Overview

Dataset statistics

Number of variables20
Number of observations27
Missing cells14
Missing cells (%)2.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory168.9 B

Variable types

Categorical10
Text4
Numeric4
Boolean2

Dataset

Description자전거 대여소 현황(제공표준)
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=4H10S6E632620W0J522E21499858&infSeq=1

Alerts

자전거대여소구분 has constant value ""Constant
공기주입기비치여부 has constant value ""Constant
자전거이용요금 is highly overall correlated with 위도 and 10 other fieldsHigh correlation
데이터기준일자 is highly overall correlated with 위도 and 10 other fieldsHigh correlation
수리대설치여부 is highly overall correlated with 경도 and 7 other fieldsHigh correlation
휴무일 is highly overall correlated with 위도 and 11 other fieldsHigh correlation
관리기관명 is highly overall correlated with 위도 and 11 other fieldsHigh correlation
요금구분 is highly overall correlated with 경도 and 6 other fieldsHigh correlation
시군명 is highly overall correlated with 위도 and 11 other fieldsHigh correlation
위도 is highly overall correlated with 시군명 and 6 other fieldsHigh correlation
경도 is highly overall correlated with 시군명 and 7 other fieldsHigh correlation
자전거보유대수 is highly overall correlated with 시군명 and 5 other fieldsHigh correlation
거치대수 is highly overall correlated with 수리대설치여부High correlation
운영시작시각 is highly overall correlated with 시군명 and 5 other fieldsHigh correlation
운영종료시각 is highly overall correlated with 위도 and 4 other fieldsHigh correlation
공기주입기유형 is highly overall correlated with 위도 and 5 other fieldsHigh correlation
수리대설치여부 is highly imbalanced (61.9%)Imbalance
소재지도로명주소 has 5 (18.5%) missing valuesMissing
거치대수 has 9 (33.3%) missing valuesMissing
자전거대여소명 has unique valuesUnique
소재지지번주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-05-03 19:06:27.646396
Analysis finished2024-05-03 19:06:43.002596
Duration15.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
과천시
8 
부천시
5 
수원시
3 
이천시
2 
평택시
2 
Other values (5)
7 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique3 ?
Unique (%)11.1%

Sample

1st row과천시
2nd row과천시
3rd row과천시
4th row이천시
5th row이천시

Common Values

ValueCountFrequency (%)
과천시 8
29.6%
부천시 5
18.5%
수원시 3
 
11.1%
이천시 2
 
7.4%
평택시 2
 
7.4%
오산시 2
 
7.4%
시흥시 2
 
7.4%
김포시 1
 
3.7%
가평군 1
 
3.7%
광명시 1
 
3.7%

Length

2024-05-03T19:06:43.303032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T19:06:43.817429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
과천시 8
29.6%
부천시 5
18.5%
수원시 3
 
11.1%
이천시 2
 
7.4%
평택시 2
 
7.4%
오산시 2
 
7.4%
시흥시 2
 
7.4%
김포시 1
 
3.7%
가평군 1
 
3.7%
광명시 1
 
3.7%

자전거대여소명
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2024-05-03T19:06:44.460657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length17
Mean length13.518519
Min length4

Characters and Unicode

Total characters365
Distinct characters106
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row갈현동(정보과학도서관 앞)
2nd row중앙동(시민회관 앞)
3rd row주암동(주암체육공원 입구)
4th row신둔천 자전거대여소
5th row복하천 자전거대여소
ValueCountFrequency (%)
공공자전거대여소 7
 
13.5%
자전거대여소 4
 
7.7%
앞 3
 
5.8%
갈현동(정보과학도서관 1
 
1.9%
월곶역 1
 
1.9%
오산천 1
 
1.9%
맑음터공원 1
 
1.9%
자라섬자전거대여소 1
 
1.9%
광교산공영자전거대여소(반딧불이쉼터 1
 
1.9%
광교산공영자전거대여소(버스종점 1
 
1.9%
Other values (31) 31
59.6%
2024-05-03T19:06:45.452997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
 
6.8%
공 24
 
6.6%
자 20
 
5.5%
거 19
 
5.2%
전 19
 
5.2%
대 17
 
4.7%
여 17
 
4.7%
소 17
 
4.7%
( 13
 
3.6%
) 13
 
3.6%
Other values (96) 181
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 309
84.7%
Space Separator 25
 
6.8%
Open Punctuation 13
 
3.6%
Close Punctuation 13
 
3.6%
Decimal Number 5
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 24
 
7.8%
자 20
 
6.5%
거 19
 
6.1%
전 19
 
6.1%
대 17
 
5.5%
여 17
 
5.5%
소 17
 
5.5%
천 10
 
3.2%
역 8
 
2.6%
동 7
 
2.3%
Other values (90) 151
48.9%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
2 2
40.0%
4 1
20.0%
Space Separator
ValueCountFrequency (%)
25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 309
84.7%
Common 56
 
15.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 24
 
7.8%
자 20
 
6.5%
거 19
 
6.1%
전 19
 
6.1%
대 17
 
5.5%
여 17
 
5.5%
소 17
 
5.5%
천 10
 
3.2%
역 8
 
2.6%
동 7
 
2.3%
Other values (90) 151
48.9%
Common
ValueCountFrequency (%)
25
44.6%
( 13
23.2%
) 13
23.2%
1 2
 
