Overview

Dataset statistics

Number of variables11
Number of observations2068
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory185.9 KiB
Average record size in memory92.1 B

Variable types

Categorical4
Numeric4
Text3

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15246/A/1/datasetView.do

Alerts

대여일자 has constant value ""Constant
이용건수 is highly overall correlated with 이동거리(M) and 1 other fieldsHigh correlation
이동거리(M) is highly overall correlated with 이용건수 and 1 other fieldsHigh correlation
이용시간(분) is highly overall correlated with 이용건수 and 1 other fieldsHigh correlation
이동거리(M) has 442 (21.4%) zerosZeros

Reproduction

Analysis started2024-05-18 05:04:21.985768
Analysis finished2024-05-18 05:04:27.674191
Duration5.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.3 KiB
2020-07-01
2068 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-07-01
2nd row2020-07-01
3rd row2020-07-01
4th row2020-07-01
5th row2020-07-01

Common Values

ValueCountFrequency (%)
2020-07-01 2068
100.0%

Length

2024-05-18T14:04:27.858215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:04:28.196962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-07-01 2068
100.0%

대여소번호
Real number (ℝ)

Distinct101
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean153.16489
Minimum5
Maximum211
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.3 KiB
2024-05-18T14:04:28.475875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile105
Q1123
median151
Q3182
95-th percentile207
Maximum211
Range206
Interquartile range (IQR)59

Descriptive statistics

Standard deviation33.635204
Coefficient of variation (CV)0.21960126
Kurtosis-0.92163241
Mean153.16489
Median Absolute Deviation (MAD)30
Skewness0.078257235
Sum316745
Variance1131.3269
MonotonicityIncreasing
2024-05-18T14:04:28.903821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
152 42
 
2.0%
207 42
 
2.0%
117 35
 
1.7%
186 34
 
1.6%
131 33
 
1.6%
123 33
 
1.6%
113 32
 
1.5%
202 32
 
1.5%
146 32
 
1.5%
144 30
 
1.5%
Other values (91) 1723
83.3%
ValueCountFrequency (%)
5 2
 
0.1%
101 18
0.9%
102 26
1.3%
103 27
1.3%
104 21
1.0%
105 19
0.9%
106 30
1.5%
107 25
1.2%
108 22
1.1%
109 24
1.2%
ValueCountFrequency (%)
211 26
1.3%
210 30
1.5%
209 22
1.1%
207 42
2.0%
206 21
1.0%
205 22
1.1%
204 17
0.8%
203 22
1.1%
202 32
1.5%
201 24
1.2%

대여소
Text

Distinct101
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size16.3 KiB
2024-05-18T14:04:29.403379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length13.895068
Min length8

Characters and Unicode

Total characters28735
Distinct characters192
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상암센터 정비실
2nd row상암센터 정비실
3rd row101. (구)합정동 주민센터
4th row101. (구)합정동 주민센터
5th row101. (구)합정동 주민센터
ValueCountFrequency (%)
앞 875
 
13.0%
옆 208
 
3.1%
2번출구 175
 
2.6%
4번출구 115
 
1.7%
1번출구 112
 
1.7%
뒤 80
 
1.2%
건너편 76
 
1.1%
7번출구 71
 
1.1%
공덕역 70
 
1.0%
합정역 70
 
1.0%
Other values (220) 4898
72.6%
2024-05-18T14:04:30.388448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4736
 
16.5%
1 2523
 
8.8%
. 2066
 
7.2%
2 1033
 
3.6%
앞 875
 
3.0%
구 872
 
3.0%
역 708
 
2.5%
출 684
 
2.4%
번 684
 
2.4%
0 609
 
2.1%
Other values (182) 13945
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14361
50.0%
Decimal Number 7145
24.9%
Space Separator 4736
 
16.5%
Other Punctuation 2066
 
7.2%
Uppercase Letter 219
 
0.8%
Open Punctuation 104
 
0.4%
Close Punctuation 104
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 875
 
6.1%
구 872
 
6.1%
역 708
 
4.9%
출 684
 
4.8%
번 684
 
4.8%
원 404
 
2.8%
교 297
 
2.1%
서 281
 
2.0%
대 268
 
1.9%
동 251
 
1.7%
Other values (160) 9037
62.9%
Decimal Number
ValueCountFrequency (%)
1 2523
35.3%
2 1033
14.5%
0 609
 
