Overview

Dataset statistics

Number of variables17
Number of observations166
Missing cells153
Missing cells (%)5.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.8 KiB
Average record size in memory140.8 B

Variable types

Categorical11
Text4
Numeric2

Dataset

Description경기도 광주시 그늘막설치현황에 대한 데이터로 관리번호, 설치장소명, 소재지주소, 설치일자, 높이, 펼침지름, 원단, 위도, 경도 등을 제공합니다.
Author경기도 광주시
URLhttps://www.data.go.kr/data/15060585/fileData.do

Alerts

시군명 has constant value ""Constant
원단 has constant value ""Constant
당해년도운영시작일자 has constant value ""Constant
당해년도운영종료일자 has constant value ""Constant
관리기관명 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 읍면동명 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 읍면동명 and 1 other fieldsHigh correlation
읍면동명 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
설치일자 is highly overall correlated with 위도 and 4 other fieldsHigh correlation
높이 is highly overall correlated with 읍면동명 and 2 other fieldsHigh correlation
펼침지름 is highly overall correlated with 설치일자 and 1 other fieldsHigh correlation
소재지도로명주소 has 153 (92.2%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-23 07:54:03.882673
Analysis finished2023-12-23 07:54:09.921908
Duration6.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
광주시
166 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광주시 166
100.0%

Length

2023-12-23T07:54:10.189183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T07:54:10.709805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광주시 166
100.0%

읍면동명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
광남2동
49 
오포읍
34 
광남1동
25 
초월읍
12 
곤지암읍
12 
Other values (8)
34 

Length

Max length5
Median length4
Mean length3.5963855
Min length3

Unique

Unique2 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
광남2동 49
29.5%
오포읍 34
20.5%
광남1동 25
15.1%
초월읍 12
 
7.2%
곤지암읍 12
 
7.2%
경안동 12
 
7.2%
탄벌동 6
 
3.6%
오포1동 5
 
3.0%
남한산성면 4
 
2.4%
송정동 3
 
1.8%
Other values (3) 4
 
2.4%

Length

2023-12-23T07:54:11.572132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
광남2동 49
29.5%
오포읍 34
20.5%
광남1동 25
15.1%
초월읍 12
 
7.2%
곤지암읍 12
 
7.2%
경안동 12
 
7.2%
탄벌동 6
 
3.6%
오포1동 5
 
3.0%
남한산성면 4
 
2.4%
송정동 3
 
1.8%
Other values (3) 4
 
2.4%

관리번호
Text

UNIQUE 

Distinct166
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-23T07:54:13.119748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1445783
Min length5

Characters and Unicode

Total characters1020
Distinct characters38
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

Unique166 ?
Unique (%)100.0%

Sample

1st row오포읍-1
2nd row오포읍-2
3rd row오포읍-3
4th row오포읍-4
5th row오포읍-5
ValueCountFrequency (%)
오포읍-1 1
 
0.6%
광남1동-25 1
 
0.6%
광남2동-2 1
 
0.6%
광남2동-3 1
 
0.6%
광남2동-4 1
 
0.6%
광남2동-5 1
 
0.6%
광남2동-6 1
 
0.6%
광남2동-7 1
 
0.6%
광남2동-8 1
 
0.6%
광남2동-9 1
 
0.6%
Other values (156) 156
94.0%
2023-12-23T07:54:15.454257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 166
16.3%
동 101
9.9%
1 97
9.5%
2 96
9.4%
남 77
 
7.5%
광 73
 
7.2%
읍 58
 
5.7%
오 39
 
3.8%
포 39
 
3.8%
3 35
 
3.4%
Other values (28) 239
23.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 518
50.8%
Decimal Number 336
32.9%
Dash Punctuation 166
 
16.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 101
19.5%
남 77
14.9%
광 73
14.1%
읍 58
11.2%
오 39
 
