Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory976.6 KiB
Average record size in memory100.0 B

Variable types

DateTime1
Numeric4
Text3
Categorical3

Dataset

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

Alerts

대여일자 has constant value ""Constant
이동거리(M) is highly overall correlated with 이용시간(분)High correlation
이용시간(분) is highly overall correlated with 이동거리(M)High correlation
대여구분코드 is highly imbalanced (51.9%)Imbalance
이동거리(M) has 1447 (14.5%) zerosZeros

Reproduction

Analysis started2024-03-13 16:25:27.498127
Analysis finished2024-03-13 16:25:29.782355
Duration2.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-01-01 00:00:00
Maximum2022-01-01 00:00:00
2024-03-14T01:25:29.817007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:25:29.888529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

대여소번호
Real number (ℝ)

Distinct1650
Distinct (%)16.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1187.4777
Minimum102
Maximum2646
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:25:29.987706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile191.95
Q1607
median1137
Q31706
95-th percentile2398
Maximum2646
Range2544
Interquartile range (IQR)1099

Descriptive statistics

Standard deviation696.25291
Coefficient of variation (CV)0.58632925
Kurtosis-0.93055131
Mean1187.4777
Median Absolute Deviation (MAD)549
Skewness0.30757418
Sum11874777
Variance484768.11
MonotonicityNot monotonic
2024-03-14T01:25:30.100168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
502 26
 
0.3%
2102 26
 
0.3%
1210 25
 
0.2%
1124 24
 
0.2%
1637 24
 
0.2%
2622 24
 
0.2%
1166 22
 
0.2%
2262 19
 
0.2%
1625 19
 
0.2%
1153 19
 
0.2%
Other values (1640) 9772
97.7%
ValueCountFrequency (%)
102 15
0.1%
103 14
0.1%
104 8
0.1%
105 6
 
0.1%
106 8
0.1%
107 9
0.1%
108 7
0.1%
109 2
 
< 0.1%
111 3
 
< 0.1%
112 6
 
0.1%
ValueCountFrequency (%)
2646 8
0.1%
2645 5
0.1%
2644 7
0.1%
2643 3
 
< 0.1%
2642 7
0.1%
2641 8
0.1%
2639 8
0.1%
2638 4
 
< 0.1%
2637 11
0.1%
2635 4
 
< 0.1%

대여소
Text

Distinct1650
Distinct (%)16.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T01:25:30.288297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length30
Mean length15.4844
Min length7

Characters and Unicode

Total characters154844
Distinct characters525
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)1.3%

Sample

1st row2270. 서초포레스타 7단지
2nd row2330. 역삼월드메르디앙아파트 앞
3rd row148. 용강동 주민센터 앞
4th row2137. KT&G 관악지점
5th row1169. 염창역 1번 출구
ValueCountFrequency (%)
앞 2650
 
8.7%
출구 455
 
1.5%
옆 452
 
1.5%
1번출구 341
 
1.1%
3번출구 289
 
1.0%
뒤 276
 
0.9%
2번출구 256
 
0.8%
4번출구 248
 
0.8%
사거리 235
 
0.8%
교차로 234
 
0.8%
Other values (3391) 24882
82.1%
2024-03-14T01:25:30.800180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20497
 
13.2%
. 10032
 
6.5%
1 9339
 
6.0%
2 6357
 
4.1%
3 3869
 
2.5%
구 3844
 
2.5%
6 3537
 
2.3%
4 3492
 
2.3%
5 3282
 
2.1%
0 3262
 
2.1%
Other values (515) 87333
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80036
51.7%
Decimal Number 41232
26.6%
Space Separator 20497
 
13.2%
Other Punctuation 10167
 
6.6%
Uppercase Letter 1085
 
0.7%
Open Punctuation 823
 
0.5%
Close Punctuation 823
 
0.5%
Dash Punctuation 79
 
0.1%
Lowercase Letter 76
 
< 0.1%
Math Symbol 13
 
< 0.1%
Other values (2) 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3844
 
4.8%
역 3128
 
3.9%
앞 3070
 
3.8%
번 2834
 
3.5%
출 2733
 
3.4%
동 2088
 
2.6%
교 1719
 
2.1%
리 1377
 
1.7%
아 1289
 
1.6%
파 1217
 
1.5%
Other values (460) 56737
70.9%
Uppercase Letter
ValueCountFrequency (%)
K 144
13.3%
S 131
12.1%
T 109
10.0%
C 102
9.4%
A 89
8.2%
B 87
8.0%
I 62
 