3.6%
2 2
 
3.6%
4 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 309
84.7%
ASCII 56
 
15.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
44.6%
( 13
23.2%
) 13
23.2%
1 2
 
3.6%
2 2
 
3.6%
4 1
 
1.8%
Hangul
ValueCountFrequency (%)
공 24
 
7.8%
자 20
 
6.5%
거 19
 
6.1%
전 19
 
6.1%
대 17
 
5.5%
여 17
 
5.5%
소 17
 
5.5%
천 10
 
3.2%
역 8
 
2.6%
동 7
 
2.3%
Other values (90) 151
48.9%

자전거대여소구분
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
유인대여소
27 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유인대여소 27
100.0%

Length

2024-05-03T19:06:45.832463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T19:06:46.356382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유인대여소 27
100.0%

소재지도로명주소
Text

MISSING 

Distinct21
Distinct (%)95.5%
Missing5
Missing (%)18.5%
Memory size348.0 B
2024-05-03T19:06:46.950379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length18
Min length13

Characters and Unicode

Total characters396
Distinct characters74
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)90.9%

Sample

1st row경기도 과천시 중앙로 24
2nd row경기도 과천시 통영로 5
3rd row경기도 과천시 장군마을길 62-1
4th row경기도 이천시 경충대로2422번길 17
5th row경기도 부천시 원미구 길주로 191
ValueCountFrequency (%)
경기도 22
22.2%
과천시 6
 
6.1%
부천시 4
 
4.0%
원미구 4
 
4.0%
오산천로 2
 
2.0%
오산시 2
 
2.0%
36 2
 
2.0%
수원시 2
 
2.0%
도서관길 2
 
2.0%
시흥시 2
 
2.0%
Other values (48) 51
51.5%
2024-05-03T19:06:48.193795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
77
19.4%
도 24
 
6.1%
경 23
 
5.8%
시 23
 
5.8%
기 22
 
5.6%
로 19
 
4.8%
1 16
 
4.0%
천 14
 
3.5%
2 11
 
2.8%
길 9
 
2.3%
Other values (64) 158
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 248
62.6%
Space Separator 77
 
19.4%
Decimal Number 68
 
17.2%
Dash Punctuation 3
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 24
 
9.7%
경 23
 
9.3%
시 23
 
9.3%
기 22
 
8.9%
로 19
 
7.7%
천 14
 
5.6%
길 9
 
3.6%
과 6
 
2.4%
구 6
 
2.4%
원 6
 
2.4%
Other values (52) 96
38.7%
Decimal Number
ValueCountFrequency (%)
1 16
23.5%
2 11
16.2%
6 9
13.2%
4 8
11.8%
5 6
 
8.8%
7 5
 
7.4%
0 5
 
7.4%
3 3
 
4.4%
8 3
 
4.4%
9 2
 
2.9%
Space Separator
ValueCountFrequency (%)
77
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 248
62.6%
Common 148
37.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 24
 
9.7%
경 23
 
9.3%
시 23
 
9.3%
기 22
 
8.9%
로 19
 
7.7%
천 14
 
5.6%
길 9
 
3.6%
과 6
 
2.4%
구 6
 
2.4%
원 6
 
2.4%
Other values (52) 96
38.7%
Common
ValueCountFrequency (%)
77
52.0%
1 16
 
10.8%
2 11
 
7.4%
6 9
 
6.1%
4 8
 
5.4%
5 6
 
4.1%
7 5
 
3.4%
0 5
 
3.4%
- 3
 
2.0%
3 3
 
2.0%
Other values (2) 5
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 248
62.6%
ASCII 148
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77
52.0%
1 16
 
10.8%
2 11
 
7.4%
6 9
 
6.1%
4 8
 
5.4%
5 6
 
4.1%
7 5
 
3.4%
0 5
 
3.4%
- 3
 
2.0%
3 3
 
2.0%
Other values (2) 5
 
3.4%
Hangul
ValueCountFrequency (%)
도 24
 
9.7%
경 23
 
9.3%
시 23
 
9.3%
기 22
 
8.9%
로 19
 
7.7%
천 14
 
5.6%
길 9
 
3.6%
과 6
 
2.4%
구 6
 
2.4%
원 6
 
2.4%
Other values (52) 96
38.7%

소재지지번주소
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2024-05-03T19:06:49.396625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length17.925926
Min length13

Characters and Unicode

Total characters484
Distinct characters74
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row경기도 과천시 갈현동 677
2nd row경기도 과천시 중앙동 6-2
3rd row경기도 과천시 주암동 53
4th row경기도 이천시 송정동 427
5th row경기도 이천시 진리동 140
ValueCountFrequency (%)
경기도 27
22.7%
과천시 8
 
6.7%
부천시 5
 
4.2%
원미구 4
 
3.4%
별양동 3
 
2.5%
수원시 3
 
2.5%
오산동 2
 
1.7%
평택시 2
 
1.7%
장안구 2
 
1.7%
시흥시 2
 
1.7%
Other values (58) 61
51.3%
2024-05-03T19:06:50.590535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
94
19.4%
시 28
 
