Overview

Dataset statistics

Number of variables6
Number of observations313
Missing cells25
Missing cells (%)1.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.8 KiB
Average record size in memory48.4 B

Variable types

Categorical2
Text4

Dataset

Description- 제주특별자치도 내에 지정된 문화재의 지정번호, 위치, 지정일 등의 정보를 제공합니다. - 데이터 제공처: 공공데이터포털
Author제주데이터허브
URLhttps://www.jejudatahub.net/data/view/data/762

Alerts

데이터갱신일자 has constant value ""Constant
소 재 지 has 16 (5.1%) missing valuesMissing
지정일 has 9 (2.9%) missing valuesMissing

Reproduction

Analysis started2023-12-11 19:58:05.051227
Analysis finished2023-12-11 19:58:05.943499
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

종별
Categorical

Distinct6
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
기념물
138 
민속문화재
88 
유형문화재
42 
무형문화재
24 
문화재자료
 
11

Length

Max length5
Median length5
Mean length4.1182109
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기념물 138
44.1%
민속문화재 88
28.1%
유형문화재 42
 
13.4%
무형문화재 24
 
7.7%
문화재자료 11
 
3.5%
등록문화재 10
 
3.2%

Length

2023-12-12T04:58:06.051831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:58:06.258248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기념물 138
44.1%
민속문화재 88
28.1%
유형문화재 42
 
13.4%
무형문화재 24
 
7.7%
문화재자료 11
 
3.5%
등록문화재 10
 
3.2%

관리번호
Text

Distinct195
Distinct (%)62.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-12T04:58:06.681965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.9361022
Min length3

Characters and Unicode

Total characters1545
Distinct characters13
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

Unique118 ?
Unique (%)37.7%

Sample

1st row제2호
2nd row제3호
3rd row제4호
4th row제5호
5th row제6호
ValueCountFrequency (%)
제2호 5
 
1.6%
제9호 5
 
1.6%
제10호 5
 
1.6%
제11호 5
 
1.6%
제3호 5
 
1.6%
제49-9호 5
 
1.6%
제4호 5
 
1.6%
제6호 5
 
1.6%
제5호 4
 
1.3%
제8호 4
 
1.3%
Other values (185) 265
84.7%
2023-12-12T04:58:07.844490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 313
20.3%
호 313
20.3%
2 201
13.0%
- 182
11.8%
1 130
8.4%
3 103
 
6.7%
4 72
 
4.7%
9 51
 
3.3%
8 46
 
3.0%
6 40
 
2.6%
Other values (3) 94
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 737
47.7%
Other Letter 626
40.5%
Dash Punctuation 182
 
11.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 201
27.3%
1 130
17.6%
3 103
14.0%
4 72
 
9.8%
9 51
 
6.9%
8 46
 
6.2%
6 40
 
5.4%
5 39
 
5.3%
0 28
 
3.8%
7 27
 
3.7%
Other Letter
ValueCountFrequency (%)
제 313
50.0%
호 313
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 182
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 919
59.5%
Hangul 626
40.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 201
21.9%
- 182
19.8%
1 130
14.1%
3 103
11.2%
4 72
 
7.8%
9 51
 
5.5%
8 46
 
5.0%
6 40
 
4.4%
5 39
 
4.2%
0 28
 
3.0%
Hangul
ValueCountFrequency (%)
제 313
50.0%
호 313
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 919
59.5%
Hangul 626
40.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 313
50.0%
호 313
50.0%
ASCII
ValueCountFrequency (%)
2 201
21.9%
- 182
19.8%
1 130
14.1%
3 103
11.2%
4 72
 
7.8%
9 51
 
5.5%
8 46
 
5.0%
6 40
 
4.4%
5 39
 
4.2%
0 28
 
3.0%

문화재명
Text

Distinct267
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-12T04:58:08.289945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length6.8370607
Min length2

Characters and Unicode

Total characters2140
Distinct characters265
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique265 ?
Unique (%)84.7%

Sample

1st row제주향교
2nd row연북정
3rd row대정향교
4th row정의향교
5th row향사당
ValueCountFrequency (%)
돌하르방 46
 
9.5%
1호 17
 
3.5%
2호 14
 
2.9%
소장 12
 
2.5%
광령지석묘 10
 
2.1%
지석묘 8
 
1.6%
3호 7
 
1.4%
4호 7
 
1.4%
등명대 6
 
1.2%
골왓마을방사탑 5
 
1.0%
Other values (296) 354
72.8%
2023-12-12T04:58:09.119653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
179
 
