Overview

Dataset statistics

Number of variables11
Number of observations5468
Missing cells5468
Missing cells (%)9.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory496.7 KiB
Average record size in memory93.0 B

Variable types

Categorical3
Numeric4
Text3
Unsupported1

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
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 5468 (100.0%) missing valuesMissing
성별 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-13 16:28:59.740821
Analysis finished2024-03-13 16:29:02.133149
Duration2.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.8 KiB
2023-08-01
5468 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-01
2nd row2023-08-01
3rd row2023-08-01
4th row2023-08-01
5th row2023-08-01

Common Values

ValueCountFrequency (%)
2023-08-01 5468
100.0%

Length

2024-03-14T01:29:02.179806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:29:02.249953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-01 5468
100.0%

대여소번호
Real number (ℝ)

Distinct2443
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2349.8937
Minimum102
Maximum6054
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.2 KiB
2024-03-14T01:29:02.333641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile267
Q11012.75
median2024.5
Q33776
95-th percentile4874.65
Maximum6054
Range5952
Interquartile range (IQR)2763.25

Descriptive statistics

Standard deviation1574.8849
Coefficient of variation (CV)0.67019407
Kurtosis-1.1391063
Mean2349.8937
Median Absolute Deviation (MAD)1356.5
Skewness0.35453032
Sum12849219
Variance2480262.3
MonotonicityNot monotonic
2024-03-14T01:29:02.438292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5052 5
 
0.1%
2717 5
 
0.1%
1986 5
 
0.1%
1180 5
 
0.1%
1172 5
 
0.1%
4809 5
 
0.1%
3754 5
 
0.1%
2715 5
 
0.1%
1738 5
 
0.1%
2719 5
 
0.1%
Other values (2433) 5418
99.1%
ValueCountFrequency (%)
102 2
< 0.1%
103 2
< 0.1%
104 2
< 0.1%
105 1
 
< 0.1%
106 1
 
< 0.1%
107 1
 
< 0.1%
108 3
0.1%
109 2
< 0.1%
111 2
< 0.1%
112 2
< 0.1%
ValueCountFrequency (%)
6054 2
< 0.1%
6053 2
< 0.1%
5871 1
 
< 0.1%
5870 1
 
< 0.1%
5869 2
< 0.1%
5868 2
< 0.1%
5867 2
< 0.1%
5866 3
0.1%
5865 2
< 0.1%
5864 2
< 0.1%

대여소
Text

Distinct2443
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Memory size42.8 KiB
2024-03-14T01:29:02.657024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length32
Mean length15.550841
Min length7

Characters and Unicode

Total characters85032
Distinct characters569
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

Unique721 ?
Unique (%)13.2%

Sample

1st row746. 목동2단지 상가
2nd row747. 목동3단지 상가
3rd row748. 목동운동장
4th row1029. 성내어울터
5th row1044. 굽은다리역
ValueCountFrequency (%)
앞 1456
 
9.2%
출구 247
 
1.6%
옆 182
 
1.1%
1번출구 166
 
1.0%
사거리 142
 
0.9%
교차로 135
 
0.9%
입구 111
 
0.7%
3번출구 111
 
0.7%
2번출구 96
 
0.6%
뒤 87
 
0.5%
Other values (4885) 13141
82.8%
2024-03-14T01:29:03.026680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10513
 
12.4%
. 5477
 
6.4%
1 4067
 
4.8%
2 3091
 
3.6%
4 2756
 
3.2%
3 2719
 
3.2%
5 2207
 
2.6%
0 1962
 
2.3%
6 1931
 
2.3%
7 1865
 
2.2%
Other values (559) 48444
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43699
51.4%
Decimal Number 23607
27.8%
Space Separator 10513
 
12.4%
Other Punctuation 5554
 
6.5%
Uppercase Letter 709
 
0.8%
Open Punctuation 401
 
0.5%
Close Punctuation 401
 
0.5%
Lowercase Letter 103
 
0.1%
Dash Punctuation 30
 
< 0.1%
Math Symbol 6
 
< 0.1%
Other values (2) 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1737
 
