Overview

Dataset statistics

Number of variables12
Number of observations25
Missing cells7
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory103.3 B

Variable types

Numeric2
Text9
DateTime1

Dataset

Description인천광역시_스마트GIS 플랫폼에 등록되어있으며 중구 문화정보(문화재명, 건립연도 등)에 대한 데이터를 제공합니다.
Author인천광역시
URLhttps://www.data.go.kr/data/15049255/fileData.do

Alerts

도로명 has 5 (20.0%) missing valuesMissing
건립연도 has 2 (8.0%) missing valuesMissing
일련번호 has unique valuesUnique
문화재명 has unique valuesUnique
지정번호 has unique valuesUnique
문화재사진명 has unique valuesUnique
영어 상점명 has unique valuesUnique
일본어 상점명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:25:40.516446
Analysis finished2023-12-12 06:25:41.582128
Duration1.07 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

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 size357.0 B
2023-12-12T15:25:41.631779image/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
2023-12-12T15:25:41.770319image/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%

문화재명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T15:25:41.996055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length7.6
Min length3

Characters and Unicode

Total characters190
Distinct characters89
Distinct categories5 ?
Distinct scripts2 ?
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 row인천선린동공화춘
2nd row구일본우선주식회사
3rd row구인천부청사
4th row제물포고등학교강당
5th row인천구대화조사무소(카페팟알)
ValueCountFrequency (%)
인천선린동공화춘 1
 
4.0%
구인천일본18은행지점 1
 
4.0%
능인교당현왕탱화 1
 
4.0%
조병수가옥 1
 
4.0%
삼목도선사주거지 1
 
4.0%
답동성당 1
 
4.0%
청·일조계지경계계단 1
 
4.0%
양주성금속비 1
 
4.0%
용궁사느티나무 1
 
4.0%
용궁사수월관음도 1
 
4.0%
Other values (15) 15
60.0%
2023-12-12T15:25:42.402126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 10
 
5.3%
구 9
 
4.7%
천 8
 
4.2%
사 7
 
3.7%
지 5
 
2.6%
일 5
 
2.6%
동 5
 
2.6%
당 5
 
2.6%
화 4
 
2.1%
본 4
 
2.1%
Other values (79) 128
67.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 182
95.8%
Decimal Number 5
 
2.6%
Other Punctuation 1
 
0.5%
Open Punctuation 1
 
0.5%
Close Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 10
 
5.5%
구 9
 
4.9%
천 8
 
4.4%
사 7
 
3.8%
지 5
 
2.7%
일 5
 
2.7%
동 5
 
2.7%
당 5
 
2.7%
화 4
 
2.2%
본 4
 
2.2%
Other values (73) 120
65.9%
Decimal Number
ValueCountFrequency (%)
8 2
40.0%
1 2
40.0%
5 1
20.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 182
95.8%
Common 8
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 10
 
5.5%
구 9
 
4.9%
천 8
 
4.4%
사 7
 
3.8%
지 5
 
2.7%
일 5
 
2.7%
동 5
 
2.7%
당 5
 
2.7%
화 4
 
2.2%
본 4
 
2.2%
Other values (73) 120
65.9%
Common
ValueCountFrequency (%)
8 2
25.0%
1 2
25.0%
· 1
12.5%
( 1
12.5%
) 1
12.5%
5 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 182
95.8%
ASCII 7
 
3.7%
None 1
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 10
 
5.5%
구 9
 
4.9%
천 8
 
4.4%
사 7
 
3.8%
지 5
 
2.7%
일 5
 
2.7%
동 5
 
2.7%
당 5
 
2.7%
화 4
 
2.2%
본 4
 
2.2%
Other values (73) 120
65.9%
ASCII
ValueCountFrequency (%)
8 2
28.6%
1 2
28.6%
( 1
14.3%
) 1
14.3%
5 1
14.3%
None
ValueCountFrequency (%)
· 1
100.0%

지정번호
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T15:25:42.626209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.64
Min length7

Characters and Unicode

Total characters241
Distinct characters29
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

Unique25 ?
Unique (%)100.0%

Sample

1st row등록문화재 제246호
2nd row등록문화재 제248호
3rd row등록문화재 제249호
4th row등록문화재 제427호
5th row등록문화재 제567호
ValueCountFrequency (%)
유형문화재 11
22.0%
등록문화재 6
 
