Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells7217
Missing cells (%)6.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory976.6 KiB
Average record size in memory100.0 B

Variable types

Categorical3
Numeric4
Text3
Boolean1

Dataset

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

Alerts

대여일자 has constant value ""Constant
대여구분코드 has constant value ""Constant
성별 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
성별 has 7217 (72.2%) missing valuesMissing
이동거리(M) has 130 (1.3%) zerosZeros

Reproduction

Analysis started2024-05-18 04:52:46.643100
Analysis finished2024-05-18 04:52:54.541391
Duration7.9 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
2022-12-01
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-01
2nd row2022-12-01
3rd row2022-12-01
4th row2022-12-01
5th row2022-12-01

Common Values

ValueCountFrequency (%)
2022-12-01 10000
100.0%

Length

2024-05-18T13:52:55.125821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:52:57.196656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-01 10000
100.0%

대여소번호
Real number (ℝ)

Distinct2468
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2122.3115
Minimum102
Maximum9980
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T13:52:57.974272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile255
Q1900
median1729.5
Q33501
95-th percentile4815.2
Maximum9980
Range9878
Interquartile range (IQR)2601

Descriptive statistics

Standard deviation1492.4594
Coefficient of variation (CV)0.70322354
Kurtosis-0.81336109
Mean2122.3115
Median Absolute Deviation (MAD)1005.5
Skewness0.57870654
Sum21223115
Variance2227435.1
MonotonicityNot monotonic
2024-05-18T13:52:58.587569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1153 15
 
0.1%
2701 13
 
0.1%
3219 12
 
0.1%
1210 12
 
0.1%
2728 12
 
0.1%
383 11
 
0.1%
2177 11
 
0.1%
2715 11
 
0.1%
785 11
 
0.1%
113 11
 
0.1%
Other values (2458) 9881
98.8%
ValueCountFrequency (%)
102 4
< 0.1%
103 3
< 0.1%
104 2
 
< 0.1%
105 3
< 0.1%
106 4
< 0.1%
107 4
< 0.1%
108 5
0.1%
109 2
 
< 0.1%
111 2
 
< 0.1%
112 6
0.1%
ValueCountFrequency (%)
9980 1
 
< 0.1%
6053 2
 
< 0.1%
5861 1
 
< 0.1%
5860 6
0.1%
5859 2
 
< 0.1%
5858 5
0.1%
5857 2
 
< 0.1%
5855 1
 
< 0.1%
5854 7
0.1%
5853 6
0.1%

대여소
Text

Distinct2468
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T13:52:59.740644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length32
Mean length15.6123
Min length7

Characters and Unicode

Total characters156123
Distinct characters573
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

Unique323 ?
Unique (%)3.2%

Sample

1st row2231. 삼성타운(삼성생명) A동 맞은편
2nd row4181. 보라매공원역 2번출구
3rd row1153. 발산역 1번, 9번 인근 대여소
4th row2647.잠실 자전거 수리센터 앞
5th row1215. 올림픽공원역 1번출구 앞
ValueCountFrequency (%)
앞 2560
 
8.7%
출구 439
 
1.5%
옆 383
 
1.3%
1번출구 315
 
1.1%
교차로 229
 
0.8%
사거리 224
 
0.8%
2번출구 215
 
0.7%
입구 208
 
0.7%
3번출구 202
 
0.7%
뒤 201
 
0.7%
Other values (4956) 24352
83.0%
2024-05-18T13:53:01.236651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19523
 
12.5%
. 10017
 
6.4%
1 8074
 
5.2%
2 5928
 
3.8%
3 4741
 
3.0%
4 4687
 
3.0%
5 3834
 
2.5%
0 3606
 
2.3%
6 3351
 
2.1%
구 3341
 
2.1%
Other values (563) 89021
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80414
51.5%
Decimal Number 42928
27.5%
Space Separator 19523
 
12.5%
Other Punctuation 10164
 
6.5%
Uppercase Letter 1187
 
0.8%
Close Punctuation 815
 
0.5%
Open Punctuation 815
 
0.5%
Lowercase Letter 165
 
0.1%
Dash Punctuation 81
 
0.1%
Connector Punctuation 11
 
< 0.1%
Other values (3) 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3341
 
