Overview

Dataset statistics

Number of variables12
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 MiB
Average record size in memory109.0 B

Variable types

DateTime1
Numeric5
Text3
Categorical3

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15245/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
대여시간 has 580 (5.8%) zerosZeros
이동거리(M) has 127 (1.3%) zerosZeros

Reproduction

Analysis started2023-12-11 08:11:07.065689
Analysis finished2023-12-11 08:11:12.532315
Duration5.47 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
Minimum2022-06-01 00:00:00
Maximum2022-06-01 00:00:00
2023-12-11T17:11:12.584800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:12.698933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

대여시간
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.7027
Minimum0
Maximum17
Zeros580
Zeros (%)5.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:11:12.809834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median12
Q315
95-th percentile17
Maximum17
Range17
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.135538
Coefficient of variation (CV)0.47983574
Kurtosis-0.52619338
Mean10.7027
Median Absolute Deviation (MAD)3
Skewness-0.77806999
Sum107027
Variance26.37375
MonotonicityNot monotonic
2023-12-11T17:11:12.963476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
16 1131
11.3%
15 961
9.6%
14 908
9.1%
13 853
 
8.5%
12 798
 
8.0%
17 756
 
7.6%
11 715
 
7.1%
10 613
 
6.1%
0 580
 
5.8%
9 531
 
5.3%
Other values (8) 2154
21.5%
ValueCountFrequency (%)
0 580
5.8%
1 461
4.6%
2 271
2.7%
3 195
 
1.9%
4 192
 
1.9%
5 158
 
1.6%
6 183
 
1.8%
7 283
2.8%
8 411
4.1%
9 531
5.3%
ValueCountFrequency (%)
17 756
7.6%
16 1131
11.3%
15 961
9.6%
14 908
9.1%
13 853
8.5%
12 798
8.0%
11 715
7.1%
10 613
6.1%
9 531
5.3%
8 411
 
4.1%

대여소번호
Real number (ℝ)

Distinct2278
Distinct (%)22.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1985.8702
Minimum102
Maximum9999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:11:13.445789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile219
Q1779.75
median1617
Q33102
95-th percentile4618
Maximum9999
Range9897
Interquartile range (IQR)2322.25

Descriptive statistics

Standard deviation1438.4195
Coefficient of variation (CV)0.72432705
Kurtosis-0.68003868
Mean1985.8702
Median Absolute Deviation (MAD)1004
Skewness0.62973046
Sum19858702
Variance2069050.7
MonotonicityNot monotonic
2023-12-11T17:11:13.641114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4217 30
 
0.3%
502 30
 
0.3%
1911 25
 
0.2%
210 24
 
0.2%
2102 23
 
0.2%
2177 22
 
0.2%
2262 21
 
0.2%
769 20
 
0.2%
207 20
 
0.2%
2620 19
 
0.2%
Other values (2268) 9766
97.7%
ValueCountFrequency (%)
102 10
0.1%
103 9
0.1%
104 5
0.1%
105 3
 
< 0.1%
106 9
0.1%
107 4
 
< 0.1%
108 2
 
< 0.1%
109 4
 
< 0.1%
111 4
 
< 0.1%
112 8
0.1%
ValueCountFrequency (%)
9999 2
 
< 0.1%
5853 1
 
< 0.1%
5852 1
 
< 0.1%
5851 5
0.1%
5753 4
< 0.1%
5752 6
0.1%
5751 2
 
< 0.1%
5306 3
< 0.1%
5301 3
< 0.1%
5078 4
< 0.1%

대여소명
Text

Distinct2278
Distinct (%)22.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T17:11:13.957187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length32
Mean length15.5589
Min length4

Characters and Unicode

Total characters155589
Distinct characters575
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

Unique440 ?
Unique (%)4.4%

Sample

1st row3766. 강서문화센터
2nd row1197. 엠펠리체 호텔 건너편
3rd row3615. 서울 논현동우체국 앞
4th row746. 목동2단지 상가
5th row4868. 석촌호수 서호 남단
ValueCountFrequency (%)
앞 2540
 
