Overview

Dataset statistics

Number of variables11
Number of observations4924
Missing cells4924
Missing cells (%)9.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory447.3 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 4924 (100.0%) missing valuesMissing
성별 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-18 04:50:18.285432
Analysis finished2024-05-18 04:50:26.553569
Duration8.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
Minimum2023-05-01 00:00:00
Maximum2023-05-01 00:00:00
2024-05-18T13:50:26.691450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:50:26.996969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

대여소번호
Real number (ℝ)

Distinct2453
Distinct (%)49.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2339.6105
Minimum102
Maximum6054
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-05-18T13:50:27.334401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile255
Q1965.75
median1993
Q33785
95-th percentile4873
Maximum6054
Range5952
Interquartile range (IQR)2819.25

Descriptive statistics

Standard deviation1575.077
Coefficient of variation (CV)0.67322188
Kurtosis-1.1515258
Mean2339.6105
Median Absolute Deviation (MAD)1322.5
Skewness0.35949557
Sum11520242
Variance2480867.5
MonotonicityNot monotonic
2024-05-18T13:50:27.828108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4125 5
 
0.1%
602 5
 
0.1%
1977 5
 
0.1%
3518 5
 
0.1%
175 5
 
0.1%
5073 5
 
0.1%
1359 5
 
0.1%
2919 5
 
0.1%
1684 5
 
0.1%
150 5
 
0.1%
Other values (2443) 4874
99.0%
ValueCountFrequency (%)
102 2
< 0.1%
103 1
 
< 0.1%
104 2
< 0.1%
105 1
 
< 0.1%
106 1
 
< 0.1%
107 1
 
< 0.1%
108 4
0.1%
109 1
 
< 0.1%
111 3
0.1%
112 1
 
< 0.1%
ValueCountFrequency (%)
6054 3
0.1%
5866 3
0.1%
5865 3
0.1%
5862 3
0.1%
5861 3
0.1%
5860 3
0.1%
5859 2
< 0.1%
5858 3
0.1%
5857 2
< 0.1%
5855 2
< 0.1%

대여소
Text

Distinct2453
Distinct (%)49.8%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
2024-05-18T13:50:28.471769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length32
Mean length15.556255
Min length7

Characters and Unicode

Total characters76599
Distinct characters569
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

Unique815 ?
Unique (%)16.6%

Sample

1st row729. 서부식자재마트 건너편
2nd row731. 서울시 도로환경관리센터
3rd row733. 신정이펜하우스314동
4th row736. 오솔길공원
5th row746. 목동2단지 상가
ValueCountFrequency (%)
앞 1301
 
9.1%
출구 242
 
1.7%
옆 183
 
1.3%
1번출구 140
 
1.0%
교차로 125
 
0.9%
입구 116
 
0.8%
사거리 111
 
0.8%
3번출구 100
 
0.7%
2번출구 89
 
0.6%
뒤 87
 
0.6%
Other values (4909) 11860
82.6%
2024-05-18T13:50:29.569567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9529
 
12.4%
. 4933
 
6.4%
1 3655
 
4.8%
2 2772
 
3.6%
4 2498
 
3.3%
3 2431
 
3.2%
5 1941
 
2.5%
6 1762
 
2.3%
0 1677
 
2.2%
7 1656
 
2.2%
Other values (559) 43745
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39468
51.5%
Decimal Number 21133
27.6%
Space Separator 9529
 
12.4%
Other Punctuation 4997
 
6.5%
Uppercase Letter 574
 
0.7%
Open Punctuation 381
 
0.5%
Close Punctuation 381
 
0.5%
Lowercase Letter 88
 
0.1%
Dash Punctuation 34
 
< 0.1%
Other Number 6
 
< 0.1%
Other values (3) 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1593
 
4.0%
앞 1492
 
3.8%
역 1238
 
3.1%
번 1091
 
2.8%
동 1079
 
2.7%
출 1065
 
2.7%
교 807
 
2.0%
파 741
 
1.9%
아 709
 
1.8%
트 680
 
1.7%
Other values (497) 28973
73.4%
Uppercase Letter
ValueCountFrequency (%)
S 73
12.7%
K 63
11.0%
T 58
10.1%
A 53
9.2%
C 43
 
