Overview

Dataset statistics

Number of variables11
Number of observations6775
Missing cells4629
Missing cells (%)6.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory608.8 KiB
Average record size in memory92.0 B

Variable types

DateTime1
Numeric4
Text3
Categorical2
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 4629 (68.3%) missing valuesMissing
이동거리(M) has 367 (5.4%) zerosZeros

Reproduction

Analysis started2024-05-18 04:56:26.080634
Analysis finished2024-05-18 04:56:33.789135
Duration7.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.1 KiB
Minimum2021-08-01 00:00:00
Maximum2021-08-01 00:00:00
2024-05-18T13:56:34.074504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:34.391567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

대여소번호
Real number (ℝ)

Distinct2129
Distinct (%)31.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1808.3826
Minimum102
Maximum4869
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size59.7 KiB
2024-05-18T13:56:34.851384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile229
Q1785
median1448
Q32629.5
95-th percentile4461.3
Maximum4869
Range4767
Interquartile range (IQR)1844.5

Descriptive statistics

Standard deviation1267.8147
Coefficient of variation (CV)0.70107661
Kurtosis-0.46810721
Mean1808.3826
Median Absolute Deviation (MAD)807
Skewness0.73917173
Sum12251792
Variance1607354.2
MonotonicityNot monotonic
2024-05-18T13:56:35.424183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
770 12
 
0.2%
2733 11
 
0.2%
2611 11
 
0.2%
746 10
 
0.1%
1684 10
 
0.1%
1153 10
 
0.1%
1050 9
 
0.1%
3566 9
 
0.1%
1125 9
 
0.1%
1168 9
 
0.1%
Other values (2119) 6675
98.5%
ValueCountFrequency (%)
102 8
0.1%
103 2
 
< 0.1%
104 3
 
< 0.1%
105 2
 
< 0.1%
106 5
0.1%
107 5
0.1%
108 4
0.1%
109 3
 
< 0.1%
111 3
 
< 0.1%
112 4
0.1%
ValueCountFrequency (%)
4869 2
 
< 0.1%
4868 5
0.1%
4867 3
< 0.1%
4865 6
0.1%
4864 7
0.1%
4863 1
 
< 0.1%
4862 1
 
< 0.1%
4861 2
 
< 0.1%
4860 2
 
< 0.1%
4859 3
< 0.1%

대여소
Text

Distinct2129
Distinct (%)31.4%
Missing0
Missing (%)0.0%
Memory size53.1 KiB
2024-05-18T13:56:36.312553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length31
Mean length15.492103
Min length7

Characters and Unicode

Total characters104959
Distinct characters538
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique464 ?
Unique (%)6.8%

Sample

1st row108. 서교동 사거리
2nd row734. 신트리공원 입구
3rd row740. 으뜸공원
4th row746. 목동2단지 상가
5th row505. 자양사거리 광진아크로텔 앞
ValueCountFrequency (%)
앞 1676
 
8.5%
출구 277
 
1.4%
옆 264
 
1.3%
1번출구 229
 
1.2%
교차로 172
 
0.9%
입구 149
 
0.8%
3번출구 148
 
0.8%
사거리 143
 
0.7%
2번출구 141
 
0.7%
4번출구 133
 
0.7%
Other values (4270) 16363
83.1%
2024-05-18T13:56:37.600571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13066
 
12.4%
. 6790
 
6.5%
1 5915
 
5.6%
2 4082
 
3.9%
3 3120
 
3.0%
4 2882
 
2.7%
0 2485
 
2.4%
5 2413
 
2.3%
6 2392
 
2.3%
7 2339
 
2.2%
Other values (528) 59475
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54147
51.6%
Decimal Number 28994
27.6%
Space Separator 13066
 
12.4%
Other Punctuation 6870
 
6.5%
Uppercase Letter 643
 
0.6%
Close Punctuation 560
 
0.5%
Open Punctuation 560
 
0.5%
Dash Punctuation 56
 
0.1%
Lowercase Letter 43
 
< 0.1%
Math Symbol 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2331
 
4.3%
앞 1956
 
3.6%
역 1772
 
3.3%
번 1580
 
2.9%
출 1540
 
2.8%
동 1494
 
2.8%
교 1173
 
2.2%
파 1038
 
1.9%
아 981
 
1.8%
리 929
 
1.7%
Other values (474) 39353
72.7%
Uppercase Letter
ValueCountFrequency (%)
S 86
13.4%
K 71
11.0%
T 63
9.8%
C 59
9.2%
A 47
 
