Overview

Dataset statistics

Number of variables8
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory70.1 B

Variable types

Numeric1
Categorical2
Text4
DateTime1

Dataset

Description부산광역시 해운대구 소재 문화재 현황국가지정, 등록문화재 및 부산광역시지정문화재, 문화재 자료 등을 소개합니다문화재명, 문화재 종류, 문화재 지정번호, 지정일자, 소재지, 관리단체 등
Author부산광역시 해운대구
URLhttps://www.data.go.kr/data/3075334/fileData.do

Alerts

연번 is highly overall correlated with 종류High correlation
종류 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
종별 is highly overall correlated with 종류High correlation
연번 has unique valuesUnique
지정번호 has unique valuesUnique
문화재명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 15:13:15.413842
Analysis finished2024-03-14 15:13:16.841865
Duration1.43 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  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 size353.0 B
2024-03-15T00:13:17.029132image/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
2024-03-15T00:13:17.424999image/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%

종류
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
시지정문화재
21 
국가지정문화재
4 

Length

Max length7
Median length6
Mean length6.16
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row국가지정문화재
2nd row국가지정문화재
3rd row국가지정문화재
4th row국가지정문화재
5th row시지정문화재

Common Values

ValueCountFrequency (%)
시지정문화재 21
84.0%
국가지정문화재 4
 
16.0%

Length

2024-03-15T00:13:17.826223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:13:18.028209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시지정문화재 21
84.0%
국가지정문화재 4
 
16.0%

종별
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
유형문화재
9 
문화재자료
8 
보물
3 
기념물
2 
등록문화재
1 
Other values (2)
2 

Length

Max length5
Median length5
Mean length4.48
Min length2

Unique

Unique3 ?
Unique (%)12.0%

Sample

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

Common Values

ValueCountFrequency (%)
유형문화재 9
36.0%
문화재자료 8
32.0%
보물 3
 
12.0%
기념물 2
 
8.0%
등록문화재 1
 
4.0%
무형문화재 1
 
4.0%
민속문화재 1
 
4.0%

Length

2024-03-15T00:13:18.212568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:13:18.410525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유형문화재 9
36.0%
문화재자료 8
32.0%
보물 3
 
12.0%
기념물 2
 
8.0%
등록문화재 1
 
4.0%
무형문화재 1
 
4.0%
민속문화재 1
 
4.0%

지정번호
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
2024-03-15T00:13:19.151965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.56
Min length3

Characters and Unicode

Total characters114
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row제953호
2nd row제954호
3rd row제574호
4th row제302호
5th row제129호
ValueCountFrequency (%)
제953호 1
 
4.0%
제50호 1
 
4.0%
제137호 1
 
4.0%
제127호 1
 
4.0%
제6호 1
 
4.0%
제46호 1
 
4.0%
제45호 1
 
4.0%
제126호 1
 
4.0%
제115호 1
 
4.0%
제79호 1
 
4.0%
Other values (15) 15
60.0%
2024-03-15T00:13:20.362211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 25
21.9%
호 25
21.9%
1 13
11.4%
2 12
10.5%
6 7
 
6.1%
5 6
 
5.3%
3 6
 
5.3%
7 6
 
5.3%
9 5
 
4.4%
4 5
 
4.4%
Other values (2) 4
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
56.1%
Other Letter 50
43.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
20.3%
2 12
18.8%
6 7
10.9%
5 6
9.4%
3 6
9.4%
7 6
9.4%
9 5
 
7.8%
4 5
 
7.8%
0 3
 
4.7%
8 1
 
1.6%
Other Letter
ValueCountFrequency (%)
제 25
50.0%
호 25
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 64
56.1%
Hangul 50
43.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
20.3%
2 12
18.8%
6 7
10.9%
5 6
9.4%
3 6
9.4%
7 6
9.4%
9 5
 
7.8%
4 5
 
7.8%
0 3
 
4.7%
8 1
 
1.6%
Hangul
ValueCountFrequency (%)
제 25
50.0%
호 25
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64
56.1%
Hangul 50
43.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 25
50.0%
호 25
50.0%
ASCII
ValueCountFrequency (%)
1 13
20.3%
2 12
18.8%
6 7
10.9%
5 6
9.4%
3 6
9.4%
7 6
9.4%
9 5
 
