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/A/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 started2024-05-04 03:15:36.016826
Analysis finished2024-05-04 03:15:45.868259
Duration9.85 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
'2018-06-03'
3124 
'2018-06-02'
3076 
'2018-06-01'
3017 
'2018-06-04'
783 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row'2018-06-02'
2nd row'2018-06-04'
3rd row'2018-06-03'
4th row'2018-06-04'
5th row'2018-06-02'

Common Values

ValueCountFrequency (%)
'2018-06-03' 3124
31.2%
'2018-06-02' 3076
30.8%
'2018-06-01' 3017
30.2%
'2018-06-04' 783
 
7.8%

Length

2024-05-04T03:15:46.059566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:15:46.366212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-06-03 3124
31.2%
2018-06-02 3076
30.8%
2018-06-01 3017
30.2%
2018-06-04 783
 
7.8%

'대여소번호'
Text

Distinct1258
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T03:15:47.047815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.5412
Min length5

Characters and Unicode

Total characters55412
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

Unique25 ?
Unique (%)0.2%

Sample

1st row'390'
2nd row'812'
3rd row'1936'
4th row'1151'
5th row'1952'
ValueCountFrequency (%)
716 21
 
0.2%
1625 21
 
0.2%
1265 21
 
0.2%
583 20
 
0.2%
914 19
 
0.2%
226 19
 
0.2%
3515 19
 
0.2%
2217 18
 
0.2%
213 18
 
0.2%
1122 18
 
0.2%
Other values (1248) 9806
98.1%
2024-05-04T03:15:48.167914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 20000
36.1%
1 7890
 
14.2%
2 6176
 
11.1%
3 3979
 
7.2%
5 3225
 
5.8%
0 3150
 
5.7%
4 2669
 
4.8%
6 2567
 
4.6%
7 2057
 
3.7%
9 1876
 
3.4%
Other values (5) 1823
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35408
63.9%
Other Punctuation 20000
36.1%
Other Letter 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7890
22.3%
2 6176
17.4%
3 3979
11.2%
5 3225
9.1%
0 3150
 
8.9%
4 2669
 
7.5%
6 2567
 
7.2%
7 2057
 
5.8%
9 1876
 
5.3%
8 1819
 
5.1%
Other Letter
ValueCountFrequency (%)
중 1
25.0%
랑 1
25.0%
센 1
25.0%
터 1
25.0%
Other Punctuation
ValueCountFrequency (%)
' 20000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 55408
> 99.9%
Hangul 4
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
' 20000
36.1%
1 7890
 
14.2%
2 6176
 
11.1%
3 3979
 
7.2%
5 3225
 
5.8%
0 3150
 
5.7%
4 2669
 
4.8%
6 2567
 
4.6%
7 2057
 
3.7%
9 1876
 
3.4%
Hangul
ValueCountFrequency (%)
중 1
25.0%
랑 1
25.0%
센 1
25.0%
터 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55408
> 99.9%
Hangul 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 20000
36.1%
1 7890
 
14.2%
2 6176
 
11.1%
3 3979
 
7.2%
5 3225
 
5.8%
0 3150
 
5.7%
4 2669
 
4.8%
6 2567
 
4.6%
7 2057
 
3.7%
9 1876
 
3.4%
Hangul
ValueCountFrequency (%)
중 1
25.0%
랑 1
25.0%
센 1
25.0%
터 1
25.0%

'대여소'
Text

Distinct1258
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T03:15:48.604564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length27
Mean length12.7092
Min length6

Characters and Unicode

Total characters127092
Distinct characters483
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

Unique25 ?
Unique (%)0.2%

Sample

1st row' 충무로역 1번출구'
2nd row' 용산전쟁기념관'
3rd row' 개봉역 1번 출구 자전거보관서쪽'
4th row' 마곡역1번출구'
5th row' 천왕연지타운2단지 앞'
ValueCountFrequency (%)
9919
31.2%
앞 2797
 
