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

DateTime1
Text2
Categorical3
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
'대여구분코드' is highly imbalanced (60.6%)Imbalance

Reproduction

Analysis started2024-03-13 16:23:46.563126
Analysis finished2024-03-13 16:23:49.835727
Duration3.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

'대여일자'
Date

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-01-01 00:00:00
Maximum2018-01-05 00:00:00
2024-03-14T01:23:49.871285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:49.950083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

'대여소번호'
Text

Distinct1006
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T01:23:50.312355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.4126
Min length5

Characters and Unicode

Total characters54126
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)0.4%

Sample

1st row'224'
2nd row'327'
3rd row'1911'
4th row'1212'
5th row'2013'
ValueCountFrequency (%)
931 32
 
0.3%
2102 30
 
0.3%
419 30
 
0.3%
1210 30
 
0.3%
311 30
 
0.3%
113 30
 
0.3%
338 29
 
0.3%
1231 26
 
0.3%
1911 25
 
0.2%
303 24
 
0.2%
Other values (996) 9714
97.1%
2024-03-14T01:23:50.750124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 20000
37.0%
1 7343
 
13.6%
2 6041
 
11.2%
3 4386
 
8.1%
0 3405
 
6.3%
5 3112
 
5.7%
4 2571
 
4.8%
6 2262
 
4.2%
9 1795
 
3.3%
8 1681
 
3.1%
Other values (5) 1530
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34110
63.0%
Other Punctuation 20000
37.0%
Other Letter 16
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7343
21.5%
2 6041
17.7%
3 4386
12.9%
0 3405
10.0%
5 3112
9.1%
4 2571
 
7.5%
6 2262
 
6.6%
9 1795
 
5.3%
8 1681
 
4.9%
7 1514
 
4.4%
Other Letter
ValueCountFrequency (%)
중 4
25.0%
랑 4
25.0%
센 4
25.0%
터 4
25.0%
Other Punctuation
ValueCountFrequency (%)
' 20000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 54110
> 99.9%
Hangul 16
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
' 20000
37.0%
1 7343
 
13.6%
2 6041
 
11.2%
3 4386
 
8.1%
0 3405
 
6.3%
5 3112
 
5.8%
4 2571
 
4.8%
6 2262
 
4.2%
9 1795
 
3.3%
8 1681
 
3.1%
Hangul
ValueCountFrequency (%)
중 4
25.0%
랑 4
25.0%
센 4
25.0%
터 4
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54110
> 99.9%
Hangul 16
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 20000
37.0%
1 7343
 
13.6%
2 6041
 
11.2%
3 4386
 
8.1%
0 3405
 
6.3%
5 3112
 
5.8%
4 2571
 
4.8%
6 2262
 
4.2%
9 1795
 
3.3%
8 1681
 
3.1%
Hangul
ValueCountFrequency (%)
중 4
25.0%
랑 4
25.0%
센 4
25.0%
터 4
25.0%

'대여소'
Text

Distinct1006
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T01:23:50.929153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length27
Mean length12.8326
Min length6

Characters and Unicode

Total characters128326
Distinct characters464
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

Unique36 ?
Unique (%)0.4%

Sample

1st row' 롯데캐슬 앞'
2nd row' 낙원상가 옆'
3rd row' 구로디지털단지역 앞'
4th row' 송파역 2번 출구앞'
5th row' 장승배기역 5번출구'
ValueCountFrequency (%)
9863
30.2%
앞 3507
 
10.7%
옆 768
 
2.3%
1번출구 511
 
1.6%
출구 438
 
1.3%
사거리 416
 
1.3%
뒤 355
 
1.1%
2번출구 342
 
1.0%
4번출구 306
 
0.9%
3번출구 292
 
0.9%
Other values (1240) 15914
48.6%
2024-03-14T01:23:51.218089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22730
 
17.7%
' 20000
 
15.6%
구 4154
 
3.2%
앞 3848
 
3.0%
역 3436
 
2.7%
번 3124
 
2.4%
출 3101
 
2.4%
동 1634
 
1.3%
교 1498
 
1.2%
리 1463
 
1.1%
Other values (454) 63338
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 78095
60.9%
Space Separator 22730
 