5.8%
경 27
 
5.6%
도 27
 
5.6%
기 27
 
5.6%
동 23
 
4.8%
- 19
 
3.9%
1 17
 
3.5%
천 16
 
3.3%
2 13
 
2.7%
Other values (64) 193
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 276
57.0%
Decimal Number 95
 
19.6%
Space Separator 94
 
19.4%
Dash Punctuation 19
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 28
 
10.1%
경 27
 
9.8%
도 27
 
9.8%
기 27
 
9.8%
동 23
 
8.3%
천 16
 
5.8%
과 9
 
3.3%
원 8
 
2.9%
구 8
 
2.9%
오 6
 
2.2%
Other values (52) 97
35.1%
Decimal Number
ValueCountFrequency (%)
1 17
17.9%
2 13
13.7%
5 12
12.6%
7 12
12.6%
3 10
10.5%
4 8
8.4%
0 7
7.4%
6 7
7.4%
8 5
 
5.3%
9 4
 
4.2%
Space Separator
ValueCountFrequency (%)
94
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 276
57.0%
Common 208
43.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 28
 
10.1%
경 27
 
9.8%
도 27
 
9.8%
기 27
 
9.8%
동 23
 
8.3%
천 16
 
5.8%
과 9
 
3.3%
원 8
 
2.9%
구 8
 
2.9%
오 6
 
2.2%
Other values (52) 97
35.1%
Common
ValueCountFrequency (%)
94
45.2%
- 19
 
9.1%
1 17
 
8.2%
2 13
 
6.2%
5 12
 
5.8%
7 12
 
5.8%
3 10
 
4.8%
4 8
 
3.8%
0 7
 
3.4%
6 7
 
3.4%
Other values (2) 9
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 276
57.0%
ASCII 208
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
94
45.2%
- 19
 
9.1%
1 17
 
8.2%
2 13
 
6.2%
5 12
 
5.8%
7 12
 
5.8%
3 10
 
4.8%
4 8
 
3.8%
0 7
 
3.4%
6 7
 
3.4%
Other values (2) 9
 
4.3%
Hangul
ValueCountFrequency (%)
시 28
 
10.1%
경 27
 
9.8%
도 27
 
9.8%
기 27
 
9.8%
동 23
 
8.3%
천 16
 
5.8%
과 9
 
3.3%
원 8
 
2.9%
구 8
 
2.9%
오 6
 
2.2%
Other values (52) 97
35.1%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.384732
Minimum36.990703
Maximum37.820894
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-05-03T19:06:50.988293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.990703
5-th percentile37.043403
Q137.302216
median37.427349
Q337.475788
95-th percentile37.574541
Maximum37.820894
Range0.83019092
Interquartile range (IQR)0.17357117

Descriptive statistics

Standard deviation0.17414119
Coefficient of variation (CV)0.0046580833
Kurtosis1.4469058
Mean37.384732
Median Absolute Deviation (MAD)0.07779835
Skewness-0.35642351
Sum1009.3878
Variance0.030325155
MonotonicityNot monotonic
2024-05-03T19:06:51.518706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
37.41841573 1
 
3.7%
37.42776096 1
 
3.7%
37.4306703 1
 
3.7%
37.4668954975 1
 
3.7%
37.48797014 1
 
3.7%
37.50639109 1
 
3.7%
37.391814 1
 
3.7%
37.351777 1
 
3.7%
37.2813308 1
 
3.7%
37.33454984 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
36.99070308 1
3.7%
37.00277051 1
3.7%
37.13821264 1
3.7%
37.1555814225 1
3.7%
37.26774009 1
3.7%
37.2813308 1
3.7%
37.30183304 1
3.7%
37.30259965 1
3.7%
37.33454984 1
3.7%
37.351777 1
3.7%
ValueCountFrequency (%)
37.820894 1
3.7%
37.59765925 1
3.7%
37.52059691 1
3.7%
37.50639109 1
3.7%
37.50514715 1
3.7%
37.48797014 1
3.7%
37.48467954 1
3.7%
37.4668954975 1
3.7%
37.46160431 1
3.7%
37.4538059 1
3.7%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98607
Minimum126.74271
Maximum127.52104
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-05-03T19:06:51.879622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.74271
5-th percentile126.74635
Q1126.78443
median126.99493
Q3127.03243
95-th percentile127.45379
Maximum127.52104
Range0.778336
Interquartile range (IQR)0.24800005

Descriptive statistics

Standard deviation0.21248218
Coefficient of variation (CV)0.0016732716
Kurtosis1.2846597
Mean126.98607
Median Absolute Deviation (MAD)0.075734784
Skewness1.1251743
Sum3428.6238
Variance0.045148678
MonotonicityNot monotonic
2024-05-03T19:06:52.412022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
126.989355 1
 
3.7%
126.9907412 1
 
3.7%
126.9949293 1
 
3.7%
126.8453131963 1
 
3.7%
126.7550005 1
 
3.7%
126.7541356 1
 
3.7%
126.742708 1
 
3.7%
126.7430094 1
 
3.7%
127.0160807 1
 
3.7%
127.0174003 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
126.742708 1
3.7%
126.7430094 1
3.7%
126.7541356 1
3.7%
126.7550005 1
3.7%
126.7606764 1
3.7%
126.7638876 1
3.7%
126.7818758 1
3.7%
126.7869752 1
3.7%
126.8453131963 1
3.7%
126.9781105 1
3.7%
ValueCountFrequency (%)
127.521044 1
3.7%
127.4600623 1
3.7%
127.4391636 1
3.7%
127.0884359 1
3.7%
127.0706640836 1
3.7%
127.064528 1
3.7%
127.0325123 1
3.7%
127.0323388 1
3.7%
127.0174003 1
3.7%
127.0160807 1
3.7%