8.5%
4 541
 
7.6%
5 488
 
6.8%
3 427
 
6.0%
7 421
 
5.9%
8 415
 
5.8%
6 403
 
5.6%
9 285
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
S 46
21.0%
K 46
21.0%
F 30
13.7%
I 30
13.7%
C 30
13.7%
B 21
9.6%
N 8
 
3.7%
H 8
 
3.7%
Space Separator
ValueCountFrequency (%)
4736
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2066
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Close Punctuation
ValueCountFrequency (%)
) 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14361
50.0%
Common 14155
49.3%
Latin 219
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 875
 
6.1%
구 872
 
6.1%
역 708
 
4.9%
출 684
 
4.8%
번 684
 
4.8%
원 404
 
2.8%
교 297
 
2.1%
서 281
 
2.0%
대 268
 
1.9%
동 251
 
1.7%
Other values (160) 9037
62.9%
Common
ValueCountFrequency (%)
4736
33.5%
1 2523
17.8%
. 2066
14.6%
2 1033
 
7.3%
0 609
 
4.3%
4 541
 
3.8%
5 488
 
3.4%
3 427
 
3.0%
7 421
 
3.0%
8 415
 
2.9%
Other values (4) 896
 
6.3%
Latin
ValueCountFrequency (%)
S 46
21.0%
K 46
21.0%
F 30
13.7%
I 30
13.7%
C 30
13.7%
B 21
9.6%
N 8
 
3.7%
H 8
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14374
50.0%
Hangul 14361
50.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4736
32.9%
1 2523
17.6%
. 2066
14.4%
2 1033
 
7.2%
0 609
 
4.2%
4 541
 
3.8%
5 488
 
3.4%
3 427
 
3.0%
7 421
 
2.9%
8 415
 
2.9%
Other values (12) 1115
 
7.8%
Hangul
ValueCountFrequency (%)
앞 875
 
6.1%
구 872
 
6.1%
역 708
 
4.9%
출 684
 
4.8%
번 684
 
4.8%
원 404
 
2.8%
교 297
 
2.1%
서 281
 
2.0%
대 268
 
1.9%
동 251
 
1.7%
Other values (160) 9037
62.9%

대여구분코드
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size16.3 KiB
정기
1361 
일일(회원)
644 
일일(비회원)
 
39
단체
 
24

Length

Max length7
Median length2
Mean length3.339942
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일일(회원)
2nd row정기
3rd row일일(비회원)
4th row일일(회원)
5th row일일(회원)

Common Values

ValueCountFrequency (%)
정기 1361
65.8%
일일(회원) 644
31.1%
일일(비회원) 39
 
1.9%
단체 24
 
1.2%

Length

2024-05-18T14:04:30.801909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:04:31.133089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 1361
65.8%
일일(회원 644
31.1%
일일(비회원 39
 
1.9%
단체 24
 
1.2%

성별
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size16.3 KiB
\N
757 
M
594 
F
497 
<NA>
219 
m
 
1

Length

Max length4
Median length1
Mean length1.6837524
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row\N
2nd row\N
3rd row\N
4th row\N
5th row\N

Common Values

ValueCountFrequency (%)
\N 757
36.6%
M 594
28.7%
F 497
24.0%
<NA> 219
 
10.6%
m 1
 
< 0.1%

Length

2024-05-18T14:04:31.510329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:04:31.804694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 757
36.6%
m 595
28.8%
f 497
24.0%
na 219
 
10.6%

연령대코드
Categorical

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size16.3 KiB
AGE_002
636 
AGE_003
474 
AGE_004
354 
AGE_005
239 
AGE_001
167 
Other values (3)
198 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAGE_002
2nd rowAGE_006
3rd rowAGE_008
4th rowAGE_002
5th rowAGE_003

Common Values

ValueCountFrequency (%)
AGE_002 636
30.8%
AGE_003 474
22.9%
AGE_004 354
17.1%
AGE_005 239
 
11.6%
AGE_001 167
 
8.1%
AGE_006 100
 
4.8%
AGE_008 72
 
3.5%
AGE_007 26
 
1.3%

Length

2024-05-18T14:04:32.103645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:04:32.502721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
age_002 636
30.8%
age_003 474
22.9%
age_004 354
17.1%
age_005 239
 
