Overview

Dataset statistics

Number of variables11
Number of observations4813
Missing cells4813
Missing cells (%)9.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory437.2 KiB
Average record size in memory93.0 B

Variable types

DateTime1
Numeric4
Text3
Categorical2
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 4813 (100.0%) missing valuesMissing
성별 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-13 16:27:47.859802
Analysis finished2024-03-13 16:27:50.032191
Duration2.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.7 KiB
Minimum2023-06-01 00:00:00
Maximum2023-06-01 00:00:00
2024-03-14T01:27:50.069906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:50.144085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

대여소번호
Real number (ℝ)

Distinct2481
Distinct (%)51.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2087.7656
Minimum102
Maximum6054
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2024-03-14T01:27:50.239332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile271.6
Q1902
median1730
Q33129
95-th percentile4782.2
Maximum6054
Range5952
Interquartile range (IQR)2227

Descriptive statistics

Standard deviation1452.1865
Coefficient of variation (CV)0.6955697
Kurtosis-0.70308707
Mean2087.7656
Median Absolute Deviation (MAD)991
Skewness0.60584796
Sum10048416
Variance2108845.7
MonotonicityNot monotonic
2024-03-14T01:27:50.580685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2735 5
 
0.1%
1343 5
 
0.1%
2921 5
 
0.1%
1961 5
 
0.1%
1158 5
 
0.1%
1163 5
 
0.1%
1665 5
 
0.1%
1668 5
 
0.1%
1669 5
 
0.1%
646 5
 
0.1%
Other values (2471) 4763
99.0%
ValueCountFrequency (%)
102 1
 
< 0.1%
103 1
 
< 0.1%
104 2
< 0.1%
105 1
 
< 0.1%
106 2
< 0.1%
107 1
 
< 0.1%
108 3
0.1%
109 3
0.1%
111 2
< 0.1%
112 2
< 0.1%
ValueCountFrequency (%)
6054 2
< 0.1%
6053 1
< 0.1%
5867 2
< 0.1%
5866 1
< 0.1%
5865 2
< 0.1%
5864 1
< 0.1%
5862 2
< 0.1%
5861 1
< 0.1%
5860 1
< 0.1%
5859 1
< 0.1%

대여소
Text

Distinct2481
Distinct (%)51.5%
Missing0
Missing (%)0.0%
Memory size37.7 KiB
2024-03-14T01:27:50.840964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length31
Mean length15.534178
Min length7

Characters and Unicode

Total characters74766
Distinct characters572
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

Unique995 ?
Unique (%)20.7%

Sample

1st row733. 신정이펜하우스314동
2nd row735. 영도초등학교
3rd row736. 오솔길공원
4th row736. 오솔길공원
5th row744. 신목동역 2번 출구
ValueCountFrequency (%)
앞 1231
 
8.8%
출구 224
 
1.6%
옆 173
 
1.2%
1번출구 160
 
1.1%
교차로 128
 
0.9%
입구 107
 
0.8%
사거리 107
 
0.8%
뒤 97
 
0.7%
3번출구 95
 
0.7%
2번출구 89
 
0.6%
Other values (4955) 11535
82.7%
2024-03-14T01:27:51.206695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9230
 
12.3%
. 4821
 
6.4%
1 3835
 
5.1%
2 2798
 
3.7%
3 2384
 
3.2%
4 2228
 
3.0%
5 1818
 
2.4%
6 1706
 
2.3%
0 1645
 
2.2%
구 1584
 
2.1%
Other values (562) 42717
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38519
51.5%
Decimal Number 20603
27.6%
Space Separator 9230
 
12.3%
Other Punctuation 4885
 
6.5%
Uppercase Letter 616
 
0.8%
Open Punctuation 392
 
0.5%
Close Punctuation 392
 
0.5%
Lowercase Letter 84
 
0.1%
Dash Punctuation 30
 
< 0.1%
Math Symbol 8
 
< 0.1%
Other values (3) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1584
 
4.1%
앞 1423
 
3.7%
역 1223
 
3.2%
번 1087
 
2.8%
출 1058
 
2.7%
동 1050
 
2.7%
교 789
 
2.0%
파 719
 
1.9%
아 675
 
1.8%
트 652
 
1.7%
Other values (501) 28259
73.4%
Uppercase Letter
ValueCountFrequency (%)
S 76
12.3%
K 63
10.2%
C 55
 