7.5%
B 42
 
7.3%
G 42
 
7.3%
P 35
 
6.1%
D 26
 
4.5%
L 25
 
4.4%
Other values (14) 114
19.9%
Lowercase Letter
ValueCountFrequency (%)
e 31
35.2%
s 17
19.3%
k 14
15.9%
n 4
 
4.5%
f 4
 
4.5%
r 4
 
4.5%
h 4
 
4.5%
t 2
 
2.3%
v 2
 
2.3%
l 2
 
2.3%
Other values (3) 4
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 3655
17.3%
2 2772
13.1%
4 2498
11.8%
3 2431
11.5%
5 1941
9.2%
6 1762
8.3%
0 1677
7.9%
7 1656
7.8%
8 1494
7.1%
9 1247
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 4933
98.7%
, 45
 
0.9%
& 11
 
0.2%
? 5
 
0.1%
· 3
 
0.1%
Other Number
ValueCountFrequency (%)
① 5
83.3%
② 1
 
16.7%
Math Symbol
ValueCountFrequency (%)
~ 3
75.0%
+ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
9529
100.0%
Open Punctuation
ValueCountFrequency (%)
( 381
100.0%
Close Punctuation
ValueCountFrequency (%)
) 381
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39469
51.5%
Common 36468
47.6%
Latin 662
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1593
 
4.0%
앞 1492
 
3.8%
역 1238
 
3.1%
번 1091
 
2.8%
동 1079
 
2.7%
출 1065
 
2.7%
교 807
 
2.0%
파 741
 
1.9%
아 709
 
1.8%
트 680
 
1.7%
Other values (498) 28974
73.4%
Latin
ValueCountFrequency (%)
S 73
 
11.0%
K 63
 
9.5%
T 58
 
8.8%
A 53
 
8.0%
C 43
 
6.5%
B 42
 
6.3%
G 42
 
6.3%
P 35
 
5.3%
e 31
 
4.7%
D 26
 
3.9%
Other values (27) 196
29.6%
Common
ValueCountFrequency (%)
9529
26.1%
. 4933
13.5%
1 3655
 
10.0%
2 2772
 
7.6%
4 2498
 
6.8%
3 2431
 
6.7%
5 1941
 
5.3%
6 1762
 
4.8%
0 1677
 
4.6%
7 1656
 
4.5%
Other values (14) 3614
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39468
51.5%
ASCII 37121
48.5%
Enclosed Alphanum 6
 
< 0.1%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9529
25.7%
. 4933
13.3%
1 3655
 
9.8%
2 2772
 
7.5%
4 2498
 
6.7%
3 2431
 
6.5%
5 1941
 
5.2%
6 1762
 
4.7%
0 1677
 
4.5%
7 1656
 
4.5%
Other values (48) 4267
11.5%
Hangul
ValueCountFrequency (%)
구 1593
 
4.0%
앞 1492
 
3.8%
역 1238
 
3.1%
번 1091
 
2.8%
동 1079
 
2.7%
출 1065
 
2.7%
교 807
 
2.0%
파 741
 
1.9%
아 709
 
1.8%
트 680
 
1.7%
Other values (497) 28973
73.4%
Enclosed Alphanum
ValueCountFrequency (%)
① 5
83.3%
② 1
 
16.7%
None
ValueCountFrequency (%)
· 3
75.0%
㈜ 1
 
25.0%

대여구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
정기권
4924 

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 4924
100.0%

Length

2024-05-18T13:50:30.048114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:50:30.371502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 4924
100.0%

성별
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4924
Missing (%)100.0%
Memory size43.4 KiB

연령대
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
20대
2826 
30대
1756 
~10대
342 

Length

Max length4
Median length3
Mean length3.0694557
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 2826
57.4%
30대 1756
35.7%
~10대 342
 
