Overview

Dataset statistics

Number of variables18
Number of observations296
Missing cells260
Missing cells (%)4.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory43.8 KiB
Average record size in memory151.4 B

Variable types

Categorical7
Numeric6
Text1
DateTime4

Dataset

Description경상북도 안동시 관내 주차장 데이터(지형지물부호, 관리번호, 행정읍면동, 법정읍면동, 도엽번호, 관리기관, 도로구간번호, 공사번호, 설치일자, 주차장위치구분, 주차요금구분, 요금, 주차면수, 장애자주차면수, 전체면적, 운영시간(개장시간), 운영시간(폐장시간), 주차방향, 대장초기화여부) 정보를 제공합니다.
Author경상북도 안동시
URLhttps://www.data.go.kr/data/15123593/fileData.do

Alerts

지형지물부호 has constant value ""Constant
관리기관 has constant value ""Constant
데이터기준일자 has constant value ""Constant
요금 is highly overall correlated with 법정읍면동 and 3 other fieldsHigh correlation
주차요금구분 is highly overall correlated with 요금High correlation
관리번호 is highly overall correlated with 법정읍면동High correlation
행정읍면동 is highly overall correlated with 주차장위치구분High correlation
법정읍면동 is highly overall correlated with 관리번호 and 1 other fieldsHigh correlation
도로구간번호 is highly overall correlated with 주차장위치구분 and 2 other fieldsHigh correlation
주차면수 is highly overall correlated with 전체면적High correlation
전체면적 is highly overall correlated with 주차면수High correlation
주차장위치구분 is highly overall correlated with 행정읍면동 and 2 other fieldsHigh correlation
주차방향 is highly overall correlated with 도로구간번호High correlation
장애자주차면수 is highly imbalanced (83.9%)Imbalance
운영시간(개장시간) has 130 (43.9%) missing valuesMissing
운영시간(폐장시간) has 130 (43.9%) missing valuesMissing
전체면적 has 43 (14.5%) zerosZeros

Reproduction

Analysis started2023-12-12 18:22:17.937321
Analysis finished2023-12-12 18:22:23.297175
Duration5.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지형지물부호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
AE230
296 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAE230
2nd rowAE230
3rd rowAE230
4th rowAE230
5th rowAE230

Common Values

ValueCountFrequency (%)
AE230 296
100.0%

Length

2023-12-13T03:22:23.351976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:22:23.439392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ae230 296
100.0%

관리번호
Real number (ℝ)

HIGH CORRELATION 

Distinct291
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7088.6824
Minimum1
Maximum100015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-13T03:22:23.534222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.75
Q174.75
median206.5
Q35014.25
95-th percentile100000.25
Maximum100015
Range100014
Interquartile range (IQR)4939.5

Descriptive statistics

Standard deviation22418.822
Coefficient of variation (CV)3.1626218
Kurtosis13.309901
Mean7088.6824
Median Absolute Deviation (MAD)153
Skewness3.8669312
Sum2098250
Variance5.0260356 × 108
MonotonicityNot monotonic
2023-12-13T03:22:23.655231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
240 2
 
0.7%
257 2
 
0.7%
242 2
 
0.7%
253 2
 
0.7%
255 2
 
0.7%
222 1
 
0.3%
100012 1
 
0.3%
259 1
 
0.3%
204 1
 
0.3%
8015 1
 
0.3%
Other values (281) 281
94.9%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
100015 1
0.3%
100014 1
0.3%
100013 1
0.3%
100012 1
0.3%
100011 1
0.3%
100010 1
0.3%
100009 1
0.3%
100008 1
0.3%
100007 1
0.3%
100006 1
0.3%

행정읍면동
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7170183 × 109
Minimum4.717011 × 109
Maximum4.7170555 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-13T03:22:24.038817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.717011 × 109
5-th percentile4.717011 × 109
Q14.7170127 × 109
median4.7170144 × 109
Q34.7170144 × 109
95-th percentile4.7170555 × 109
Maximum4.7170555 × 109
Range44500
Interquartile range (IQR)1700

Descriptive statistics

Standard deviation13118.156
Coefficient of variation (CV)2.7810272 × 10-6
Kurtosis4.1372063
Mean4.7170183 × 109
Median Absolute Deviation (MAD)100
Skewness2.4373901
Sum1.3962374 × 1012
Variance1.7208603 × 108
MonotonicityNot monotonic
2023-12-13T03:22:24.136152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
4717014400 86
29.1%
4717014300 56
18.9%
4717011000 34
 
