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-15248/F/1/datasetView.do

Alerts

대여일자 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
이동거리(M) has 538 (5.4%) zerosZeros

Reproduction

Analysis started2024-03-13 13:00:34.246119
Analysis finished2024-03-13 13:00:38.995952
Duration4.75 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
2024-03-13T22:00:39.053231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:00:39.158898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

대여소번호
Real number (ℝ)

Distinct2499
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2001.3252
Minimum102
Maximum4892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T22:00:39.734762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile240.95
Q1825
median1690
Q33002.25
95-th percentile4580
Maximum4892
Range4790
Interquartile range (IQR)2177.25

Descriptive statistics

Standard deviation1387.8396
Coefficient of variation (CV)0.69346033
Kurtosis-0.89272079
Mean2001.3252
Median Absolute Deviation (MAD)968
Skewness0.54760411
Sum20013252
Variance1926098.9
MonotonicityNot monotonic
2024-03-13T22:00:39.931976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
770 13
 
0.1%
247 12
 
0.1%
3518 12
 
0.1%
746 11
 
0.1%
2647 11
 
0.1%
2721 11
 
0.1%
2431 10
 
0.1%
1132 10
 
0.1%
549 10
 
0.1%
637 10
 
0.1%
Other values (2489) 9890
98.9%
ValueCountFrequency (%)
102 5
0.1%
103 9
0.1%
104 4
< 0.1%
105 2
 
< 0.1%
106 3
 
< 0.1%
107 5
0.1%
108 8
0.1%
109 1
 
< 0.1%
111 7
0.1%
112 3
 
< 0.1%
ValueCountFrequency (%)
4892 2
 
< 0.1%
4891 3
< 0.1%
4889 3
< 0.1%
4888 3
< 0.1%
4887 3
< 0.1%
4886 3
< 0.1%
4885 5
0.1%
4883 3
< 0.1%
4882 7
0.1%
4881 3
< 0.1%

대여소명
Text

Distinct2499
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T22:00:40.308018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length31
Mean length15.5858
Min length7

Characters and Unicode

Total characters155858
Distinct characters581
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

Unique229 ?
Unique (%)2.3%

Sample

1st row3810. 신봉천주유소 B
2nd row1235. 잠실트리지움310동 옆
3rd row2279. 교대역 5번출구뒤
4th row2711.가로공원공영주차장 1번 출구
5th row4046. 경춘선 숲길
ValueCountFrequency (%)
앞 2689
 
9.1%
출구 443
 
1.5%
옆 410
 
1.4%
1번출구 295
 
1.0%
교차로 257
 
0.9%
입구 230
 
0.8%
사거리 214
 
0.7%
3번출구 203
 
0.7%
2번출구 203
 
0.7%
뒤 193
 
0.7%
Other values (4982) 24257
82.5%
2024-03-13T22:00:40.816802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19588
 
12.6%
. 10037
 
6.4%
1 7934
 
5.1%
2 6201
 
4.0%
3 4900
 
3.1%
4 4804
 
3.1%
5 3543
 
2.3%
0 3524
 
2.3%
6 3395
 
2.2%
7 3279
 
2.1%
Other values (571) 88653
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80134
51.4%
Decimal Number 42726
27.4%
Space Separator 19588
 
12.6%
Other Punctuation 10138
 
6.5%
Uppercase Letter 1347
 
0.9%
Close Punctuation 806
 
0.5%
Open Punctuation 806
 
0.5%
Lowercase Letter 208
 
0.1%
Dash Punctuation 72
 
< 0.1%
Math Symbol 12
 
< 0.1%
Other values (3) 21
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3247
 
4.1%
앞 3149
 
3.9%
역 2499
 
3.1%
번 2215
 
2.8%
출 2181
 
2.7%
동 2158
 
2.7%
교 1666
 
2.1%
파 1480
 
1.8%
아 1435
 
1.8%
트 1344
 
1.7%
Other values (507) 58760
73.3%
Uppercase Letter
ValueCountFrequency (%)
S 195
14.5%
K 168
12.5%
T 120
8.9%
C 118
8.8%
G 91
 
6.8%
A 90
 
6.7%
D 89
 
6.6%
B 75
 
5.6%
P 67
 
5.0%
M 64
 
4.8%
Other values (13) 270
20.0%
Lowercase Letter
ValueCountFrequency (%)
e 69
33.2%
s 28
13.5%
k 23
 
