Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory986.3 KiB
Average record size in memory101.0 B

Variable types

Categorical4
Text2
Numeric5

Dataset

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

Alerts

'이용건수' is highly overall correlated with '운동량' and 3 other fieldsHigh correlation
'운동량' is highly overall correlated with '이용건수' and 3 other fieldsHigh correlation
'탄소량' is highly overall correlated with '이용건수' and 3 other fieldsHigh correlation
'이동거리(M)' is highly overall correlated with '이용건수' and 3 other fieldsHigh correlation
'이동시간(분)' is highly overall correlated with '이용건수' and 3 other fieldsHigh correlation
'대여구분코드' is highly overall correlated with 'SEX_CD'High correlation
'SEX_CD' is highly overall correlated with '대여구분코드'High correlation

Reproduction

Analysis started2024-03-13 16:23:37.873681
Analysis finished2024-03-13 16:23:41.403931
Duration3.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

'대여일자'
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
'2018-06-02'
3169 
'2018-06-03'
3083 
'2018-06-01'
2994 
'2018-06-04'
754 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row'2018-06-04'
2nd row'2018-06-01'
3rd row'2018-06-03'
4th row'2018-06-03'
5th row'2018-06-01'

Common Values

ValueCountFrequency (%)
'2018-06-02' 3169
31.7%
'2018-06-03' 3083
30.8%
'2018-06-01' 2994
29.9%
'2018-06-04' 754
 
7.5%

Length

2024-03-14T01:23:41.471592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:23:41.561349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-06-02 3169
31.7%
2018-06-03 3083
30.8%
2018-06-01 2994
29.9%
2018-06-04 754
 
7.5%

'대여소번호'
Text

Distinct1255
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T01:23:41.895964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.544
Min length5

Characters and Unicode

Total characters55440
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)0.2%

Sample

1st row'641'
2nd row'2348'
3rd row'1020'
4th row'1438'
5th row'615'
ValueCountFrequency (%)
2219 25
 
0.2%
210 23
 
0.2%
825 22
 
0.2%
207 21
 
0.2%
565 21
 
0.2%
133 20
 
0.2%
154 20
 
0.2%
302 19
 
0.2%
1209 19
 
0.2%
222 19
 
0.2%
Other values (1245) 9791
97.9%
2024-03-14T01:23:42.337544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 20000
36.1%
1 7842
 
14.1%
2 6088
 
11.0%
3 4041
 
7.3%
0 3350
 
6.0%
5 3163
 
5.7%
4 2674
 
4.8%
6 2598
 
4.7%
7 1999
 
3.6%
9 1904
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35440
63.9%
Other Punctuation 20000
36.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7842
22.1%
2 6088
17.2%
3 4041
11.4%
0 3350
9.5%
5 3163
8.9%
4 2674
 
7.5%
6 2598
 
7.3%
7 1999
 
5.6%
9 1904
 
5.4%
8 1781
 
5.0%
Other Punctuation
ValueCountFrequency (%)
' 20000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 55440
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
' 20000
36.1%
1 7842
 
14.1%
2 6088
 
11.0%
3 4041
 
7.3%
0 3350
 
6.0%
5 3163
 
5.7%
4 2674
 
4.8%
6 2598
 
4.7%
7 1999
 
3.6%
9 1904
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55440
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 20000
36.1%
1 7842
 
14.1%
2 6088
 
11.0%
3 4041
 
7.3%
0 3350
 
6.0%
5 3163
 
5.7%
4 2674
 
4.8%
6 2598
 
4.7%
7 1999
 
3.6%
9 1904
 
3.4%

'대여소'
Text

Distinct1255
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T01:23:42.560732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length27
Mean length12.6718
Min length6

Characters and Unicode

Total characters126718
Distinct characters482
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)0.2%

Sample

1st row' 용두역 4번출구'
2nd row' 포스코사거리(기업은행)'
3rd row' 강동경찰서'
4th row' 홈플러스 신내점 앞'
5th row' 용두동 레미안허브리츠아파트 앞'
ValueCountFrequency (%)
9931
31.4%
앞 2718
 