11.5%
4717055500 32
 
10.8%
4717014500 25
 
8.4%
4717012700 22
 
7.4%
4717012200 22
 
7.4%
4717012800 7
 
2.4%
4717025000 6
 
2.0%
4717013300 3
 
1.0%
ValueCountFrequency (%)
4717011000 34
 
11.5%
4717012200 22
 
7.4%
4717012700 22
 
7.4%
4717012800 7
 
2.4%
4717013300 3
 
1.0%
4717014300 56
18.9%
4717014400 86
29.1%
4717014500 25
 
8.4%
4717014600 3
 
1.0%
4717025000 6
 
2.0%
ValueCountFrequency (%)
4717055500 32
 
10.8%
4717025000 6
 
2.0%
4717014600 3
 
1.0%
4717014500 25
 
8.4%
4717014400 86
29.1%
4717014300 56
18.9%
4717013300 3
 
1.0%
4717012800 7
 
2.4%
4717012700 22
 
7.4%
4717012200 22
 
7.4%

법정읍면동
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7170123 × 109
Minimum4.7170101 × 109
Maximum4.717025 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-13T03:22:24.233483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.7170101 × 109
5-th percentile4.7170102 × 109
Q14.7170112 × 109
median4.717012 × 109
Q34.7170129 × 109
95-th percentile4.717014 × 109
Maximum4.717025 × 109
Range14923
Interquartile range (IQR)1700

Descriptive statistics

Standard deviation2108.2597
Coefficient of variation (CV)4.469481 × 10-7
Kurtosis24.630845
Mean4.7170123 × 109
Median Absolute Deviation (MAD)800
Skewness4.42046
Sum1.3962356 × 1012
Variance4444758.9
MonotonicityNot monotonic
2023-12-13T03:22:24.339591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
4717013000 32
 
10.8%
4717011000 30
 
10.1%
4717014000 25
 
8.4%
4717012200 22
 
7.4%
4717011200 16
 
5.4%
4717012700 15
 
5.1%
4717011600 14
 
4.7%
4717011700 12
 
4.1%
4717010100 12
 
4.1%
4717012500 10
 
3.4%
Other values (21) 108
36.5%
ValueCountFrequency (%)
4717010100 12
 
4.1%
4717010200 7
 
2.4%
4717010300 4
 
1.4%
4717010800 2
 
0.7%
4717010900 5
 
1.7%
4717011000 30
10.1%
4717011100 7
 
2.4%
4717011200 16
5.4%
4717011300 9
 
3.0%
4717011400 4
 
1.4%
ValueCountFrequency (%)
4717025023 2
 
0.7%
4717025021 4
 
1.4%
4717014000 25
8.4%
4717013700 4
 
1.4%
4717013600 3
 
1.0%
4717013300 3
 
1.0%
4717013000 32
10.8%
4717012900 7
 
2.4%
4717012800 7
 
2.4%
4717012700 15
5.1%

도엽번호
Text

Distinct67
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-13T03:22:24.521268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters2960
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)5.4%

Sample

1st row368072074D
2nd row368072065C
3rd row368072505B
4th row368072065D
5th row368072074C
ValueCountFrequency (%)
368072077b 17
 
5.7%
368081666d 15
 
5.1%
368072505b 15
 
5.1%
368072067c 14
 
4.7%
368081681d 14
 
4.7%
368072066c 13
 
4.4%
368072065d 12
 
4.1%
368072076a 9
 
3.0%
368072077a 8
 
2.7%
368081655d 8
 
2.7%
Other values (57) 171
57.8%
2023-12-13T03:22:24.813277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 542
18.3%
0 525
17.7%
8 404
13.6%
7 361
12.2%
3 317
10.7%
2 236
8.0%
5 116
 
3.9%
1 94
 
3.2%
D 85
 
2.9%
B 81
 
2.7%
Other values (4) 199
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2664
90.0%
Uppercase Letter 296
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 542
20.3%
0 525
19.7%
8 404
15.2%
7 361
13.6%
3 317
11.9%
2 236
8.9%
5 116
 
