Overview

Dataset statistics

Number of variables12
Number of observations74
Missing cells23
Missing cells (%)2.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.4 KiB
Average record size in memory101.7 B

Variable types

Numeric4
Categorical6
Text2

Dataset

Description이 데이터는 충청남도 아산시의 주차장 정보를 담고 있습니다. 주차장명, 주차장주소, 운영방식, 주차장층수, 주차장면적, 주차면수, 관리부서 등의 정보를 포함합니다.
Author충청남도 아산시
URLhttps://www.data.go.kr/data/15090162/fileData.do

Alerts

전화번호 has constant value ""Constant
관리부서 has constant value ""Constant
연번 is highly overall correlated with 설치연도 and 1 other fieldsHigh correlation
전체면적(제곱미터) is highly overall correlated with 주차면수High correlation
주차면수 is highly overall correlated with 전체면적(제곱미터) and 1 other fieldsHigh correlation
설치연도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
운영방식 is highly overall correlated with 주차면수 and 2 other fieldsHigh correlation
주차장 층수 is highly overall correlated with 운영방식High correlation
주차요금유무 is highly overall correlated with 운영방식High correlation
주차장 층수 is highly imbalanced (76.3%)Imbalance
주차요금유무 is highly imbalanced (65.2%)Imbalance
설치연도 has 23 (31.1%) missing valuesMissing
연번 has unique valuesUnique
주차장명 has unique valuesUnique
주소지(도로명주소 또는 지번) has unique valuesUnique

Reproduction

Analysis started2024-03-15 02:05:52.418071
Analysis finished2024-03-15 02:05:57.403729
Duration4.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.5
Minimum1
Maximum74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size794.0 B
2024-03-15T11:05:57.534989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.65
Q119.25
median37.5
Q355.75
95-th percentile70.35
Maximum74
Range73
Interquartile range (IQR)36.5

Descriptive statistics

Standard deviation21.505813
Coefficient of variation (CV)0.57348835
Kurtosis-1.2
Mean37.5
Median Absolute Deviation (MAD)18.5
Skewness0
Sum2775
Variance462.5
MonotonicityStrictly increasing
2024-03-15T11:05:57.818213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
57 1
 
1.4%
55 1
 
1.4%
54 1
 
1.4%
53 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
Other values (64) 64
86.5%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
74 1
1.4%
73 1
1.4%
72 1
1.4%
71 1
1.4%
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size720.0 B
노외
51 
노상
23 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노외 51
68.9%
노상 23
31.1%

Length

2024-03-15T11:05:58.072650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:05:58.253709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노외 51
68.9%
노상 23
31.1%

주차장명
Text

UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size720.0 B
2024-03-15T11:05:59.065824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length12.689189
Min length9

Characters and Unicode

Total characters939
Distinct characters84
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)100.0%

Sample

1st row시민로 노상주차장
2nd row배방읍 장재리 제1노상주차장
3rd row배방읍 장재리 제4노상주차장
4th row청운로 제2노상주차장
5th row삼동로 노상주차장
ValueCountFrequency (%)
노상주차장 12
 
7.1%
배방읍 12
 
7.1%
제1공영주차장 11
 
6.5%
제2공영주차장 9
 
5.3%
탕정지구 9
 
5.3%
제3공영주차장 8
 
4.7%
온천동 8
 
4.7%
제4공영주차장 6
 
3.5%
공영주차장 6
 
3.5%
북수리 6
 
3.5%
Other values (52) 83
48.8%
2024-03-15T11:06:00.525634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
96
 
10.2%
주 78
 
8.3%
장 77
 
8.2%
차 75
 
8.0%
제 58
 
6.2%
공 56
 
6.0%
영 53
 
5.6%
노 28
 
3.0%
동 25
 
2.7%
리 24
 
2.6%
Other values (74) 369
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 770
82.0%
Space Separator 96
 
10.2%
Decimal Number 73
 
7.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 78
 
10.1%
장 77
 
10.0%
차 75
 
9.7%
제 58
 
7.5%
공 56
 
7.3%
영 53
 
6.9%
노 28
 
3.6%
동 25
 
3.2%
리 24
 
3.1%
상 23
 
3.0%
Other values (64) 273
35.5%
Decimal Number
ValueCountFrequency (%)
1 16
21.9%
2 16
21.9%
3 12
16.4%
4 9
12.3%
5 6
 
8.2%
6 5
 
6.8%
9 4
 
5.5%
7 4
 
5.5%
8 1
 
1.4%
Space Separator
ValueCountFrequency (%)
96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 770
82.0%
Common 169
 
