Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells7208
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/F/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 7208 (72.1%) missing valuesMissing
이동거리(M) has 129 (1.3%) zerosZeros

Reproduction

Analysis started2024-03-13 16:26:39.080812
Analysis finished2024-03-13 16:26:41.619739
Duration2.54 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

2024-03-14T01:26:41.680744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:26:41.767366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-01 10000
100.0%

대여소번호
Real number (ℝ)

Distinct2469
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2118.969
Minimum102
Maximum9980
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:26:41.871200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile251
Q1857
median1725.5
Q33502
95-th percentile4815
Maximum9980
Range9878
Interquartile range (IQR)2645

Descriptive statistics

Standard deviation1494.0825
Coefficient of variation (CV)0.70509882
Kurtosis-0.82040583
Mean2118.969
Median Absolute Deviation (MAD)1009.5
Skewness0.57703614
Sum21189690
Variance2232282.7
MonotonicityNot monotonic
2024-03-14T01:26:42.023577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1153 14
 
0.1%
2701 13
 
0.1%
2728 12
 
0.1%
1210 12
 
0.1%
113 12
 
0.1%
3219 12
 
0.1%
785 11
 
0.1%
1158 11
 
0.1%
770 11
 
0.1%
383 11
 
0.1%
Other values (2459) 9881
98.8%
ValueCountFrequency (%)
102 4
< 0.1%
103 3
< 0.1%
104 2
 
< 0.1%
105 3
< 0.1%
106 5
0.1%
107 4
< 0.1%
108 5
0.1%
109 1
 
< 0.1%
111 3
< 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 5
0.1%

대여소
Text

Distinct2469
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T01:26:42.266076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length32
Mean length15.6087
Min length7

Characters and Unicode

Total characters156087
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

Unique320 ?
Unique (%)3.2%

Sample

1st row1196. 서울식물원(문화센터) 건너편
2nd row2244.교육개발원입구 교차로
3rd row1435. 능산삼거리
4th row126. 서강대 후문 옆
5th row3685. 강동리엔파크14단지(1401동 앞)
ValueCountFrequency (%)
앞 2579
 
8.8%
출구 438
 
1.5%
옆 382
 
1.3%
1번출구 318
 
1.1%
교차로 226
 
0.8%
사거리 219
 
0.7%
2번출구 218
 
0.7%
입구 208
 
0.7%
뒤 202
 
0.7%
3번출구 200
 
0.7%
Other values (4961) 24349
83.0%
2024-03-14T01:26:42.620103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19534
 
12.5%
. 10017
 
6.4%
1 8044
 
5.2%
2 5928
 
3.8%
3 4754
 
3.0%
4 4656
 
3.0%
5 3848
 
2.5%
0 3595
 
2.3%
구 3344
 
2.1%
6 3343
 
2.1%
Other values (563) 89024
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80464
51.6%
Decimal Number 42850
27.5%
Space Separator 19534
 
12.5%
Other Punctuation 10157
 
6.5%
Uppercase Letter 1182
 
0.8%
Open Punctuation 812
 
0.5%
Close Punctuation 812
 
0.5%
Lowercase Letter 166
 
0.1%
Dash Punctuation 79
 
0.1%
Connector Punctuation 11
 
< 0.1%
Other values (3) 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3344
 
4.2%
앞 2982
 
3.7%
역 2600
 
3.2%
번 2320
 
2.9%
출 2263
 
2.8%
동 2184
 
2.7%
교 1614
 
2.0%
파 1404
 
1.7%
리 1356
 
1.7%
아 1348
 
1.7%
Other values (501) 59049
73.4%
Uppercase Letter
ValueCountFrequency (%)
S 157
13.3%
K 120
10.2%
C 110
9.3%
T 99
 
8.4%
G 86
 
7.3%
D 85
 
7.2%
B 77
 
6.5%
A 75
 
6.3%
M 62
 
5.2%
L 53
 
4.5%
Other values (14) 258
21.8%
Lowercase Letter
ValueCountFrequency (%)
e 55
33.1%
s 21
 
12.7%
k 18
 
10.8%
n 16
 
9.6%
y 8
 
4.8%
l 8
 
4.8%
t 7
 
4.2%
v 7
 
4.2%
h 6
 
3.6%
r 6
 
3.6%
Other values (3) 14
 
8.4%
Decimal Number
ValueCountFrequency (%)
1 8044
18.8%
2 5928
13.8%
3 4754
11.1%
4 4656
10.9%
5 3848
9.0%
0 3595
8.4%
6 3343
7.8%
7 3288
7.7%
8 2891
 