7.5%
포 39
 
7.5%
지 12
 
2.3%
암 12
 
2.3%
곤 12
 
2.3%
안 12
 
2.3%
Other values (17) 83
16.0%
Decimal Number
ValueCountFrequency (%)
1 97
28.9%
2 96
28.6%
3 35
 
10.4%
4 28
 
8.3%
5 16
 
4.8%
7 14
 
4.2%
8 13
 
3.9%
6 13
 
3.9%
9 12
 
3.6%
0 12
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 518
50.8%
Common 502
49.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 101
19.5%
남 77
14.9%
광 73
14.1%
읍 58
11.2%
오 39
 
7.5%
포 39
 
7.5%
지 12
 
2.3%
암 12
 
2.3%
곤 12
 
2.3%
안 12
 
2.3%
Other values (17) 83
16.0%
Common
ValueCountFrequency (%)
- 166
33.1%
1 97
19.3%
2 96
19.1%
3 35
 
7.0%
4 28
 
5.6%
5 16
 
3.2%
7 14
 
2.8%
8 13
 
2.6%
6 13
 
2.6%
9 12
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 518
50.8%
ASCII 502
49.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 166
33.1%
1 97
19.3%
2 96
19.1%
3 35
 
7.0%
4 28
 
5.6%
5 16
 
3.2%
7 14
 
2.8%
8 13
 
2.6%
6 13
 
2.6%
9 12
 
2.4%
Hangul
ValueCountFrequency (%)
동 101
19.5%
남 77
14.9%
광 73
14.1%
읍 58
11.2%
오 39
 
7.5%
포 39
 
7.5%
지 12
 
2.3%
암 12
 
2.3%
곤 12
 
2.3%
안 12
 
2.3%
Other values (17) 83
16.0%

설치장소명
Text

Distinct140
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-23T07:54:16.677373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length9.5783133
Min length3

Characters and Unicode

Total characters1590
Distinct characters204
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)73.5%

Sample

1st row광명초삼거리
2nd row광명초삼거리
3rd row태재고개사거리
4th row태재고개사거리
5th row양촌사거리
ValueCountFrequency (%)
앞 61
 
16.5%
사거리 12
 
3.3%
건너편 11
 
3.0%
맞은편 10
 
2.7%
교통섬 7
 
1.9%
삼거리 5
 
1.4%
인근 5
 
1.4%
2단지 5
 
1.4%
태전힐스테이트 5
 
1.4%
힐스테이트 5
 
1.4%
Other values (157) 243
65.9%
2023-12-23T07:54:18.798178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
203
 
12.8%
앞 65
 
4.1%
리 58
 
3.6%
지 45
 
2.8%
교 41
 
2.6%
거 40
 
2.5%
트 33
 
2.1%
이 30
 
1.9%
태 29
 
1.8%
단 27
 
1.7%
Other values (194) 1019
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1258
79.1%
Space Separator 203
 
12.8%
Decimal Number 85
 
5.3%
Close Punctuation 14
 
0.9%
Open Punctuation 14
 
0.9%
Uppercase Letter 9
 
0.6%
Other Punctuation 4
 
0.3%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 65
 
5.2%
리 58
 
4.6%
지 45
 
3.6%
교 41
 
3.3%
거 40
 
3.2%
트 33
 
2.6%
이 30
 
2.4%
태 29
 
2.3%
단 27
 
2.1%
사 26
 
2.1%
Other values (172) 864
68.7%
Decimal Number
ValueCountFrequency (%)
2 19
22.4%
1 16
18.8%
3 14
16.5%
5 13
15.3%
8 6
 
7.1%
7 6
 
7.1%
9 4
 
4.7%
6 4
 
4.7%
4 3
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
A 2
22.2%
L 1
11.1%
G 1
11.1%
K 1
11.1%
B 1
11.1%
I 1
11.1%
U 1
11.1%
C 1
11.1%
Space Separator
ValueCountFrequency (%)
203
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1258
79.1%
Common 323
 