4.2%
앞 2966
 
3.7%
역 2596
 
3.2%
번 2318
 
2.9%
출 2259
 
2.8%
동 2181
 
2.7%
교 1610
 
2.0%
파 1408
 
1.8%
리 1361
 
1.7%
아 1349
 
1.7%
Other values (501) 59025
73.4%
Uppercase Letter
ValueCountFrequency (%)
S 157
13.2%
K 123
10.4%
C 109
9.2%
T 101
 
8.5%
G 88
 
7.4%
D 84
 
7.1%
B 76
 
6.4%
A 74
 
6.2%
M 62
 
5.2%
L 53
 
4.5%
Other values (14) 260
21.9%
Lowercase Letter
ValueCountFrequency (%)
e 55
33.3%
s 21
 
12.7%
k 18
 
10.9%
n 16
 
9.7%
l 8
 
4.8%
y 8
 
4.8%
t 7
 
4.2%
f 6
 
3.6%
r 6
 
3.6%
h 6
 
3.6%
Other values (3) 14
 
8.5%
Decimal Number
ValueCountFrequency (%)
1 8074
18.8%
2 5928
13.8%
3 4741
11.0%
4 4687
10.9%
5 3834
8.9%
0 3606
8.4%
6 3351
7.8%
7 3300
7.7%
8 2894
 
6.7%
9 2513
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 10017
98.6%
, 95
 
0.9%
& 30
 
0.3%
? 13
 
0.1%
· 9
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 7
77.8%
+ 2
 
22.2%
Other Number
ValueCountFrequency (%)
① 3
60.0%
② 2
40.0%
Space Separator
ValueCountFrequency (%)
19523
100.0%
Close Punctuation
ValueCountFrequency (%)
) 815
100.0%
Open Punctuation
ValueCountFrequency (%)
( 815
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 11
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80420
51.5%
Common 74351
47.6%
Latin 1352
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3341
 
4.2%
앞 2966
 
3.7%
역 2596
 
3.2%
번 2318
 
2.9%
출 2259
 
2.8%
동 2181
 
2.7%
교 1610
 
2.0%
파 1408
 
1.8%
리 1361
 
1.7%
아 1349
 
1.7%
Other values (502) 59031
73.4%
Latin
ValueCountFrequency (%)
S 157
 
11.6%
K 123
 
9.1%
C 109
 
8.1%
T 101
 
7.5%
G 88
 
6.5%
D 84
 
6.2%
B 76
 
5.6%
A 74
 
5.5%
M 62
 
4.6%
e 55
 
4.1%
Other values (27) 423
31.3%
Common
ValueCountFrequency (%)
19523
26.3%
. 10017
13.5%
1 8074
10.9%
2 5928
 
8.0%
3 4741
 
6.4%
4 4687
 
6.3%
5 3834
 
5.2%
0 3606
 
4.8%
6 3351
 
4.5%
7 3300
 
4.4%
Other values (14) 7290
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80414
51.5%
ASCII 75689
48.5%
None 15
 
< 0.1%
Enclosed Alphanum 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19523
25.8%
. 10017
13.2%
1 8074
10.7%
2 5928
 
7.8%
3 4741
 
6.3%
4 4687
 
6.2%
5 3834
 
5.1%
0 3606
 
4.8%
6 3351
 
4.4%
7 3300
 
4.4%
Other values (48) 8628
11.4%
Hangul
ValueCountFrequency (%)
구 3341
 
4.2%
앞 2966
 
3.7%
역 2596
 
3.2%
번 2318
 
2.9%
출 2259
 
2.8%
동 2181
 
2.7%
교 1610
 
2.0%
파 1408
 
1.8%
리 1361
 
1.7%
아 1349
 
1.7%
Other values (501) 59025
73.4%
None
ValueCountFrequency (%)
· 9
60.0%
㈜ 6
40.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 3
60.0%
② 2
40.0%

대여구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정기권
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정기권 10000
100.0%

Length

2024-05-18T13:53:01.871882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:53:02.276489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 10000
100.0%

성별
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing7217
Missing (%)72.2%
Memory size97.7 KiB
False
2783 
(Missing)
7217 
ValueCountFrequency (%)
False 2783
 
27.8%
(Missing) 7217
72.2%
2024-05-18T13:53:02.744813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