7.3%
G 45
 
7.0%
B 44
 
6.8%
I 37
 
5.8%
D 34
 
5.3%
M 30
 
4.7%
Other values (12) 127
19.8%
Decimal Number
ValueCountFrequency (%)
1 5915
20.4%
2 4082
14.1%
3 3120
10.8%
4 2882
9.9%
0 2485
8.6%
5 2413
8.3%
6 2392
8.2%
7 2339
 
8.1%
8 1712
 
5.9%
9 1654
 
5.7%
Lowercase Letter
ValueCountFrequency (%)
e 20
46.5%
k 6
 
14.0%
t 4
 
9.3%
s 4
 
9.3%
a 2
 
4.7%
g 2
 
4.7%
n 2
 
4.7%
y 1
 
2.3%
l 1
 
2.3%
v 1
 
2.3%
Other Punctuation
ValueCountFrequency (%)
. 6790
98.8%
, 61
 
0.9%
& 10
 
0.1%
? 8
 
0.1%
· 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 10
90.9%
+ 1
 
9.1%
Space Separator
ValueCountFrequency (%)
13066
100.0%
Close Punctuation
ValueCountFrequency (%)
) 560
100.0%
Open Punctuation
ValueCountFrequency (%)
( 560
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54147
51.6%
Common 50126
47.8%
Latin 686
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2331
 
4.3%
앞 1956
 
3.6%
역 1772
 
3.3%
번 1580
 
2.9%
출 1540
 
2.8%
동 1494
 
2.8%
교 1173
 
2.2%
파 1038
 
1.9%
아 981
 
1.8%
리 929
 
1.7%
Other values (474) 39353
72.7%
Latin
ValueCountFrequency (%)
S 86
12.5%
K 71
10.3%
T 63
 
9.2%
C 59
 
8.6%
A 47
 
6.9%
G 45
 
6.6%
B 44
 
6.4%
I 37
 
5.4%
D 34
 
5.0%
M 30
 
4.4%
Other values (22) 170
24.8%
Common
ValueCountFrequency (%)
13066
26.1%
. 6790
13.5%
1 5915
11.8%
2 4082
 
8.1%
3 3120
 
6.2%
4 2882
 
5.7%
0 2485
 
5.0%
5 2413
 
4.8%
6 2392
 
4.8%
7 2339
 
4.7%
Other values (12) 4642
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54147
51.6%
ASCII 50811
48.4%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13066
25.7%
. 6790
13.4%
1 5915
11.6%
2 4082
 
8.0%
3 3120
 
6.1%
4 2882
 
5.7%
0 2485
 
4.9%
5 2413
 
4.7%
6 2392
 
4.7%
7 2339
 
4.6%
Other values (43) 5327
10.5%
Hangul
ValueCountFrequency (%)
구 2331
 
4.3%
앞 1956
 
3.6%
역 1772
 
3.3%
번 1580
 
2.9%
출 1540
 
2.8%
동 1494
 
2.8%
교 1173
 
2.2%
파 1038
 
1.9%
아 981
 
1.8%
리 929
 
1.7%
Other values (474) 39353
72.7%
None
ValueCountFrequency (%)
· 1
100.0%

대여구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.1 KiB
정기권
6775 

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 6775
100.0%

Length

2024-05-18T13:56:38.082988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:56:38.491456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 6775
100.0%

성별
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing4629
Missing (%)68.3%
Memory size13.4 KiB
False
2146 
(Missing)
4629 
ValueCountFrequency (%)
False 2146
31.7%
(Missing) 4629
68.3%
2024-05-18T13:56:38.850881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

연령대
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size53.1 KiB
20대
2604 
30대
1590 
40대
1013 
50대
651 
~10대
496 
Other values (3)
421 

Length

Max length5
Median length3
Mean length3.0487085
Min length2

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 2604
38.4%
30대 1590
23.5%
40대 1013
 
