Overview

Dataset statistics

Number of variables4
Number of observations153
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.9 KiB
Average record size in memory32.9 B

Variable types

Categorical2
Text2

Dataset

Description경상남도 남해군 관내의 종료시설 현황입니다. 종교구분, 시설명, 주소, 전화번호 등의 정보를 포함하고 있습니다.
Author경상남도 남해군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15117952

Alerts

종교구분 is highly imbalanced (52.1%)Imbalance
전화번호 is highly imbalanced (57.4%)Imbalance
시설명 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:38:39.614757
Analysis finished2023-12-11 00:38:39.977889
Duration0.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

종교구분
Categorical

IMBALANCE 

Distinct7
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
개신교
99 
불교
42 
천도교
 
7
천주교
 
2
원불교
 
1
Other values (2)
 
2

Length

Max length3
Median length3
Mean length2.7254902
Min length2

Unique

Unique3 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
개신교 99
64.7%
불교 42
27.5%
천도교 7
 
4.6%
천주교 2
 
1.3%
원불교 1
 
0.7%
천추교 1
 
0.7%
통일교 1
 
0.7%

Length

2023-12-11T09:38:40.061770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:38:40.252332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개신교 99
64.7%
불교 42
27.5%
천도교 7
 
4.6%
천주교 2
 
1.3%
원불교 1
 
0.7%
천추교 1
 
0.7%
통일교 1
 
0.7%

시설명
Text

UNIQUE 

Distinct153
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T09:38:40.876988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length4.8562092
Min length3

Characters and Unicode

Total characters743
Distinct characters177
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique153 ?
Unique (%)100.0%

Sample

1st row소망교회
2nd row동행교회
3rd row남해읍장로교회
4th row임마누엘남해교회
5th row기쁜소식남해교회
ValueCountFrequency (%)
천도교 5
 
3.0%
남해교회 2
 
1.2%
남해성당 2
 
1.2%
소망교회 1
 
0.6%
미조공소 1
 
0.6%
학림사 1
 
0.6%
갈릴기도원 1
 
0.6%
원불교 1
 
0.6%
남해교당 1
 
0.6%
은점공소 1
 
0.6%
Other values (149) 149
90.3%
2023-12-11T09:38:41.336611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 112
 
15.1%
회 99
 
13.3%
남 29
 
3.9%
해 26
 
3.5%
사 24
 
3.2%
암 16
 
2.2%
천 13
 
1.7%
12
 
1.6%
도 11
 
1.5%
선 9
 
1.2%
Other values (167) 392
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 722
97.2%
Space Separator 12
 
1.6%
Close Punctuation 3
 
0.4%
Open Punctuation 3
 
0.4%
Uppercase Letter 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 112
 
15.5%
회 99
 
13.7%
남 29
 
4.0%
해 26
 
3.6%
사 24
 
3.3%
암 16
 
2.2%
천 13
 
1.8%
도 11
 
1.5%
선 9
 
1.2%
로 8
 
1.1%
Other values (161) 375
51.9%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
I 1
33.3%
G 1
33.3%
Space Separator
ValueCountFrequency (%)
12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 722
97.2%
Common 18
 
2.4%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 112
 
15.5%
회 99
 
13.7%
남 29
 
4.0%
해 26
 
3.6%
사 24
 
3.3%
암 16
 
2.2%
천 13
 
1.8%
도 11
 
1.5%
선 9
 
1.2%
로 8
 
1.1%
Other values (161) 375
51.9%
Common
ValueCountFrequency (%)
12
66.7%
) 3
 
16.7%
( 3
 
16.7%
Latin
ValueCountFrequency (%)
S 1
33.3%
I 1
33.3%
G 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 722
97.2%
ASCII 21
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 112
 
15.5%
회 99
 
13.7%
남 29
 
4.0%
해 26
 
3.6%
사 24
 
3.3%
암 16
 
2.2%
천 13
 
1.8%
도 11
 
1.5%
선 9
 
1.2%
로 8
 
1.1%
Other values (161) 375
51.9%
ASCII
ValueCountFrequency (%)
12
57.1%
) 3
 
14.3%
( 3
 
14.3%
S 1
 
4.8%
I 1
 
4.8%
G 1
 
4.8%

주소
Text

UNIQUE 

Distinct153
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T09:38:41.654059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length13.653595
Min length7

Characters and Unicode

Total characters2089
Distinct characters106
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

Unique153 ?
Unique (%)100.0%

Sample

1st row남해읍 스포츠로287
2nd row남해읍 선소로76번길39-21
3rd row남해읍 망운로35
4th row남해읍 망운로21번길59
5th row남해읍 망운로61번길30-7
ValueCountFrequency (%)
남해읍 24
 
5.8%
삼동면 15
 
3.6%
남면 13
 
3.1%
고현면 12
 
2.9%
이동면 10
 
2.4%
창선면 10
 
2.4%
서면 8
 
1.9%
미조면 8
 
1.9%
동부대로 8
 
1.9%
설천면 8
 
1.9%
Other values (249) 297
71.9%
2023-12-11T09:38:42.177717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
265
 
12.7%
1 145
 
6.9%
로 127
 
6.1%
2 95
 
4.5%
면 93
 
4.5%
3 89
 
4.3%
- 87
 
4.2%
길 84
 
4.0%
번 77
 
3.7%
남 69
 
3.3%
Other values (96) 958
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1005
48.1%
Decimal Number 728
34.8%
Space Separator 265
 