11.1%
l 12
 
5.8%
t 11
 
5.3%
n 10
 
4.8%
h 7
 
3.4%
c 7
 
3.4%
o 7
 
3.4%
m 7
 
3.4%
Other values (6) 27
 
13.0%
Decimal Number
ValueCountFrequency (%)
1 7934
18.6%
2 6201
14.5%
3 4900
11.5%
4 4804
11.2%
5 3543
8.3%
0 3524
8.2%
6 3395
7.9%
7 3279
7.7%
8 2744
 
6.4%
9 2402
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 10037
99.0%
, 57
 
0.6%
& 26
 
0.3%
· 11
 
0.1%
? 7
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 7
58.3%
+ 5
41.7%
Other Number
ValueCountFrequency (%)
① 5
62.5%
② 3
37.5%
Space Separator
ValueCountFrequency (%)
19588
100.0%
Close Punctuation
ValueCountFrequency (%)
) 806
100.0%
Open Punctuation
ValueCountFrequency (%)
( 806
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 72
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 7
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80141
51.4%
Common 74162
47.6%
Latin 1555
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3247
 
4.1%
앞 3149
 
3.9%
역 2499
 
3.1%
번 2215
 
2.8%
출 2181
 
2.7%
동 2158
 
2.7%
교 1666
 
2.1%
파 1480
 
1.8%
아 1435
 
1.8%
트 1344
 
1.7%
Other values (508) 58767
73.3%
Latin
ValueCountFrequency (%)
S 195
12.5%
K 168
 
10.8%
T 120
 
7.7%
C 118
 
7.6%
G 91
 
5.9%
A 90
 
5.8%
D 89
 
5.7%
B 75
 
4.8%
e 69
 
4.4%
P 67
 
4.3%
Other values (29) 473
30.4%
Common
ValueCountFrequency (%)
19588
26.4%
. 10037
13.5%
1 7934
10.7%
2 6201
 
8.4%
3 4900
 
6.6%
4 4804
 
6.5%
5 3543
 
4.8%
0 3524
 
4.8%
6 3395
 
4.6%
7 3279
 
4.4%
Other values (14) 6957
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80134
51.4%
ASCII 75698
48.6%
None 18
 
< 0.1%
Enclosed Alphanum 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19588
25.9%
. 10037
13.3%
1 7934
10.5%
2 6201
 
8.2%
3 4900
 
6.5%
4 4804
 
6.3%
5 3543
 
4.7%
0 3524
 
4.7%
6 3395
 
4.5%
7 3279
 
4.3%
Other values (50) 8493
11.2%
Hangul
ValueCountFrequency (%)
구 3247
 
4.1%
앞 3149
 
3.9%
역 2499
 
3.1%
번 2215
 
2.8%
출 2181
 
2.7%
동 2158
 
2.7%
교 1666
 
2.1%
파 1480
 
1.8%
아 1435
 
1.8%
트 1344
 
1.7%
Other values (507) 58760
73.3%
None
ValueCountFrequency (%)
· 11
61.1%
㈜ 7
38.9%
Enclosed Alphanum
ValueCountFrequency (%)
① 5
62.5%
② 3
37.5%

대여구분코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정기
5785 
일일(회원)
3679 
단체
 
325
일일(비회원)
 
210
10분이용권
 
1

Length

Max length7
Median length2
Mean length3.577
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row정기
2nd row정기
3rd row정기
4th row일일(회원)
5th row일일(회원)

Common Values

ValueCountFrequency (%)
정기 5785
57.9%
일일(회원) 3679
36.8%
단체 325
 
3.2%
일일(비회원) 210
 
2.1%
10분이용권 1
 
< 0.1%

Length

2024-03-13T22:00:40.982175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:00:41.137301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 5785
57.9%
일일(회원 3679
36.8%
단체 325
 
3.2%
일일(비회원 210
 
2.1%
10분이용권 1
 
< 0.1%

성별
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
M
3213 
\N
2996 
F
2669 
<NA>
1118 
m
 
3

Length

Max length4
Median length1
Mean length1.635
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowM
2nd row<NA>
3rd rowM
4th row\N
5th row\N

Common Values

ValueCountFrequency (%)
M 3213
32.1%
\N 2996
30.0%
F 2669
26.7%
<NA> 1118
 
11.2%
m 3
 
< 0.1%
f 1
 
< 0.1%

Length

2024-03-13T22:00:41.303368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:00:41.442660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 3216
32.2%
n 2996
30.0%
f 2670
26.7%
na 1118
 
11.2%

연령대코드
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20대
1990 
30대
1772 
40대
1493 
기타
1469 
50대
1266 
Other values (3)
2010 

