Overview

Dataset statistics

Number of variables8
Number of observations46
Missing cells4
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory67.9 B

Variable types

Categorical2
Numeric1
Text4
DateTime1

Dataset

Description서울특별시 중구 관내 문화재 현황입니다. 지정 구분, 종별, 지정번호, 위치, 지정일자, 소재지 등 정보를 제공합니다
URLhttps://www.data.go.kr/data/3079250/fileData.do

Alerts

구분 is highly overall correlated with 지정번호 and 1 other fieldsHigh correlation
종별 is highly overall correlated with 구분High correlation
지정번호 is highly overall correlated with 구분High correlation
위 치 has 4 (8.7%) missing valuesMissing
문화재명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:28:28.134400
Analysis finished2023-12-12 22:28:29.129884
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size500.0 B
시지정문화재
23 
등록문화재
12 
국가지정문화재
11 

Length

Max length7
Median length6.5
Mean length5.9782609
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
시지정문화재 23
50.0%
등록문화재 12
26.1%
국가지정문화재 11
23.9%

Length

2023-12-13T07:28:29.203147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:28:29.323150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시지정문화재 23
50.0%
등록문화재 12
26.1%
국가지정문화재 11
23.9%

종별
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
12 
사적
10 
기념물
8 
유 형
7 
민속문화재
7 
Other values (2)
2 

Length

Max length5
Median length4
Mean length3.3043478
Min length2

Unique

Unique2 ?
Unique (%)4.3%

Sample

1st row국보
2nd row사적
3rd row사적
4th row사적
5th row사적

Common Values

ValueCountFrequency (%)
<NA> 12
26.1%
사적 10
21.7%
기념물 8
17.4%
유 형 7
15.2%
민속문화재 7
15.2%
국보 1
 
2.2%
자료 1
 
2.2%

Length

2023-12-13T07:28:29.428198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:28:29.559064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 12
22.6%
사적 10
18.9%
기념물 8
15.1%
유 7
13.2%
형 7
13.2%
민속문화재 7
13.2%
국보 1
 
1.9%
자료 1
 
1.9%

지정번호
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean148.56522
Minimum1
Maximum836
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T07:28:29.675292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.5
Q114.5
median38.5
Q3252.75
95-th percentile611.75
Maximum836
Range835
Interquartile range (IQR)238.25

Descriptive statistics

Standard deviation204.79135
Coefficient of variation (CV)1.3784609
Kurtosis3.1300971
Mean148.56522
Median Absolute Deviation (MAD)33.5
Skewness1.8345615
Sum6834
Variance41939.496
MonotonicityNot monotonic
2023-12-13T07:28:29.814305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 3
 
6.5%
20 3
 
6.5%
5 2
 
4.3%
18 2
 
4.3%
39 1
 
2.2%
6 1
 
2.2%
8 1
 
2.2%
24 1
 
2.2%
32 1
 
2.2%
53 1
 
2.2%
Other values (30) 30
65.2%
ValueCountFrequency (%)
1 3
6.5%
3 1
 
2.2%
5 2
4.3%
6 1
 
2.2%
7 1
 
2.2%
8 1
 
2.2%
10 1
 
2.2%
11 1
 
2.2%
14 1
 
2.2%
16 1
 
2.2%
ValueCountFrequency (%)
836 1
2.2%
735 1
2.2%
662 1
2.2%
461 1
2.2%
412 1
2.2%
402 1
2.2%
284 1
2.2%
280 1
2.2%
267 1
2.2%
258 1
2.2%

문화재명
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-13T07:28:30.060858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length15
Mean length8.9130435
Min length3

Characters and Unicode

Total characters410
Distinct characters135
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

Unique46 ?
Unique (%)100.0%

Sample

1st row서울 숭례문(남대문)
2nd row서울 한양도성(광희문포함)
3rd row덕수궁
4th row환구단
5th row서울 약현성당
ValueCountFrequency (%)
서울 17
 