15.0%
50대 651
 
9.6%
~10대 496
 
7.3%
60대 210
 
3.1%
기타 196
 
2.9%
70대이상 15
 
0.2%

Length

2024-05-18T13:56:39.147416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:56:39.602722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 2604
38.4%
30대 1590
23.5%
40대 1013
 
15.0%
50대 651
 
9.6%
10대 496
 
7.3%
60대 210
 
3.1%
기타 196
 
2.9%
70대이상 15
 
0.2%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6568266
Minimum1
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size59.7 KiB
2024-05-18T13:56:40.010270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum18
Range17
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3338013
Coefficient of variation (CV)0.80503376
Kurtosis19.744686
Mean1.6568266
Median Absolute Deviation (MAD)0
Skewness3.6155006
Sum11225
Variance1.7790259
MonotonicityNot monotonic
2024-05-18T13:56:40.470052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 4527
66.8%
2 1256
 
18.5%
3 490
 
7.2%
4 220
 
3.2%
5 119
 
1.8%
6 67
 
1.0%
7 37
 
0.5%
9 23
 
0.3%
8 15
 
0.2%
10 7
 
0.1%
Other values (6) 14
 
0.2%
ValueCountFrequency (%)
1 4527
66.8%
2 1256
 
18.5%
3 490
 
7.2%
4 220
 
3.2%
5 119
 
1.8%
6 67
 
1.0%
7 37
 
0.5%
8 15
 
0.2%
9 23
 
0.3%
10 7
 
0.1%
ValueCountFrequency (%)
18 1
 
< 0.1%
15 2
 
< 0.1%
14 2
 
< 0.1%
13 3
 
< 0.1%
12 2
 
< 0.1%
11 4
 
0.1%
10 7
 
0.1%
9 23
0.3%
8 15
0.2%
7 37
0.5%

운동량
Text

Distinct5108
Distinct (%)75.4%
Missing0
Missing (%)0.0%
Memory size53.1 KiB
2024-05-18T13:56:41.320092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1616236
Min length2

Characters and Unicode

Total characters34970
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

Unique4114 ?
Unique (%)60.7%

Sample

1st row132.12
2nd row68.47
3rd row24.18
4th row12.19
5th row19.77
ValueCountFrequency (%)
0.00 356
 
5.3%
n 17
 
0.3%
13.90 6
 
0.1%
10.04 5
 
0.1%
24.45 5
 
0.1%
27.94 5
 
0.1%
16.72 5
 
0.1%
16.22 5
 
0.1%
29.41 5
 
0.1%
30.63 5
 
0.1%
Other values (5098) 6361
93.9%
2024-05-18T13:56:42.506795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6758
19.3%
1 3969
11.3%
2 3380
9.7%
0 3254
9.3%
3 3067
8.8%
4 2662
 
7.6%
5 2526
 
7.2%
6 2396
 
6.9%
7 2369
 
6.8%
8 2310
 
6.6%
Other values (3) 2279
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28178
80.6%
Other Punctuation 6775
 
19.4%
Uppercase Letter 17
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3969
14.1%
2 3380
12.0%
0 3254
11.5%
3 3067
10.9%
4 2662
9.4%
5 2526
9.0%
6 2396
8.5%
7 2369
8.4%
8 2310
8.2%
9 2245
8.0%
Other Punctuation
ValueCountFrequency (%)
. 6758
99.7%
\ 17
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34953
> 99.9%
Latin 17
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 6758
19.3%
1 3969
11.4%
2 3380
9.7%
0 3254
9.3%
3 3067
8.8%
4 2662
 
7.6%
5 2526
 
7.2%
6 2396
 
6.9%
7 2369
 
6.8%
8 2310
 
6.6%
Other values (2) 2262
 
6.5%
Latin
ValueCountFrequency (%)
N 17
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34970
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 6758
19.3%
1 3969
11.3%
2 3380
9.7%
0 3254
9.3%
3 3067
8.8%
4 2662
 
7.6%
5 2526
 
7.2%
6 2396
 
6.9%
7 2369
 
6.8%
8 2310
 
6.6%
Other values (3) 2279
 
6.5%

탄소량
Text

Distinct436
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size53.1 KiB
2024-05-18T13:56:43.206849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.9951292
Min length2

