Overview

Dataset statistics

Number of variables11
Number of observations6455
Missing cells6455
Missing cells (%)9.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory586.4 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/A/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 6455 (100.0%) missing valuesMissing
성별 is an unsupported type, check if it needs cleaning or further analysisUnsupported
이동거리(M) has 454 (7.0%) zerosZeros

Reproduction

Analysis started2024-05-18 04:55:27.479648
Analysis finished2024-05-18 04:55:36.418048
Duration8.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.6 KiB
Minimum2021-10-01 00:00:00
Maximum2021-10-01 00:00:00
2024-05-18T13:55:36.579743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:36.878747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

대여소번호
Real number (ℝ)

Distinct2343
Distinct (%)36.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1948.4617
Minimum102
Maximum5063
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size56.9 KiB
2024-05-18T13:55:37.271690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile234
Q1788
median1630
Q32817.5
95-th percentile4564.3
Maximum5063
Range4961
Interquartile range (IQR)2029.5

Descriptive statistics

Standard deviation1372.477
Coefficient of variation (CV)0.70439005
Kurtosis-0.78949234
Mean1948.4617
Median Absolute Deviation (MAD)974
Skewness0.60673635
Sum12577320
Variance1883693.1
MonotonicityNot monotonic
2024-05-18T13:55:37.704680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
646 7
 
0.1%
117 6
 
0.1%
3966 6
 
0.1%
1336 6
 
0.1%
4016 6
 
0.1%
1985 6
 
0.1%
1471 6
 
0.1%
670 6
 
0.1%
4571 6
 
0.1%
1166 6
 
0.1%
Other values (2333) 6394
99.1%
ValueCountFrequency (%)
102 4
0.1%
103 3
< 0.1%
104 2
< 0.1%
105 2
< 0.1%
106 3
< 0.1%
107 2
< 0.1%
108 4
0.1%
109 3
< 0.1%
111 2
< 0.1%
112 3
< 0.1%
ValueCountFrequency (%)
5063 4
0.1%
5062 4
0.1%
5061 3
< 0.1%
5059 4
0.1%
5057 3
< 0.1%
5056 4
0.1%
5055 4
0.1%
5053 4
0.1%
5052 4
0.1%
4902 1
 
< 0.1%

대여소
Text

Distinct2343
Distinct (%)36.3%
Missing0
Missing (%)0.0%
Memory size50.6 KiB
2024-05-18T13:55:38.331078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length31
Mean length15.50395
Min length7

Characters and Unicode

Total characters100078
Distinct characters555
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

Unique353 ?
Unique (%)5.5%

Sample

1st row729. 서부식자재마트 건너편
2nd row731. 서울시 도로환경관리센터
3rd row732. 신월중학교
4th row733. 신정이펜하우스314동
5th row734. 신트리공원 입구
ValueCountFrequency (%)
앞 1659
 
8.9%
출구 267
 
1.4%
옆 248
 
1.3%
1번출구 205
 
1.1%
교차로 161
 
0.9%
사거리 153
 
0.8%
입구 132
 
0.7%
2번출구 130
 
0.7%
뒤 129
 
0.7%
3번출구 124
 
0.7%
Other values (4657) 15520
82.9%
2024-05-18T13:55:39.435578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12385
 
12.4%
. 6474
 
6.5%
1 5219
 
5.2%
2 3933
 
3.9%
3 3095
 
3.1%
4 2842
 
2.8%
5 2415
 
2.4%
0 2293
 
2.3%
6 2287
 
2.3%
7 2209
 
2.2%
Other values (545) 56926
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51560
51.5%
Decimal Number 27551
27.5%
Space Separator 12385
 
12.4%
Other Punctuation 6544
 
6.5%
Uppercase Letter 801
 
0.8%
Close Punctuation 537
 
0.5%
Open Punctuation 537
 
0.5%
Lowercase Letter 93
 
0.1%
Dash Punctuation 48
 
< 0.1%
Math Symbol 10
 
< 0.1%
Other values (2) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2089
 
4.1%
앞 1940
 
3.8%
역 1642
 
3.2%
번 1462
 
2.8%
출 1435
 
2.8%
동 1415
 
2.7%
교 1061
 
2.1%
파 987
 
1.9%
아 937
 
1.8%
리 899
 
1.7%
Other values (489) 37693
73.1%
Uppercase Letter
ValueCountFrequency (%)
S 90
11.2%
K 87
10.9%
T 81
10.1%
C 73
9.1%
A 60
 