12.0%
기념물 4
 
8.0%
제51호 2
 
4.0%
문화재자료 2
 
4.0%
민속자료 1
 
2.0%
제24호 1
 
2.0%
제16호 1
 
2.0%
제55호 1
 
2.0%
제287호 1
 
2.0%
Other values (20) 20
40.0%
2023-12-12T15:25:42.985130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
 
10.4%
제 25
 
10.4%
호 25
 
10.4%
문 19
 
7.9%
화 19
 
7.9%
재 19
 
7.9%
형 11
 
4.6%
유 11
 
4.6%
5 8
 
3.3%
1 8
 
3.3%
Other values (19) 71
29.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 163
67.6%
Decimal Number 53
 
22.0%
Space Separator 25
 
10.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 25
15.3%
호 25
15.3%
문 19
11.7%
화 19
11.7%
재 19
11.7%
형 11
6.7%
유 11
6.7%
록 6
 
3.7%
등 6
 
3.7%
기 4
 
2.5%
Other values (8) 18
11.0%
Decimal Number
ValueCountFrequency (%)
5 8
15.1%
1 8
15.1%
2 7
13.2%
4 7
13.2%
7 6
11.3%
6 6
11.3%
9 5
9.4%
8 3
 
5.7%
0 2
 
3.8%
3 1
 
1.9%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 163
67.6%
Common 78
32.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 25
15.3%
호 25
15.3%
문 19
11.7%
화 19
11.7%
재 19
11.7%
형 11
6.7%
유 11
6.7%
록 6
 
3.7%
등 6
 
3.7%
기 4
 
2.5%
Other values (8) 18
11.0%
Common
ValueCountFrequency (%)
25
32.1%
5 8
 
10.3%
1 8
 
10.3%
2 7
 
9.0%
4 7
 
9.0%
7 6
 
7.7%
6 6
 
7.7%
9 5
 
6.4%
8 3
 
3.8%
0 2
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 163
67.6%
ASCII 78
32.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
32.1%
5 8
 
10.3%
1 8
 
10.3%
2 7
 
9.0%
4 7
 
9.0%
7 6
 
7.7%
6 6
 
7.7%
9 5
 
6.4%
8 3
 
3.8%
0 2
 
2.6%
Hangul
ValueCountFrequency (%)
제 25
15.3%
호 25
15.3%
문 19
11.7%
화 19
11.7%
재 19
11.7%
형 11
6.7%
유 11
6.7%
록 6
 
3.7%
등 6
 
3.7%
기 4
 
2.5%
Other values (8) 18
11.0%

소재지
Text

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T15:25:43.302170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length18.64
Min length8

Characters and Unicode

Total characters466
Distinct characters64
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

Unique21 ?
Unique (%)84.0%

Sample

1st row차이나타운로 56-14 (선린동 38-1/2)
2nd row제물량로218번길 3 (해안동1가 9)
3rd row신포로27번길 80 (관동1가 9)
4th row자유공원로 58-9 (전동 26)
5th row신포로27번길 96-2 (관동1가 17)
ValueCountFrequency (%)
운남동 4
 
4.2%
운남로 3
 
3.2%
신포로23번길 3
 
3.2%
199-1 3
 
3.2%
관동1가 3
 
3.2%
신포로27번길 2
 
2.1%
9 2
 
2.1%
중앙동2가 2
 
2.1%
3 2
 
2.1%
능인사 2
 
2.1%
Other values (64) 69
72.6%
2023-12-12T15:25:43.807595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
70
 
15.0%
1 35
 
7.5%
동 25
 
5.4%
2 25
 
5.4%
로 20
 
4.3%
( 20
 
4.3%
) 20
 
4.3%
9 19
 
4.1%
- 19
 
4.1%
3 19
 
4.1%
Other values (54) 194
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 184
39.5%
Decimal Number 150
32.2%
Space Separator 70
 
