Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells8
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1005.9 KiB
Average record size in memory103.0 B

Variable types

Categorical4
Numeric6
Text1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15248/F/1/datasetView.do

Alerts

대여일자 has constant value ""Constant
이용건수 is highly overall correlated with 운동량 and 3 other fieldsHigh correlation
운동량 is highly overall correlated with 이용건수 and 3 other fieldsHigh correlation
탄소량 is highly overall correlated with 이용건수 and 3 other fieldsHigh correlation
이동거리(M) is highly overall correlated with 이용건수 and 3 other fieldsHigh correlation
이용시간(분) is highly overall correlated with 이용건수 and 3 other fieldsHigh correlation

Reproduction

Analysis started2024-03-13 13:01:14.122493
Analysis finished2024-03-13 13:01:21.672454
Duration7.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
202307
10000 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row202307
2nd row202307
3rd row202307
4th row202307
5th row202307

Common Values

ValueCountFrequency (%)
202307 10000
100.0%

Length

2024-03-13T22:01:21.754704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:01:21.855696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202307 10000
100.0%

대여소번호
Real number (ℝ)

Distinct2439
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2035.5344
Minimum102
Maximum4634
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T22:01:22.027658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile248
Q1906
median1761.5
Q33131
95-th percentile4454.1
Maximum4634
Range4532
Interquartile range (IQR)2225

Descriptive statistics

Standard deviation1349.0463
Coefficient of variation (CV)0.66274799
Kurtosis-1.0525037
Mean2035.5344
Median Absolute Deviation (MAD)979.5
Skewness0.42952699
Sum20355344
Variance1819926
MonotonicityNot monotonic
2024-03-13T22:01:22.232371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
949 14
 
0.1%
1616 11
 
0.1%
1278 11
 
0.1%
1106 10
 
0.1%
4592 10
 
0.1%
1450 10
 
0.1%
1569 10
 
0.1%
1708 10
 
0.1%
916 10
 
0.1%
956 10
 
0.1%
Other values (2429) 9894
98.9%
ValueCountFrequency (%)
102 5
0.1%
103 3
< 0.1%
104 5
0.1%
105 4
< 0.1%
106 5
0.1%
107 5
0.1%
108 3
< 0.1%
109 1
 
< 0.1%
111 2
 
< 0.1%
112 5
0.1%
ValueCountFrequency (%)
4634 2
 
< 0.1%
4633 3
< 0.1%
4632 1
 
< 0.1%
4629 6
0.1%
4627 2
 
< 0.1%
4625 3
< 0.1%
4623 3
< 0.1%
4622 1
 
< 0.1%
4621 3
< 0.1%
4620 5
0.1%

대여소명
Text

Distinct2439
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T22:01:22.576058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length31
Mean length15.5976
Min length7

Characters and Unicode

Total characters155976
Distinct characters567
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

Unique177 ?
Unique (%)1.8%

Sample

1st row2341. 일원역 4~5번 출구 사이
2nd row3573.광나루안전체험관
3rd row1662. 노원역7번출구
4th row530. 청계벽산아파트 앞
5th row161. 무악재역1번 출구
ValueCountFrequency (%)
앞 2738
 
9.3%
출구 425
 
1.4%
옆 377
 
1.3%
입구 299
 
1.0%
1번출구 294
 
1.0%
교차로 260
 
0.9%
사거리 226
 
0.8%
3번출구 200
 
0.7%
뒤 162
 
0.6%
2번출구 161
 
0.5%
Other values (4851) 24182
82.5%
2024-03-13T22:01:23.603668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19515
 
12.5%
. 10023
 
6.4%
1 7790
 
5.0%
2 6273
 
4.0%
3 5243
 
3.4%
4 4765
 
3.1%
0 3615
 
2.3%
5 3547
 
2.3%
6 3315
 
2.1%
구 3201
 
2.1%
Other values (557) 88689
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80643
51.7%
Decimal Number 42571
27.3%
Space Separator 19515
 
12.5%
Other Punctuation 10125
 
6.5%
Uppercase Letter 1248
 
0.8%
Close Punctuation 812
 
0.5%
Open Punctuation 812
 
0.5%
Lowercase Letter 154
 
0.1%
Dash Punctuation 63
 
< 0.1%
Math Symbol 18
 
< 0.1%
Other values (3) 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3201
 
4.0%
앞 3192
 
4.0%
역 2308
 
2.9%
동 2215
 
2.7%
번 2031
 
2.5%
출 1969
 
2.4%
교 1732
 
2.1%
아 1585
 
2.0%
파 1582
 
2.0%
트 1458
 
1.8%
Other values (497) 59370
73.6%
Uppercase Letter
ValueCountFrequency (%)
A 148
11.9%
S 143
11.5%
C 119
9.5%
B 105
8.4%
T 103
8.3%
K 97
 