4.0%
앞 1674
 
3.8%
역 1352
 
3.1%
동 1205
 
2.8%
번 1193
 
2.7%
출 1167
 
2.7%
파 849
 
1.9%
교 842
 
1.9%
아 821
 
1.9%
트 786
 
1.8%
Other values (498) 32073
73.4%
Uppercase Letter
ValueCountFrequency (%)
S 74
10.4%
T 69
9.7%
K 69
9.7%
A 64
9.0%
C 62
 
8.7%
B 59
 
8.3%
G 46
 
6.5%
D 44
 
6.2%
I 34
 
4.8%
M 33
 
4.7%
Other values (14) 155
21.9%
Lowercase Letter
ValueCountFrequency (%)
e 35
34.0%
k 16
15.5%
s 14
 
13.6%
n 8
 
7.8%
t 7
 
6.8%
l 4
 
3.9%
y 4
 
3.9%
v 3
 
2.9%
g 3
 
2.9%
a 3
 
2.9%
Other values (3) 6
 
5.8%
Decimal Number
ValueCountFrequency (%)
1 4067
17.2%
2 3091
13.1%
4 2756
11.7%
3 2719
11.5%
5 2207
9.3%
0 1962
8.3%
6 1931
8.2%
7 1865
7.9%
8 1643
7.0%
9 1366
 
5.8%
Other Punctuation
ValueCountFrequency (%)
. 5477
98.6%
, 52
 
0.9%
& 15
 
0.3%
? 5
 
0.1%
· 5
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 3
50.0%
+ 3
50.0%
Other Number
ValueCountFrequency (%)
② 3
60.0%
① 2
40.0%
Space Separator
ValueCountFrequency (%)
10513
100.0%
Open Punctuation
ValueCountFrequency (%)
( 401
100.0%
Close Punctuation
ValueCountFrequency (%)
) 401
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43699
51.4%
Common 40521
47.7%
Latin 812
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1737
 
4.0%
앞 1674
 
3.8%
역 1352
 
3.1%
동 1205
 
2.8%
번 1193
 
2.7%
출 1167
 
2.7%
파 849
 
1.9%
교 842
 
1.9%
아 821
 
1.9%
트 786
 
1.8%
Other values (498) 32073
73.4%
Latin
ValueCountFrequency (%)
S 74
 
9.1%
T 69
 
8.5%
K 69
 
8.5%
A 64
 
7.9%
C 62
 
7.6%
B 59
 
7.3%
G 46
 
5.7%
D 44
 
5.4%
e 35
 
4.3%
I 34
 
4.2%
Other values (27) 256
31.5%
Common
ValueCountFrequency (%)
10513
25.9%
. 5477
13.5%
1 4067
 
10.0%
2 3091
 
7.6%
4 2756
 
6.8%
3 2719
 
6.7%
5 2207
 
5.4%
0 1962
 
4.8%
6 1931
 
4.8%
7 1865
 
4.6%
Other values (14) 3933
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43699
51.4%
ASCII 41323
48.6%
None 5
 
< 0.1%
Enclosed Alphanum 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10513
25.4%
. 5477
13.3%
1 4067
 
9.8%
2 3091
 
7.5%
4 2756
 
6.7%
3 2719
 
6.6%
5 2207
 
5.3%
0 1962
 
4.7%
6 1931
 
4.7%
7 1865
 
4.5%
Other values (48) 4735
11.5%
Hangul
ValueCountFrequency (%)
구 1737
 
4.0%
앞 1674
 
3.8%
역 1352
 
3.1%
동 1205
 
2.8%
번 1193
 
2.7%
출 1167
 
2.7%
파 849
 
1.9%
교 842
 
1.9%
아 821
 
1.9%
트 786
 
1.8%
Other values (498) 32073
73.4%
None
ValueCountFrequency (%)
· 5
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
② 3
60.0%
① 2
40.0%

대여구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.8 KiB
정기권
5468 

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 5468
100.0%

Length

2024-03-14T01:29:03.130443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:29:03.202110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 5468
100.0%

성별
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5468
Missing (%)100.0%
Memory size48.2 KiB

연령대
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.8 KiB
20대
3193 
30대
1964 
~10대
 