11.6%
age_001 167
 
8.1%
age_006 100
 
4.8%
age_008 72
 
3.5%
age_007 26
 
1.3%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8510638
Minimum1
Maximum76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.3 KiB
2024-05-18T14:04:32.894019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile12
Maximum76
Range75
Interquartile range (IQR)4

Descriptive statistics

Standard deviation5.0669503
Coefficient of variation (CV)1.3157274
Kurtosis37.183032
Mean3.8510638
Median Absolute Deviation (MAD)1
Skewness4.6317457
Sum7964
Variance25.673985
MonotonicityNot monotonic
2024-05-18T14:04:33.186764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
1 793
38.3%
2 373
18.0%
3 241
 
11.7%
4 141
 
6.8%
5 123
 
5.9%
6 75
 
3.6%
7 60
 
2.9%
9 46
 
2.2%
8 42
 
2.0%
11 28
 
1.4%
Other values (29) 146
 
7.1%
ValueCountFrequency (%)
1 793
38.3%
2 373
18.0%
3 241
 
11.7%
4 141
 
6.8%
5 123
 
5.9%
6 75
 
3.6%
7 60
 
2.9%
8 42
 
2.0%
9 46
 
2.2%
10 27
 
1.3%
ValueCountFrequency (%)
76 1
< 0.1%
57 1
< 0.1%
48 1
< 0.1%
43 1
< 0.1%
41 1
< 0.1%
39 1
< 0.1%
35 1
< 0.1%
34 1
< 0.1%
33 1
< 0.1%
31 2
0.1%

운동량
Text

Distinct1608
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size16.3 KiB
2024-05-18T14:04:33.722385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.4119923
Min length2

Characters and Unicode

Total characters11192
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1588 ?
Unique (%)76.8%

Sample

1st row0.00
2nd row0.00
3rd row161.39
4th row1322.96
5th row597.47
ValueCountFrequency (%)
0.00 434
 
21.0%
n 8
 
0.4%
45.48 3
 
0.1%
23.17 3
 
0.1%
39.90 2
 
0.1%
90.31 2
 
0.1%
360.12 2
 
0.1%
127.71 2
 
0.1%
35.24 2
 
0.1%
85.30 2
 
0.1%
Other values (1598) 1608
77.8%
2024-05-18T14:04:34.580159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 2060
18.4%
0 1971
17.6%
1 1130
10.1%
2 935
8.4%
3 830
7.4%
5 765
 
6.8%
4 756
 
6.8%
8 709
 
6.3%
6 709
 
6.3%
7 695
 
6.2%
Other values (3) 632
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9116
81.5%
Other Punctuation 2068
 
18.5%
Uppercase Letter 8
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1971
21.6%
1 1130
12.4%
2 935
10.3%
3 830
9.1%
5 765
 
8.4%
4 756
 
8.3%
8 709
 
7.8%
6 709
 
7.8%
7 695
 
7.6%
9 616
 
6.8%
Other Punctuation
ValueCountFrequency (%)
. 2060
99.6%
\ 8
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
N 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11184
99.9%
Latin 8
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 2060
18.4%
0 1971
17.6%
1 1130
10.1%
2 935
8.4%
3 830
7.4%
5 765
 
6.8%
4 756
 
6.8%
8 709
 
6.3%
6 709
 
6.3%
7 695
 
6.2%
Other values (2) 624
 
5.6%
Latin
ValueCountFrequency (%)
N 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11192
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 2060
18.4%
0 1971
17.6%
1 1130
10.1%
2 935
8.4%
3 830
7.4%
5 765
 
6.8%
4 756
 
6.8%
8 709
 
6.3%
6 709
 
6.3%
7 695
 
6.2%
Other values (3) 632
 
5.6%

탄소량
Text

Distinct721
Distinct (%)34.9%
Missing0
Missing (%)0.0%
Memory size16.3 KiB
2024-05-18T14:04:35.280873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.0691489
Min length2

Characters and Unicode

Total characters8415
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique391 ?
Unique (%)18.9%

Sample

1st row0.00
2nd row0.00
3rd row1.45
4th row11.93
5th row4.31
ValueCountFrequency (%)
0.00 434
 
21.0%
0.40 14
 
0.7%
0.19 13
 
0.6%
0.27 13
 
0.6%
0.25 12
 
0.6%
0.26 10
 
0.5%
0.33 10
 
0.5%
0.45 9
 
0.4%
0.58 9
 
0.4%
0.21 9
 
0.4%
Other values (711) 1535
74.2%
2024-05-18T14:04:36.360116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2154
25.6%
. 2060
24.5%
1 785
 
