Overview

Dataset statistics

Number of variables11
Number of observations5567
Missing cells5567
Missing cells (%)9.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory505.7 KiB
Average record size in memory93.0 B

Variable types

Categorical3
Numeric4
Text3
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 5567 (100.0%) missing valuesMissing
성별 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-13 16:28:02.180114
Analysis finished2024-03-13 16:28:04.154798
Duration1.97 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size43.6 KiB
2023-04-01
5567 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-04-01
2nd row2023-04-01
3rd row2023-04-01
4th row2023-04-01
5th row2023-04-01

Common Values

ValueCountFrequency (%)
2023-04-01 5567
100.0%

Length

2024-03-14T01:28:04.210862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:28:04.287152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-04-01 5567
100.0%

대여소번호
Real number (ℝ)

Distinct2410
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2147.6012
Minimum102
Maximum6054
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.1 KiB
2024-03-14T01:28:04.366041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile254
Q1916
median1742
Q33516
95-th percentile4825.7
Maximum6054
Range5952
Interquartile range (IQR)2600

Descriptive statistics

Standard deviation1497.3768
Coefficient of variation (CV)0.69723224
Kurtosis-0.84168378
Mean2147.6012
Median Absolute Deviation (MAD)998
Skewness0.5668775
Sum11955696
Variance2242137.3
MonotonicityNot monotonic
2024-03-14T01:28:04.683403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1297 7
 
0.1%
792 6
 
0.1%
2622 6
 
0.1%
2715 6
 
0.1%
2601 6
 
0.1%
2608 6
 
0.1%
2630 6
 
0.1%
765 6
 
0.1%
1278 6
 
0.1%
2728 6
 
0.1%
Other values (2400) 5506
98.9%
ValueCountFrequency (%)
102 3
0.1%
103 3
0.1%
104 3
0.1%
105 2
< 0.1%
106 2
< 0.1%
107 3
0.1%
108 2
< 0.1%
109 3
0.1%
111 2
< 0.1%
112 1
 
< 0.1%
ValueCountFrequency (%)
6054 2
< 0.1%
5866 2
< 0.1%
5865 3
0.1%
5864 1
 
< 0.1%
5862 3
0.1%
5861 2
< 0.1%
5860 2
< 0.1%
5859 2
< 0.1%
5858 2
< 0.1%
5857 2
< 0.1%

대여소
Text

Distinct2410
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Memory size43.6 KiB
2024-03-14T01:28:04.892783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length31
Mean length15.531345
Min length7

Characters and Unicode

Total characters86463
Distinct characters566
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique590 ?
Unique (%)10.6%

Sample

1st row731. 서울시 도로환경관리센터
2nd row732. 신월중학교
3rd row735. 영도초등학교
4th row747. 목동3단지 상가
5th row1029. 성내어울터
ValueCountFrequency (%)
앞 1460
 
8.9%
출구 264
 
1.6%
옆 205
 
1.3%
1번출구 179
 
1.1%
교차로 136
 
0.8%
사거리 116
 
0.7%
입구 115
 
0.7%
뒤 114
 
0.7%
3번출구 109
 
0.7%
2번출구 106
 
0.6%
Other values (4838) 13526
82.8%
2024-03-14T01:28:05.230236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10879
 
12.6%
. 5576
 
6.4%
1 4437
 
5.1%
2 3268
 
3.8%
4 2635
 
3.0%
3 2617
 
3.0%
5 2139
 
2.5%
6 1991
 
2.3%
0 1933
 
2.2%
7 1820
 
2.1%
Other values (556) 49168
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44509
51.5%
Decimal Number 23812
27.5%
Space Separator 10879
 
12.6%
Other Punctuation 5648
 
6.5%
Uppercase Letter 612
 
0.7%
Close Punctuation 434
 
0.5%
Open Punctuation 434
 
0.5%
Lowercase Letter 79
 
0.1%
Dash Punctuation 37
 
< 0.1%
Connector Punctuation 6
 
< 0.1%
Other values (3) 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1797
 