311

Length

Max length4
Median length3
Mean length3.0568764
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row~10대
2nd row~10대
3rd row~10대
4th row~10대
5th row~10대

Common Values

ValueCountFrequency (%)
20대 3193
58.4%
30대 1964
35.9%
~10대 311
 
5.7%

Length

2024-03-14T01:29:03.290907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:29:03.394427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 3193
58.4%
30대 1964
35.9%
10대 311
 
5.7%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4091075
Minimum1
Maximum58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.2 KiB
2024-03-14T01:29:03.485705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile11
Maximum58
Range57
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.8804106
Coefficient of variation (CV)1.1382482
Kurtosis26.097197
Mean3.4091075
Median Absolute Deviation (MAD)1
Skewness3.7103703
Sum18641
Variance15.057587
MonotonicityNot monotonic
2024-03-14T01:29:03.579886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1 2180
39.9%
2 1040
19.0%
3 611
 
11.2%
4 409
 
7.5%
5 272
 
5.0%
6 210
 
3.8%
7 157
 
2.9%
8 112
 
2.0%
9 100
 
1.8%
10 75
 
1.4%
Other values (24) 302
 
5.5%
ValueCountFrequency (%)
1 2180
39.9%
2 1040
19.0%
3 611
 
11.2%
4 409
 
7.5%
5 272
 
5.0%
6 210
 
3.8%
7 157
 
2.9%
8 112
 
2.0%
9 100
 
1.8%
10 75
 
1.4%
ValueCountFrequency (%)
58 2
< 0.1%
45 1
 
< 0.1%
40 1
 
< 0.1%
37 1
 
< 0.1%
35 1
 
< 0.1%
32 1
 
< 0.1%
29 2
< 0.1%
28 3
0.1%
26 4
0.1%
25 4
0.1%

운동량
Text

Distinct4783
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size42.8 KiB
2024-03-14T01:29:03.864242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.4100219
Min length2

Characters and Unicode

Total characters29582
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

Unique4228 ?
Unique (%)77.3%

Sample

1st row14.16
2nd row88.10
3rd row30.59
4th row45.58
5th row77.28
ValueCountFrequency (%)
0.00 39
 
0.7%
n 7
 
0.1%
12.47 5
 
0.1%
34.75 5
 
0.1%
18.73 4
 
0.1%
195.66 4
 
0.1%
17.25 4
 
0.1%
140.35 4
 
0.1%
18.30 4
 
0.1%
21.11 4
 
0.1%
Other values (4773) 5388
98.5%
2024-03-14T01:29:04.258317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 5461
18.5%
1 3564
12.0%
2 2893
9.8%
3 2586
8.7%
4 2510
8.5%
5 2252
7.6%
6 2173
 
7.3%
7 2132
 
7.2%
0 2054
 
6.9%
8 2041
 
6.9%
Other values (3) 1916
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24107
81.5%
Other Punctuation 5468
 
18.5%
Uppercase Letter 7
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3564
14.8%
2 2893
12.0%
3 2586
10.7%
4 2510
10.4%
5 2252
9.3%
6 2173
9.0%
7 2132
8.8%
0 2054
8.5%
8 2041
8.5%
9 1902
7.9%
Other Punctuation
ValueCountFrequency (%)
. 5461
99.9%
\ 7
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29575
> 99.9%
Latin 7
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 5461
18.5%
1 3564
12.1%
2 2893
9.8%
3 2586
8.7%
4 2510
8.5%
5 2252
7.6%
6 2173
 
7.3%
7 2132
 
7.2%
0 2054
 
6.9%
8 2041
 
6.9%
Other values (2) 1909
 
6.5%
Latin
ValueCountFrequency (%)
N 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29582
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 5461
18.5%
1 3564
12.0%
2 2893
9.8%
3 2586
8.7%
4 2510
8.5%
5 2252
7.6%
6 2173
 
7.3%
7 2132
 
7.2%
0 2054
 
6.9%
8 2041
 
6.9%
Other values (3) 1916
 
6.5%

탄소량
Text

Distinct636
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size42.8 KiB
2024-03-14T01:29:04.619249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.0007315
Min length2