8.8%
옆 585
 
1.8%
1번출구 459
 
1.4%
출구 393
 
1.2%
사거리 336
 
1.1%
2번출구 304
 
1.0%
뒤 297
 
0.9%
4번출구 257
 
0.8%
교차로 255
 
0.8%
Other values (1513) 16168
50.9%
2024-05-04T03:15:49.269308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21799
 
17.2%
' 20000
 
15.7%
구 3803
 
3.0%
앞 3340
 
2.6%
역 3073
 
2.4%
번 2783
 
2.2%
출 2750
 
2.2%
동 1788
 
1.4%
교 1507
 
1.2%
리 1425
 
1.1%
Other values (473) 64824
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 77878
61.3%
Space Separator 21799
 
17.2%
Other Punctuation 20062
 
15.8%
Decimal Number 4848
 
3.8%
Uppercase Letter 1225
 
1.0%
Close Punctuation 555
 
0.4%
Open Punctuation 555
 
0.4%
Dash Punctuation 69
 
0.1%
Lowercase Letter 61
 
< 0.1%
Math Symbol 31
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3803
 
4.9%
앞 3340
 
4.3%
역 3073
 
3.9%
번 2783
 
3.6%
출 2750
 
3.5%
동 1788
 
2.3%
교 1507
 
1.9%
리 1425
 
1.8%
원 1291
 
1.7%
사 1239
 
1.6%
Other values (421) 54879
70.5%
Uppercase Letter
ValueCountFrequency (%)
K 177
14.4%
C 139
11.3%
S 124
10.1%
A 90
 
7.3%
L 88
 
7.2%
T 73
 
6.0%
G 71
 
5.8%
M 67
 
5.5%
I 60
 
4.9%
B 54
 
4.4%
Other values (13) 282
23.0%
Decimal Number
ValueCountFrequency (%)
1 1376
28.4%
2 871
18.0%
3 658
13.6%
4 574
11.8%
5 330
 
6.8%
0 243
 
5.0%
8 235
 
4.8%
6 221
 
4.6%
7 216
 
4.5%
9 124
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
e 29
47.5%
t 10
 
16.4%
k 6
 
9.8%
m 4
 
6.6%
o 4
 
6.6%
l 4
 
6.6%
c 4
 
6.6%
Other Punctuation
ValueCountFrequency (%)
' 20000
99.7%
, 40
 
0.2%
? 12
 
0.1%
& 8
 
< 0.1%
@ 2
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 20
64.5%
+ 11
35.5%
Space Separator
ValueCountFrequency (%)
21799
100.0%
Close Punctuation
ValueCountFrequency (%)
) 555
100.0%
Open Punctuation
ValueCountFrequency (%)
( 555
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 77878
61.3%
Common 47928
37.7%
Latin 1286
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3803
 
4.9%
앞 3340
 
4.3%
역 3073
 
3.9%
번 2783
 
3.6%
출 2750
 
3.5%
동 1788
 
2.3%
교 1507
 
1.9%
리 1425
 
1.8%
원 1291
 
1.7%
사 1239
 
1.6%
Other values (421) 54879
70.5%
Latin
ValueCountFrequency (%)
K 177
13.8%
C 139
10.8%
S 124
 
9.6%
A 90
 
7.0%
L 88
 
6.8%
T 73
 
5.7%
G 71
 
5.5%
M 67
 
5.2%
I 60
 
4.7%
B 54
 
4.2%
Other values (20) 343
26.7%
Common
ValueCountFrequency (%)
21799
45.5%
' 20000
41.7%
1 1376
 
2.9%
2 871
 
1.8%
3 658
 
1.4%
4 574
 
1.2%
) 555
 
1.2%
( 555
 
1.2%
5 330
 
0.7%
0 243
 
0.5%
Other values (12) 967
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 77878
61.3%
ASCII 49214
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21799
44.3%
' 20000
40.6%
1 1376
 