6.7%
9 2503
 
5.8%
Other Punctuation
ValueCountFrequency (%)
. 10017
98.6%
, 91
 
0.9%
& 28
 
0.3%
? 13
 
0.1%
· 8
 
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 (%)
19534
100.0%
Open Punctuation
ValueCountFrequency (%)
( 812
100.0%
Close Punctuation
ValueCountFrequency (%)
) 812
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 11
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80470
51.6%
Common 74269
47.6%
Latin 1348
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3344
 
4.2%
앞 2982
 
3.7%
역 2600
 
3.2%
번 2320
 
2.9%
출 2263
 
2.8%
동 2184
 
2.7%
교 1614
 
2.0%
파 1404
 
1.7%
리 1356
 
1.7%
아 1348
 
1.7%
Other values (502) 59055
73.4%
Latin
ValueCountFrequency (%)
S 157
 
11.6%
K 120
 
8.9%
C 110
 
8.2%
T 99
 
7.3%
G 86
 
6.4%
D 85
 
6.3%
B 77
 
5.7%
A 75
 
5.6%
M 62
 
4.6%
e 55
 
4.1%
Other values (27) 422
31.3%
Common
ValueCountFrequency (%)
19534
26.3%
. 10017
13.5%
1 8044
10.8%
2 5928
 
8.0%
3 4754
 
6.4%
4 4656
 
6.3%
5 3848
 
5.2%
0 3595
 
4.8%
6 3343
 
4.5%
7 3288
 
4.4%
Other values (14) 7262
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80464
51.6%
ASCII 75604
48.4%
None 14
 
< 0.1%
Enclosed Alphanum 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19534
25.8%
. 10017
13.2%
1 8044
10.6%
2 5928
 
7.8%
3 4754
 
6.3%
4 4656
 
6.2%
5 3848
 
5.1%
0 3595
 
4.8%
6 3343
 
4.4%
7 3288
 
4.3%
Other values (48) 8597
11.4%
Hangul
ValueCountFrequency (%)
구 3344
 
4.2%
앞 2982
 
3.7%
역 2600
 
3.2%
번 2320
 
2.9%
출 2263
 
2.8%
동 2184
 
2.7%
교 1614
 
2.0%
파 1404
 
1.7%
리 1356
 
1.7%
아 1348
 
1.7%
Other values (501) 59049
73.4%
None
ValueCountFrequency (%)
· 8
57.1%
㈜ 6
42.9%
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

2024-03-14T01:26:42.723039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:26:42.791468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 10000
100.0%

성별
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing7208
Missing (%)72.1%
Memory size97.7 KiB
False
2792 
(Missing)
7208 
ValueCountFrequency (%)
False 2792
 
27.9%
(Missing) 7208
72.1%
2024-03-14T01:26:42.847361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

연령대
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20대
4031 
30대
2140 
40대
1226 
50대
903 
~10대
793 
Other values (3)
907 

Length

Max length5
Median length3
Mean length3.0333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
20대 4031
40.3%
30대 2140
21.4%
40대 1226
 
12.3%
50대 903
 
9.0%
~10대 793
 
7.9%
기타 558
 
5.6%
60대 300
 
3.0%
70대이상 49
 
0.5%

Length

2024-03-14T01:26:42.924608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:26:43.021293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 4031
40.3%
30대 2140
21.4%
40대 1226
 
12.3%
50대 903
 
9.0%
10대 793
 
7.9%
기타 558
 
5.6%
60대 300
 
3.0%
70대이상 49
 
0.5%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.171
Minimum1
Maximum42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:26:43.138559image/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 deviation2.1946846
Coefficient of variation (CV)1.0109096
Kurtosis34.397676
Mean2.171
Median Absolute Deviation (MAD)0
Skewness4.2977114
Sum21710
Variance4.8166407
MonotonicityNot monotonic
2024-03-14T01:26:43.238941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1 5507
55.1%
2 2050
 
20.5%
3 975
 
9.8%
4 498
 
5.0%
5 314
 
3.1%
6 206
 
2.1%
7 144
 
1.4%
8 89
 
0.9%
9 57
 
0.6%
10 43
 
0.4%
Other values (17) 117
 
1.2%
ValueCountFrequency (%)
1 5507
55.1%
2 2050
 
20.5%
3 975
 
9.8%
4 498
 
5.0%
5 314
 
3.1%
6 206
 
2.1%
7 144
 
1.4%
8 89
 
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

Distinct7038
Distinct (%)70.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T01:26:43.540997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.2211
Min length2

Characters and Unicode

Total characters52211
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

Unique5236 ?
Unique (%)52.4%

Sample

1st row57.72
2nd row28.11
3rd row89.92
4th row120.25
5th row43.70
ValueCountFrequency (%)
0.00 130
 