15.0%
Open Punctuation 20
 
4.3%
Close Punctuation 20
 
4.3%
Dash Punctuation 19
 
4.1%
Other Punctuation 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 25
 
13.6%
로 20
 
10.9%
가 11
 
6.0%
길 11
 
6.0%
번 11
 
6.0%
운 10
 
5.4%
남 9
 
4.9%
신 5
 
2.7%
중 5
 
2.7%
포 5
 
2.7%
Other values (38) 72
39.1%
Decimal Number
ValueCountFrequency (%)
1 35
23.3%
2 25
16.7%
9 19
12.7%
3 19
12.7%
7 11
 
7.3%
6 10
 
6.7%
8 10
 
6.7%
4 8
 
5.3%
5 7
 
4.7%
0 6
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
/ 1
33.3%
Space Separator
ValueCountFrequency (%)
70
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 282
60.5%
Hangul 184
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 25
 
13.6%
로 20
 
10.9%
가 11
 
6.0%
길 11
 
6.0%
번 11
 
6.0%
운 10
 
5.4%
남 9
 
4.9%
신 5
 
2.7%
중 5
 
2.7%
포 5
 
2.7%
Other values (38) 72
39.1%
Common
ValueCountFrequency (%)
70
24.8%
1 35
12.4%
2 25
 
8.9%
( 20
 
7.1%
) 20
 
7.1%
9 19
 
6.7%
- 19
 
6.7%
3 19
 
6.7%
7 11
 
3.9%
6 10
 
3.5%
Other values (6) 34
12.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 282
60.5%
Hangul 184
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
70
24.8%
1 35
12.4%
2 25
 
8.9%
( 20
 
7.1%
) 20
 
7.1%
9 19
 
6.7%
- 19
 
6.7%
3 19
 
6.7%
7 11
 
3.9%
6 10
 
3.5%
Other values (6) 34
12.1%
Hangul
ValueCountFrequency (%)
동 25
 
13.6%
로 20
 
10.9%
가 11
 
6.0%
길 11
 
6.0%
번 11
 
6.0%
운 10
 
5.4%
남 9
 
4.9%
신 5
 
2.7%
중 5
 
2.7%
포 5
 
2.7%
Other values (38) 72
39.1%

도로명
Text

MISSING 

Distinct17
Distinct (%)85.0%
Missing5
Missing (%)20.0%
Memory size332.0 B
2023-12-12T15:25:44.034782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length19.15
Min length17

Characters and Unicode

Total characters383
Distinct characters42
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

Unique15 ?
Unique (%)75.0%

Sample

1st row인천광역시 중구 차이나타운로 56-14
2nd row인천광역시 중구 제물량로218번길 3
3rd row인천광역시 중구 신포로27번길 80
4th row인천광역시 중구 자유공원로 58-9
5th row인천광역시 중구 신포로27번길 96-2
ValueCountFrequency (%)
인천광역시 20
24.7%
중구 20
24.7%
운남로 3
 
3.7%
199-1 3
 
3.7%
신포로23번길 3
 
3.7%
우현로62번길 2
 
2.5%
19 2
 
2.5%
신포로27번길 2
 
2.5%
우현로 1
 
1.2%
21-32 1
 
1.2%
Other values (24) 24
29.6%
2023-12-12T15:25:44.410100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
61
15.9%
중 22
 
5.7%
인 21
 
5.5%
광 20
 
5.2%
역 20
 
5.2%
시 20
 
5.2%
구 20
 
5.2%
천 20
 
5.2%
로 20
 
5.2%
1 17
 
4.4%
Other values (32) 142
37.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 232
60.6%
Decimal Number 80
 
20.9%
Space Separator 61
 
15.9%
Dash Punctuation 10
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 22
9.5%
인 21
9.1%
광 20
8.6%
역 20
8.6%
시 20
8.6%
구 20
8.6%
천 20
8.6%
로 20
8.6%
번 11
 
4.7%
길 11
 
4.7%
Other values (20) 47
20.3%
Decimal Number
ValueCountFrequency (%)
1 17
21.2%
2 14
17.5%
9 14
17.5%
3 9
11.2%
5 6
 
7.5%
8 6
 
7.5%
6 5
 
6.2%
7 4
 
5.0%
0 3
 
3.8%
4 2
 
2.5%
Space Separator
ValueCountFrequency (%)
61
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 232
60.6%
Common 151
39.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 22
9.5%
인 21
9.1%
광 20
8.6%
역 20
8.6%
시 20
8.6%
구 20
8.6%
천 20
8.6%
로 20
8.6%
번 11
 