2.8%
2 871
 
1.8%
3 658
 
1.3%
4 574
 
1.2%
) 555
 
1.1%
( 555
 
1.1%
5 330
 
0.7%
0 243
 
0.5%
Other values (42) 2253
 
4.6%
Hangul
ValueCountFrequency (%)
구 3803
 
4.9%
앞 3340
 
4.3%
역 3073
 
3.9%
번 2783
 
3.6%
출 2750
 
3.5%
동 1788
 
2.3%
교 1507
 
1.9%
리 1425
 
1.8%
원 1291
 
1.7%
사 1239
 
1.6%
Other values (421) 54879
70.5%

'대여구분코드'
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
'정기'
6333 
'일일(회원)'
2823 
'일일(비회원)'
723 
'단체'
 
121

Length

Max length9
Median length4
Mean length5.4907
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
'정기' 6333
63.3%
'일일(회원)' 2823
28.2%
'일일(비회원)' 723
 
7.2%
'단체' 121
 
1.2%

Length

2024-05-04T03:15:49.688545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:15:49.884421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 6333
63.3%
일일(회원 2823
28.2%
일일(비회원 723
 
7.2%
단체 121
 
1.2%

'SEX_CD'
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
'M'
4799 
'F'
4577 
''
624 

Length

Max length3
Median length3
Mean length2.9376
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
'M' 4799
48.0%
'F' 4577
45.8%
'' 624
 
6.2%

Length

2024-05-04T03:15:50.103734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:15:50.360188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 4799
48.0%
f 4577
45.8%
624
 
6.2%

'연령대코드'
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
'20대'
3213 
'30대'
2558 
'40대'
1667 
'50대'
932 
<NA>
727 
Other values (3)
903 

Length

Max length6
Median length5
Mean length4.9895
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
'20대' 3213
32.1%
'30대' 2558
25.6%
'40대' 1667
16.7%
'50대' 932
 
9.3%
<NA> 727
 
7.3%
'~10대' 521
 
5.2%
'60대' 281
 
2.8%
'70대~' 101
 
1.0%

Length

2024-05-04T03:15:50.600819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:15:50.819810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 3213
32.1%
30대 2558
25.6%
40대 1667
16.7%
50대 932
 
9.3%
na 727
 
7.3%
10대 521
 
5.2%
60대 281
 
2.8%
70대 101
 
1.0%

'이용건수'
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2259
Minimum1
Maximum89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:15:51.061715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile10
Maximum89
Range88
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.7457272
Coefficient of variation (CV)1.1611418
Kurtosis63.797981
Mean3.2259
Median Absolute Deviation (MAD)1
Skewness5.2706601
Sum32259
Variance14.030472
MonotonicityNot monotonic
2024-05-04T03:15:51.391279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1 3962
39.6%
2 1992
19.9%
3 1226
 
12.3%
4 800
 
8.0%
5 520
 
5.2%
6 388
 
3.9%
7 243
 
2.4%
8 176
 
1.8%
9 138
 
1.4%
10 103
 
1.0%
Other values (33) 452
 
4.5%
ValueCountFrequency (%)
1 3962
39.6%
2 1992
19.9%
3 1226
 
12.3%
4 800
 
8.0%
5 520
 
5.2%
6 388
 
3.9%
7 243
 
2.4%
8 176
 
1.8%
9 138
 
1.4%
10 103
 
1.0%
ValueCountFrequency (%)
89 1
< 0.1%
77 1
< 0.1%
54 1
< 0.1%
53 1
< 0.1%
50 1
< 0.1%
46 1
< 0.1%
45 1
< 0.1%
39 2
< 0.1%
36 1
< 0.1%
35 2
< 0.1%

'운동량'
Real number (ℝ)

HIGH CORRELATION 

Distinct8424
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean421.41727
Minimum0
Maximum12855.85
Zeros68
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:15:51.865751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile23.674
Q182.45
median207.815
Q3473.9225
95-th percentile1597.44
Maximum12855.85
Range12855.85
Interquartile range (IQR)391.4725

