Overview

Dataset statistics

Number of variables11
Number of observations6223
Missing cells6223
Missing cells (%)9.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory565.3 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/A/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 6223 (100.0%) missing valuesMissing
성별 is an unsupported type, check if it needs cleaning or further analysisUnsupported
이동거리(M) has 500 (8.0%) zerosZeros

Reproduction

Analysis started2024-05-18 04:55:55.754403
Analysis finished2024-05-18 04:56:05.547269
Duration9.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.7 KiB
2021-09-01
6223 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-09-01
2nd row2021-09-01
3rd row2021-09-01
4th row2021-09-01
5th row2021-09-01

Common Values

ValueCountFrequency (%)
2021-09-01 6223
100.0%

Length

2024-05-18T13:56:05.756831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:56:06.217340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-09-01 6223
100.0%

대여소번호
Real number (ℝ)

Distinct2327
Distinct (%)37.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1916.0071
Minimum102
Maximum5063
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.8 KiB
2024-05-18T13:56:06.629735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile235
Q1778
median1620
Q32735
95-th percentile4552.9
Maximum5063
Range4961
Interquartile range (IQR)1957

Descriptive statistics

Standard deviation1349.6185
Coefficient of variation (CV)0.70439119
Kurtosis-0.75066194
Mean1916.0071
Median Absolute Deviation (MAD)963
Skewness0.61629659
Sum11923312
Variance1821470.1
MonotonicityNot monotonic
2024-05-18T13:56:07.260834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
263 7
 
0.1%
708 6
 
0.1%
2715 6
 
0.1%
996 6
 
0.1%
247 6
 
0.1%
2622 6
 
0.1%
646 6
 
0.1%
2910 6
 
0.1%
3509 6
 
0.1%
3010 6
 
0.1%
Other values (2317) 6162
99.0%
ValueCountFrequency (%)
102 3
< 0.1%
103 4
0.1%
104 2
< 0.1%
105 2
< 0.1%
106 2
< 0.1%
107 2
< 0.1%
108 4
0.1%
109 1
 
< 0.1%
111 3
< 0.1%
112 2
< 0.1%
ValueCountFrequency (%)
5063 4
0.1%
5059 2
< 0.1%
4902 1
 
< 0.1%
4872 4
0.1%
4870 3
< 0.1%
4869 3
< 0.1%
4868 3
< 0.1%
4867 2
< 0.1%
4865 4
0.1%
4864 4
0.1%

대여소
Text

Distinct2327
Distinct (%)37.4%
Missing0
Missing (%)0.0%
Memory size48.7 KiB
2024-05-18T13:56:07.972771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length31
Mean length15.50458
Min length7

Characters and Unicode

Total characters96485
Distinct characters561
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique359 ?
Unique (%)5.8%

Sample

1st row108. 서교동 사거리
2nd row729. 서부식자재마트 건너편
3rd row731. 서울시 도로환경관리센터
4th row734. 신트리공원 입구
5th row735. 영도초등학교
ValueCountFrequency (%)
앞 1611
 
8.9%
출구 259
 
1.4%
옆 238
 
1.3%
1번출구 187
 
1.0%
사거리 167
 
0.9%
교차로 160
 
0.9%
3번출구 131
 
0.7%
입구 130
 
0.7%
뒤 128
 
0.7%
2번출구 126
 
0.7%
Other values (4617) 14979
82.7%
2024-05-18T13:56:09.423142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12003
 
12.4%
. 6239
 
6.5%
1 5008
 
5.2%
2 3717
 
3.9%
3 3009
 
3.1%
4 2799
 
2.9%
5 2273
 
2.4%
0 2196
 
2.3%
6 2167
 
2.2%
7 2116
 
2.2%
Other values (551) 54958
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49758
51.6%
Decimal Number 26491
27.5%
Space Separator 12003
 