20.3%
Latin 9
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 65
 
5.2%
리 58
 
4.6%
지 45
 
3.6%
교 41
 
3.3%
거 40
 
3.2%
트 33
 
2.6%
이 30
 
2.4%
태 29
 
2.3%
단 27
 
2.1%
사 26
 
2.1%
Other values (172) 864
68.7%
Common
ValueCountFrequency (%)
203
62.8%
2 19
 
5.9%
1 16
 
5.0%
3 14
 
4.3%
) 14
 
4.3%
( 14
 
4.3%
5 13
 
4.0%
8 6
 
1.9%
7 6
 
1.9%
9 4
 
1.2%
Other values (4) 14
 
4.3%
Latin
ValueCountFrequency (%)
A 2
22.2%
L 1
11.1%
G 1
11.1%
K 1
11.1%
B 1
11.1%
I 1
11.1%
U 1
11.1%
C 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1258
79.1%
ASCII 332
 
20.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
203
61.1%
2 19
 
5.7%
1 16
 
4.8%
3 14
 
4.2%
) 14
 
4.2%
( 14
 
4.2%
5 13
 
3.9%
8 6
 
1.8%
7 6
 
1.8%
9 4
 
1.2%
Other values (12) 23
 
6.9%
Hangul
ValueCountFrequency (%)
앞 65
 
5.2%
리 58
 
4.6%
지 45
 
3.6%
교 41
 
3.3%
거 40
 
3.2%
트 33
 
2.6%
이 30
 
2.4%
태 29
 
2.3%
단 27
 
2.1%
사 26
 
2.1%
Other values (172) 864
68.7%

소재지도로명주소
Text

MISSING 

Distinct12
Distinct (%)92.3%
Missing153
Missing (%)92.2%
Memory size1.4 KiB
2023-12-23T07:54:19.519733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length17.076923
Min length14

Characters and Unicode

Total characters222
Distinct characters38
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

Unique11 ?
Unique (%)84.6%

Sample

1st row경기도 광주시 마루들길 205
2nd row경기도 광주시 양벌로 193
3rd row경기도 광주시 청석로 85
4th row경기도 광주시 마루들길 217
5th row경기도 광주시 청석로 85
ValueCountFrequency (%)
경기도 13
23.6%
광주시 13
23.6%
경충대로 3
 
5.5%
광주대로 2
 
3.6%
곤지암읍 2
 
3.6%
청석로 2
 
3.6%
마루들길 2
 
3.6%
85 2
 
3.6%
205 1
 
1.8%
순암로 1
 
1.8%
Other values (14) 14
25.5%
2023-12-23T07:54:20.701993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
18.9%
경 16
 
7.2%
광 15
 
6.8%
주 15
 
6.8%
기 13
 
5.9%
도 13
 
5.9%
시 13
 
5.9%
로 11
 
5.0%
3 8
 
3.6%
1 7
 
3.2%
Other values (28) 69
31.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 139
62.6%
Space Separator 42
 
18.9%
Decimal Number 40
 
18.0%
Dash Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 16
11.5%
광 15
10.8%
주 15
10.8%
기 13
9.4%
도 13
9.4%
시 13
9.4%
로 11
 
7.9%
암 5
 
3.6%
대 5
 
3.6%
지 3
 
2.2%
Other values (16) 30
21.6%
Decimal Number
ValueCountFrequency (%)
3 8
20.0%
1 7
17.5%
5 5
12.5%
7 4
10.0%
6 3
 
7.5%
4 3
 
7.5%
0 3
 
7.5%
2 3
 
7.5%
8 3
 
7.5%
9 1
 
2.5%
Space Separator
ValueCountFrequency (%)
42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 139
62.6%
Common 83
37.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 16
11.5%
광 15
10.8%
주 15
10.8%
기 13
9.4%
도 13
9.4%
시 13
9.4%
로 11
 