Characters and Unicode

Total characters21876
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

Unique172 ?
Unique (%)3.1%

Sample

1st row0.15
2nd row0.72
3rd row0.39
4th row0.48
5th row0.63
ValueCountFrequency (%)
0.26 69
 
1.3%
0.19 67
 
1.2%
0.20 62
 
1.1%
0.23 62
 
1.1%
0.22 58
 
1.1%
0.27 56
 
1.0%
0.31 56
 
1.0%
0.34 55
 
1.0%
0.17 55
 
1.0%
0.16 54
 
1.0%
Other values (626) 4874
89.1%
2024-03-14T01:29:05.049217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 5461
25.0%
0 4252
19.4%
1 2485
11.4%
2 1869
 
8.5%
3 1537
 
7.0%
4 1265
 
5.8%
5 1116
 
5.1%
6 1071
 
4.9%
7 1002
 
4.6%
8 919
 
4.2%
Other values (3) 899
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16401
75.0%
Other Punctuation 5468
 
25.0%
Uppercase Letter 7
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4252
25.9%
1 2485
15.2%
2 1869
11.4%
3 1537
 
9.4%
4 1265
 
7.7%
5 1116
 
6.8%
6 1071
 
6.5%
7 1002
 
6.1%
8 919
 
5.6%
9 885
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 5461
99.9%
\ 7
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21869
> 99.9%
Latin 7
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 5461
25.0%
0 4252
19.4%
1 2485
11.4%
2 1869
 
8.5%
3 1537
 
7.0%
4 1265
 
5.8%
5 1116
 
5.1%
6 1071
 
4.9%
7 1002
 
4.6%
8 919
 
4.2%
Other values (2) 892
 
4.1%
Latin
ValueCountFrequency (%)
N 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21876
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 5461
25.0%
0 4252
19.4%
1 2485
11.4%
2 1869
 
8.5%
3 1537
 
7.0%
4 1265
 
5.8%
5 1116
 
5.1%
6 1071
 
4.9%
7 1002
 
4.6%
8 919
 
4.2%
Other values (3) 899
 
4.1%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION 

Distinct4627
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5711.8614
Minimum0
Maximum72071.07
Zeros39
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size48.2 KiB
2024-03-14T01:29:05.164150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile526.8965
Q11401.9075
median3188.47
Q37272.5925
95-th percentile19523.437
Maximum72071.07
Range72071.07
Interquartile range (IQR)5870.685

Descriptive statistics

Standard deviation6946.1983
Coefficient of variation (CV)1.2161006
Kurtosis13.129163
Mean5711.8614
Median Absolute Deviation (MAD)2178.47
Skewness2.9373152
Sum31232458
Variance48249670
MonotonicityNot monotonic
2024-03-14T01:29:05.271622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 39
 
0.7%
1020.0 9
 
0.2%
1110.0 9
 
0.2%
600.0 9
 
0.2%
790.0 9
 
0.2%
860.0 9
 
0.2%
1640.0 9
 
0.2%
1010.0 9
 
0.2%
880.0 9
 
0.2%
2290.0 8
 
0.1%
Other values (4617) 5349
97.8%
ValueCountFrequency (%)
0.0 39
0.7%
0.48 1
 
< 0.1%
10.0 1
 
< 0.1%
17.38 1
 
< 0.1%
28.3 1
 
< 0.1%
34.94 1
 
< 0.1%
88.14 1
 
< 0.1%
88.19 1
 
< 0.1%
88.2 1
 
< 0.1%
88.23 1
 
< 0.1%
ValueCountFrequency (%)
72071.07 1
< 0.1%
71909.36 1
< 0.1%
65701.69 1
< 0.1%
62605.28 1
< 0.1%
61407.11 1
< 0.1%
56173.37 1
< 0.1%
54995.75 1
< 0.1%
52548.55 1
< 0.1%
52461.53 1
< 0.1%
52314.26 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct286
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.527615
Minimum0
Maximum997
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size48.2 KiB
2024-03-14T01:29:05.386497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q110
median23
Q355
95-th percentile150
Maximum997
Range997
Interquartile range (IQR)45