12.4%
Other Punctuation 6310
 
6.5%
Uppercase Letter 764
 
0.8%
Close Punctuation 498
 
0.5%
Open Punctuation 498
 
0.5%
Lowercase Letter 102
 
0.1%
Dash Punctuation 38
 
< 0.1%
Math Symbol 11
 
< 0.1%
Other values (2) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2016
 
4.1%
앞 1877
 
3.8%
역 1566
 
3.1%
번 1412
 
2.8%
출 1376
 
2.8%
동 1373
 
2.8%
교 1036
 
2.1%
파 899
 
1.8%
리 878
 
1.8%
아 870
 
1.7%
Other values (495) 36455
73.3%
Uppercase Letter
ValueCountFrequency (%)
S 83
10.9%
K 81
10.6%
C 78
10.2%
T 70
9.2%
D 57
 
7.5%
A 52
 
6.8%
M 47
 
6.2%
G 45
 
5.9%
B 43
 
5.6%
P 36
 
4.7%
Other values (13) 172
22.5%
Decimal Number
ValueCountFrequency (%)
1 5008
18.9%
2 3717
14.0%
3 3009
11.4%
4 2799
10.6%
5 2273
8.6%
0 2196
8.3%
6 2167
8.2%
7 2116
8.0%
8 1691
 
6.4%
9 1515
 
5.7%
Lowercase Letter
ValueCountFrequency (%)
e 34
33.3%
k 20
19.6%
s 16
15.7%
n 8
 
7.8%
t 7
 
6.9%
y 4
 
3.9%
l 4
 
3.9%
g 3
 
2.9%
a 3
 
2.9%
v 3
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 6239
98.9%
, 46
 
0.7%
& 17
 
0.3%
? 6
 
0.1%
· 2
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 8
72.7%
+ 3
 
27.3%
Space Separator
ValueCountFrequency (%)
12003
100.0%
Close Punctuation
ValueCountFrequency (%)
) 498
100.0%
Open Punctuation
ValueCountFrequency (%)
( 498
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49762
51.6%
Common 45857
47.5%
Latin 866
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2016
 
4.1%
앞 1877
 
3.8%
역 1566
 
3.1%
번 1412
 
2.8%
출 1376
 
2.8%
동 1373
 
2.8%
교 1036
 
2.1%
파 899
 
1.8%
리 878
 
1.8%
아 870
 
1.7%
Other values (496) 36459
73.3%
Latin
ValueCountFrequency (%)
S 83
 
9.6%
K 81
 
9.4%
C 78
 
9.0%
T 70
 
8.1%
D 57
 
6.6%
A 52
 
6.0%
M 47
 
5.4%
G 45
 
5.2%
B 43
 
5.0%
P 36
 
4.2%
Other values (23) 274
31.6%
Common
ValueCountFrequency (%)
12003
26.2%
. 6239
13.6%
1 5008
10.9%
2 3717
 
8.1%
3 3009
 
6.6%
4 2799
 
6.1%
5 2273
 
5.0%
0 2196
 
4.8%
6 2167
 
4.7%
7 2116
 
4.6%
Other values (12) 4330
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49758
51.6%
ASCII 46721
48.4%
None 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12003
25.7%
. 6239
13.4%
1 5008
10.7%
2 3717
 
8.0%
3 3009
 
6.4%
4 2799
 
6.0%
5 2273
 
4.9%
0 2196
 
4.7%
6 2167
 
4.6%
7 2116
 
4.5%
Other values (44) 5194
11.1%
Hangul
ValueCountFrequency (%)
구 2016
 
4.1%
앞 1877
 
3.8%
역 1566
 
3.1%
번 1412
 
2.8%
출 1376
 
2.8%
동 1373
 
2.8%
교 1036
 
2.1%
파 899
 
1.8%
리 878
 
1.8%
아 870
 
1.7%
Other values (495) 36455
73.3%
None
ValueCountFrequency (%)
㈜ 4
66.7%
· 2
33.3%

대여구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size48.7 KiB
정기권
6223 

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 6223
100.0%

Length

2024-05-18T13:56:10.012487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:56:10.397346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 6223
100.0%

성별
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6223
Missing (%)100.0%
Memory size54.8 KiB

연령대
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size48.7 KiB
20대
2357 
30대
1940 
40대
1195 
~10대
731 

Length

Max length4
Median length3
Mean length3.1174675
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 2357
37.9%
30대 1940
31.2%
40대 1195
19.2%
~10대 731
 