연령대
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20대
4016 
30대
2138 
40대
1221 
50대
909 
~10대
806 
Other values (3)
910 

Length

Max length5
Median length3
Mean length3.0348
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
20대 4016
40.2%
30대 2138
21.4%
40대 1221
 
12.2%
50대 909
 
9.1%
~10대 806
 
8.1%
기타 556
 
5.6%
60대 305
 
3.0%
70대이상 49
 
0.5%

Length

2024-05-18T13:53:03.367496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:53:03.735419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 4016
40.2%
30대 2138
21.4%
40대 1221
 
12.2%
50대 909
 
9.1%
10대 806
 
8.1%
기타 556
 
5.6%
60대 305
 
3.0%
70대이상 49
 
0.5%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.165
Minimum1
Maximum42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T13:53:04.100938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile6
Maximum42
Range41
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.1823041
Coefficient of variation (CV)1.0079927
Kurtosis34.968221
Mean2.165
Median Absolute Deviation (MAD)0
Skewness4.3214951
Sum21650
Variance4.7624512
MonotonicityNot monotonic
2024-05-18T13:53:04.451994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1 5509
55.1%
2 2054
 
20.5%
3 975
 
9.8%
4 500
 
5.0%
5 315
 
3.1%
6 205
 
2.1%
7 142
 
1.4%
8 85
 
0.9%
9 57
 
0.6%
10 43
 
0.4%
Other values (17) 115
 
1.1%
ValueCountFrequency (%)
1 5509
55.1%
2 2054
 
20.5%
3 975
 
9.8%
4 500
 
5.0%
5 315
 
3.1%
6 205
 
2.1%
7 142
 
1.4%
8 85
 
0.9%
9 57
 
0.6%
10 43
 
0.4%
ValueCountFrequency (%)
42 1
 
< 0.1%
32 2
< 0.1%
28 1
 
< 0.1%
27 1
 
< 0.1%
25 2
< 0.1%
24 1
 
< 0.1%
23 1
 
< 0.1%
21 1
 
< 0.1%
20 1
 
< 0.1%
18 3
< 0.1%

운동량
Text

Distinct7029
Distinct (%)70.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T13:53:05.360586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.2197
Min length2

Characters and Unicode

Total characters52197
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

Unique5216 ?
Unique (%)52.2%

Sample

1st row213.05
2nd row132.77
3rd row34.69
4th row188.61
5th row161.58
ValueCountFrequency (%)
0.00 131
 
1.3%
n 25
 
0.2%
21.62 11
 
0.1%
14.41 11
 
0.1%
15.44 10
 
0.1%
23.17 10
 
0.1%
21.88 10
 
0.1%
14.16 9
 
0.1%
17.76 9
 
0.1%
20.59 9
 
0.1%
Other values (7019) 9765
97.7%
2024-05-18T13:53:07.108218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9975
19.1%
1 6366
12.2%
2 5147
9.9%
3 4536
8.7%
4 4196
8.0%
0 3796
 
7.3%
5 3774
 
7.2%
6 3753
 
7.2%
7 3580
 
6.9%
8 3520
 
6.7%
Other values (3) 3554
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42172
80.8%
Other Punctuation 10000
 
19.2%
Uppercase Letter 25
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6366
15.1%
2 5147
12.2%
3 4536
10.8%
4 4196
9.9%
0 3796
9.0%
5 3774
8.9%
6 3753
8.9%
7 3580
8.5%
8 3520
8.3%
9 3504
8.3%
Other Punctuation
ValueCountFrequency (%)
. 9975
99.8%
\ 25
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52172
> 99.9%
Latin 25
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9975
19.1%
1 6366
12.2%
2 5147
9.9%
3 4536
8.7%
4 4196
8.0%
0 3796
 
7.3%
5 3774
 
7.2%
6 3753
 
7.2%
7 3580
 
6.9%
8 3520
 
6.7%
Other values (2) 3529
 
6.8%
Latin
ValueCountFrequency (%)
N 25
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52197
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9975
19.1%
1 6366
12.2%
2 5147
9.9%
3 4536
8.7%
4 4196
8.0%
0 3796
 