8.6%
옆 607
 
1.9%
1번출구 450
 
1.4%
출구 448
 
1.4%
사거리 323
 
1.0%
2번출구 312
 
1.0%
뒤 310
 
1.0%
4번출구 252
 
0.8%
3번출구 239
 
0.8%
Other values (1508) 16082
50.8%
2024-03-14T01:23:42.900673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21715
 
17.1%
' 20000
 
15.8%
구 3930
 
3.1%
앞 3235
 
2.6%
역 3138
 
2.5%
번 2826
 
2.2%
출 2799
 
2.2%
동 1750
 
1.4%
교 1511
 
1.2%
리 1446
 
1.1%
Other values (472) 64368
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 77516
61.2%
Space Separator 21715
 
17.1%
Other Punctuation 20068
 
15.8%
Decimal Number 4876
 
3.8%
Uppercase Letter 1166
 
0.9%
Open Punctuation 594
 
0.5%
Close Punctuation 594
 
0.5%
Dash Punctuation 89
 
0.1%
Lowercase Letter 70
 
0.1%
Math Symbol 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3930
 
5.1%
앞 3235
 
4.2%
역 3138
 
4.0%
번 2826
 
3.6%
출 2799
 
3.6%
동 1750
 
2.3%
교 1511
 
1.9%
리 1446
 
1.9%
원 1220
 
1.6%
사 1198
 
1.5%
Other values (420) 54463
70.3%
Uppercase Letter
ValueCountFrequency (%)
K 165
14.2%
S 155
13.3%
C 137
11.7%
T 75
 
6.4%
L 72
 
6.2%
G 71
 
6.1%
A 70
 
6.0%
I 69
 
5.9%
M 61
 
5.2%
B 54
 
4.6%
Other values (13) 237
20.3%
Decimal Number
ValueCountFrequency (%)
1 1407
28.9%
2 911
18.7%
3 653
13.4%
4 559
 
11.5%
5 318
 
6.5%
8 249
 
5.1%
0 248
 
5.1%
6 220
 
4.5%
7 211
 
4.3%
9 100
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
e 21
30.0%
t 14
20.0%
m 7
 
10.0%
l 7
 
10.0%
k 7
 
10.0%
c 7
 
10.0%
o 7
 
10.0%
Other Punctuation
ValueCountFrequency (%)
' 20000
99.7%
, 45
 
0.2%
? 11
 
0.1%
& 6
 
< 0.1%
@ 6
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 17
85.0%
+ 3
 
15.0%
Space Separator
ValueCountFrequency (%)
21715
100.0%
Open Punctuation
ValueCountFrequency (%)
( 594
100.0%
Close Punctuation
ValueCountFrequency (%)
) 594
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 77516
61.2%
Common 47966
37.9%
Latin 1236
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3930
 
5.1%
앞 3235
 
4.2%
역 3138
 
4.0%
번 2826
 
3.6%
출 2799
 
3.6%
동 1750
 
2.3%
교 1511
 
1.9%
리 1446
 
1.9%
원 1220
 
1.6%
사 1198
 
1.5%
Other values (420) 54463
70.3%
Latin
ValueCountFrequency (%)
K 165
13.3%
S 155
12.5%
C 137
11.1%
T 75
 
6.1%
L 72
 
5.8%
G 71
 
5.7%
A 70
 
5.7%
I 69
 
5.6%
M 61
 
4.9%
B 54
 
4.4%
Other values (20) 307
24.8%
Common
ValueCountFrequency (%)
21715
45.3%
' 20000
41.7%
1 1407
 
2.9%
2 911
 
1.9%
3 653
 
1.4%
( 594
 
1.2%
) 594
 
1.2%
4 559
 
1.2%
5 318
 
0.7%
8 249
 
0.5%
Other values (12) 966
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 77516
61.2%
ASCII 49202
38.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21715
44.1%
' 20000
40.6%
1 1407
 