7.8%
D 81
 
6.5%
M 67
 
5.4%
G 66
 
5.3%
P 64
 
5.1%
Other values (13) 255
20.4%
Lowercase Letter
ValueCountFrequency (%)
e 39
25.3%
k 34
22.1%
s 29
18.8%
t 11
 
7.1%
n 10
 
6.5%
v 6
 
3.9%
l 5
 
3.2%
y 5
 
3.2%
h 3
 
1.9%
r 3
 
1.9%
Other values (3) 9
 
5.8%
Decimal Number
ValueCountFrequency (%)
1 7790
18.3%
2 6273
14.7%
3 5243
12.3%
4 4765
11.2%
0 3615
8.5%
5 3547
8.3%
6 3315
7.8%
7 2931
 
6.9%
9 2548
 
6.0%
8 2544
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 10023
99.0%
, 62
 
0.6%
& 19
 
0.2%
? 13
 
0.1%
· 8
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 13
72.2%
+ 5
 
27.8%
Space Separator
ValueCountFrequency (%)
19515
100.0%
Close Punctuation
ValueCountFrequency (%)
) 812
100.0%
Open Punctuation
ValueCountFrequency (%)
( 812
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Other Number
ValueCountFrequency (%)
① 5
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80645
51.7%
Common 73929
47.4%
Latin 1402
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3201
 
4.0%
앞 3192
 
4.0%
역 2308
 
2.9%
동 2215
 
2.7%
번 2031
 
2.5%
출 1969
 
2.4%
교 1732
 
2.1%
아 1585
 
2.0%
파 1582
 
2.0%
트 1458
 
1.8%
Other values (498) 59372
73.6%
Latin
ValueCountFrequency (%)
A 148
 
10.6%
S 143
 
10.2%
C 119
 
8.5%
B 105
 
7.5%
T 103
 
7.3%
K 97
 
6.9%
D 81
 
5.8%
M 67
 
4.8%
G 66
 
4.7%
P 64
 
4.6%
Other values (26) 409
29.2%
Common
ValueCountFrequency (%)
19515
26.4%
. 10023
13.6%
1 7790
 
10.5%
2 6273
 
8.5%
3 5243
 
7.1%
4 4765
 
6.4%
0 3615
 
4.9%
5 3547
 
4.8%
6 3315
 
4.5%
7 2931
 
4.0%
Other values (13) 6912
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80643
51.7%
ASCII 75318
48.3%
None 10
 
< 0.1%
Enclosed Alphanum 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19515
25.9%
. 10023
13.3%
1 7790
 
10.3%
2 6273
 
8.3%
3 5243
 
7.0%
4 4765
 
6.3%
0 3615
 
4.8%
5 3547
 
4.7%
6 3315
 
4.4%
7 2931
 
3.9%
Other values (47) 8301
11.0%
Hangul
ValueCountFrequency (%)
구 3201
 
4.0%
앞 3192
 
4.0%
역 2308
 
2.9%
동 2215
 
2.7%
번 2031
 
2.5%
출 1969
 
2.4%
교 1732
 
2.1%
아 1585
 
2.0%
파 1582
 
2.0%
트 1458
 
1.8%
Other values (497) 59370
73.6%
None
ValueCountFrequency (%)
· 8
80.0%
㈜ 2
 
20.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 5
100.0%

대여구분코드
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정기권
5505 
일일권
4234 
일일권(비회원)
 
261

Length

Max length8
Median length3
Mean length3.1305
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일일권
2nd row정기권
3rd row일일권
4th row일일권
5th row정기권

Common Values

ValueCountFrequency (%)
정기권 5505
55.0%
일일권 4234
42.3%
일일권(비회원) 261
 
2.6%

Length

2024-03-13T22:01:23.791915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:01:23.925476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 5505
55.0%
일일권 4234
42.3%
일일권(비회원 261
 
2.6%

성별
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
M
3518 
<NA>
3266 
F
3215 
m
 
1

Length

Max length4
Median length1
Mean length1.9798
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
M 3518
35.2%
<NA> 3266
32.7%
F 3215
32.1%
m 1
 
< 0.1%

Length

2024-03-13T22:01:24.070743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:01:24.265186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 3519
35.2%
na 3266
32.7%
f 3215
32.1%

연령대코드
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
기타
1702 
20대
1536 
30대
1464 
40대
1436 
~10대
1319 
Other values (3)
2543 