1.3%
n 24
 
0.2%
21.62 12
 
0.1%
14.41 11
 
0.1%
14.16 10
 
0.1%
21.88 10
 
0.1%
23.17 10
 
0.1%
15.44 9
 
0.1%
23.68 9
 
0.1%
20.59 9
 
0.1%
Other values (7028) 9766
97.7%
2024-03-14T01:26:43.945728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9976
19.1%
1 6363
12.2%
2 5157
9.9%
3 4531
8.7%
4 4172
8.0%
0 3805
 
7.3%
5 3779
 
7.2%
6 3759
 
7.2%
7 3584
 
6.9%
8 3529
 
6.8%
Other values (3) 3556
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42187
80.8%
Other Punctuation 10000
 
19.2%
Uppercase Letter 24
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6363
15.1%
2 5157
12.2%
3 4531
10.7%
4 4172
9.9%
0 3805
9.0%
5 3779
9.0%
6 3759
8.9%
7 3584
8.5%
8 3529
8.4%
9 3508
8.3%
Other Punctuation
ValueCountFrequency (%)
. 9976
99.8%
\ 24
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52187
> 99.9%
Latin 24
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9976
19.1%
1 6363
12.2%
2 5157
9.9%
3 4531
8.7%
4 4172
8.0%
0 3805
 
7.3%
5 3779
 
7.2%
6 3759
 
7.2%
7 3584
 
6.9%
8 3529
 
6.8%
Other values (2) 3532
 
6.8%
Latin
ValueCountFrequency (%)
N 24
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52211
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9976
19.1%
1 6363
12.2%
2 5157
9.9%
3 4531
8.7%
4 4172
8.0%
0 3805
 
7.3%
5 3779
 
7.2%
6 3759
 
7.2%
7 3584
 
6.9%
8 3529
 
6.8%
Other values (3) 3556
 
6.8%

탄소량
Text

Distinct454
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T01:26:44.318058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.9953
Min length2

Characters and Unicode

Total characters39953
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

Unique110 ?
Unique (%)1.1%

Sample

1st row0.52
2nd row0.21
3rd row0.97
4th row1.14
5th row0.44
ValueCountFrequency (%)
0.16 170
 
1.7%
0.19 165
 
1.7%
0.18 156
 
1.6%
0.14 152
 
1.5%
0.23 150
 
1.5%
0.21 146
 
1.5%
0.24 146
 
1.5%
0.13 145
 
1.5%
0.17 142
 
1.4%
0.22 140
 
1.4%
Other values (444) 8488
84.9%
2024-03-14T01:26:44.762970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9976
25.0%
0 9495
23.8%
1 4435
11.1%
2 3130
 
7.8%
3 2562
 
6.4%
4 2103
 
5.3%
5 1892
 
4.7%
6 1759
 
4.4%
7 1577
 
3.9%
8 1540
 
3.9%
Other values (3) 1484
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29929
74.9%
Other Punctuation 10000
 
25.0%
Uppercase Letter 24
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9495
31.7%
1 4435
14.8%
2 3130
 
10.5%
3 2562
 
8.6%
4 2103
 
7.0%
5 1892
 
6.3%
6 1759
 
5.9%
7 1577
 
5.3%
8 1540
 
5.1%
9 1436
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 9976
99.8%
\ 24
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39929
99.9%
Latin 24
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9976
25.0%
0 9495
23.8%
1 4435
11.1%
2 3130
 
7.8%
3 2562
 
6.4%
4 2103
 
5.3%
5 1892
 
4.7%
6 1759
 
4.4%
7 1577
 
3.9%
8 1540
 
3.9%
Other values (2) 1460
 
3.7%
Latin
ValueCountFrequency (%)
N 24
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39953
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9976
25.0%
0 9495
23.8%
1 4435
11.1%
2 3130
 
7.8%
3 2562
 
6.4%
4 2103
 
5.3%
5 1892
 
4.7%
6 1759
 
4.4%
7 1577
 
3.9%
8 1540
 
3.9%
Other values (3) 1484
 
3.7%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7176
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3276.6585
Minimum0
Maximum49144.87
Zeros129
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:26:44.881160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile430
Q11043.5625
median2074.72
Q34203.46
95-th percentile10157.063
Maximum49144.87
Range49144.87
Interquartile range (IQR)3159.8975

Descriptive statistics

Standard deviation3531.6713
Coefficient of variation (CV)1.0778271
Kurtosis14.837209
Mean3276.6585
Median Absolute Deviation (MAD)1263.77
Skewness2.9232516
Sum32766585
Variance12472702
MonotonicityNot monotonic
2024-03-14T01:26:44.985850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 129
 