7.9%
암 5
 
3.6%
대 5
 
3.6%
지 3
 
2.2%
Other values (16) 30
21.6%
Common
ValueCountFrequency (%)
42
50.6%
3 8
 
9.6%
1 7
 
8.4%
5 5
 
6.0%
7 4
 
4.8%
6 3
 
3.6%
4 3
 
3.6%
0 3
 
3.6%
2 3
 
3.6%
8 3
 
3.6%
Other values (2) 2
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 139
62.6%
ASCII 83
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42
50.6%
3 8
 
9.6%
1 7
 
8.4%
5 5
 
6.0%
7 4
 
4.8%
6 3
 
3.6%
4 3
 
3.6%
0 3
 
3.6%
2 3
 
3.6%
8 3
 
3.6%
Other values (2) 2
 
2.4%
Hangul
ValueCountFrequency (%)
경 16
11.5%
광 15
10.8%
주 15
10.8%
기 13
9.4%
도 13
9.4%
시 13
9.4%
로 11
 
7.9%
암 5
 
3.6%
대 5
 
3.6%
지 3
 
2.2%
Other values (16) 30
21.6%

소재지지번주소
Text

Distinct127
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-23T07:54:21.773179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length17.86747
Min length14

Characters and Unicode

Total characters2966
Distinct characters66
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)62.7%

Sample

1st row경기도 광주시 능평동 441-2
2nd row경기도 광주시 능평동 441-2
3rd row경기도 광주시 신현동 709-18
4th row경기도 광주시 신현동 709-22
5th row경기도 광주시 양벌동 1055-5
ValueCountFrequency (%)
경기도 166
23.8%
광주시 166
23.8%
태전동 61
 
8.8%
양벌동 21
 
3.0%
초월읍 12
 
1.7%
곤지암읍 12
 
1.7%
장지동 9
 
1.3%
곤지암리 8
 
1.1%
경안동 7
 
1.0%
탄벌동 6
 
0.9%
Other values (151) 229
32.9%
2023-12-23T07:54:23.636942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
531
17.9%
경 173
 
5.8%
광 169
 
5.7%
도 167
 
5.6%
주 166
 
5.6%
시 166
 
5.6%
기 166
 
5.6%
동 141
 
4.8%
- 134
 
4.5%
2 121
 
4.1%
Other values (56) 1032
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1617
54.5%
Decimal Number 678
22.9%
Space Separator 531
 
17.9%
Dash Punctuation 134
 
4.5%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 173
10.7%
광 169
10.5%
도 167
10.3%
주 166
10.3%
시 166
10.3%
기 166
10.3%
동 141
8.7%
전 61
 
3.8%
태 61
 
3.8%
지 32
 
2.0%
Other values (42) 315
19.5%
Decimal Number
ValueCountFrequency (%)
2 121
17.8%
1 120
17.7%
7 81
11.9%
3 74
10.9%
0 64
9.4%
4 53
7.8%
5 51
7.5%
6 45
 
6.6%
9 42
 
6.2%
8 27
 
4.0%
Space Separator
ValueCountFrequency (%)
531
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 134
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1617
54.5%
Common 1349
45.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 173
10.7%
광 169
10.5%
도 167
10.3%
주 166
10.3%
시 166
10.3%
기 166
10.3%
동 141
8.7%
전 61
 
3.8%
태 61
 
3.8%
지 32
 
2.0%
Other values (42) 315
19.5%
Common
ValueCountFrequency (%)
531
39.4%
- 134
 
9.9%
2 121
 
9.0%
1 120
 
8.9%
7 81
 
6.0%
3 74
 
5.5%
0 64
 
4.7%
4 53
 
3.9%
5 51
 
3.8%
6 45
 
3.3%
Other values (4) 75
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1617
54.5%
ASCII 1349
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
531
39.4%
- 134
 
9.9%
2 121
 
9.0%
1 120
 
8.9%
7 81
 
6.0%
3 74
 
5.5%
0 64
 
4.7%
4 53
 
3.9%
5 51
 
3.8%
6 45
 
3.3%
Other values (4) 75
 
5.6%
Hangul
ValueCountFrequency (%)
경 173
10.7%
광 169
10.5%
도 167
10.3%
주 166
10.3%
시 166
10.3%
기 166
10.3%
동 141
8.7%
전 61
 
