Overview

Dataset statistics

Number of variables11
Number of observations85
Missing cells2
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.6 KiB
Average record size in memory91.5 B

Variable types

Numeric2
Categorical5
Text3
DateTime1

Dataset

Description부산광역시 사상구 관내(12개동 중 11개 동 , 단 모라3동은 주거지주차장 없음) 주거지전용주차장 현황(주차장명,주차장 위치,주차장 구간,주차장 면수, 주차장 운영시간 등의 정보를 제공 )
Author부산광역시 사상구
URLhttps://www.data.go.kr/data/3078957/fileData.do

Alerts

관리방법 has constant value ""Constant
폐지여부 has constant value ""Constant
주차구분 is highly overall correlated with 운영시간High correlation
운영시간 is highly overall correlated with 주차구분High correlation
연번 is highly overall correlated with 행정동명High correlation
행정동명 is highly overall correlated with 연번High correlation
인근주요지점 has 2 (2.4%) missing valuesMissing
연번 has unique valuesUnique
주차장명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 09:11:24.190638
Analysis finished2024-03-14 09:11:27.280447
Duration3.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct85
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43
Minimum1
Maximum85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size893.0 B
2024-03-14T18:11:27.487948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.2
Q122
median43
Q364
95-th percentile80.8
Maximum85
Range84
Interquartile range (IQR)42

Descriptive statistics

Standard deviation24.681302
Coefficient of variation (CV)0.57398377
Kurtosis-1.2
Mean43
Median Absolute Deviation (MAD)21
Skewness0
Sum3655
Variance609.16667
MonotonicityStrictly increasing
2024-03-14T18:11:27.927168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
55 1
 
1.2%
63 1
 
1.2%
62 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
Other values (75) 75
88.2%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
85 1
1.2%
84 1
1.2%
83 1
1.2%
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%

행정동명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size808.0 B
모라1동
13 
감전동
10 
주례3동
10 
덕포2동
9 
주례2동
9 
Other values (6)
34 

Length

Max length4
Median length4
Mean length3.6117647
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row삼락동
2nd row삼락동
3rd row삼락동
4th row삼락동
5th row모라1동

Common Values

ValueCountFrequency (%)
모라1동 13
15.3%
감전동 10
11.8%
주례3동 10
11.8%
덕포2동 9
10.6%
주례2동 9
10.6%
엄궁동 9
10.6%
괘법동 6
7.1%
주례1동 6
7.1%
덕포1동 5
 
5.9%
삼락동 4
 
4.7%

Length

2024-03-14T18:11:28.350762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
모라1동 13
15.3%
감전동 10
11.8%
주례3동 10
11.8%
덕포2동 9
10.6%
주례2동 9
10.6%
엄궁동 9
10.6%
괘법동 6
7.1%
주례1동 6
7.1%
덕포1동 5
 
5.9%
삼락동 4
 
4.7%

주차장명
Text

UNIQUE 

Distinct85
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size808.0 B
2024-03-14T18:11:29.275819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length12
Mean length7.4823529
Min length3

Characters and Unicode

Total characters636
Distinct characters170
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)100.0%

Sample

1st row한마음주변
2nd row삼락재첩국거리주변
3rd row삼락생태공원주변
4th row현대골드빌라주변
5th row농심주변
ValueCountFrequency (%)
주변 4
 
4.1%
구 2
 
2.1%
모라철로변 2
 
2.1%
조양맨션주변 1
 
1.0%
주례럭키아파트도로 1
 
1.0%
주례여중학교주변 1
 
1.0%
경남정보대학교주변 1
 
1.0%
주례중학교주변 1
 
1.0%
장성주차장 1
 
1.0%
주례2동행정복지센터주변 1
 
1.0%
Other values (82) 82
84.5%
2024-03-14T18:11:30.683750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 84
 
13.2%
변 70
 
11.0%
동 15
 
2.4%
길 14
 
2.2%
12
 
1.9%
로 11
 
1.7%
트 10
 
1.6%
장 10
 
1.6%
파 9
 
1.4%
아 9
 
1.4%
Other values (160) 392
61.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 592
93.1%
Decimal Number 21
 