운영시작시각
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size348.0 B
09:00
17 
10:00
8 
07:00
 
1
11:30
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique2 ?
Unique (%)7.4%

Sample

1st row09:00
2nd row09:00
3rd row09:00
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
09:00 17
63.0%
10:00 8
29.6%
07:00 1
 
3.7%
11:30 1
 
3.7%

Length

2024-05-03T19:06:52.831192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T19:06:53.150149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09:00 17
63.0%
10:00 8
29.6%
07:00 1
 
3.7%
11:30 1
 
3.7%

운영종료시각
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size348.0 B
18:00
19 
17:00
3 
22:00
2 
19:00
 
1
21:00
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique3 ?
Unique (%)11.1%

Sample

1st row18:00
2nd row18:00
3rd row18:00
4th row18:00
5th row18:00

Common Values

ValueCountFrequency (%)
18:00 19
70.4%
17:00 3
 
11.1%
22:00 2
 
7.4%
19:00 1
 
3.7%
21:00 1
 
3.7%
20:00 1
 
3.7%

Length

2024-05-03T19:06:53.545470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T19:06:53.929002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
18:00 19
70.4%
17:00 3
 
11.1%
22:00 2
 
7.4%
19:00 1
 
3.7%
21:00 1
 
3.7%
20:00 1
 
3.7%

휴무일
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
월요일+화요일+국경일
8 
토요일+일요일+공휴일
4 
동절기
3 
매주 월요일+명절 당일
2 
월+명절+성탄절
2 
Other values (7)
8 

Length

Max length42
Median length17
Mean length12.222222
Min length3

Unique

Unique6 ?
Unique (%)22.2%

Sample

1st row월요일+화요일+국경일
2nd row월요일+화요일+국경일
3rd row월요일+화요일+국경일
4th row매주 월요일+명절 당일
5th row매주 월요일+명절 당일

Common Values

ValueCountFrequency (%)
월요일+화요일+국경일 8
29.6%
토요일+일요일+공휴일 4
14.8%
동절기 3
 
11.1%
매주 월요일+명절 당일 2
 
7.4%
월+명절+성탄절 2
 
7.4%
매주 월요일 휴무 2
 
7.4%
금요일+공휴일 1
 
3.7%
3월~11월까지 주말에만 운영 1
 
3.7%
동절기(12월+1월+2월+3월) 1
 
3.7%
토+일+기타공휴일/동절기 휴관 2023.12.01. ~ 2024.03.03. 1
 
3.7%
Other values (2) 2
 
7.4%

Length

2024-05-03T19:06:54.362723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
월요일+화요일+국경일 8
17.8%
매주 4
 
8.9%
토요일+일요일+공휴일 4
 
8.9%
동절기 3
 
6.7%
휴관 2
 
4.4%
월요일+명절 2
 
4.4%
당일 2
 
4.4%
월+명절+성탄절 2
 
4.4%
월요일 2
 
4.4%
휴무 2
 
4.4%
Other values (12) 14
31.1%

요금구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size348.0 B
무료
19 
유료
7 
혼합
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row무료
2nd row무료
3rd row무료
4th row유료
5th row유료

Common Values

ValueCountFrequency (%)
무료 19
70.4%
유료 7
 
25.9%
혼합 1
 
3.7%

Length

2024-05-03T19:06:54.841105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T19:06:55.189872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무료 19
70.4%
유료 7
 
25.9%
혼합 1
 
3.7%

자전거이용요금
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Memory size348.0 B
무료
17 
1일 1천원
3 
(1인용) 30분 1500원 60분 2000원 추가 10분당 1000원+(2인용) 30분 2000원 60분 3000원 추가 10분당 1000원+(5인승) 30분 10000원 60분 20000원 추가 10분당 3000원+(8인승) 30분 15000원 60분 25000원 추가 10분당 3000원+(1인승전기자전거) 30분 7000원 60분 12000원 추가 10분당 2000원+(2인승 전기자전거) 30분 12000원 60분 20000원 추가 10분
2 
<NA>
2 
1인승 1시간 6000원+2인승 1시간 10000원+추가요금 10분당 1000원
 
1
Other values (2)
2 

Length

Max length250
Median length2
Mean length23.481481
Min length2

Unique

Unique3 ?
Unique (%)11.1%

Sample

1st row무료
2nd row무료
3rd row무료
4th row(1인용) 30분 1500원 60분 2000원 추가 10분당 1000원+(2인용) 30분 2000원 60분 3000원 추가 10분당 1000원+(5인승) 30분 10000원 60분 20000원 추가 10분당 3000원+(8인승) 30분 15000원 60분 25000원 추가 10분당 3000원+(1인승전기자전거) 30분 7000원 60분 12000원 추가 10분당 2000원+(2인승 전기자전거) 30분 12000원 60분 20000원 추가 10분
5th row(1인용) 30분 1500원 60분 2000원 추가 10분당 1000원+(2인용) 30분 2000원 60분 3000원 추가 10분당 1000원+(5인승) 30분 10000원 60분 20000원 추가 10분당 3000원+(8인승) 30분 15000원 60분 25000원 추가 10분당 3000원+(1인승전기자전거) 30분 7000원 60분 12000원 추가 10분당 2000원+(2인승 전기자전거) 30분 12000원 60분 20000원 추가 10분