2.9%
2 911
 
1.9%
3 653
 
1.3%
( 594
 
1.2%
) 594
 
1.2%
4 559
 
1.1%
5 318
 
0.6%
8 249
 
0.5%
Other values (42) 2202
 
4.5%
Hangul
ValueCountFrequency (%)
구 3930
 
5.1%
앞 3235
 
4.2%
역 3138
 
4.0%
번 2826
 
3.6%
출 2799
 
3.6%
동 1750
 
2.3%
교 1511
 
1.9%
리 1446
 
1.9%
원 1220
 
1.6%
사 1198
 
1.5%
Other values (420) 54463
70.3%

'대여구분코드'
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
'정기'
6311 
'일일(회원)'
2858 
'일일(비회원)'
708 
'단체'
 
123

Length

Max length9
Median length4
Mean length5.4972
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row'정기'
2nd row'일일(회원)'
3rd row'정기'
4th row'정기'
5th row'정기'

Common Values

ValueCountFrequency (%)
'정기' 6311
63.1%
'일일(회원)' 2858
28.6%
'일일(비회원)' 708
 
7.1%
'단체' 123
 
1.2%

Length

2024-03-14T01:23:43.018236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:23:43.096621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 6311
63.1%
일일(회원 2858
28.6%
일일(비회원 708
 
7.1%
단체 123
 
1.2%

'SEX_CD'
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
'M'
4828 
'F'
4563 
''
609 

Length

Max length3
Median length3
Mean length2.9391
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row'F'
2nd row'M'
3rd row'F'
4th row'M'
5th row'M'

Common Values

ValueCountFrequency (%)
'M' 4828
48.3%
'F' 4563
45.6%
'' 609
 
6.1%

Length

2024-03-14T01:23:43.180605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:23:43.254752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 4828
48.3%
f 4563
45.6%
609
 
6.1%

'연령대코드'
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
'20대'
3267 
'30대'
2458 
'40대'
1701 
'50대'
955 
<NA>
711 
Other values (3)
908 

Length

Max length6
Median length5
Mean length4.9907
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row'20대'
2nd row'20대'
3rd row'40대'
4th row'40대'
5th row'30대'

Common Values

ValueCountFrequency (%)
'20대' 3267
32.7%
'30대' 2458
24.6%
'40대' 1701
17.0%
'50대' 955
 
9.6%
<NA> 711
 
7.1%
'~10대' 501
 
5.0%
'60대' 290
 
2.9%
'70대~' 117
 
1.2%

Length

2024-03-14T01:23:43.343478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:23:43.444494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 3267
32.7%
30대 2458
24.6%
40대 1701
17.0%
50대 955
 
9.6%
na 711
 
7.1%
10대 501
 
5.0%
60대 290
 
2.9%
70대 117
 
1.2%

'이용건수'
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.226
Minimum1
Maximum77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:23:43.569797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile10
Maximum77
Range76
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.7777971
Coefficient of variation (CV)1.1710468
Kurtosis45.250584
Mean3.226
Median Absolute Deviation (MAD)1
Skewness4.7449433
Sum32260
Variance14.271751
MonotonicityNot monotonic
2024-03-14T01:23:43.712192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1 4016
40.2%
2 1992
19.9%
3 1201
 
12.0%
4 803
 
8.0%
5 484
 
4.8%
6 355
 
3.5%
7 264
 
2.6%
8 177
 
1.8%
9 138
 
1.4%
10 114
 
1.1%
Other values (36) 456
 
4.6%
ValueCountFrequency (%)
1 4016
40.2%
2 1992
19.9%
3 1201
 
12.0%
4 803
 
8.0%
5 484
 
4.8%
6 355
 
3.5%
7 264
 
2.6%
8 177
 
1.8%
9 138
 
1.4%
10 114
 
1.1%
ValueCountFrequency (%)
77 1
< 0.1%
69 1
< 0.1%
51 1
< 0.1%
50 1
< 0.1%
47 1
< 0.1%
45 1
< 0.1%
41 2
< 0.1%
40 1
< 0.1%
38 1
< 0.1%
37 1
< 0.1%

'운동량'
Real number (ℝ)