3.8%
태 61
 
3.8%
지 32
 
2.0%
Other values (42) 315
19.5%

설치일자
Categorical

HIGH CORRELATION 

Distinct33
Distinct (%)19.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-05-31
15 
2021-06-08
15 
2022-05-31
15 
2020-04-17
12 
2020-07-30
 
9
Other values (28)
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique4 ?
Unique (%)2.4%

Sample

1st row2021-09-09
2nd row2021-09-09
3rd row2021-09-09
4th row2021-09-09
5th row2021-09-09

Common Values

ValueCountFrequency (%)
2023-05-31 15
 
9.0%
2021-06-08 15
 
9.0%
2022-05-31 15
 
9.0%
2020-04-17 12
 
7.2%
2020-07-30 9
 
5.4%
2020-07-31 9
 
5.4%
2021-04-29 8
 
4.8%
2021-08-17 7
 
4.2%
2021-05-18 7
 
4.2%
2021-09-09 6
 
3.6%
Other values (23) 63
38.0%

Length

2023-12-23T07:54:24.277368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-05-31 15
 
9.0%
2021-06-08 15
 
9.0%
2022-05-31 15
 
9.0%
2020-04-17 12
 
7.2%
2020-07-30 9
 
5.4%
2020-07-31 9
 
5.4%
2021-04-29 8
 
4.8%
2021-08-17 7
 
4.2%
2021-05-18 7
 
4.2%
2021-09-09 6
 
3.6%
Other values (23) 63
38.0%

높이
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
3.0
50 
5.0
46 
3.5
42 
4.0
26 
3.2
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5.0
2nd row5.0
3rd row5.0
4th row5.0
5th row5.0

Common Values

ValueCountFrequency (%)
3.0 50
30.1%
5.0 46
27.7%
3.5 42
25.3%
4.0 26
15.7%
3.2 2
 
1.2%

Length

2023-12-23T07:54:24.632860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T07:54:25.040506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3.0 50
30.1%
5.0 46
27.7%
3.5 42
25.3%
4.0 26
15.7%
3.2 2
 
1.2%

펼침지름
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
3.0
60 
5.0
48 
4.0
48 
3.5
10 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5.0
2nd row5.0
3rd row5.0
4th row5.0
5th row5.0

Common Values

ValueCountFrequency (%)
3.0 60
36.1%
5.0 48
28.9%
4.0 48
28.9%
3.5 10
 
6.0%

Length

2023-12-23T07:54:25.699806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T07:54:26.353407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3.0 60
36.1%
5.0 48
28.9%
4.0 48
28.9%
3.5 10
 
6.0%

원단
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
PE매쉬
166 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
PE매쉬 166
100.0%

Length

2023-12-23T07:54:27.017782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T07:54:27.911877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
pe매쉬 166
100.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct126
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.387052
Minimum37.315126
Maximum37.470394
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-23T07:54:29.434232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.315126
5-th percentile37.351186
Q137.377817
median37.38475
Q337.394837
95-th percentile37.425102
Maximum37.470394
Range0.15526762
Interquartile range (IQR)0.017019583

Descriptive statistics

Standard deviation0.023293691
Coefficient of variation (CV)0.00062304165
Kurtosis2.2023193
Mean37.387052
Median Absolute Deviation (MAD)0.0099138
Skewness0.76639073
Sum6206.2506
Variance0.00054259602
MonotonicityNot monotonic
2023-12-23T07:54:30.830666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.38314838 5
 