Common Values

ValueCountFrequency (%)
무료 17
63.0%
1일 1천원 3
 
11.1%
(1인용) 30분 1500원 60분 2000원 추가 10분당 1000원+(2인용) 30분 2000원 60분 3000원 추가 10분당 1000원+(5인승) 30분 10000원 60분 20000원 추가 10분당 3000원+(8인승) 30분 15000원 60분 25000원 추가 10분당 3000원+(1인승전기자전거) 30분 7000원 60분 12000원 추가 10분당 2000원+(2인승 전기자전거) 30분 12000원 60분 20000원 추가 10분 2
 
7.4%
<NA> 2
 
7.4%
1인승 1시간 6000원+2인승 1시간 10000원+추가요금 10분당 1000원 1
 
3.7%
30분당 3000원 1
 
3.7%
1시간 무료 초과 10분당 1000원 1
 
3.7%

Length

2024-05-03T19:06:55.930434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T19:06:56.656820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무료 18
14.4%
30분 12
 
9.6%
추가 12
 
9.6%
60분 12
 
9.6%
10분당 12
 
9.6%
2000원 4
 
3.2%
20000원 4
 
3.2%
12000원 4
 
3.2%
1시간 3
 
2.4%
1천원 3
 
2.4%
Other values (22) 41
32.8%

자전거보유대수
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.518519
Minimum15
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-05-03T19:06:57.472470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile16.5
Q121
median50
Q396
95-th percentile153.7
Maximum300
Range285
Interquartile range (IQR)75

Descriptive statistics

Standard deviation64.504842
Coefficient of variation (CV)0.90193202
Kurtosis4.8446235
Mean71.518519
Median Absolute Deviation (MAD)30
Skewness1.9183896
Sum1931
Variance4160.8746
MonotonicityNot monotonic
2024-05-03T19:06:57.950196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
20 5
18.5%
15 2
 
7.4%
50 1
 
3.7%
30 1
 
3.7%
100 1
 
3.7%
39 1
 
3.7%
35 1
 
3.7%
140 1
 
3.7%
154 1
 
3.7%
73 1
 
3.7%
Other values (12) 12
44.4%
ValueCountFrequency (%)
15 2
 
7.4%
20 5
18.5%
22 1
 
3.7%
30 1
 
3.7%
31 1
 
3.7%
35 1
 
3.7%
39 1
 
3.7%
40 1
 
3.7%
50 1
 
3.7%
60 1
 
3.7%
ValueCountFrequency (%)
300 1
3.7%
154 1
3.7%
153 1
3.7%
141 1
3.7%
140 1
3.7%
119 1
3.7%
100 1
3.7%
92 1
3.7%
80 1
3.7%
73 1
3.7%

거치대수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)50.0%
Missing9
Missing (%)33.3%
Infinite0
Infinite (%)0.0%
Mean76.555556
Minimum20
Maximum600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-05-03T19:06:58.714572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile20
Q120
median26
Q345
95-th percentile243
Maximum600
Range580
Interquartile range (IQR)25

Descriptive statistics

Standard deviation139.0312
Coefficient of variation (CV)1.8160824
Kurtosis13.287599
Mean76.555556
Median Absolute Deviation (MAD)6
Skewness3.5202046
Sum1378
Variance19329.673
MonotonicityNot monotonic
2024-05-03T19:06:59.615389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
20 7
25.9%
30 4
14.8%
50 1
 
3.7%
180 1
 
3.7%
22 1
 
3.7%
92 1
 
3.7%
153 1
 
3.7%
21 1
 
3.7%
600 1
 
3.7%
(Missing) 9
33.3%
ValueCountFrequency (%)
20 7
25.9%
21 1
 
3.7%
22 1
 
3.7%
30 4
14.8%
50 1
 
3.7%
92 1
 
3.7%
153 1
 
3.7%
180 1
 
3.7%
600 1
 
3.7%
ValueCountFrequency (%)
600 1
 
3.7%
180 1
 
3.7%
153 1
 
3.7%
92 1
 
3.7%
50 1
 
3.7%
30 4
14.8%
22 1
 
3.7%
21 1
 
3.7%
20 7
25.9%

공기주입기비치여부
Boolean

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size159.0 B
True
27 
ValueCountFrequency (%)
True 27
100.0%
2024-05-03T19:07:00.198098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

공기주입기유형
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size348.0 B
수동식
13 
기계식
11 
<NA>
3 

Length

Max length4
Median length3
Mean length3.1111111
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수동식 13
48.1%
기계식 11
40.7%
<NA> 3
 
11.1%

Length

2024-05-03T19:07:00.603621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T19:07:00.963302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수동식 13
48.1%
기계식 11
40.7%
na 3
 
11.1%

수리대설치여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size159.0 B
False
25 
True
 
2
ValueCountFrequency (%)
False 25
92.6%
True 2
 
7.4%
2024-05-03T19:07:01.419094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