8.6%
출구 481
 
1.6%
1번출구 385
 
1.3%
옆 374
 
1.3%
교차로 242
 
0.8%
3번출구 218
 
0.7%
뒤 210
 
0.7%
사거리 208
 
0.7%
2번출구 194
 
0.7%
입구 193
 
0.7%
Other values (4582) 24330
82.8%
2023-12-11T17:11:14.432880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19556
 
12.6%
. 10018
 
6.4%
1 8240
 
5.3%
2 6222
 
4.0%
4 4566
 
2.9%
3 4452
 
2.9%
0 3665
 
2.4%
5 3625
 
2.3%
구 3544
 
2.3%
6 3437
 
2.2%
Other values (565) 88264
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80196
51.5%
Decimal Number 42667
27.4%
Space Separator 19556
 
12.6%
Other Punctuation 10141
 
6.5%
Uppercase Letter 1123
 
0.7%
Close Punctuation 839
 
0.5%
Open Punctuation 839
 
0.5%
Lowercase Letter 107
 
0.1%
Dash Punctuation 89
 
0.1%
Connector Punctuation 15
 
< 0.1%
Other values (3) 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3544
 
4.4%
앞 2942
 
3.7%
역 2850
 
3.6%
번 2532
 
3.2%
출 2469
 
3.1%
동 2065
 
2.6%
교 1663
 
2.1%
파 1383
 
1.7%
아 1359
 
1.7%
리 1337
 
1.7%
Other values (501) 58052
72.4%
Uppercase Letter
ValueCountFrequency (%)
S 146
13.0%
C 121
10.8%
K 113
10.1%
T 99
8.8%
D 84
 
7.5%
B 75
 
6.7%
I 74
 
6.6%
G 62
 
5.5%
A 60
 
5.3%
P 51
 
4.5%
Other values (13) 238
21.2%
Lowercase Letter
ValueCountFrequency (%)
e 59
55.1%
s 9
 
8.4%
k 9
 
8.4%
t 6
 
5.6%
l 3
 
2.8%
h 2
 
1.9%
r 2
 
1.9%
n 2
 
1.9%
f 2
 
1.9%
c 2
 
1.9%
Other values (6) 11
 
10.3%
Decimal Number
ValueCountFrequency (%)
1 8240
19.3%
2 6222
14.6%
4 4566
10.7%
3 4452
10.4%
0 3665
8.6%
5 3625
8.5%
6 3437
8.1%
7 3306
7.7%
8 2746
 
6.4%
9 2408
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 10018
98.8%
, 84
 
0.8%
& 15
 
0.1%
? 14
 
0.1%
· 10
 
0.1%
Other Number
ValueCountFrequency (%)
① 7
63.6%
② 4
36.4%
Math Symbol
ValueCountFrequency (%)
~ 3
75.0%
+ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
19556
100.0%
Close Punctuation
ValueCountFrequency (%)
) 839
100.0%
Open Punctuation
ValueCountFrequency (%)
( 839
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 15
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80198
51.5%
Common 74161
47.7%
Latin 1230
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3544
 
4.4%
앞 2942
 
3.7%
역 2850
 
3.6%
번 2532
 
3.2%
출 2469
 
3.1%
동 2065
 
2.6%
교 1663
 
2.1%
파 1383
 
1.7%
아 1359
 
1.7%
리 1337
 
1.7%
Other values (502) 58054
72.4%
Latin
ValueCountFrequency (%)
S 146
11.9%
C 121
 
9.8%
K 113
 
9.2%
T 99
 
8.0%
D 84
 
6.8%
B 75
 
6.1%
I 74
 
6.0%
G 62
 
5.0%
A 60
 
4.9%
e 59
 
4.8%
Other values (29) 337
27.4%
Common
ValueCountFrequency (%)
19556
26.4%
. 10018
13.5%
1 8240
11.1%
2 6222
 
