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

Categorical4
Numeric5
Text3

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 384 (3.8%) zerosZeros
이동거리(M) has 139 (1.4%) zerosZeros

Reproduction

Analysis started2023-12-11 08:11:20.976392
Analysis finished2023-12-11 08:11:26.916079
Duration5.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022-05-01
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-05-01
2nd row2022-05-01
3rd row2022-05-01
4th row2022-05-01
5th row2022-05-01

Common Values

ValueCountFrequency (%)
2022-05-01 10000
100.0%

Length

2023-12-11T17:11:27.028584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:11:27.167130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-05-01 10000
100.0%

대여시간
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.7399
Minimum0
Maximum20
Zeros384
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:11:27.285062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q110
median14
Q316
95-th percentile19
Maximum20
Range20
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.0743298
Coefficient of variation (CV)0.39830217
Kurtosis0.40485819
Mean12.7399
Median Absolute Deviation (MAD)3
Skewness-1.0072079
Sum127399
Variance25.748823
MonotonicityNot monotonic
2023-12-11T17:11:27.465959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
15 978
9.8%
16 935
9.3%
14 890
 
8.9%
17 888
 
8.9%
13 806
 
8.1%
18 768
 
7.7%
12 746
 
7.5%
11 640
 
6.4%
19 614
 
6.1%
10 502
 
5.0%
Other values (11) 2233
22.3%
ValueCountFrequency (%)
0 384
3.8%
1 275
2.8%
2 175
1.8%
3 124
 
1.2%
4 70
 
0.7%
5 66
 
0.7%
6 90
 
0.9%
7 152
 
1.5%
8 295
2.9%
9 398
4.0%
ValueCountFrequency (%)
20 204
 
2.0%
19 614
6.1%
18 768
7.7%
17 888
8.9%
16 935
9.3%
15 978
9.8%
14 890
8.9%
13 806
8.1%
12 746
7.5%
11 640
6.4%

대여소번호
Real number (ℝ)

Distinct2262
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1945.3905
Minimum102
Maximum9999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:11:27.660913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile207
Q1744
median1557
Q32919
95-th percentile4574
Maximum9999
Range9897
Interquartile range (IQR)2175

Descriptive statistics

Standard deviation1423.6848
Coefficient of variation (CV)0.73182469
Kurtosis-0.78370735
Mean1945.3905
Median Absolute Deviation (MAD)1000
Skewness0.59798318
Sum19453905
Variance2026878.4
MonotonicityNot monotonic
2023-12-11T17:11:27.851611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4217 40
 
0.4%
207 40
 
0.4%
1210 35
 
0.4%
502 32
 
0.3%
2622 32
 
0.3%
272 30
 
0.3%
2102 29
 
0.3%
210 28
 
0.3%
3533 24
 
0.2%
2219 22
 
0.2%
Other values (2252) 9688
96.9%
ValueCountFrequency (%)
102 10
0.1%
103 13
0.1%
104 5
 
0.1%
105 2
 
< 0.1%
106 21
0.2%
107 7
 
0.1%
108 2
 
< 0.1%
109 6
 
0.1%
111 4
 
< 0.1%
112 9
0.1%
ValueCountFrequency (%)
9999 1
 
< 0.1%
5852 1
 
< 0.1%
5851 3
 
< 0.1%
5301 8
0.1%
5076 1
 
< 0.1%
5075 5
0.1%
5074 10
0.1%
5073 1
 
< 0.1%
5072 1
 
< 0.1%
5070 6
0.1%

대여소명
Text

Distinct2262
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T17:11:28.225198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length32
Mean length15.5369
Min length4

Characters and Unicode

Total characters155369
Distinct characters567
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique423 ?
Unique (%)4.2%

Sample

1st row919. 서울혁신파크
2nd row145. 공덕역 5번출구
3rd row1913. 구로리공원
4th row184. 7번가피자 서교망원점
5th row2621. 한성백제역 2번 출구
ValueCountFrequency (%)
앞 2556
 