관리기관전화번호
Text

Distinct14
Distinct (%)51.9%
Missing0
Missing (%)0.0%
Memory size348.0 B
2024-05-03T19:07:01.993769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.111111
Min length12

Characters and Unicode

Total characters327
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)29.6%

Sample

1st row02-3677-2289
2nd row02-3677-2291
3rd row02-3677-2290
4th row031-631-7875
5th row031-631-7879
ValueCountFrequency (%)
032-625-9093 5
18.5%
02-3677-2288 5
18.5%
031-228-3504 3
11.1%
031-658-4788 2
 
7.4%
031-8036-7704 2
 
7.4%
031-310-3138 2
 
7.4%
02-3677-2289 1
 
3.7%
02-3677-2291 1
 
3.7%
02-3677-2290 1
 
3.7%
031-631-7875 1
 
3.7%
Other values (4) 4
14.8%
2024-05-03T19:07:03.565685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 54
16.5%
3 46
14.1%
0 44
13.5%
2 43
13.1%
8 31
9.5%
7 30
9.2%
6 21
 
6.4%
1 21
 
6.4%
9 17
 
5.2%
5 12
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 273
83.5%
Dash Punctuation 54
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 46
16.8%
0 44
16.1%
2 43
15.8%
8 31
11.4%
7 30
11.0%
6 21
7.7%
1 21
7.7%
9 17
 
6.2%
5 12
 
4.4%
4 8
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 327
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 54
16.5%
3 46
14.1%
0 44
13.5%
2 43
13.1%
8 31
9.5%
7 30
9.2%
6 21
 
6.4%
1 21
 
6.4%
9 17
 
5.2%
5 12
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 327
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 54
16.5%
3 46
14.1%
0 44
13.5%
2 43
13.1%
8 31
9.5%
7 30
9.2%
6 21
 
6.4%
1 21
 
6.4%
9 17
 
5.2%
5 12
 
3.7%

관리기관명
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
경기도 과천시청
8 
경기도 부천시청
5 
경기도 수원시청
3 
이천시장애인자립생활센터
2 
평택지역자활센터
2 
Other values (5)
7 

Length

Max length16
Median length8
Mean length8.6296296
Min length8

Unique

Unique3 ?
Unique (%)11.1%

Sample

1st row경기도 과천시청
2nd row경기도 과천시청
3rd row경기도 과천시청
4th row이천시장애인자립생활센터
5th row이천시장애인자립생활센터

Common Values

ValueCountFrequency (%)
경기도 과천시청 8
29.6%
경기도 부천시청 5
18.5%
경기도 수원시청 3
 
11.1%
이천시장애인자립생활센터 2
 
7.4%
평택지역자활센터 2
 
7.4%
경기도 오산시청 2
 
7.4%
경기도 시흥시청 2
 
7.4%
㈜워터웨이플러스 1
 
3.7%
가평군시설관리공단 1
 
3.7%
경기도 광명시 경륜경정사업본부 1
 
3.7%

Length

2024-05-03T19:07:04.375472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T19:07:05.166372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 21
42.9%
과천시청 8
 
16.3%
부천시청 5
 
10.2%
수원시청 3
 
6.1%
이천시장애인자립생활센터 2
 
4.1%
평택지역자활센터 2
 
4.1%
오산시청 2
 
4.1%
시흥시청 2
 
4.1%
㈜워터웨이플러스 1
 
2.0%
가평군시설관리공단 1
 
2.0%
Other values (2) 2
 
4.1%

데이터기준일자
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-04
11 
2024-01-11
5 
2023-11-24
3 
2023-10-31
2 
2023-11-20
2 
Other values (3)
4 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique2 ?
Unique (%)7.4%

Sample

1st row2023-12-04
2nd row2023-12-04
3rd row2023-12-04
4th row2023-10-31
5th row2023-10-31

Common Values

ValueCountFrequency (%)
2023-12-04 11
40.7%
2024-01-11 5
18.5%
2023-11-24 3
 
11.1%
2023-10-31 2
 
7.4%
2023-11-20 2
 
7.4%
2023-11-28 2
 
7.4%
2023-10-23 1
 
3.7%
2022-10-27 1
 
3.7%

Length

2024-05-03T19:07:05.981799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T19:07:06.336514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-12-04 11
40.7%
2024-01-11 5
18.5%
2023-11-24 3
 
