Overview

Dataset statistics

Number of variables11
Number of observations9570
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory859.9 KiB
Average record size in memory92.0 B

Variable types

DateTime1
Numeric4
Text3
Categorical3

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15246/F/1/datasetView.do

Alerts

대여일자 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
이동거리(M) has 644 (6.7%) zerosZeros

Reproduction

Analysis started2024-03-13 16:27:40.173083
Analysis finished2024-03-13 16:27:42.572326
Duration2.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size74.9 KiB
Minimum2022-03-01 00:00:00
Maximum2022-03-01 00:00:00
2024-03-14T01:27:42.607265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:42.679238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

대여소번호
Real number (ℝ)

Distinct765
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean557.71714
Minimum3
Maximum1078
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size84.2 KiB
2024-03-14T01:27:42.773793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile140
Q1293
median557
Q3786
95-th percentile1023
Maximum1078
Range1075
Interquartile range (IQR)493

Descriptive statistics

Standard deviation282.60844
Coefficient of variation (CV)0.50672361
Kurtosis-1.1585895
Mean557.71714
Median Absolute Deviation (MAD)240
Skewness0.11687952
Sum5337353
Variance79867.53
MonotonicityIncreasing
2024-03-14T01:27:42.886221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
502 45
 
0.5%
207 44
 
0.5%
565 41
 
0.4%
765 36
 
0.4%
272 36
 
0.4%
583 34
 
0.4%
907 33
 
0.3%
418 33
 
0.3%
186 32
 
0.3%
853 32
 
0.3%
Other values (755) 9204
96.2%
ValueCountFrequency (%)
3 2
 
< 0.1%
102 19
0.2%
103 23
0.2%
104 15
0.2%
105 10
0.1%
106 23
0.2%
107 16
0.2%
108 17
0.2%
109 14
0.1%
111 10
0.1%
ValueCountFrequency (%)
1078 19
0.2%
1077 16
0.2%
1076 19
0.2%
1075 13
0.1%
1074 15
0.2%
1073 8
0.1%
1072 17
0.2%
1071 3
 
< 0.1%
1070 6
 
0.1%
1069 3
 
< 0.1%

대여소
Text

Distinct765
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size74.9 KiB
2024-03-14T01:27:43.106401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length14.723929
Min length4

Characters and Unicode

Total characters140908
Distinct characters417
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)0.1%

Sample

1st row중랑센터
2nd row중랑센터
3rd row102. 망원역 1번출구 앞
4th row102. 망원역 1번출구 앞
5th row102. 망원역 1번출구 앞
ValueCountFrequency (%)
앞 2963
 
10.1%
옆 546
 
1.9%
1번출구 386
 
1.3%
출구 369
 
1.3%
사거리 337
 
1.1%
2번출구 320
 
1.1%
3번출구 287
 
1.0%
4번출구 255
 
0.9%
뒤 243
 
0.8%
입구 232
 
0.8%
Other values (1595) 23418
79.8%
2024-03-14T01:27:43.471603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19937
 
14.1%
. 9568
 
6.8%
1 5032
 
3.6%
2 4278
 
3.0%
4 3538
 
2.5%
3 3486
 
2.5%
구 3457
 
2.5%
앞 3312
 
2.4%
7 3290
 
2.3%
5 3267
 
2.3%
Other values (407) 81743
58.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74474
52.9%
Decimal Number 34039
24.2%
Space Separator 19937
 
14.1%
Other Punctuation 9612
 
6.8%
Uppercase Letter 1432
 
1.0%
Open Punctuation 681
 
0.5%
Close Punctuation 681
 
0.5%
Dash Punctuation 33
 
< 0.1%
Math Symbol 19
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3457
 
4.6%
앞 3312
 
4.4%
역 2888
 
3.9%
번 2578
 
3.5%
출 2564
 
3.4%
동 2125
 
2.9%
교 1603
 
2.2%
리 1423
 
1.9%
아 1248
 
1.7%
원 1180
 
1.6%
Other values (371) 52096
70.0%
Uppercase Letter
ValueCountFrequency (%)
C 203
14.2%
S 196
13.7%
K 155
10.8%
B 133
9.3%
D 107
 