4.7%
길 11
 
4.7%
Other values (20) 47
20.3%
Common
ValueCountFrequency (%)
61
40.4%
1 17
 
11.3%
2 14
 
9.3%
9 14
 
9.3%
- 10
 
6.6%
3 9
 
6.0%
5 6
 
4.0%
8 6
 
4.0%
6 5
 
3.3%
7 4
 
2.6%
Other values (2) 5
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 232
60.6%
ASCII 151
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
61
40.4%
1 17
 
11.3%
2 14
 
9.3%
9 14
 
9.3%
- 10
 
6.6%
3 9
 
6.0%
5 6
 
4.0%
8 6
 
4.0%
6 5
 
3.3%
7 4
 
2.6%
Other values (2) 5
 
3.3%
Hangul
ValueCountFrequency (%)
중 22
9.5%
인 21
9.1%
광 20
8.6%
역 20
8.6%
시 20
8.6%
구 20
8.6%
천 20
8.6%
로 20
8.6%
번 11
 
4.7%
길 11
 
4.7%
Other values (20) 47
20.3%

지번
Text

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T15:25:44.657264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length16.24
Min length12

Characters and Unicode

Total characters406
Distinct characters43
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)84.0%

Sample

1st row인천광역시 중구 선린동 38-1/2
2nd row인천광역시 중구 해안동1가 9
3rd row인천광역시 중구 관동1가 9
4th row인천광역시 중구 전동 26
5th row인천광역시 중구 관동1가 17
ValueCountFrequency (%)
인천광역시 25
25.3%
중구 25
25.3%
운남동 4
 
4.0%
관동1가 3
 
3.0%
9 2
 
2.0%
중앙동2가 2
 
2.0%
237 2
 
2.0%
용동 2
 
2.0%
운서동 1
 
1.0%
내동 1
 
1.0%
Other values (32) 32
32.3%
2023-12-12T15:25:45.037555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
74
18.2%
중 28
 
6.9%
인 26
 
6.4%
동 25
 
6.2%
광 25
 
6.2%
역 25
 
6.2%
시 25
 
6.2%
구 25
 
6.2%
천 25
 
6.2%
1 18
 
4.4%
Other values (33) 110
27.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 252
62.1%
Space Separator 74
 
18.2%
Decimal Number 70
 
17.2%
Dash Punctuation 9
 
2.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 28
11.1%
인 26
10.3%
동 25
9.9%
광 25
9.9%
역 25
9.9%
시 25
9.9%
구 25
9.9%
천 25
9.9%
가 11
 
4.4%
남 5
 
2.0%
Other values (20) 32
12.7%
Decimal Number
ValueCountFrequency (%)
1 18
25.7%
2 11
15.7%
3 10
14.3%
7 7
 
10.0%
4 6
 
8.6%
9 5
 
7.1%
6 5
 
7.1%
8 4
 
5.7%
0 3
 
4.3%
5 1
 
1.4%
Space Separator
ValueCountFrequency (%)
74
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 252
62.1%
Common 154
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 28
11.1%
인 26
10.3%
동 25
9.9%
광 25
9.9%
역 25
9.9%
시 25
9.9%
구 25
9.9%
천 25
9.9%
가 11
 
4.4%
남 5
 
2.0%
Other values (20) 32
12.7%
Common
ValueCountFrequency (%)
74
48.1%
1 18
 
11.7%
2 11
 
7.1%
3 10
 
6.5%
- 9
 
5.8%
7 7
 
4.5%
4 6
 
3.9%
9 5
 
3.2%
6 5
 
3.2%
8 4
 
2.6%
Other values (3) 5
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 252
62.1%
ASCII 154
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
74
48.1%
1 18
 
11.7%
2 11
 
7.1%
3 10
 
6.5%
- 9
 
5.8%
7 7
 
4.5%
4 6
 
3.9%
9 5
 
3.2%
6 5
 
3.2%
8 4
 
2.6%
Other values (3) 5
 
3.2%
Hangul
ValueCountFrequency (%)
중 28
11.1%
인 26
10.3%
동 25
9.9%
광 25
9.9%
역 25
9.9%
시 25
9.9%
구 25
9.9%
천 25
9.9%
가 11
 
