Overview

Dataset statistics

Number of variables11
Number of observations6578
Missing cells6578
Missing cells (%)9.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory597.5 KiB
Average record size in memory93.0 B

Variable types

DateTime1
Numeric4
Text3
Categorical2
Unsupported1

Dataset

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

Alerts

대여일자 has constant value ""Constant
대여구분코드 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
성별 has 6578 (100.0%) missing valuesMissing
성별 is an unsupported type, check if it needs cleaning or further analysisUnsupported
이동거리(M) has 154 (2.3%) zerosZeros

Reproduction

Analysis started2024-04-20 17:41:52.572881
Analysis finished2024-04-20 17:41:57.730604
Duration5.16 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.5 KiB
Minimum2021-07-01 00:00:00
Maximum2021-07-01 00:00:00
2024-04-21T02:41:57.855741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:41:58.155957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

대여소번호
Real number (ℝ)

Distinct2343
Distinct (%)35.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1899.3232
Minimum102
Maximum4869
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size57.9 KiB
2024-04-21T02:41:58.515256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile236
Q1780.25
median1611
Q32720
95-th percentile4515
Maximum4869
Range4767
Interquartile range (IQR)1939.75

Descriptive statistics

Standard deviation1325.9175
Coefficient of variation (CV)0.69809999
Kurtosis-0.69516456
Mean1899.3232
Median Absolute Deviation (MAD)934.5
Skewness0.62861927
Sum12493748
Variance1758057.2
MonotonicityNot monotonic
2024-04-21T02:41:58.953432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1385 8
 
0.1%
240 7
 
0.1%
2739 7
 
0.1%
2728 7
 
0.1%
2701 7
 
0.1%
230 6
 
0.1%
1721 6
 
0.1%
102 6
 
0.1%
279 6
 
0.1%
2611 6
 
0.1%
Other values (2333) 6512
99.0%
ValueCountFrequency (%)
102 6
0.1%
103 2
 
< 0.1%
104 3
< 0.1%
105 1
 
< 0.1%
106 2
 
< 0.1%
107 3
< 0.1%
108 3
< 0.1%
109 3
< 0.1%
111 4
0.1%
112 3
< 0.1%
ValueCountFrequency (%)
4869 2
 
< 0.1%
4868 4
0.1%
4867 2
 
< 0.1%
4865 5
0.1%
4864 4
0.1%
4862 1
 
< 0.1%
4861 2
 
< 0.1%
4860 3
< 0.1%
4859 5
0.1%
4857 2
 
< 0.1%

대여소
Text

Distinct2343
Distinct (%)35.6%
Missing0
Missing (%)0.0%
Memory size51.5 KiB
2024-04-21T02:42:00.119886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length31
Mean length15.473548
Min length7

Characters and Unicode

Total characters101785
Distinct characters557
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique318 ?
Unique (%)4.8%

Sample

1st row729. 서부식자재마트 건너편
2nd row731. 서울시 도로환경관리센터
3rd row734. 신트리공원 입구
4th row736. 오솔길공원
5th row739. 신월사거리
ValueCountFrequency (%)
앞 1693
 
8.9%
출구 263
 
1.4%
옆 247
 
1.3%
1번출구 199
 
1.0%
교차로 170
 
0.9%
사거리 154
 
0.8%
입구 154
 
0.8%
3번출구 136
 
0.7%
2번출구 135
 
0.7%
뒤 122
 
0.6%
Other values (4647) 15754
82.8%
2024-04-21T02:42:01.558221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12569
 
12.3%
. 6597
 
6.5%
1 5332
 
5.2%
2 3932
 
3.9%
3 3173
 
3.1%
4 2903
 
2.9%
5 2421
 
2.4%
6 2342
 
2.3%
7 2306
 
2.3%
0 2296
 
2.3%
Other values (547) 57914
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52493
51.6%
Decimal Number 28029
27.5%
Space Separator 12569
 
12.3%
Other Punctuation 6667
 
6.6%
Uppercase Letter 813
 
0.8%
Close Punctuation 532
 
0.5%
Open Punctuation 532
 
0.5%
Lowercase Letter 83
 
0.1%
Dash Punctuation 46
 
< 0.1%
Math Symbol 10
 
< 0.1%
Other values (2) 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2141
 