9.3%
2 614
 
7.3%
3 487
 
5.8%
4 452
 
5.4%
5 430
 
5.1%
6 364
 
4.3%
7 360
 
4.3%
9 349
 
4.1%
Other values (3) 360
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6339
75.3%
Other Punctuation 2068
 
24.6%
Uppercase Letter 8
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2154
34.0%
1 785
 
12.4%
2 614
 
9.7%
3 487
 
7.7%
4 452
 
7.1%
5 430
 
6.8%
6 364
 
5.7%
7 360
 
5.7%
9 349
 
5.5%
8 344
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 2060
99.6%
\ 8
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
N 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8407
99.9%
Latin 8
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2154
25.6%
. 2060
24.5%
1 785
 
9.3%
2 614
 
7.3%
3 487
 
5.8%
4 452
 
5.4%
5 430
 
5.1%
6 364
 
4.3%
7 360
 
4.3%
9 349
 
4.2%
Other values (2) 352
 
4.2%
Latin
ValueCountFrequency (%)
N 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8415
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2154
25.6%
. 2060
24.5%
1 785
 
9.3%
2 614
 
7.3%
3 487
 
5.8%
4 452
 
5.4%
5 430
 
5.1%
6 364
 
4.3%
7 360
 
4.3%
9 349
 
4.1%
Other values (3) 360
 
4.3%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1520
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14746.977
Minimum0
Maximum386480.72
Zeros442
Zeros (%)21.4%
Negative0
Negative (%)0.0%
Memory size18.3 KiB
2024-05-18T14:04:36.724573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1840
median5068.325
Q314883.153
95-th percentile62788.332
Maximum386480.72
Range386480.72
Interquartile range (IQR)14043.153

Descriptive statistics

Standard deviation31405.093
Coefficient of variation (CV)2.1295953
Kurtosis38.221555
Mean14746.977
Median Absolute Deviation (MAD)5068.325
Skewness5.3541759
Sum30496748
Variance9.8627984 × 108
MonotonicityNot monotonic
2024-05-18T14:04:36.996684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 442
 
21.4%
1740.0 6
 
0.3%
900.0 4
 
0.2%
3620.0 4
 
0.2%
850.0 4
 
0.2%
2060.0 4
 
0.2%
5530.0 3
 
0.1%
1550.0 3
 
0.1%
3480.0 3
 
0.1%
1100.0 3
 
0.1%
Other values (1510) 1592
77.0%
ValueCountFrequency (%)
0.0 442
21.4%
50.0 1
 
< 0.1%
110.0 1
 
< 0.1%
130.0 1
 
< 0.1%
141.9 1
 
< 0.1%
141.92 1
 
< 0.1%
176.3 1
 
< 0.1%
180.0 1
 
< 0.1%
200.0 1
 
< 0.1%
208.41 1
 
< 0.1%
ValueCountFrequency (%)
386480.72 1
< 0.1%
349483.04 1
< 0.1%
279311.52 1
< 0.1%
274043.18 1
< 0.1%
270413.36 1
< 0.1%
266817.2 1
< 0.1%
265007.99 1
< 0.1%
251730.0 1
< 0.1%
237556.25 1
< 0.1%
236880.0 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct467
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean141.13685
Minimum0
Maximum5034
Zeros2
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size18.3 KiB
2024-05-18T14:04:37.270274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q131
median75
Q3168
95-th percentile463.3
Maximum5034
Range5034
Interquartile range (IQR)137

Descriptive statistics

Standard deviation236.13693
Coefficient of variation (CV)1.6731062
Kurtosis128.59198
Mean141.13685
Median Absolute Deviation (MAD)54.5
Skewness8.4526235
Sum291871
Variance55760.651
MonotonicityNot monotonic
2024-05-18T14:04:37.549974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 28
 
1.4%
8 26
 
1.3%
13 25
 
1.2%
12 25
 
1.2%
5 24
 
1.2%
14 23
 
1.1%
16 21
 
1.0%
17 20
 
1.0%
7 20
 
1.0%
49 19
 
0.9%
Other values (457) 1837
88.8%
ValueCountFrequency (%)
0 2
 
0.1%
1 2
 
0.1%
2 10
 
0.5%
3 15
0.7%
4 16
0.8%
5 24
1.2%
6 19
0.9%
7 20
1.0%
8 26
1.3%
9 16
0.8%
ValueCountFrequency (%)
5034 1
< 0.1%
3809 1
< 0.1%
2297 1
< 0.1%
2144 1
< 0.1%
1857 1
< 0.1%
1753 1
< 0.1%
1640 1
< 0.1%
1501 1
< 0.1%
1465 1
< 0.1%
1414 1
< 0.1%