12.7%
Dash Punctuation 87
 
4.2%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 127
 
12.6%
면 93
 
9.3%
길 84
 
8.4%
번 77
 
7.7%
남 69
 
6.9%
동 44
 
4.4%
대 43
 
4.3%
해 41
 
4.1%
선 24
 
2.4%
서 24
 
2.4%
Other values (82) 379
37.7%
Decimal Number
ValueCountFrequency (%)
1 145
19.9%
2 95
13.0%
3 89
12.2%
5 64
8.8%
6 63
8.7%
4 59
8.1%
8 57
 
7.8%
7 56
 
7.7%
9 53
 
7.3%
0 47
 
6.5%
Space Separator
ValueCountFrequency (%)
265
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1084
51.9%
Hangul 1005
48.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 127
 
12.6%
면 93
 
9.3%
길 84
 
8.4%
번 77
 
7.7%
남 69
 
6.9%
동 44
 
4.4%
대 43
 
4.3%
해 41
 
4.1%
선 24
 
2.4%
서 24
 
2.4%
Other values (82) 379
37.7%
Common
ValueCountFrequency (%)
265
24.4%
1 145
13.4%
2 95
 
8.8%
3 89
 
8.2%
- 87
 
8.0%
5 64
 
5.9%
6 63
 
5.8%
4 59
 
5.4%
8 57
 
5.3%
7 56
 
5.2%
Other values (4) 104
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1084
51.9%
Hangul 1005
48.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
265
24.4%
1 145
13.4%
2 95
 
8.8%
3 89
 
8.2%
- 87
 
8.0%
5 64
 
5.9%
6 63
 
5.8%
4 59
 
5.4%
8 57
 
5.3%
7 56
 
5.2%
Other values (4) 104
 
9.6%
Hangul
ValueCountFrequency (%)
로 127
 
12.6%
면 93
 
9.3%
길 84
 
8.4%
번 77
 
7.7%
남 69
 
6.9%
동 44
 
4.4%
대 43
 
4.3%
해 41
 
4.1%
선 24
 
2.4%
서 24
 
2.4%
Other values (82) 379
37.7%

전화번호
Categorical

IMBALANCE 

Distinct39
Distinct (%)25.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
111 
<NA>
 
5
055-867-2259
 
1
055-867-3638
 
1
055-864-3243
 
1
Other values (34)
34 

Length

Max length12
Median length1
Mean length3.7581699
Min length1

Unique

Unique37 ?
Unique (%)24.2%

Sample

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

Common Values

ValueCountFrequency (%)
111
72.5%
<NA> 5
 
3.3%
055-867-2259 1
 
0.7%
055-867-3638 1
 
0.7%
055-864-3243 1
 
0.7%
055-867-5857 1
 
0.7%
055-863-3095 1
 
0.7%
055-864-2468 1
 
0.7%
055-864-4298 1
 
0.7%
055-862-0347 1
 
0.7%
Other values (29) 29
 
19.0%

Length

2023-12-11T09:38:42.394765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5
 
11.9%
055-863-1996 1
 
2.4%
055-867-7012 1
 
2.4%
055-864-1901 1
 
2.4%
055-863-0917 1
 
2.4%
055-863-5927 1
 
2.4%
055-863-5011 1
 
2.4%
055-862-1327 1
 
2.4%
055-862-7051 1
 
2.4%
055-863-4143 1
 
2.4%
Other values (28) 28
66.7%

Correlations

2023-12-11T09:38:42.492885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종교구분전화번호
종교구분1.0000.000
전화번호0.0001.000
2023-12-11T09:38:42.580233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전화번호종교구분
전화번호1.0000.000
종교구분0.0001.000
2023-12-11T09:38:42.673839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종교구분전화번호
종교구분1.0000.000
전화번호0.0001.000

Missing values

2023-12-11T09:38:39.857303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:38:39.945408image/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

종교구분시설명주소전화번호
0개신교소망교회남해읍 스포츠로287
1개신교동행교회남해읍 선소로76번길39-21
2개신교남해읍장로교회남해읍 망운로35
3개신교임마누엘남해교회남해읍 망운로21번길59
4개신교기쁜소식남해교회남해읍 망운로61번길30-7
5개신교남해제일교회남해읍 망운로65
6개신교남해성결교회남해읍 망운로21번길68-7
7개신교하나님의교회남해읍 화전로43번길11(기아자동차2층)
8개신교남해선교원남해읍 일등내과 4층
9개신교북림교회남해읍 화전로96번가길 4-8
종교구분시설명주소전화번호
143불교문수선원강진로 130-17055-864-1901
144불교반야용선사노량로 183번길 4055-862-9841
145불교운대암창선로153번길 240055-867-3725
146불교성명사율도로 180-1055-867-1556
147불교유심사(문수사)창선로153번길 39-56055-867-3666
148불교극락선원흥선로790번길 27055-867-6249
149불교세심사흥선로 767-28055-867-4937
150불교보현사흥선로 1598-119055-867-7012
151불교수미정사옥천로 296-20055-867-0574
152불교금강암흥선로199번길 9-6055-867-3577