4.1%
앞 1968
 
3.7%
역 1614
 
3.1%
번 1457
 
2.8%
동 1448
 
2.8%
출 1412
 
2.7%
교 1125
 
2.1%
파 987
 
1.9%
아 959
 
1.8%
리 915
 
1.7%
Other values (491) 38467
73.3%
Uppercase Letter
ValueCountFrequency (%)
K 96
11.8%
S 94
11.6%
T 83
10.2%
C 76
9.3%
D 59
 
7.3%
A 59
 
7.3%
M 46
 
5.7%
G 45
 
5.5%
B 43
 
5.3%
P 43
 
5.3%
Other values (13) 169
20.8%
Decimal Number
ValueCountFrequency (%)
1 5332
19.0%
2 3932
14.0%
3 3173
11.3%
4 2903
10.4%
5 2421
8.6%
6 2342
8.4%
7 2306
8.2%
0 2296
8.2%
8 1710
 
6.1%
9 1614
 
5.8%
Lowercase Letter
ValueCountFrequency (%)
e 31
37.3%
k 13
15.7%
s 12
 
14.5%
n 8
 
9.6%
l 4
 
4.8%
v 4
 
4.8%
y 4
 
4.8%
t 3
 
3.6%
g 2
 
2.4%
a 2
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 6597
99.0%
, 46
 
0.7%
& 16
 
0.2%
? 6
 
0.1%
· 2
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 8
80.0%
+ 2
 
20.0%
Space Separator
ValueCountFrequency (%)
12569
100.0%
Close Punctuation
ValueCountFrequency (%)
) 532
100.0%
Open Punctuation
ValueCountFrequency (%)
( 532
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52499
51.6%
Common 48390
47.5%
Latin 896
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2141
 
4.1%
앞 1968
 
3.7%
역 1614
 
3.1%
번 1457
 
2.8%
동 1448
 
2.8%
출 1412
 
2.7%
교 1125
 
2.1%
파 987
 
1.9%
아 959
 
1.8%
리 915
 
1.7%
Other values (492) 38473
73.3%
Latin
ValueCountFrequency (%)
K 96
 
10.7%
S 94
 
10.5%
T 83
 
9.3%
C 76
 
8.5%
D 59
 
6.6%
A 59
 
6.6%
M 46
 
5.1%
G 45
 
5.0%
B 43
 
4.8%
P 43
 
4.8%
Other values (23) 252
28.1%
Common
ValueCountFrequency (%)
12569
26.0%
. 6597
13.6%
1 5332
11.0%
2 3932
 
8.1%
3 3173
 
6.6%
4 2903
 
6.0%
5 2421
 
5.0%
6 2342
 
4.8%
7 2306
 
4.8%
0 2296
 
4.7%
Other values (12) 4519
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52493
51.6%
ASCII 49284
48.4%
None 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12569
25.5%
. 6597
13.4%
1 5332
10.8%
2 3932
 
8.0%
3 3173
 
6.4%
4 2903
 
5.9%
5 2421
 
4.9%
6 2342
 
4.8%
7 2306
 
4.7%
0 2296
 
4.7%
Other values (44) 5413
11.0%
Hangul
ValueCountFrequency (%)
구 2141
 
4.1%
앞 1968
 
3.7%
역 1614
 
3.1%
번 1457
 
2.8%
동 1448
 
2.8%
출 1412
 
2.7%
교 1125
 
2.1%
파 987
 
1.9%
아 959
 
1.8%
리 915
 
1.7%
Other values (491) 38467
73.3%
None
ValueCountFrequency (%)
㈜ 6
75.0%
· 2
 
25.0%

대여구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.5 KiB
정기권
6578 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정기권 6578
100.0%

Length

2024-04-21T02:42:01.965410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:42:02.264890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 6578
100.0%

성별
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6578
Missing (%)100.0%
Memory size57.9 KiB

연령대
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size51.5 KiB
20대
2502 
30대
2048 
40대
1228 
~10대
800 

Length

Max length4
Median length3
Mean length3.1216175
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row~10대
2nd row~10대
3rd row~10대
4th row~10대
5th row~10대