3.3%
Space Separator 12
 
1.9%
Open Punctuation 4
 
0.6%
Close Punctuation 4
 
0.6%
Dash Punctuation 2
 
0.3%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 84
 
14.2%
변 70
 
11.8%
동 15
 
2.5%
길 14
 
2.4%
로 11
 
1.9%
트 10
 
1.7%
장 10
 
1.7%
파 9
 
1.5%
아 9
 
1.5%
원 8
 
1.4%
Other values (147) 352
59.5%
Decimal Number
ValueCountFrequency (%)
1 6
28.6%
9 3
14.3%
2 3
14.3%
3 3
14.3%
4 2
 
9.5%
7 2
 
9.5%
8 1
 
4.8%
0 1
 
4.8%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 592
93.1%
Common 44
 
6.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 84
 
14.2%
변 70
 
11.8%
동 15
 
2.5%
길 14
 
2.4%
로 11
 
1.9%
트 10
 
1.7%
장 10
 
1.7%
파 9
 
1.5%
아 9
 
1.5%
원 8
 
1.4%
Other values (147) 352
59.5%
Common
ValueCountFrequency (%)
12
27.3%
1 6
13.6%
( 4
 
9.1%
) 4
 
9.1%
9 3
 
6.8%
2 3
 
6.8%
3 3
 
6.8%
4 2
 
4.5%
- 2
 
4.5%
7 2
 
4.5%
Other values (3) 3
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 592
93.1%
ASCII 44
 
6.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 84
 
14.2%
변 70
 
11.8%
동 15
 
2.5%
길 14
 
2.4%
로 11
 
1.9%
트 10
 
1.7%
장 10
 
1.7%
파 9
 
1.5%
아 9
 
1.5%
원 8
 
1.4%
Other values (147) 352
59.5%
ASCII
ValueCountFrequency (%)
12
27.3%
1 6
13.6%
( 4
 
9.1%
) 4
 
9.1%
9 3
 
6.8%
2 3
 
6.8%
3 3
 
6.8%
4 2
 
4.5%
- 2
 
4.5%
7 2
 
4.5%
Other values (3) 3
 
6.8%

주차장위치
Text

Distinct83
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size808.0 B
2024-03-14T18:11:31.511478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length11.458824
Min length4

Characters and Unicode

Total characters974
Distinct characters94
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)95.3%

Sample

1st row삼락동 411-2
2nd row삼락동 54-13
3rd row삼락동 419-20
4th row삼락동 417-18(사상로277번나길 26)
5th row모덕로67번길,사상로469번길
ValueCountFrequency (%)
감전동 8
 
4.8%
주례동 8
 
4.8%
덕포동 6
 
3.6%
앞 5
 
3.0%
주례2동 4
 
2.4%
엄궁동 4
 
2.4%
덕포1동 4
 
2.4%
삼락동 4
 
2.4%
일원 4
 
2.4%
괘법동 3
 
1.8%
Other values (108) 115
69.7%
2024-03-14T18:11:32.563999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
81
 
8.3%
1 62
 
6.4%
동 54
 
5.5%
2 46
 
4.7%
로 43
 
4.4%
- 41
 
4.2%
9 34
 
3.5%
번 34
 
3.5%
길 33
 
3.4%
0 30
 
3.1%
Other values (84) 516
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 478
49.1%
Decimal Number 332
34.1%
Space Separator 81
 
8.3%
Dash Punctuation 41
 
4.2%
Other Punctuation 14
 
1.4%
Close Punctuation 14
 
1.4%
Open Punctuation 14
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 54
 
11.3%
로 43
 
9.0%
번 34
 
7.1%
길 33
 
6.9%
주 26
 
5.4%
례 17
 
3.6%
대 15
 
3.1%
양 14
 
2.9%
덕 13
 
2.7%
궁 12
 
2.5%
Other values (69) 217
45.4%
Decimal Number
ValueCountFrequency (%)
1 62
18.7%
2 46
13.9%
9 34
10.2%
0 30
9.0%
4 30
9.0%
5 30
9.0%
7 29
8.7%
8 25
7.5%
3 24
 
7.2%
6 22
 
6.6%
Space Separator
ValueCountFrequency (%)
81
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 496
50.9%
Hangul 478
49.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 54
 