Length

Max length5
Median length3
Mean length3.0381
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row~10대
2nd row30대
3rd row40대
4th row30대
5th row60대

Common Values

ValueCountFrequency (%)
기타 1702
17.0%
20대 1536
15.4%
30대 1464
14.6%
40대 1436
14.4%
~10대 1319
13.2%
50대 1301
13.0%
60대 860
8.6%
70대이상 382
 
3.8%

Length

2024-03-13T22:01:24.465360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:01:24.617883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 1702
17.0%
20대 1536
15.4%
30대 1464
14.6%
40대 1436
14.4%
10대 1319
13.2%
50대 1301
13.0%
60대 860
8.6%
70대이상 382
 
3.8%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct380
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.4573
Minimum1
Maximum1379
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T22:01:24.786562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median13
Q342
95-th percentile165
Maximum1379
Range1378
Interquartile range (IQR)38

Descriptive statistics

Standard deviation71.247763
Coefficient of variation (CV)1.852646
Kurtosis43.340469
Mean38.4573
Median Absolute Deviation (MAD)11
Skewness5.0377308
Sum384573
Variance5076.2438
MonotonicityNot monotonic
2024-03-13T22:01:24.987606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1064
 
10.6%
2 728
 
7.3%
3 578
 
5.8%
4 457
 
4.6%
5 409
 
4.1%
6 357
 
3.6%
7 306
 
3.1%
9 268
 
2.7%
8 255
 
2.5%
10 204
 
2.0%
Other values (370) 5374
53.7%
ValueCountFrequency (%)
1 1064
10.6%
2 728
7.3%
3 578
5.8%
4 457
4.6%
5 409
 
4.1%
6 357
 
3.6%
7 306
 
3.1%
8 255
 
2.5%
9 268
 
2.7%
10 204
 
2.0%
ValueCountFrequency (%)
1379 1
< 0.1%
1012 1
< 0.1%
990 1
< 0.1%
965 1
< 0.1%
875 1
< 0.1%
836 1
< 0.1%
830 1
< 0.1%
771 1
< 0.1%
743 1
< 0.1%
742 1
< 0.1%

운동량
Real number (ℝ)

HIGH CORRELATION 

Distinct9723
Distinct (%)97.3%
Missing4
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2373.2788
Minimum0
Maximum82888.42
Zeros14
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T22:01:25.190111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile41.3025
Q1238.49
median848.995
Q32637.4625
95-th percentile9717.7425
Maximum82888.42
Range82888.42
Interquartile range (IQR)2398.9725

Descriptive statistics

Standard deviation4226.8818
Coefficient of variation (CV)1.7810304
Kurtosis47.892679
Mean2373.2788
Median Absolute Deviation (MAD)741.015
Skewness5.1440013
Sum23723295
Variance17866529
MonotonicityNot monotonic
2024-03-13T22:01:25.409081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 14
 
0.1%
66.92 4
 
< 0.1%
37.32 3
 
< 0.1%
675.92 3
 
< 0.1%
195.06 3
 
< 0.1%
136.42 3
 
< 0.1%
41.62 3
 
< 0.1%
14.67 3
 
< 0.1%
29.09 3
 
< 0.1%
79.76 3
 
< 0.1%
Other values (9713) 9954
99.5%
(Missing) 4
 
< 0.1%
ValueCountFrequency (%)
0.0 14
0.1%
0.01 1
 
< 0.1%
0.1 1
 
< 0.1%
0.74 1
 
< 0.1%
1.29 1
 
< 0.1%
1.36 1
 
< 0.1%
2.55 1
 
< 0.1%
2.78 1
 
< 0.1%
3.47 1
 
< 0.1%
3.49 1
 
< 0.1%
ValueCountFrequency (%)
82888.42 1
< 0.1%
66800.41 1
< 0.1%
63992.42 1
< 0.1%
63691.27 1
< 0.1%
54855.52 1
< 0.1%
52518.45 1
< 0.1%
51607.78 1
< 0.1%
46037.88 1
< 0.1%
43545.95 1
< 0.1%
42292.31 1
< 0.1%

탄소량
Real number (ℝ)

HIGH CORRELATION 

Distinct4077
Distinct (%)40.8%
Missing4
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean20.618779
Minimum0
Maximum678.36
Zeros15
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T22:01:25.595582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.38
Q12.19
median7.655
Q323.285
95-th percentile84.6975
Maximum678.36
Range678.36
Interquartile range (IQR)21.095