8.4%
방 76
 
3.6%
지 70
 
3.3%
묘 57
 
2.7%
사 55
 
2.6%
호 55
 
2.6%
석 52
 
2.4%
하 52
 
2.4%
리 51
 
2.4%
돌 47
 
2.2%
Other values (255) 1446
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1894
88.5%
Space Separator 179
 
8.4%
Decimal Number 62
 
2.9%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
방 76
 
4.0%
지 70
 
3.7%
묘 57
 
3.0%
사 55
 
2.9%
호 55
 
2.9%
석 52
 
2.7%
하 52
 
2.7%
리 51
 
2.7%
돌 47
 
2.5%
르 46
 
2.4%
Other values (241) 1333
70.4%
Decimal Number
ValueCountFrequency (%)
1 21
33.9%
2 15
24.2%
3 8
 
12.9%
4 8
 
12.9%
5 5
 
8.1%
9 1
 
1.6%
6 1
 
1.6%
7 1
 
1.6%
8 1
 
1.6%
0 1
 
1.6%
Space Separator
ValueCountFrequency (%)
179
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
․ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1891
88.4%
Common 246
 
11.5%
Han 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
방 76
 
4.0%
지 70
 
3.7%
묘 57
 
3.0%
사 55
 
2.9%
호 55
 
2.9%
석 52
 
2.7%
하 52
 
2.7%
리 51
 
2.7%
돌 47
 
2.5%
르 46
 
2.4%
Other values (238) 1330
70.3%
Common
ValueCountFrequency (%)
179
72.8%
1 21
 
8.5%
2 15
 
6.1%
3 8
 
3.3%
4 8
 
3.3%
5 5
 
2.0%
) 2
 
0.8%
( 2
 
0.8%
․ 1
 
0.4%
9 1
 
0.4%
Other values (4) 4
 
1.6%
Han
ValueCountFrequency (%)
燈 1
33.3%
明 1
33.3%
臺 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1891
88.4%
ASCII 245
 
11.4%
CJK 3
 
0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
179
73.1%
1 21
 
8.6%
2 15
 
6.1%
3 8
 
3.3%
4 8
 
3.3%
5 5
 
2.0%
) 2
 
0.8%
( 2
 
0.8%
9 1
 
0.4%
6 1
 
0.4%
Other values (3) 3
 
1.2%
Hangul
ValueCountFrequency (%)
방 76
 
4.0%
지 70
 
3.7%
묘 57
 
3.0%
사 55
 
2.9%
호 55
 
2.9%
석 52
 
2.7%
하 52
 
2.7%
리 51
 
2.7%
돌 47
 
2.5%
르 46
 
2.4%
Other values (238) 1330
70.3%
Punctuation
ValueCountFrequency (%)
․ 1
100.0%
CJK
ValueCountFrequency (%)
燈 1
33.3%
明 1
33.3%
臺 1
33.3%

소 재 지
Text

MISSING 

Distinct255
Distinct (%)85.9%
Missing16
Missing (%)5.1%
Memory size2.6 KiB
2023-12-12T04:58:09.493108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length19.875421
Min length6

Characters and Unicode

Total characters5903
Distinct characters187
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

Unique230 ?
Unique (%)77.4%

Sample

1st row제주시 용담동 298번지
2nd row제주시 조천읍 조천리 2690번지
3rd row서귀포시 안덕면 사계리 3126번지
4th row서귀포시 표선면 성읍리 820-1번지
5th row제주시 삼도1동 970-2번지
ValueCountFrequency (%)
제주시 188
 
16.2%
서귀포시 109
 
9.4%
대정읍 33
 
2.8%
애월읍 29
 
2.5%
조천읍 21
 
1.8%
표선면 21
 
1.8%
외 20
 
1.7%
구좌읍 18
 
1.6%
성산읍 15
 
1.3%
이도1동 12
 
1.0%
Other values (403) 695
59.9%
2023-12-12T04:58:10.036136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
868
 
14.7%
시 303
 
5.1%
1 300
 
5.1%
지 270
 
4.6%
번 250
 
4.2%
주 216
 
3.7%
제 213
 
3.6%
2 170
 
2.9%
동 155
 
2.6%
읍 153
 
2.6%
Other values (177) 3005
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3576
60.6%
Decimal Number 1105
 