5.7%
G 51
 
4.7%
M 49
 
4.5%
L 45
 
4.1%
Other values (12) 216
19.9%
Decimal Number
ValueCountFrequency (%)
1 9339
22.6%
2 6357
15.4%
3 3869
9.4%
6 3537
 
8.6%
4 3492
 
8.5%
5 3282
 
8.0%
0 3262
 
7.9%
7 3032
 
7.4%
9 2565
 
6.2%
8 2497
 
6.1%
Lowercase Letter
ValueCountFrequency (%)
e 26
34.2%
n 12
15.8%
l 10
 
13.2%
y 6
 
7.9%
o 4
 
5.3%
m 4
 
5.3%
c 4
 
5.3%
t 4
 
5.3%
k 3
 
3.9%
s 3
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 10032
98.7%
, 106
 
1.0%
? 13
 
0.1%
& 11
 
0.1%
· 5
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 11
84.6%
+ 2
 
15.4%
Space Separator
ValueCountFrequency (%)
20497
100.0%
Open Punctuation
ValueCountFrequency (%)
( 823
100.0%
Close Punctuation
ValueCountFrequency (%)
) 823
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 12
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80037
51.7%
Common 73646
47.6%
Latin 1161
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3844
 
4.8%
역 3128
 
3.9%
앞 3070
 
3.8%
번 2834
 
3.5%
출 2733
 
3.4%
동 2088
 
2.6%
교 1719
 
2.1%
리 1377
 
1.7%
아 1289
 
1.6%
파 1217
 
1.5%
Other values (461) 56738
70.9%
Latin
ValueCountFrequency (%)
K 144
12.4%
S 131
11.3%
T 109
 
9.4%
C 102
 
8.8%
A 89
 
7.7%
B 87
 
7.5%
I 62
 
5.3%
G 51
 
4.4%
M 49
 
4.2%
L 45
 
3.9%
Other values (22) 292
25.2%
Common
ValueCountFrequency (%)
20497
27.8%
. 10032
13.6%
1 9339
12.7%
2 6357
 
8.6%
3 3869
 
5.3%
6 3537
 
4.8%
4 3492
 
4.7%
5 3282
 
4.5%
0 3262
 
4.4%
7 3032
 
4.1%
Other values (12) 6947
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80036
51.7%
ASCII 74802
48.3%
None 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20497
27.4%
. 10032
13.4%
1 9339
12.5%
2 6357
 
8.5%
3 3869
 
5.2%
6 3537
 
4.7%
4 3492
 
4.7%
5 3282
 
4.4%
0 3262
 
4.4%
7 3032
 
4.1%
Other values (43) 8103
 
10.8%
Hangul
ValueCountFrequency (%)
구 3844
 
4.8%
역 3128
 
3.9%
앞 3070
 
3.8%
번 2834
 
3.5%
출 2733
 
3.4%
동 2088
 
2.6%
교 1719
 
2.1%
리 1377
 
1.7%
아 1289
 
1.6%
파 1217
 
1.5%
Other values (460) 56737
70.9%
None
ValueCountFrequency (%)
· 5
83.3%
㈜ 1
 
16.7%

대여구분코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정기
7461 
일일(회원)
2283 
일일(비회원)
 
145
단체
 
111

Length

Max length7
Median length2
Mean length2.9857
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정기
2nd row정기
3rd row정기
4th row정기
5th row정기

Common Values

ValueCountFrequency (%)
정기 7461
74.6%
일일(회원) 2283
 
22.8%
일일(비회원) 145
 
1.5%
단체 111
 
1.1%

Length

2024-03-14T01:25:30.905311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:25:30.982072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 7461
74.6%
일일(회원 2283
 
22.8%
일일(비회원 145
 
1.5%
단체 111
 
1.1%

성별
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
M
4078 
\N
3169 
F
2285 
<NA>
465 
m
 
2

Length

Max length4
Median length1
Mean length1.4564
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowF
2nd row\N
3rd rowM
4th rowM
5th row\N

Common Values

ValueCountFrequency (%)
M 4078
40.8%
\N 3169
31.7%
F 2285
22.9%
<NA> 465
 
4.7%
m 2
 
< 0.1%
f 1
 
< 0.1%

Length

2024-03-14T01:25:31.067411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:25:31.152395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 4080
40.8%
n 3169
31.7%
f 2286
22.9%
na 465
 