3.0%
37.38123205 5
 
3.0%
37.38001615 5
 
3.0%
37.37979035 4
 
2.4%
37.39483684 4
 
2.4%
37.38476356 4
 
2.4%
37.3789793 4
 
2.4%
37.37483584 3
 
1.8%
37.38269201 3
 
1.8%
37.41093079 2
 
1.2%
Other values (116) 127
76.5%
ValueCountFrequency (%)
37.31512639 1
0.6%
37.34737503 1
0.6%
37.34850572 1
0.6%
37.34934517 1
0.6%
37.34964726 1
0.6%
37.35028461 1
0.6%
37.35044515 1
0.6%
37.35054868 1
0.6%
37.35092203 1
0.6%
37.35197818 1
0.6%
ValueCountFrequency (%)
37.47039401 2
1.2%
37.46328371 1
0.6%
37.44850444 1
0.6%
37.44568211 2
1.2%
37.43261895 1
0.6%
37.42626589 1
0.6%
37.4253231 1
0.6%
37.4244373 1
0.6%
37.41937067 1
0.6%
37.41914359 1
0.6%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct126
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.24823
Minimum127.15026
Maximum127.35224
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-23T07:54:32.522416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.15026
5-th percentile127.17189
Q1127.22972
median127.23659
Q3127.25865
95-th percentile127.33909
Maximum127.35224
Range0.2019732
Interquartile range (IQR)0.028934025

Descriptive statistics

Standard deviation0.039755191
Coefficient of variation (CV)0.00031242234
Kurtosis1.2467136
Mean127.24823
Median Absolute Deviation (MAD)0.0115731
Skewness0.55352425
Sum21123.207
Variance0.0015804752
MonotonicityNot monotonic
2023-12-23T07:54:33.654912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.2331262 5
 
3.0%
127.2335861 5
 
3.0%
127.228122 5
 
3.0%
127.2308117 4
 
2.4%
127.2445611 4
 
2.4%
127.2334712 4
 
2.4%
127.2562034 4
 
2.4%
127.2282653 3
 
1.8%
127.2294496 3
 
1.8%
127.248907 2
 
1.2%
Other values (116) 127
76.5%
ValueCountFrequency (%)
127.1502629 1
0.6%
127.150895 1
0.6%
127.160406 1
0.6%
127.1606092 1
0.6%
127.1610772 1
0.6%
127.1636798 1
0.6%
127.1654291 1
0.6%
127.1661253 1
0.6%
127.1681161 1
0.6%
127.1832069 1
0.6%
ValueCountFrequency (%)
127.3522361 1
0.6%
127.3485171 1
0.6%
127.3477492 1
0.6%
127.3466304 1
0.6%
127.3461725 1
0.6%
127.3455845 1
0.6%
127.3452574 1
0.6%
127.3404959 1
0.6%
127.3396531 1
0.6%
127.3374119 1
0.6%

당해년도운영시작일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-05-31
166 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-31
2nd row2023-05-31
3rd row2023-05-31
4th row2023-05-31
5th row2023-05-31

Common Values

ValueCountFrequency (%)
2023-05-31 166
100.0%

Length

2023-12-23T07:54:34.430363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T07:54:34.810426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-31 166
100.0%

당해년도운영종료일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-10-31
166 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2023-10-31 166
100.0%

Length

2023-12-23T07:54:35.399976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T07:54:35.873774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-31 166
100.0%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
경기도 광주시청
166 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 광주시청
2nd row경기도 광주시청
3rd row경기도 광주시청
4th row경기도 광주시청
5th row경기도 광주시청

Common Values

ValueCountFrequency (%)
경기도 광주시청 166
100.0%

Length

2023-12-23T07:54:36.397022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T07:54:36.821449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 166
50.0%
광주시청 166
50.0%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
031-760-4499
166 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row031-760-4499
2nd row031-760-4499
3rd row031-760-4499
4th row031-760-4499
5th row031-760-4499

Common Values

ValueCountFrequency (%)
031-760-4499 166
100.0%

Length

2023-12-23T07:54:37.460435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T07:54:38.090035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
031-760-4499 166
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-08
166 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-12-08
2nd row2023-12-08
3rd row2023-12-08
4th row2023-12-08
5th row2023-12-08