Common Values

ValueCountFrequency (%)
20대 2502
38.0%
30대 2048
31.1%
40대 1228
18.7%
~10대 800
 
12.2%

Length

2024-04-21T02:42:02.594136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:42:02.923160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 2502
38.0%
30대 2048
31.1%
40대 1228
18.7%
10대 800
 
12.2%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9697476
Minimum1
Maximum71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size57.9 KiB
2024-04-21T02:42:03.275805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile13
Maximum71
Range70
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.6098667
Coefficient of variation (CV)1.1612493
Kurtosis20.830237
Mean3.9697476
Median Absolute Deviation (MAD)1
Skewness3.485873
Sum26113
Variance21.250871
MonotonicityNot monotonic
2024-04-21T02:42:03.711560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1 2306
35.1%
2 1144
17.4%
3 786
 
11.9%
4 566
 
8.6%
5 356
 
5.4%
6 298
 
4.5%
7 225
 
3.4%
8 157
 
2.4%
9 123
 
1.9%
10 117
 
1.8%
Other values (34) 500
 
7.6%
ValueCountFrequency (%)
1 2306
35.1%
2 1144
17.4%
3 786
 
11.9%
4 566
 
8.6%
5 356
 
5.4%
6 298
 
4.5%
7 225
 
3.4%
8 157
 
2.4%
9 123
 
1.9%
10 117
 
1.8%
ValueCountFrequency (%)
71 1
 
< 0.1%
47 1
 
< 0.1%
46 1
 
< 0.1%
44 2
< 0.1%
43 1
 
< 0.1%
41 1
 
< 0.1%
40 1
 
< 0.1%
39 1
 
< 0.1%
38 4
0.1%
37 1
 
< 0.1%

운동량
Text

Distinct5857
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size51.5 KiB
2024-04-21T02:42:05.046049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.5215871
Min length2

Characters and Unicode

Total characters36321
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

Unique5354 ?
Unique (%)81.4%

Sample

1st row177.63
2nd row20.32
3rd row112.28
4th row105.39
5th row52.71
ValueCountFrequency (%)
0.00 145
 
2.2%
n 12
 
0.2%
18.53 5
 
0.1%
58.98 5
 
0.1%
41.71 4
 
0.1%
12.36 4
 
0.1%
25.34 3
 
< 0.1%
12.67 3
 
< 0.1%
14.86 3
 
< 0.1%
48.49 3
 
< 0.1%
Other values (5847) 6391
97.2%
2024-04-21T02:42:06.620443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6566
18.1%
1 4299
11.8%
2 3602
9.9%
3 3257
9.0%
4 2896
8.0%
0 2861
7.9%
5 2788
7.7%
6 2620
 
7.2%
7 2557
 
7.0%
8 2542
 
7.0%
Other values (3) 2333
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29731
81.9%
Other Punctuation 6578
 
18.1%
Uppercase Letter 12
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4299
14.5%
2 3602
12.1%
3 3257
11.0%
4 2896
9.7%
0 2861
9.6%
5 2788
9.4%
6 2620
8.8%
7 2557
8.6%
8 2542
8.5%
9 2309
7.8%
Other Punctuation
ValueCountFrequency (%)
. 6566
99.8%
\ 12
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36309
> 99.9%
Latin 12
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 6566
18.1%
1 4299
11.8%
2 3602
9.9%
3 3257
9.0%
4 2896
8.0%
0 2861
7.9%
5 2788
7.7%
6 2620
 
7.2%
7 2557
 
7.0%
8 2542
 
7.0%
Other values (2) 2321
 
6.4%
Latin
ValueCountFrequency (%)
N 12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36321
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 6566
18.1%
1 4299
11.8%
2 3602
9.9%
3 3257
9.0%
4 2896
8.0%
0 2861
7.9%
5 2788
7.7%
6 2620
 
7.2%
7 2557
 
7.0%
8 2542
 
7.0%
Other values (3) 2333
 
6.4%

탄소량
Text

Distinct853
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size51.5 KiB
2024-04-21T02:42:07.998202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.0126178
Min length2