18.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 78
 
10.1%
장 77
 
10.0%
차 75
 
9.7%
제 58
 
7.5%
공 56
 
7.3%
영 53
 
6.9%
노 28
 
3.6%
동 25
 
3.2%
리 24
 
3.1%
상 23
 
3.0%
Other values (64) 273
35.5%
Common
ValueCountFrequency (%)
96
56.8%
1 16
 
9.5%
2 16
 
9.5%
3 12
 
7.1%
4 9
 
5.3%
5 6
 
3.6%
6 5
 
3.0%
9 4
 
2.4%
7 4
 
2.4%
8 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 770
82.0%
ASCII 169
 
18.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
96
56.8%
1 16
 
9.5%
2 16
 
9.5%
3 12
 
7.1%
4 9
 
5.3%
5 6
 
3.6%
6 5
 
3.0%
9 4
 
2.4%
7 4
 
2.4%
8 1
 
0.6%
Hangul
ValueCountFrequency (%)
주 78
 
10.1%
장 77
 
10.0%
차 75
 
9.7%
제 58
 
7.5%
공 56
 
7.3%
영 53
 
6.9%
노 28
 
3.6%
동 25
 
3.2%
리 24
 
3.1%
상 23
 
3.0%
Other values (64) 273
35.5%

주소지(도로명주소 또는 지번)
Text

UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size720.0 B
2024-03-15T11:06:01.804998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length29.5
Mean length20.094595
Min length9

Characters and Unicode

Total characters1487
Distinct characters150
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)100.0%

Sample

1st row온천대로 교차로(온양관광호텔)~시민로 442번길 교차로
2nd rowKTX천안아산역 2번 출구 교통광장 일원
3rd row배방읍 장재리 2011번지
4th row온양제분소~문화로 교차로(새소망교회)
5th row삼동로 8번길(온수주차장)~문화로 교차로
ValueCountFrequency (%)
충청남도 51
 
16.3%
아산시 51
 
16.3%
배방읍 13
 
4.2%
탕정면 7
 
2.2%
매곡리 7
 
2.2%
온천동 7
 
2.2%
교차로 6
 
1.9%
북수리 6
 
1.9%
둔포면 6
 
1.9%
방축동 4
 
1.3%
Other values (137) 155
49.5%
2024-03-15T11:06:03.322086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
239
 
16.1%
1 59
 
4.0%
아 57
 
3.8%
산 57
 
3.8%
도 55
 
3.7%
시 55
 
3.7%
청 52
 
3.5%
남 52
 
3.5%
충 51
 
3.4%
로 47
 
3.2%
Other values (140) 763
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 942
63.3%
Decimal Number 244
 
16.4%
Space Separator 239
 
16.1%
Math Symbol 16
 
1.1%
Close Punctuation 13
 
0.9%
Open Punctuation 13
 
0.9%
Dash Punctuation 12
 
0.8%
Other Punctuation 4
 
0.3%
Uppercase Letter 3
 
0.2%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 57
 
6.1%
산 57
 
6.1%
도 55
 
5.8%
시 55
 
5.8%
청 52
 
5.5%
남 52
 
5.5%
충 51
 
5.4%
로 47
 
5.0%
리 37
 
3.9%
교 28
 
3.0%
Other values (120) 451
47.9%
Decimal Number
ValueCountFrequency (%)
1 59
24.2%
2 36
14.8%
4 25
10.2%
9 22
 
9.0%
3 21
 
8.6%
6 19
 
7.8%
0 18
 
7.4%
5 18
 
7.4%
8 13
 
5.3%
7 13
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
K 1
33.3%
T 1
33.3%
X 1
33.3%
Space Separator
ValueCountFrequency (%)
239
100.0%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 942
63.3%
Common 541
36.4%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 57
 
6.1%
산 57
 
6.1%
도 55
 
5.8%
시 55
 
5.8%
청 52
 
5.5%
남 52
 
5.5%
충 51
 
5.4%
로 47
 
5.0%
리 37
 
3.9%
교 28
 
3.0%
Other values (120) 451
47.9%
Common
ValueCountFrequency (%)
239
44.2%
1 59
 
10.9%
2 36
 
6.7%
4 25
 
4.6%
9 22
 
4.1%
3 21
 
3.9%
6 19
 
3.5%
0 18
 
3.3%
5 18
 
3.3%
~ 16
 
3.0%
Other values (6) 68
 
12.6%
Latin
ValueCountFrequency (%)
K 1
25.0%
T 1
25.0%
X 1
25.0%
m 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 942
63.3%
ASCII 545
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
239
43.9%
1 59
 