HIGH CORRELATION 

Distinct8421
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean416.89589
Minimum0
Maximum12764.05
Zeros68
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:23:43.828197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile23.1285
Q179.79
median198.84
Q3477.9825
95-th percentile1572.1225
Maximum12764.05
Range12764.05
Interquartile range (IQR)398.1925

Descriptive statistics

Standard deviation649.12135
Coefficient of variation (CV)1.5570347
Kurtosis53.755365
Mean416.89589
Median Absolute Deviation (MAD)147.1
Skewness5.2628931
Sum4168958.9
Variance421358.53
MonotonicityNot monotonic
2024-03-14T01:23:43.946258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 68
 
0.7%
26.0 9
 
0.1%
58.17 7
 
0.1%
25.23 7
 
0.1%
30.37 7
 
0.1%
56.63 7
 
0.1%
37.07 7
 
0.1%
111.2 7
 
0.1%
32.43 7
 
0.1%
32.95 7
 
0.1%
Other values (8411) 9867
98.7%
ValueCountFrequency (%)
0.0 68
0.7%
0.23 1
 
< 0.1%
0.26 1
 
< 0.1%
0.41 1
 
< 0.1%
0.49 1
 
< 0.1%
0.54 1
 
< 0.1%
1.09 1
 
< 0.1%
1.11 1
 
< 0.1%
1.39 1
 
< 0.1%
1.73 1
 
< 0.1%
ValueCountFrequency (%)
12764.05 1
< 0.1%
11817.63 1
< 0.1%
11555.75 1
< 0.1%
10334.47 1
< 0.1%
7958.39 1
< 0.1%
7885.85 1
< 0.1%
7485.62 1
< 0.1%
6682.76 1
< 0.1%
6403.56 1
< 0.1%
6153.95 1
< 0.1%

'탄소량'
Real number (ℝ)

HIGH CORRELATION 

Distinct1611
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.709479
Minimum0
Maximum111.43
Zeros72
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:23:44.057203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.22
Q10.72
median1.795
Q34.23
95-th percentile14.18
Maximum111.43
Range111.43
Interquartile range (IQR)3.51

Descriptive statistics

Standard deviation5.7625169
Coefficient of variation (CV)1.5534572
Kurtosis53.267814
Mean3.709479
Median Absolute Deviation (MAD)1.315
Skewness5.266009
Sum37094.79
Variance33.2066
MonotonicityNot monotonic
2024-03-14T01:23:44.180956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 72
 
0.7%
0.27 56
 
0.6%
0.48 56
 
0.6%
0.19 50
 
0.5%
0.71 50
 
0.5%
0.38 50
 
0.5%
0.26 49
 
0.5%
0.29 49
 
0.5%
0.32 49
 
0.5%
0.16 48
 
0.5%
Other values (1601) 9471
94.7%
ValueCountFrequency (%)
0.0 72
0.7%
0.01 4
 
< 0.1%
0.02 3
 
< 0.1%
0.03 3
 
< 0.1%
0.04 4
 
< 0.1%
0.05 3
 
< 0.1%
0.06 3
 
< 0.1%
0.07 7
 
0.1%
0.08 13
 
0.1%
0.09 18
 
0.2%
ValueCountFrequency (%)
111.43 1
< 0.1%
107.68 1
< 0.1%
96.83 1
< 0.1%
91.45 1
< 0.1%
80.48 1
< 0.1%
66.34 1
< 0.1%
63.49 1
< 0.1%
62.0 1
< 0.1%
56.63 1
< 0.1%
56.42 1
< 0.1%

'이동거리(M)'
Real number (ℝ)

HIGH CORRELATION 

Distinct3613
Distinct (%)36.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15989.261
Minimum0
Maximum480540
Zeros68
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:23:44.292735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile930
Q13120
median7740
Q318230
95-th percentile61111
Maximum480540
Range480540
Interquartile range (IQR)15110