11.7%

Length

2024-05-18T13:56:10.915323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:56:11.360208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 2357
37.9%
30대 1940
31.2%
40대 1195
19.2%
10대 731
 
11.7%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5781777
Minimum1
Maximum53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.8 KiB
2024-05-18T13:56:11.874397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile12
Maximum53
Range52
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.9801766
Coefficient of variation (CV)1.1123474
Kurtosis16.264005
Mean3.5781777
Median Absolute Deviation (MAD)1
Skewness3.1608343
Sum22267
Variance15.841806
MonotonicityNot monotonic
2024-05-18T13:56:12.357772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1 2333
37.5%
2 1184
19.0%
3 708
 
11.4%
4 485
 
7.8%
5 351
 
5.6%
6 253
 
4.1%
7 195
 
3.1%
8 148
 
2.4%
9 96
 
1.5%
10 85
 
1.4%
Other values (25) 385
 
6.2%
ValueCountFrequency (%)
1 2333
37.5%
2 1184
19.0%
3 708
 
11.4%
4 485
 
7.8%
5 351
 
5.6%
6 253
 
4.1%
7 195
 
3.1%
8 148
 
2.4%
9 96
 
1.5%
10 85
 
1.4%
ValueCountFrequency (%)
53 1
 
< 0.1%
48 1
 
< 0.1%
39 1
 
< 0.1%
33 4
0.1%
32 2
< 0.1%
31 2
< 0.1%
29 2
< 0.1%
28 4
0.1%
27 1
 
< 0.1%
26 4
0.1%

운동량
Text

Distinct5172
Distinct (%)83.1%
Missing0
Missing (%)0.0%
Memory size48.7 KiB
2024-05-18T13:56:13.232422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.3671862
Min length2

Characters and Unicode

Total characters33400
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

Unique4692 ?
Unique (%)75.4%

Sample

1st row0.00
2nd row0.00
3rd row160.67
4th row207.35
5th row17.50
ValueCountFrequency (%)
0.00 482
 
7.7%
n 19
 
0.3%
19.96 5
 
0.1%
24.71 5
 
0.1%
30.89 5
 
0.1%
36.04 4
 
0.1%
32.43 4
 
0.1%
31.40 4
 
0.1%
61.59 4
 
0.1%
17.50 4
 
0.1%
Other values (5162) 5687
91.4%
2024-05-18T13:56:14.487406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6204
18.6%
1 3652
10.9%
0 3610
10.8%
2 3150
9.4%
3 2777
8.3%
4 2541
7.6%
5 2413
 
7.2%
6 2363
 
7.1%
8 2276
 
6.8%
7 2264
 
6.8%
Other values (3) 2150
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27158
81.3%
Other Punctuation 6223
 
18.6%
Uppercase Letter 19
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3652
13.4%
0 3610
13.3%
2 3150
11.6%
3 2777
10.2%
4 2541
9.4%
5 2413
8.9%
6 2363
8.7%
8 2276
8.4%
7 2264
8.3%
9 2112
7.8%
Other Punctuation
ValueCountFrequency (%)
. 6204
99.7%
\ 19
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33381
99.9%
Latin 19
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 6204
18.6%
1 3652
10.9%
0 3610
10.8%
2 3150
9.4%
3 2777
8.3%
4 2541
7.6%
5 2413
 
7.2%
6 2363
 
7.1%
8 2276
 
6.8%
7 2264
 
6.8%
Other values (2) 2131
 
6.4%
Latin
ValueCountFrequency (%)
N 19
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 6204
18.6%
1 3652
10.9%
0 3610
10.8%
2 3150
9.4%
3 2777
8.3%
4 2541
7.6%
5 2413
 
7.2%
6 2363
 
7.1%
8 2276
 
6.8%
7 2264
 
6.8%
Other values (3) 2150
 
6.4%

탄소량
Text

Distinct711
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size48.7 KiB
2024-05-18T13:56:15.532479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.9998393
Min length2