10.8%
2 36
 
6.6%
4 25
 
4.6%
9 22
 
4.0%
3 21
 
3.9%
6 19
 
3.5%
0 18
 
3.3%
5 18
 
3.3%
~ 16
 
2.9%
Other values (10) 72
 
13.2%
Hangul
ValueCountFrequency (%)
아 57
 
6.1%
산 57
 
6.1%
도 55
 
5.8%
시 55
 
5.8%
청 52
 
5.5%
남 52
 
5.5%
충 51
 
5.4%
로 47
 
5.0%
리 37
 
3.9%
교 28
 
3.0%
Other values (120) 451
47.9%

운영방식
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size720.0 B
직영
62 
위탁
12 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row위탁
2nd row위탁
3rd row위탁
4th row직영
5th row직영

Common Values

ValueCountFrequency (%)
직영 62
83.8%
위탁 12
 
16.2%

Length

2024-03-15T11:06:03.789561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:06:04.159929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
직영 62
83.8%
위탁 12
 
16.2%

주차장 층수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size720.0 B
지평식
68 
지상4층
 
3
지상3층
 
1
지하1층/지상4층
 
1
지상1층
 
1

Length

Max length9
Median length3
Mean length3.1486486
Min length3

Unique

Unique3 ?
Unique (%)4.1%

Sample

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

Common Values

ValueCountFrequency (%)
지평식 68
91.9%
지상4층 3
 
4.1%
지상3층 1
 
1.4%
지하1층/지상4층 1
 
1.4%
지상1층 1
 
1.4%

Length

2024-03-15T11:06:04.439426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:06:04.684100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지평식 68
91.9%
지상4층 3
 
4.1%
지상3층 1
 
1.4%
지하1층/지상4층 1
 
1.4%
지상1층 1
 
1.4%

전체면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct70
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1533.9262
Minimum84
Maximum12449.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size794.0 B
2024-03-15T11:06:05.149042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum84
5-th percentile163.8
Q1592.5
median971.15
Q31973.7
95-th percentile4723.566
Maximum12449.1
Range12365.1
Interquartile range (IQR)1381.2

Descriptive statistics

Standard deviation1785.4802
Coefficient of variation (CV)1.1639935
Kurtosis18.674189
Mean1533.9262
Median Absolute Deviation (MAD)523.6
Skewness3.6160413
Sum113510.54
Variance3187939.5
MonotonicityNot monotonic
2024-03-15T11:06:05.435733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
276.0 2
 
2.7%
984.0 2
 
2.7%
156.0 2
 
2.7%
552.0 2
 
2.7%
84.0 1
 
1.4%
3477.5 1
 
1.4%
2849.76 1
 
1.4%
700.5 1
 
1.4%
804.2 1
 
1.4%
670.1 1
 
1.4%
Other values (60) 60
81.1%
ValueCountFrequency (%)
84.0 1
1.4%
108.0 1
1.4%
156.0 2
2.7%
168.0 1
1.4%
216.0 1
1.4%
240.0 1
1.4%
248.0 1
1.4%
276.0 2
2.7%
321.0 1
1.4%
324.0 1
1.4%
ValueCountFrequency (%)
12449.1 1
1.4%
5153.0 1
1.4%
5140.0 1
1.4%
4954.16 1
1.4%
4599.4 1
1.4%
4167.0 1
1.4%
3477.5 1
1.4%
3064.5 1
1.4%
3023.2 1
1.4%
2914.12 1
1.4%

주차면수
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)71.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.310811
Minimum7
Maximum355
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size794.0 B
2024-03-15T11:06:05.692383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile12.65
Q125.25
median40
Q380
95-th percentile166.7
Maximum355
Range348
Interquartile range (IQR)54.75

Descriptive statistics

Standard deviation55.253569
Coefficient of variation (CV)0.93159355
Kurtosis10.673224
Mean59.310811
Median Absolute Deviation (MAD)21.5
Skewness2.7126158
Sum4389
Variance3052.9569
MonotonicityNot monotonic
2024-03-15T11:06:06.045874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30 4
 
