Overview

Dataset statistics

Number of variables11
Number of observations4984
Missing cells4984
Missing cells (%)9.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory452.8 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 4984 (100.0%) missing valuesMissing
성별 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-13 16:28:52.830668
Analysis finished2024-03-13 16:28:55.119898
Duration2.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
Minimum2023-09-01 00:00:00
Maximum2023-09-01 00:00:00
2024-03-14T01:28:55.155426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:55.222388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

대여소번호
Real number (ℝ)

Distinct2452
Distinct (%)49.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2109.3355
Minimum102
Maximum6054
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.9 KiB
2024-03-14T01:28:55.310810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile267.15
Q1902.75
median1760
Q33202
95-th percentile4810.7
Maximum6054
Range5952
Interquartile range (IQR)2299.25

Descriptive statistics

Standard deviation1464.1008
Coefficient of variation (CV)0.69410522
Kurtosis-0.70531803
Mean2109.3355
Median Absolute Deviation (MAD)986
Skewness0.59985845
Sum10512928
Variance2143591
MonotonicityNot monotonic
2024-03-14T01:28:55.422670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2648 6
 
0.1%
1691 6
 
0.1%
2728 6
 
0.1%
765 6
 
0.1%
1153 6
 
0.1%
792 6
 
0.1%
2723 5
 
0.1%
2717 5
 
0.1%
1182 5
 
0.1%
1180 5
 
0.1%
Other values (2442) 4928
98.9%
ValueCountFrequency (%)
102 2
< 0.1%
103 2
< 0.1%
104 2
< 0.1%
105 2
< 0.1%
106 2
< 0.1%
107 1
 
< 0.1%
108 1
 
< 0.1%
109 2
< 0.1%
111 1
 
< 0.1%
112 4
0.1%
ValueCountFrequency (%)
6054 1
 
< 0.1%
5871 2
< 0.1%
5870 1
 
< 0.1%
5869 1
 
< 0.1%
5868 2
< 0.1%
5867 2
< 0.1%
5866 1
 
< 0.1%
5865 2
< 0.1%
5864 1
 
< 0.1%
5862 3
0.1%

대여소
Text

Distinct2452
Distinct (%)49.2%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
2024-03-14T01:28:55.633065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length32
Mean length15.514246
Min length7

Characters and Unicode

Total characters77323
Distinct characters574
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique893 ?
Unique (%)17.9%

Sample

1st row731. 서울시 도로환경관리센터
2nd row735. 영도초등학교
3rd row744. 신목동역 2번 출구
4th row746. 목동2단지 상가
5th row747. 목동3단지 상가
ValueCountFrequency (%)
앞 1275
 
8.8%
출구 236
 
1.6%
옆 170
 
1.2%
1번출구 169
 
1.2%
교차로 127
 
0.9%
사거리 121
 
0.8%
입구 111
 
0.8%
3번출구 107
 
0.7%
뒤 107
 
0.7%
2번출구 97
 
0.7%
Other values (4917) 11998
82.6%
2024-03-14T01:28:55.958576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9642
 
12.5%
. 4995
 
6.5%
1 3897
 
5.0%
2 2943
 
3.8%
3 2402
 
3.1%
4 2294
 
3.0%
5 1910
 
2.5%
0 1728
 
2.2%
6 1723
 
2.2%
구 1690
 
2.2%
Other values (564) 44099
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39786
51.5%
Decimal Number 21292
27.5%
Space Separator 9642
 
12.5%
Other Punctuation 5060
 
6.5%
Uppercase Letter 657
 
0.8%
Open Punctuation 383
 
0.5%
Close Punctuation 383
 
0.5%
Lowercase Letter 81
 
0.1%
Dash Punctuation 27
 
< 0.1%
Math Symbol 8
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1690
 
4.2%
앞 1471
 
3.7%
역 1314
 
3.3%
번 1151
 
2.9%
출 1119
 
2.8%
동 1096
 
2.8%
교 803
 
2.0%
파 768
 
1.9%
아 726
 
1.8%
트 697
 
1.8%
Other values (504) 28951
72.8%
Uppercase Letter
ValueCountFrequency (%)
S 70
10.7%
A 69
10.5%
K 62
9.4%
C 57
8.7%
T 56
 
