Overview

Dataset statistics

Number of variables4
Number of observations30
Missing cells5
Missing cells (%)4.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory36.4 B

Variable types

Text3
Categorical1

Dataset

Description제주도내 박물관, 갤러리 등 여성선호공간 정보 제공
Author제주특별자치도
URLhttps://www.data.go.kr/data/15056103/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연락처 has 5 (16.7%) missing valuesMissing
명칭 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:57:09.872823
Analysis finished2023-12-12 08:57:10.252467
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

명칭
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-12T17:57:10.409484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6
Min length2

Characters and Unicode

Total characters180
Distinct characters90
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row이레
2nd row제주공연장
3rd row조안베어뮤지엄
4th row다비치리
5th row현인갤러리
ValueCountFrequency (%)
이레 1
 
3.3%
제주공연장 1
 
3.3%
프리머스 1
 
3.3%
제주박물관 1
 
3.3%
제주국제컨벤션센터 1
 
3.3%
기당미술관 1
 
3.3%
야구명예의전당 1
 
3.3%
제주항일기념관 1
 
3.3%
민속박물관 1
 
3.3%
문화진흥원 1
 
3.3%
Other values (20) 20
66.7%
2023-12-12T17:57:10.866349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 14
 
7.8%
물 9
 
5.0%
박 9
 
5.0%
제 8
 
4.4%
주 7
 
3.9%
화 6
 
3.3%
아 5
 
2.8%
문 5
 
2.8%
리 4
 
2.2%
미 3
 
1.7%
Other values (80) 110
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 180
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 14
 
7.8%
물 9
 
5.0%
박 9
 
5.0%
제 8
 
4.4%
주 7
 
3.9%
화 6
 
3.3%
아 5
 
2.8%
문 5
 
2.8%
리 4
 
2.2%
미 3
 
1.7%
Other values (80) 110
61.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 180
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 14
 
7.8%
물 9
 
5.0%
박 9
 
5.0%
제 8
 
4.4%
주 7
 
3.9%
화 6
 
3.3%
아 5
 
2.8%
문 5
 
2.8%
리 4
 
2.2%
미 3
 
1.7%
Other values (80) 110
61.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 180
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 14
 
7.8%
물 9
 
5.0%
박 9
 
5.0%
제 8
 
4.4%
주 7
 
3.9%
화 6
 
3.3%
아 5
 
2.8%
문 5
 
2.8%
리 4
 
2.2%
미 3
 
1.7%
Other values (80) 110
61.1%

연락처
Text

MISSING 

Distinct24
Distinct (%)96.0%
Missing5
Missing (%)16.7%
Memory size372.0 B
2023-12-12T17:57:11.114039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters300
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row064-787-2249
2nd row064-794-4444
3rd row064-739-1024
4th row064-733-7226
5th row064-747-1500
ValueCountFrequency (%)
064-754-5211 2
 
8.0%
064-794-4444 1
 
4.0%
064-735-1000 1
 
4.0%
064-733-1586 1
 
4.0%
064-735-3634 1
 
4.0%
064-710-7793 1
 
4.0%
064-755-1976 1
 
4.0%
064-738-6565 1
 
4.0%
064-764-7777 1
 
4.0%
064-784-7856 1
 
4.0%
Other values (14) 14
56.0%
2023-12-12T17:57:11.483265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 50
16.7%
7 45
15.0%
0 43
14.3%
4 41
13.7%
6 36
12.0%
5 19
 
6.3%
8 17
 
5.7%
2 16
 
5.3%
3 14
 
4.7%
1 12
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 250
83.3%
Dash Punctuation 50
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 45
18.0%
0 43
17.2%
4 41
16.4%
6 36
14.4%
5 19
7.6%
8 17
 
6.8%
2 16
 
6.4%
3 14
 
5.6%
1 12
 
4.8%
9 7
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 50
16.7%
7 45
15.0%
0 43
14.3%
4 41
13.7%
6 36
12.0%
5 19
 
6.3%
8 17
 
5.7%
2 16
 
5.3%
3 14
 
4.7%
1 12
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 50
16.7%
7 45
15.0%
0 43
14.3%
4 41
13.7%
6 36
12.0%
5 19
 
6.3%
8 17
 
5.7%
2 16
 
5.3%
3 14
 
4.7%
1 12
 
4.0%

주소
Text

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-12T17:57:11.759681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length22.466667
Min length18

Characters and Unicode

Total characters674
Distinct characters77
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

Unique28 ?
Unique (%)93.3%

Sample

1st row제주특별자치도 서귀포시 표선면 번영로 2564-21
2nd row제주특별자치도 서귀포시 안덕면 동광로 214
3rd row제주특별자치도 서귀포시 대포로 113
4th row제주특별자치도 서귀포시 인정오름로 135-18
5th row제주특별자치도 제주시 도령로 26
ValueCountFrequency (%)
제주특별자치도 30
23.3%
서귀포시 15
 
11.6%
제주시 15
 
11.6%
동광로 3
 
2.3%
26 2
 
1.6%
안덕면 2
 
1.6%
번영로 2
 
1.6%
표선면 2
 
1.6%
1 2
 
1.6%
일주동로 2
 
1.6%
Other values (52) 54
41.9%
2023-12-12T17:57:12.536827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
17.8%
주 48
 