8.4%
4 4566
 
6.2%
3 4452
 
6.0%
0 3665
 
4.9%
5 3625
 
4.9%
6 3437
 
4.6%
7 3306
 
4.5%
Other values (14) 7074
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80196
51.5%
ASCII 75370
48.4%
None 12
 
< 0.1%
Enclosed Alphanum 11
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19556
25.9%
. 10018
13.3%
1 8240
10.9%
2 6222
 
8.3%
4 4566
 
6.1%
3 4452
 
5.9%
0 3665
 
4.9%
5 3625
 
4.8%
6 3437
 
4.6%
7 3306
 
4.4%
Other values (50) 8283
11.0%
Hangul
ValueCountFrequency (%)
구 3544
 
4.4%
앞 2942
 
3.7%
역 2850
 
3.6%
번 2532
 
3.2%
출 2469
 
3.1%
동 2065
 
2.6%
교 1663
 
2.1%
파 1383
 
1.7%
아 1359
 
1.7%
리 1337
 
1.7%
Other values (501) 58052
72.4%
None
ValueCountFrequency (%)
· 10
83.3%
㈜ 2
 
16.7%
Enclosed Alphanum
ValueCountFrequency (%)
① 7
63.6%
② 4
36.4%

대여구분코드
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정기권
7073 
일일권
2695 
일일권(비회원)
 
129
단체권
 
103

Length

Max length8
Median length3
Mean length3.0645
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정기권
2nd row일일권
3rd row일일권
4th row정기권
5th row정기권

Common Values

ValueCountFrequency (%)
정기권 7073
70.7%
일일권 2695
 
27.0%
일일권(비회원) 129
 
1.3%
단체권 103
 
1.0%

Length

2023-12-11T17:11:14.586916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:11:14.689926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 7073
70.7%
일일권 2695
 
27.0%
일일권(비회원 129
 
1.3%
단체권 103
 
1.0%

성별
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
M
3858 
<NA>
3530 
F
2609 
m
 
3

Length

Max length4
Median length1
Mean length2.059
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
M 3858
38.6%
<NA> 3530
35.3%
F 2609
26.1%
m 3
 
< 0.1%

Length

2023-12-11T17:11:14.807228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:11:14.941259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 3861
38.6%
na 3530
35.3%
f 2609
26.1%

연령대코드
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20대
3467 
30대
2342 
40대
1331 
기타
1018 
50대
846 
Other values (3)
996 

Length

Max length5
Median length3
Mean length2.9703
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30대
2nd row기타
3rd row~10대
4th row20대
5th row40대

Common Values

ValueCountFrequency (%)
20대 3467
34.7%
30대 2342
23.4%
40대 1331
 
13.3%
기타 1018
 
10.2%
50대 846
 
8.5%
~10대 649
 
6.5%
60대 311
 
3.1%
70대이상 36
 
0.4%

Length

2023-12-11T17:11:15.075930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:11:15.210418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 3467
34.7%
30대 2342
23.4%
40대 1331
 
13.3%
기타 1018
 
10.2%
50대 846
 
8.5%
10대 649
 
6.5%
60대 311
 
3.1%
70대이상 36
 
0.4%

이용건수
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1322
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:11:15.352419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum8
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.43674047
Coefficient of variation (CV)0.38574498
Kurtosis34.48584
Mean1.1322
Median Absolute Deviation (MAD)0
Skewness4.7364242
Sum11322
Variance0.19074223
MonotonicityNot monotonic
2023-12-11T17:11:15.487375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 8940
89.4%
2 873
 
8.7%
3 138
 
1.4%
4 33
 
0.3%
5 11
 
0.1%
8 2
 
< 0.1%
6 2
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
1 8940
89.4%
2 873
 
8.7%
3 138
 
1.4%
4 33
 
0.3%
5 11
 
0.1%
6 2
 
< 0.1%
7 1
 
< 0.1%
8 2
 
< 0.1%
ValueCountFrequency (%)
8 2
 
< 0.1%
7 1
 
< 0.1%
6 2
 
< 0.1%
5 11
 
0.1%
4 33
 
0.3%
3 138
 
1.4%
2 873
 
8.7%
1 8940
89.4%

운동량
Text

Distinct6867
Distinct (%)68.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T17:11:15.965717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.2052
Min length2

