%
송파나루 6
 
1.2%
건대입구 6
 
1.2%
오금 5
 
1.0%
동작(현충원 5
 
1.0%
국회의사당 5
 
1.0%
Other values (223) 437
87.4%
2024-04-19T14:59:44.641447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 90
 
4.4%
( 90
 
4.4%
대 72
 
3.5%
구 72
 
3.5%
동 64
 
3.1%
신 57
 
2.8%
청 39
 
1.9%
원 37
 
1.8%
산 34
 
1.7%
입 34
 
1.7%
Other values (224) 1444
71.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1820
89.5%
Close Punctuation 90
 
4.4%
Open Punctuation 90
 
4.4%
Decimal Number 19
 
0.9%
Other Punctuation 8
 
0.4%
Uppercase Letter 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 72
 
4.0%
구 72
 
4.0%
동 64
 
3.5%
신 57
 
3.1%
청 39
 
2.1%
원 37
 
2.0%
산 34
 
1.9%
입 34
 
1.9%
문 33
 
1.8%
성 30
 
1.6%
Other values (215) 1348
74.1%
Decimal Number
ValueCountFrequency (%)
3 13
68.4%
4 4
 
21.1%
5 2
 
10.5%
Other Punctuation
ValueCountFrequency (%)
. 6
75.0%
· 2
 
25.0%
Uppercase Letter
ValueCountFrequency (%)
D 4
66.7%
P 2
33.3%
Close Punctuation
ValueCountFrequency (%)
) 90
100.0%
Open Punctuation
ValueCountFrequency (%)
( 90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1820
89.5%
Common 207
 
10.2%
Latin 6
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 72
 
4.0%
구 72
 
4.0%
동 64
 
3.5%
신 57
 
3.1%
청 39
 
2.1%
원 37
 
2.0%
산 34
 
1.9%
입 34
 
1.9%
문 33
 
1.8%
성 30
 
1.6%
Other values (215) 1348
74.1%
Common
ValueCountFrequency (%)
) 90
43.5%
( 90
43.5%
3 13
 
6.3%
. 6
 
2.9%
4 4
 
1.9%
· 2
 
1.0%
5 2
 
1.0%
Latin
ValueCountFrequency (%)
D 4
66.7%
P 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1820
89.5%
ASCII 211
 
10.4%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 90
42.7%
( 90
42.7%
3 13
 
6.2%
. 6
 
2.8%
D 4
 
1.9%
4 4
 
1.9%
5 2
 
0.9%
P 2
 
0.9%
Hangul
ValueCountFrequency (%)
대 72
 
4.0%
구 72
 
4.0%
동 64
 
3.5%
신 57
 
3.1%
청 39
 
2.1%
원 37
 
2.0%
산 34
 
1.9%
입 34
 
1.9%
문 33
 
1.8%
성 30
 
1.6%
Other values (215) 1348
74.1%
None
ValueCountFrequency (%)
· 2
100.0%

승차인원(GETON_CNT)
Real number (ℝ)

ZEROS 

Distinct296
Distinct (%)59.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean208.63
Minimum0
Maximum2511
Zeros10
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-19T14:59:44.776670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q147.75
median121.5
Q3255
95-th percentile715.65
Maximum2511
Range2511
Interquartile range (IQR)207.25

Descriptive statistics

Standard deviation277.45987
Coefficient of variation (CV)1.3299136
Kurtosis16.730504
Mean208.63
Median Absolute Deviation (MAD)90.5
Skewness3.3984446
Sum104315
Variance76983.977
MonotonicityNot monotonic
2024-04-19T14:59:44.919720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10
 
2.0%
75 7
 
1.4%
227 5
 
1.0%
51 5
 
1.0%
4 5
 
1.0%
65 5
 
1.0%
44 5
 
1.0%
14 5
 
1.0%
1 5
 
1.0%
21 4
 
0.8%
Other values (286) 444
88.8%
ValueCountFrequency (%)
0 10
2.0%
1 5
1.0%
2 3
 
0.6%
3 3
 
0.6%
4 5
1.0%
5 3
 
0.6%
6 2
 
0.4%
7 2
 
0.4%
8 2
 
0.4%
9 1
 
0.2%
ValueCountFrequency (%)
2511 1
0.2%
1908 1
0.2%
1711 1
0.2%
1500 1
0.2%
1478 1
0.2%
1426 1
0.2%
1369 1
0.2%
1221 1
0.2%
1202 1
0.2%
1196 1
0.2%

하차인원(GETOFF_CNT)
Real number (ℝ)

ZEROS 

Distinct293
Distinct (%)58.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean217.712
Minimum0
Maximum4022
Zeros16
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-19T14:59:45.065014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.95
Q163.75
median128
Q3237
95-th percentile736.2
Maximum4022
Range4022
Interquartile range (IQR)173.25

Descriptive statistics

Standard deviation325.46364
Coefficient of variation (CV)1.4949274
Kurtosis45.463745
Mean217.712
Median Absolute Deviation (MAD)79
Skewness5.4062859
Sum108856
Variance105926.58
MonotonicityNot monotonic
2024-04-19T14:59:45.241117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 16
 