7.5%
D 54
 
6.7%
G 54
 
6.7%
B 46
 
5.7%
M 44
 
5.5%
P 43
 
5.4%
Other values (13) 169
21.1%
Decimal Number
ValueCountFrequency (%)
1 5219
18.9%
2 3933
14.3%
3 3095
11.2%
4 2842
10.3%
5 2415
8.8%
0 2293
8.3%
6 2287
8.3%
7 2209
8.0%
8 1689
 
6.1%
9 1569
 
5.7%
Lowercase Letter
ValueCountFrequency (%)
e 36
38.7%
k 16
17.2%
s 13
 
14.0%
n 8
 
8.6%
t 5
 
5.4%
y 4
 
4.3%
l 4
 
4.3%
v 3
 
3.2%
a 2
 
2.2%
g 2
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 6474
98.9%
, 48
 
0.7%
& 13
 
0.2%
? 6
 
0.1%
· 3
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 9
90.0%
+ 1
 
10.0%
Space Separator
ValueCountFrequency (%)
12385
100.0%
Close Punctuation
ValueCountFrequency (%)
) 537
100.0%
Open Punctuation
ValueCountFrequency (%)
( 537
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51564
51.5%
Common 47620
47.6%
Latin 894
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2089
 
4.1%
앞 1940
 
3.8%
역 1642
 
3.2%
번 1462
 
2.8%
출 1435
 
2.8%
동 1415
 
2.7%
교 1061
 
2.1%
파 987
 
1.9%
아 937
 
1.8%
리 899
 
1.7%
Other values (490) 37697
73.1%
Latin
ValueCountFrequency (%)
S 90
 
10.1%
K 87
 
9.7%
T 81
 
9.1%
C 73
 
8.2%
A 60
 
6.7%
D 54
 
6.0%
G 54
 
6.0%
B 46
 
5.1%
M 44
 
4.9%
P 43
 
4.8%
Other values (23) 262
29.3%
Common
ValueCountFrequency (%)
12385
26.0%
. 6474
13.6%
1 5219
11.0%
2 3933
 
8.3%
3 3095
 
6.5%
4 2842
 
6.0%
5 2415
 
5.1%
0 2293
 
4.8%
6 2287
 
4.8%
7 2209
 
4.6%
Other values (12) 4468
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51560
51.5%
ASCII 48511
48.5%
None 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12385
25.5%
. 6474
13.3%
1 5219
10.8%
2 3933
 
8.1%
3 3095
 
6.4%
4 2842
 
5.9%
5 2415
 
5.0%
0 2293
 
4.7%
6 2287
 
4.7%
7 2209
 
4.6%
Other values (44) 5359
11.0%
Hangul
ValueCountFrequency (%)
구 2089
 
4.1%
앞 1940
 
3.8%
역 1642
 
3.2%
번 1462
 
2.8%
출 1435
 
2.8%
동 1415
 
2.7%
교 1061
 
2.1%
파 987
 
1.9%
아 937
 
1.8%
리 899
 
1.7%
Other values (489) 37693
73.1%
None
ValueCountFrequency (%)
㈜ 4
57.1%
· 3
42.9%

대여구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.6 KiB
정기권
6455 

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 6455
100.0%

Length

2024-05-18T13:55:39.830595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:55:40.102036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 6455
100.0%

성별
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6455
Missing (%)100.0%
Memory size56.9 KiB

연령대
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size50.6 KiB
20대
2438 
30대
1944 
40대
1319 
~10대
754 

Length

Max length4
Median length3
Mean length3.1168087
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 2438
37.8%
30대 1944
30.1%
40대 1319
20.4%
~10대 754
 