Length

Max length5
Median length3
Mean length2.9011
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row50대
3rd row30대
4th row30대
5th row10대

Common Values

ValueCountFrequency (%)
20대 1990
19.9%
30대 1772
17.7%
40대 1493
14.9%
기타 1469
14.7%
50대 1266
12.7%
10대 1074
10.7%
60대 696
 
7.0%
70대이상 240
 
2.4%

Length

2024-03-13T22:00:41.600779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:00:41.752376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 1990
19.9%
30대 1772
17.7%
40대 1493
14.9%
기타 1469
14.7%
50대 1266
12.7%
10대 1074
10.7%
60대 696
 
7.0%
70대이상 240
 
2.4%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct190
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.1739
Minimum1
Maximum576
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T22:00:41.912250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q315
95-th percentile59
Maximum576
Range575
Interquartile range (IQR)13

Descriptive statistics

Standard deviation25.610503
Coefficient of variation (CV)1.8068776
Kurtosis47.430517
Mean14.1739
Median Absolute Deviation (MAD)4
Skewness5.0376451
Sum141739
Variance655.89785
MonotonicityNot monotonic
2024-03-13T22:00:42.106282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2099
21.0%
2 1334
13.3%
3 853
 
8.5%
4 605
 
6.0%
5 487
 
4.9%
6 379
 
3.8%
7 306
 
3.1%
8 290
 
2.9%
9 244
 
2.4%
10 199
 
2.0%
Other values (180) 3204
32.0%
ValueCountFrequency (%)
1 2099
21.0%
2 1334
13.3%
3 853
8.5%
4 605
 
6.0%
5 487
 
4.9%
6 379
 
3.8%
7 306
 
3.1%
8 290
 
2.9%
9 244
 
2.4%
10 199
 
2.0%
ValueCountFrequency (%)
576 1
< 0.1%
331 1
< 0.1%
316 1
< 0.1%
298 1
< 0.1%
281 1
< 0.1%
271 1
< 0.1%
266 1
< 0.1%
264 1
< 0.1%
261 1
< 0.1%
260 1
< 0.1%

운동량
Text

Distinct8756
Distinct (%)87.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T22:00:42.662075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.8173
Min length2

Characters and Unicode

Total characters58173
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

Unique8151 ?
Unique (%)81.5%

Sample

1st row32.24
2nd row30.66
3rd row4357.85
4th row181.42
5th row328.02
ValueCountFrequency (%)
0.00 518
 
5.2%
n 20
 
0.2%
27.80 5
 
< 0.1%
24.71 5
 
< 0.1%
15.19 4
 
< 0.1%
25.23 4
 
< 0.1%
36.04 4
 
< 0.1%
35.26 4
 
< 0.1%
23.42 4
 
< 0.1%
92.25 4
 
< 0.1%
Other values (8746) 9428
94.3%
2024-03-13T22:00:43.267377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9980
17.2%
1 6501
11.2%
0 5542
9.5%
2 5514
9.5%
3 4919
8.5%
4 4809
8.3%
5 4416
7.6%
6 4316
7.4%
8 4142
7.1%
7 4033
6.9%
Other values (3) 4001
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48153
82.8%
Other Punctuation 10000
 
17.2%
Uppercase Letter 20
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6501
13.5%
0 5542
11.5%
2 5514
11.5%
3 4919
10.2%
4 4809
10.0%
5 4416
9.2%
6 4316
9.0%
8 4142
8.6%
7 4033
8.4%
9 3961
8.2%
Other Punctuation
ValueCountFrequency (%)
. 9980
99.8%
\ 20
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58153
> 99.9%
Latin 20
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9980
17.2%
1 6501
11.2%
0 5542
9.5%
2 5514
9.5%
3 4919
8.5%
4 4809
8.3%
5 4416
7.6%
6 4316
7.4%
8 4142
7.1%
7 4033
6.9%
Other values (2) 3981
 
6.8%
Latin
ValueCountFrequency (%)
N 20
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58173
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9980
17.2%
1 6501
11.2%
0 5542
9.5%
2 5514
9.5%
3 4919
8.5%
4 4809
8.3%
5 4416
7.6%
6 4316
7.4%
8 4142
7.1%
7 4033
6.9%
Other values (3) 4001
6.9%

탄소량
Text

Distinct2158
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T22:00:43.758343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.161
Min length2

Characters and Unicode

Total characters41610
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

Unique974 ?
Unique (%)9.7%

Sample

1st row0.24
2nd row0.22
3rd row31.39
4th row1.63
5th row2.51
ValueCountFrequency (%)
0.00 522
 