1.3%
670.0 29
 
0.3%
800.0 25
 
0.2%
690.0 22
 
0.2%
630.0 21
 
0.2%
620.0 21
 
0.2%
790.0 21
 
0.2%
1020.0 21
 
0.2%
640.0 20
 
0.2%
710.0 20
 
0.2%
Other values (7166) 9671
96.7%
ValueCountFrequency (%)
0.0 129
1.3%
0.1 2
 
< 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%
Mean25.5862
Minimum0
Maximum444
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T01:26:45.095623image/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 deviation29.815014
Coefficient of variation (CV)1.1652771
Kurtosis19.679094
Mean25.5862
Median Absolute Deviation (MAD)10
Skewness3.3269137
Sum255862
Variance888.93506
MonotonicityNot monotonic
2024-03-14T01:26:45.217511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 496
 
5.0%
5 473
 
4.7%
6 453
 
4.5%
7 445
 
4.5%
9 391
 
3.9%
8 391
 
3.9%
3 377
 
3.8%
10 361
 
3.6%
11 316
 
3.2%
12 296
 
3.0%
Other values (197) 6001
60.0%
ValueCountFrequency (%)
0 4
 
< 0.1%
1 81
 
0.8%
2 255
2.5%
3 377
3.8%
4 496
5.0%
5 473
4.7%
6 453
4.5%
7 445
4.5%
8 391
3.9%
9 391
3.9%
ValueCountFrequency (%)
444 1
< 0.1%
365 1
< 0.1%
342 1
< 0.1%
339 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%

Interactions

2024-03-14T01:26:41.113513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:26:39.946223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:26:40.463433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:26:40.770156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:26:41.180110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:26:40.247735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:26:40.528596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:26:40.859768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:26:41.255588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:26:40.326087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:26:40.596537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:26:40.951577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:26:41.335579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:26:40.395530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:26:40.679914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:26:41.043702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T01:26:45.286521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호연령대이용건수이동거리(M)이용시간(분)
대여소번호1.0000.0570.0000.0000.000
연령대0.0571.0000.1630.1510.149
이용건수0.0000.1631.0000.8220.661
이동거리(M)0.0000.1510.8221.0000.879
이용시간(분)0.0000.1490.6610.8791.000
2024-03-14T01:26:45.364687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)연령대
대여소번호1.000-0.053-0.034-0.0430.019
이용건수-0.0531.0000.6950.6760.080
이동거리(M)-0.0340.6951.0000.8890.072
이용시간(분)-0.0430.6760.8891.0000.071
연령대0.0190.0800.0720.0711.000

Missing values

2024-03-14T01:26:41.429107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T01:26:41.553229image/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)
9032022-12-0111961196. 서울식물원(문화센터) 건너편정기권<NA>20대157.720.522242.5414
54242022-12-0122442244.교육개발원입구 교차로정기권<NA>40대128.110.21910.06
22772022-12-0114351435. 능산삼거리정기권<NA>20대389.920.974170.0140
17142022-12-01126126. 서강대 후문 옆정기권<NA>20대3120.251.144921.9163
16202022-12-0136853685. 강동리엔파크14단지(1401동 앞)정기권<NA>20대243.700.441863.228
73292022-12-0118221822. 서울 시흥동우체국 앞정기권<NA>기타10.000.02105.776
18552022-12-0146784678. 백련산로 녹번센트레빌정기권<NA>20대124.600.251090.07
87012022-12-0121862186. 낙성대입구삼거리정기권F20대254.350.492111.1921
84072022-12-0124142414. 도곡역 아카데미스위트 앞정기권F20대2107.811.144882.1389
97652022-12-0114421442. 중랑구 중소기업 창업센터정기권F30대4274.822.6011183.8774
대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
83802022-12-0110771077.강동역 1번출구 앞정기권F20대379.860.723102.0836
100272022-12-0135303530. 왕십리자이아파트 후문(삼거리)정기권F30대115.890.16680.04
35142022-12-0144644464. 올림픽공원 북2문정기권<NA>30대189.240.803466.9616
1952022-12-0145574557. 리버뷰신안인스빌2차 후문정기권<NA>~10대3133.221.104732.0312
102282022-12-01771771.목동아파트 703동 앞정기권F30대251.540.642720.8912
4152022-12-0111571157. 강서구청정기권<NA>20대9582.834.9421264.21145
32052022-12-0127042704.홈플러스(강서점)정기권<NA>30대8376.262.9812895.4296
55462022-12-01949949. 연신내역 1번 출구정기권<NA>50대121.160.241027.59
87592022-12-0137823782. 겸재정선미술관정기권F20대236.750.401712.419
6932022-12-0135233523. 건국대학교 과학관(이과대) 앞정기권<NA>20대6208.341.647102.16110