Descriptive statistics

Standard deviation24839.052
Coefficient of variation (CV)1.5534834
Kurtosis53.288663
Mean15989.261
Median Absolute Deviation (MAD)5660
Skewness5.2668406
Sum1.5989261 × 108
Variance6.1697851 × 108
MonotonicityNot monotonic
2024-03-14T01:23:44.399971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 68
 
0.7%
1440 18
 
0.2%
1970 18
 
0.2%
1200 17
 
0.2%
1290 17
 
0.2%
2330 17
 
0.2%
1170 16
 
0.2%
1080 16
 
0.2%
1160 16
 
0.2%
2090 16
 
0.2%
Other values (3603) 9781
97.8%
ValueCountFrequency (%)
0 68
0.7%
10 2
 
< 0.1%
20 2
 
< 0.1%
40 2
 
< 0.1%
50 1
 
< 0.1%
60 1
 
< 0.1%
70 2
 
< 0.1%
100 1
 
< 0.1%
110 1
 
< 0.1%
120 1
 
< 0.1%
ValueCountFrequency (%)
480540 1
< 0.1%
464120 1
< 0.1%
417400 1
< 0.1%
394120 1
< 0.1%
346920 1
< 0.1%
285990 1
< 0.1%
273660 1
< 0.1%
267230 1
< 0.1%
244120 1
< 0.1%
243160 1
< 0.1%

'이동시간(분)'
Real number (ℝ)

HIGH CORRELATION 

Distinct644
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean104.9033
Minimum0
Maximum3860
Zeros12
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:23:44.503530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q124
median58
Q3124.25
95-th percentile347
Maximum3860
Range3860
Interquartile range (IQR)100.25

Descriptive statistics

Standard deviation157.1894
Coefficient of variation (CV)1.4984219
Kurtosis103.72722
Mean104.9033
Median Absolute Deviation (MAD)41
Skewness7.1204672
Sum1049033
Variance24708.507
MonotonicityNot monotonic
2024-03-14T01:23:44.631957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11 132
 
1.3%
8 132
 
1.3%
12 131
 
1.3%
5 131
 
1.3%
16 127
 
1.3%
7 127
 
1.3%
14 126
 
1.3%
9 125
 
1.2%
10 121
 
1.2%
20 120
 
1.2%
Other values (634) 8728
87.3%
ValueCountFrequency (%)
0 12
 
0.1%
1 8
 
0.1%
2 49
 
0.5%
3 61
0.6%
4 100
1.0%
5 131
1.3%
6 114
1.1%
7 127
1.3%
8 132
1.3%
9 125
1.2%
ValueCountFrequency (%)
3860 1
< 0.1%
3651 1
< 0.1%
3006 1
< 0.1%
2827 1
< 0.1%
2413 1
< 0.1%
2343 1
< 0.1%
1907 1
< 0.1%
1857 1
< 0.1%
1782 1
< 0.1%
1691 1
< 0.1%