Characters and Unicode

Total characters26395
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

Unique255 ?
Unique (%)3.9%

Sample

1st row1.73
2nd row0.16
3rd row0.91
4th row0.95
5th row0.47
ValueCountFrequency (%)
0.00 148
 
2.2%
0.10 57
 
0.9%
0.35 54
 
0.8%
0.31 52
 
0.8%
0.16 52
 
0.8%
0.52 51
 
0.8%
0.30 51
 
0.8%
0.22 50
 
0.8%
0.18 49
 
0.7%
0.39 47
 
0.7%
Other values (843) 5967
90.7%
2024-04-21T02:42:09.777937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6566
24.9%
0 4793
18.2%
1 2955
11.2%
2 2202
 
8.3%
3 1865
 
7.1%
4 1553
 
5.9%
5 1456
 
5.5%
6 1328
 
5.0%
7 1280
 
4.8%
8 1198
 
4.5%
Other values (3) 1199
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19805
75.0%
Other Punctuation 6578
 
24.9%
Uppercase Letter 12
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4793
24.2%
1 2955
14.9%
2 2202
11.1%
3 1865
 
9.4%
4 1553
 
7.8%
5 1456
 
7.4%
6 1328
 
6.7%
7 1280
 
6.5%
8 1198
 
6.0%
9 1175
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 6566
99.8%
\ 12
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26383
> 99.9%
Latin 12
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 6566
24.9%
0 4793
18.2%
1 2955
11.2%
2 2202
 
8.3%
3 1865
 
7.1%
4 1553
 
5.9%
5 1456
 
5.5%
6 1328
 
5.0%
7 1280
 
4.9%
8 1198
 
4.5%
Other values (2) 1187
 
4.5%
Latin
ValueCountFrequency (%)
N 12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26395
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 6566
24.9%
0 4793
18.2%
1 2955
11.2%
2 2202
 
8.3%
3 1865
 
7.1%
4 1553
 
5.9%
5 1456
 
5.5%
6 1328
 
5.0%
7 1280
 
4.8%
8 1198
 
4.5%
Other values (3) 1199
 
4.5%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct5989
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8063.3931
Minimum0
Maximum147799
Zeros154
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size57.9 KiB
2024-04-21T02:42:10.197989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile430
Q11763.265
median4446.915
Q310429.195
95-th percentile27869.006
Maximum147799
Range147799
Interquartile range (IQR)8665.93

Descriptive statistics

Standard deviation10278.656
Coefficient of variation (CV)1.2747309
Kurtosis21.187599
Mean8063.3931
Median Absolute Deviation (MAD)3285.36
Skewness3.3901701
Sum53041000
Variance1.0565077 × 108
MonotonicityNot monotonic
2024-04-21T02:42:10.649515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 154
 
2.3%
670.0 7
 
0.1%
1700.0 7
 
0.1%
410.0 6
 
0.1%
222.39 6
 
0.1%
580.0 6
 
0.1%
980.0 6
 
0.1%
600.0 6
 
0.1%
111.2 6
 
0.1%
1350.0 6
 
0.1%
Other values (5979) 6368
96.8%
ValueCountFrequency (%)
0.0 154
2.3%
0.1 2
 
< 0.1%
0.2 1
 
< 0.1%
0.26 1
 
< 0.1%
0.39 1
 
< 0.1%
20.0 1
 
< 0.1%
40.0 1
 
< 0.1%
50.0 1
 
< 0.1%
60.0 1
 
< 0.1%
88.12 1
 
< 0.1%
ValueCountFrequency (%)
147799.0 1
< 0.1%
145109.34 1
< 0.1%
116178.75 1
< 0.1%
104309.31 1
< 0.1%
102443.78 1
< 0.1%
89105.43 1
< 0.1%
82140.86 1
< 0.1%
77683.01 1
< 0.1%
76436.9 1
< 0.1%
75930.28 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct387
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.333232
Minimum0
Maximum984
Zeros8
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size57.9 KiB
2024-04-21T02:42:11.087206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q114
median36
Q379
95-th percentile215
Maximum984
Range984
Interquartile range (IQR)65