Characters and Unicode

Total characters52052
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

Unique5083 ?
Unique (%)50.8%

Sample

1st row32.43
2nd row28.83
3rd row316.34
4th row58.17
5th row178.37
ValueCountFrequency (%)
0.00 104
 
1.0%
n 30
 
0.3%
29.34 12
 
0.1%
20.85 12
 
0.1%
26.00 11
 
0.1%
32.43 11
 
0.1%
27.03 10
 
0.1%
23.17 10
 
0.1%
24.20 10
 
0.1%
33.98 10
 
0.1%
Other values (6857) 9780
97.8%
2023-12-11T17:11:16.684192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9970
19.2%
1 5975
11.5%
2 5132
9.9%
3 4755
9.1%
4 4196
8.1%
5 3989
7.7%
6 3716
 
7.1%
0 3673
 
7.1%
7 3606
 
6.9%
8 3566
 
6.9%
Other values (3) 3474
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42022
80.7%
Other Punctuation 10000
 
19.2%
Uppercase Letter 30
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5975
14.2%
2 5132
12.2%
3 4755
11.3%
4 4196
10.0%
5 3989
9.5%
6 3716
8.8%
0 3673
8.7%
7 3606
8.6%
8 3566
8.5%
9 3414
8.1%
Other Punctuation
ValueCountFrequency (%)
. 9970
99.7%
\ 30
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52022
99.9%
Latin 30
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9970
19.2%
1 5975
11.5%
2 5132
9.9%
3 4755
9.1%
4 4196
8.1%
5 3989
7.7%
6 3716
 
7.1%
0 3673
 
7.1%
7 3606
 
6.9%
8 3566
 
6.9%
Other values (2) 3444
 
6.6%
Latin
ValueCountFrequency (%)
N 30
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52052
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9970
19.2%
1 5975
11.5%
2 5132
9.9%
3 4755
9.1%
4 4196
8.1%
5 3989
7.7%
6 3716
 
7.1%
0 3673
 
7.1%
7 3606
 
6.9%
8 3566
 
6.9%
Other values (3) 3474
 
6.7%

탄소량
Text

Distinct515
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T17:11:17.260298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.9945
Min length2

Characters and Unicode

Total characters39945
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 row0.21
2nd row0.26
3rd row2.85
4th row0.52
5th row1.77
ValueCountFrequency (%)
0.18 173
 
1.7%
0.26 172
 
1.7%
0.29 168
 
1.7%
0.21 155
 
1.6%
0.23 155
 
1.6%
0.20 153
 
1.5%
0.19 152
 
1.5%
0.28 145
 
1.5%
0.17 144
 
1.4%
0.24 142
 
1.4%
Other values (505) 8441
84.4%
2023-12-11T17:11:17.926936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9970
25.0%
0 9599
24.0%
1 4154
10.4%
2 3159
 
7.9%
3 2696
 
6.7%
4 2191
 
5.5%
5 1892
 
4.7%
6 1744
 
4.4%
8 1562
 
3.9%
7 1502
 
3.8%
Other values (3) 1476
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29915
74.9%
Other Punctuation 10000
 
25.0%
Uppercase Letter 30
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9599
32.1%
1 4154
13.9%
2 3159
 
10.6%
3 2696
 
9.0%
4 2191
 
7.3%
5 1892
 
6.3%
6 1744
 
5.8%
8 1562
 
5.2%
7 1502
 
5.0%
9 1416
 
4.7%
Other Punctuation
ValueCountFrequency (%)
. 9970
99.7%
\ 30
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39915
99.9%
Latin 30
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9970
25.0%
0 9599
24.0%
1 4154
10.4%
2 3159
 