11.1%
2023-10-31 2
 
7.4%
2023-11-20 2
 
7.4%
2023-11-28 2
 
7.4%
2023-10-23 1
 
3.7%
2022-10-27 1
 
3.7%

Interactions

2024-05-03T19:06:39.329619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:06:35.139236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:06:36.466342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:06:38.035779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:06:39.635605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:06:35.433468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:06:36.790566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:06:38.277861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:06:39.955155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:06:35.904630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:06:37.223758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:06:38.592983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:06:40.289891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:06:36.196431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:06:37.611812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:06:38.996837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T19:07:06.723150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명자전거대여소명소재지도로명주소소재지지번주소위도경도운영시작시각운영종료시각휴무일요금구분자전거이용요금자전거보유대수거치대수공기주입기유형수리대설치여부관리기관전화번호관리기관명데이터기준일자
시군명1.0001.0001.0001.0000.9680.9400.9410.8541.0001.0001.0000.8950.4231.0001.0001.0001.0001.000
자전거대여소명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위도0.9681.0001.0001.0001.0000.6950.7940.8080.9880.6420.8290.8090.6820.8250.6830.9640.9680.968
경도0.9401.0001.0001.0000.6951.0000.6920.0000.9860.9710.9250.8500.5800.9960.9580.9880.9400.868
운영시작시각0.9411.0001.0001.0000.7940.6921.0000.6941.0000.7940.8870.5830.0000.6240.4420.9270.9410.965
운영종료시각0.8541.0001.0001.0000.8080.0000.6941.0000.9900.0000.8810.8700.0000.2120.0000.8280.8540.624
휴무일1.0001.0001.0001.0000.9880.9861.0000.9901.0001.0001.0000.9580.4671.0001.0000.9591.0001.000
요금구분1.0001.0001.0001.0000.6420.9710.7940.0001.0001.0001.0000.7630.0000.1630.2511.0001.0000.934
자전거이용요금1.0001.0001.0001.0000.8290.9250.8870.8811.0001.0001.0000.9490.0000.3141.0001.0001.0000.933
자전거보유대수0.8951.0001.0001.0000.8090.8500.5830.8700.9580.7630.9491.0000.6900.0000.8930.9400.8950.796
거치대수0.4231.0001.0001.0000.6820.5800.0000.0000.4670.0000.0000.6901.0000.612NaN0.0000.4230.423
공기주입기유형1.0001.0001.0001.0000.8250.9960.6240.2121.0000.1630.3140.0000.6121.0000.0001.0001.0000.910
수리대설치여부1.0001.0001.0001.0000.6830.9580.4420.0001.0000.2511.0000.893NaN0.0001.0001.0001.0001.000
관리기관전화번호1.0001.0001.0001.0000.9640.9880.9270.8280.9591.0001.0000.9400.0001.0001.0001.0001.0001.000
관리기관명1.0001.0001.0001.0000.9680.9400.9410.8541.0001.0001.0000.8950.4231.0001.0001.0001.0001.000
데이터기준일자1.0001.0001.0001.0000.9680.8680.9650.6241.0000.9340.9330.7960.4230.9101.0001.0001.0001.000
2024-05-03T19:07:07.214738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자전거이용요금데이터기준일자운영종료시각수리대설치여부휴무일공기주입기유형관리기관명요금구분시군명운영시작시각
자전거이용요금1.0000.8390.5110.9090.8580.3470.9180.9290.9180.725
데이터기준일자0.8391.0000.3760.8720.8890.6600.9460.8340.9460.681
운영종료시각0.5110.3761.0000.0000.7130.2260.5970.0000.5970.495
수리대설치여부0.9090.8720.0001.0000.7750.0000.8250.3970.8250.279
휴무일0.8580.8890.7130.7751.0000.7980.9390.7910.9390.808
공기주입기유형0.3470.6600.2260.0000.7981.0000.8530.2550.8530.407
관리기관명0.9180.9460.5970.8250.9390.8531.0000.8421.0000.735
요금구분0.9290.8340.0000.3970.7910.2550.8421.0000.8420.837
시군명0.9180.9460.5970.8250.9390.8531.0000.8421.0000.735
운영시작시각0.7250.6810.4950.2790.8080.4070.7350.8370.7351.000
2024-05-03T19:07:07.763352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도자전거보유대수거치대수시군명운영시작시각운영종료시각휴무일요금구분자전거이용요금공기주입기유형수리대설치여부관리기관명데이터기준일자
위도1.000-0.444-0.3650.1270.8480.4070.5850.7940.4500.6540.5640.4450.8480.708
경도-0.4441.0000.047-0.0580.7560.4930.0000.6910.7380.6000.8550.7480.7560.678
자전거보유대수-0.3650.0471.0000.4560.6700.4180.4660.5940.4730.6600.0000.6470.6700.587
거치대수0.127-0.0580.4561.0000.3230.0000.0000.2630.0000.0000.3781.0000.3230.323
시군명0.8480.7560.6700.3231.0000.7350.5970.9390.8420.9180.8530.8251.0000.946
운영시작시각0.4070.4930.4180.0000.7351.0000.4950.8080.8370.7250.4070.2790.7350.681
운영종료시각0.5850.0000.4660.0000.5970.4951.0000.7130.0000.5110.2260.0000.5970.376
휴무일0.7940.6910.5940.2630.9390.8080.7131.0000.7910.8580.7980.7750.9390.889
요금구분0.4500.7380.4730.0000.8420.8370.0000.7911.0000.9290.2550.3970.8420.834
자전거이용요금0.6540.6000.6600.0000.9180.7250.5110.8580.9291.0000.3470.9090.9180.839
공기주입기유형0.5640.8550.0000.3780.8530.4070.2260.7980.2550.3471.0000.0000.8530.660
수리대설치여부0.4450.7480.6471.0000.8250.2790.0000.7750.3970.9090.0001.0000.8250.872
관리기관명0.8480.7560.6700.3231.0000.7350.5970.9390.8420.9180.8530.8251.0000.946
데이터기준일자0.7080.6780.5870.3230.9460.6810.3760.8890.8340.8390.6600.8720.9461.000