Interactions

2024-03-14T01:23:40.756607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:38.922636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:39.361275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:39.971294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:40.367430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:40.848420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:39.001458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:39.443516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:40.065232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:40.449592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:40.928242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:39.078238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:39.517020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:40.138159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:40.523841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:41.003017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:39.165126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:39.587579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:40.211201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:40.597477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:41.079878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:39.266532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:39.662098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:40.288604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:40.667482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T01:23:44.716060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
'대여일자''대여구분코드''SEX_CD''연령대코드''이용건수''운동량''탄소량''이동거리(M)''이동시간(분)'
'대여일자'1.0000.3370.2310.0850.0470.0190.0170.0170.062
'대여구분코드'0.3371.0000.6320.1870.0700.0420.0430.0440.163
'SEX_CD'0.2310.6321.0000.1120.0000.0990.0810.0810.141
'연령대코드'0.0850.1870.1121.0000.1840.1280.1350.1350.121
'이용건수'0.0470.0700.0000.1841.0000.9270.9300.9310.775
'운동량'0.0190.0420.0990.1280.9271.0000.9820.9830.788
'탄소량'0.0170.0430.0810.1350.9300.9821.0001.0000.804
'이동거리(M)'0.0170.0440.0810.1350.9310.9831.0001.0000.804
'이동시간(분)'0.0620.1630.1410.1210.7750.7880.8040.8041.000
2024-03-14T01:23:44.811838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
'대여일자''SEX_CD''대여구분코드''연령대코드'
'대여일자'1.0000.2200.1370.059
'SEX_CD'0.2201.0000.6520.120
'대여구분코드'0.1370.6521.0000.129
'연령대코드'0.0590.1200.1291.000
2024-03-14T01:23:45.133826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
'이용건수''운동량''탄소량''이동거리(M)''이동시간(분)''대여일자''대여구분코드''SEX_CD''연령대코드'
'이용건수'1.0000.7240.7240.7240.7370.0300.0450.0000.098
'운동량'0.7241.0000.9920.9920.8810.0120.0270.0430.068
'탄소량'0.7240.9921.0001.0000.8900.0110.0280.0350.071
'이동거리(M)'0.7240.9921.0001.0000.8900.0110.0280.0350.071
'이동시간(분)'0.7370.8810.8900.8901.0000.0280.0740.0890.065
'대여일자'0.0300.0120.0110.0110.0281.0000.1370.2200.059
'대여구분코드'0.0450.0270.0280.0280.0740.1371.0000.6520.129
'SEX_CD'0.0000.0430.0350.0350.0890.2200.6521.0000.120
'연령대코드'0.0980.0680.0710.0710.0650.0590.1290.1201.000

Missing values

2024-03-14T01:23:41.197061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T01:23:41.325897image/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

'대여일자''대여소번호''대여소''대여구분코드''SEX_CD''연령대코드''이용건수''운동량''탄소량''이동거리(M)''이동시간(분)'
39852'2018-06-04''641'' 용두역 4번출구''정기''F''20대'121472.6614.7263480379
10859'2018-06-01''2348'' 포스코사거리(기업은행)''일일(회원)''M''20대'1120.031.0433028
28387'2018-06-03''1020'' 강동경찰서''정기''F''40대'1174.481.79773092
32116'2018-06-03''1438'' 홈플러스 신내점 앞''정기''M''40대'384.670.67288062
5540'2018-06-01''615'' 용두동 레미안허브리츠아파트 앞''정기''M''30대'2221.261.73745039
20823'2018-06-02''397'' 종묘공영주차장 건너편''일일(회원)''F''20대'4594.825.8725270310
35893'2018-06-03''602'' 장안동 사거리''일일(회원)''M''20대'61167.919.9342810304
27292'2018-06-03''1846'' 롯데캐슬골드파크1차 동문''정기''F''30대'1143.091.45623038
26202'2018-06-03''1643'' 태릉입구역 8번출구''정기''F''20대'5248.722.721169083
13525'2018-06-02''552'' 대림아크로리버 앞''정기''F''20대'241.710.43187011
'대여일자''대여소번호''대여소''대여구분코드''SEX_CD''연령대코드''이용건수''운동량''탄소량''이동거리(M)''이동시간(분)'
20408'2018-06-02''1337'' 돈암성당 옆''일일(회원)''F''~10대'1225.641.89814060
10484'2018-06-01''228'' 선유도역 3번출구 앞''일일(회원)''M''20대'71576.5413.1256560336
41270'2018-06-04''2341'' 일원역 4~5번 출구 사이''정기''F''30대'3258.52.8212170152
23051'2018-06-02''579'' 마장역 4번출구''일일(회원)''M''20대'6803.398.034470260
16275'2018-06-02''1157'' 강서구청''정기''M''20대'4237.161.99857064
9109'2018-06-01''1010'' 강동세무서''일일(회원)''F''20대'395.280.94402029
34652'2018-06-03''609'' 제기2교''일일(회원)''F''30대'151.680.61261016
8079'2018-06-01''1260'' 방이동 한양3차아파트 옆''정기''M''60대'121.090.167106
25942'2018-06-02''1320'' 종암 농협지점 앞''단체''M''40대'2148.031.24534051
31093'2018-06-03''1102'' 방화사거리 마을버스 버스정류장''정기''M''30대'2127.971.03442022