4.4%
남 5
 
2.0%
Other values (20) 32
12.7%

건립연도
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)87.0%
Missing2
Missing (%)8.0%
Infinite0
Infinite (%)0.0%
Mean1853.7391
Minimum690
Maximum1956
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T15:25:45.158230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum690
5-th percentile1856.4
Q11886.5
median1903
Q31927.5
95-th percentile1938.6
Maximum1956
Range1266
Interquartile range (IQR)41

Descriptive statistics

Standard deviation254.86738
Coefficient of variation (CV)0.13748827
Kurtosis22.51638
Mean1853.7391
Median Absolute Deviation (MAD)20
Skewness-4.7231281
Sum42636
Variance64957.383
MonotonicityNot monotonic
2023-12-12T15:25:45.274171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1890 2
 
8.0%
1883 2
 
8.0%
1933 2
 
8.0%
1932 1
 
4.0%
1895 1
 
4.0%
1878 1
 
4.0%
690 1
 
4.0%
1880 1
 
4.0%
1922 1
 
4.0%
1956 1
 
4.0%
Other values (10) 10
40.0%
(Missing) 2
 
8.0%
ValueCountFrequency (%)
690 1
4.0%
1854 1
4.0%
1878 1
4.0%
1880 1
4.0%
1883 2
8.0%
1890 2
8.0%
1892 1
4.0%
1895 1
4.0%
1901 1
4.0%
1903 1
4.0%
ValueCountFrequency (%)
1956 1
4.0%
1939 1
4.0%
1935 1
4.0%
1933 2
8.0%
1932 1
4.0%
1923 1
4.0%
1922 1
4.0%
1911 1
4.0%
1908 1
4.0%
1905 1
4.0%

지정연도
Date

Distinct15
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
Minimum1981-09-25 00:00:00
Maximum2016-02-24 00:00:00
2023-12-12T15:25:45.392430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:45.516208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)

문화재사진명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T15:25:45.735849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length16.56
Min length12

Characters and Unicode

Total characters414
Distinct characters100
Distinct categories7 ?
Distinct scripts3 ?
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 row0002_인천선린동공화춘.png
2nd row0003_구일본우선주식회사.png
3rd row0004_구인천부청사.png
4th row0005_제물포고등학교강당.png
5th row0006_인천구대화조사무소(카페팟알).png
ValueCountFrequency (%)
0002_인천선린동공화춘.png 1
 
4.0%
0015_구인천일본18은행지점.png 1
 
4.0%
0024_능인교당현왕탱화.png 1
 
4.0%
0023_조병수가옥.png 1
 
4.0%
0022_삼목도선사주거지.png 1
 
4.0%
0001_답동성당.png 1
 
4.0%
0021_청일조계지경계계단.png 1
 
4.0%
0020_양주성금속비.png 1
 
4.0%
0019_용궁사느티나무.png 1
 
4.0%
0018_용궁사수월관음도.png 1
 
4.0%
Other values (15) 15
60.0%
2023-12-12T15:25:46.505940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 61
 
14.7%
. 25
 
6.0%
_ 25
 
6.0%
g 25
 
6.0%
n 25
 
6.0%
p 25
 
6.0%
1 15
 
3.6%
인 10
 
2.4%
구 9
 
2.2%
2 9
 
2.2%
Other values (90) 185
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 182
44.0%
Decimal Number 105
25.4%
Lowercase Letter 75
18.1%
Other Punctuation 25
 
6.0%
Connector Punctuation 25
 
6.0%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 10
 
5.5%
구 9
 
4.9%
천 8
 
4.4%
사 7
 
3.8%
동 5
 
2.7%
당 5
 
2.7%
지 5
 
2.7%
일 5
 
2.7%
용 4
 
2.2%
화 4
 
2.2%
Other values (73) 120
65.9%
Decimal Number
ValueCountFrequency (%)
0 61
58.1%
1 15
 
14.3%
2 9
 
8.6%
5 4
 
3.8%
8 4
 
3.8%
3 3
 
2.9%
4 3
 
2.9%
9 2
 
1.9%
7 2
 
1.9%
6 2
 
1.9%
Lowercase Letter
ValueCountFrequency (%)
g 25
33.3%
n 25
33.3%
p 25
33.3%
Other Punctuation
ValueCountFrequency (%)
. 25
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 182
44.0%
Common 157
37.9%
Latin 75
18.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 10
 