Missing values

2024-05-03T19:06:40.866291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T19:06:42.083970image/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.
2024-05-03T19:06:42.706711image/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

시군명자전거대여소명자전거대여소구분소재지도로명주소소재지지번주소위도경도운영시작시각운영종료시각휴무일요금구분자전거이용요금자전거보유대수거치대수공기주입기비치여부공기주입기유형수리대설치여부관리기관전화번호관리기관명데이터기준일자
0과천시갈현동(정보과학도서관 앞)유인대여소경기도 과천시 중앙로 24경기도 과천시 갈현동 67737.418416126.98935509:0018:00월요일+화요일+국경일무료무료1520Y수동식N02-3677-2289경기도 과천시청2023-12-04
1과천시중앙동(시민회관 앞)유인대여소경기도 과천시 통영로 5경기도 과천시 중앙동 6-237.427761126.99074109:0018:00월요일+화요일+국경일무료무료2020Y수동식N02-3677-2291경기도 과천시청2023-12-04
2과천시주암동(주암체육공원 입구)유인대여소경기도 과천시 장군마을길 62-1경기도 과천시 주암동 5337.461604127.03251209:0018:00월요일+화요일+국경일무료무료1520Y수동식N02-3677-2290경기도 과천시청2023-12-04
3이천시신둔천 자전거대여소유인대여소<NA>경기도 이천시 송정동 42737.3026127.43916410:0018:00매주 월요일+명절 당일유료(1인용) 30분 1500원 60분 2000원 추가 10분당 1000원+(2인용) 30분 2000원 60분 3000원 추가 10분당 1000원+(5인승) 30분 10000원 60분 20000원 추가 10분당 3000원+(8인승) 30분 15000원 60분 25000원 추가 10분당 3000원+(1인승전기자전거) 30분 7000원 60분 12000원 추가 10분당 2000원+(2인승 전기자전거) 30분 12000원 60분 20000원 추가 10분119<NA>Y수동식Y031-631-7875이천시장애인자립생활센터2023-10-31
4이천시복하천 자전거대여소유인대여소경기도 이천시 경충대로2422번길 17경기도 이천시 진리동 14037.26774127.46006210:0018:00매주 월요일+명절 당일유료(1인용) 30분 1500원 60분 2000원 추가 10분당 1000원+(2인용) 30분 2000원 60분 3000원 추가 10분당 1000원+(5인승) 30분 10000원 60분 20000원 추가 10분당 3000원+(8인승) 30분 15000원 60분 25000원 추가 10분당 3000원+(1인승전기자전거) 30분 7000원 60분 12000원 추가 10분당 2000원+(2인승 전기자전거) 30분 12000원 60분 20000원 추가 10분141<NA>Y수동식Y031-631-7879이천시장애인자립생활센터2023-10-31
5부천시공공자전거대여소 부천시청역유인대여소경기도 부천시 원미구 길주로 191경기도 부천시 원미구 중동 1033-137.505147126.76388809:0018:00토요일+일요일+공휴일무료무료4050Y기계식N032-625-9093경기도 부천시청2024-01-11
6부천시공공자전거대여소 부천역유인대여소경기도 부천시 원미구 부천로 3-1경기도 부천시 원미구 심곡동 173-137.48468126.78187609:0018:00토요일+일요일+공휴일무료무료31180Y기계식N032-625-9093경기도 부천시청2024-01-11
7부천시공공자전거대여소 굴포천유인대여소<NA>경기도 부천시 오정구 삼정동 366-537.520597126.76067609:0018:00금요일+공휴일무료무료2222Y기계식N032-625-9093경기도 부천시청2024-01-11
8과천시문원동(2단지 문천사 앞)유인대여소<NA>경기도 과천시 문원동 106-237.425525127.0066609:0018:00월요일+화요일+국경일무료무료2020Y수동식N02-3677-2288경기도 과천시청2023-12-04
9과천시과천동(뒷골 공영주차장)유인대여소<NA>경기도 과천시 과천동 367-437.453806126.99902209:0018:00월요일+화요일+국경일무료무료2020Y수동식N02-3677-2288경기도 과천시청2023-12-04
시군명자전거대여소명자전거대여소구분소재지도로명주소소재지지번주소위도경도운영시작시각운영종료시각휴무일요금구분자전거이용요금자전거보유대수거치대수공기주입기비치여부공기주입기유형수리대설치여부관리기관전화번호관리기관명데이터기준일자
17가평군자라섬자전거대여소유인대여소경기도 가평군 가평읍 자라섬로60경기도 가평군 가평읍 대곡리 27-14번지37.820894127.52104409:0017:00동절기(12월+1월+2월+3월)유료30분당 3000원50<NA>Y기계식N031-8078-8323가평군시설관리공단2023-12-04
18수원시광교산공영자전거대여소(반딧불이쉼터)유인대여소경기도 수원시 장안구 광교산로 166경기도 수원시 장안구 하광교동 산 57-237.301833127.03233910:0018:00동절기유료1일 1천원72<NA>Y수동식N031-228-3504경기도 수원시청2023-11-24
19수원시광교산공영자전거대여소(버스종점)유인대여소<NA>경기도 수원시 장안구 상광교동 42-137.33455127.017410:0018:00동절기유료1일 1천원70<NA>Y수동식N031-228-3504경기도 수원시청2023-11-24
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