4.7%

연령대코드
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20대
2981 
30대
2104 
40대
1427 
기타
1149 
50대
1119 
Other values (3)
1220 

Length

Max length5
Median length3
Mean length2.9007
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row50대
2nd row20대
3rd row50대
4th row40대
5th row20대

Common Values

ValueCountFrequency (%)
20대 2981
29.8%
30대 2104
21.0%
40대 1427
14.3%
기타 1149
 
11.5%
50대 1119
 
11.2%
10대 675
 
6.8%
60대 467
 
4.7%
70대이상 78
 
0.8%

Length

2024-03-14T01:25:31.245624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:25:31.355596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 2981
29.8%
30대 2104
21.0%
40대 1427
14.3%
기타 1149
 
11.5%
50대 1119
 
11.2%
10대 675
 
6.8%
60대 467
 
4.7%
70대이상 78
 
0.8%

이용건수
Real number (ℝ)

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4951
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:25:31.468421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile3
Maximum12
Range11
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.96149282
Coefficient of variation (CV)0.64309599
Kurtosis13.552046
Mean1.4951
Median Absolute Deviation (MAD)0
Skewness3.0186293
Sum14951
Variance0.92446844
MonotonicityNot monotonic
2024-03-14T01:25:31.562389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 6931
69.3%
2 2001
 
20.0%
3 616
 
6.2%
4 250
 
2.5%
5 123
 
1.2%
6 37
 
0.4%
7 22
 
0.2%
8 10
 
0.1%
9 5
 
0.1%
10 3
 
< 0.1%
ValueCountFrequency (%)
1 6931
69.3%
2 2001
 
20.0%
3 616
 
6.2%
4 250
 
2.5%
5 123
 
1.2%
6 37
 
0.4%
7 22
 
0.2%
8 10
 
0.1%
9 5
 
0.1%
10 3
 
< 0.1%
ValueCountFrequency (%)
12 2
 
< 0.1%
10 3
 
< 0.1%
9 5
 
0.1%
8 10
 
0.1%
7 22
 
0.2%
6 37
 
0.4%
5 123
 
1.2%
4 250
 
2.5%
3 616
 
6.2%
2 2001
20.0%

운동량
Text

Distinct6179
Distinct (%)61.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T01:25:31.864138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0814
Min length2

Characters and Unicode

Total characters50814
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

Unique4773 ?
Unique (%)47.7%

Sample

1st row0.00
2nd row31.13
3rd row37.98
4th row62.55
5th row34.69
ValueCountFrequency (%)
0.00 1412
 
14.1%
n 37
 
0.4%
23.17 11
 
0.1%
36.04 10
 
0.1%
41.70 10
 
0.1%
18.53 10
 
0.1%
22.45 9
 
0.1%
25.23 9
 
0.1%
28.83 9
 
0.1%
24.03 8
 
0.1%
Other values (6169) 8475
84.8%
2024-03-14T01:25:32.274019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9963
19.6%
0 7062
13.9%
1 5345
10.5%
2 4532
8.9%
3 3979
 
7.8%
4 3733
 
7.3%
5 3534
 
7.0%
6 3345
 
6.6%
7 3110
 
6.1%
8 3090
 
6.1%
Other values (3) 3121
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40777
80.2%
Other Punctuation 10000
 
19.7%
Uppercase Letter 37
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7062
17.3%
1 5345
13.1%
2 4532
11.1%
3 3979
9.8%
4 3733
9.2%
5 3534
8.7%
6 3345
8.2%
7 3110
7.6%
8 3090
7.6%
9 3047
7.5%
Other Punctuation
ValueCountFrequency (%)
. 9963
99.6%
\ 37
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
N 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 50777
99.9%
Latin 37
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9963
19.6%
0 7062
13.9%
1 5345
10.5%
2 4532
8.9%
3 3979
 
7.8%
4 3733
 
7.4%
5 3534
 
7.0%
6 3345
 
6.6%
7 3110
 
6.1%
8 3090
 
6.1%
Other values (2) 3084
 
6.1%
Latin
ValueCountFrequency (%)
N 37
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50814
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9963
19.6%
0 7062
13.9%
1 5345
10.5%
2 4532
8.9%
3 3979
 
7.8%
4 3733
 
7.3%
5 3534
 
7.0%
6 3345
 
6.6%
7 3110
 
6.1%
8 3090
 
6.1%
Other values (3) 3121
 
6.1%

탄소량
Text

Distinct511
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T01:25:32.647902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.993
Min length2