4.4%
1 94
 
3.5%
4 43
 
1.6%
9 26
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
D 85
28.7%
B 81
27.4%
A 70
23.6%
C 60
20.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2664
90.0%
Latin 296
 
10.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 542
20.3%
0 525
19.7%
8 404
15.2%
7 361
13.6%
3 317
11.9%
2 236
8.9%
5 116
 
4.4%
1 94
 
3.5%
4 43
 
1.6%
9 26
 
1.0%
Latin
ValueCountFrequency (%)
D 85
28.7%
B 81
27.4%
A 70
23.6%
C 60
20.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2960
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 542
18.3%
0 525
17.7%
8 404
13.6%
7 361
12.2%
3 317
10.7%
2 236
8.0%
5 116
 
3.9%
1 94
 
3.2%
D 85
 
2.9%
B 81
 
2.7%
Other values (4) 199
 
6.7%

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
MNG001
296 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMNG001
2nd rowMNG001
3rd rowMNG001
4th rowMNG001
5th rowMNG001

Common Values

ValueCountFrequency (%)
MNG001 296
100.0%

Length

2023-12-13T03:22:24.929173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:22:25.010819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mng001 296
100.0%

도로구간번호
Real number (ℝ)

HIGH CORRELATION 

Distinct141
Distinct (%)47.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32961.703
Minimum56
Maximum140362
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-13T03:22:25.092409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum56
5-th percentile69
Q11550.75
median8005
Q367038
95-th percentile140200
Maximum140362
Range140306
Interquartile range (IQR)65487.25

Descriptive statistics

Standard deviation40024.637
Coefficient of variation (CV)1.214277
Kurtosis0.30070965
Mean32961.703
Median Absolute Deviation (MAD)7925
Skewness1.0793853
Sum9756664
Variance1.6019716 × 109
MonotonicityNot monotonic
2023-12-13T03:22:25.233049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8021 15
 
5.1%
8005 8
 
2.7%
8023 7
 
2.4%
69 7
 
2.4%
67032 6
 
2.0%
67053 6
 
2.0%
78029 6
 
2.0%
514 6
 
2.0%
865 5
 
1.7%
140259 5
 
1.7%
Other values (131) 225
76.0%
ValueCountFrequency (%)
56 4
1.4%
58 2
 
0.7%
60 2
 
0.7%
62 1
 
0.3%
64 2
 
0.7%
65 1
 
0.3%
66 1
 
0.3%
67 1
 
0.3%
69 7
2.4%
76 2
 
0.7%
ValueCountFrequency (%)
140362 4
1.4%
140259 5
1.7%
140250 1
 
0.3%
140247 4
1.4%
140200 2
 
0.7%
79104 1
 
0.3%
79036 1
 
0.3%
79033 2
 
0.7%
79024 1
 
0.3%
78029 6
2.0%

설치일자
Date

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum1990-01-01 00:00:00
Maximum2017-01-01 00:00:00
2023-12-13T03:22:25.342002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:25.422253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

주차장위치구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
PST001
242 
PST002
54 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPST001
2nd rowPST001
3rd rowPST001
4th rowPST001
5th rowPST001

Common Values

ValueCountFrequency (%)
PST001 242
81.8%
PST002 54
 
18.2%

Length

2023-12-13T03:22:25.514414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:22:25.600478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
pst001 242
81.8%
pst002 54
 
18.2%

주차요금구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
CHR001
203 
CHR002
91 
CHR000
 
2

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCHR001
2nd rowCHR002
3rd rowCHR001
4th rowCHR002
5th rowCHR001

Common Values

ValueCountFrequency (%)
CHR001 203
68.6%
CHR002 91
30.7%
CHR000 2
 
0.7%

Length

2023-12-13T03:22:25.709873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:22:25.836352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
chr001 203
68.6%
chr002 91
30.7%
chr000 2
 
0.7%

요금
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
143 
무료
95 
30분당500원
57 
30분당
 
1

Length

Max length8
Median length4
Mean length4.1283784
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row무료
2nd row30분당500원
3rd row<NA>
4th row<NA>
5th row무료

Common Values

ValueCountFrequency (%)
<NA> 143
48.3%
무료 95
32.1%
30분당500원 57
 
19.3%
30분당 1
 
0.3%

Length

2023-12-13T03:22:25.974876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:22:26.076048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 143
48.3%
무료 95
32.1%
30분당500원 57
 