8.7%
출구 484
 
1.6%
옆 401
 
1.4%
1번출구 391
 
1.3%
3번출구 262
 
0.9%
사거리 244
 
0.8%
교차로 236
 
0.8%
2번출구 229
 
0.8%
뒤 227
 
0.8%
4번출구 197
 
0.7%
Other values (4555) 24278
82.3%
2023-12-11T17:11:28.806090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19681
 
12.7%
. 10020
 
6.4%
1 8102
 
5.2%
2 6538
 
4.2%
3 4693
 
3.0%
4 4446
 
2.9%
5 3711
 
2.4%
0 3704
 
2.4%
구 3571
 
2.3%
6 3365
 
2.2%
Other values (557) 87538
56.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79805
51.4%
Decimal Number 42612
27.4%
Space Separator 19681
 
12.7%
Other Punctuation 10163
 
6.5%
Uppercase Letter 1121
 
0.7%
Close Punctuation 837
 
0.5%
Open Punctuation 837
 
0.5%
Lowercase Letter 172
 
0.1%
Dash Punctuation 116
 
0.1%
Other Number 10
 
< 0.1%
Other values (2) 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3571
 
4.5%
앞 2993
 
3.8%
역 2900
 
3.6%
번 2614
 
3.3%
출 2540
 
3.2%
동 2030
 
2.5%
교 1576
 
2.0%
리 1365
 
1.7%
파 1287
 
1.6%
원 1273
 
1.6%
Other values (495) 57656
72.2%
Uppercase Letter
ValueCountFrequency (%)
S 159
14.2%
K 135
12.0%
C 109
9.7%
T 104
9.3%
G 75
 
6.7%
B 67
 
6.0%
I 66
 
5.9%
A 59
 
5.3%
P 53
 
4.7%
L 52
 
4.6%
Other values (12) 242
21.6%
Lowercase Letter
ValueCountFrequency (%)
e 56
32.6%
s 22
 
12.8%
k 21
 
12.2%
t 12
 
7.0%
l 10
 
5.8%
n 8
 
4.7%
m 6
 
3.5%
o 6
 
3.5%
c 6
 
3.5%
f 5
 
2.9%
Other values (6) 20
 
11.6%
Decimal Number
ValueCountFrequency (%)
1 8102
19.0%
2 6538
15.3%
3 4693
11.0%
4 4446
10.4%
5 3711
8.7%
0 3704
8.7%
6 3365
7.9%
7 3101
 
7.3%
8 2656
 
6.2%
9 2296
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 10020
98.6%
, 115
 
1.1%
& 13
 
0.1%
? 8
 
0.1%
· 7
 
0.1%
Other Number
ValueCountFrequency (%)
① 9
90.0%
② 1
 
10.0%
Math Symbol
ValueCountFrequency (%)
~ 6
75.0%
+ 2
 
25.0%
Space Separator
ValueCountFrequency (%)
19681
100.0%
Close Punctuation
ValueCountFrequency (%)
) 837
100.0%
Open Punctuation
ValueCountFrequency (%)
( 837
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79805
51.4%
Common 74271
47.8%
Latin 1293
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3571
 
4.5%
앞 2993
 
3.8%
역 2900
 
3.6%
번 2614
 
3.3%
출 2540
 
3.2%
동 2030
 
2.5%
교 1576
 
2.0%
리 1365
 
1.7%
파 1287
 
1.6%
원 1273
 
1.6%
Other values (495) 57656
72.2%
Latin
ValueCountFrequency (%)
S 159
 
12.3%
K 135
 
10.4%
C 109
 
8.4%
T 104
 
8.0%
G 75
 
5.8%
B 67
 
5.2%
I 66
 
5.1%
A 59
 
4.6%
e 56
 
4.3%
P 53
 
4.1%
Other values (28) 410
31.7%
Common
ValueCountFrequency (%)
19681
26.5%
. 10020
13.5%
1 8102
10.9%
2 6538
 