8.9%
T 51
 
8.3%
A 51
 
8.3%
D 41
 
6.7%
G 38
 
6.2%
B 38
 
6.2%
P 30
 
4.9%
I 30
 
4.9%
Other values (13) 143
23.2%
Lowercase Letter
ValueCountFrequency (%)
e 34
40.5%
s 11
 
13.1%
k 10
 
11.9%
n 8
 
9.5%
y 4
 
4.8%
l 4
 
4.8%
v 3
 
3.6%
t 2
 
2.4%
f 2
 
2.4%
r 2
 
2.4%
Other values (3) 4
 
4.8%
Decimal Number
ValueCountFrequency (%)
1 3835
18.6%
2 2798
13.6%
3 2384
11.6%
4 2228
10.8%
5 1818
8.8%
6 1706
8.3%
0 1645
8.0%
7 1580
7.7%
8 1398
 
6.8%
9 1211
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 4821
98.7%
, 44
 
0.9%
& 13
 
0.3%
? 6
 
0.1%
· 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 6
75.0%
+ 2
 
25.0%
Other Number
ValueCountFrequency (%)
① 1
50.0%
② 1
50.0%
Space Separator
ValueCountFrequency (%)
9230
100.0%
Open Punctuation
ValueCountFrequency (%)
( 392
100.0%
Close Punctuation
ValueCountFrequency (%)
) 392
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38523
51.5%
Common 35543
47.5%
Latin 700
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1584
 
4.1%
앞 1423
 
3.7%
역 1223
 
3.2%
번 1087
 
2.8%
출 1058
 
2.7%
동 1050
 
2.7%
교 789
 
2.0%
파 719
 
1.9%
아 675
 
1.8%
트 652
 
1.7%
Other values (502) 28263
73.4%
Latin
ValueCountFrequency (%)
S 76
 
10.9%
K 63
 
9.0%
C 55
 
7.9%
T 51
 
7.3%
A 51
 
7.3%
D 41
 
5.9%
G 38
 
5.4%
B 38
 
5.4%
e 34
 
4.9%
P 30
 
4.3%
Other values (26) 223
31.9%
Common
ValueCountFrequency (%)
9230
26.0%
. 4821
13.6%
1 3835
10.8%
2 2798
 
7.9%
3 2384
 
6.7%
4 2228
 
6.3%
5 1818
 
5.1%
6 1706
 
4.8%
0 1645
 
4.6%
7 1580
 
4.4%
Other values (14) 3498
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38519
51.5%
ASCII 36240
48.5%
None 5
 
< 0.1%
Enclosed Alphanum 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9230
25.5%
. 4821
13.3%
1 3835
10.6%
2 2798
 
7.7%
3 2384
 
6.6%
4 2228
 
6.1%
5 1818
 
5.0%
6 1706
 
4.7%
0 1645
 
4.5%
7 1580
 
4.4%
Other values (47) 4195
11.6%
Hangul
ValueCountFrequency (%)
구 1584
 
4.1%
앞 1423
 
3.7%
역 1223
 
3.2%
번 1087
 
2.8%
출 1058
 
2.7%
동 1050
 
2.7%
교 789
 
2.0%
파 719
 
1.9%
아 675
 
1.8%
트 652
 
1.7%
Other values (501) 28259
73.4%
None
ValueCountFrequency (%)
㈜ 4
80.0%
· 1
 
20.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 1
50.0%
② 1
50.0%

대여구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.7 KiB
정기권
4813 

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 4813
100.0%

Length

2024-03-14T01:27:51.313808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:27:51.388323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 4813
100.0%

성별
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4813
Missing (%)100.0%
Memory size42.4 KiB

연령대
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.7 KiB
20대
3259 
30대
1189 
~10대
365 

Length

Max length4
Median length3
Mean length3.0758363
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 3259
67.7%
30대 1189
 