8.5%
B 51
 
7.8%
G 46
 
7.0%
D 39
 
5.9%
L 37
 
5.6%
M 30
 
4.6%
Other values (14) 140
21.3%
Lowercase Letter
ValueCountFrequency (%)
e 26
32.1%
k 13
16.0%
s 13
16.0%
n 8
 
9.9%
l 4
 
4.9%
y 4
 
4.9%
t 3
 
3.7%
v 2
 
2.5%
r 2
 
2.5%
h 2
 
2.5%
Other values (3) 4
 
4.9%
Decimal Number
ValueCountFrequency (%)
1 3897
18.3%
2 2943
13.8%
3 2402
11.3%
4 2294
10.8%
5 1910
9.0%
0 1728
8.1%
6 1723
8.1%
7 1682
7.9%
8 1435
 
6.7%
9 1278
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 4995
98.7%
, 42
 
0.8%
& 13
 
0.3%
? 7
 
0.1%
· 3
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 5
62.5%
+ 3
37.5%
Space Separator
ValueCountFrequency (%)
9642
100.0%
Open Punctuation
ValueCountFrequency (%)
( 383
100.0%
Close Punctuation
ValueCountFrequency (%)
) 383
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Other Number
ValueCountFrequency (%)
② 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39786
51.5%
Common 36799
47.6%
Latin 738
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1690
 
4.2%
앞 1471
 
3.7%
역 1314
 
3.3%
번 1151
 
2.9%
출 1119
 
2.8%
동 1096
 
2.8%
교 803
 
2.0%
파 768
 
1.9%
아 726
 
1.8%
트 697
 
1.8%
Other values (504) 28951
72.8%
Latin
ValueCountFrequency (%)
S 70
 
9.5%
A 69
 
9.3%
K 62
 
8.4%
C 57
 
7.7%
T 56
 
7.6%
B 51
 
6.9%
G 46
 
6.2%
D 39
 
5.3%
L 37
 
5.0%
M 30
 
4.1%
Other values (27) 221
29.9%
Common
ValueCountFrequency (%)
9642
26.2%
. 4995
13.6%
1 3897
10.6%
2 2943
 
8.0%
3 2402
 
6.5%
4 2294
 
6.2%
5 1910
 
5.2%
0 1728
 
4.7%
6 1723
 
4.7%
7 1682
 
4.6%
Other values (13) 3583
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39786
51.5%
ASCII 37533
48.5%
None 3
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9642
25.7%
. 4995
13.3%
1 3897
10.4%
2 2943
 
7.8%
3 2402
 
6.4%
4 2294
 
6.1%
5 1910
 
5.1%
0 1728
 
4.6%
6 1723
 
4.6%
7 1682
 
4.5%
Other values (48) 4317
11.5%
Hangul
ValueCountFrequency (%)
구 1690
 
4.2%
앞 1471
 
3.7%
역 1314
 
3.3%
번 1151
 
2.9%
출 1119
 
2.8%
동 1096
 
2.8%
교 803
 
2.0%
파 768
 
1.9%
아 726
 
1.8%
트 697
 
1.8%
Other values (504) 28951
72.8%
None
ValueCountFrequency (%)
· 3
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
② 1
100.0%

대여구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
정기권
4984 

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 4984
100.0%

Length

2024-03-14T01:28:56.061346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:28:56.128999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 4984
100.0%

성별
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4984
Missing (%)100.0%
Memory size43.9 KiB

연령대
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
20대
3434 
30대
1165 
~10대
385 

Length

Max length4
Median length3
Mean length3.0772472
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 3434
68.9%
30대 1165
 
23.4%
~10대 385
 
7.7%

Length

2024-03-14T01:28:56.204397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:28:56.275312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 3434
68.9%
30대 1165
 