7.1%
제 45
 
6.7%
도 34
 
5.0%
시 31
 
4.6%
특 30
 
4.5%
별 30
 
4.5%
자 30
 
4.5%
치 30
 
4.5%
로 29
 
4.3%
Other values (67) 247
36.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 456
67.7%
Space Separator 120
 
17.8%
Decimal Number 93
 
13.8%
Dash Punctuation 5
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 48
 
10.5%
제 45
 
9.9%
도 34
 
7.5%
시 31
 
6.8%
특 30
 
6.6%
별 30
 
6.6%
자 30
 
6.6%
치 30
 
6.6%
로 29
 
6.4%
서 17
 
3.7%
Other values (55) 132
28.9%
Decimal Number
ValueCountFrequency (%)
1 25
26.9%
2 15
16.1%
9 9
 
9.7%
3 9
 
9.7%
6 9
 
9.7%
4 8
 
8.6%
8 6
 
6.5%
7 5
 
5.4%
5 5
 
5.4%
0 2
 
2.2%
Space Separator
ValueCountFrequency (%)
120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 456
67.7%
Common 218
32.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 48
 
10.5%
제 45
 
9.9%
도 34
 
7.5%
시 31
 
6.8%
특 30
 
6.6%
별 30
 
6.6%
자 30
 
6.6%
치 30
 
6.6%
로 29
 
6.4%
서 17
 
3.7%
Other values (55) 132
28.9%
Common
ValueCountFrequency (%)
120
55.0%
1 25
 
11.5%
2 15
 
6.9%
9 9
 
4.1%
3 9
 
4.1%
6 9
 
4.1%
4 8
 
3.7%
8 6
 
2.8%
7 5
 
2.3%
5 5
 
2.3%
Other values (2) 7
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 456
67.7%
ASCII 218
32.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
120
55.0%
1 25
 
11.5%
2 15
 
6.9%
9 9
 
4.1%
3 9
 
4.1%
6 9
 
4.1%
4 8
 
3.7%
8 6
 
2.8%
7 5
 
2.3%
5 5
 
2.3%
Other values (2) 7
 
3.2%
Hangul
ValueCountFrequency (%)
주 48
 
10.5%
제 45
 
9.9%
도 34
 
7.5%
시 31
 
6.8%
특 30
 
6.6%
별 30
 
6.6%
자 30
 
6.6%
치 30
 
6.6%
로 29
 
6.4%
서 17
 
3.7%
Other values (55) 132
28.9%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2015-01-01
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015-01-01
2nd row2015-01-01
3rd row2015-01-01
4th row2015-01-01
5th row2015-01-01

Common Values

ValueCountFrequency (%)
2015-01-01 30
100.0%

Length

2023-12-12T17:57:12.681438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:57:12.811955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015-01-01 30
100.0%

Correlations

2023-12-12T17:57:12.897869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
명칭연락처주소
명칭1.0001.0001.000
연락처1.0001.0001.000
주소1.0001.0001.000

Missing values

2023-12-12T17:57:10.100831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:57:10.218018image/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

명칭연락처주소데이터기준일자
0이레064-787-2249제주특별자치도 서귀포시 표선면 번영로 2564-212015-01-01
1제주공연장064-794-4444제주특별자치도 서귀포시 안덕면 동광로 2142015-01-01
2조안베어뮤지엄064-739-1024제주특별자치도 서귀포시 대포로 1132015-01-01
3다비치리064-733-7226제주특별자치도 서귀포시 인정오름로 135-182015-01-01
4현인갤러리064-747-1500제주특별자치도 제주시 도령로 262015-01-01
5대왕미술관064-757-8589제주특별자치도 제주시 공설로7길 12015-01-01
6솔거화랑064-752-2587제주특별자치도 제주시 중앙로19길 262015-01-01
7트릭아트뮤지엄064-787-8774제주특별자치도 서귀포시 표선면 번영로 26442015-01-01
8우도등대박물관064-720-2672제주특별자치도 제주시 임항로 1282015-01-01
9제주요도자기문화박물관064-748-0121제주특별자치도 제주시 애월읍 평화로 28472015-01-01
명칭연락처주소데이터기준일자
20아프리카박물관064-738-6565제주특별자치도 서귀포시 이어도로 492015-01-01
21문화진흥원064-754-5211제주특별자치도 제주시 동광로 692015-01-01
22민속박물관064-755-1976제주특별자치도 제주시 일주동로 293-12015-01-01
23제주항일기념관064-710-7793제주특별자치도 제주시 조천읍 신북로 3032015-01-01
24야구명예의전당064-735-3634제주특별자치도 서귀포시 중산간서로 972015-01-01
25기당미술관064-733-1586제주특별자치도 서귀포시 남성중로153번길 152015-01-01
26제주국제컨벤션센터064-735-1000제주특별자치도 서귀포시 중문관광로 2242015-01-01
27제주박물관064-720-8000제주특별자치도 제주시 일주동로 172015-01-01
28프리머스<NA>제주특별자치도 제주시 연북로 12015-01-01
29제주학생문화원<NA>제주특별자치도 제주시 연삼로 4892015-01-01