24.7%
~10대 365
 
7.6%

Length

2024-03-14T01:27:51.476237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:27:51.563411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 3259
67.7%
30대 1189
 
24.7%
10대 365
 
7.6%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3299397
Minimum1
Maximum68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2024-03-14T01:27:51.657179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile14
Maximum68
Range67
Interquartile range (IQR)4

Descriptive statistics

Standard deviation5.0819153
Coefficient of variation (CV)1.1736688
Kurtosis16.983604
Mean4.3299397
Median Absolute Deviation (MAD)1
Skewness3.1867372
Sum20840
Variance25.825864
MonotonicityNot monotonic
2024-03-14T01:27:51.792387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
1 1670
34.7%
2 799
16.6%
3 504
 
10.5%
4 378
 
7.9%
5 270
 
5.6%
6 228
 
4.7%
7 160
 
3.3%
8 130
 
2.7%
9 119
 
2.5%
10 94
 
2.0%
Other values (32) 461
 
9.6%
ValueCountFrequency (%)
1 1670
34.7%
2 799
16.6%
3 504
 
10.5%
4 378
 
7.9%
5 270
 
5.6%
6 228
 
4.7%
7 160
 
3.3%
8 130
 
2.7%
9 119
 
2.5%
10 94
 
2.0%
ValueCountFrequency (%)
68 1
< 0.1%
58 1
< 0.1%
45 1
< 0.1%
44 2
< 0.1%
42 1
< 0.1%
39 2
< 0.1%
37 1
< 0.1%
36 2
< 0.1%
35 2
< 0.1%
34 2
< 0.1%

운동량
Text

Distinct4412
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size37.7 KiB
2024-03-14T01:27:52.080412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.5252441
Min length2

Characters and Unicode

Total characters26593
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

Unique4112 ?
Unique (%)85.4%

Sample

1st row27.32
2nd row24.09
3rd row25.20
4th row14.45
5th row11.10
ValueCountFrequency (%)
0.00 49
 
1.0%
n 9
 
0.2%
24.71 7
 
0.1%
21.95 5
 
0.1%
65.06 4
 
0.1%
20.00 4
 
0.1%
15.44 4
 
0.1%
53.22 4
 
0.1%
12.10 4
 
0.1%
13.64 3
 
0.1%
Other values (4402) 4720
98.1%
2024-03-14T01:27:52.460647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4804
18.1%
1 3078
11.6%
2 2679
10.1%
3 2325
8.7%
4 2169
8.2%
5 2048
7.7%
0 1969
7.4%
6 1951
7.3%
7 1901
 
7.1%
9 1829
 
6.9%
Other values (3) 1840
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21771
81.9%
Other Punctuation 4813
 
18.1%
Uppercase Letter 9
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3078
14.1%
2 2679
12.3%
3 2325
10.7%
4 2169
10.0%
5 2048
9.4%
0 1969
9.0%
6 1951
9.0%
7 1901
8.7%
9 1829
8.4%
8 1822
8.4%
Other Punctuation
ValueCountFrequency (%)
. 4804
99.8%
\ 9
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26584
> 99.9%
Latin 9
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4804
18.1%
1 3078
11.6%
2 2679
10.1%
3 2325
8.7%
4 2169
8.2%
5 2048
7.7%
0 1969
7.4%
6 1951
7.3%
7 1901
 
7.2%
9 1829
 
6.9%
Other values (2) 1831
 
6.9%
Latin
ValueCountFrequency (%)
N 9
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26593
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4804
18.1%
1 3078
11.6%
2 2679
10.1%
3 2325
8.7%
4 2169
8.2%
5 2048
7.7%
0 1969
7.4%
6 1951
7.3%
7 1901
 
7.1%
9 1829
 
6.9%
Other values (3) 1840
 
6.9%

탄소량
Text

Distinct794
Distinct (%)16.5%
Missing0
Missing (%)0.0%
Memory size37.7 KiB
2024-03-14T01:27:52.797078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.0097652
Min length2

Characters and Unicode

Total characters19299
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

Unique261 ?
Unique (%)5.4%

Sample

1st row0.25
2nd row0.29
3rd row0.23
4th row0.15
5th row0.14
ValueCountFrequency (%)
0.00 51
 