18.9%
구 8
 
8.9%
가옥 2
 
2.2%
남대문로 2
 
2.2%
와룡묘 1
 
1.1%
관성묘 1
 
1.1%
삼청동오장위김춘영가옥 1
 
1.1%
관훈동 1
 
1.1%
민씨 1
 
1.1%
심슨기념관 1
 
1.1%
Other values (55) 55
61.1%
2023-12-13T07:28:30.444603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44
 
10.7%
서 21
 
5.1%
울 21
 
5.1%
관 14
 
3.4%
구 11
 
2.7%
동 10
 
2.4%
수 10
 
2.4%
문 9
 
2.2%
사 8
 
2.0%
국 7
 
1.7%
Other values (125) 255
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 355
86.6%
Space Separator 44
 
10.7%
Close Punctuation 4
 
1.0%
Open Punctuation 4
 
1.0%
Decimal Number 2
 
0.5%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 21
 
5.9%
울 21
 
5.9%
관 14
 
3.9%
구 11
 
3.1%
동 10
 
2.8%
수 10
 
2.8%
문 9
 
2.5%
사 8
 
2.3%
국 7
 
2.0%
가 7
 
2.0%
Other values (120) 237
66.8%
Space Separator
ValueCountFrequency (%)
44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Decimal Number
ValueCountFrequency (%)
2 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 355
86.6%
Common 55
 
13.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 21
 
5.9%
울 21
 
5.9%
관 14
 
3.9%
구 11
 
3.1%
동 10
 
2.8%
수 10
 
2.8%
문 9
 
2.5%
사 8
 
2.3%
국 7
 
2.0%
가 7
 
2.0%
Other values (120) 237
66.8%
Common
ValueCountFrequency (%)
44
80.0%
) 4
 
7.3%
( 4
 
7.3%
2 2
 
3.6%
, 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 355
86.6%
ASCII 55
 
13.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44
80.0%
) 4
 
7.3%
( 4
 
7.3%
2 2
 
3.6%
, 1
 
1.8%
Hangul
ValueCountFrequency (%)
서 21
 
5.9%
울 21
 
5.9%
관 14
 
3.9%
구 11
 
3.1%
동 10
 
2.8%
수 10
 
2.8%
문 9
 
2.5%
사 8
 
2.3%
국 7
 
2.0%
가 7
 
2.0%
Other values (120) 237
66.8%

위 치
Text

MISSING 

Distinct42
Distinct (%)100.0%
Missing4
Missing (%)8.7%
Memory size500.0 B
2023-12-13T07:28:30.672414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length17.690476
Min length5

Characters and Unicode

Total characters743
Distinct characters61
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row서울특별시 중구 남대문로4가 29
2nd row서울특별시 중구 돈의문~오간수문(광희동2가 105)
3rd row서울특별시 중구 정동 5-1 등
4th row서울특별시 중구 소공동 87-14
5th row서울특별시 중구 중림동 149-2
ValueCountFrequency (%)
서울특별시 42
25.0%
중구 41
24.4%
정동 9
 
5.4%
장충동2가 4
 
2.4%
등 4
 
2.4%
소공동 2
 
1.2%
남대문로1가 2
 
1.2%
예장동 2
 
1.2%
만리동2가 2
 
1.2%
명동2가 2
 
1.2%
Other values (57) 58
34.5%
2023-12-13T07:28:31.053071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
126
17.0%
서 43
 
5.8%
특 42
 
5.7%
별 42
 
5.7%
시 42
 
5.7%
중 42
 
5.7%
울 42
 
5.7%
구 41
 
5.5%
1 41
 
5.5%
동 29
 
3.9%
Other values (51) 253
34.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 446
60.0%
Decimal Number 141
 
19.0%
Space Separator 126
 
17.0%
Dash Punctuation 27
 
3.6%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 43
9.6%
특 42
9.4%
별 42
9.4%
시 42
9.4%
중 42
9.4%
울 42
9.4%
구 41
9.2%
동 29
 
6.5%
가 21
 
4.7%
로 12
 
2.7%
Other values (36) 90
20.2%
Decimal Number
ValueCountFrequency (%)
1 41
29.1%
2 28
19.9%
3 15
 