Descriptive statistics

Standard deviation36.038424
Coefficient of variation (CV)1.7478448
Kurtosis47.833811
Mean20.618779
Median Absolute Deviation (MAD)6.645
Skewness5.1380448
Sum206105.31
Variance1298.768
MonotonicityNot monotonic
2024-03-13T22:01:25.805313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.72 23
 
0.2%
0.79 23
 
0.2%
0.26 22
 
0.2%
0.38 22
 
0.2%
0.3 22
 
0.2%
0.15 22
 
0.2%
0.41 20
 
0.2%
0.21 20
 
0.2%
0.87 20
 
0.2%
0.44 20
 
0.2%
Other values (4067) 9782
97.8%
ValueCountFrequency (%)
0.0 15
0.1%
0.01 2
 
< 0.1%
0.02 1
 
< 0.1%
0.03 2
 
< 0.1%
0.04 5
 
0.1%
0.05 6
 
0.1%
0.06 2
 
< 0.1%
0.07 6
 
0.1%
0.08 5
 
0.1%
0.09 12
0.1%
ValueCountFrequency (%)
678.36 1
< 0.1%
575.18 1
< 0.1%
536.22 1
< 0.1%
533.98 1
< 0.1%
528.87 1
< 0.1%
496.81 1
< 0.1%
415.72 1
< 0.1%
404.24 1
< 0.1%
375.98 1
< 0.1%
375.15 1
< 0.1%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION 

Distinct9738
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89165.805
Minimum0
Maximum2925518.3
Zeros13
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T22:01:25.989123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1641.216
Q19460.8475
median33021.535
Q3100635.65
95-th percentile365993.62
Maximum2925518.3
Range2925518.3
Interquartile range (IQR)91174.805

Descriptive statistics

Standard deviation155862.52
Coefficient of variation (CV)1.7480078
Kurtosis47.792857
Mean89165.805
Median Absolute Deviation (MAD)28659.855
Skewness5.1381406
Sum8.9165805 × 108
Variance2.4293125 × 1010
MonotonicityNot monotonic
2024-03-13T22:01:26.201394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 13
 
0.1%
1130.0 5
 
0.1%
1450.0 5
 
0.1%
1030.0 5
 
0.1%
650.0 5
 
0.1%
1620.0 4
 
< 0.1%
2370.0 4
 
< 0.1%
390.0 4
 
< 0.1%
720.0 4
 
< 0.1%
800.0 4
 
< 0.1%
Other values (9728) 9947
99.5%
ValueCountFrequency (%)
0.0 13
0.1%
0.2 1
 
< 0.1%
4.86 1
 
< 0.1%
50.0 1
 
< 0.1%
88.18 1
 
< 0.1%
130.0 1
 
< 0.1%
134.83 1
 
< 0.1%
140.0 1
 
< 0.1%
170.65 1
 
< 0.1%
176.18 1
 
< 0.1%
ValueCountFrequency (%)
2925518.33 1
< 0.1%
2488112.26 1
< 0.1%
2313933.08 1
< 0.1%
2302736.5 1
< 0.1%
2299519.83 1
< 0.1%
2163973.94 1
< 0.1%
1792015.74 1
< 0.1%
1743446.04 1
< 0.1%
1631799.62 1
< 0.1%
1620689.62 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct2535
Distinct (%)25.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean767.1719
Minimum1
Maximum23633
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T22:01:26.396256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14
Q187
median291.5
Q3893.25
95-th percentile3074.1
Maximum23633
Range23632
Interquartile range (IQR)806.25

Descriptive statistics

Standard deviation1301.3656
Coefficient of variation (CV)1.6963155
Kurtosis35.759285
Mean767.1719
Median Absolute Deviation (MAD)250.5
Skewness4.5355159
Sum7671719
Variance1693552.4
MonotonicityNot monotonic
2024-03-13T22:01:26.638164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 50
 
0.5%
4 47
 
0.5%
12 47
 
0.5%
16 46
 
0.5%
11 45
 
0.4%
6 44
 
0.4%
17 44
 
0.4%
9 43
 
0.4%
13 43
 
0.4%
23 42
 
0.4%
Other values (2525) 9549
95.5%
ValueCountFrequency (%)
1 7
 
0.1%
2 20
 
0.2%
3 20
 
0.2%
4 47
0.5%
5 37
0.4%
6 44
0.4%
7 40
0.4%
8 50
0.5%
9 43
0.4%
10 39
0.4%
ValueCountFrequency (%)
23633 1
< 0.1%
18909 1
< 0.1%
16862 1
< 0.1%
16760 1
< 0.1%
16155 1
< 0.1%
15712 1
< 0.1%
14338 1
< 0.1%
12827 1
< 0.1%
12380 1
< 0.1%
11978 1
< 0.1%