7.5%
I 93
 
6.5%
T 80
 
5.6%
M 70
 
4.9%
G 66
 
4.6%
L 54
 
3.8%
Other values (9) 275
19.2%
Decimal Number
ValueCountFrequency (%)
1 5032
14.8%
2 4278
12.6%
4 3538
10.4%
3 3486
10.2%
7 3290
9.7%
5 3267
9.6%
0 3240
9.5%
6 3016
8.9%
8 2533
7.4%
9 2359
6.9%
Other Punctuation
ValueCountFrequency (%)
. 9568
99.5%
, 44
 
0.5%
Space Separator
ValueCountFrequency (%)
19937
100.0%
Open Punctuation
ValueCountFrequency (%)
( 681
100.0%
Close Punctuation
ValueCountFrequency (%)
) 681
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Math Symbol
ValueCountFrequency (%)
~ 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74474
52.9%
Common 65002
46.1%
Latin 1432
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3457
 
4.6%
앞 3312
 
4.4%
역 2888
 
3.9%
번 2578
 
3.5%
출 2564
 
3.4%
동 2125
 
2.9%
교 1603
 
2.2%
리 1423
 
1.9%
아 1248
 
1.7%
원 1180
 
1.6%
Other values (371) 52096
70.0%
Latin
ValueCountFrequency (%)
C 203
14.2%
S 196
13.7%
K 155
10.8%
B 133
9.3%
D 107
 
7.5%
I 93
 
6.5%
T 80
 
5.6%
M 70
 
4.9%
G 66
 
4.6%
L 54
 
3.8%
Other values (9) 275
19.2%
Common
ValueCountFrequency (%)
19937
30.7%
. 9568
14.7%
1 5032
 
7.7%
2 4278
 
6.6%
4 3538
 
5.4%
3 3486
 
5.4%
7 3290
 
5.1%
5 3267
 
5.0%
0 3240
 
5.0%
6 3016
 
4.6%
Other values (7) 6350
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74474
52.9%
ASCII 66434
47.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19937
30.0%
. 9568
14.4%
1 5032
 
7.6%
2 4278
 
6.4%
4 3538
 
5.3%
3 3486
 
5.2%
7 3290
 
5.0%
5 3267
 
4.9%
0 3240
 
4.9%
6 3016
 
4.5%
Other values (26) 7782
 
11.7%
Hangul
ValueCountFrequency (%)
구 3457
 
4.6%
앞 3312
 
4.4%
역 2888
 
3.9%
번 2578
 
3.5%
출 2564
 
3.4%
동 2125
 
2.9%
교 1603
 
2.2%
리 1423
 
1.9%
아 1248
 
1.7%
원 1180
 
1.6%
Other values (371) 52096
70.0%

대여구분코드
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size74.9 KiB
정기
6500 
일일(회원)
2743 
일일(비회원)
 
168
단체
 
159

Length

Max length7
Median length2
Mean length3.2342738
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정기
2nd row정기
3rd row일일(회원)
4th row일일(회원)
5th row일일(회원)

Common Values

ValueCountFrequency (%)
정기 6500
67.9%
일일(회원) 2743
28.7%
일일(비회원) 168
 
1.8%
단체 159
 
1.7%

Length

2024-03-14T01:27:43.584659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:27:43.660933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 6500
67.9%
일일(회원 2743
28.7%
일일(비회원 168
 
1.8%
단체 159
 
1.7%

성별
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size74.9 KiB
M
3643 
\N
2952 
F
2502 
<NA>
472 
f
 
1

Length

Max length4
Median length1
Mean length1.4564263
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowM
2nd rowM
3rd row\N
4th row\N
5th row<NA>

Common Values

ValueCountFrequency (%)
M 3643
38.1%
\N 2952
30.8%
F 2502
26.1%
<NA> 472
 
4.9%
f 1
 
< 0.1%

Length

2024-03-14T01:27:43.747644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:27:43.828543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 3643
38.1%
n 2952
30.8%
f 2503
26.2%
na 472
 
4.9%

연령대코드
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size74.9 KiB
20대
2732 
30대
2058 
40대
1452 
기타
1159 
50대
1039 
Other values (3)
1130 

Length

Max length5
Median length3
Mean length2.8912226
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20대
2nd row50대
3rd row20대
4th row30대
5th row20대

Common Values

ValueCountFrequency (%)
20대 2732
28.5%
30대 2058
21.5%
40대 1452
15.2%
기타 1159
12.1%
50대 1039
 