Characters and Unicode

Total characters27067
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

Unique116 ?
Unique (%)1.7%

Sample

1st row1.29
2nd row0.57
3rd row0.26
4th row0.13
5th row0.18
ValueCountFrequency (%)
0.00 360
 
5.3%
0.22 107
 
1.6%
0.19 104
 
1.5%
0.18 99
 
1.5%
0.20 96
 
1.4%
0.16 94
 
1.4%
0.25 91
 
1.3%
0.13 90
 
1.3%
0.24 87
 
1.3%
0.23 87
 
1.3%
Other values (426) 5560
82.1%
2024-05-18T13:56:44.253307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7031
26.0%
. 6758
25.0%
1 2766
 
10.2%
2 2084
 
7.7%
3 1726
 
6.4%
4 1371
 
5.1%
5 1235
 
4.6%
6 1136
 
4.2%
7 1042
 
3.8%
9 953
 
3.5%
Other values (3) 965
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20275
74.9%
Other Punctuation 6775
 
25.0%
Uppercase Letter 17
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7031
34.7%
1 2766
 
13.6%
2 2084
 
10.3%
3 1726
 
8.5%
4 1371
 
6.8%
5 1235
 
6.1%
6 1136
 
5.6%
7 1042
 
5.1%
9 953
 
4.7%
8 931
 
4.6%
Other Punctuation
ValueCountFrequency (%)
. 6758
99.7%
\ 17
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27050
99.9%
Latin 17
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7031
26.0%
. 6758
25.0%
1 2766
 
10.2%
2 2084
 
7.7%
3 1726
 
6.4%
4 1371
 
5.1%
5 1235
 
4.6%
6 1136
 
4.2%
7 1042
 
3.9%
9 953
 
3.5%
Other values (2) 948
 
3.5%
Latin
ValueCountFrequency (%)
N 17
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7031
26.0%
. 6758
25.0%
1 2766
 
10.2%
2 2084
 
7.7%
3 1726
 
6.4%
4 1371
 
5.1%
5 1235
 
4.6%
6 1136
 
4.2%
7 1042
 
3.8%
9 953
 
3.5%
Other values (3) 965
 
3.6%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct5377
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3237.9334
Minimum0
Maximum54022.12
Zeros367
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size59.7 KiB
2024-05-18T13:56:44.856900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1940
median1911.97
Q34088.48
95-th percentile10814.203
Maximum54022.12
Range54022.12
Interquartile range (IQR)3148.48

Descriptive statistics

Standard deviation3810.9866
Coefficient of variation (CV)1.1769812
Kurtosis15.637585
Mean3237.9334
Median Absolute Deviation (MAD)1222.25
Skewness3.0238672
Sum21936998
Variance14523619
MonotonicityNot monotonic
2024-05-18T13:56:45.349128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 367
 
5.4%
630.0 11
 
0.2%
950.0 11
 
0.2%
790.0 11
 
0.2%
580.0 10
 
0.1%
570.0 10
 
0.1%
890.0 10
 
0.1%
760.0 10
 
0.1%
940.0 10
 
0.1%
560.0 9
 
0.1%
Other values (5367) 6316
93.2%
ValueCountFrequency (%)
0.0 367
5.4%
0.1 5
 
0.1%
0.2 1
 
< 0.1%
0.29 1
 
< 0.1%
0.67 1
 
< 0.1%
10.0 2
 
< 0.1%
40.0 1
 
< 0.1%
50.0 1
 
< 0.1%
60.0 1
 
< 0.1%
88.08 1
 
< 0.1%
ValueCountFrequency (%)
54022.12 1
< 0.1%
40123.72 1
< 0.1%
34190.0 1
< 0.1%
33993.78 1
< 0.1%
33060.24 1
< 0.1%
32850.61 1
< 0.1%
31982.54 1
< 0.1%
31900.48 1
< 0.1%
31755.67 1
< 0.1%
31251.17 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct177
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.269077
Minimum0
Maximum402
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size59.7 KiB
2024-05-18T13:56:45.803560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q18
median16
Q335
95-th percentile79
Maximum402
Range402
Interquartile range (IQR)27