Interactions

2024-03-13T22:01:20.387717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:16.306426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:17.045258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:17.995711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:18.789963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:19.552969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:20.502079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:16.424003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:17.183744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:18.124440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:18.916065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:19.683207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:20.646710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:16.551164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:17.370291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:18.271727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:19.053678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:19.853903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:20.779864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:16.666610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:17.553932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:18.401209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:19.171446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:19.999904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:20.892028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:16.798575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:17.716828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:18.562182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:19.292561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:20.136853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:21.035417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:16.929106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:17.874393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:18.676337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:19.439039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:01:20.271569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:01:26.803387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
대여소번호1.0000.0000.0000.0000.0440.0390.0370.0380.052
대여구분코드0.0001.0000.0000.3830.3370.2220.2270.2260.246
성별0.0000.0001.0000.0780.1500.1610.1660.1670.104
연령대코드0.0000.3830.0781.0000.2010.1800.1930.1930.194
이용건수0.0440.3370.1500.2011.0000.8530.8580.8570.869
운동량0.0390.2220.1610.1800.8531.0000.9900.9880.964
탄소량0.0370.2270.1660.1930.8580.9901.0001.0000.966
이동거리(M)0.0380.2260.1670.1930.8570.9881.0001.0000.965
이용시간(분)0.0520.2460.1040.1940.8690.9640.9660.9651.000
2024-03-13T22:01:26.972450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여구분코드성별연령대코드
대여구분코드1.0000.0000.264
성별0.0001.0000.049
연령대코드0.2640.0491.000
2024-03-13T22:01:27.130267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수운동량탄소량이동거리(M)이용시간(분)대여구분코드성별연령대코드
대여소번호1.000-0.061-0.058-0.060-0.059-0.0700.0000.0000.000
이용건수-0.0611.0000.9400.9430.9430.9440.1570.0660.099
운동량-0.0580.9401.0000.9970.9970.9710.1360.0970.086
탄소량-0.0600.9430.9971.0001.0000.9750.1380.0730.093
이동거리(M)-0.0590.9430.9971.0001.0000.9750.1380.0740.093
이용시간(분)-0.0700.9440.9710.9750.9751.0000.1510.0620.094
대여구분코드0.0000.1570.1360.1380.1380.1511.0000.0000.264
성별0.0000.0660.0970.0730.0740.0620.0001.0000.049
연령대코드0.0000.0990.0860.0930.0930.0940.2640.0491.000

Missing values

2024-03-13T22:01:21.183876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:01:21.377993image/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.
2024-03-13T22:01:21.595099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

대여일자대여소번호대여소명대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
6103920230723412341. 일원역 4~5번 출구 사이일일권F~10대284.550.773284.6346
7590120230735733573.광나루안전체험관정기권M30대1357409.055.48239159.222111
4495220230716621662. 노원역7번출구일일권<NA>40대161739.7814.3261725.28444
13937202307530530. 청계벽산아파트 앞일일권<NA>30대10316.893.0112975.2891
2034202307161161. 무악재역1번 출구정기권M60대211789.1714.6963278.65394
8873020230743034303. 매헌역 2번출구앞광역버스 정류장앞(22-297)일일권<NA>40대3232.41.968444.0154
7439320230735203520. 광진경찰서정기권<NA>기타852949.5929.29126145.56717
3416620230712301230. 송파중학교 정문정기권F~10대14579.566.8629499.73245
2752720230710191019. 다성이즈빌아파트(호원대 대각선 맞은편)정기권M30대42820670.91166.15718510.237616
7916920230737263726.삼양동사거리일일권<NA>30대286.480.753259.1921
대여일자대여소번호대여소명대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
16166202307602602. 장안동 사거리일일권<NA>50대3145.881.215251.2451
4230220230715301530. 광산사거리정기권<NA>~10대3203.42.179338.664
15441202307576576. 광나루역 3번 출구정기권M40대19615645.92122.84529784.395292
25511202307949949. 연신내역 1번 출구일일권F20대201049.8510.5245354.28547
8377202307355355. 서울사대부설초등학교 앞일일권<NA>50대130.150.251087.778
8256120230739273927. 구로월드아파트 앞정기권<NA>20대1577394.7867.08292428.82341
8196720230739053905. 희훈타워빌 앞정기권M30대30111745.4897.8423895.044747
2928920230710731073. SSTS 몰 앞정기권F기타13475.094.6119787.92150
7731820230736463646. 선정릉역 4번 출구정기권M20대281700.114.562540.93501
4229420230715301530. 광산사거리일일권M~10대353366.3228.53122836.91952