4.0%
앞 1681
 
3.8%
역 1441
 
3.2%
번 1273
 
2.9%
출 1237
 
2.8%
동 1212
 
2.7%
교 953
 
2.1%
파 853
 
1.9%
아 788
 
1.8%
트 753
 
1.7%
Other values (495) 32521
73.1%
Uppercase Letter
ValueCountFrequency (%)
S 67
10.9%
K 64
10.5%
T 62
10.1%
A 57
9.3%
C 52
 
8.5%
G 39
 
6.4%
I 37
 
6.0%
B 36
 
5.9%
D 35
 
5.7%
M 30
 
4.9%
Other values (13) 133
21.7%
Lowercase Letter
ValueCountFrequency (%)
e 31
39.2%
s 12
 
15.2%
k 12
 
15.2%
t 4
 
5.1%
n 4
 
5.1%
l 2
 
2.5%
y 2
 
2.5%
a 2
 
2.5%
g 2
 
2.5%
v 2
 
2.5%
Other values (3) 6
 
7.6%
Decimal Number
ValueCountFrequency (%)
1 4437
18.6%
2 3268
13.7%
4 2635
11.1%
3 2617
11.0%
5 2139
9.0%
6 1991
8.4%
0 1933
8.1%
7 1820
7.6%
8 1608
 
6.8%
9 1364
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 5576
98.7%
, 47
 
0.8%
& 12
 
0.2%
· 7
 
0.1%
? 6
 
0.1%
Other Number
ValueCountFrequency (%)
① 4
66.7%
② 2
33.3%
Math Symbol
ValueCountFrequency (%)
~ 4
80.0%
+ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
10879
100.0%
Close Punctuation
ValueCountFrequency (%)
) 434
100.0%
Open Punctuation
ValueCountFrequency (%)
( 434
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44511
51.5%
Common 41261
47.7%
Latin 691
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1797
 
4.0%
앞 1681
 
3.8%
역 1441
 
3.2%
번 1273
 
2.9%
출 1237
 
2.8%
동 1212
 
2.7%
교 953
 
2.1%
파 853
 
1.9%
아 788
 
1.8%
트 753
 
1.7%
Other values (496) 32523
73.1%
Latin
ValueCountFrequency (%)
S 67
 
9.7%
K 64
 
9.3%
T 62
 
9.0%
A 57
 
8.2%
C 52
 
7.5%
G 39
 
5.6%
I 37
 
5.4%
B 36
 
5.2%
D 35
 
5.1%
e 31
 
4.5%
Other values (26) 211
30.5%
Common
ValueCountFrequency (%)
10879
26.4%
. 5576
13.5%
1 4437
10.8%
2 3268
 
7.9%
4 2635
 
6.4%
3 2617
 
6.3%
5 2139
 
5.2%
6 1991
 
4.8%
0 1933
 
4.7%
7 1820
 
4.4%
Other values (14) 3966
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44509
51.5%
ASCII 41939
48.5%
None 9
 
< 0.1%
Enclosed Alphanum 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10879
25.9%
. 5576
13.3%
1 4437
10.6%
2 3268
 
7.8%
4 2635
 
6.3%
3 2617
 
6.2%
5 2139
 
5.1%
6 1991
 
4.7%
0 1933
 
4.6%
7 1820
 
4.3%
Other values (47) 4644
11.1%
Hangul
ValueCountFrequency (%)
구 1797
 
4.0%
앞 1681
 
3.8%
역 1441
 
3.2%
번 1273
 
2.9%
출 1237
 
2.8%
동 1212
 
2.7%
교 953
 
2.1%
파 853
 
1.9%
아 788
 
1.8%
트 753
 
1.7%
Other values (495) 32521
73.1%
None
ValueCountFrequency (%)
· 7
77.8%
㈜ 2
 
22.2%
Enclosed Alphanum
ValueCountFrequency (%)
① 4
66.7%
② 2
33.3%

대여구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size43.6 KiB
정기권
5567 

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 5567
100.0%

Length

2024-03-14T01:28:05.332260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:28:05.398335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 5567
100.0%

성별
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5567
Missing (%)100.0%
Memory size49.1 KiB

연령대
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size43.6 KiB
20대
2585 
30대
2074 
40대
571 
~10대
337 

