Overview

Dataset statistics

Number of variables7
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory64.3 B

Variable types

Numeric3
Categorical2
Text2

Dataset

Description전라남도 영광군의 장애인전용주차구역 현황이 있는 자료입니다. 연번, 분류, 노상 및 노외 구분, 주차장 주소, 주차장 이름, 주차장 전체 주차면수 및 장애인 주차면수가 있습니다.
Author전라남도 영광군
URLhttps://www.data.go.kr/data/15106996/fileData.do

Alerts

분류 has constant value ""Constant
주차면수 is highly overall correlated with 장애인 주차면수High correlation
장애인 주차면수 is highly overall correlated with 주차면수High correlation
노상_노외 is highly imbalanced (75.8%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:56:57.896641
Analysis finished2023-12-12 07:56:59.146421
Duration1.25 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T16:56:59.507676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q17
median13
Q319
95-th percentile23.8
Maximum25
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.3598007
Coefficient of variation (CV)0.56613852
Kurtosis-1.2
Mean13
Median Absolute Deviation (MAD)6
Skewness0
Sum325
Variance54.166667
MonotonicityStrictly increasing
2023-12-12T16:56:59.636974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 1
 
4.0%
2 1
 
4.0%
25 1
 
4.0%
24 1
 
4.0%
23 1
 
4.0%
22 1
 
4.0%
21 1
 
4.0%
20 1
 
4.0%
19 1
 
4.0%
18 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
1 1
4.0%
2 1
4.0%
3 1
4.0%
4 1
4.0%
5 1
4.0%
6 1
4.0%
7 1
4.0%
8 1
4.0%
9 1
4.0%
10 1
4.0%
ValueCountFrequency (%)
25 1
4.0%
24 1
4.0%
23 1
4.0%
22 1
4.0%
21 1
4.0%
20 1
4.0%
19 1
4.0%
18 1
4.0%
17 1
4.0%
16 1
4.0%

분류
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
공영
25 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공영 25
100.0%

Length

2023-12-12T16:56:59.765729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:56:59.916522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공영 25
100.0%

노상_노외
Categorical

IMBALANCE 

Distinct2
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
노외
24 
노회
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)4.0%

Sample

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

Common Values

ValueCountFrequency (%)
노외 24
96.0%
노회 1
 
4.0%

Length

2023-12-12T16:57:00.029326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:57:00.134899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노외 24
96.0%
노회 1
 
4.0%

주소
Text

Distinct22
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T16:57:00.307991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length22.84
Min length19

Characters and Unicode

Total characters571
Distinct characters64
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

Unique21 ?
Unique (%)84.0%

Sample

1st row전라남도 영광군 영광읍 남천리 326, 신하리 32-14
2nd row전라남도 영광군 영광읍 단주리579-4
3rd row전라남도 영광군 영광읍 도동리270 (우등숯불)
4th row전라남도 영광군 영광읍 도동리 270(고궁식당앞)
5th row전라남도 영광군 영광읍 도동리 107-88
ValueCountFrequency (%)
전라남도 25
20.3%
영광군 25
20.3%
영광읍 17
13.8%
단주리672 4
 
3.3%
도동리 3
 
2.4%
홍농읍 3
 
2.4%
계마리 2
 
1.6%
백수읍 2
 
1.6%
남천리 2
 
1.6%
염산면 2
 
1.6%
Other values (35) 38
30.9%
2023-12-12T16:57:00.704448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
98
17.2%
영 42
 
7.4%
광 42
 
7.4%
남 30
 
5.3%
도 29
 
5.1%
전 25
 
4.4%
군 25
 
4.4%
라 25
 
4.4%
리 24
 
4.2%
읍 23
 
4.0%
Other values (54) 208
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 352
61.6%
Decimal Number 99
 
17.3%
Space Separator 98
 
17.2%
Dash Punctuation 13
 
2.3%
Close Punctuation 4
 
0.7%
Open Punctuation 4
 
0.7%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 42
11.9%
광 42
11.9%
남 30
 
8.5%
도 29
 
8.2%
전 25
 
7.1%
군 25
 
7.1%
라 25
 
7.1%
리 24
 
6.8%
읍 23
 
6.5%
단 6
 
1.7%
Other values (39) 81
23.0%
Decimal Number
ValueCountFrequency (%)
1 20
20.2%
2 17
17.2%
0 11
11.1%
7 11
11.1%
3 9
9.1%
6 9
9.1%
8 8
 
8.1%
9 7
 
7.1%
4 4
 
4.0%
5 3
 
3.0%
Space Separator
ValueCountFrequency (%)
98
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 352
61.6%
Common 219
38.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 42
11.9%
광 42
11.9%
남 30
 