Descriptive statistics

Standard deviation674.59397
Coefficient of variation (CV)1.6007744
Kurtosis66.099893
Mean421.41727
Median Absolute Deviation (MAD)150.485
Skewness5.9372634
Sum4214172.7
Variance455077.03
MonotonicityNot monotonic
2024-05-04T03:15:52.309764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 68
 
0.7%
33.98 9
 
0.1%
57.66 8
 
0.1%
15.44 8
 
0.1%
43.24 8
 
0.1%
21.62 8
 
0.1%
17.5 7
 
0.1%
34.23 6
 
0.1%
51.74 6
 
0.1%
28.83 6
 
0.1%
Other values (8414) 9866
98.7%
ValueCountFrequency (%)
0.0 68
0.7%
0.26 1
 
< 0.1%
0.83 1
 
< 0.1%
0.87 1
 
< 0.1%
0.93 1
 
< 0.1%
1.03 1
 
< 0.1%
1.09 1
 
< 0.1%
1.73 1
 
< 0.1%
2.16 1
 
< 0.1%
2.85 1
 
< 0.1%
ValueCountFrequency (%)
12855.85 1
< 0.1%
12764.05 1
< 0.1%
11817.63 1
< 0.1%
11003.53 1
< 0.1%
10954.16 1
< 0.1%
10069.72 1
< 0.1%
9383.54 1
< 0.1%
8850.36 1
< 0.1%
7854.32 1
< 0.1%
7670.02 1
< 0.1%

'탄소량'
Real number (ℝ)

HIGH CORRELATION 

Distinct1587
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.744058
Minimum0
Maximum132.4
Zeros69
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:15:52.721189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.22
Q10.75
median1.88
Q34.23
95-th percentile14.2105
Maximum132.4
Range132.4
Interquartile range (IQR)3.48

Descriptive statistics

Standard deviation5.9464639
Coefficient of variation (CV)1.5882403
Kurtosis71.093847
Mean3.744058
Median Absolute Deviation (MAD)1.36
Skewness6.0460166
Sum37440.58
Variance35.360433
MonotonicityNot monotonic
2024-05-04T03:15:53.129038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 69
 
0.7%
0.32 55
 
0.5%
0.35 53
 
0.5%
0.52 52
 
0.5%
0.39 51
 
0.5%
0.36 50
 
0.5%
0.29 48
 
0.5%
0.19 47
 
0.5%
0.68 46
 
0.5%
0.23 46
 
0.5%
Other values (1577) 9483
94.8%
ValueCountFrequency (%)
0.0 69
0.7%
0.01 6
 
0.1%
0.02 2
 
< 0.1%
0.03 1
 
< 0.1%
0.04 6
 
0.1%
0.05 5
 
0.1%
0.06 6
 
0.1%
0.07 8
 
0.1%
0.08 13
 
0.1%
0.09 10
 
0.1%
ValueCountFrequency (%)
132.4 1
< 0.1%
111.43 1
< 0.1%
98.72 1
< 0.1%
96.83 1
< 0.1%
88.17 1
< 0.1%
84.73 1
< 0.1%
84.56 1
< 0.1%
70.76 1
< 0.1%
69.1 1
< 0.1%
66.51 1
< 0.1%

'이동거리(M)'
Real number (ℝ)

HIGH CORRELATION 

Distinct3654
Distinct (%)36.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16138.092
Minimum0
Maximum570520
Zeros68
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:15:53.535838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile960
Q13230
median8105
Q318230
95-th percentile61231.5
Maximum570520
Range570520
Interquartile range (IQR)15000

Descriptive statistics

Standard deviation25631.767
Coefficient of variation (CV)1.5882774
Kurtosis71.092948
Mean16138.092
Median Absolute Deviation (MAD)5845
Skewness6.046242
Sum1.6138092 × 108
Variance6.5698746 × 108
MonotonicityNot monotonic
2024-05-04T03:15:53.953075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 68
 