7.8%
4 5
 
7.8%
0 3
 
4.7%
8 1
 
1.6%

지정일자
Date

Distinct17
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
Minimum1973-12-31 00:00:00
Maximum2023-11-29 00:00:00
2024-03-15T00:13:20.554569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:13:20.746766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)

문화재명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
2024-03-15T00:13:21.405948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length7.64
Min length2

Characters and Unicode

Total characters191
Distinct characters92
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row조숭고신왕지
2nd row조서경무과홍패
3rd row박만정 해서암행일기
4th row송정역
5th row폭포사 묘법연화경
ValueCountFrequency (%)
해운정사 4
 
9.8%
삼절사 2
 
4.9%
현수제승법수 2
 
4.9%
묘법연화경 2
 
4.9%
백운사 2
 
4.9%
일괄 1
 
2.4%
현왕도 1
 
2.4%
선문염송집 1
 
2.4%
법어 1
 
2.4%
반송 1
 
2.4%
Other values (24) 24
58.5%
2024-03-15T00:13:22.282975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
 
8.4%
사 11
 
5.8%
법 7
 
3.7%
운 7
 
3.7%
정 6
 
3.1%
해 6
 
3.1%
고 4
 
2.1%
화 4
 
2.1%
수 4
 
2.1%
경 4
 
2.1%
Other values (82) 122
63.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 167
87.4%
Space Separator 16
 
8.4%
Decimal Number 4
 
2.1%
Dash Punctuation 2
 
1.0%
Math Symbol 1
 
0.5%
Close Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 11
 
6.6%
법 7
 
4.2%
운 7
 
4.2%
정 6
 
3.6%
해 6
 
3.6%
고 4
 
2.4%
화 4
 
2.4%
수 4
 
2.4%
경 4
 
2.4%
석 4
 
2.4%
Other values (74) 110
65.9%
Decimal Number
ValueCountFrequency (%)
1 1
25.0%
3 1
25.0%
4 1
25.0%
7 1
25.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166
86.9%
Common 24
 
12.6%
Han 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 11
 
6.6%
법 7
 
4.2%
운 7
 
4.2%
정 6
 
3.6%
해 6
 
3.6%
고 4
 
2.4%
화 4
 
2.4%
수 4
 
2.4%
경 4
 
2.4%
석 4
 
2.4%
Other values (73) 109
65.7%
Common
ValueCountFrequency (%)
16
66.7%
- 2
 
8.3%
+ 1
 
4.2%
) 1
 
4.2%
1 1
 
4.2%
3 1
 
4.2%
4 1
 
4.2%
7 1
 
4.2%
Han
ValueCountFrequency (%)
舊 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166
86.9%
ASCII 24
 
12.6%
CJK 1
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
66.7%
- 2
 
8.3%
+ 1
 
4.2%
) 1
 
4.2%
1 1
 
4.2%
3 1
 
4.2%
4 1
 
4.2%
7 1
 
4.2%
Hangul
ValueCountFrequency (%)
사 11
 
6.6%
법 7
 
4.2%
운 7
 
4.2%
정 6
 
3.6%
해 6
 
3.6%
고 4
 
2.4%
화 4
 
2.4%
수 4
 
2.4%
경 4
 
2.4%
석 4
 
2.4%
Other values (73) 109
65.7%
CJK
ValueCountFrequency (%)
舊 1
100.0%

소재지
Text

Distinct17
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
2024-03-15T00:13:23.009963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length20.32
Min length7

Characters and Unicode

Total characters508
Distinct characters53
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

Unique13 ?
Unique (%)52.0%

Sample

1st row국립중앙박물관
2nd row국립중앙박물관
3rd row부산광역시 해운대구
4th row부산광역시 해운대구 송정중앙로8번길 60(송정동)
5th row부산광역시 해운대구 장산로 331-112(우동)
ValueCountFrequency (%)
부산광역시 23
26.4%
해운대구 23
26.4%
우동2로 4
 
4.6%
40-6(우동 4
 
4.6%
국립중앙박물관 2
 
2.3%
운봉길 2
 
2.3%
315(반송동 2
 
2.3%
장산로 2
 
2.3%
148-1번지 1
 
1.1%
710-1일원 1
 
1.1%
Other values (23) 23
26.4%
2024-03-15T00:13:24.147346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
64
 