Descriptive statistics

Standard deviation78.544862
Coefficient of variation (CV)1.26008
Kurtosis19.6875
Mean62.333232
Median Absolute Deviation (MAD)26
Skewness3.3972347
Sum410028
Variance6169.2954
MonotonicityNot monotonic
2024-04-21T02:42:11.521724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 157
 
2.4%
6 155
 
2.4%
5 149
 
2.3%
4 146
 
2.2%
9 133
 
2.0%
8 132
 
2.0%
12 122
 
1.9%
10 118
 
1.8%
11 117
 
1.8%
14 110
 
1.7%
Other values (377) 5239
79.6%
ValueCountFrequency (%)
0 8
 
0.1%
1 28
 
0.4%
2 101
1.5%
3 110
1.7%
4 146
2.2%
5 149
2.3%
6 155
2.4%
7 157
2.4%
8 132
2.0%
9 133
2.0%
ValueCountFrequency (%)
984 1
< 0.1%
950 1
< 0.1%
924 1
< 0.1%
860 1
< 0.1%
811 1
< 0.1%
714 1
< 0.1%
682 1
< 0.1%
659 1
< 0.1%
651 1
< 0.1%
621 1
< 0.1%

Interactions

2024-04-21T02:41:55.921568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:41:53.738991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:41:54.388940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:41:55.062623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:41:56.181906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:41:53.891884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:41:54.551989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:41:55.229122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:41:56.442658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:41:54.062934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:41:54.723645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:41:55.414046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:41:56.722476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:41:54.231356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:41:54.901496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:41:55.652776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T02:42:11.741068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호연령대이용건수이동거리(M)이용시간(분)
대여소번호1.0000.1260.0950.0520.073
연령대0.1261.0000.4290.2710.317
이용건수0.0950.4291.0000.7380.767
이동거리(M)0.0520.2710.7381.0000.878
이용시간(분)0.0730.3170.7670.8781.000
2024-04-21T02:42:11.924982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)연령대
대여소번호1.000-0.091-0.074-0.0740.075
이용건수-0.0911.0000.8160.8330.191
이동거리(M)-0.0740.8161.0000.9190.176
이용시간(분)-0.0740.8330.9191.0000.194
연령대0.0750.1910.1760.1941.000

Missing values

2024-04-21T02:41:57.041355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T02:41:57.514916image/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

대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
02021-07-01729729. 서부식자재마트 건너편정기권<NA>~10대4177.631.737412.6147
12021-07-01731731. 서울시 도로환경관리센터정기권<NA>~10대120.320.16684.016
22021-07-01734734. 신트리공원 입구정기권<NA>~10대3112.280.913938.7146
32021-07-01736736. 오솔길공원정기권<NA>~10대1105.390.954094.253
42021-07-01739739. 신월사거리정기권<NA>~10대352.710.472033.9968
52021-07-01740740. 으뜸공원정기권<NA>~10대5113.421.144921.1431
62021-07-01746746. 목동2단지 상가정기권<NA>~10대269.070.582491.6521
72021-07-01747747. 목동3단지 상가정기권<NA>~10대10.000.000.05
82021-07-01748748. 목동운동장정기권<NA>~10대17.340.06254.0510
92021-07-01939939. 은평구청 교차로정기권<NA>~10대10.000.000.07
대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
65682021-07-01643643. 동대문구민체육센터 (육교아래)정기권<NA>40대5354.803.1813712.1380
65692021-07-01230230. 영등포구청역 1번출구정기권<NA>40대6449.893.3914625.8177
65702021-07-01262262. 영문초등학교 사거리정기권<NA>40대6436.782.9912842.8378
65712021-07-01262262. 영문초등학교 사거리정기권<NA>40대2156.461.345766.431
65722021-07-01263263. 근로자회관 사거리정기권<NA>40대9575.724.6720173.69150
65732021-07-01264264. 교보생명보험 앞정기권<NA>40대1176.641.888110.076
65742021-07-01265265. 영등포유통상가 사거리정기권<NA>40대4391.672.7611871.7990
65752021-07-01141141. 연대 대운동장 옆정기권<NA>40대161.040.552371.2544
65762021-07-01266266. 영등포청과시장 사거리정기권<NA>40대10.000.000.05
65772021-07-01267267. 삼성화재 사옥 옆정기권<NA>40대138.310.281209.3419