1.1%
0.29 44
 
0.9%
0.28 44
 
0.9%
0.18 43
 
0.9%
0.23 42
 
0.9%
0.16 41
 
0.9%
0.19 40
 
0.8%
0.52 40
 
0.8%
0.22 40
 
0.8%
0.32 39
 
0.8%
Other values (784) 4389
91.2%
2024-03-14T01:27:53.263055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4804
24.9%
0 3264
16.9%
1 2159
11.2%
2 1768
 
9.2%
3 1394
 
7.2%
4 1172
 
6.1%
5 1061
 
5.5%
6 1001
 
5.2%
8 933
 
4.8%
7 919
 
4.8%
Other values (3) 824
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14477
75.0%
Other Punctuation 4813
 
24.9%
Uppercase Letter 9
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3264
22.5%
1 2159
14.9%
2 1768
12.2%
3 1394
9.6%
4 1172
 
8.1%
5 1061
 
7.3%
6 1001
 
6.9%
8 933
 
6.4%
7 919
 
6.3%
9 806
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 4804
99.8%
\ 9
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19290
> 99.9%
Latin 9
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4804
24.9%
0 3264
16.9%
1 2159
11.2%
2 1768
 
9.2%
3 1394
 
7.2%
4 1172
 
6.1%
5 1061
 
5.5%
6 1001
 
5.2%
8 933
 
4.8%
7 919
 
4.8%
Other values (2) 815
 
4.2%
Latin
ValueCountFrequency (%)
N 9
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19299
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4804
24.9%
0 3264
16.9%
1 2159
11.2%
2 1768
 
9.2%
3 1394
 
7.2%
4 1172
 
6.1%
5 1061
 
5.5%
6 1001
 
5.2%
8 933
 
4.8%
7 919
 
4.8%
Other values (3) 824
 
4.3%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION 

Distinct4271
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8211.2241
Minimum0
Maximum124401.46
Zeros48
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2024-03-14T01:27:53.378205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile584.934
Q11820.72
median4569.46
Q310682.37
95-th percentile28284.188
Maximum124401.46
Range124401.46
Interquartile range (IQR)8861.65

Descriptive statistics

Standard deviation10178.684
Coefficient of variation (CV)1.2396061
Kurtosis14.68211
Mean8211.2241
Median Absolute Deviation (MAD)3339.46
Skewness3.0218952
Sum39520622
Variance1.036056 × 108
MonotonicityNot monotonic
2024-03-14T01:27:53.484454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 48
 
1.0%
510.0 9
 
0.2%
790.0 8
 
0.2%
990.0 8
 
0.2%
1060.0 8
 
0.2%
800.0 7
 
0.1%
680.0 7
 
0.1%
840.0 6
 
0.1%
1260.0 6
 
0.1%
2390.0 6
 
0.1%
Other values (4261) 4700
97.7%
ValueCountFrequency (%)
0.0 48
1.0%
0.13 1
 
< 0.1%
0.2 1
 
< 0.1%
10.0 2
 
< 0.1%
30.0 1
 
< 0.1%
40.0 1
 
< 0.1%
44.36 1
 
< 0.1%
50.0 1
 
< 0.1%
50.45 1
 
< 0.1%
60.0 1
 
< 0.1%
ValueCountFrequency (%)
124401.46 1
< 0.1%
99236.25 1
< 0.1%
94420.89 1
< 0.1%
86756.16 1
< 0.1%
85360.66 1
< 0.1%
84157.6 1
< 0.1%
83714.74 1
< 0.1%
81469.77 1
< 0.1%
76902.43 1
< 0.1%
76885.46 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct355
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.455641
Minimum0
Maximum811
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size42.4 KiB
2024-03-14T01:27:53.591537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q113
median34
Q377
95-th percentile211
Maximum811
Range811
Interquartile range (IQR)64

Descriptive statistics

Standard deviation75.818189
Coefficient of variation (CV)1.2541127
Kurtosis13.373704
Mean60.455641
Median Absolute Deviation (MAD)26
Skewness2.967294
Sum290973
Variance5748.3977
MonotonicityNot monotonic
2024-03-14T01:27:53.704260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 137
 