18.7%
Space Separator 868
 
14.7%
Dash Punctuation 120
 
2.0%
Open Punctuation 108
 
1.8%
Close Punctuation 107
 
1.8%
Uppercase Letter 12
 
0.2%
Other Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 303
 
8.5%
지 270
 
7.6%
번 250
 
7.0%
주 216
 
6.0%
제 213
 
6.0%
동 155
 
4.3%
읍 153
 
4.3%
리 152
 
4.3%
서 122
 
3.4%
귀 118
 
3.3%
Other values (157) 1624
45.4%
Decimal Number
ValueCountFrequency (%)
1 300
27.1%
2 170
15.4%
3 115
 
10.4%
6 109
 
9.9%
9 101
 
9.1%
5 69
 
6.2%
8 68
 
6.2%
7 62
 
5.6%
4 61
 
5.5%
0 50
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
B 4
33.3%
K 2
16.7%
S 2
16.7%
M 2
16.7%
C 2
16.7%
Space Separator
ValueCountFrequency (%)
868
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%
Open Punctuation
ValueCountFrequency (%)
( 108
100.0%
Close Punctuation
ValueCountFrequency (%)
) 107
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3576
60.6%
Common 2315
39.2%
Latin 12
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 303
 
8.5%
지 270
 
7.6%
번 250
 
7.0%
주 216
 
6.0%
제 213
 
6.0%
동 155
 
4.3%
읍 153
 
4.3%
리 152
 
4.3%
서 122
 
3.4%
귀 118
 
3.3%
Other values (157) 1624
45.4%
Common
ValueCountFrequency (%)
868
37.5%
1 300
 
13.0%
2 170
 
7.3%
- 120
 
5.2%
3 115
 
5.0%
6 109
 
4.7%
( 108
 
4.7%
) 107
 
4.6%
9 101
 
4.4%
5 69
 
3.0%
Other values (5) 248
 
10.7%
Latin
ValueCountFrequency (%)
B 4
33.3%
K 2
16.7%
S 2
16.7%
M 2
16.7%
C 2
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3576
60.6%
ASCII 2327
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
868
37.3%
1 300
 
12.9%
2 170
 
7.3%
- 120
 
5.2%
3 115
 
4.9%
6 109
 
4.7%
( 108
 
4.6%
) 107
 
4.6%
9 101
 
4.3%
5 69
 
3.0%
Other values (10) 260
 
11.2%
Hangul
ValueCountFrequency (%)
시 303
 
8.5%
지 270
 
7.6%
번 250
 
7.0%
주 216
 
6.0%
제 213
 
6.0%
동 155
 
4.3%
읍 153
 
4.3%
리 152
 
4.3%
서 122
 
3.4%
귀 118
 
3.3%
Other values (157) 1624
45.4%

지정일
Text

MISSING 

Distinct55
Distinct (%)18.1%
Missing9
Missing (%)2.9%
Memory size2.6 KiB
2023-12-12T04:58:10.349336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length10
Mean length10.101974
Min length10

Characters and Unicode

Total characters3071
Distinct characters19
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)6.6%

Sample

1st row1971.08.26
2nd row1971.08.26
3rd row1971.08.26
4th row1971.08.26
5th row1975.03.12
ValueCountFrequency (%)
1971.08.26 73
23.8%
1990.05.30 18
 
5.9%
1995.08.26 17
 
5.5%
1996.07.18 17
 
5.5%
1998.01.07 15
 
4.9%
2005.10.05 13
 
4.2%
1976.09.09 10
 
3.3%
2003.07.02 10
 
3.3%
1973.04.03 10
 
3.3%
2021.07.28 9
 
2.9%
Other values (47) 115
37.5%
2023-12-12T04:58:10.922673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 622
20.3%
. 614
20.0%
1 455
14.8%
9 337
11.0%
2 286
9.3%
7 197
 
6.4%
8 168
 
5.5%
6 150
 
4.9%
5 98
 
3.2%
3 68
 
2.2%
Other values (9) 76
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2444
79.6%
Other Punctuation 614
 
20.0%
Other Letter 4
 
0.1%
Space Separator 3
 
0.1%
Open Punctuation 2
 
0.1%
Initial Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 622
25.5%
1 455
18.6%
9 337
13.8%
2 286
11.7%
7 197
 