23.4%
10대 385
 
7.7%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8250401
Minimum1
Maximum61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.9 KiB
2024-03-14T01:28:56.354234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile13
Maximum61
Range60
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.3917496
Coefficient of variation (CV)1.1481578
Kurtosis18.565269
Mean3.8250401
Median Absolute Deviation (MAD)1
Skewness3.2575256
Sum19064
Variance19.287464
MonotonicityNot monotonic
2024-03-14T01:28:56.448877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1 1830
36.7%
2 899
18.0%
3 566
 
11.4%
4 395
 
7.9%
5 272
 
5.5%
6 223
 
4.5%
7 141
 
2.8%
8 122
 
2.4%
9 80
 
1.6%
10 76
 
1.5%
Other values (27) 380
 
7.6%
ValueCountFrequency (%)
1 1830
36.7%
2 899
18.0%
3 566
 
11.4%
4 395
 
7.9%
5 272
 
5.5%
6 223
 
4.5%
7 141
 
2.8%
8 122
 
2.4%
9 80
 
1.6%
10 76
 
1.5%
ValueCountFrequency (%)
61 1
 
< 0.1%
58 1
 
< 0.1%
36 2
< 0.1%
35 1
 
< 0.1%
34 3
0.1%
33 1
 
< 0.1%
31 1
 
< 0.1%
30 1
 
< 0.1%
29 4
0.1%
28 3
0.1%

운동량
Text

Distinct4483
Distinct (%)89.9%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
2024-03-14T01:28:56.752853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.4676966
Min length2

Characters and Unicode

Total characters27251
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

Unique4091 ?
Unique (%)82.1%

Sample

1st row49.99
2nd row12.69
3rd row41.62
4th row14.16
5th row74.70
ValueCountFrequency (%)
0.00 42
 
0.8%
n 8
 
0.2%
38.61 5
 
0.1%
21.36 4
 
0.1%
41.18 4
 
0.1%
49.69 4
 
0.1%
35.01 4
 
0.1%
16.47 4
 
0.1%
24.39 4
 
0.1%
28.06 4
 
0.1%
Other values (4473) 4901
98.3%
2024-03-14T01:28:57.163886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4976
18.3%
1 3180
11.7%
2 2673
9.8%
3 2511
9.2%
4 2197
8.1%
6 2047
7.5%
5 2032
7.5%
0 1948
 
7.1%
7 1934
 
7.1%
9 1869
 
6.9%
Other values (3) 1884
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22259
81.7%
Other Punctuation 4984
 
18.3%
Uppercase Letter 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3180
14.3%
2 2673
12.0%
3 2511
11.3%
4 2197
9.9%
6 2047
9.2%
5 2032
9.1%
0 1948
8.8%
7 1934
8.7%
9 1869
8.4%
8 1868
8.4%
Other Punctuation
ValueCountFrequency (%)
. 4976
99.8%
\ 8
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27243
> 99.9%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4976
18.3%
1 3180
11.7%
2 2673
9.8%
3 2511
9.2%
4 2197
8.1%
6 2047
7.5%
5 2032
7.5%
0 1948
 
7.2%
7 1934
 
7.1%
9 1869
 
6.9%
Other values (2) 1876
 
6.9%
Latin
ValueCountFrequency (%)
N 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27251
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4976
18.3%
1 3180
11.7%
2 2673
9.8%
3 2511
9.2%
4 2197
8.1%
6 2047
7.5%
5 2032
7.5%
0 1948
 
7.1%
7 1934
 
7.1%
9 1869
 
6.9%
Other values (3) 1884
 
6.9%

탄소량
Text

Distinct702
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
2024-03-14T01:28:57.489440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.0032103
Min length2

Characters and Unicode

Total characters19952
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

Unique212 ?
Unique (%)4.3%

Sample

1st row0.48
2nd row0.17
3rd row0.41
4th row0.15
5th row0.84
ValueCountFrequency (%)
0.18 60
 