Characters and Unicode

Total characters24891
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

Unique213 ?
Unique (%)3.4%

Sample

1st row0.00
2nd row0.00
3rd row1.46
4th row1.74
5th row0.22
ValueCountFrequency (%)
0.00 487
 
7.8%
0.22 59
 
0.9%
0.19 59
 
0.9%
0.21 59
 
0.9%
0.26 58
 
0.9%
0.25 54
 
0.9%
0.29 53
 
0.9%
0.13 52
 
0.8%
0.16 52
 
0.8%
0.24 51
 
0.8%
Other values (701) 5239
84.2%
2024-05-18T13:56:16.940319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6204
24.9%
0 5569
22.4%
1 2550
10.2%
2 2020
 
8.1%
3 1698
 
6.8%
4 1393
 
5.6%
5 1207
 
4.8%
6 1125
 
4.5%
7 1081
 
4.3%
9 1005
 
4.0%
Other values (3) 1039
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18649
74.9%
Other Punctuation 6223
 
25.0%
Uppercase Letter 19
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5569
29.9%
1 2550
13.7%
2 2020
 
10.8%
3 1698
 
9.1%
4 1393
 
7.5%
5 1207
 
6.5%
6 1125
 
6.0%
7 1081
 
5.8%
9 1005
 
5.4%
8 1001
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 6204
99.7%
\ 19
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24872
99.9%
Latin 19
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 6204
24.9%
0 5569
22.4%
1 2550
10.3%
2 2020
 
8.1%
3 1698
 
6.8%
4 1393
 
5.6%
5 1207
 
4.9%
6 1125
 
4.5%
7 1081
 
4.3%
9 1005
 
4.0%
Other values (2) 1020
 
4.1%
Latin
ValueCountFrequency (%)
N 19
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24891
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 6204
24.9%
0 5569
22.4%
1 2550
10.2%
2 2020
 
8.1%
3 1698
 
6.8%
4 1393
 
5.6%
5 1207
 
4.8%
6 1125
 
4.5%
7 1081
 
4.3%
9 1005
 
4.0%
Other values (3) 1039
 
4.2%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4858
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6254.2484
Minimum0
Maximum115857.06
Zeros500
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size54.8 KiB
2024-05-18T13:56:17.413618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11247.065
median3360
Q38255.165
95-th percentile21677.964
Maximum115857.06
Range115857.06
Interquartile range (IQR)7008.1

Descriptive statistics

Standard deviation8070.9337
Coefficient of variation (CV)1.2904722
Kurtosis18.441774
Mean6254.2484
Median Absolute Deviation (MAD)2580.63
Skewness3.2029908
Sum38920188
Variance65139971
MonotonicityNot monotonic
2024-05-18T13:56:18.131485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 500
 
8.0%
940.0 10
 
0.2%
790.0 9
 
0.1%
960.0 9
 
0.1%
720.0 9
 
0.1%
840.0 8
 
0.1%
860.0 8
 
0.1%
1290.0 8
 
0.1%
700.0 8
 
0.1%
1450.0 8
 
0.1%
Other values (4848) 5646
90.7%
ValueCountFrequency (%)
0.0 500
8.0%
0.1 1
 
< 0.1%
0.2 1
 
< 0.1%
0.3 1
 
< 0.1%
0.39 1
 
< 0.1%
10.0 1
 
< 0.1%
20.0 1
 
< 0.1%
40.0 1
 
< 0.1%
88.06 1
 
< 0.1%
88.21 1
 
< 0.1%
ValueCountFrequency (%)
115857.06 1
< 0.1%
99461.15 1
< 0.1%
79632.91 1
< 0.1%
73490.36 1
< 0.1%
73290.91 1
< 0.1%
71104.66 1
< 0.1%
67312.72 1
< 0.1%
64314.1 1
< 0.1%
63962.6 1
< 0.1%
62461.53 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct353
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.187048
Minimum1
Maximum747
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size54.8 KiB
2024-05-18T13:56:18.727212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q113
median34
Q376
95-th percentile195
Maximum747
Range746
Interquartile range (IQR)63