Length

Max length4
Median length3
Mean length3.0605353
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 2585
46.4%
30대 2074
37.3%
40대 571
 
10.3%
~10대 337
 
6.1%

Length

2024-03-14T01:28:05.472228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:28:05.548890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 2585
46.4%
30대 2074
37.3%
40대 571
 
10.3%
10대 337
 
6.1%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2417819
Minimum1
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.1 KiB
2024-03-14T01:28:05.632800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile10
Maximum48
Range47
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.6039205
Coefficient of variation (CV)1.1117097
Kurtosis18.028202
Mean3.2417819
Median Absolute Deviation (MAD)1
Skewness3.3209418
Sum18047
Variance12.988243
MonotonicityNot monotonic
2024-03-14T01:28:05.729936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1 2316
41.6%
2 1038
18.6%
3 619
 
11.1%
4 413
 
7.4%
5 297
 
5.3%
6 196
 
3.5%
7 149
 
2.7%
8 119
 
2.1%
9 96
 
1.7%
10 64
 
1.1%
Other values (25) 260
 
4.7%
ValueCountFrequency (%)
1 2316
41.6%
2 1038
18.6%
3 619
 
11.1%
4 413
 
7.4%
5 297
 
5.3%
6 196
 
3.5%
7 149
 
2.7%
8 119
 
2.1%
9 96
 
1.7%
10 64
 
1.1%
ValueCountFrequency (%)
48 1
< 0.1%
43 1
< 0.1%
36 1
< 0.1%
33 2
< 0.1%
32 1
< 0.1%
31 1
< 0.1%
30 1
< 0.1%
29 1
< 0.1%
27 2
< 0.1%
26 2
< 0.1%

운동량
Text

Distinct4985
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size43.6 KiB
2024-03-14T01:28:06.058689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.4788935
Min length2

Characters and Unicode

Total characters30501
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

Unique4527 ?
Unique (%)81.3%

Sample

1st row36.30
2nd row40.06
3rd row28.51
4th row99.16
5th row54.78
ValueCountFrequency (%)
0.00 40
 
0.7%
n 8
 
0.1%
27.80 6
 
0.1%
18.53 6
 
0.1%
20.08 5
 
0.1%
15.65 5
 
0.1%
32.82 4
 
0.1%
23.42 4
 
0.1%
43.76 4
 
0.1%
51.48 4
 
0.1%
Other values (4975) 5481
98.5%
2024-03-14T01:28:06.511404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 5559
18.2%
1 3604
11.8%
2 3049
10.0%
3 2695
8.8%
4 2516
8.2%
5 2342
7.7%
6 2237
7.3%
8 2176
 
7.1%
7 2163
 
7.1%
0 2109
 
6.9%
Other values (3) 2051
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24926
81.7%
Other Punctuation 5567
 
18.3%
Uppercase Letter 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3604
14.5%
2 3049
12.2%
3 2695
10.8%
4 2516
10.1%
5 2342
9.4%
6 2237
9.0%
8 2176
8.7%
7 2163
8.7%
0 2109
8.5%
9 2035
8.2%
Other Punctuation
ValueCountFrequency (%)
. 5559
99.9%
\ 8
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30493
> 99.9%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 5559
18.2%
1 3604
11.8%
2 3049
10.0%
3 2695
8.8%
4 2516
8.3%
5 2342
7.7%
6 2237
7.3%
8 2176
 
7.1%
7 2163
 
7.1%
0 2109
 
6.9%
Other values (2) 2043
 
6.7%
Latin
ValueCountFrequency (%)
N 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30501
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 5559
18.2%
1 3604
11.8%
2 3049
10.0%
3 2695
8.8%
4 2516
8.2%
5 2342
7.7%
6 2237
7.3%
8 2176
 
7.1%
7 2163
 
7.1%
0 2109
 
6.9%
Other values (3) 2051
 
6.7%

탄소량
Text

Distinct736
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size43.6 KiB
2024-03-14T01:28:06.857445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.0070056
Min length2