11.7%

Length

2024-05-18T13:55:40.650319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:55:40.985963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 2438
37.8%
30대 1944
30.1%
40대 1319
20.4%
10대 754
 
11.7%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8264911
Minimum1
Maximum64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size56.9 KiB
2024-05-18T13:55:41.372811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile12
Maximum64
Range63
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.3394057
Coefficient of variation (CV)1.1340431
Kurtosis18.052685
Mean3.8264911
Median Absolute Deviation (MAD)1
Skewness3.2933863
Sum24700
Variance18.830442
MonotonicityNot monotonic
2024-05-18T13:55:41.760779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 2278
35.3%
2 1187
18.4%
3 774
 
12.0%
4 515
 
8.0%
5 380
 
5.9%
6 283
 
4.4%
7 200
 
3.1%
8 171
 
2.6%
9 125
 
1.9%
10 95
 
1.5%
Other values (30) 447
 
6.9%
ValueCountFrequency (%)
1 2278
35.3%
2 1187
18.4%
3 774
 
12.0%
4 515
 
8.0%
5 380
 
5.9%
6 283
 
4.4%
7 200
 
3.1%
8 171
 
2.6%
9 125
 
1.9%
10 95
 
1.5%
ValueCountFrequency (%)
64 1
 
< 0.1%
46 1
 
< 0.1%
42 1
 
< 0.1%
41 1
 
< 0.1%
36 4
0.1%
35 1
 
< 0.1%
34 2
< 0.1%
33 1
 
< 0.1%
32 3
< 0.1%
31 3
< 0.1%

운동량
Text

Distinct5361
Distinct (%)83.1%
Missing0
Missing (%)0.0%
Memory size50.6 KiB
2024-05-18T13:55:42.687383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.3976762
Min length2

Characters and Unicode

Total characters34842
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

Unique4817 ?
Unique (%)74.6%

Sample

1st row131.56
2nd row17.74
3rd row36.80
4th row0.00
5th row131.05
ValueCountFrequency (%)
0.00 447
 
6.9%
n 7
 
0.1%
30.89 5
 
0.1%
17.76 4
 
0.1%
32.38 4
 
0.1%
27.28 4
 
0.1%
11.84 4
 
0.1%
15.44 4
 
0.1%
31.05 4
 
0.1%
87.68 4
 
0.1%
Other values (5351) 5968
92.5%
2024-05-18T13:55:43.919217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6448
18.5%
1 4061
11.7%
0 3570
10.2%
2 3130
9.0%
3 2947
8.5%
4 2735
7.8%
5 2624
7.5%
6 2466
 
7.1%
7 2386
 
6.8%
8 2302
 
6.6%
Other values (3) 2173
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28380
81.5%
Other Punctuation 6455
 
18.5%
Uppercase Letter 7
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4061
14.3%
0 3570
12.6%
2 3130
11.0%
3 2947
10.4%
4 2735
9.6%
5 2624
9.2%
6 2466
8.7%
7 2386
8.4%
8 2302
8.1%
9 2159
7.6%
Other Punctuation
ValueCountFrequency (%)
. 6448
99.9%
\ 7
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34835
> 99.9%
Latin 7
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 6448
18.5%
1 4061
11.7%
0 3570
10.2%
2 3130
9.0%
3 2947
8.5%
4 2735
7.9%
5 2624
7.5%
6 2466
 
7.1%
7 2386
 
6.8%
8 2302
 
6.6%
Other values (2) 2166
 
6.2%
Latin
ValueCountFrequency (%)
N 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34842
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 6448
18.5%
1 4061
11.7%
0 3570
10.2%
2 3130
9.0%
3 2947
8.5%
4 2735
7.8%
5 2624
7.5%
6 2466
 
7.1%
7 2386
 
6.8%
8 2302
 
6.6%
Other values (3) 2173
 
6.2%

탄소량
Text

Distinct735
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size50.6 KiB
2024-05-18T13:55:45.038663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.0051123
Min length2

Characters and Unicode

Total characters25853
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

Unique218 ?
Unique (%)3.4%

Sample

1st row1.45
2nd row0.15
3rd row0.47
4th row0.00
5th row1.10
ValueCountFrequency (%)
0.00 448
 