Characters and Unicode

Total characters39930
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

Unique126 ?
Unique (%)1.3%

Sample

1st row0.00
2nd row0.30
3rd row0.32
4th row0.56
5th row0.30
ValueCountFrequency (%)
0.00 1421
 
14.2%
0.19 147
 
1.5%
0.17 132
 
1.3%
0.20 131
 
1.3%
0.26 125
 
1.2%
0.22 121
 
1.2%
0.32 120
 
1.2%
0.23 119
 
1.2%
0.35 117
 
1.2%
0.24 117
 
1.2%
Other values (501) 7450
74.5%
2024-03-14T01:25:33.057456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12019
30.1%
. 9963
25.0%
1 3556
 
8.9%
2 2750
 
6.9%
3 2336
 
5.9%
4 1939
 
4.9%
5 1756
 
4.4%
6 1530
 
3.8%
7 1420
 
3.6%
8 1364
 
3.4%
Other values (3) 1297
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29893
74.9%
Other Punctuation 10000
 
25.0%
Uppercase Letter 37
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12019
40.2%
1 3556
 
11.9%
2 2750
 
9.2%
3 2336
 
7.8%
4 1939
 
6.5%
5 1756
 
5.9%
6 1530
 
5.1%
7 1420
 
4.8%
8 1364
 
4.6%
9 1223
 
4.1%
Other Punctuation
ValueCountFrequency (%)
. 9963
99.6%
\ 37
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
N 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39893
99.9%
Latin 37
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12019
30.1%
. 9963
25.0%
1 3556
 
8.9%
2 2750
 
6.9%
3 2336
 
5.9%
4 1939
 
4.9%
5 1756
 
4.4%
6 1530
 
3.8%
7 1420
 
3.6%
8 1364
 
3.4%
Other values (2) 1260
 
3.2%
Latin
ValueCountFrequency (%)
N 37
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39930
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12019
30.1%
. 9963
25.0%
1 3556
 
8.9%
2 2750
 
6.9%
3 2336
 
5.9%
4 1939
 
4.9%
5 1756
 
4.4%
6 1530
 
3.8%
7 1420
 
3.6%
8 1364
 
3.4%
Other values (3) 1297
 
3.2%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct5000
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3143.3531
Minimum0
Maximum96921
Zeros1447
Zeros (%)14.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:25:33.178253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1750
median1740.58
Q33901.9825
95-th percentile11328.617
Maximum96921
Range96921
Interquartile range (IQR)3151.9825

Descriptive statistics

Standard deviation4174.5095
Coefficient of variation (CV)1.3280435
Kurtosis36.62189
Mean3143.3531
Median Absolute Deviation (MAD)1300.58
Skewness3.8304044
Sum31433531
Variance17426530
MonotonicityNot monotonic
2024-03-14T01:25:33.287301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1447
 
14.5%
1050.0 31
 
0.3%
1070.0 24
 
0.2%
1400.0 22
 
0.2%
720.0 22
 
0.2%
640.0 22
 
0.2%
830.0 22
 
0.2%
820.0 22
 
0.2%
950.0 21
 
0.2%
960.0 21
 
0.2%
Other values (4990) 8346
83.5%
ValueCountFrequency (%)
0.0 1447
14.5%
0.1 2
 
< 0.1%
0.2 2
 
< 0.1%
0.26 3
 
< 0.1%
0.29 1
 
< 0.1%
10.0 2
 
< 0.1%
20.0 1
 
< 0.1%
40.0 2
 
< 0.1%
60.0 1
 
< 0.1%
80.0 2
 
< 0.1%
ValueCountFrequency (%)
96921.0 1
< 0.1%
47514.01 1
< 0.1%
43833.26 1
< 0.1%
43810.0 1
< 0.1%
36192.73 1
< 0.1%
35340.0 1
< 0.1%
35010.0 1
< 0.1%
34380.0 1
< 0.1%
34368.04 1
< 0.1%
33847.15 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct257
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.0389
Minimum0
Maximum911
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:25:33.391551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q19
median19
Q344
95-th percentile112
Maximum911
Range911
Interquartile range (IQR)35

Descriptive statistics

Standard deviation41.077073
Coefficient of variation (CV)1.2067685
Kurtosis36.360942
Mean34.0389
Median Absolute Deviation (MAD)13
Skewness3.9152135
Sum340389
Variance1687.3259
MonotonicityNot monotonic
2024-03-14T01:25:33.515495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 412
 