17.7%
Other Punctuation 20050
 
15.6%
Decimal Number 4829
 
3.8%
Uppercase Letter 1270
 
1.0%
Close Punctuation 602
 
0.5%
Open Punctuation 602
 
0.5%
Dash Punctuation 87
 
0.1%
Lowercase Letter 30
 
< 0.1%
Math Symbol 29
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 4154
 
5.3%
앞 3848
 
4.9%
역 3436
 
4.4%
번 3124
 
4.0%
출 3101
 
4.0%
동 1634
 
2.1%
교 1498
 
1.9%
리 1463
 
1.9%
사 1271
 
1.6%
대 1223
 
1.6%
Other values (404) 53343
68.3%
Uppercase Letter
ValueCountFrequency (%)
K 172
13.5%
C 160
12.6%
S 120
9.4%
M 99
 
7.8%
T 89
 
7.0%
A 85
 
6.7%
B 74
 
5.8%
D 69
 
5.4%
G 68
 
5.4%
I 60
 
4.7%
Other values (13) 274
21.6%
Decimal Number
ValueCountFrequency (%)
1 1359
28.1%
2 891
18.5%
3 634
13.1%
4 609
12.6%
5 297
 
6.2%
8 255
 
5.3%
6 242
 
5.0%
7 230
 
4.8%
0 186
 
3.9%
9 126
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
e 10
33.3%
l 4
 
13.3%
m 4
 
13.3%
o 4
 
13.3%
c 4
 
13.3%
t 4
 
13.3%
Other Punctuation
ValueCountFrequency (%)
' 20000
99.8%
, 37
 
0.2%
@ 8
 
< 0.1%
& 5
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 28
96.6%
+ 1
 
3.4%
Space Separator
ValueCountFrequency (%)
22730
100.0%
Close Punctuation
ValueCountFrequency (%)
) 602
100.0%
Open Punctuation
ValueCountFrequency (%)
( 602
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 78095
60.9%
Common 48931
38.1%
Latin 1300
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 4154
 
5.3%
앞 3848
 
4.9%
역 3436
 
4.4%
번 3124
 
4.0%
출 3101
 
4.0%
동 1634
 
2.1%
교 1498
 
1.9%
리 1463
 
1.9%
사 1271
 
1.6%
대 1223
 
1.6%
Other values (404) 53343
68.3%
Latin
ValueCountFrequency (%)
K 172
13.2%
C 160
12.3%
S 120
 
9.2%
M 99
 
7.6%
T 89
 
6.8%
A 85
 
6.5%
B 74
 
5.7%
D 69
 
5.3%
G 68
 
5.2%
I 60
 
4.6%
Other values (19) 304
23.4%
Common
ValueCountFrequency (%)
22730
46.5%
' 20000
40.9%
1 1359
 
2.8%
2 891
 
1.8%
3 634
 
1.3%
4 609
 
1.2%
) 602
 
1.2%
( 602
 
1.2%
5 297
 
0.6%
8 255
 
0.5%
Other values (11) 952
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 78095
60.9%
ASCII 50231
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22730
45.3%
' 20000
39.8%
1 1359
 
2.7%
2 891
 
1.8%
3 634
 
1.3%
4 609
 
1.2%
) 602
 
1.2%
( 602
 
1.2%
5 297
 
0.6%
8 255
 
0.5%
Other values (40) 2252
 
4.5%
Hangul
ValueCountFrequency (%)
구 4154
 
5.3%
앞 3848
 
4.9%
역 3436
 
4.4%
번 3124
 
4.0%
출 3101
 
4.0%
동 1634
 
2.1%
교 1498
 
1.9%
리 1463
 
1.9%
사 1271
 
1.6%
대 1223
 
1.6%
Other values (404) 53343
68.3%

'대여구분코드'
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
'정기'
8338 
'일일(회원)'
1300 
'일일(비회원)'
 
334
'단체'
 
28

Length

Max length9
Median length4
Mean length4.687
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
'정기' 8338
83.4%
'일일(회원)' 1300
 
13.0%
'일일(비회원)' 334
 
3.3%
'단체' 28
 
0.3%

Length

2024-03-14T01:23:51.325021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:23:51.401211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 8338
83.4%
일일(회원 1300
 
13.0%
일일(비회원 334
 
3.3%
단체 28
 
0.3%

'SEX_CD'
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
'M'
6047 
'F'
3652 
''
 
301

Length

Max length3
Median length3
Mean length2.9699
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
'M' 6047
60.5%
'F' 3652
36.5%
'' 301
 
3.0%

Length

2024-03-14T01:23:51.485780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:23:51.559300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 6047
60.5%
f 3652
36.5%
301
 
3.0%

'연령대코드'
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
'20대'
3536 
'30대'
2563 
'40대'
1809 
'50대'
1097 
<NA>
 
335
Other values (3)
660 

Length

Max length6
Median length5
Mean length4.9991
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row'20대'
2nd row'20대'
3rd row'40대'
4th row<NA>
5th row'50대'