12.6%
산 27
 
5.3%
운 25
 
4.9%
부 23
 
4.5%
광 23
 
4.5%
역 23
 
4.5%
시 23
 
4.5%
해 23
 
4.5%
대 23
 
4.5%
구 23
 
4.5%
Other values (43) 231
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 323
63.6%
Decimal Number 83
 
16.3%
Space Separator 64
 
12.6%
Open Punctuation 13
 
2.6%
Close Punctuation 13
 
2.6%
Dash Punctuation 12
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 27
 
8.4%
운 25
 
7.7%
부 23
 
7.1%
광 23
 
7.1%
역 23
 
7.1%
시 23
 
7.1%
해 23
 
7.1%
대 23
 
7.1%
구 23
 
7.1%
동 20
 
6.2%
Other values (29) 90
27.9%
Decimal Number
ValueCountFrequency (%)
1 22
26.5%
2 17
20.5%
4 9
10.8%
0 7
 
8.4%
8 6
 
7.2%
3 6
 
7.2%
6 5
 
6.0%
7 5
 
6.0%
5 4
 
4.8%
9 2
 
2.4%
Space Separator
ValueCountFrequency (%)
64
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 323
63.6%
Common 185
36.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 27
 
8.4%
운 25
 
7.7%
부 23
 
7.1%
광 23
 
7.1%
역 23
 
7.1%
시 23
 
7.1%
해 23
 
7.1%
대 23
 
7.1%
구 23
 
7.1%
동 20
 
6.2%
Other values (29) 90
27.9%
Common
ValueCountFrequency (%)
64
34.6%
1 22
 
11.9%
2 17
 
9.2%
( 13
 
7.0%
) 13
 
7.0%
- 12
 
6.5%
4 9
 
4.9%
0 7
 
3.8%
8 6
 
3.2%
3 6
 
3.2%
Other values (4) 16
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 323
63.6%
ASCII 185
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
64
34.6%
1 22
 
11.9%
2 17
 
9.2%
( 13
 
7.0%
) 13
 
7.0%
- 12
 
6.5%
4 9
 
4.9%
0 7
 
3.8%
8 6
 
3.2%
3 6
 
3.2%
Other values (4) 16
 
8.6%
Hangul
ValueCountFrequency (%)
산 27
 
8.4%
운 25
 
7.7%
부 23
 
7.1%
광 23
 
7.1%
역 23
 
7.1%
시 23
 
7.1%
해 23
 
7.1%
대 23
 
7.1%
구 23
 
7.1%
동 20
 
6.2%
Other values (29) 90
27.9%

관리주체
Text

Distinct15
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
2024-03-15T00:13:24.817141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length5.04
Min length2

Characters and Unicode

Total characters126
Distinct characters50
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)32.0%

Sample

1st row국립중앙박물관
2nd row국립중앙박물관
3rd row개인
4th row한국철도공사
5th row폭포사
ValueCountFrequency (%)
해운정사 4
14.3%
개인 3
10.7%
국립중앙박물관 2
 
7.1%
백운사 2
 
7.1%
남원양씨삼절사 2
 
7.1%
반송문회 2
 
7.1%
해운대구청장 2
 
7.1%
대원각사 2
 
7.1%
예능보유자 1
 
3.6%
장산신당보존위원회 1
 
3.6%
Other values (7) 7
25.0%
2024-03-15T00:13:25.582004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 16
 
12.7%
운 8
 
6.3%
원 7
 
5.6%
해 6
 
4.8%
장 5
 
4.0%
인 5
 
4.0%
각 4
 
3.2%
대 4
 
3.2%
정 4
 
3.2%
3
 
2.4%
Other values (40) 64
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 123
97.6%
Space Separator 3
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 16
 
13.0%
운 8
 
6.5%
원 7
 
5.7%
해 6
 
4.9%
장 5
 
4.1%
인 5
 
4.1%
각 4
 
3.3%
대 4
 
3.3%
정 4
 
3.3%
개 3
 
2.4%
Other values (39) 61
49.6%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 123
97.6%
Common 3
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 16
 
13.0%
운 8
 
6.5%
원 7
 
5.7%
해 6
 
4.9%
장 5
 
4.1%
인 5
 
4.1%
각 4
 
3.3%
대 4
 
3.3%
정 4
 
3.3%
개 3
 
2.4%
Other values (39) 61
49.6%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 123
97.6%
ASCII 3
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 16
 