5.5%
구 9
 
4.9%
천 8
 
4.4%
사 7
 
3.8%
동 5
 
2.7%
당 5
 
2.7%
지 5
 
2.7%
일 5
 
2.7%
용 4
 
2.2%
화 4
 
2.2%
Other values (73) 120
65.9%
Common
ValueCountFrequency (%)
0 61
38.9%
. 25
15.9%
_ 25
15.9%
1 15
 
9.6%
2 9
 
5.7%
5 4
 
2.5%
8 4
 
2.5%
3 3
 
1.9%
4 3
 
1.9%
9 2
 
1.3%
Other values (4) 6
 
3.8%
Latin
ValueCountFrequency (%)
g 25
33.3%
n 25
33.3%
p 25
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 232
56.0%
Hangul 182
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 61
26.3%
. 25
10.8%
_ 25
10.8%
g 25
10.8%
n 25
10.8%
p 25
10.8%
1 15
 
6.5%
2 9
 
3.9%
5 4
 
1.7%
8 4
 
1.7%
Other values (7) 14
 
6.0%
Hangul
ValueCountFrequency (%)
인 10
 
5.5%
구 9
 
4.9%
천 8
 
4.4%
사 7
 
3.8%
동 5
 
2.7%
당 5
 
2.7%
지 5
 
2.7%
일 5
 
2.7%
용 4
 
2.2%
화 4
 
2.2%
Other values (73) 120
65.9%

영어 상점명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T15:25:46.812556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length35
Mean length27.76
Min length11

Characters and Unicode

Total characters694
Distinct characters52
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
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 rowIncheon Seonlindong Gonghwachun
2nd rowOld Japan Useon corporation
3rd rowOld Incheon buGovernment Office
4th rowJemulpo High School Auditorium
5th rowIncheon Gu daeHwajo Office(cafe pot-R)
ValueCountFrequency (%)
incheon 9
 
9.7%
old 5
 
5.4%
japan 4
 
4.3%
yonggungsa 3
 
3.2%
branch 3
 
3.2%
jemulpo 2
 
2.2%
taenghwa 2
 
2.2%
site 2
 
2.2%
church 2
 
2.2%
neungingyodang 2
 
2.2%
Other values (58) 59
63.4%
2023-12-12T15:25:47.279540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 75
 
10.8%
68
 
9.8%
o 61
 
8.8%
e 54
 
7.8%
a 46
 
6.6%
g 40
 
5.8%
h 30
 
4.3%
u 30
 
4.3%
c 23
 
3.3%
i 23
 
3.3%
Other values (42) 244
35.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 526
75.8%
Uppercase Letter 91
 
13.1%
Space Separator 68
 
9.8%
Decimal Number 4
 
0.6%
Dash Punctuation 2
 
0.3%
Other Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 75
14.3%
o 61
11.6%
e 54
10.3%
a 46
 
8.7%
g 40
 
7.6%
h 30
 
5.7%
u 30
 
5.7%
c 23
 
4.4%
i 23
 
4.4%
l 22
 
4.2%
Other values (14) 122
23.2%
Uppercase Letter
ValueCountFrequency (%)
J 11
12.1%
S 10
11.0%
I 9
9.9%
G 9
9.9%
O 8
8.8%
D 8
8.8%
Y 6
 
6.6%
C 5
 
5.5%
H 4
 
4.4%
N 4
 
4.4%
Other values (10) 17
18.7%
Decimal Number
ValueCountFrequency (%)
8 2
50.0%
5 1
25.0%
1 1
25.0%
Space Separator
ValueCountFrequency (%)
68
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 617
88.9%
Common 77
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 75
 
12.2%
o 61
 
9.9%
e 54
 
8.8%
a 46
 
7.5%
g 40
 
6.5%
h 30
 
4.9%
u 30
 
4.9%
c 23
 
3.7%
i 23
 
3.7%
l 22
 
3.6%
Other values (34) 213
34.5%
Common
ValueCountFrequency (%)
68
88.3%
8 2
 
2.6%
- 2
 
2.6%
5 1
 
1.3%
, 1
 
1.3%
) 1
 
1.3%
1 1
 
1.3%
( 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 694
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 75
 