5.2%
0.16 46
 
0.5%
0.34 46
 
0.5%
0.29 43
 
0.4%
0.21 42
 
0.4%
0.30 42
 
0.4%
0.45 42
 
0.4%
0.24 41
 
0.4%
0.26 40
 
0.4%
0.38 40
 
0.4%
Other values (2148) 9096
91.0%
2024-03-13T22:00:44.476401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9980
24.0%
0 6406
15.4%
1 4682
11.3%
2 3509
 
8.4%
3 3101
 
7.5%
4 2637
 
6.3%
5 2482
 
6.0%
6 2336
 
5.6%
7 2201
 
5.3%
8 2171
 
5.2%
Other values (3) 2105
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31590
75.9%
Other Punctuation 10000
 
24.0%
Uppercase Letter 20
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6406
20.3%
1 4682
14.8%
2 3509
11.1%
3 3101
9.8%
4 2637
8.3%
5 2482
 
7.9%
6 2336
 
7.4%
7 2201
 
7.0%
8 2171
 
6.9%
9 2065
 
6.5%
Other Punctuation
ValueCountFrequency (%)
. 9980
99.8%
\ 20
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41590
> 99.9%
Latin 20
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9980
24.0%
0 6406
15.4%
1 4682
11.3%
2 3509
 
8.4%
3 3101
 
7.5%
4 2637
 
6.3%
5 2482
 
6.0%
6 2336
 
5.6%
7 2201
 
5.3%
8 2171
 
5.2%
Other values (2) 2085
 
5.0%
Latin
ValueCountFrequency (%)
N 20
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41610
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9980
24.0%
0 6406
15.4%
1 4682
11.3%
2 3509
 
8.4%
3 3101
 
7.5%
4 2637
 
6.3%
5 2482
 
6.0%
6 2336
 
5.6%
7 2201
 
5.3%
8 2171
 
5.2%
Other values (3) 2105
 
5.1%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8363
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24647.457
Minimum0
Maximum797884.14
Zeros538
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T22:00:44.817510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12905.2625
median9355.565
Q327285.798
95-th percentile100734.95
Maximum797884.14
Range797884.14
Interquartile range (IQR)24380.535

Descriptive statistics

Standard deviation42809.349
Coefficient of variation (CV)1.7368668
Kurtosis39.670397
Mean24647.457
Median Absolute Deviation (MAD)7828.09
Skewness4.7467469
Sum2.4647457 × 108
Variance1.8326404 × 109
MonotonicityNot monotonic
2024-03-13T22:00:45.072778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 538
 
5.4%
1990.0 9
 
0.1%
1560.0 9
 
0.1%
2150.0 9
 
0.1%
1600.0 8
 
0.1%
1380.0 8
 
0.1%
1620.0 8
 
0.1%
880.0 8
 
0.1%
1050.0 7
 
0.1%
980.0 7
 
0.1%
Other values (8353) 9389
93.9%
ValueCountFrequency (%)
0.0 538
5.4%
10.0 4
 
< 0.1%
30.0 1
 
< 0.1%
70.0 1
 
< 0.1%
80.0 1
 
< 0.1%
88.1 1
 
< 0.1%
88.17 1
 
< 0.1%
88.23 1
 
< 0.1%
90.0 2
 
< 0.1%
110.0 1
 
< 0.1%
ValueCountFrequency (%)
797884.14 1
< 0.1%
706339.16 1
< 0.1%
575068.17 1
< 0.1%
527515.91 1
< 0.1%
501888.23 1
< 0.1%
488220.54 1
< 0.1%
455706.12 1
< 0.1%
445389.76 1
< 0.1%
436521.87 1
< 0.1%
424749.2 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct1392
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean278.3273
Minimum1
Maximum7757
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T22:00:45.339908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q138
median110
Q3309
95-th percentile1136.05
Maximum7757
Range7756
Interquartile range (IQR)271

Descriptive statistics

Standard deviation459.19871
Coefficient of variation (CV)1.6498515
Kurtosis26.541093
Mean278.3273
Median Absolute Deviation (MAD)89
Skewness4.0632428
Sum2783273
Variance210863.46
MonotonicityNot monotonic
2024-03-13T22:00:45.599357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11 102
 