7.3%
5 3774
 
7.2%
6 3753
 
7.2%
7 3580
 
6.9%
8 3520
 
6.7%
Other values (3) 3554
 
6.8%

탄소량
Text

Distinct452
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T13:53:08.285429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.9951
Min length2

Characters and Unicode

Total characters39951
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

Unique109 ?
Unique (%)1.1%

Sample

1st row2.01
2nd row0.92
3rd row0.34
4th row1.78
5th row1.65
ValueCountFrequency (%)
0.16 171
 
1.7%
0.19 158
 
1.6%
0.18 157
 
1.6%
0.14 152
 
1.5%
0.23 150
 
1.5%
0.21 146
 
1.5%
0.24 146
 
1.5%
0.17 145
 
1.5%
0.13 143
 
1.4%
0.22 141
 
1.4%
Other values (442) 8491
84.9%
2024-05-18T13:53:10.015717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9975
25.0%
0 9499
23.8%
1 4435
11.1%
2 3126
 
7.8%
3 2571
 
6.4%
4 2103
 
5.3%
5 1882
 
4.7%
6 1756
 
4.4%
7 1582
 
4.0%
8 1541
 
3.9%
Other values (3) 1481
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29926
74.9%
Other Punctuation 10000
 
25.0%
Uppercase Letter 25
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9499
31.7%
1 4435
14.8%
2 3126
 
10.4%
3 2571
 
8.6%
4 2103
 
7.0%
5 1882
 
6.3%
6 1756
 
5.9%
7 1582
 
5.3%
8 1541
 
5.1%
9 1431
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 9975
99.8%
\ 25
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39926
99.9%
Latin 25
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9975
25.0%
0 9499
23.8%
1 4435
11.1%
2 3126
 
7.8%
3 2571
 
6.4%
4 2103
 
5.3%
5 1882
 
4.7%
6 1756
 
4.4%
7 1582
 
4.0%
8 1541
 
3.9%
Other values (2) 1456
 
3.6%
Latin
ValueCountFrequency (%)
N 25
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39951
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9975
25.0%
0 9499
23.8%
1 4435
11.1%
2 3126
 
7.8%
3 2571
 
6.4%
4 2103
 
5.3%
5 1882
 
4.7%
6 1756
 
4.4%
7 1582
 
4.0%
8 1541
 
3.9%
Other values (3) 1481
 
3.7%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7165
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3269.9378
Minimum0
Maximum49144.87
Zeros130
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T13:53:10.581965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile430
Q11043.2975
median2070
Q34182.5175
95-th percentile10152.313
Maximum49144.87
Range49144.87
Interquartile range (IQR)3139.22

Descriptive statistics

Standard deviation3522.7014
Coefficient of variation (CV)1.0772992
Kurtosis14.915775
Mean3269.9378
Median Absolute Deviation (MAD)1260
Skewness2.9269764
Sum32699378
Variance12409425
MonotonicityNot monotonic
2024-05-18T13:53:11.100312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 130
 
1.3%
670.0 29
 
0.3%
800.0 25
 
0.2%
690.0 23
 
0.2%
620.0 22
 
0.2%
1020.0 21
 
0.2%
710.0 20
 
0.2%
640.0 20
 
0.2%
630.0 20
 
0.2%
550.0 20
 
0.2%
Other values (7155) 9670
96.7%
ValueCountFrequency (%)
0.0 130
1.3%
0.1 3
 
< 0.1%
0.13 2
 
< 0.1%
10.0 4
 
< 0.1%
20.0 4
 
< 0.1%
23.66 1
 
< 0.1%
27.92 1
 
< 0.1%
30.0 1
 
< 0.1%
31.39 1
 
< 0.1%
32.89 1
 
< 0.1%
ValueCountFrequency (%)
49144.87 1
< 0.1%
41873.67 1
< 0.1%
41525.64 1
< 0.1%
39212.91 1
< 0.1%
33967.07 1
< 0.1%
30606.79 1
< 0.1%
30491.13 1
< 0.1%
30445.2 1
< 0.1%
29923.54 1
< 0.1%
29502.23 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct207
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.5311
Minimum0
Maximum444
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T13:53:11.607417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q17
median15
Q333
95-th percentile82
Maximum444
Range444
Interquartile range (IQR)26