Common Values

ValueCountFrequency (%)
2023-12-08 166
100.0%

Length

2023-12-23T07:54:38.464840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T07:54:38.979837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-12-08 166
100.0%

Interactions

2023-12-23T07:54:06.727830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:54:05.877394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:54:07.408501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:54:06.355564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-23T07:54:39.383542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동명소재지도로명주소설치일자높이펼침지름위도경도
읍면동명1.0001.0000.9730.8500.6660.9230.821
소재지도로명주소1.0001.0000.9011.0001.0001.0001.000
설치일자0.9730.9011.0000.9850.9570.9080.879
높이0.8501.0000.9851.0000.7350.7020.647
펼침지름0.6661.0000.9570.7351.0000.4160.301
위도0.9231.0000.9080.7020.4161.0000.680
경도0.8211.0000.8790.6470.3010.6801.000
2023-12-23T07:54:39.969018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치일자펼침지름높이읍면동명
설치일자1.0000.7580.8450.742
펼침지름0.7581.0000.6750.444
높이0.8450.6751.0000.658
읍면동명0.7420.4440.6581.000
2023-12-23T07:54:40.666664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도읍면동명설치일자높이펼침지름
위도1.0000.0590.7300.5780.4960.274
경도0.0591.0000.5190.5130.3180.180
읍면동명0.7300.5191.0000.7420.6580.444
설치일자0.5780.5130.7421.0000.8450.758
높이0.4960.3180.6580.8451.0000.675
펼침지름0.2740.1800.4440.7580.6751.000

Missing values

2023-12-23T07:54:08.343522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-23T07:54:09.409631image/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

시군명읍면동명관리번호설치장소명소재지도로명주소소재지지번주소설치일자높이펼침지름원단위도경도당해년도운영시작일자당해년도운영종료일자관리기관명관리기관전화번호데이터기준일자
0광주시오포읍오포읍-1광명초삼거리<NA>경기도 광주시 능평동 441-22021-09-095.05.0PE매쉬37.358223127.1610772023-05-312023-10-31경기도 광주시청031-760-44992023-12-08
1광주시오포읍오포읍-2광명초삼거리<NA>경기도 광주시 능평동 441-22021-09-095.05.0PE매쉬37.358688127.1606092023-05-312023-10-31경기도 광주시청031-760-44992023-12-08
2광주시오포읍오포읍-3태재고개사거리<NA>경기도 광주시 신현동 709-182021-09-095.05.0PE매쉬37.360236127.1502632023-05-312023-10-31경기도 광주시청031-760-44992023-12-08
3광주시오포읍오포읍-4태재고개사거리<NA>경기도 광주시 신현동 709-222021-09-095.05.0PE매쉬37.360241127.1508952023-05-312023-10-31경기도 광주시청031-760-44992023-12-08
4광주시오포읍오포읍-5양촌사거리<NA>경기도 광주시 양벌동 1055-52021-09-095.05.0PE매쉬37.370784127.2468682023-05-312023-10-31경기도 광주시청031-760-44992023-12-08
5광주시오포읍오포읍-6양벌삼거리<NA>경기도 광주시 양벌동 66-132021-09-095.05.0PE매쉬37.389163127.2549622023-05-312023-10-31경기도 광주시청031-760-44992023-12-08
6광주시오포읍오포읍-7광명초삼거리교차로<NA>경기도 광주시 신현동 367-222019-07-025.05.0PE매쉬37.358696127.1604062023-05-312023-10-31경기도 광주시청031-760-44992023-12-08
7광주시오포읍오포읍-8오포서부파출소 인근<NA>경기도 광주시 능평동 95-42019-07-225.05.0PE매쉬37.347375127.1832072023-05-312023-10-31경기도 광주시청031-760-44992023-12-08
8광주시오포읍오포읍-9롯데슈퍼사거리경기도 광주시 마루들길 205경기도 광주시 양벌동 308-172019-07-225.05.0PE매쉬37.378619127.2547282023-05-312023-10-31경기도 광주시청031-760-44992023-12-08
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