19.3%
30분당 1
 
0.3%

주차면수
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0743243
Minimum1
Maximum59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-13T03:22:26.177459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q310
95-th percentile20
Maximum59
Range58
Interquartile range (IQR)8

Descriptive statistics

Standard deviation7.9289995
Coefficient of variation (CV)1.1208137
Kurtosis10.92085
Mean7.0743243
Median Absolute Deviation (MAD)3
Skewness2.7742375
Sum2094
Variance62.869033
MonotonicityNot monotonic
2023-12-13T03:22:26.296832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 54
18.2%
2 46
15.5%
3 30
10.1%
4 27
9.1%
11 17
 
5.7%
7 15
 
5.1%
5 13
 
4.4%
6 12
 
4.1%
9 10
 
3.4%
10 9
 
3.0%
Other values (19) 63
21.3%
ValueCountFrequency (%)
1 54
18.2%
2 46
15.5%
3 30
10.1%
4 27
9.1%
5 13
 
4.4%
6 12
 
4.1%
7 15
 
5.1%
8 9
 
3.0%
9 10
 
3.4%
10 9
 
3.0%
ValueCountFrequency (%)
59 1
 
0.3%
49 1
 
0.3%
44 1
 
0.3%
38 1
 
0.3%
34 1
 
0.3%
31 3
1.0%
30 1
 
0.3%
28 1
 
0.3%
26 3
1.0%
23 2
0.7%

장애자주차면수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
0
281 
1
 
7
2
 
5
3
 
2
6
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 281
94.9%
1 7
 
2.4%
2 5
 
1.7%
3 2
 
0.7%
6 1
 
0.3%

Length

2023-12-13T03:22:26.420243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:22:26.520963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 281
94.9%
1 7
 
2.4%
2 5
 
1.7%
3 2
 
0.7%
6 1
 
0.3%

전체면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct250
Distinct (%)84.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80.688615
Minimum0
Maximum650.04
Zeros43
Zeros (%)14.5%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-13T03:22:26.671141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112.44
median44.445
Q3109.5125
95-th percentile295.3475
Maximum650.04
Range650.04
Interquartile range (IQR)97.0725

Descriptive statistics

Standard deviation104.82734
Coefficient of variation (CV)1.299159
Kurtosis7.5688453
Mean80.688615
Median Absolute Deviation (MAD)34.65
Skewness2.4905837
Sum23883.83
Variance10988.771
MonotonicityNot monotonic
2023-12-13T03:22:26.862071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 43
 
14.5%
109.64 2
 
0.7%
45.55 2
 
0.7%
48.29 2
 
0.7%
23.79 2
 
0.7%
163.63 1
 
0.3%
102.38 1
 
0.3%
107.5 1
 
0.3%
384.54 1
 
0.3%
23.95 1
 
0.3%
Other values (240) 240
81.1%
ValueCountFrequency (%)
0.0 43
14.5%
6.03 1
 
0.3%
8.35 1
 
0.3%
9.34 1
 
0.3%
9.46 1
 
0.3%
9.72 1
 
0.3%
9.87 1
 
0.3%
10.02 1
 
0.3%
10.09 1
 
0.3%
10.17 1
 
0.3%
ValueCountFrequency (%)
650.04 1
0.3%
586.51 1
0.3%
554.82 1
0.3%
518.61 1
0.3%
451.13 1
0.3%
443.84 1
0.3%
420.44 1
0.3%
384.54 1
0.3%
380.2 1
0.3%
376.0 1
0.3%

운영시간(개장시간)
Date

MISSING 

Distinct4
Distinct (%)2.4%
Missing130
Missing (%)43.9%
Memory size2.4 KiB
Minimum2023-12-13 00:00:00
Maximum2023-12-13 18:00:00
2023-12-13T03:22:27.006906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:27.124342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

운영시간(폐장시간)
Date

MISSING 

Distinct2
Distinct (%)1.2%
Missing130
Missing (%)43.9%
Memory size2.4 KiB
Minimum2023-12-13 00:00:00
Maximum2023-12-13 20:00:00
2023-12-13T03:22:27.248705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:27.364566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