1.2%
0.17 53
 
1.1%
0.26 52
 
1.0%
0.19 47
 
0.9%
0.33 46
 
0.9%
0.16 46
 
0.9%
0.20 44
 
0.9%
0.42 44
 
0.9%
0.29 44
 
0.9%
0.00 44
 
0.9%
Other values (692) 4504
90.4%
2024-03-14T01:28:57.906488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4976
24.9%
0 3664
18.4%
1 2242
11.2%
2 1706
 
8.6%
3 1467
 
7.4%
4 1178
 
5.9%
5 1051
 
5.3%
6 1014
 
5.1%
7 972
 
4.9%
8 873
 
4.4%
Other values (3) 809
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14960
75.0%
Other Punctuation 4984
 
25.0%
Uppercase Letter 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3664
24.5%
1 2242
15.0%
2 1706
11.4%
3 1467
9.8%
4 1178
 
7.9%
5 1051
 
7.0%
6 1014
 
6.8%
7 972
 
6.5%
8 873
 
5.8%
9 793
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 4976
99.8%
\ 8
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19944
> 99.9%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4976
24.9%
0 3664
18.4%
1 2242
11.2%
2 1706
 
8.6%
3 1467
 
7.4%
4 1178
 
5.9%
5 1051
 
5.3%
6 1014
 
5.1%
7 972
 
4.9%
8 873
 
4.4%
Other values (2) 801
 
4.0%
Latin
ValueCountFrequency (%)
N 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4976
24.9%
0 3664
18.4%
1 2242
11.2%
2 1706
 
8.6%
3 1467
 
7.4%
4 1178
 
5.9%
5 1051
 
5.3%
6 1014
 
5.1%
7 972
 
4.9%
8 873
 
4.4%
Other values (3) 809
 
4.1%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION 

Distinct4363
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6918.0918
Minimum0
Maximum147917.5
Zeros41
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size43.9 KiB
2024-03-14T01:28:58.020922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile551.647
Q11611.4775
median3871.985
Q39147.05
95-th percentile23105.474
Maximum147917.5
Range147917.5
Interquartile range (IQR)7535.5725

Descriptive statistics

Standard deviation8640.6446
Coefficient of variation (CV)1.2489925
Kurtosis35.916487
Mean6918.0918
Median Absolute Deviation (MAD)2776.71
Skewness4.0163955
Sum34479769
Variance74660739
MonotonicityNot monotonic
2024-03-14T01:28:58.137230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 41
 
0.8%
780.0 10
 
0.2%
1090.0 10
 
0.2%
1500.0 8
 
0.2%
730.0 8
 
0.2%
1420.0 8
 
0.2%
2030.0 8
 
0.2%
410.0 8
 
0.2%
960.0 8
 
0.2%
480.0 7
 
0.1%
Other values (4353) 4868
97.7%
ValueCountFrequency (%)
0.0 41
0.8%
0.13 1
 
< 0.1%
10.0 2
 
< 0.1%
20.0 1
 
< 0.1%
40.0 1
 
< 0.1%
60.0 1
 
< 0.1%
80.0 1
 
< 0.1%
89.0 1
 
< 0.1%
117.27 1
 
< 0.1%
130.0 1
 
< 0.1%
ValueCountFrequency (%)
147917.5 1
< 0.1%
129516.65 1
< 0.1%
125825.06 1
< 0.1%
69193.89 1
< 0.1%
67453.49 1
< 0.1%
65996.05 1
< 0.1%
64552.88 1
< 0.1%
64499.03 1
< 0.1%
63831.29 1
< 0.1%
62318.72 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct322
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53.071629
Minimum1
Maximum1070
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.9 KiB
2024-03-14T01:28:58.252150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q111
median30
Q369
95-th percentile185
Maximum1070
Range1069
Interquartile range (IQR)58

Descriptive statistics

Standard deviation66.773178
Coefficient of variation (CV)1.2581709
Kurtosis23.69837
Mean53.071629
Median Absolute Deviation (MAD)22
Skewness3.46127
Sum264509
Variance4458.6573
MonotonicityNot monotonic
2024-03-14T01:28:58.357637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 156
 