4.1%
5 362
 
3.6%
7 360
 
3.6%
9 346
 
3.5%
8 336
 
3.4%
4 334
 
3.3%
11 319
 
3.2%
3 298
 
3.0%
10 287
 
2.9%
12 256
 
2.6%
Other values (247) 6690
66.9%
ValueCountFrequency (%)
0 3
 
< 0.1%
1 49
 
0.5%
2 174
1.7%
3 298
3.0%
4 334
3.3%
5 362
3.6%
6 412
4.1%
7 360
3.6%
8 336
3.4%
9 346
3.5%
ValueCountFrequency (%)
911 1
< 0.1%
546 1
< 0.1%
502 1
< 0.1%
467 1
< 0.1%
417 1
< 0.1%
402 1
< 0.1%
398 1
< 0.1%
393 1
< 0.1%
386 1
< 0.1%
367 1
< 0.1%

Interactions

2024-03-14T01:25:29.270672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:25:28.382508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:25:28.659394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:25:28.938463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:25:29.338574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:25:28.452077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:25:28.730043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:25:29.008192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:25:29.413640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:25:28.523468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:25:28.802783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:25:29.090639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:25:29.490705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:25:28.594359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:25:28.872654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:25:29.184413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T01:25:33.618319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호대여구분코드성별연령대코드이용건수이동거리(M)이용시간(분)
대여소번호1.0000.0440.0190.0520.0650.0350.038
대여구분코드0.0441.0000.1240.4810.1250.0910.122
성별0.0190.1241.0000.1090.0760.0000.000
연령대코드0.0520.4810.1091.0000.1320.0050.033
이용건수0.0650.1250.0760.1321.0000.5640.624
이동거리(M)0.0350.0910.0000.0050.5641.0000.704
이용시간(분)0.0380.1220.0000.0330.6240.7041.000
2024-03-14T01:25:33.718407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여구분코드성별연령대코드
대여구분코드1.0000.1020.231
성별0.1021.0000.066
연령대코드0.2310.0661.000
2024-03-14T01:25:33.789039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)대여구분코드성별연령대코드
대여소번호1.000-0.047-0.017-0.0260.0270.0080.025
이용건수-0.0471.0000.4140.4590.0750.0320.063
이동거리(M)-0.0170.4141.0000.6720.0590.0000.003
이용시간(분)-0.0260.4590.6721.0000.0840.0000.017
대여구분코드0.0270.0750.0590.0841.0000.1020.231
성별0.0080.0320.0000.0000.1021.0000.066
연령대코드0.0250.0630.0030.0170.2310.0661.000

Missing values

2024-03-14T01:25:29.582623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T01:25:29.717946image/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

대여일자대여소번호대여소대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
129122022-01-0122702270. 서초포레스타 7단지정기F50대10.000.000.036
131082022-01-0123302330. 역삼월드메르디앙아파트 앞정기\N20대131.130.301310.09
4322022-01-01148148. 용강동 주민센터 앞정기M50대137.980.321370.020
122822022-01-0121372137. KT&G 관악지점정기M40대162.550.562430.021
73082022-01-0111691169. 염창역 1번 출구정기\N20대234.690.301320.09
112912022-01-0119241924. 삼부르네상스파크빌정기F20대130.480.271148.848
102232022-01-0116651665. 양지근린공원앞정기\N40대10.000.000.08
55472022-01-01916916. 평생학습관 앞정기M60대126.640.21897.1338
121012022-01-0121052105. 미성동 신림체육센터정기M20대161.460.512217.1827
7492022-01-01198198. 충정2교정기M50대129.700.291250.017
대여일자대여소번호대여소대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
47942022-01-01781781.신정보도육교 아래정기F10대10.000.000.04
134792022-01-0125152515.서초초등학교 후문정기\N40대10.000.000.09
10502022-01-01233233. 양평1동 YP센터 앞정기M40대299.780.863710.034
25752022-01-01471471.회현사거리 남측정기M40대2479.932.5711080.061
58482022-01-01972972. 수색역정기M30대4140.611.104748.2534
112532022-01-0119131913. 구로리공원정기<NA>20대147.070.341485.9516
47292022-01-01776776.목마공원일일(회원)\N20대2434.463.7516157.02181
129512022-01-0122812281. 연세사랑병원신관앞정기\N40대10.000.000.06
135242022-01-0125252525.반포쇼핑타운 2동 앞일일(회원)M20대1100.900.913920.034
37382022-01-01635635. 시조사 앞 (청량고정문 옆)정기F20대168.540.632704.2520