11.3%
로 43
 
9.0%
번 34
 
7.1%
길 33
 
6.9%
주 26
 
5.4%
례 17
 
3.6%
대 15
 
3.1%
양 14
 
2.9%
덕 13
 
2.7%
궁 12
 
2.5%
Other values (69) 217
45.4%
Common
ValueCountFrequency (%)
81
16.3%
1 62
12.5%
2 46
9.3%
- 41
8.3%
9 34
 
6.9%
0 30
 
6.0%
4 30
 
6.0%
5 30
 
6.0%
7 29
 
5.8%
8 25
 
5.0%
Other values (5) 88
17.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 496
50.9%
Hangul 478
49.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
81
16.3%
1 62
12.5%
2 46
9.3%
- 41
8.3%
9 34
 
6.9%
0 30
 
6.0%
4 30
 
6.0%
5 30
 
6.0%
7 29
 
5.8%
8 25
 
5.0%
Other values (5) 88
17.7%
Hangul
ValueCountFrequency (%)
동 54
 
11.3%
로 43
 
9.0%
번 34
 
7.1%
길 33
 
6.9%
주 26
 
5.4%
례 17
 
3.6%
대 15
 
3.1%
양 14
 
2.9%
덕 13
 
2.7%
궁 12
 
2.5%
Other values (69) 217
45.4%

인근주요지점
Text

MISSING 

Distinct79
Distinct (%)95.2%
Missing2
Missing (%)2.4%
Memory size808.0 B
2024-03-14T18:11:33.384535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length18
Mean length8.9879518
Min length3

Characters and Unicode

Total characters746
Distinct characters169
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

Unique76 ?
Unique (%)91.6%

Sample

1st row삼덕초등학교 건너편
2nd row낙동대로1534번길 34~40사이
3rd row삼락생태공원 입구, 운산로
4th row현대골드빌라
5th row(주)농심 주변
ValueCountFrequency (%)
주변 13
 
9.5%
앞 8
 
5.8%
옆 4
 
2.9%
백양대로703번길 3
 
2.2%
동주중학교 3
 
2.2%
건너편 2
 
1.5%
맞은편 2
 
1.5%
감전동 2
 
1.5%
창신공원 2
 
1.5%
태원아파트 2
 
1.5%
Other values (95) 96
70.1%
2024-03-14T18:11:34.666673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55
 
7.4%
주 34
 
4.6%
동 22
 
2.9%
트 19
 
2.5%
학 18
 
2.4%
파 18
 
2.4%
아 18
 
2.4%
변 17
 
2.3%
원 14
 
1.9%
교 14
 
1.9%
Other values (159) 517
69.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 626
83.9%
Space Separator 55
 
7.4%
Decimal Number 40
 
5.4%
Other Punctuation 9
 
1.2%
Close Punctuation 4
 
0.5%
Open Punctuation 4
 
0.5%
Math Symbol 4
 
0.5%
Dash Punctuation 2
 
0.3%
Lowercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 34
 
5.4%
동 22
 
3.5%
트 19
 
3.0%
학 18
 
2.9%
파 18
 
2.9%
아 18
 
2.9%
변 17
 
2.7%
원 14
 
2.2%
교 14
 
2.2%
로 13
 
2.1%
Other values (142) 439
70.1%
Decimal Number
ValueCountFrequency (%)
1 6
15.0%
0 6
15.0%
3 6
15.0%
4 5
12.5%
9 4
10.0%
7 4
10.0%
5 3
7.5%
6 3
7.5%
2 3
7.5%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
55
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 626
83.9%
Common 118
 
15.8%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 34
 
5.4%
동 22
 
3.5%
트 19
 
3.0%
학 18
 
2.9%
파 18
 
2.9%
아 18
 
2.9%
변 17
 
2.7%
원 14
 
2.2%
교 14
 
2.2%
로 13
 
2.1%
Other values (142) 439
70.1%
Common
ValueCountFrequency (%)
55
46.6%
, 9
 
7.6%
1 6
 
5.1%
0 6
 
5.1%
3 6
 
5.1%
4 5
 
4.2%
) 4
 
3.4%
9 4
 
3.4%
( 4
 
3.4%
7 4
 
3.4%
Other values (5) 15
 
12.7%
Latin
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 626
83.9%
ASCII 120
 