Interactions

2024-05-18T14:04:25.687705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:04:22.907477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:04:23.694588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:04:24.659365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:04:26.022433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:04:23.115145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:04:23.855782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:04:24.919092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:04:26.297304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:04:23.285942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:04:24.112396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:04:25.126326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:04:26.581763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:04:23.476254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:04:24.394961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:04:25.418259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T14:04:37.972063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호대여구분코드성별연령대코드이용건수이동거리(M)이용시간(분)
대여소번호1.0000.0000.0000.0000.0250.0550.087
대여구분코드0.0001.0000.2420.7790.1050.0690.049
성별0.0000.2421.0000.3240.0700.0000.049
연령대코드0.0000.7790.3241.0000.1400.1000.090
이용건수0.0250.1050.0700.1401.0000.8630.889
이동거리(M)0.0550.0690.0000.1000.8631.0000.736
이용시간(분)0.0870.0490.0490.0900.8890.7361.000
2024-05-18T14:04:38.160888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령대코드성별대여구분코드
연령대코드1.0000.1490.445
성별0.1491.0000.097
대여구분코드0.4450.0971.000
2024-05-18T14:04:38.323359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)대여구분코드성별연령대코드
대여소번호1.0000.0030.0010.0080.0000.0000.000
이용건수0.0031.0000.6600.7860.0690.0420.070
이동거리(M)0.0010.6601.0000.7120.0440.0000.049
이용시간(분)0.0080.7860.7121.0000.0340.0340.048
대여구분코드0.0000.0690.0440.0341.0000.0970.445
성별0.0000.0420.0000.0340.0971.0000.149
연령대코드0.0000.0700.0490.0480.4450.1491.000

Missing values

2024-05-18T14:04:26.960400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T14:04:27.469959image/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

대여일자대여소번호대여소대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
02020-07-015상암센터 정비실일일(회원)\NAGE_00210.000.000.00
12020-07-015상암센터 정비실정기\NAGE_00610.000.000.00
22020-07-01101101. (구)합정동 주민센터일일(비회원)\NAGE_0081161.391.456270.037
32020-07-01101101. (구)합정동 주민센터일일(회원)\NAGE_00241322.9611.9351397.09253
42020-07-01101101. (구)합정동 주민센터일일(회원)\NAGE_0033597.474.3118556.43100
52020-07-01101101. (구)합정동 주민센터일일(회원)\NAGE_0082194.461.707336.9953
62020-07-01101101. (구)합정동 주민센터일일(회원)FAGE_0023337.163.6115592.0114
72020-07-01101101. (구)합정동 주민센터일일(회원)MAGE_00211034.499.3240190.0121
82020-07-01101101. (구)합정동 주민센터정기\NAGE_00251123.8210.9247070.068
92020-07-01101101. (구)합정동 주민센터정기\NAGE_00320.000.000.045
대여일자대여소번호대여소대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
20582020-07-01211211. 여의도역 4번출구 옆정기\NAGE_006122.680.17715.815
20592020-07-01211211. 여의도역 4번출구 옆정기\NAGE_0081289.462.9212602.6672
20602020-07-01211211. 여의도역 4번출구 옆정기<NA>AGE_0022199.511.416070.029
20612020-07-01211211. 여의도역 4번출구 옆정기<NA>AGE_003368.020.472015.1334
20622020-07-01211211. 여의도역 4번출구 옆정기<NA>AGE_0041296.372.329978.8944
20632020-07-01211211. 여의도역 4번출구 옆정기FAGE_002552.890.552373.6839
20642020-07-01211211. 여의도역 4번출구 옆정기FAGE_0036535.415.2822749.29153
20652020-07-01211211. 여의도역 4번출구 옆정기FAGE_004386.440.713100.062
20662020-07-01211211. 여의도역 4번출구 옆정기MAGE_002583.020.723092.0943
20672020-07-01211211. 여의도역 4번출구 옆정기MAGE_00318712.816.1826670.73411