8.8%
3 4693
 
6.3%
4 4446
 
6.0%
5 3711
 
5.0%
0 3704
 
5.0%
6 3365
 
4.5%
7 3101
 
4.2%
Other values (14) 6910
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79805
51.4%
ASCII 75547
48.6%
Enclosed Alphanum 10
 
< 0.1%
None 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19681
26.1%
. 10020
13.3%
1 8102
10.7%
2 6538
 
8.7%
3 4693
 
6.2%
4 4446
 
5.9%
5 3711
 
4.9%
0 3704
 
4.9%
6 3365
 
4.5%
7 3101
 
4.1%
Other values (49) 8186
10.8%
Hangul
ValueCountFrequency (%)
구 3571
 
4.5%
앞 2993
 
3.8%
역 2900
 
3.6%
번 2614
 
3.3%
출 2540
 
3.2%
동 2030
 
2.5%
교 1576
 
2.0%
리 1365
 
1.7%
파 1287
 
1.6%
원 1273
 
1.6%
Other values (495) 57656
72.2%
Enclosed Alphanum
ValueCountFrequency (%)
① 9
90.0%
② 1
 
10.0%
None
ValueCountFrequency (%)
· 7
100.0%

대여구분코드
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정기권
6515 
일일권
3124 
일일권(비회원)
 
188
단체권
 
173

Length

Max length8
Median length3
Mean length3.094
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정기권 6515
65.1%
일일권 3124
31.2%
일일권(비회원) 188
 
1.9%
단체권 173
 
1.7%

Length

2023-12-11T17:11:29.005054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:11:29.121720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 6515
65.1%
일일권 3124
31.2%
일일권(비회원 188
 
1.9%
단체권 173
 
1.7%

성별
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
M
3883 
<NA>
3509 
F
2608 

Length

Max length4
Median length1
Mean length2.0527
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
M 3883
38.8%
<NA> 3509
35.1%
F 2608
26.1%

Length

2023-12-11T17:11:29.248219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:11:29.378275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 3883
38.8%
na 3509
35.1%
f 2608
26.1%

연령대코드
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20대
3559 
30대
2296 
40대
1319 
기타
1174 
50대
807 
Other values (3)
845 

Length

Max length5
Median length3
Mean length2.9461
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30대
2nd row20대
3rd row20대
4th row20대
5th row40대

Common Values

ValueCountFrequency (%)
20대 3559
35.6%
30대 2296
23.0%
40대 1319
 
13.2%
기타 1174
 
11.7%
50대 807
 
8.1%
~10대 583
 
5.8%
60대 236
 
2.4%
70대이상 26
 
0.3%

Length

2023-12-11T17:11:29.584567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:11:29.758086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 3559
35.6%
30대 2296
23.0%
40대 1319
 
13.2%
기타 1174
 
11.7%
50대 807
 
8.1%
10대 583
 
5.8%
60대 236
 
2.4%
70대이상 26
 
0.3%

이용건수
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.13
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:11:29.912533image/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 deviation0.43808583
Coefficient of variation (CV)0.38768657
Kurtosis41.308786
Mean1.13
Median Absolute Deviation (MAD)0
Skewness5.0916424
Sum11300
Variance0.19191919
MonotonicityNot monotonic
2023-12-11T17:11:30.051735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 8958
89.6%
2 864
 
8.6%
3 128
 
1.3%
4 36
 
0.4%
5 5
 
0.1%
6 5
 
0.1%
8 3
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
1 8958
89.6%
2 864
 
8.6%
3 128
 
1.3%
4 36
 
0.4%
5 5
 
0.1%
6 5
 
0.1%
7 1
 
< 0.1%
8 3
 
< 0.1%
ValueCountFrequency (%)
8 3
 
< 0.1%
7 1
 
< 0.1%
6 5
 
0.1%
5 5
 
0.1%
4 36
 
0.4%
3 128
 
1.3%
2 864
 
8.6%
1 8958
89.6%

운동량
Text

Distinct6986
Distinct (%)69.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T17:11:30.483315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.262
Min length2