10.9%
10대 619
 
6.5%
60대 452
 
4.7%
70대이상 59
 
0.6%

Length

2024-03-14T01:27:43.951279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:27:44.282115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 2732
28.5%
30대 2058
21.5%
40대 1452
15.2%
기타 1159
12.1%
50대 1039
 
10.9%
10대 619
 
6.5%
60대 452
 
4.7%
70대이상 59
 
0.6%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8159875
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size84.2 KiB
2024-03-14T01:27:44.381855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum28
Range27
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.4853925
Coefficient of variation (CV)0.81795305
Kurtosis38.455972
Mean1.8159875
Median Absolute Deviation (MAD)0
Skewness4.3494206
Sum17379
Variance2.2063908
MonotonicityNot monotonic
2024-03-14T01:27:44.467726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 5655
59.1%
2 2134
 
22.3%
3 874
 
9.1%
4 431
 
4.5%
5 213
 
2.2%
6 110
 
1.1%
7 59
 
0.6%
8 41
 
0.4%
9 20
 
0.2%
10 13
 
0.1%
Other values (11) 20
 
0.2%
ValueCountFrequency (%)
1 5655
59.1%
2 2134
 
22.3%
3 874
 
9.1%
4 431
 
4.5%
5 213
 
2.2%
6 110
 
1.1%
7 59
 
0.6%
8 41
 
0.4%
9 20
 
0.2%
10 13
 
0.1%
ValueCountFrequency (%)
28 1
 
< 0.1%
25 1
 
< 0.1%
20 3
< 0.1%
19 3
< 0.1%
18 1
 
< 0.1%
17 1
 
< 0.1%
16 2
< 0.1%
14 1
 
< 0.1%
13 1
 
< 0.1%
12 4
< 0.1%

운동량
Text

Distinct7259
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Memory size74.9 KiB
2024-03-14T01:27:44.751946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.3412748
Min length2

Characters and Unicode

Total characters51116
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

Unique6053 ?
Unique (%)63.2%

Sample

1st row126.64
2nd row66.60
3rd row119.51
4th row209.18
5th row34.49
ValueCountFrequency (%)
0.00 622
 
6.5%
n 27
 
0.3%
36.81 9
 
0.1%
28.31 7
 
0.1%
19.82 7
 
0.1%
42.73 7
 
0.1%
45.62 7
 
0.1%
24.45 6
 
0.1%
31.92 6
 
0.1%
23.42 6
 
0.1%
Other values (7249) 8866
92.6%
2024-03-14T01:27:45.155253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9543
18.7%
1 5787
11.3%
0 5112
10.0%
2 4817
9.4%
3 4334
8.5%
4 3864
7.6%
5 3765
 
7.4%
6 3680
 
7.2%
7 3454
 
6.8%
9 3383
 
6.6%
Other values (3) 3377
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41519
81.2%
Other Punctuation 9570
 
18.7%
Uppercase Letter 27
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5787
13.9%
0 5112
12.3%
2 4817
11.6%
3 4334
10.4%
4 3864
9.3%
5 3765
9.1%
6 3680
8.9%
7 3454
8.3%
9 3383
8.1%
8 3323
8.0%
Other Punctuation
ValueCountFrequency (%)
. 9543
99.7%
\ 27
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51089
99.9%
Latin 27
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9543
18.7%
1 5787
11.3%
0 5112
10.0%
2 4817
9.4%
3 4334
8.5%
4 3864
7.6%
5 3765
 
7.4%
6 3680
 
7.2%
7 3454
 
6.8%
9 3383
 
6.6%
Other values (2) 3350
 
6.6%
Latin
ValueCountFrequency (%)
N 27
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51116
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9543
18.7%
1 5787
11.3%
0 5112
10.0%
2 4817
9.4%
3 4334
8.5%
4 3864
7.6%
5 3765
 
7.4%
6 3680
 
7.2%
7 3454
 
6.8%
9 3383
 
6.6%
Other values (3) 3377
 
6.6%

탄소량
Text

Distinct711
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size74.9 KiB
2024-03-14T01:27:45.460989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.9980146
Min length2

Characters and Unicode

Total characters38261
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

Unique185 ?
Unique (%)1.9%

Sample

1st row1.14
2nd row0.58
3rd row1.38
4th row1.73
5th row0.31
ValueCountFrequency (%)
0.00 627
 