16.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
55
45.8%
, 9
 
7.5%
1 6
 
5.0%
0 6
 
5.0%
3 6
 
5.0%
4 5
 
4.2%
) 4
 
3.3%
9 4
 
3.3%
( 4
 
3.3%
7 4
 
3.3%
Other values (7) 17
 
14.2%
Hangul
ValueCountFrequency (%)
주 34
 
5.4%
동 22
 
3.5%
트 19
 
3.0%
학 18
 
2.9%
파 18
 
2.9%
아 18
 
2.9%
변 17
 
2.7%
원 14
 
2.2%
교 14
 
2.2%
로 13
 
2.1%
Other values (142) 439
70.1%

설치일
Date

Distinct71
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Memory size808.0 B
Minimum1998-01-01 00:00:00
Maximum2024-02-01 00:00:00
2024-03-14T18:11:35.066013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:11:35.477086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

주차면수
Real number (ℝ)

Distinct41
Distinct (%)48.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.411765
Minimum4
Maximum96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size893.0 B
2024-03-14T18:11:35.876272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile5.2
Q111
median20
Q337
95-th percentile75.4
Maximum96
Range92
Interquartile range (IQR)26

Descriptive statistics

Standard deviation20.683726
Coefficient of variation (CV)0.78312549
Kurtosis2.0812134
Mean26.411765
Median Absolute Deviation (MAD)11
Skewness1.4742567
Sum2245
Variance427.81653
MonotonicityNot monotonic
2024-03-14T18:11:36.493582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
17 5
 
5.9%
10 5
 
5.9%
11 4
 
4.7%
20 4
 
4.7%
8 4
 
4.7%
15 3
 
3.5%
7 3
 
3.5%
36 3
 
3.5%
26 3
 
3.5%
9 3
 
3.5%
Other values (31) 48
56.5%
ValueCountFrequency (%)
4 2
 
2.4%
5 3
3.5%
6 1
 
1.2%
7 3
3.5%
8 4
4.7%
9 3
3.5%
10 5
5.9%
11 4
4.7%
12 2
 
2.4%
14 2
 
2.4%
ValueCountFrequency (%)
96 1
1.2%
90 1
1.2%
85 1
1.2%
79 1
1.2%
78 1
1.2%
65 1
1.2%
54 1
1.2%
50 1
1.2%
48 2
2.4%
47 2
2.4%

관리방법
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size808.0 B
자체관리
85 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자체관리 85
100.0%

Length

2024-03-14T18:11:36.887233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:11:37.193072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자체관리 85
100.0%

주차구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size808.0 B
노상
52 
노외
33 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row노외
2nd row노외
3rd row노외
4th row노외
5th row노상

Common Values

ValueCountFrequency (%)
노상 52
61.2%
노외 33
38.8%

Length

2024-03-14T18:11:37.515223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:11:37.826320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노상 52
61.2%
노외 33
38.8%

운영시간
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size808.0 B
야간
49 
전일제만
30 
전일 + 주간 + 야간
 
3
주간 + 야간
 
1
주간
 
1

Length

Max length12
Median length2
Mean length3.1764706
Min length2

Unique

Unique3 ?
Unique (%)3.5%

Sample

1st row전일제만
2nd row전일제만
3rd row전일제만
4th row전일제만
5th row야간

Common Values

ValueCountFrequency (%)
야간 49
57.6%
전일제만 30
35.3%
전일 + 주간 + 야간 3
 
3.5%
주간 + 야간 1
 
1.2%
주간 1
 
1.2%
전일 + 야간 1
 
1.2%

Length

2024-03-14T18:11:38.174785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:11:38.516562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
야간 54
53.5%
전일제만 30
29.7%
8
 
7.9%
주간 5
 
5.0%
전일 4
 
4.0%

폐지여부
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size808.0 B
정상
85 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상 85
100.0%

Length

2024-03-14T18:11:38.895189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:11:39.205628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 85
100.0%