3.2%
107 7
 
1.4%
114 6
 
1.2%
65 6
 
1.2%
120 5
 
1.0%
117 5
 
1.0%
84 5
 
1.0%
1 5
 
1.0%
155 5
 
1.0%
38 4
 
0.8%
Other values (283) 436
87.2%
ValueCountFrequency (%)
0 16
3.2%
1 5
 
1.0%
2 2
 
0.4%
3 1
 
0.2%
4 1
 
0.2%
5 1
 
0.2%
6 2
 
0.4%
8 3
 
0.6%
10 2
 
0.4%
12 1
 
0.2%
ValueCountFrequency (%)
4022 1
0.2%
2387 1
0.2%
2103 1
0.2%
1655 1
0.2%
1569 1
0.2%
1465 1
0.2%
1464 1
0.2%
1415 1
0.2%
1398 1
0.2%
1364 1
0.2%

Interactions

2024-04-19T14:59:41.194892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:38.482527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:39.037753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:39.563749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:40.084179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:40.639947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:41.619452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:38.566451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:39.134613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:39.642004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:40.204423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:40.732852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:41.711539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:38.666469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:39.220675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:39.731360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:40.291764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:40.828820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:41.812102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:38.768465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:39.302432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:39.803883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:40.369450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:40.923841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:41.900792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:38.849827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:39.380929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:39.884170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:40.452707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:41.004721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:41.990045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:38.933621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:39.462905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:39.989258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:40.537770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:59:41.093109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T14:59:45.349756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년(YEAR)월(MONTH)일(DAY)시간(HOUR)분_30분단위(HALF_HOUR)역ID(STATION_ID)호선명(LINE_NM)승차인원(GETON_CNT)하차인원(GETOFF_CNT)
년(YEAR)1.0000.0530.0000.0000.0520.0000.0000.0880.010
월(MONTH)0.0531.0000.2430.1740.0000.0690.0000.0000.000
일(DAY)0.0000.2431.0000.0000.0000.0000.1690.0000.047
시간(HOUR)0.0000.1740.0001.0000.0000.0000.1330.0000.104
분_30분단위(HALF_HOUR)0.0520.0000.0000.0001.0000.0490.0000.1100.130
역ID(STATION_ID)0.0000.0690.0000.0000.0491.0000.0800.1370.056
호선명(LINE_NM)0.0000.0000.1690.1330.0000.0801.0000.0000.000
승차인원(GETON_CNT)0.0880.0000.0000.0000.1100.1370.0001.0000.000
하차인원(GETOFF_CNT)0.0100.0000.0470.1040.1300.0560.0000.0001.000
2024-04-19T14:59:45.471436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년(YEAR)분_30분단위(HALF_HOUR)호선명(LINE_NM)
년(YEAR)1.0000.0630.000
분_30분단위(HALF_HOUR)0.0631.0000.000
호선명(LINE_NM)0.0000.0001.000
2024-04-19T14:59:45.573626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월(MONTH)일(DAY)시간(HOUR)역ID(STATION_ID)승차인원(GETON_CNT)하차인원(GETOFF_CNT)년(YEAR)분_30분단위(HALF_HOUR)호선명(LINE_NM)
월(MONTH)1.0000.0210.081-0.0200.0640.0010.0210.0000.000
일(DAY)0.0211.000-0.003-0.034-0.060-0.0080.0000.0000.084
시간(HOUR)0.081-0.0031.0000.0340.050-0.0020.0000.0000.056
역ID(STATION_ID)-0.020-0.0340.0341.000-0.035-0.0940.0000.0080.047
승차인원(GETON_CNT)0.064-0.0600.050-0.0351.000-0.0190.0500.1090.000
하차인원(GETOFF_CNT)0.001-0.008-0.002-0.094-0.0191.0000.0040.1380.000
년(YEAR)0.0210.0000.0000.0000.0500.0041.0000.0630.000
분_30분단위(HALF_HOUR)0.0000.0000.0000.0080.1090.1380.0631.0000.000
호선명(LINE_NM)0.0000.0840.0560.0470.0000.0000.0000.0001.000

Missing values

2024-04-19T14:59:42.138696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T14:59:42.293657image/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

년(YEAR)월(MONTH)일(DAY)시간(HOUR)분_30분단위(HALF_HOUR)역ID(STATION_ID)호선명(LINE_NM)역명(STATION_NM)승차인원(GETON_CNT)하차인원(GETOFF_CNT)
0202092014301596호선마곡174357
120201231702022호선응암102292
2202062521027484호선구산245106
3201973018025175호선개화231118
420171814041374호선화랑대(서울여대입구)5310
5201881714027408호선미아사거리37437
62018312703402호선교대(법원.검찰청)6549
720195281303402호선역삼16013
8201810623028256호선회현(남대문시장)14850
92017216163025209호선2~3단계춘의185221
년(YEAR)월(MONTH)일(DAY)시간(HOUR)분_30분단위(HALF_HOUR)역ID(STATION_ID)호선명(LINE_NM)역명(STATION_NM)승차인원(GETON_CNT)하차인원(GETOFF_CNT)
49020196277027597호선약수61529
491201733163025298호선성신여대입구(돈암)6481
492201971822041375호선용두(동대문구청)47052
49320215231302272호선가양486261
494201710323041364호선송파나루15567
49520211020213025506호선용답20856
496202022213025293호선월드컵경기장(성산)6561
49720201219223041285호선명일8270
498201942418027607호선산성21742
499202164183025129호선이대111265