Characters and Unicode

Total characters22307
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

Unique235 ?
Unique (%)4.2%

Sample

1st row0.30
2nd row0.35
3rd row0.42
4th row0.74
5th row0.52
ValueCountFrequency (%)
0.29 63
 
1.1%
0.23 57
 
1.0%
0.19 57
 
1.0%
0.21 55
 
1.0%
0.22 51
 
0.9%
0.24 50
 
0.9%
0.28 49
 
0.9%
0.15 48
 
0.9%
0.16 48
 
0.9%
0.35 47
 
0.8%
Other values (726) 5042
90.6%
2024-03-14T01:28:07.304033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 5559
24.9%
0 4059
18.2%
1 2529
11.3%
2 1911
 
8.6%
3 1584
 
7.1%
4 1333
 
6.0%
5 1204
 
5.4%
6 1106
 
5.0%
7 1047
 
4.7%
8 994
 
4.5%
Other values (3) 981
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16732
75.0%
Other Punctuation 5567
 
25.0%
Uppercase Letter 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4059
24.3%
1 2529
15.1%
2 1911
11.4%
3 1584
 
9.5%
4 1333
 
8.0%
5 1204
 
7.2%
6 1106
 
6.6%
7 1047
 
6.3%
8 994
 
5.9%
9 965
 
5.8%
Other Punctuation
ValueCountFrequency (%)
. 5559
99.9%
\ 8
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22299
> 99.9%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 5559
24.9%
0 4059
18.2%
1 2529
11.3%
2 1911
 
8.6%
3 1584
 
7.1%
4 1333
 
6.0%
5 1204
 
5.4%
6 1106
 
5.0%
7 1047
 
4.7%
8 994
 
4.5%
Other values (2) 973
 
4.4%
Latin
ValueCountFrequency (%)
N 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22307
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 5559
24.9%
0 4059
18.2%
1 2529
11.3%
2 1911
 
8.6%
3 1584
 
7.1%
4 1333
 
6.0%
5 1204
 
5.4%
6 1106
 
5.0%
7 1047
 
4.7%
8 994
 
4.5%
Other values (3) 981
 
4.4%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION 

Distinct4758
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6944.3929
Minimum0
Maximum216193.51
Zeros47
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size49.1 KiB
2024-03-14T01:28:07.421472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile590
Q11620.775
median3800
Q38618.435
95-th percentile23475.282
Maximum216193.51
Range216193.51
Interquartile range (IQR)6997.66

Descriptive statistics

Standard deviation9344.1615
Coefficient of variation (CV)1.3455692
Kurtosis64.617761
Mean6944.3929
Median Absolute Deviation (MAD)2660
Skewness5.2132237
Sum38659435
Variance87313354
MonotonicityNot monotonic
2024-03-14T01:28:07.521191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 47
 
0.8%
1170.0 12
 
0.2%
800.0 11
 
0.2%
750.0 10
 
0.2%
1430.0 10
 
0.2%
1080.0 9
 
0.2%
920.0 9
 
0.2%
590.0 8
 
0.1%
780.0 8
 
0.1%
490.0 8
 
0.1%
Other values (4748) 5435
97.6%
ValueCountFrequency (%)
0.0 47
0.8%
20.0 1
 
< 0.1%
26.44 1
 
< 0.1%
30.0 1
 
< 0.1%
39.73 1
 
< 0.1%
40.0 1
 
< 0.1%
43.4 1
 
< 0.1%
70.0 3
 
0.1%
80.0 1
 
< 0.1%
88.19 1
 
< 0.1%
ValueCountFrequency (%)
216193.51 1
< 0.1%
129548.89 1
< 0.1%
124026.27 1
< 0.1%
92500.05 1
< 0.1%
88271.02 1
< 0.1%
83175.72 1
< 0.1%
75703.49 1
< 0.1%
74529.72 1
< 0.1%
74457.02 1
< 0.1%
67960.37 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct354
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.625112
Minimum0
Maximum1465
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size49.1 KiB
2024-03-14T01:28:07.617790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q112
median31
Q369
95-th percentile189
Maximum1465
Range1465
Interquartile range (IQR)57