6.6%
0.26 100
 
1.0%
0.35 92
 
1.0%
0.29 89
 
0.9%
0.33 84
 
0.9%
0.30 82
 
0.9%
0.16 78
 
0.8%
0.21 78
 
0.8%
0.13 78
 
0.8%
0.45 77
 
0.8%
Other values (701) 8185
85.5%
2024-03-14T01:27:45.873026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9543
24.9%
0 8673
22.7%
1 4078
10.7%
2 2882
 
7.5%
3 2479
 
6.5%
4 2113
 
5.5%
5 1883
 
4.9%
6 1832
 
4.8%
7 1669
 
4.4%
9 1529
 
4.0%
Other values (3) 1580
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28664
74.9%
Other Punctuation 9570
 
25.0%
Uppercase Letter 27
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8673
30.3%
1 4078
14.2%
2 2882
 
10.1%
3 2479
 
8.6%
4 2113
 
7.4%
5 1883
 
6.6%
6 1832
 
6.4%
7 1669
 
5.8%
9 1529
 
5.3%
8 1526
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 9543
99.7%
\ 27
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38234
99.9%
Latin 27
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9543
25.0%
0 8673
22.7%
1 4078
10.7%
2 2882
 
7.5%
3 2479
 
6.5%
4 2113
 
5.5%
5 1883
 
4.9%
6 1832
 
4.8%
7 1669
 
4.4%
9 1529
 
4.0%
Other values (2) 1553
 
4.1%
Latin
ValueCountFrequency (%)
N 27
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38261
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9543
24.9%
0 8673
22.7%
1 4078
10.7%
2 2882
 
7.5%
3 2479
 
6.5%
4 2113
 
5.5%
5 1883
 
4.9%
6 1832
 
4.8%
7 1669
 
4.4%
9 1529
 
4.0%
Other values (3) 1580
 
4.1%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6739
Distinct (%)70.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5436.47
Minimum0
Maximum198438.33
Zeros644
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size84.2 KiB
2024-03-14T01:27:45.990685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11347.185
median3060.46
Q36852.5275
95-th percentile18410.577
Maximum198438.33
Range198438.33
Interquartile range (IQR)5505.3425

Descriptive statistics

Standard deviation7556.7174
Coefficient of variation (CV)1.3900044
Kurtosis106.71024
Mean5436.47
Median Absolute Deviation (MAD)2150.46
Skewness6.7318299
Sum52027018
Variance57103978
MonotonicityNot monotonic
2024-03-14T01:27:46.141339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 644
 
6.7%
1100.0 17
 
0.2%
1430.0 15
 
0.2%
580.0 15
 
0.2%
1240.0 15
 
0.2%
1120.0 15
 
0.2%
1140.0 13
 
0.1%
1350.0 13
 
0.1%
1520.0 13
 
0.1%
2190.0 13
 
0.1%
Other values (6729) 8797
91.9%
ValueCountFrequency (%)
0.0 644
6.7%
0.1 4
 
< 0.1%
10.0 2
 
< 0.1%
14.51 1
 
< 0.1%
20.0 3
 
< 0.1%
30.0 3
 
< 0.1%
40.0 2
 
< 0.1%
50.0 1
 
< 0.1%
60.0 1
 
< 0.1%
70.0 1
 
< 0.1%
ValueCountFrequency (%)
198438.33 1
< 0.1%
173806.29 1
< 0.1%
137520.7 1
< 0.1%
128978.77 1
< 0.1%
116409.87 1
< 0.1%
115546.6 1
< 0.1%
101134.01 1
< 0.1%
90967.88 1
< 0.1%
69706.88 1
< 0.1%
68839.65 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct347
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.303657
Minimum0
Maximum1802
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size84.2 KiB
2024-03-14T01:27:46.286596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q113
median31
Q366
95-th percentile158
Maximum1802
Range1802
Interquartile range (IQR)53

Descriptive statistics

Standard deviation66.642212
Coefficient of variation (CV)1.2989759
Kurtosis100.64364
Mean51.303657
Median Absolute Deviation (MAD)22
Skewness6.49682
Sum490976
Variance4441.1844
MonotonicityNot monotonic
2024-03-14T01:27:46.392643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 264
 