10.6%
4 11
 
7.8%
5 9
 
6.4%
0 9
 
6.4%
9 8
 
5.7%
6 7
 
5.0%
8 7
 
5.0%
7 6
 
4.3%
Space Separator
ValueCountFrequency (%)
126
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 446
60.0%
Common 297
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 43
9.6%
특 42
9.4%
별 42
9.4%
시 42
9.4%
중 42
9.4%
울 42
9.4%
구 41
9.2%
동 29
 
6.5%
가 21
 
4.7%
로 12
 
2.7%
Other values (36) 90
20.2%
Common
ValueCountFrequency (%)
126
42.4%
1 41
 
13.8%
2 28
 
9.4%
- 27
 
9.1%
3 15
 
5.1%
4 11
 
3.7%
5 9
 
3.0%
0 9
 
3.0%
9 8
 
2.7%
6 7
 
2.4%
Other values (5) 16
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 446
60.0%
ASCII 297
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
126
42.4%
1 41
 
13.8%
2 28
 
9.4%
- 27
 
9.1%
3 15
 
5.1%
4 11
 
3.7%
5 9
 
3.0%
0 9
 
3.0%
9 8
 
2.7%
6 7
 
2.4%
Other values (5) 16
 
5.4%
Hangul
ValueCountFrequency (%)
서 43
9.6%
특 42
9.4%
별 42
9.4%
시 42
9.4%
중 42
9.4%
울 42
9.4%
구 41
9.2%
동 29
 
6.5%
가 21
 
4.7%
로 12
 
2.7%
Other values (36) 90
20.2%

건축연도
Text

Distinct34
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-13T07:28:31.272696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.3043478
Min length4

Characters and Unicode

Total characters198
Distinct characters23
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

Unique28 ?
Unique (%)60.9%

Sample

1st row1398
2nd row1396
3rd row조선시대
4th row1897
5th row1892
ValueCountFrequency (%)
조선시대 5
 
10.6%
1928 3
 
6.4%
대한제국 3
 
6.4%
1897 3
 
6.4%
1935 2
 
4.3%
1926 2
 
4.3%
중건 1
 
2.1%
1950년대 1
 
2.1%
1930 1
 
2.1%
1905 1
 
2.1%
Other values (25) 25
53.2%
2023-12-13T07:28:31.610399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 40
20.2%
9 33
16.7%
8 19
9.6%
0 14
 
7.1%
대 13
 
6.6%
3 10
 
5.1%
6 9
 
4.5%
2 9
 
4.5%
5 7
 
3.5%
조 6
 
3.0%
Other values (13) 38
19.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 148
74.7%
Other Letter 49
 
24.7%
Space Separator 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 13
26.5%
조 6
12.2%
년 6
12.2%
선 6
12.2%
시 5
 
10.2%
국 3
 
6.1%
제 3
 
6.1%
한 3
 
6.1%
전 1
 
2.0%
기 1
 
2.0%
Other values (2) 2
 
4.1%
Decimal Number
ValueCountFrequency (%)
1 40
27.0%
9 33
22.3%
8 19
12.8%
0 14
 
9.5%
3 10
 
6.8%
6 9
 
6.1%
2 9
 
6.1%
5 7
 
4.7%
7 6
 
4.1%
4 1
 
0.7%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 149
75.3%
Hangul 49
 
24.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 13
26.5%
조 6
12.2%
년 6
12.2%
선 6
12.2%
시 5
 
10.2%
국 3
 
6.1%
제 3
 
6.1%
한 3
 
6.1%
전 1
 
2.0%
기 1
 
2.0%
Other values (2) 2
 
4.1%
Common
ValueCountFrequency (%)
1 40
26.8%
9 33
22.1%
8 19
12.8%
0 14
 
9.4%
3 10
 
6.7%
6 9
 
6.0%
2 9
 
6.0%
5 7
 
4.7%
7 6
 
4.0%
4 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 149
75.3%
Hangul 49
 
24.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 40
26.8%
9 33
22.1%
8 19
12.8%
0 14
 