7.9%
3 2696
 
6.8%
4 2191
 
5.5%
5 1892
 
4.7%
6 1744
 
4.4%
8 1562
 
3.9%
7 1502
 
3.8%
Other values (2) 1446
 
3.6%
Latin
ValueCountFrequency (%)
N 30
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39945
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9970
25.0%
0 9599
24.0%
1 4154
10.4%
2 3159
 
7.9%
3 2696
 
6.7%
4 2191
 
5.5%
5 1892
 
4.7%
6 1744
 
4.4%
8 1562
 
3.9%
7 1502
 
3.8%
Other values (3) 1476
 
3.7%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6295
Distinct (%)62.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3388.2402
Minimum0
Maximum88177.9
Zeros127
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:11:18.117309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile400.475
Q11040
median1960
Q33975.7875
95-th percentile11610.45
Maximum88177.9
Range88177.9
Interquartile range (IQR)2935.7875

Descriptive statistics

Standard deviation4236.9092
Coefficient of variation (CV)1.2504749
Kurtosis37.779392
Mean3388.2402
Median Absolute Deviation (MAD)1143.285
Skewness4.1932847
Sum33882402
Variance17951400
MonotonicityNot monotonic
2023-12-11T17:11:18.288862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 127
 
1.3%
1010.0 29
 
0.3%
1250.0 29
 
0.3%
730.0 25
 
0.2%
770.0 25
 
0.2%
1140.0 24
 
0.2%
950.0 23
 
0.2%
940.0 22
 
0.2%
1240.0 21
 
0.2%
900.0 21
 
0.2%
Other values (6285) 9654
96.5%
ValueCountFrequency (%)
0.0 127
1.3%
0.1 2
 
< 0.1%
0.2 1
 
< 0.1%
2.87 1
 
< 0.1%
8.94 1
 
< 0.1%
9.41 1
 
< 0.1%
10.0 8
 
0.1%
14.46 1
 
< 0.1%
15.34 1
 
< 0.1%
19.07 1
 
< 0.1%
ValueCountFrequency (%)
88177.9 1
< 0.1%
74650.0 1
< 0.1%
55457.61 1
< 0.1%
48801.71 1
< 0.1%
47494.94 1
< 0.1%
40840.16 1
< 0.1%
38623.91 1
< 0.1%
36630.0 1
< 0.1%
35826.03 1
< 0.1%
35640.0 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct234
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.927
Minimum0
Maximum1038
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:11:18.455997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q18
median17
Q339
95-th percentile101
Maximum1038
Range1038
Interquartile range (IQR)31

Descriptive statistics

Standard deviation38.127961
Coefficient of variation (CV)1.2740322
Kurtosis69.996299
Mean29.927
Median Absolute Deviation (MAD)11
Skewness5.1726063
Sum299270
Variance1453.7414
MonotonicityNot monotonic
2023-12-11T17:11:18.601516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 435
 
4.3%
6 421
 
4.2%
7 414
 
4.1%
4 389
 
3.9%
8 388
 
3.9%
9 375
 
3.8%
3 345
 
3.5%
11 324
 
3.2%
10 317
 
3.2%
12 314
 
3.1%
Other values (224) 6278
62.8%
ValueCountFrequency (%)
0 3
 
< 0.1%
1 73
 
0.7%
2 221
2.2%
3 345
3.5%
4 389
3.9%
5 435
4.3%
6 421
4.2%
7 414
4.1%
8 388
3.9%
9 375
3.8%
ValueCountFrequency (%)
1038 1
< 0.1%
535 1
< 0.1%
527 1
< 0.1%
486 1
< 0.1%
421 1
< 0.1%
415 1
< 0.1%
406 1
< 0.1%
379 1
< 0.1%
366 1
< 0.1%
362 1
< 0.1%