Characters and Unicode

Total characters52620
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

Unique5230 ?
Unique (%)52.3%

Sample

1st row6.87
2nd row42.17
3rd row38.47
4th row29.94
5th row9.41
ValueCountFrequency (%)
0.00 113
 
1.1%
n 38
 
0.4%
24.95 12
 
0.1%
28.83 12
 
0.1%
43.24 11
 
0.1%
29.86 10
 
0.1%
56.63 10
 
0.1%
14.67 10
 
0.1%
25.23 10
 
0.1%
29.94 9
 
0.1%
Other values (6976) 9765
97.7%
2023-12-11T17:11:31.148847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9962
18.9%
1 6197
11.8%
2 5224
9.9%
3 4630
8.8%
4 4316
8.2%
5 4027
7.7%
0 3770
 
7.2%
6 3766
 
7.2%
8 3580
 
6.8%
7 3570
 
6.8%
Other values (3) 3578
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42582
80.9%
Other Punctuation 10000
 
19.0%
Uppercase Letter 38
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6197
14.6%
2 5224
12.3%
3 4630
10.9%
4 4316
10.1%
5 4027
9.5%
0 3770
8.9%
6 3766
8.8%
8 3580
8.4%
7 3570
8.4%
9 3502
8.2%
Other Punctuation
ValueCountFrequency (%)
. 9962
99.6%
\ 38
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
N 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52582
99.9%
Latin 38
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9962
18.9%
1 6197
11.8%
2 5224
9.9%
3 4630
8.8%
4 4316
8.2%
5 4027
7.7%
0 3770
 
7.2%
6 3766
 
7.2%
8 3580
 
6.8%
7 3570
 
6.8%
Other values (2) 3540
 
6.7%
Latin
ValueCountFrequency (%)
N 38
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52620
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9962
18.9%
1 6197
11.8%
2 5224
9.9%
3 4630
8.8%
4 4316
8.2%
5 4027
7.7%
0 3770
 
7.2%
6 3766
 
7.2%
8 3580
 
6.8%
7 3570
 
6.8%
Other values (3) 3578
 
6.8%

탄소량
Text

Distinct570
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T17:11:31.660802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.9931
Min length2

Characters and Unicode

Total characters39931
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

Unique146 ?
Unique (%)1.5%

Sample

1st row0.08
2nd row0.49
3rd row0.35
4th row0.35
5th row0.11
ValueCountFrequency (%)
0.19 178
 
1.8%
0.18 149
 
1.5%
0.23 147
 
1.5%
0.20 147
 
1.5%
0.24 145
 
1.5%
0.29 143
 
1.4%
0.21 139
 
1.4%
0.15 131
 
1.3%
0.14 130
 
1.3%
0.35 130
 
1.3%
Other values (560) 8561
85.6%
2023-12-11T17:11:32.374117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9962
24.9%
0 9125
22.9%
1 4296
10.8%
2 3216
 
8.1%
3 2671
 
6.7%
4 2240
 
5.6%
5 2005
 
5.0%
6 1715
 
4.3%
7 1588
 
4.0%
8 1523
 
3.8%
Other values (3) 1590
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29893
74.9%
Other Punctuation 10000
 
25.0%
Uppercase Letter 38
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9125
30.5%
1 4296
14.4%
2 3216
 
10.8%
3 2671
 
8.9%
4 2240
 
7.5%
5 2005
 
6.7%
6 1715
 
5.7%
7 1588
 
5.3%
8 1523
 
5.1%
9 1514
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 9962
99.6%
\ 38
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
N 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39893
99.9%
Latin 38
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9962
25.0%
0 9125
22.9%
1 4296
10.8%
2 3216
 