9.4%
3 10
 
6.7%
6 9
 
6.0%
2 9
 
6.0%
5 7
 
4.7%
7 6
 
4.0%
4 1
 
0.7%
Hangul
ValueCountFrequency (%)
대 13
26.5%
조 6
12.2%
년 6
12.2%
선 6
12.2%
시 5
 
10.2%
국 3
 
6.1%
제 3
 
6.1%
한 3
 
6.1%
전 1
 
2.0%
기 1
 
2.0%
Other values (2) 2
 
4.1%

규모
Text

Distinct44
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-13T07:28:31.857438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length8.4782609
Min length2

Characters and Unicode

Total characters390
Distinct characters24
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)93.5%

Sample

1st row1,318㎡
2nd row7,210m
3rd row63,609㎡
4th row4,278㎡
5th row1,309㎡
ValueCountFrequency (%)
1棟 3
 
6.4%
13,104,31㎡ 1
 
2.1%
14,932,71㎡ 1
 
2.1%
6992.1㎡ 1
 
2.1%
3棟(166.6㎡ 1
 
2.1%
1棟(31.6㎡ 1
 
2.1%
1棟(167.9㎡ 1
 
2.1%
1棟(422.2㎡ 1
 
2.1%
2棟(237.7㎡ 1
 
2.1%
2棟(536.3㎡ 1
 
2.1%
Other values (35) 35
74.5%
2023-12-13T07:28:32.234605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 64
16.4%
㎡ 41
10.5%
棟 27
 
6.9%
( 27
 
6.9%
) 27
 
6.9%
. 26
 
6.7%
, 24
 
6.2%
2 24
 
6.2%
3 22
 
5.6%
6 18
 
4.6%
Other values (14) 90
23.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 209
53.6%
Other Punctuation 50
 
12.8%
Other Symbol 41
 
10.5%
Other Letter 34
 
8.7%
Open Punctuation 27
 
6.9%
Close Punctuation 27
 
6.9%
Lowercase Letter 1
 
0.3%
Space Separator 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 64
30.6%
2 24
 
11.5%
3 22
 
10.5%
6 18
 
8.6%
4 17
 
8.1%
7 17
 
8.1%
0 15
 
7.2%
9 12
 
5.7%
5 10
 
4.8%
8 10
 
4.8%
Other Letter
ValueCountFrequency (%)
棟 27
79.4%
基 2
 
5.9%
株 1
 
2.9%
전 1
 
2.9%
면 1
 
2.9%
현 1
 
2.9%
관 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 26
52.0%
, 24
48.0%
Other Symbol
ValueCountFrequency (%)
㎡ 41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 355
91.0%
Han 30
 
7.7%
Hangul 4
 
1.0%
Latin 1
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 64
18.0%
㎡ 41
11.5%
( 27
7.6%
) 27
7.6%
. 26
 
7.3%
, 24
 
6.8%
2 24
 
6.8%
3 22
 
6.2%
6 18
 
5.1%
4 17
 
4.8%
Other values (6) 65
18.3%
Hangul
ValueCountFrequency (%)
전 1
25.0%
면 1
25.0%
현 1
25.0%
관 1
25.0%
Han
ValueCountFrequency (%)
棟 27
90.0%
基 2
 
6.7%
株 1
 
3.3%
Latin
ValueCountFrequency (%)
m 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 315
80.8%
CJK Compat 41
 
10.5%
CJK 30
 
7.7%
Hangul 4
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 64
20.3%
( 27
8.6%
) 27
8.6%
. 26
8.3%
, 24
 
7.6%
2 24
 
7.6%
3 22
 
7.0%
6 18
 
5.7%
4 17
 
5.4%
7 17
 
5.4%
Other values (6) 49
15.6%
CJK Compat
ValueCountFrequency (%)
㎡ 41
100.0%
CJK
ValueCountFrequency (%)
棟 27
90.0%
基 2
 