Common Values

ValueCountFrequency (%)
'20대' 3536
35.4%
'30대' 2563
25.6%
'40대' 1809
18.1%
'50대' 1097
 
11.0%
<NA> 335
 
3.4%
'60대' 334
 
3.3%
'70대~' 167
 
1.7%
'~10대' 159
 
1.6%

Length

2024-03-14T01:23:51.646895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:23:51.757387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 3536
35.4%
30대 2563
25.6%
40대 1809
18.1%
50대 1097
 
11.0%
na 335
 
3.4%
60대 334
 
3.3%
70대 167
 
1.7%
10대 159
 
1.6%

'이용건수'
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7002
Minimum1
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:23:51.852491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum15
Range14
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.284167
Coefficient of variation (CV)0.75530349
Kurtosis13.38801
Mean1.7002
Median Absolute Deviation (MAD)0
Skewness3.0557325
Sum17002
Variance1.6490849
MonotonicityNot monotonic
2024-03-14T01:23:51.933182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 6294
62.9%
2 2132
 
21.3%
3 809
 
8.1%
4 346
 
3.5%
5 189
 
1.9%
6 91
 
0.9%
7 64
 
0.6%
8 36
 
0.4%
9 15
 
0.1%
11 10
 
0.1%
Other values (5) 14
 
0.1%
ValueCountFrequency (%)
1 6294
62.9%
2 2132
 
21.3%
3 809
 
8.1%
4 346
 
3.5%
5 189
 
1.9%
6 91
 
0.9%
7 64
 
0.6%
8 36
 
0.4%
9 15
 
0.1%
10 7
 
0.1%
ValueCountFrequency (%)
15 1
 
< 0.1%
14 1
 
< 0.1%
13 2
 
< 0.1%
12 3
 
< 0.1%
11 10
 
0.1%
10 7
 
0.1%
9 15
 
0.1%
8 36
 
0.4%
7 64
0.6%
6 91
0.9%

'운동량'
Real number (ℝ)

HIGH CORRELATION 

Distinct6763
Distinct (%)67.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean154.9817
Minimum0
Maximum7481.67
Zeros87
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:23:52.034252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16.449
Q140.44
median81.605
Q3169.0925
95-th percentile476.9685
Maximum7481.67
Range7481.67
Interquartile range (IQR)128.6525

Descriptive statistics

Standard deviation277.41153
Coefficient of variation (CV)1.7899631
Kurtosis158.72804
Mean154.9817
Median Absolute Deviation (MAD)49.955
Skewness9.2621744
Sum1549817
Variance76957.156
MonotonicityNot monotonic
2024-03-14T01:23:52.143010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 87
 
0.9%
18.53 15
 
0.1%
25.48 14
 
0.1%
27.28 14
 
0.1%
43.24 13
 
0.1%
27.03 12
 
0.1%
28.83 12
 
0.1%
28.31 12
 
0.1%
73.36 11
 
0.1%
29.09 11
 
0.1%
Other values (6753) 9799
98.0%
ValueCountFrequency (%)
0.0 87
0.9%
0.2 2
 
< 0.1%
0.34 1
 
< 0.1%
0.74 1
 
< 0.1%
1.54 1
 
< 0.1%
1.75 1
 
< 0.1%
2.06 1
 
< 0.1%
2.61 1
 
< 0.1%
2.83 1
 
< 0.1%
2.99 1
 
< 0.1%
ValueCountFrequency (%)
7481.67 1
< 0.1%
7259.62 1
< 0.1%
6124.24 1
< 0.1%
5639.38 1
< 0.1%
4812.89 1
< 0.1%
3557.52 1
< 0.1%
3504.63 1
< 0.1%
3444.53 1
< 0.1%
3270.85 1
< 0.1%
3171.45 1
< 0.1%

'탄소량'
Real number (ℝ)

HIGH CORRELATION 

Distinct767
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.321242
Minimum0
Maximum64.46
Zeros89
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:23:52.286916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.15
Q10.36
median0.71
Q31.44
95-th percentile4.0205
Maximum64.46
Range64.46
Interquartile range (IQR)1.08

Descriptive statistics

Standard deviation2.3279706
Coefficient of variation (CV)1.7619562
Kurtosis149.02392
Mean1.321242
Median Absolute Deviation (MAD)0.43
Skewness8.9840583
Sum13212.42
Variance5.419447
MonotonicityNot monotonic
2024-03-14T01:23:52.435962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.26 125
 