주차방향
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
PKN003
147 
PKN001
137 
PKN002
 
12

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPKN001
2nd rowPKN003
3rd rowPKN001
4th rowPKN001
5th rowPKN001

Common Values

ValueCountFrequency (%)
PKN003 147
49.7%
PKN001 137
46.3%
PKN002 12
 
4.1%

Length

2023-12-13T03:22:27.521673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:22:27.643123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
pkn003 147
49.7%
pkn001 137
46.3%
pkn002 12
 
4.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum2023-08-31 00:00:00
Maximum2023-08-31 00:00:00
2023-12-13T03:22:27.799904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:27.949518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T03:22:21.995253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:18.665972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:19.321864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:19.880504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:20.574816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:21.349377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:22.123677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:18.747430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:19.423735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:19.992188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:20.699723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:21.451896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:22.244236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:18.837473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:19.526150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:20.095335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:20.828117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:21.562009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:22.396190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:18.985472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:19.616071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:20.225929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:20.974230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:21.663460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:22.539328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:19.109981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:19.702264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:20.344251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:21.115257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:21.774542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:22.641971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:19.204257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:19.789866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:20.452127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:21.239433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:21.879577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:22:28.046768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호행정읍면동법정읍면동도엽번호도로구간번호설치일자주차장위치구분주차요금구분요금주차면수장애자주차면수전체면적운영시간(개장시간)운영시간(폐장시간)주차방향
관리번호1.0000.0140.3031.0001.0000.4540.6890.0840.1470.0000.0000.0000.3740.3840.137
행정읍면동0.0141.0000.6971.0000.9540.8920.5770.4920.6490.4920.2980.5080.3320.2970.573
법정읍면동0.3030.6971.0000.9970.8040.3780.6060.2360.5810.4320.0000.4550.5140.9120.195
도엽번호1.0001.0000.9971.0000.9971.0001.0000.8650.8850.8650.0000.8130.9251.0000.942
도로구간번호1.0000.9540.8040.9971.0000.8290.8260.6330.7150.2540.0000.1930.6020.7150.830
설치일자0.4540.8920.3781.0000.8291.0000.6740.4860.7010.3730.2500.3320.3790.3400.640
주차장위치구분0.6890.5770.6061.0000.8260.6741.0000.1890.3570.4870.1990.4400.7980.7940.291
주차요금구분0.0840.4920.2360.8650.6330.4860.1891.0000.7840.2860.0000.3721.0000.9990.257
요금0.1470.6490.5810.8850.7150.7010.3570.7841.0000.4000.0000.3540.6721.0000.606
주차면수0.0000.4920.4320.8650.2540.3730.4870.2860.4001.0000.0000.9500.3640.5390.456
장애자주차면수0.0000.2980.0000.0000.0000.2500.1990.0000.0000.0001.0000.0000.0000.0790.142
전체면적0.0000.5080.4550.8130.1930.3320.4400.3720.3540.9500.0001.0000.4120.5910.444
운영시간(개장시간)0.3740.3320.5140.9250.6020.3790.7981.0000.6720.3640.0000.4121.0001.0000.112
운영시간(폐장시간)0.3840.2970.9121.0000.7150.3400.7940.9991.0000.5390.0790.5911.0001.0000.125
주차방향0.1370.5730.1950.9420.8300.6400.2910.2570.6060.4560.1420.4440.1120.1251.000
2023-12-13T03:22:28.221072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주차방향주차장위치구분장애자주차면수요금주차요금구분
주차방향1.0000.4690.1070.2760.083
주차장위치구분0.4691.0000.2410.5670.309
장애자주차면수0.1070.2411.0000.0000.000
요금0.2760.5670.0001.0000.983
주차요금구분0.0830.3090.0000.9831.000
2023-12-13T03:22:28.362258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호행정읍면동법정읍면동도로구간번호주차면수전체면적주차장위치구분주차요금구분요금장애자주차면수주차방향
관리번호1.0000.1290.551-0.1840.4550.4190.4840.1400.2420.0000.227
행정읍면동0.1291.0000.3260.1900.2940.2310.8100.1650.2980.2420.261
법정읍면동0.5510.3261.000-0.0580.4100.4230.4270.2390.6010.0000.188
도로구간번호-0.1840.190-0.0581.000-0.0390.2460.6260.3260.6980.0000.515
주차면수0.4550.2940.410-0.0391.0000.8320.3800.1760.2850.0000.307
전체면적0.4190.2310.4230.2460.8321.0000.3330.2380.2360.0000.294
주차장위치구분0.4840.8100.4270.6260.3800.3331.0000.3090.5670.2410.469
주차요금구분0.1400.1650.2390.3260.1760.2380.3091.0000.9830.0000.083
요금0.2420.2980.6010.6980.2850.2360.5670.9831.0000.0000.276
장애자주차면수0.0000.2420.0000.0000.0000.0000.2410.0000.0001.0000.107
주차방향0.2270.2610.1880.5150.3070.2940.4690.0830.2760.1071.000