13.0%
운 8
 
6.5%
원 7
 
5.7%
해 6
 
4.9%
장 5
 
4.1%
인 5
 
4.1%
각 4
 
3.3%
대 4
 
3.3%
정 4
 
3.3%
개 3
 
2.4%
Other values (39) 61
49.6%
ASCII
ValueCountFrequency (%)
3
100.0%

Interactions

2024-03-15T00:13:15.880840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T00:13:25.739341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종류종별지정번호지정일자문화재명소재지관리주체
연번1.0000.9800.8201.0000.8351.0000.8680.881
종류0.9801.0001.0001.0001.0001.0000.6400.786
종별0.8201.0001.0001.0000.9351.0000.8300.967
지정번호1.0001.0001.0001.0001.0001.0001.0001.000
지정일자0.8351.0000.9351.0001.0001.0000.9570.963
문화재명1.0001.0001.0001.0001.0001.0001.0001.000
소재지0.8680.6400.8301.0000.9571.0001.0000.973
관리주체0.8810.7860.9671.0000.9631.0000.9731.000
2024-03-15T00:13:26.022402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종류종별
종류1.0000.885
종별0.8851.000
2024-03-15T00:13:26.257064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종류종별
연번1.0000.7050.482
종류0.7051.0000.885
종별0.4820.8851.000

Missing values

2024-03-15T00:13:16.225684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T00:13:16.664212image/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

연번종류종별지정번호지정일자문화재명소재지관리주체
01국가지정문화재보물제953호1988-06-16조숭고신왕지국립중앙박물관국립중앙박물관
12국가지정문화재보물제954호1988-06-16조서경무과홍패국립중앙박물관국립중앙박물관
23국가지정문화재보물제574호1973-12-31박만정 해서암행일기부산광역시 해운대구개인
34국가지정문화재등록문화재제302호2006-12-04송정역부산광역시 해운대구 송정중앙로8번길 60(송정동)한국철도공사
45시지정문화재유형문화재제129호2013-10-23폭포사 묘법연화경부산광역시 해운대구 장산로 331-112(우동)폭포사
56시지정문화재유형문화재제132호2013-10-23백운사 묘법연화경 권1-3부산광역시 해운대구 운봉길 315(반송동)백운사
67시지정문화재유형문화재제133호2013-10-23백운사 묘법연화경권4-7부산광역시 해운대구 운봉길 315(반송동)백운사
78시지정문화재유형문화재제149호2014-09-24해운정사 전법게부산광역시 해운대구 우동2로 40-6(우동)해운정사
89시지정문화재유형문화재제201호2019-04-10원오사 고봉화상선요부산광역시 해운대구 윗반송로 124-5 (반송동)원오사
910시지정문화재유형문화재제212호2020-04-29해운정사 삼층석탑부산광역시 해운대구 우동2로 40-6(우동)해운정사
연번종류종별지정번호지정일자문화재명소재지관리주체
1516시지정문화재문화재자료제78호2014-09-24해운정사 선문염송집부산광역시 해운대구 우동2로 40-6(우동)해운정사
1617시지정문화재문화재자료제79호2014-09-24해운정사 현수제승법수부산광역시 해운대구 우동2로 40-6(우동)해운정사
1718시지정문화재문화재자료제115호2021-01-27법어부산광역시 해운대구개인
1819시지정문화재문화재자료제126호2022-11-30반송 삼절사 고문서 일괄부산광역시 해운대구남원양씨삼절사 반송문회
1920시지정문화재기념물제45호1999-03-09해운대석각부산광역시 해운대구 우1동710-1(공유수면)해운대구청장
2021시지정문화재기념물제46호1999-03-09동백섬부산광역시 해운대구 우1동 710-1일원해운대구청장
2122시지정문화재민속문화재제6호2009-12-07장산 마고당+천제단부산광역시 해운대구 우동 산 148-1번지장산신당보존위원회
2223시지정문화재문화재자료제127호2023-03-16칠성여래도부산광역시 해운대구 송정1로8번길 25-78 2층덕인사
2324시지정문화재유형문화재제137호2014-03-19자치통감강목부산광역시 해운대구 좌동 1132대원각사
2425시지정문화재유형문화재제226호2023-11-29선종영가집부산광역시 해운대구 장산로427-291대원각사