Descriptive statistics

Standard deviation29.699748
Coefficient of variation (CV)1.1632773
Kurtosis19.190062
Mean25.5311
Median Absolute Deviation (MAD)10
Skewness3.2957146
Sum255311
Variance882.07504
MonotonicityNot monotonic
2024-05-18T13:53:12.048012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 494
 
4.9%
5 477
 
4.8%
6 454
 
4.5%
7 441
 
4.4%
9 390
 
3.9%
3 384
 
3.8%
8 384
 
3.8%
10 360
 
3.6%
11 324
 
3.2%
12 296
 
3.0%
Other values (197) 5996
60.0%
ValueCountFrequency (%)
0 4
 
< 0.1%
1 80
 
0.8%
2 255
2.5%
3 384
3.8%
4 494
4.9%
5 477
4.8%
6 454
4.5%
7 441
4.4%
8 384
3.8%
9 390
3.9%
ValueCountFrequency (%)
444 1
< 0.1%
365 1
< 0.1%
342 1
< 0.1%
333 1
< 0.1%
316 1
< 0.1%
300 1
< 0.1%
285 1
< 0.1%
279 1
< 0.1%
265 1
< 0.1%
262 1
< 0.1%

Interactions

2024-05-18T13:52:51.823229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:48.762285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:49.750790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:50.757748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:52.085024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:49.003753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:49.994352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:51.021783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:52.448699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:49.239870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:50.224457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:51.283552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:52.712454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:49.500468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:50.477400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:51.546531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T13:53:12.310494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호연령대이용건수이동거리(M)이용시간(분)
대여소번호1.0000.0590.0000.0000.000
연령대0.0591.0000.1620.1510.151
이용건수0.0000.1621.0000.8230.682
이동거리(M)0.0000.1510.8231.0000.890
이용시간(분)0.0000.1510.6820.8901.000
2024-05-18T13:53:12.756422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)연령대
대여소번호1.000-0.050-0.031-0.0390.020
이용건수-0.0501.0000.6930.6750.080
이동거리(M)-0.0310.6931.0000.8890.072
이용시간(분)-0.0390.6750.8891.0000.072
연령대0.0200.0800.0720.0721.000

Missing values

2024-05-18T13:52:53.239849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T13:52:54.100947image/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

대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
24212022-12-0122312231. 삼성타운(삼성생명) A동 맞은편정기권<NA>20대6213.052.018639.7376
38372022-12-0141814181. 보라매공원역 2번출구정기권<NA>30대3132.770.923960.118
4132022-12-0111531153. 발산역 1번, 9번 인근 대여소정기권<NA>20대134.690.341460.012
83992022-12-0126472647.잠실 자전거 수리센터 앞정기권F20대8188.611.787694.8560
94202022-12-0112151215. 올림픽공원역 1번출구 앞정기권F20대2161.581.657110.028
20862022-12-01571571. 세종대학교 대양AI센터정기권<NA>20대18.500.09370.02
52392022-12-01577577. 광진청소년수련관정기권<NA>40대274.310.512205.9711
69282022-12-0116831683. 노원문화예술회관정기권<NA>기타168.440.622658.73133
92662022-12-01196196. 연희교차로 인근정기권F20대118.360.17713.386
68612022-12-0119561956. 동아1차APT105동 버스정류장(신도림중학교 방면)정기권<NA>기타10.000.12535.164
대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
91832022-12-0143324332. 이수교차로정기권F20대124.580.21886.687
35872022-12-0140094009. 월계프라자정기권<NA>30대111.050.12536.823
52622022-12-01141141. 연대 대운동장 옆정기권<NA>40대168.720.622669.9649
48602022-12-01180180. 충정로역 7번출구 아래정기권<NA>40대171.680.512180.9212
75992022-12-0135593559.성동구민종합체육센터 앞정기권F~10대165.480.592543.7316
93102022-12-01634634. 외국어대 정문 앞정기권F20대8326.513.4414791.77129
90112022-12-0148194819. 면목동 새싹어린이공원 앞정기권F20대3153.071.375946.4537
47452022-12-0127102710.라이품 공영주차장 앞정기권<NA>40대131.960.301301.936
26232022-12-01734734. 신트리공원 입구정기권<NA>30대4234.762.068904.5153
21992022-12-0110201020. 강동경찰서정기권<NA>20대15579.305.4523514.87255