6.9%

Length

2024-05-18T13:50:30.688542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:50:31.013490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 2826
57.4%
30대 1756
35.7%
10대 342
 
6.9%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6287571
Minimum1
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-05-18T13:50:31.438309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile12
Maximum48
Range47
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.0456307
Coefficient of variation (CV)1.1148805
Kurtosis15.589015
Mean3.6287571
Median Absolute Deviation (MAD)1
Skewness3.1250092
Sum17868
Variance16.367127
MonotonicityNot monotonic
2024-05-18T13:50:31.976096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1 1870
38.0%
2 885
18.0%
3 549
 
11.1%
4 362
 
7.4%
5 321
 
6.5%
6 203
 
4.1%
7 143
 
2.9%
8 115
 
2.3%
9 93
 
1.9%
10 90
 
1.8%
Other values (26) 293
 
6.0%
ValueCountFrequency (%)
1 1870
38.0%
2 885
18.0%
3 549
 
11.1%
4 362
 
7.4%
5 321
 
6.5%
6 203
 
4.1%
7 143
 
2.9%
8 115
 
2.3%
9 93
 
1.9%
10 90
 
1.8%
ValueCountFrequency (%)
48 1
< 0.1%
44 1
< 0.1%
42 1
< 0.1%
40 1
< 0.1%
35 1
< 0.1%
34 1
< 0.1%
32 1
< 0.1%
31 2
< 0.1%
30 1
< 0.1%
28 2
< 0.1%

운동량
Text

Distinct4450
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
2024-05-18T13:50:32.739765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.4989846
Min length2

Characters and Unicode

Total characters27077
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

Unique4066 ?
Unique (%)82.6%

Sample

1st row171.69
2nd row99.01
3rd row69.86
4th row15.47
5th row71.32
ValueCountFrequency (%)
0.00 38
 
0.8%
23.17 5
 
0.1%
17.25 5
 
0.1%
n 5
 
0.1%
33.26 4
 
0.1%
22.59 4
 
0.1%
23.76 4
 
0.1%
19.05 3
 
0.1%
95.93 3
 
0.1%
11.09 3
 
0.1%
Other values (4440) 4850
98.5%
2024-05-18T13:50:34.438901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4919
18.2%
1 3135
11.6%
2 2663
9.8%
3 2429
9.0%
4 2194
8.1%
5 2092
7.7%
0 1971
7.3%
7 1956
 
7.2%
6 1934
 
7.1%
8 1903
 
7.0%
Other values (3) 1881
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22148
81.8%
Other Punctuation 4924
 
18.2%
Uppercase Letter 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3135
14.2%
2 2663
12.0%
3 2429
11.0%
4 2194
9.9%
5 2092
9.4%
0 1971
8.9%
7 1956
8.8%
6 1934
8.7%
8 1903
8.6%
9 1871
8.4%
Other Punctuation
ValueCountFrequency (%)
. 4919
99.9%
\ 5
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27072
> 99.9%
Latin 5
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4919
18.2%
1 3135
11.6%
2 2663
9.8%
3 2429
9.0%
4 2194
8.1%
5 2092
7.7%
0 1971
7.3%
7 1956
 
7.2%
6 1934
 
7.1%
8 1903
 
7.0%
Other values (2) 1876
 
6.9%
Latin
ValueCountFrequency (%)
N 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27077
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4919
18.2%
1 3135
11.6%
2 2663
9.8%
3 2429
9.0%
4 2194
8.1%
5 2092
7.7%
0 1971
7.3%
7 1956
 
7.2%
6 1934
 
7.1%
8 1903
 
7.0%
Other values (3) 1881
 
6.9%

탄소량
Text

Distinct742
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
2024-05-18T13:50:35.417901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.0083266
Min length2

Characters and Unicode

Total characters19737
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

Unique244 ?
Unique (%)5.0%

Sample

1st row1.29
2nd row0.94
3rd row0.64
4th row0.14
5th row0.69
ValueCountFrequency (%)
0.24 51
 