3.1%
4 145
 
2.9%
5 142
 
2.8%
7 124
 
2.5%
3 118
 
2.4%
11 116
 
2.3%
10 114
 
2.3%
8 113
 
2.3%
9 113
 
2.3%
16 101
 
2.0%
Other values (312) 3742
75.1%
ValueCountFrequency (%)
1 34
 
0.7%
2 77
1.5%
3 118
2.4%
4 145
2.9%
5 142
2.8%
6 156
3.1%
7 124
2.5%
8 113
2.3%
9 113
2.3%
10 114
2.3%
ValueCountFrequency (%)
1070 1
< 0.1%
807 1
< 0.1%
746 1
< 0.1%
557 1
< 0.1%
550 1
< 0.1%
529 1
< 0.1%
487 1
< 0.1%
485 1
< 0.1%
481 1
< 0.1%
474 1
< 0.1%

Interactions

2024-03-14T01:28:54.345189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:53.439715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:53.737425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:54.041675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:54.422951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:53.508616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:53.811466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:54.116060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:54.516901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:53.581685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:53.882060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:54.190888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:54.863922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:53.656831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:53.968363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:54.267723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T01:28:58.424662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호연령대이용건수이동거리(M)이용시간(분)
대여소번호1.0000.3340.0860.0340.046
연령대0.3341.0000.1640.1520.228
이용건수0.0860.1641.0000.8520.723
이동거리(M)0.0340.1520.8521.0000.890
이용시간(분)0.0460.2280.7230.8901.000
2024-03-14T01:28:58.501326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)연령대
대여소번호1.000-0.042-0.041-0.0540.213
이용건수-0.0421.0000.8220.8200.098
이동거리(M)-0.0410.8221.0000.9330.103
이용시간(분)-0.0540.8200.9331.0000.102
연령대0.2130.0980.1030.1021.000

Missing values

2024-03-14T01:28:54.956398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T01:28:55.070835image/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)
02023-09-01731731. 서울시 도로환경관리센터정기권<NA>~10대249.990.482059.8618
12023-09-01735735. 영도초등학교정기권<NA>~10대112.690.17712.246
22023-09-01744744. 신목동역 2번 출구정기권<NA>~10대141.620.411751.8425
32023-09-01746746. 목동2단지 상가정기권<NA>~10대114.160.15650.03
42023-09-01747747. 목동3단지 상가정기권<NA>~10대174.700.843627.6824
52023-09-01748748. 목동운동장정기권<NA>~10대14.940.06240.06
62023-09-01948948. 디지털미디어 시티역 4번출구(DMC역)정기권<NA>~10대19.310.11470.02
72023-09-0111501150. 송정역 1번출구정기권<NA>~10대252.250.522265.5815
82023-09-0111521152. 마곡역교차로정기권<NA>~10대139.450.291245.1610
92023-09-0111531153. 발산역 1번, 9번 인근 대여소정기권<NA>~10대283.270.743168.8920
대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
49742023-09-01848848. 삼각지12번 출구정기권<NA>30대169.650.411758.896
49752023-09-01849849. 삼각지 자이아파트정기권<NA>30대220.790.17750.177
49762023-09-01850850. KCC용산월츠타워정기권<NA>30대2192.021.225285.3141
49772023-09-01852852. 청암자이아파트 앞정기권<NA>30대290.760.833581.3916
49782023-09-01852852. 청암자이아파트 앞정기권<NA>30대342.980.763309.3627
49792023-09-01853853.용산역 맞은편정기권<NA>30대5583.304.5619624.43129
49802023-09-01853853.용산역 맞은편정기권<NA>30대2528.473.9316945.7366
49812023-09-01857857. 현대 안성타워정기권<NA>30대264.200.445882.33101
49822023-09-01860860.LG한강 자이아파트 앞정기권<NA>30대3491.183.8016394.797
49832023-09-01863863.이촌역2번 출구정기권<NA>30대178.610.713054.1434