6.9%
0.20 60
 
0.9%
0.16 58
 
0.9%
0.15 57
 
0.9%
0.23 51
 
0.8%
0.32 51
 
0.8%
0.31 49
 
0.8%
0.27 48
 
0.7%
0.35 48
 
0.7%
0.18 46
 
0.7%
Other values (725) 5539
85.8%
2024-05-18T13:55:46.953524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6448
24.9%
0 5636
21.8%
1 2777
10.7%
2 2067
 
8.0%
3 1720
 
6.7%
4 1483
 
5.7%
5 1315
 
5.1%
6 1174
 
4.5%
7 1114
 
4.3%
8 1076
 
4.2%
Other values (3) 1043
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19391
75.0%
Other Punctuation 6455
 
25.0%
Uppercase Letter 7
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5636
29.1%
1 2777
14.3%
2 2067
 
10.7%
3 1720
 
8.9%
4 1483
 
7.6%
5 1315
 
6.8%
6 1174
 
6.1%
7 1114
 
5.7%
8 1076
 
5.5%
9 1029
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 6448
99.9%
\ 7
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25846
> 99.9%
Latin 7
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 6448
24.9%
0 5636
21.8%
1 2777
10.7%
2 2067
 
8.0%
3 1720
 
6.7%
4 1483
 
5.7%
5 1315
 
5.1%
6 1174
 
4.5%
7 1114
 
4.3%
8 1076
 
4.2%
Other values (2) 1036
 
4.0%
Latin
ValueCountFrequency (%)
N 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25853
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 6448
24.9%
0 5636
21.8%
1 2777
10.7%
2 2067
 
8.0%
3 1720
 
6.7%
4 1483
 
5.7%
5 1315
 
5.1%
6 1174
 
4.5%
7 1114
 
4.3%
8 1076
 
4.2%
Other values (3) 1043
 
4.0%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct5131
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6425.5053
Minimum0
Maximum79758.03
Zeros454
Zeros (%)7.0%
Negative0
Negative (%)0.0%
Memory size56.9 KiB
2024-05-18T13:55:47.750025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11385.11
median3612.36
Q38359.685
95-th percentile22118.271
Maximum79758.03
Range79758.03
Interquartile range (IQR)6974.575

Descriptive statistics

Standard deviation8074.3376
Coefficient of variation (CV)1.2566074
Kurtosis11.279509
Mean6425.5053
Median Absolute Deviation (MAD)2724.13
Skewness2.8065647
Sum41476637
Variance65194927
MonotonicityNot monotonic
2024-05-18T13:55:48.441752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 454
 
7.0%
1360.0 10
 
0.2%
600.0 9
 
0.1%
1120.0 9
 
0.1%
980.0 9
 
0.1%
1980.0 9
 
0.1%
1390.0 9
 
0.1%
880.0 8
 
0.1%
2120.0 8
 
0.1%
1650.0 8
 
0.1%
Other values (5121) 5922
91.7%
ValueCountFrequency (%)
0.0 454
7.0%
20.0 1
 
< 0.1%
30.0 1
 
< 0.1%
70.0 2
 
< 0.1%
88.1 1
 
< 0.1%
88.13 1
 
< 0.1%
88.14 2
 
< 0.1%
88.16 1
 
< 0.1%
88.18 1
 
< 0.1%
88.19 1
 
< 0.1%
ValueCountFrequency (%)
79758.03 1
< 0.1%
74073.18 1
< 0.1%
67301.39 1
< 0.1%
65660.0 1
< 0.1%
65431.82 1
< 0.1%
61227.06 1
< 0.1%
61129.57 1
< 0.1%
61118.64 1
< 0.1%
60919.93 1
< 0.1%
60205.93 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct378
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.300077
Minimum0
Maximum740
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size56.9 KiB
2024-05-18T13:55:49.075209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q114
median36
Q376
95-th percentile203
Maximum740
Range740
Interquartile range (IQR)62