1.2%
0.19 115
 
1.1%
0.35 109
 
1.1%
0.24 108
 
1.1%
0.23 106
 
1.1%
0.32 106
 
1.1%
0.28 104
 
1.0%
0.39 102
 
1.0%
0.16 100
 
1.0%
0.18 99
 
1.0%
Other values (757) 8926
89.3%
ValueCountFrequency (%)
0.0 89
0.9%
0.01 2
 
< 0.1%
0.02 2
 
< 0.1%
0.03 4
 
< 0.1%
0.04 3
 
< 0.1%
0.05 5
 
0.1%
0.06 7
 
0.1%
0.07 11
 
0.1%
0.08 30
 
0.3%
0.09 28
 
0.3%
ValueCountFrequency (%)
64.46 1
< 0.1%
57.45 1
< 0.1%
52.76 1
< 0.1%
37.6 1
< 0.1%
36.77 1
< 0.1%
32.07 1
< 0.1%
31.05 1
< 0.1%
29.61 1
< 0.1%
29.53 1
< 0.1%
27.43 1
< 0.1%

'이동거리(M)'
Real number (ℝ)

HIGH CORRELATION 

Distinct1885
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5695.175
Minimum0
Maximum277840
Zeros87
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:23:52.578160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile650
Q11550
median3080
Q36200
95-th percentile17331.5
Maximum277840
Range277840
Interquartile range (IQR)4650

Descriptive statistics

Standard deviation10034.36
Coefficient of variation (CV)1.7619054
Kurtosis149.03238
Mean5695.175
Median Absolute Deviation (MAD)1870
Skewness8.9841792
Sum56951750
Variance1.0068837 × 108
MonotonicityNot monotonic
2024-03-14T01:23:52.699041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 87
 
0.9%
1030 39
 
0.4%
1190 36
 
0.4%
1280 35
 
0.4%
1530 34
 
0.3%
1560 32
 
0.3%
1160 31
 
0.3%
1960 31
 
0.3%
1100 30
 
0.3%
1330 30
 
0.3%
Other values (1875) 9615
96.2%
ValueCountFrequency (%)
0 87
0.9%
10 2
 
< 0.1%
30 1
 
< 0.1%
60 1
 
< 0.1%
70 1
 
< 0.1%
80 1
 
< 0.1%
110 2
 
< 0.1%
140 1
 
< 0.1%
150 1
 
< 0.1%
160 1
 
< 0.1%
ValueCountFrequency (%)
277840 1
< 0.1%
247650 1
< 0.1%
227430 1
< 0.1%
162050 1
< 0.1%
158490 1
< 0.1%
138210 1
< 0.1%
133820 1
< 0.1%
127660 1
< 0.1%
127290 1
< 0.1%
118220 1
< 0.1%

'이동시간(분)'
Real number (ℝ)

HIGH CORRELATION 

Distinct247
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.3952
Minimum0
Maximum674
Zeros19
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:23:53.044689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q110
median20
Q343
95-th percentile106
Maximum674
Range674
Interquartile range (IQR)33

Descriptive statistics

Standard deviation38.523019
Coefficient of variation (CV)1.1535496
Kurtosis22.578673
Mean33.3952
Median Absolute Deviation (MAD)13
Skewness3.3927915
Sum333952
Variance1484.023
MonotonicityNot monotonic
2024-03-14T01:23:53.151243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 354
 
3.5%
6 338
 
3.4%
7 331
 
3.3%
8 323
 
3.2%
9 322
 
3.2%
4 308
 
3.1%
11 300
 
3.0%
3 288
 
2.9%
10 280
 
2.8%
12 261
 
2.6%
Other values (237) 6895
69.0%
ValueCountFrequency (%)
0 19
 
0.2%
1 41
 
0.4%
2 167
1.7%
3 288
2.9%
4 308
3.1%
5 354
3.5%
6 338
3.4%
7 331
3.3%
8 323
3.2%
9 322
3.2%
ValueCountFrequency (%)
674 1
< 0.1%
545 1
< 0.1%
430 1
< 0.1%
407 1
< 0.1%
373 1
< 0.1%
372 1
< 0.1%
360 1
< 0.1%
356 1
< 0.1%
352 1
< 0.1%
329 1
< 0.1%