1.0%
14 96
 
1.0%
5 94
 
0.9%
10 93
 
0.9%
12 91
 
0.9%
6 84
 
0.8%
8 84
 
0.8%
7 83
 
0.8%
15 83
 
0.8%
18 82
 
0.8%
Other values (1382) 9108
91.1%
ValueCountFrequency (%)
1 14
 
0.1%
2 36
 
0.4%
3 51
0.5%
4 75
0.8%
5 94
0.9%
6 84
0.8%
7 83
0.8%
8 84
0.8%
9 80
0.8%
10 93
0.9%
ValueCountFrequency (%)
7757 1
< 0.1%
5507 1
< 0.1%
5320 1
< 0.1%
4983 1
< 0.1%
4802 1
< 0.1%
4785 1
< 0.1%
4758 1
< 0.1%
4368 1
< 0.1%
4109 1
< 0.1%
4098 1
< 0.1%

Interactions

2024-03-13T22:00:38.060800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:00:36.011711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:00:36.716800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:00:37.325240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:00:38.209684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:00:36.159981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:00:36.911291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:00:37.471923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:00:38.330745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:00:36.318047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:00:37.036119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:00:37.607097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:00:38.503224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:00:36.541008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:00:37.174166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:00:37.882260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:00:45.778548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호대여구분코드성별연령대코드이용건수이동거리(M)이용시간(분)
대여소번호1.0000.0400.0000.0070.0460.0570.039
대여구분코드0.0401.0000.2670.3220.1430.2280.191
성별0.0000.2671.0000.0510.0440.0770.053
연령대코드0.0070.3220.0511.0000.1460.1310.138
이용건수0.0460.1430.0440.1461.0000.7090.790
이동거리(M)0.0570.2280.0770.1310.7091.0000.866
이용시간(분)0.0390.1910.0530.1380.7900.8661.000
2024-03-13T22:00:45.907441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여구분코드성별연령대코드
대여구분코드1.0000.1020.204
성별0.1021.0000.031
연령대코드0.2040.0311.000
2024-03-13T22:00:46.018077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)대여구분코드성별연령대코드
대여소번호1.000-0.049-0.050-0.0590.0170.0000.004
이용건수-0.0491.0000.8720.8850.0910.0280.079
이동거리(M)-0.0500.8721.0000.9250.0970.0320.063
이용시간(분)-0.0590.8850.9251.0000.1110.0300.068
대여구분코드0.0170.0910.0970.1111.0000.1020.204
성별0.0000.0280.0320.0300.1021.0000.031
연령대코드0.0040.0790.0630.0680.2040.0311.000

Missing values

2024-03-13T22:00:38.706985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:00:38.888897image/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

대여일자대여소번호대여소명대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
811442022-0138103810. 신봉천주유소 B정기M기타232.240.241017.6241
356842022-0112351235. 잠실트리지움310동 옆정기<NA>50대130.660.22967.936
603882022-0122792279. 교대역 5번출구뒤정기M30대944357.8531.39135305.371617
686602022-0127112711.가로공원공영주차장 1번 출구일일(회원)\N30대4181.421.637060.0164
842532022-0140464046. 경춘선 숲길일일(회원)\N10대6328.022.5110797.8773
523242022-0119361936. 개봉역 1번 출구 자전거보관서쪽일일(비회원)\N기타8938.058.4536443.68710
697662022-0127412741.마곡수명산파크5-6단지일일(회원)\N10대149.560.451925.3216
752302022-0135183518. 군자역 7번출구뒤정기M20대2106683.1755.94241171.552556
199562022-01716716.신정6동 주민센터 인근일일(회원)M30대445.670.431860.062
881012022-0144624462. 가락중학교 앞정기<NA>20대9261.272.239606.62133
대여일자대여소번호대여소명대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
55752022-01252252. 보라매역4번출구정기F70대이상250.530.743190.060
548152022-0120412041. 사당중학교 버스정류소정기F40대141.960.381630.011
866992022-0142624262. 서대문자연사박물관 입구정기\N40대148.410.411746.5712
797572022-0137633763. 등촌태영아파트일일(회원)F40대237.740.331412.0713
755492022-0135333533. 건대입구역 사거리(롯데백화점)단체F40대7684.196.1726580.93310
875192022-0143734373. 서울숲 지식산업센터일일(회원)<NA>20대183.200.893820.018
478752022-0117091709. 쌍문역4번출구 주변일일(회원)F10대38.550.08360.0132
526762022-0119551955. 디지털입구 교차로정기M10대4152.651.164993.0652
915972022-0146104610. 한남나인원 105동 앞정기M20대479.040.622640.049
119012022-01446446. 상명대입구정기M20대201194.849.7141908.65301