2.8%
7 131
 
2.7%
5 122
 
2.5%
4 114
 
2.4%
8 105
 
2.2%
3 102
 
2.1%
9 96
 
2.0%
11 95
 
2.0%
10 93
 
1.9%
12 91
 
1.9%
Other values (345) 3727
77.4%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 34
 
0.7%
2 59
1.2%
3 102
2.1%
4 114
2.4%
5 122
2.5%
6 137
2.8%
7 131
2.7%
8 105
2.2%
9 96
2.0%
ValueCountFrequency (%)
811 1
< 0.1%
737 1
< 0.1%
692 1
< 0.1%
668 1
< 0.1%
664 1
< 0.1%
605 1
< 0.1%
602 1
< 0.1%
584 1
< 0.1%
576 1
< 0.1%
571 1
< 0.1%

Interactions

2024-03-14T01:27:49.492234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:48.527238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:48.834406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:49.164321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:49.575599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:48.600615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:48.910127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:49.237166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:49.660189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:48.679699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:48.993231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:49.320147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:49.745858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:48.753779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:49.072061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:49.405127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T01:27:53.785177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호연령대이용건수이동거리(M)이용시간(분)
대여소번호1.0000.3220.0660.0390.074
연령대0.3221.0000.2740.2760.219
이용건수0.0660.2741.0000.8970.778
이동거리(M)0.0390.2760.8971.0000.851
이용시간(분)0.0740.2190.7780.8511.000
2024-03-14T01:27:53.872869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)연령대
대여소번호1.000-0.032-0.041-0.0360.204
이용건수-0.0321.0000.8470.8410.125
이동거리(M)-0.0410.8471.0000.9360.126
이용시간(분)-0.0360.8410.9361.0000.133
연령대0.2040.1250.1260.1331.000

Missing values

2024-03-14T01:27:49.856356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T01:27:49.979541image/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)
02023-06-01733733. 신정이펜하우스314동정기권<NA>~10대127.320.251095.16
12023-06-01735735. 영도초등학교정기권<NA>~10대124.090.291267.597
22023-06-01736736. 오솔길공원정기권<NA>~10대125.200.231010.07
32023-06-01736736. 오솔길공원정기권<NA>~10대114.450.15663.475
42023-06-01744744. 신목동역 2번 출구정기권<NA>~10대111.100.14623.155
52023-06-01948948. 디지털미디어 시티역 4번출구(DMC역)정기권<NA>~10대19.140.11461.483
62023-06-0110361036. 고덕동 주양쇼핑정기권<NA>~10대138.620.331434.0613
72023-06-01509509. 이마트 버스정류소 옆정기권<NA>~10대13.650.03141.916
82023-06-0110441044. 굽은다리역정기권<NA>~10대146.020.411787.9521
92023-06-0111501150. 송정역 1번출구정기권<NA>~10대144.790.401740.09
대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
48032023-06-01993993.은평뉴타운 은뜨락아파트앞정기권<NA>30대3130.821.014330.3839
48042023-06-01996996.응암역2번출구 국민은행 앞정기권<NA>30대4130.721.185137.7833
48052023-06-01996996.응암역2번출구 국민은행 앞정기권<NA>30대110.280.13576.613
48062023-06-01665665.이문동 쌍용아파트 정문정기권<NA>30대138.720.451955.6314
48072023-06-01667667.청량차도 육교 밑정기권<NA>30대116.630.14600.02
48082023-06-01668668.서울축산농협(장안지점)정기권<NA>30대12733.436.1026307.23143
48092023-06-01668668.서울축산농협(장안지점)정기권<NA>30대174.760.783371.2821
48102023-06-01669669.청계한신휴플러스앞 삼거리정기권<NA>30대3140.811.345764.2141
48112023-06-01170170. DMC파크뷰자이아파트 302동 앞정기권<NA>30대163.540.572468.5815
48122023-06-01670670.삼육서울병원 버스정류장정기권<NA>30대5255.452.3210003.2583