5.4%
28 3
 
4.1%
40 2
 
2.7%
97 2
 
2.7%
88 2
 
2.7%
39 2
 
2.7%
25 2
 
2.7%
64 2
 
2.7%
83 2
 
2.7%
20 2
 
2.7%
Other values (43) 51
68.9%
ValueCountFrequency (%)
7 1
1.4%
8 1
1.4%
9 1
1.4%
12 1
1.4%
13 2
2.7%
14 1
1.4%
17 1
1.4%
18 2
2.7%
19 1
1.4%
20 2
2.7%
ValueCountFrequency (%)
355 1
1.4%
188 1
1.4%
175 1
1.4%
168 1
1.4%
166 1
1.4%
165 1
1.4%
140 1
1.4%
132 1
1.4%
97 2
2.7%
95 1
1.4%

주차요금유무
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size720.0 B
무
64 
유(무인)
8 
무(무인)
 
1
유
 
1

Length

Max length5
Median length1
Mean length1.4864865
Min length1

Unique

Unique2 ?
Unique (%)2.7%

Sample

1st row무(무인)
2nd row유(무인)
3rd row유
4th row무
5th row무

Common Values

ValueCountFrequency (%)
무 64
86.5%
유(무인) 8
 
10.8%
무(무인) 1
 
1.4%
유 1
 
1.4%

Length

2024-03-15T11:06:06.328856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:06:06.538935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무 64
86.5%
유(무인 8
 
10.8%
무(무인 1
 
1.4%
유 1
 
1.4%

설치연도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct13
Distinct (%)25.5%
Missing23
Missing (%)31.1%
Infinite0
Infinite (%)0.0%
Mean2017.549
Minimum2003
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size794.0 B
2024-03-15T11:06:06.793696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2003
5-th percentile2007
Q12015
median2019
Q32022
95-th percentile2023
Maximum2023
Range20
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.3528076
Coefficient of variation (CV)0.0026531239
Kurtosis-0.087752915
Mean2017.549
Median Absolute Deviation (MAD)3
Skewness-0.94139553
Sum102895
Variance28.652549
MonotonicityNot monotonic
2024-03-15T11:06:07.183832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2023 10
13.5%
2019 9
 
12.2%
2021 6
 
8.1%
2010 5
 
6.8%
2022 5
 
6.8%
2015 4
 
5.4%
2016 4
 
5.4%
2007 3
 
4.1%
2017 1
 
1.4%
2011 1
 
1.4%
Other values (3) 3
 
4.1%
(Missing) 23
31.1%
ValueCountFrequency (%)
2003 1
 
1.4%
2007 3
 
4.1%
2010 5
6.8%
2011 1
 
1.4%
2012 1
 
1.4%
2015 4
5.4%
2016 4
5.4%
2017 1
 
1.4%
2019 9
12.2%
2020 1
 
1.4%
ValueCountFrequency (%)
2023 10
13.5%
2022 5
6.8%
2021 6
8.1%
2020 1
 
1.4%
2019 9
12.2%
2017 1
 
1.4%
2016 4
 
5.4%
2015 4
 
5.4%
2012 1
 
1.4%
2011 1
 
1.4%

전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size720.0 B
041-540-2746
74 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row041-540-2746
2nd row041-540-2746
3rd row041-540-2746
4th row041-540-2746
5th row041-540-2746

Common Values

ValueCountFrequency (%)
041-540-2746 74
100.0%

Length

2024-03-15T11:06:07.466415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:06:07.641934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
041-540-2746 74
100.0%

관리부서
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size720.0 B
교통행정과
74 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
교통행정과 74
100.0%

Length

2024-03-15T11:06:07.837111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:06:08.107303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교통행정과 74
100.0%

Interactions

2024-03-15T11:05:55.752714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:05:53.278461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:05:54.187986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:05:54.904391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:05:55.955853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:05:53.539770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:05:54.345852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:05:55.228084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:05:56.218135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:05:53.803947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:05:54.516086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:05:55.382862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:05:56.486499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:05:54.024317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:05:54.679105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:05:55.550559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T11:06:08.329458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분주차장명주소지(도로명주소 또는 지번)운영방식주차장 층수전체면적(제곱미터)주차면수주차요금유무설치연도
연번1.0000.9991.0001.0000.0440.3740.5370.4090.0000.700
구분0.9991.0001.0001.0000.0000.0000.5520.0000.294NaN
주차장명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
주소지(도로명주소 또는 지번)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
운영방식0.0440.0001.0001.0001.0000.5380.6190.5190.9860.409
주차장 층수0.3740.0001.0001.0000.5381.0000.5430.4810.4610.000
전체면적(제곱미터)0.5370.5521.0001.0000.6190.5431.0000.8380.2540.438
주차면수0.4090.0001.0001.0000.5190.4810.8381.0000.0000.596
주차요금유무0.0000.2941.0001.0000.9860.4610.2540.0001.0000.300
설치연도0.700NaN1.0001.0000.4090.0000.4380.5960.3001.000
2024-03-15T11:06:08.708624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분주차요금유무운영방식주차장 층수
구분1.0000.1920.0000.000
주차요금유무0.1921.0000.8810.389
운영방식0.0000.8811.0000.638
주차장 층수0.0000.3890.6381.000
2024-03-15T11:06:08.990961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번전체면적(제곱미터)주차면수설치연도구분운영방식주차장 층수주차요금유무
연번1.0000.4940.2130.6050.9130.0000.1530.000
전체면적(제곱미터)0.4941.0000.8350.0590.3870.4370.4020.161
주차면수0.2130.8351.0000.0040.0000.5370.3270.000
설치연도0.6050.0590.0041.0001.0000.2570.0000.164
구분0.9130.3870.0001.0001.0000.0000.0000.192
운영방식0.0000.4370.5370.2570.0001.0000.6380.881
주차장 층수0.1530.4020.3270.0000.0000.6381.0000.389
주차요금유무0.0000.1610.0000.1640.1920.8810.3891.000