2.8%
5 259
 
2.7%
6 248
 
2.6%
7 226
 
2.4%
8 222
 
2.3%
10 212
 
2.2%
9 194
 
2.0%
12 190
 
2.0%
3 189
 
2.0%
13 188
 
2.0%
Other values (337) 7378
77.1%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 31
 
0.3%
2 121
1.3%
3 189
2.0%
4 264
2.8%
5 259
2.7%
6 248
2.6%
7 226
2.4%
8 222
2.3%
9 194
2.0%
ValueCountFrequency (%)
1802 1
< 0.1%
1383 1
< 0.1%
1141 1
< 0.1%
1138 1
< 0.1%
974 1
< 0.1%
959 1
< 0.1%
920 1
< 0.1%
793 1
< 0.1%
706 1
< 0.1%
695 1
< 0.1%

Interactions

2024-03-14T01:27:42.065131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:41.027462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:41.339291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:41.652337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:42.138444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:41.097960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:41.411946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:41.772763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:42.212982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:41.174262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:41.488123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:41.898461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:42.292628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:41.265608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:41.567640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:41.982371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T01:27:46.470511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호대여구분코드성별연령대코드이용건수이동거리(M)이용시간(분)
대여소번호1.0000.0640.0000.0380.0700.0610.052
대여구분코드0.0641.0000.2860.5050.1100.0840.097
성별0.0000.2861.0000.1610.0530.0000.000
연령대코드0.0380.5050.1611.0000.1410.0540.033
이용건수0.0700.1100.0530.1411.0000.8830.875
이동거리(M)0.0610.0840.0000.0540.8831.0000.978
이용시간(분)0.0520.0970.0000.0330.8750.9781.000
2024-03-14T01:27:46.554272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여구분코드성별연령대코드
대여구분코드1.0000.1150.245
성별0.1151.0000.073
연령대코드0.2450.0731.000
2024-03-14T01:27:46.629953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)대여구분코드성별연령대코드
대여소번호1.000-0.042-0.068-0.0670.0380.0000.018
이용건수-0.0421.0000.5330.5640.0660.0320.067
이동거리(M)-0.0680.5331.0000.8510.0540.0000.027
이용시간(분)-0.0670.5640.8511.0000.0620.0000.016
대여구분코드0.0380.0660.0540.0621.0000.1150.245
성별0.0000.0320.0000.0000.1151.0000.073
연령대코드0.0180.0670.0270.0160.2450.0731.000

Missing values

2024-03-14T01:27:42.395639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T01:27:42.516124image/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

대여일자대여소번호대여소대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
02022-03-013중랑센터정기M20대1126.641.144920.023
12022-03-013중랑센터정기M50대166.600.582510.010
22022-03-01102102. 망원역 1번출구 앞일일(회원)\N20대2119.511.385937.7394
32022-03-01102102. 망원역 1번출구 앞일일(회원)\N30대1209.181.737440.045
42022-03-01102102. 망원역 1번출구 앞일일(회원)<NA>20대134.490.311340.08
52022-03-01102102. 망원역 1번출구 앞일일(회원)F20대4444.674.0617538.26196
62022-03-01102102. 망원역 1번출구 앞일일(회원)M10대1157.641.185103.7166
72022-03-01102102. 망원역 1번출구 앞일일(회원)M20대4319.502.5210851.56122
82022-03-01102102. 망원역 1번출구 앞일일(회원)M30대286.960.602559.3516
92022-03-01102102. 망원역 1번출구 앞일일(회원)M40대145.150.411754.1711
대여일자대여소번호대여소대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
95602022-03-0110781078.둔촌사거리정기F20대150.370.562400.016
95612022-03-0110781078.둔촌사거리정기F30대144.430.472040.011
95622022-03-0110781078.둔촌사거리정기F40대1197.161.657112.468
95632022-03-0110781078.둔촌사거리정기F50대189.690.703020.019
95642022-03-0110781078.둔촌사거리정기F기타113.640.15650.010
95652022-03-0110781078.둔촌사거리정기M10대182.800.622680.7515
95662022-03-0110781078.둔촌사거리정기M20대118.170.14620.05
95672022-03-0110781078.둔촌사거리정기M30대163.320.451950.011
95682022-03-0110781078.둔촌사거리정기M40대1229.431.988520.053
95692022-03-0110781078.둔촌사거리정기M60대4258.572.239621.5262