Descriptive statistics

Standard deviation57.715592
Coefficient of variation (CV)1.3259535
Kurtosis35.801973
Mean43.527615
Median Absolute Deviation (MAD)16
Skewness4.2259788
Sum238009
Variance3331.0896
MonotonicityNot monotonic
2024-03-14T01:29:05.504870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 195
 
3.6%
5 186
 
3.4%
8 179
 
3.3%
3 171
 
3.1%
7 170
 
3.1%
6 164
 
3.0%
9 158
 
2.9%
10 148
 
2.7%
12 133
 
2.4%
11 117
 
2.1%
Other values (276) 3847
70.4%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 38
 
0.7%
2 75
 
1.4%
3 171
3.1%
4 195
3.6%
5 186
3.4%
6 164
3.0%
7 170
3.1%
8 179
3.3%
9 158
2.9%
ValueCountFrequency (%)
997 1
< 0.1%
880 1
< 0.1%
665 1
< 0.1%
647 1
< 0.1%
552 1
< 0.1%
532 1
< 0.1%
531 1
< 0.1%
502 1
< 0.1%
487 1
< 0.1%
447 1
< 0.1%

Interactions

2024-03-14T01:29:01.642004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:29:00.376388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:29:00.697368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:29:01.026481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:29:01.712715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:29:00.453397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:29:00.772521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:29:01.152243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:29:01.783866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:29:00.544924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:29:00.852483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:29:01.273670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:29:01.857072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:29:00.620228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:29:00.935058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:29:01.572528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T01:29:05.595346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호연령대이용건수이동거리(M)이용시간(분)
대여소번호1.0000.1430.1020.0770.063
연령대0.1431.0000.2540.2100.212
이용건수0.1020.2541.0000.7980.854
이동거리(M)0.0770.2100.7981.0000.760
이용시간(분)0.0630.2120.8540.7601.000
2024-03-14T01:29:05.685743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)연령대
대여소번호1.000-0.056-0.045-0.0540.086
이용건수-0.0561.0000.7990.7930.115
이동거리(M)-0.0450.7991.0000.9210.128
이용시간(분)-0.0540.7930.9211.0000.095
연령대0.0860.1150.1280.0951.000

Missing values

2024-03-14T01:29:01.951635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T01:29:02.075098image/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)
02023-08-01746746. 목동2단지 상가정기권<NA>~10대114.160.15650.03
12023-08-01747747. 목동3단지 상가정기권<NA>~10대188.100.723090.019
22023-08-01748748. 목동운동장정기권<NA>~10대230.590.391679.168
32023-08-0110291029. 성내어울터정기권<NA>~10대245.580.482106.1324
42023-08-0110441044. 굽은다리역정기권<NA>~10대177.280.632710.2824
52023-08-0111501150. 송정역 1번출구정기권<NA>~10대119.740.241017.5113
62023-08-0111511151. 마곡역1번출구정기권<NA>~10대110.090.12520.03
72023-08-0111521152. 마곡역교차로정기권<NA>~10대340.000.361562.5917
82023-08-0111531153. 발산역 1번, 9번 인근 대여소정기권<NA>~10대168.640.582512.1645
92023-08-0111551155. 기쁜우리복지관정기권<NA>~10대141.780.331406.8714
대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
54582023-08-0140944094.도봉여성센터정기권<NA>30대128.540.251060.07
54592023-08-0141334133.래미안허브리츠아파트 앞정기권<NA>30대19.200.06280.01
54602023-08-0138223822.신림4,5동교정기권<NA>30대1105.210.954087.620
54612023-08-01130130. 신촌역(2호선) 7번출구 앞정기권<NA>30대129.680.271153.07
54622023-08-01130130. 신촌역(2호선) 7번출구 앞정기권<NA>30대254.930.592560.016
54632023-08-01713713. 양서중학교 옆정기권<NA>30대194.790.773324.5114
54642023-08-01713713. 양서중학교 옆정기권<NA>30대2217.111.968434.7940
54652023-08-0158645864.장훈고 앞정기권<NA>30대149.040.461965.5712
54662023-08-0142754275.농협생명본사빌딩 서관정기권<NA>30대141.230.371601.7411
54672023-08-0144234423.현대백화점 미아점정기권<NA>30대137.250.341447.2414