8.1%
3 2671
 
6.7%
4 2240
 
5.6%
5 2005
 
5.0%
6 1715
 
4.3%
7 1588
 
4.0%
8 1523
 
3.8%
Other values (2) 1552
 
3.9%
Latin
ValueCountFrequency (%)
N 38
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39931
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9962
24.9%
0 9125
22.9%
1 4296
10.8%
2 3216
 
8.1%
3 2671
 
6.7%
4 2240
 
5.6%
5 2005
 
5.0%
6 1715
 
4.3%
7 1588
 
4.0%
8 1523
 
3.8%
Other values (3) 1590
 
4.0%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6362
Distinct (%)63.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3884.4445
Minimum0
Maximum87255.1
Zeros139
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:11:32.541700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile430
Q11110
median2180
Q34796.5625
95-th percentile13073.241
Maximum87255.1
Range87255.1
Interquartile range (IQR)3686.5625

Descriptive statistics

Standard deviation4763.8114
Coefficient of variation (CV)1.2263817
Kurtosis23.50642
Mean3884.4445
Median Absolute Deviation (MAD)1340
Skewness3.5159308
Sum38844445
Variance22693899
MonotonicityNot monotonic
2023-12-11T17:11:32.677946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 139
 
1.4%
820.0 25
 
0.2%
1120.0 23
 
0.2%
870.0 23
 
0.2%
570.0 22
 
0.2%
840.0 22
 
0.2%
1410.0 21
 
0.2%
1190.0 21
 
0.2%
1530.0 20
 
0.2%
900.0 20
 
0.2%
Other values (6352) 9664
96.6%
ValueCountFrequency (%)
0.0 139
1.4%
0.1 7
 
0.1%
0.13 1
 
< 0.1%
0.2 2
 
< 0.1%
0.39 1
 
< 0.1%
5.69 1
 
< 0.1%
6.59 1
 
< 0.1%
10.0 6
 
0.1%
11.35 1
 
< 0.1%
13.31 1
 
< 0.1%
ValueCountFrequency (%)
87255.1 1
< 0.1%
59836.79 1
< 0.1%
54215.43 1
< 0.1%
52672.95 1
< 0.1%
47087.55 1
< 0.1%
45779.93 1
< 0.1%
44350.0 1
< 0.1%
40682.67 1
< 0.1%
40160.57 1
< 0.1%
39720.0 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct241
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.4292
Minimum0
Maximum695
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:11:32.813592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q19
median19
Q345
95-th percentile108
Maximum695
Range695
Interquartile range (IQR)36

Descriptive statistics

Standard deviation38.722075
Coefficient of variation (CV)1.1583309
Kurtosis23.23939
Mean33.4292
Median Absolute Deviation (MAD)13
Skewness3.3167971
Sum334292
Variance1499.3991
MonotonicityNot monotonic
2023-12-11T17:11:32.967384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 417
 
4.2%
6 398
 
4.0%
4 386
 
3.9%
8 371
 
3.7%
7 371
 
3.7%
9 327
 
3.3%
11 294
 
2.9%
12 294
 
2.9%
10 271
 
2.7%
3 267
 
2.7%
Other values (231) 6604
66.0%
ValueCountFrequency (%)
0 5
 
0.1%
1 48
 
0.5%
2 199
2.0%
3 267
2.7%
4 386
3.9%
5 417
4.2%
6 398
4.0%
7 371
3.7%
8 371
3.7%
9 327
3.3%
ValueCountFrequency (%)
695 1
< 0.1%
521 1
< 0.1%
474 1
< 0.1%
428 1
< 0.1%
399 1
< 0.1%
389 2
< 0.1%
377 1
< 0.1%
361 1
< 0.1%
326 1
< 0.1%
321 1
< 0.1%