Descriptive statistics

Standard deviation28.944875
Coefficient of variation (CV)1.1018611
Kurtosis21.454321
Mean26.269077
Median Absolute Deviation (MAD)10
Skewness3.3358928
Sum177973
Variance837.8058
MonotonicityNot monotonic
2024-05-18T13:56:46.271066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 335
 
4.9%
5 322
 
4.8%
7 268
 
4.0%
4 267
 
3.9%
8 262
 
3.9%
9 240
 
3.5%
12 229
 
3.4%
3 219
 
3.2%
10 219
 
3.2%
11 209
 
3.1%
Other values (167) 4205
62.1%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 41
 
0.6%
2 162
2.4%
3 219
3.2%
4 267
3.9%
5 322
4.8%
6 335
4.9%
7 268
4.0%
8 262
3.9%
9 240
3.5%
ValueCountFrequency (%)
402 1
< 0.1%
395 1
< 0.1%
345 1
< 0.1%
336 1
< 0.1%
286 1
< 0.1%
271 2
< 0.1%
257 1
< 0.1%
254 1
< 0.1%
240 1
< 0.1%
236 1
< 0.1%

Interactions

2024-05-18T13:56:31.157315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:27.717866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:28.814271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:29.984907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:31.673771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:27.978618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:29.102149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:30.290332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:32.136614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:28.251896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:29.378677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:30.578072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:32.462811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:28.524227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:29.676987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:56:30.867313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T13:56:46.559910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호연령대이용건수이동거리(M)이용시간(분)
대여소번호1.0000.0760.0780.0320.000
연령대0.0761.0000.2330.0830.102
이용건수0.0780.2331.0000.6640.761
이동거리(M)0.0320.0830.6641.0000.729
이용시간(분)0.0000.1020.7610.7291.000
2024-05-18T13:56:46.830453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)연령대
대여소번호1.000-0.033-0.030-0.0320.036
이용건수-0.0331.0000.5270.5440.113
이동거리(M)-0.0300.5271.0000.8340.040
이용시간(분)-0.0320.5440.8341.0000.049
연령대0.0360.1130.0400.0491.000

Missing values

2024-05-18T13:56:32.910702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T13:56:33.485356image/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)
02021-08-01108108. 서교동 사거리정기권<NA>~10대1132.121.295560.655
12021-08-01734734. 신트리공원 입구정기권<NA>~10대168.470.572470.016
22021-08-01740740. 으뜸공원정기권<NA>~10대124.180.261110.07
32021-08-01746746. 목동2단지 상가정기권<NA>~10대112.190.13570.03
42021-08-01505505. 자양사거리 광진아크로텔 앞정기권<NA>~10대119.770.18780.04
52021-08-0110241024. 강동구청 앞정기권<NA>~10대270.350.662844.7634
62021-08-0110261026. 대명초교 입구 교차로정기권<NA>~10대136.720.251065.866
72021-08-0110331033. 고덕동 아남아파트정기권<NA>~10대139.300.351526.638
82021-08-0110341034. 고덕동 래미안 힐스테이트정기권<NA>~10대123.850.22926.745
92021-08-0110351035. 고덕역 4번출구정기권<NA>~10대3145.781.235296.8429
대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
67652021-08-0134163416.동묘앞역 6번출구정기권F50대10.000.000.07
67662021-08-0134173417.창신3동주민센터정기권F50대155.780.652817.0416
67672021-08-0110781078.둔촌사거리정기권F50대114.580.14593.656
67682021-08-0110791079.강일동입구교차로정기권F50대123.170.21900.05
67692021-08-0126232623.석촌동 주민센터정기권F50대239.120.441900.031
67702021-08-0126272627.문정시영아파트 5동 앞 공원정기권F50대130.690.361550.09
67712021-08-0126372637. 아시아지하보도 14번 출구정기권F50대131.630.321377.015
67722021-08-0126462646.레이크펠리스101동앞정기권F50대123.410.241019.275
67732021-08-0126512651.경찰병원역 3번출구 앞정기권F50대2106.030.964119.2161
67742021-08-01375375. 다산 어린이공원정기권F50대293.941.034446.1225