8.5%
도 29
 
8.2%
전 25
 
7.1%
군 25
 
7.1%
라 25
 
7.1%
리 24
 
6.8%
읍 23
 
6.5%
단 6
 
1.7%
Other values (39) 81
23.0%
Common
ValueCountFrequency (%)
98
44.7%
1 20
 
9.1%
2 17
 
7.8%
- 13
 
5.9%
0 11
 
5.0%
7 11
 
5.0%
3 9
 
4.1%
6 9
 
4.1%
8 8
 
3.7%
9 7
 
3.2%
Other values (5) 16
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 352
61.6%
ASCII 219
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
98
44.7%
1 20
 
9.1%
2 17
 
7.8%
- 13
 
5.9%
0 11
 
5.0%
7 11
 
5.0%
3 9
 
4.1%
6 9
 
4.1%
8 8
 
3.7%
9 7
 
3.2%
Other values (5) 16
 
7.3%
Hangul
ValueCountFrequency (%)
영 42
11.9%
광 42
11.9%
남 30
 
8.5%
도 29
 
8.2%
전 25
 
7.1%
군 25
 
7.1%
라 25
 
7.1%
리 24
 
6.8%
읍 23
 
6.5%
단 6
 
1.7%
Other values (39) 81
23.0%

주차장명
Text

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T16:57:00.940698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length11.56
Min length8

Characters and Unicode

Total characters289
Distinct characters89
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

Unique23 ?
Unique (%)92.0%

Sample

1st row우시장 주차광장
2nd row영광터미널 공용주차장
3rd row영광메일시장제1주차장
4th row영광메일시장제1주차장
5th row청소년문화센터 주차장
ValueCountFrequency (%)
공용주차장 7
 
13.5%
주차장 5
 
9.6%
스포티움 4
 
7.7%
영광군청 2
 
3.8%
가마미해수욕장 2
 
3.8%
부설주차장 2
 
3.8%
영광메일시장제1주차장 2
 
3.8%
광장 1
 
1.9%
제1주차장 1
 
1.9%
부설(제3주차장 1
 
1.9%
Other values (25) 25
48.1%
2023-12-12T16:57:01.328589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 32
 
11.1%
28
 
9.7%
주 25
 
8.7%
차 25
 
8.7%
제 8
 
2.8%
광 8
 
2.8%
공 8
 
2.8%
용 7
 
2.4%
설 7
 
2.4%
영 6
 
2.1%
Other values (79) 135
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 245
84.8%
Space Separator 28
 
9.7%
Decimal Number 8
 
2.8%
Close Punctuation 4
 
1.4%
Open Punctuation 4
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 32
 
13.1%
주 25
 
10.2%
차 25
 
10.2%
제 8
 
3.3%
광 8
 
3.3%
공 8
 
3.3%
용 7
 
2.9%
설 7
 
2.9%
영 6
 
2.4%
부 6
 
2.4%
Other values (72) 113
46.1%
Decimal Number
ValueCountFrequency (%)
1 4
50.0%
2 2
25.0%
9 1
 
12.5%
3 1
 
12.5%
Space Separator
ValueCountFrequency (%)
28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 245
84.8%
Common 44
 
15.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 32
 
13.1%
주 25
 
10.2%
차 25
 
10.2%
제 8
 
3.3%
광 8
 
3.3%
공 8
 
3.3%
용 7
 
2.9%
설 7
 
2.9%
영 6
 
2.4%
부 6
 
2.4%
Other values (72) 113
46.1%
Common
ValueCountFrequency (%)
28
63.6%
) 4
 
9.1%
( 4
 
9.1%
1 4
 
9.1%
2 2
 
4.5%
9 1
 
2.3%
3 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 245
84.8%
ASCII 44
 
15.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 32
 
13.1%
주 25
 
10.2%
차 25
 
10.2%
제 8
 
3.3%
광 8
 
3.3%
공 8
 
3.3%
용 7
 
2.9%
설 7
 
2.9%
영 6
 
2.4%
부 6
 
2.4%
Other values (72) 113
46.1%
ASCII
ValueCountFrequency (%)
28
63.6%
) 4
 
9.1%
( 4
 
9.1%
1 4
 
9.1%
2 2
 
4.5%
9 1
 
2.3%
3 1
 
2.3%

주차면수
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean152.84
Minimum10
Maximum700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T16:57:01.475938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile20.6
Q143
median113
Q3172
95-th percentile591.6
Maximum700
Range690
Interquartile range (IQR)129

Descriptive statistics

Standard deviation176.76366
Coefficient of variation (CV)1.1565275
Kurtosis5.701739
Mean152.84
Median Absolute Deviation (MAD)70
Skewness2.3892443
Sum3821
Variance31245.39
MonotonicityNot monotonic
2023-12-12T16:57:01.588365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
40 2
 