1.0%
0.26 51
 
1.0%
0.31 46
 
0.9%
0.16 46
 
0.9%
0.17 43
 
0.9%
0.25 41
 
0.8%
0.20 40
 
0.8%
0.33 40
 
0.8%
0.19 40
 
0.8%
0.29 40
 
0.8%
Other values (732) 4486
91.1%
2024-05-18T13:50:37.553422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4919
24.9%
0 3474
17.6%
1 2235
11.3%
2 1735
 
8.8%
3 1378
 
7.0%
4 1180
 
6.0%
5 1106
 
5.6%
6 993
 
5.0%
7 916
 
4.6%
8 897
 
4.5%
Other values (3) 904
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14808
75.0%
Other Punctuation 4924
 
24.9%
Uppercase Letter 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3474
23.5%
1 2235
15.1%
2 1735
11.7%
3 1378
 
9.3%
4 1180
 
8.0%
5 1106
 
7.5%
6 993
 
6.7%
7 916
 
6.2%
8 897
 
6.1%
9 894
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 4919
99.9%
\ 5
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19732
> 99.9%
Latin 5
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4919
24.9%
0 3474
17.6%
1 2235
11.3%
2 1735
 
8.8%
3 1378
 
7.0%
4 1180
 
6.0%
5 1106
 
5.6%
6 993
 
5.0%
7 916
 
4.6%
8 897
 
4.5%
Other values (2) 899
 
4.6%
Latin
ValueCountFrequency (%)
N 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19737
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4919
24.9%
0 3474
17.6%
1 2235
11.3%
2 1735
 
8.8%
3 1378
 
7.0%
4 1180
 
6.0%
5 1106
 
5.6%
6 993
 
5.0%
7 916
 
4.6%
8 897
 
4.5%
Other values (3) 904
 
4.6%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION 

Distinct4216
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7455.7766
Minimum0
Maximum201182.88
Zeros41
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-05-18T13:50:38.344310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile580
Q11697.0075
median4132.505
Q39460.165
95-th percentile25380.347
Maximum201182.88
Range201182.88
Interquartile range (IQR)7763.1575

Descriptive statistics

Standard deviation9674.149
Coefficient of variation (CV)1.2975374
Kurtosis50.031616
Mean7455.7766
Median Absolute Deviation (MAD)2943.385
Skewness4.558219
Sum36712244
Variance93589159
MonotonicityNot monotonic
2024-05-18T13:50:39.086990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 41
 
0.8%
1050.0 11
 
0.2%
1130.0 9
 
0.2%
1320.0 9
 
0.2%
710.0 8
 
0.2%
1030.0 8
 
0.2%
1370.0 7
 
0.1%
540.0 7
 
0.1%
820.0 7
 
0.1%
1100.0 7
 
0.1%
Other values (4206) 4810
97.7%
ValueCountFrequency (%)
0.0 41
0.8%
4.64 1
 
< 0.1%
10.0 1
 
< 0.1%
27.91 1
 
< 0.1%
28.26 1
 
< 0.1%
30.0 1
 
< 0.1%
50.0 1
 
< 0.1%
62.27 1
 
< 0.1%
88.12 1
 
< 0.1%
88.13 1
 
< 0.1%
ValueCountFrequency (%)
201182.88 1
< 0.1%
147047.89 1
< 0.1%
93898.19 1
< 0.1%
88779.99 1
< 0.1%
81382.02 1
< 0.1%
81147.87 1
< 0.1%
71951.68 1
< 0.1%
71614.52 1
< 0.1%
70707.9 1
< 0.1%
68062.74 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct343
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.09342
Minimum0
Maximum1402
Zeros3
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-05-18T13:50:39.999983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q112
median32
Q372
95-th percentile195
Maximum1402
Range1402
Interquartile range (IQR)60

Descriptive statistics

Standard deviation74.825904
Coefficient of variation (CV)1.3105872
Kurtosis38.376455
Mean57.09342
Median Absolute Deviation (MAD)23
Skewness4.2153847
Sum281128
Variance5598.9159
MonotonicityNot monotonic
2024-05-18T13:50:40.629071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 131
 