8.1%
8 168
 
6.9%
6 150
 
6.1%
5 98
 
4.0%
3 68
 
2.8%
4 63
 
2.6%
Other Letter
ValueCountFrequency (%)
추 1
25.0%
가 1
25.0%
변 1
25.0%
경 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 614
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3067
99.9%
Hangul 4
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 622
20.3%
. 614
20.0%
1 455
14.8%
9 337
11.0%
2 286
9.3%
7 197
 
6.4%
8 168
 
5.5%
6 150
 
4.9%
5 98
 
3.2%
3 68
 
2.2%
Other values (5) 72
 
2.3%
Hangul
ValueCountFrequency (%)
추 1
25.0%
가 1
25.0%
변 1
25.0%
경 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3065
99.8%
Hangul 4
 
0.1%
Punctuation 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 622
20.3%
. 614
20.0%
1 455
14.8%
9 337
11.0%
2 286
9.3%
7 197
 
6.4%
8 168
 
5.5%
6 150
 
4.9%
5 98
 
3.2%
3 68
 
2.2%
Other values (4) 70
 
2.3%
Punctuation
ValueCountFrequency (%)
‘ 2
100.0%
Hangul
ValueCountFrequency (%)
추 1
25.0%
가 1
25.0%
변 1
25.0%
경 1
25.0%

데이터갱신일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2022-10-28
313 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-10-28
2nd row2022-10-28
3rd row2022-10-28
4th row2022-10-28
5th row2022-10-28

Common Values

ValueCountFrequency (%)
2022-10-28 313
100.0%

Length

2023-12-12T04:58:11.133241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:58:11.259642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-10-28 313
100.0%

Correlations

2023-12-12T04:58:11.330358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종별지정일
종별1.0000.961
지정일0.9611.000

Missing values

2023-12-12T04:58:05.571858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T04:58:05.734985image/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.
2023-12-12T04:58:05.868066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

종별관리번호문화재명소 재 지지정일데이터갱신일자
0유형문화재제2호제주향교제주시 용담동 298번지1971.08.262022-10-28
1유형문화재제3호연북정제주시 조천읍 조천리 2690번지1971.08.262022-10-28
2유형문화재제4호대정향교서귀포시 안덕면 사계리 3126번지1971.08.262022-10-28
3유형문화재제5호정의향교서귀포시 표선면 성읍리 820-1번지1971.08.262022-10-28
4유형문화재제6호향사당제주시 삼도1동 970-2번지1975.03.122022-10-28
5유형문화재제8호신촌향사제주시 조천읍 신촌리 2156-1번지1975.03.122022-10-28
6유형문화재제9호추자처사각제주시 추자면 영흥리 285번지1975.03.122022-10-28
7유형문화재제10호용방록제주시 용담1동 298-8번지(제주향교 내)1991.06.042022-10-28
8유형문화재제11호연방록제주시 용담1동 298-8번지(제주향교 내)1991.06.042022-10-28
9유형문화재제12호급제선생안제주시 이도1동 1313번지(제주 삼성혈 전시관)1991.06.042022-10-28
종별관리번호문화재명소 재 지지정일데이터갱신일자
303등록문화재제1호제주 등명대(燈明臺)<NA>2021.07.282022-10-28
304등록문화재제1-1호고산리 등명대제주시 한경면 고산리 3616-18번지2021.07.282022-10-28
305등록문화재제1-2호김녕리 등명대제주시 구좌읍 김녕리 1270-1번지2021.07.282022-10-28
306등록문화재제1-3호대포동 등명대서귀포시 대포동 2184-12번지2021.07.282022-10-28
307등록문화재제1-4호보목동 등명대서귀포시 보목포구2021.07.282022-10-28
308등록문화재제1-5호북촌리 등명대제주시 조천읍 북촌리 1363-1번지2021.07.282022-10-28
309등록문화재제1-6호영일동 등명대제주시 우도면 연평리 133-1번지2021.07.282022-10-28
310등록문화재제2호제주 관음사 후불도제주시 산록북로 6602021.07.282022-10-28
311등록문화재제3호제주 금붕사 오백나한도제주시 구좌읍 일주동로 3618-12021.07.282022-10-28
312등록문화재제4호옛 한림성당 종탑제주시 한림읍 대림리 1814번지2022.06.292022-10-28