6.7%
株 1
 
3.3%
Hangul
ValueCountFrequency (%)
전 1
25.0%
면 1
25.0%
현 1
25.0%
관 1
25.0%

지정일자
Date

Distinct35
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Memory size500.0 B
Minimum1901-03-15 00:00:00
Maximum2022-07-14 00:00:00
2023-12-13T07:28:32.369560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:28:32.525497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)

Interactions

2023-12-13T07:28:28.859217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:28:32.616961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분종별지정번호문화재명위 치건축연도규모지정일자
구분1.0001.0000.9221.0001.0000.6560.8101.000
종별1.0001.0000.5411.0001.0000.6091.0000.987
지정번호0.9220.5411.0001.0001.0000.7990.9481.000
문화재명1.0001.0001.0001.0001.0001.0001.0001.000
위 치1.0001.0001.0001.0001.0001.0001.0001.000
건축연도0.6560.6090.7991.0001.0001.0000.9740.781
규모0.8101.0000.9481.0001.0000.9741.0000.852
지정일자1.0000.9871.0001.0001.0000.7810.8521.000
2023-12-13T07:28:32.708526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분종별
구분1.0000.935
종별0.9351.000
2023-12-13T07:28:32.780503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정번호구분종별
지정번호1.0000.6250.360
구분0.6251.0000.935
종별0.3600.9351.000

Missing values

2023-12-13T07:28:28.968378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:28:29.085338image/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

구분종별지정번호문화재명위 치건축연도규모지정일자
0국가지정문화재국보1서울 숭례문(남대문)서울특별시 중구 남대문로4가 2913981,318㎡1962-12-20
1국가지정문화재사적10서울 한양도성(광희문포함)서울특별시 중구 돈의문~오간수문(광희동2가 105)13967,210m1963-01-21
2국가지정문화재사적124덕수궁서울특별시 중구 정동 5-1 등조선시대63,609㎡1963-01-18
3국가지정문화재사적157환구단서울특별시 중구 소공동 87-1418974,278㎡1967-07-15
4국가지정문화재사적252서울 약현성당서울특별시 중구 중림동 149-218921,309㎡1976-11-16
5국가지정문화재사적253서울 구 러시아공사관서울특별시 중구 정동 15-1 등18901,022㎡1977-11-22
6국가지정문화재사적256서울 정동교회서울특별시 중구 정동 34-318971,133㎡1977-11-22
7국가지정문화재사적258서울 명동성당서울특별시 중구 명동2가 1-118981,668㎡1977-11-22
8국가지정문화재사적280서울 한국은행 본관서울특별시 중구 남대문로3가 11019128,703㎡1981-09-25
9국가지정문화재사적284구 서울역사서울특별시 중구 봉래동2가 122-2819252,964㎡1981-09-25
구분종별지정번호문화재명위 치건축연도규모지정일자
36등록문화재<NA>11서울 구 국회의사당서울특별시 중구 태평로1가 60-119351棟2002-05-31
37등록문화재<NA>52구 서울특별시청사서울특별시 중구 태평로1가 3119261棟2003-06-30
38등록문화재<NA>237서울 구 대법원 청사서울특별시 중구 서소문동 371928전면, 현관2006-03-02
39등록문화재<NA>238서울 구 미국문화원서울특별시 중구 을지로1가 6319381棟(4,208.26㎡)2006-03-02
40등록문화재<NA>267경운궁 양이재서울특별시 중구 정동319051棟(145㎡)2006-09-19
41등록문화재<NA>402서울 구 신아일보 별관서울특별시 중구 정동 1-2819301棟(2,000.53㎡)2008-08-27
42등록문화재<NA>412서울 신당동 박정희 가옥서울특별시 중구 신당동 62-431950년대1棟(128.93㎡)2008-10-10
43등록문화재<NA>662서울 남대문로 2층 한옥상가서울특별시1900년대1棟(75㎡)2016-08-17
44등록문화재<NA>735서울 동국대학교 구 본관(석조관)<NA>19581棟(1,407.4㎡)2018-11-06
45등록문화재<NA>836유네스코회관서울특별시 중구 명동2가 50-1419671棟(13,367.1㎡)2022-07-14