2.7%
7 129
 
2.6%
9 122
 
2.5%
6 121
 
2.5%
3 120
 
2.4%
4 115
 
2.3%
10 114
 
2.3%
5 110
 
2.2%
11 100
 
2.0%
13 94
 
1.9%
Other values (333) 3768
76.5%
ValueCountFrequency (%)
0 3
 
0.1%
1 26
 
0.5%
2 65
1.3%
3 120
2.4%
4 115
2.3%
5 110
2.2%
6 121
2.5%
7 129
2.6%
8 131
2.7%
9 122
2.5%
ValueCountFrequency (%)
1402 1
< 0.1%
1079 1
< 0.1%
736 1
< 0.1%
734 1
< 0.1%
631 1
< 0.1%
623 1
< 0.1%
583 1
< 0.1%
546 1
< 0.1%
539 1
< 0.1%
533 1
< 0.1%

Interactions

2024-05-18T13:50:24.035601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:50:19.828030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:50:21.194742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:50:22.418339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:50:24.437628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:50:20.165725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:50:21.478294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:50:22.736672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:50:24.886044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:50:20.450783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:50:21.790457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:50:23.137063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:50:25.344025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:50:20.870855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:50:22.118937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:50:23.530635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T13:50:41.048463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호연령대이용건수이동거리(M)이용시간(분)
대여소번호1.0000.1530.1360.0640.065
연령대0.1531.0000.2590.1350.155
이용건수0.1360.2591.0000.8070.827
이동거리(M)0.0640.1350.8071.0000.923
이용시간(분)0.0650.1550.8270.9231.000
2024-05-18T13:50:41.406803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)연령대
대여소번호1.000-0.055-0.055-0.0620.092
이용건수-0.0551.0000.8140.8150.160
이동거리(M)-0.0550.8141.0000.9340.091
이용시간(분)-0.0620.8150.9341.0000.099
연령대0.0920.1600.0910.0991.000

Missing values

2024-05-18T13:50:25.795741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T13:50:26.336155image/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)
02023-05-01729729. 서부식자재마트 건너편정기권<NA>~10대1171.691.295558.5227
12023-05-01731731. 서울시 도로환경관리센터정기권<NA>~10대199.010.944032.6434
22023-05-01733733. 신정이펜하우스314동정기권<NA>~10대269.860.642800.09
32023-05-01736736. 오솔길공원정기권<NA>~10대115.470.14620.03
42023-05-01746746. 목동2단지 상가정기권<NA>~10대271.320.692969.218
52023-05-01747747. 목동3단지 상가정기권<NA>~10대154.650.642760.020
62023-05-01948948. 디지털미디어 시티역 4번출구(DMC역)정기권<NA>~10대19.110.11460.04
72023-05-0110231023. 한국종합기술사옥 앞정기권<NA>~10대110.480.11490.03
82023-05-0110271027. 프라자 아파트 앞정기권<NA>~10대173.270.662846.5416
92023-05-0110291029. 성내어울터정기권<NA>~10대233.190.351526.38
대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
49142023-05-01809809. 한남 유수지 복개주차장정기권<NA>30대1250.912.048800.039
49152023-05-01810810. 이태원지하보도정기권<NA>30대10.000.000.00
49162023-05-01811811. 녹사평역1번출구정기권<NA>30대176.970.692990.434
49172023-05-01813813. 삼각지역 3번출구정기권<NA>30대196.031.134850.042
49182023-05-01815815. LIG강촌아파트 103동앞정기권<NA>30대243.560.462000.020
49192023-05-01815815. LIG강촌아파트 103동앞정기권<NA>30대140.850.371586.9934
49202023-05-01385385. 종각역 5번출구정기권<NA>30대160.580.622683.7416
49212023-05-01387387. 훈련원공원주차장 앞정기권<NA>30대2126.711.074637.4331
49222023-05-01181181. 망원초록길 입구정기권<NA>30대61019.419.5140978.33264
49232023-05-01182182. 망원2빗물펌프장 앞정기권<NA>30대3145.631.697260.053