Descriptive statistics

Standard deviation73.500224
Coefficient of variation (CV)1.2189076
Kurtosis12.376884
Mean60.300077
Median Absolute Deviation (MAD)26
Skewness2.8913659
Sum389237
Variance5402.2829
MonotonicityNot monotonic
2024-05-18T13:55:49.561239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 158
 
2.4%
6 150
 
2.3%
8 148
 
2.3%
7 143
 
2.2%
4 140
 
2.2%
3 126
 
2.0%
10 125
 
1.9%
13 124
 
1.9%
9 121
 
1.9%
11 116
 
1.8%
Other values (368) 5104
79.1%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 35
 
0.5%
2 77
1.2%
3 126
2.0%
4 140
2.2%
5 158
2.4%
6 150
2.3%
7 143
2.2%
8 148
2.3%
9 121
1.9%
ValueCountFrequency (%)
740 1
< 0.1%
679 1
< 0.1%
673 1
< 0.1%
666 1
< 0.1%
647 1
< 0.1%
636 1
< 0.1%
625 1
< 0.1%
608 1
< 0.1%
585 1
< 0.1%
569 1
< 0.1%

Interactions

2024-05-18T13:55:33.974380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:29.958956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:31.357628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:32.706861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:34.286669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:30.339972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:31.724918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:33.022669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:34.704070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:30.668108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:32.091506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:33.326279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:35.074834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:31.005701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:32.401481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:33.660275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T13:55:49.924039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호연령대이용건수이동거리(M)이용시간(분)
대여소번호1.0000.1100.0950.0760.100
연령대0.1101.0000.2970.3140.319
이용건수0.0950.2971.0000.6510.741
이동거리(M)0.0760.3140.6511.0000.888
이용시간(분)0.1000.3190.7410.8881.000
2024-05-18T13:55:50.628804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)연령대
대여소번호1.000-0.082-0.069-0.0780.066
이용건수-0.0821.0000.7750.8290.194
이동거리(M)-0.0690.7751.0000.8680.192
이용시간(분)-0.0780.8290.8681.0000.196
연령대0.0660.1940.1920.1961.000

Missing values

2024-05-18T13:55:35.578397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T13:55:36.225957image/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)
02021-10-01729729. 서부식자재마트 건너편정기권<NA>~10대3131.561.456233.1236
12021-10-01731731. 서울시 도로환경관리센터정기권<NA>~10대117.740.15640.06
22021-10-01732732. 신월중학교정기권<NA>~10대136.800.472020.037
32021-10-01733733. 신정이펜하우스314동정기권<NA>~10대10.000.000.08
42021-10-01734734. 신트리공원 입구정기권<NA>~10대2131.051.104727.3843
52021-10-01735735. 영도초등학교정기권<NA>~10대393.670.913959.2663
62021-10-01739739. 신월사거리정기권<NA>~10대117.900.15645.664
72021-10-01740740. 으뜸공원정기권<NA>~10대250.270.512194.5649
82021-10-01742742. 등촌역 5번 출구 뒤정기권<NA>~10대118.060.20860.319
92021-10-01744744. 신목동역 2번 출구정기권<NA>~10대118.820.20864.326
대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
64452021-10-0114011401. 극동늘푸른아파트정기권<NA>40대10.000.000.08
64462021-10-0113141314. 정릉꿈에그린1단지 201동 앞정기권<NA>40대1106.521.255380.034
64472021-10-01210210. IFC몰정기권<NA>40대7156.141.295566.8143
64482021-10-0114021402. 금란주차장 앞정기권<NA>40대10.000.000.029
64492021-10-0113181318. 길음역 3번출구 뒤정기권<NA>40대555.860.421835.4441
64502021-10-0113181318. 길음역 3번출구 뒤정기권<NA>40대169.210.843640.8627
64512021-10-0113191319. 종암사거리 분수대정기권<NA>40대2238.842.068869.6101
64522021-10-0114031403. 중화빌딩 앞 (동부시장)정기권<NA>40대3252.502.3910307.18103
64532021-10-0114051405. 망우역 1번출구정기권<NA>40대235.880.301323.495
64542021-10-01211211. 여의도역 4번출구 옆정기권<NA>40대246.160.401702.613