Missing values

2023-12-13T03:22:22.818959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:22:23.088606image/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.
2023-12-13T03:22:23.238475image/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

지형지물부호관리번호행정읍면동법정읍면동도엽번호관리기관도로구간번호설치일자주차장위치구분주차요금구분요금주차면수장애자주차면수전체면적운영시간(개장시간)운영시간(폐장시간)주차방향데이터기준일자
0AE230503747170143004717012100368072074DMNG00155782017-01-01PST001CHR001무료160109.00:000:00PKN0012023-08-31
1AE2302547170143004717012000368072065CMNG001650182017-01-01PST001CHR00230분당500원1012.18:0020:00PKN0032023-08-31
2AE23025247170145004717014000368072505BMNG00119952017-01-01PST001CHR001<NA>4056.94<NA><NA>PKN0012023-08-31
3AE23011847170143004717011900368072065DMNG001692017-01-01PST001CHR002<NA>100.0<NA><NA>PKN0012023-08-31
4AE230503447170143004717012100368072074CMNG00154732017-01-01PST001CHR001무료120153.90:000:00PKN0012023-08-31
5AE23023047170143004717011900368072085BMNG00115142017-01-01PST001CHR001<NA>170173.9<NA><NA>PKN0012023-08-31
6AE2303747170144004717011600368072076BMNG001761332017-01-01PST001CHR00230분당500원9098.248:0020:00PKN0032023-08-31
7AE23011047170143004717011700368072075BMNG001802017-01-01PST001CHR002<NA>700.0<NA><NA>PKN0012023-08-31
8AE23014347170144004717011600368072076AMNG001602017-01-01PST001CHR002<NA>1900.0<NA><NA>PKN0022023-08-31
9AE2302747170143004717012000368072065CMNG001650192017-01-01PST001CHR00230분당500원1011.698:0020:00PKN0032023-08-31
지형지물부호관리번호행정읍면동법정읍면동도엽번호관리기관도로구간번호설치일자주차장위치구분주차요금구분요금주차면수장애자주차면수전체면적운영시간(개장시간)운영시간(폐장시간)주차방향데이터기준일자
286AE230247170128004717012800368072054CMNG001540582017-01-01PST001CHR001<NA>3026.25<NA><NA>PKN0032023-08-31
287AE23023547170145004717014000368072096CMNG00119822017-01-01PST001CHR001<NA>170211.93<NA><NA>PKN0012023-08-31
288AE2308847170144004717011100368072078AMNG001780292017-01-01PST001CHR00230분당500원1011.818:0020:00PKN0032023-08-31
289AE230801047170555004717013000368081666AMNG00180232010-01-01PST002CHR001무료100420.440:000:00PKN0032023-08-31
290AE230803047170555004717013000368081666AMNG00180232010-01-01PST002CHR001무료10098.940:000:00PKN0032023-08-31
291AE2309547170144004717010900368072079AMNG001790242017-01-01PST001CHR001<NA>90284.85<NA><NA>PKN0012023-08-31
292AE2309447170144004717010900368072078BMNG001780172017-01-01PST001CHR001<NA>8086.95<NA><NA>PKN0032023-08-31
293AE23020347170110004717011000368081682CMNG0015142017-01-01PST001CHR001<NA>2022.3<NA><NA>PKN0012023-08-31
294AE230800147170555004717013000368081655DMNG00180052010-01-01PST002CHR001무료2222.180:000:00PKN0032023-08-31
295AE23021847170110004717011000368072089BMNG00114462017-01-01PST001CHR001<NA>7082.21<NA><NA>PKN0022023-08-31