0.7%
2260 18
 
0.2%
2310 18
 
0.2%
1080 17
 
0.2%
1370 17
 
0.2%
1060 16
 
0.2%
1970 15
 
0.1%
2940 15
 
0.1%
1590 15
 
0.1%
1200 15
 
0.1%
Other values (3644) 9786
97.9%
ValueCountFrequency (%)
0 68
0.7%
10 1
 
< 0.1%
30 1
 
< 0.1%
40 4
 
< 0.1%
60 1
 
< 0.1%
70 1
 
< 0.1%
90 1
 
< 0.1%
120 1
 
< 0.1%
160 1
 
< 0.1%
170 4
 
< 0.1%
ValueCountFrequency (%)
570520 1
< 0.1%
480540 1
< 0.1%
425570 1
< 0.1%
417400 1
< 0.1%
379820 1
< 0.1%
365320 1
< 0.1%
364550 1
< 0.1%
305140 1
< 0.1%
297980 1
< 0.1%
286690 1
< 0.1%

'이동시간(분)'
Real number (ℝ)

HIGH CORRELATION 

Distinct646
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean105.3548
Minimum0
Maximum4929
Zeros9
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:15:54.360030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q125
median59
Q3125
95-th percentile342
Maximum4929
Range4929
Interquartile range (IQR)100

Descriptive statistics

Standard deviation160.81843
Coefficient of variation (CV)1.5264462
Kurtosis150.19149
Mean105.3548
Median Absolute Deviation (MAD)42
Skewness8.3360576
Sum1053548
Variance25862.568
MonotonicityNot monotonic
2024-05-04T03:15:54.789886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 134
 
1.3%
11 133
 
1.3%
8 130
 
1.3%
7 129
 
1.3%
14 123
 
1.2%
10 123
 
1.2%
16 118
 
1.2%
20 118
 
1.2%
17 118
 
1.2%
9 117
 
1.2%
Other values (636) 8757
87.6%
ValueCountFrequency (%)
0 9
 
0.1%
1 10
 
0.1%
2 40
 
0.4%
3 70
0.7%
4 95
0.9%
5 94
0.9%
6 114
1.1%
7 129
1.3%
8 130
1.3%
9 117
1.2%
ValueCountFrequency (%)
4929 1
< 0.1%
3640 1
< 0.1%
3042 1
< 0.1%
2827 1
< 0.1%
2779 1
< 0.1%
2413 1
< 0.1%
1879 1
< 0.1%
1857 1
< 0.1%
1792 1
< 0.1%
1658 1
< 0.1%