Descriptive statistics

Standard deviation75.727931
Coefficient of variation (CV)1.3613983
Kurtosis47.785529
Mean55.625112
Median Absolute Deviation (MAD)22
Skewness4.8186985
Sum309665
Variance5734.7195
MonotonicityNot monotonic
2024-03-14T01:28:07.724319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 170
 
3.1%
6 153
 
2.7%
7 145
 
2.6%
9 142
 
2.6%
8 136
 
2.4%
4 134
 
2.4%
3 120
 
2.2%
11 113
 
2.0%
10 109
 
2.0%
12 107
 
1.9%
Other values (344) 4238
76.1%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 29
 
0.5%
2 58
 
1.0%
3 120
2.2%
4 134
2.4%
5 170
3.1%
6 153
2.7%
7 145
2.6%
8 136
2.4%
9 142
2.6%
ValueCountFrequency (%)
1465 1
< 0.1%
1164 1
< 0.1%
1032 1
< 0.1%
835 1
< 0.1%
813 1
< 0.1%
718 1
< 0.1%
717 1
< 0.1%
711 1
< 0.1%
637 1
< 0.1%
617 1
< 0.1%

Interactions

2024-03-14T01:28:03.590288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:02.768479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:03.047446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:03.322847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:03.664686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:02.838196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:03.117224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:03.392476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:03.736523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:02.908476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:03.183344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:03.458730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:03.828411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:02.973855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:03.249894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:28:03.520086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T01:28:07.797435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호연령대이용건수이동거리(M)이용시간(분)
대여소번호1.0000.2060.0890.0510.067
연령대0.2061.0000.2390.1250.210
이용건수0.0890.2391.0000.8370.830
이동거리(M)0.0510.1250.8371.0000.937
이용시간(분)0.0670.2100.8300.9371.000
2024-03-14T01:28:07.872187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)연령대
대여소번호1.000-0.029-0.030-0.0400.124
이용건수-0.0291.0000.7970.7850.145
이동거리(M)-0.0300.7971.0000.9220.086
이용시간(분)-0.0400.7850.9221.0000.096
연령대0.1240.1450.0860.0961.000

Missing values

2024-03-14T01:28:03.969536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T01:28:04.103093image/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)
02023-04-01731731. 서울시 도로환경관리센터정기권<NA>~10대236.300.301309.5310
12023-04-01732732. 신월중학교정기권<NA>~10대140.060.351510.018
22023-04-01735735. 영도초등학교정기권<NA>~10대128.510.421800.014
32023-04-01747747. 목동3단지 상가정기권<NA>~10대299.160.743176.617
42023-04-0110291029. 성내어울터정기권<NA>~10대154.780.522231.2211
52023-04-0110441044. 굽은다리역정기권<NA>~10대274.390.672890.020
62023-04-0111521152. 마곡역교차로정기권<NA>~10대117.790.17748.664
72023-04-0111531153. 발산역 1번, 9번 인근 대여소정기권<NA>~10대3169.201.526573.0859
82023-04-0112531253. 오금역 3번 출구 뒤정기권<NA>~10대3161.191.888112.7550
92023-04-0112561256. 문정현대아파트 교차로정기권<NA>~10대117.440.19800.874
대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
55572023-04-0129102910.도깨비시장정기권<NA>40대2174.641.426108.5936
55582023-04-0129112911.상계역중앙시장정기권<NA>40대2149.161.345779.9428
55592023-04-0129122912.대진고등학교정기권<NA>40대1169.941.536602.3432
55602023-04-0129192919.등나무 근린공원(시립북서울미술관 앞)정기권<NA>40대232.380.351510.029
55612023-04-0129212921.중계역 2번출구정기권<NA>40대138.400.421829.5326
55622023-04-0117441744.도봉소방서 옆정기권<NA>40대4146.391.225221.545
55632023-04-0117481748. 방학역 1번출구정기권<NA>40대113.380.12504.396
55642023-04-0117511751. 창원초등학교 교차로정기권<NA>40대152.270.461970.0813
55652023-04-0117521752. 창동 주공 4단지 입구 옆정기권<NA>40대10.000.000.02
55662023-04-0117541754. 창동시장입구 사거리정기권<NA>40대161.300.602580.027