Descriptive statistics

Standard deviation69.490658
Coefficient of variation (CV)1.1942633
Kurtosis12.575023
Mean58.187048
Median Absolute Deviation (MAD)25
Skewness2.8286673
Sum362098
Variance4828.9515
MonotonicityNot monotonic
2024-05-18T13:56:19.686058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 166
 
2.7%
6 162
 
2.6%
8 153
 
2.5%
4 152
 
2.4%
9 134
 
2.2%
3 123
 
2.0%
7 121
 
1.9%
13 115
 
1.8%
10 115
 
1.8%
12 114
 
1.8%
Other values (343) 4868
78.2%
ValueCountFrequency (%)
1 21
 
0.3%
2 97
1.6%
3 123
2.0%
4 152
2.4%
5 166
2.7%
6 162
2.6%
7 121
1.9%
8 153
2.5%
9 134
2.2%
10 115
1.8%
ValueCountFrequency (%)
747 1
< 0.1%
696 1
< 0.1%
693 1
< 0.1%
650 1
< 0.1%
617 1
< 0.1%
614 1
< 0.1%
594 1
< 0.1%
559 1
< 0.1%
539 1
< 0.1%
535 1
< 0.1%

Interactions

2024-05-18T13:56:02.916610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:58.171000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:59.733474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:01.493418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:03.319663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:58.543600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:00.186649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:01.868192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:03.597304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:58.923877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:00.544953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:02.194661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:04.001463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:55:59.315670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:01.090534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:02.502399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T13:56:19.995704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호연령대이용건수이동거리(M)이용시간(분)
대여소번호1.0000.1230.0860.0150.083
연령대0.1231.0000.3220.2730.340
이용건수0.0860.3221.0000.8080.761
이동거리(M)0.0150.2730.8081.0000.810
이용시간(분)0.0830.3400.7610.8101.000
2024-05-18T13:56:20.435230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)연령대
대여소번호1.000-0.083-0.066-0.0720.074
이용건수-0.0831.0000.7650.8210.211
이동거리(M)-0.0660.7651.0000.8500.178
이용시간(분)-0.0720.8210.8501.0000.209
연령대0.0740.2110.1780.2091.000

Missing values

2024-05-18T13:56:04.663952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T13:56:05.326363image/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)
02021-09-01108108. 서교동 사거리정기권<NA>~10대20.000.000.053
12021-09-01729729. 서부식자재마트 건너편정기권<NA>~10대10.000.000.012
22021-09-01731731. 서울시 도로환경관리센터정기권<NA>~10대2160.671.466313.3634
32021-09-01734734. 신트리공원 입구정기권<NA>~10대1207.351.747480.050
42021-09-01735735. 영도초등학교정기권<NA>~10대217.500.22940.015
52021-09-01735735. 영도초등학교정기권<NA>~10대114.450.13570.02
62021-09-01739739. 신월사거리정기권<NA>~10대10.000.000.042
72021-09-01739739. 신월사거리정기권<NA>~10대1165.991.164990.041
82021-09-01740740. 으뜸공원정기권<NA>~10대126.400.261110.958
92021-09-01744744. 신목동역 2번 출구정기권<NA>~10대179.300.622670.012
대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
62132021-09-0111201120. 대림경동아파트앞정기권<NA>40대127.880.261100.07
62142021-09-0111221122. 황금내근린공원정기권<NA>40대3457.673.7516150.0121
62152021-09-0111241124. 발산역 6번 출구 뒤정기권<NA>40대10354.653.2513966.98137
62162021-09-0111241124. 발산역 6번 출구 뒤정기권<NA>40대138.600.411772.1321
62172021-09-0111261126. 우장산역 1번출구옆(우장산아이파크105동앞)정기권<NA>40대180.510.692990.023
62182021-09-0111271127. 화곡역 버스정류장정기권<NA>40대147.130.371587.010
62192021-09-0111291129. 화곡역 1번 출구 앞정기권<NA>40대350.790.371613.4635
62202021-09-0111311131. 꿈돌이공원 앞정기권<NA>40대137.320.341450.09
62212021-09-0111321132. 등촌역 7번출구정기권<NA>40대244.650.311342.442
62222021-09-01206206. KBS 앞정기권<NA>40대3175.401.265410.084