8.0%
150 1
 
4.0%
136 1
 
4.0%
154 1
 
4.0%
118 1
 
4.0%
209 1
 
4.0%
700 1
 
4.0%
20 1
 
4.0%
46 1
 
4.0%
10 1
 
4.0%
Other values (14) 14
56.0%
ValueCountFrequency (%)
10 1
4.0%
20 1
4.0%
23 1
4.0%
33 1
4.0%
40 2
8.0%
43 1
4.0%
46 1
4.0%
50 1
4.0%
53 1
4.0%
81 1
4.0%
ValueCountFrequency (%)
700 1
4.0%
675 1
4.0%
258 1
4.0%
255 1
4.0%
209 1
4.0%
202 1
4.0%
172 1
4.0%
154 1
4.0%
150 1
4.0%
145 1
4.0%

장애인 주차면수
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.28
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T16:57:01.714195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median2
Q35
95-th percentile12.4
Maximum20
Range19
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.3638668
Coefficient of variation (CV)1.019595
Kurtosis6.7092278
Mean4.28
Median Absolute Deviation (MAD)0
Skewness2.5050552
Sum107
Variance19.043333
MonotonicityNot monotonic
2023-12-12T16:57:01.857562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 13
52.0%
3 3
 
12.0%
5 2
 
8.0%
6 1
 
4.0%
8 1
 
4.0%
13 1
 
4.0%
4 1
 
4.0%
1 1
 
4.0%
10 1
 
4.0%
20 1
 
4.0%
ValueCountFrequency (%)
1 1
 
4.0%
2 13
52.0%
3 3
 
12.0%
4 1
 
4.0%
5 2
 
8.0%
6 1
 
4.0%
8 1
 
4.0%
10 1
 
4.0%
13 1
 
4.0%
20 1
 
4.0%
ValueCountFrequency (%)
20 1
 
4.0%
13 1
 
4.0%
10 1
 
4.0%
8 1
 
4.0%
6 1
 
4.0%
5 2
 
8.0%
4 1
 
4.0%
3 3
 
12.0%
2 13
52.0%
1 1
 
4.0%

Interactions

2023-12-12T16:56:58.706198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:58.212780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:58.447294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:58.785432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:58.290429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:58.526889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:58.878155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:58.366118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:58.620106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:57:01.946926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번노상_노외주소주차장명주차면수장애인 주차면수
연번1.0000.0000.9470.9140.6950.479
노상_노외0.0001.0001.0001.0000.0000.000
주소0.9471.0001.0000.9520.0000.000
주차장명0.9141.0000.9521.0000.9291.000
주차면수0.6950.0000.0000.9291.0000.784
장애인 주차면수0.4790.0000.0001.0000.7841.000
2023-12-12T16:57:02.074447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번주차면수장애인 주차면수노상_노외
연번1.0000.0270.0440.000
주차면수0.0271.0000.7950.000
장애인 주차면수0.0440.7951.0000.000
노상_노외0.0000.0000.0001.000

Missing values

2023-12-12T16:56:58.994000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:56:59.105934image/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

연번분류노상_노외주소주차장명주차면수장애인 주차면수
01공영노외전라남도 영광군 영광읍 남천리 326, 신하리 32-14우시장 주차광장1503
12공영노외전라남도 영광군 영광읍 단주리579-4영광터미널 공용주차장2025
23공영노외전라남도 영광군 영광읍 도동리270 (우등숯불)영광메일시장제1주차장812
34공영노외전라남도 영광군 영광읍 도동리 270(고궁식당앞)영광메일시장제1주차장532
45공영노외전라남도 영광군 영광읍 도동리 107-88청소년문화센터 주차장402
56공영노외전라남도 영광군 영광읍 백학리359-14만남의 광장 주차장952
67공영노외전라남도 영광군 영광읍 무령리 186영광군청 제1주차장1132
78공영노외전라남도 영광군 영광읍 단주리 629-12대신지구 제2주차장403
89공영노외전라남도 영광군 영광읍 신남로100-35영광고추시장 부설주차장2586
910공영노외전라남도 영광군 영광읍 무령리 187영광군청 부설주차장1725
연번분류노상_노외주소주차장명주차면수장애인 주차면수
1516공영노외전라남도 영광군 영광읍 단주리672스포티움 부설(양궁주차장)332
1617공영노외전라남도 영광군 백수읍 법백로 39 (백수읍 길용리)백수생활체육공원 주차장1452
1718공영노외전라남도 영광군 홍농읍 동부로13(홍농읍 상하리)홍농복지회관 주차장501
1819공영노외전라남도 영광군 법성면 법성리 691법성매립지 제9주차장102
1920공영노회전라남도 영광군 법성면 법성리 1223-17법성 뉴타운 공용주차장462
2021공영노외전라남도 영광군 홍농읍 계마리 880-1가마미해수욕장 입구 공용주차장202
2122공영노외전라남도 영광군 홍농읍 계마리 798-3외 20필지가마미해수욕장 공용주차장70010
2223공영노외전라남도 영광군 염산면 봉남리 1220-8설도 젓갈타운 공용주차장20920
2324공영노외전라남도 영광군 염산면 옥실리 1106-40칠산타워 공용주차장1182
2425공영노외전라남도 영광군 영광읍 도동리 91-1물무산행복숲주차장1543