Interactions

2023-12-11T17:11:25.707231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:22.592066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:23.330911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:24.037414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:24.705597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:25.860160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:22.740925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:23.499639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:24.195929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:24.835218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:26.004003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:22.880901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:23.623924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:24.320575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:24.951780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:26.170693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:23.035187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:23.748126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:24.439908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:25.090952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:26.315899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:23.163856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:23.889985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:24.556836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:11:25.554266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T17:11:33.064240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여시간대여소번호대여구분코드성별연령대코드이용건수이동거리(M)이용시간(분)
대여시간1.0000.0220.1560.1640.1310.0670.0540.079
대여소번호0.0221.0000.0280.0080.0370.0000.0190.031
대여구분코드0.1560.0281.0000.0680.4970.4040.2580.244
성별0.1640.0080.0681.0000.1380.0320.0500.052
연령대코드0.1310.0370.4970.1381.0000.1140.0600.078
이용건수0.0670.0000.4040.0320.1141.0000.8340.630
이동거리(M)0.0540.0190.2580.0500.0600.8341.0000.747
이용시간(분)0.0790.0310.2440.0520.0780.6300.7471.000
2023-12-11T17:11:33.184626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여구분코드성별연령대코드
대여구분코드1.0000.0450.240
성별0.0451.0000.104
연령대코드0.2400.1041.000
2023-12-11T17:11:33.277942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여시간대여소번호이용건수이동거리(M)이용시간(분)대여구분코드성별연령대코드
대여시간1.0000.0010.0650.0270.0720.1040.1250.061
대여소번호0.0011.000-0.054-0.029-0.0310.0190.0090.019
이용건수0.065-0.0541.0000.2850.2930.1900.0240.038
이동거리(M)0.027-0.0290.2851.0000.8260.1180.0380.020
이용시간(분)0.072-0.0310.2930.8261.0000.1580.0520.038
대여구분코드0.1040.0190.1900.1180.1581.0000.0450.240
성별0.1250.0090.0240.0380.0520.0451.0000.104
연령대코드0.0610.0190.0380.0200.0380.2400.1041.000

Missing values

2023-12-11T17:11:26.529707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T17:11:26.784246image/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)
174702022-05-019919919. 서울혁신파크일일권F30대16.870.08327.292
565822022-05-0115145145. 공덕역 5번출구일일권<NA>20대142.170.492130.064
143552022-05-01819131913. 구로리공원일일권M20대138.470.351494.748
717482022-05-0117184184. 7번가피자 서교망원점정기권<NA>20대129.940.351512.218
577612022-05-011526212621. 한성백제역 2번 출구일일권F40대19.410.11494.8132
648812022-05-0116275275. 신동아아파트정기권M30대131.710.241040.08
114012022-05-01740284028. 한일유앤아이아파트 105동 인근정기권<NA>50대117.020.15661.117
260402022-05-011135513551.성동도로사업소정기권M50대1119.951.084660.026
604632022-05-011513631363. 보문4교 인근정기권<NA>30대1101.931.134856.7625
147582022-05-01818201820. 신한은행 시흥대로금융센터지점정기권<NA>40대152.770.482050.013
대여일자대여시간대여소번호대여소명대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
921662022-05-0119434434. 신당 래미안 버스정류장정기권M30대127.720.231000.04
741442022-05-011735333533. 건대입구역 사거리(롯데백화점)정기권M40대140.420.311325.698
244332022-05-011145174517. 성보하이드로빌딩정기권<NA>30대150.060.552385.1719
635732022-05-0116492492.성산시영아파트 후문정기권F20대2143.881.345775.33109
515252022-05-011423472347. 두산건설 본사정기권<NA>30대1223.961.385953.2110
553382022-05-011510351035. 고덕역 4번출구정기권M20대130.190.271172.896
426602022-05-0113204204. 국회의사당역 5번출구 옆정기권<NA>20대1139.881.285519.1749
704522022-05-011616621662. 노원역7번출구정기권M~10대1388.163.5015080.078
319832022-05-0112284284. 센트럴 푸르지오 시티 앞정기권M40대124.950.19840.054
708862022-05-011616691669. 중계역 3번출구정기권M40대164.220.612615.8131