Interactions

2024-05-04T03:15:43.686353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:38.566843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:39.795450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:41.084940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:42.610803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:43.927471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:38.746739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:40.062088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:41.470950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:42.774780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:44.218750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:39.013291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:40.313132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:41.756909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:42.987348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:44.411734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:39.284673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:40.552090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:42.038494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:43.216857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:44.591897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:39.576808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:40.780858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:42.350062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:15:43.467561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T03:15:55.059276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
'대여일자''대여구분코드''SEX_CD''연령대코드''이용건수''운동량''탄소량''이동거리(M)''이동시간(분)'
'대여일자'1.0000.3370.2340.0900.0360.0000.0280.0280.038
'대여구분코드'0.3371.0000.6320.1870.0670.0670.0820.0820.137
'SEX_CD'0.2340.6321.0000.0990.0950.1220.1160.1160.237
'연령대코드'0.0900.1870.0991.0000.1530.1150.1090.1090.121
'이용건수'0.0360.0670.0950.1531.0000.8180.8880.8870.964
'운동량'0.0000.0670.1220.1150.8181.0000.9720.9720.831
'탄소량'0.0280.0820.1160.1090.8880.9721.0001.0000.890
'이동거리(M)'0.0280.0820.1160.1090.8870.9721.0001.0000.890
'이동시간(분)'0.0380.1370.2370.1210.9640.8310.8900.8901.000
2024-05-04T03:15:55.368372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
'SEX_CD''연령대코드''대여구분코드''대여일자'
'SEX_CD'1.0000.1060.6530.223
'연령대코드'0.1061.0000.1300.062
'대여구분코드'0.6530.1301.0000.137
'대여일자'0.2230.0620.1371.000
2024-05-04T03:15:55.603001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
'이용건수''운동량''탄소량''이동거리(M)''이동시간(분)''대여일자''대여구분코드''SEX_CD''연령대코드'
'이용건수'1.0000.7190.7210.7210.7350.0240.0430.0420.081
'운동량'0.7191.0000.9920.9920.8760.0000.0400.0730.058
'탄소량'0.7210.9921.0001.0000.8870.0170.0490.0690.057
'이동거리(M)'0.7210.9921.0001.0000.8870.0170.0490.0690.057
'이동시간(분)'0.7350.8760.8870.8871.0000.0240.0880.1070.043
'대여일자'0.0240.0000.0170.0170.0241.0000.1370.2230.062
'대여구분코드'0.0430.0400.0490.0490.0880.1371.0000.6530.130
'SEX_CD'0.0420.0730.0690.0690.1070.2230.6531.0000.106
'연령대코드'0.0810.0580.0570.0570.0430.0620.1300.1061.000

Missing values

2024-05-04T03:15:45.138157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T03:15:45.644445image/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)'
14013'2018-06-02''390'' 충무로역 1번출구''정기''F''20대'5621.056.0926280165
40870'2018-06-04''812'' 용산전쟁기념관''정기''F''30대'2243.541.76760063
37118'2018-06-03''1936'' 개봉역 1번 출구 자전거보관서쪽''일일(회원)''M''30대'2995.867.8733940225
40435'2018-06-04''1151'' 마곡역1번출구''정기''F''30대'296.320.9389046
14829'2018-06-02''1952'' 천왕연지타운2단지 앞''정기''F''30대'1100.130.9389038
38550'2018-06-03''418'' 월드컵경기장역 3번출구 옆''일일(비회원)'''<NA>2201.281.817820167
13420'2018-06-02''612'' 시립동부병원 앞 사거리''정기''F''20대'3501.434.882106091
33886'2018-06-03''243'' 이앤씨드림타워 앞''일일(회원)''F''20대'7301.363.1613620205
27255'2018-06-03''1445'' 용마지구대''정기''F''30대'1856.839.133934023
19748'2018-06-02''924'' 메뚜기다리''정기''M''50대'140.510.3615508
'대여일자''대여소번호''대여소''대여구분코드''SEX_CD''연령대코드''이용건수''운동량''탄소량''이동거리(M)''이동시간(분)'
22693'2018-06-02''3102'' 연희삼거리''일일(회원)''M''20대'7657.925.9125530197
12530'2018-06-01''1416'' 상봉역 3번출구''일일(비회원)'''<NA>133.720.313107
14712'2018-06-02''2127'' 보성운수차고지 맞은편''정기''F''30대'1122.271.1475025
1579'2018-06-01''1454'' 한국전력공사(동대문 중랑지사)''정기''F''30대'270.80.77332018
32728'2018-06-03''388'' 동성중학교 앞''정기''M''50대'154.670.41177023
39030'2018-06-03''1106'' 신방화사거리''단체''M''40대'21959.0115.36596083
13786'2018-06-02''1920'' 서울미래초등학교 사거리''정기''F''20대'3917.549.2339800150
1172'2018-06-01''2333'' 양재역 3번출구 주변''정기''F''20대'3993.539.173950047
19164'2018-06-02''226'' 샛강역 1번출구 앞''정기''M''40대'297.570.73315016
30227'2018-06-03''2231'' 삼성타운(삼성생명) A동 맞은편''정기''M''20대'61389.3310.8546780259