Interactions

2023-12-11T17:11:11.599376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:08.938751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:09.680943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:10.347921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:11.030418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:11.704943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:09.107198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:09.822356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:10.488672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:11.160930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:11.797761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:09.252373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:09.974431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:10.611875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:11.275177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:11.914541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:09.420205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:10.104689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:10.746526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:11.410340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:12.035029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:09.556040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:10.214725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:10.869700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:11.509297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T17:11:18.723443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여시간대여소번호대여구분코드성별연령대코드이용건수이동거리(M)이용시간(분)
대여시간1.0000.0210.1560.1650.1200.0750.0250.060
대여소번호0.0211.0000.0330.0000.0290.0080.1060.043
대여구분코드0.1560.0331.0000.0230.4640.3080.2230.188
성별0.1650.0000.0231.0000.0970.0000.0000.030
연령대코드0.1200.0290.4640.0971.0000.1490.0200.041
이용건수0.0750.0080.3080.0000.1491.0000.4860.347
이동거리(M)0.0250.1060.2230.0000.0200.4861.0000.633
이용시간(분)0.0600.0430.1880.0300.0410.3470.6331.000
2023-12-11T17:11:18.856070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여구분코드성별연령대코드
대여구분코드1.0000.0220.221
성별0.0221.0000.061
연령대코드0.2210.0611.000
2023-12-11T17:11:18.981449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여시간대여소번호이용건수이동거리(M)이용시간(분)대여구분코드성별연령대코드
대여시간1.000-0.0130.0920.0160.1000.0940.0990.057
대여소번호-0.0131.000-0.032-0.017-0.0190.0230.0000.015
이용건수0.092-0.0321.0000.2980.2860.1420.0000.050
이동거리(M)0.016-0.0170.2981.0000.8190.1440.0000.010
이용시간(분)0.100-0.0190.2860.8191.0000.1300.0200.022
대여구분코드0.0940.0230.1420.1440.1301.0000.0220.221
성별0.0990.0000.0000.0000.0200.0221.0000.061
연령대코드0.0570.0150.0500.0100.0220.2210.0611.000

Missing values

2023-12-11T17:11:12.206115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T17:11:12.420009image/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

대여일자대여시간대여소번호대여소명대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
434942022-06-011137663766. 강서문화센터정기권M30대132.430.21910.013
938542022-06-011711971197. 엠펠리체 호텔 건너편일일권F기타128.830.261120.07
114212022-06-01236153615. 서울 논현동우체국 앞일일권M~10대1316.342.8512290.01038
439802022-06-0112746746. 목동2단지 상가정기권<NA>20대158.170.522260.08
165152022-06-01548684868. 석촌호수 서호 남단정기권<NA>40대1178.371.777634.2150
18392022-06-010162162. 봉원고가차도 밑정기권M30대113.320.12517.5310
625622022-06-011419851985. 구로도서관정기권M30대116.350.14589.692
74152022-06-01139053905. 희훈타워빌 앞일일권<NA>20대1100.890.913919.618
253362022-06-01824052405. 청담공원앞 교차로정기권<NA>20대15.700.07320.03
38562022-06-01038153815. 광일빌딩일일권M30대1151.871.315640.031
대여일자대여시간대여소번호대여소명대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
79292022-06-011522522. 금호역 1번출구 앞일일권F30대122.670.20880.749
893982022-06-011736553655. 둔촌신성미소지움아파트정기권F20대10.000.000.02
673742022-06-011426372637. 아시아지하보도 14번 출구정기권M20대173.030.692974.6423
818622022-06-011637813781. 강서아동복지센터일일권<NA>20대117.670.23970.013
299412022-06-01912601260. 방이동 한양3차아파트 옆일일권F50대1137.731.345796.89111
903212022-06-011713671367. 길음문화복합미디어센터정기권F기타125.110.19823.436
353242022-06-0110749749. 이대목동병원보도육교단체권<NA>40대2592.754.5619695.24112
241932022-06-01839693969. 독산역 롯데캐슬 104동 앞정기권M30대1145.410.954080.010
306532022-06-01919071907. 구일우성(아) 육교 밑정기권F30대121.290.261120.05
683842022-06-011510771077.강동역 1번출구 앞정기권<NA>20대242.060.411770.029