Interactions

2024-03-14T18:11:25.987978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:11:25.528679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:11:26.218025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:11:25.754297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T18:11:39.403713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동명주차장명주차장위치인근주요지점설치일주차면수주차구분운영시간
연번1.0000.9291.0001.0001.0000.8980.0990.0000.199
행정동명0.9291.0001.0001.0001.0000.9240.0000.2910.397
주차장명1.0001.0001.0001.0001.0001.0001.0001.0001.000
주차장위치1.0001.0001.0001.0000.9880.9980.0001.0001.000
인근주요지점1.0001.0001.0000.9881.0000.9910.9821.0001.000
설치일0.8980.9241.0000.9980.9911.0000.0001.0000.904
주차면수0.0990.0001.0000.0000.9820.0001.0000.4590.281
주차구분0.0000.2911.0001.0001.0001.0000.4591.0000.994
운영시간0.1990.3971.0001.0001.0000.9040.2810.9941.000
2024-03-14T18:11:39.704288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주차구분행정동명운영시간
주차구분1.0000.2610.906
행정동명0.2611.0000.206
운영시간0.9060.2061.000
2024-03-14T18:11:39.957049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번주차면수행정동명주차구분운영시간
연번1.000-0.0790.7390.0000.096
주차면수-0.0791.0000.0000.4390.137
행정동명0.7390.0001.0000.2610.206
주차구분0.0000.4390.2611.0000.906
운영시간0.0960.1370.2060.9061.000

Missing values

2024-03-14T18:11:26.569453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T18:11:27.075596image/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

연번행정동명주차장명주차장위치인근주요지점설치일주차면수관리방법주차구분운영시간폐지여부
01삼락동한마음주변삼락동 411-2삼덕초등학교 건너편2009-07-1518자체관리노외전일제만정상
12삼락동삼락재첩국거리주변삼락동 54-13낙동대로1534번길 34~40사이2010-05-0129자체관리노외전일제만정상
23삼락동삼락생태공원주변삼락동 419-20삼락생태공원 입구, 운산로2013-06-0110자체관리노외전일제만정상
34삼락동현대골드빌라주변삼락동 417-18(사상로277번나길 26)현대골드빌라2014-08-0122자체관리노외전일제만정상
45모라1동농심주변모덕로67번길,사상로469번길(주)농심 주변1998-04-0116자체관리노상야간정상
56모라1동농협주변사상로478번길사상농협모라지점2000-01-0111자체관리노상야간정상
67모라1동여로횟집앞백양대로979번길여로횟집앞1999-05-0134자체관리노상야간정상
78모라1동한일아파트주변백양대로950번길한일아파트 주변2008-05-0136자체관리노상야간정상
89모라1동우신아파트주변모라1동 1362(백양대로 880) 주변모라동 우신아파트2008-05-0124자체관리노상야간정상
910모라1동동원아파트주변모라로88번길모라동원타운 주변2008-06-2048자체관리노상야간정상
연번행정동명주차장명주차장위치인근주요지점설치일주차면수관리방법주차구분운영시간폐지여부
7576학장동새밭마을 주거지전용 주차장학장동 574-66, 149청파아파트2022-12-238자체관리노외전일제만정상
7677엄궁동엄궁롯데캐슬리버주변엄궁로179번길엄궁롯데캐슬리버1998-03-0190자체관리노상야간정상
7778엄궁동구 엄궁동사무소엄궁중로구 엄궁동사무소 앞2007-04-2044자체관리노상야간정상
7879엄궁동엄궁동행복센터주변엄궁북로(엄궁동주민센터 앞)엄궁동행복센터 앞2007-04-2020자체관리노상야간정상
7980엄궁동엄궁동우체국주변엄궁동 522-7엄궁동우체국 주변2007-07-017자체관리노외전일제만정상
8081엄궁동남산길주변엄궁동 192신대동아파트주변2007-07-0515자체관리노외전일제만정상
8182엄궁동엄궁중앙길주변엄궁로191번길,엄궁북로(엄궁초등학교 앞)엄궁초등학교 앞2009-04-0944자체관리노상야간정상
8283엄궁동당산마을주변엄궁남로11번길당산마을(당산나무)2010-04-0126자체관리노상야간정상
8384엄궁동엄궁목장길주변엄궁동 186-4신대동아파트주변2010-06-0115자체관리노외전일제만정상
8485엄궁동학진초등학교주변엄궁동 25-140학진초등학교2010-06-1511자체관리노외전일제만정상