Interactions

2024-03-14T01:23:49.225441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:47.585337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:47.989593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:48.439142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:48.825884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:49.308409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:47.657872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:48.105377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:48.518194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:48.900192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:49.389552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:47.733395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:48.187578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:48.595252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:48.995632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:49.466215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:47.812187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:48.265132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:48.673038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:49.076264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:49.542173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:47.886317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:48.352140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:48.745977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:23:49.149485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T01:23:53.243515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
'대여일자''대여구분코드''SEX_CD''연령대코드''이용건수''운동량''탄소량''이동거리(M)''이동시간(분)'
'대여일자'1.0000.1730.2950.0710.1040.0000.0120.0120.033
'대여구분코드'0.1731.0000.6460.2370.1190.0290.0680.0680.222
'SEX_CD'0.2950.6461.0000.0840.1990.0770.0660.0660.234
'연령대코드'0.0710.2370.0841.0000.1050.0000.0000.0000.028
'이용건수'0.1040.1190.1990.1051.0000.2670.2430.2430.378
'운동량'0.0000.0290.0770.0000.2671.0000.9360.9360.486
'탄소량'0.0120.0680.0660.0000.2430.9361.0001.0000.423
'이동거리(M)'0.0120.0680.0660.0000.2430.9361.0001.0000.423
'이동시간(분)'0.0330.2220.2340.0280.3780.4860.4230.4231.000
2024-03-14T01:23:53.333469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
'SEX_CD''대여구분코드''연령대코드'
'SEX_CD'1.0000.6700.090
'대여구분코드'0.6701.0000.163
'연령대코드'0.0900.1631.000
2024-03-14T01:23:53.406345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
'이용건수''운동량''탄소량''이동거리(M)''이동시간(분)''대여구분코드''SEX_CD''연령대코드'
'이용건수'1.0000.5400.5360.5360.5060.0710.1210.053
'운동량'0.5401.0000.9870.9870.8300.0190.0340.000
'탄소량'0.5360.9871.0001.0000.8480.0310.0410.000
'이동거리(M)'0.5360.9871.0001.0000.8480.0310.0410.000
'이동시간(분)'0.5060.8300.8480.8481.0000.1440.1050.015
'대여구분코드'0.0710.0190.0310.0310.1441.0000.6700.163
'SEX_CD'0.1210.0340.0410.0410.1050.6701.0000.090
'연령대코드'0.0530.0000.0000.0000.0150.1630.0901.000

Missing values

2024-03-14T01:23:49.645811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T01:23:49.777613image/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)'
15766'2018-01-05''224'' 롯데캐슬 앞''정기''F''20대'111.920.125103
16767'2018-01-05''327'' 낙원상가 옆''정기''M''20대'9328.322.511086079
14272'2018-01-04''1911'' 구로디지털단지역 앞''정기''M''40대'5810.266.3527350162
3246'2018-01-01''1212'' 송파역 2번 출구앞''일일(비회원)'''<NA>260.230.54234018
4374'2018-01-02''2013'' 장승배기역 5번출구''정기''F''50대'129.860.2711604
10744'2018-01-03''415'' DMC역 9번출구 앞''정기''M''50대'248.620.4418708
16600'2018-01-05''374'' 청구역 2번출구 앞''정기''F''60대'128.510.351500104
2413'2018-01-01''2332'' 선릉역3번출구''일일(회원)''F''20대'143.240.3615609
10969'2018-01-03''220'' 미성아파트 A동 앞''일일(회원)''F''20대'2752.96.7829250195
15376'2018-01-04''385'' 종각역 5번출구''일일(비회원)'''<NA>132.690.29127014
'대여일자''대여소번호''대여소''대여구분코드''SEX_CD''연령대코드''이용건수''운동량''탄소량''이동거리(M)''이동시간(분)'
708'2018-01-01''508'' 성수아카데미타워 앞''정기''M''20대'123.090.198105
3880'2018-01-02''614'' 용두동 사거리''정기''F''30대'2218.432.371021046
4162'2018-01-02''602'' 장안동 사거리''정기''F''40대'149.680.45193013
13055'2018-01-04''1229'' 송파체육문화회관 앞''정기''M''20대'175.260.51221016
6660'2018-01-02''207'' 여의나루역 1번출구 앞''정기''M''60대'120.330.187903
15375'2018-01-04''810'' 이태원지하보도''일일(비회원)'''<NA>156.890.51221013
9346'2018-01-03''375'' 다산 어린이공원''정기''M''30대'21825.9115.386629022
7266'2018-01-02''2108'' 은천치안센터''일일(회원)''M''50대'194.770.9386030
16722'2018-01-05''2268'' 서초4동주민센터 ''정기''M''20대'10.00.0010
10930'2018-01-03''1714'' 도봉문화정보도서관 삼거리''일일(회원)''F''20대'162.550.56243054