Missing values

2024-03-15T11:05:56.865531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T11:05:57.210307image/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

연번구분주차장명주소지(도로명주소 또는 지번)운영방식주차장 층수전체면적(제곱미터)주차면수주차요금유무설치연도전화번호관리부서
01노상시민로 노상주차장온천대로 교차로(온양관광호텔)~시민로 442번길 교차로위탁지평식84.07무(무인)<NA>041-540-2746교통행정과
12노상배방읍 장재리 제1노상주차장KTX천안아산역 2번 출구 교통광장 일원위탁지평식1140.095유(무인)<NA>041-540-2746교통행정과
23노상배방읍 장재리 제4노상주차장배방읍 장재리 2011번지위탁지평식276.023유<NA>041-540-2746교통행정과
34노상청운로 제2노상주차장온양제분소~문화로 교차로(새소망교회)직영지평식900.075무<NA>041-540-2746교통행정과
45노상삼동로 노상주차장삼동로 8번길(온수주차장)~문화로 교차로직영지평식984.082무<NA>041-540-2746교통행정과
56노상청운로96번길 노상주차장온양온천초교 담장길직영지평식168.014무<NA>041-540-2746교통행정과
67노상온양역길 노상주차장청운로 교차로~외암로 교차로직영지평식216.018무<NA>041-540-2746교통행정과
78노상온천동 제2노상주차장시민로 교차로(기아자동차)~아산로 교차로(쌍용자동차)직영지평식960.080무<NA>041-540-2746교통행정과
89노상온천동 제5노상주차장온천동 우체국 뒷길직영지평식156.013무<NA>041-540-2746교통행정과
910노상온천동 제6노상주차장외암로 교차로~하모니마트직영지평식552.046무<NA>041-540-2746교통행정과
연번구분주차장명주소지(도로명주소 또는 지번)운영방식주차장 층수전체면적(제곱미터)주차면수주차요금유무설치연도전화번호관리부서
6465노외둔포면 둔포리 공영주차장충청남도 아산시 둔포면 둔포리 458-16직영지평식2249.088무2023041-540-2746교통행정과
6566노외탕정지구 제1공영주차장충청남도 아산시 탕정면 매곡리 1167직영지평식321.028무2023041-540-2746교통행정과
6667노외탕정지구 제2공영주차장충청남도 아산시 탕정면 매곡리 1202직영지평식5140.0188무2023041-540-2746교통행정과
6768노외탕정지구 제3공영주차장충청남도 아산시 탕정면 매곡리 1240직영지평식1240.038무2023041-540-2746교통행정과
6869노외탕정지구 제4공영주차장충청남도 아산시 탕정면 매곡리 1272직영지평식1133.042무2023041-540-2746교통행정과
6970노외탕정지구 제5공영주차장충청남도 아산시 탕정면 매곡리 1329직영지평식815.030무2023041-540-2746교통행정과
7071노외탕정지구 제6공영주차장충청남도 아산시 탕정면 매곡리 1374직영지평식590.018무2023041-540-2746교통행정과
7172노외탕정지구 제7공영주차장충청남도 아산시 탕정면 매곡리 1408직영지평식1210.044무2023041-540-2746교통행정과
7273노외탕정지구 제8공영주차장충청남도 아산시 배방읍 세교리 1532직영지평식1570.057무2023041-540-2746교통행정과
7374노외탕정지구 제9공영주차장충청남도 아산시 배방읍 세교리 1576직영지평식1080.034무2023041-540-2746교통행정과