10.8%
68
 
9.8%
o 61
 
8.8%
e 54
 
7.8%
a 46
 
6.6%
g 40
 
5.8%
h 30
 
4.3%
u 30
 
4.3%
c 23
 
3.3%
i 23
 
3.3%
Other values (42) 244
35.2%

일본어 상점명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T15:25:47.539341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length9
Mean length7.68
Min length3

Characters and Unicode

Total characters192
Distinct characters113
Distinct categories5 ?
Distinct scripts4 ?
Distinct blocks6 ?
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 row仁川善隣洞共和春
2nd row日本ウソン株式社
3rd row仁川(インチョン)政府
4th row物浦高等校講堂
5th row仁川大和組事務所(カペパッアル)
ValueCountFrequency (%)
仁川善隣洞共和春 1
 
4.0%
仁川(インチョン)日本18銀行支店 1
 
4.0%
能仁敎堂現王幀 1
 
4.0%
ゾビョンス家屋 1
 
4.0%
サムモクドソンサ住居址 1
 
4.0%
塔洞聖堂 1
 
4.0%
·日租界地境界階段 1
 
4.0%
良柱星金碑 1
 
4.0%
龍宮寺ケヤキ 1
 
4.0%
龍宮寺水月音 1
 
4.0%
Other values (15) 15
60.0%
2023-12-12T15:25:47.956218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
仁 9
 
4.7%
ン 9
 
4.7%
川 7
 
3.6%
日 5
 
2.6%
堂 5
 
2.6%
( 4
 
2.1%
) 4
 
2.1%
本 4
 
2.1%
洞 4
 
2.1%
ョ 4
 
2.1%
Other values (103) 137
71.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 178
92.7%
Decimal Number 5
 
2.6%
Open Punctuation 4
 
2.1%
Close Punctuation 4
 
2.1%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
仁 9
 
5.1%
ン 9
 
5.1%
川 7
 
3.9%
日 5
 
2.8%
堂 5
 
2.8%
本 4
 
2.2%
洞 4
 
2.2%
ョ 4
 
2.2%
店 3
 
1.7%
チ 3
 
1.7%
Other values (97) 125
70.2%
Decimal Number
ValueCountFrequency (%)
8 2
40.0%
1 2
40.0%
5 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 133
69.3%
Katakana 44
 
22.9%
Common 14
 
7.3%
Hiragana 1
 
0.5%

Most frequent character per script

Han
ValueCountFrequency (%)
仁 9
 
6.8%
川 7
 
5.3%
日 5
 
3.8%
堂 5
 
3.8%
本 4
 
3.0%
洞 4
 
3.0%
店 3
 
2.3%
支 3
 
2.3%
行 3
 
2.3%
龍 3
 
2.3%
Other values (72) 87
65.4%
Katakana
ValueCountFrequency (%)
ン 9
20.5%
ョ 4
 
9.1%
チ 3
 
6.8%
イ 3
 
6.8%
ソ 2
 
4.5%
ル 2
 
4.5%
サ 2
 
4.5%
ム 2
 
4.5%
ク 2
 
4.5%
キ 1
 
2.3%
Other values (14) 14
31.8%
Common
ValueCountFrequency (%)
( 4
28.6%
) 4
28.6%
8 2
14.3%
1 2
14.3%
· 1
 
7.1%
5 1
 
7.1%
Hiragana
ValueCountFrequency (%)
と 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 130
67.7%
Katakana 44
 
22.9%
ASCII 13
 
6.8%
CJK Compat Ideographs 3
 
1.6%
None 1
 
0.5%
Hiragana 1
 
0.5%

Most frequent character per block

CJK
ValueCountFrequency (%)
仁 9
 
6.9%
川 7
 
5.4%
日 5
 
3.8%
堂 5
 
3.8%
本 4
 
3.1%
洞 4
 
3.1%
店 3
 
2.3%
支 3
 
2.3%
行 3
 
2.3%
龍 3
 
2.3%
Other values (69) 84
64.6%
Katakana
ValueCountFrequency (%)
ン 9
20.5%
ョ 4
 
9.1%
チ 3
 
6.8%
イ 3
 
6.8%
ソ 2
 
4.5%
ル 2
 
4.5%
サ 2
 
4.5%
ム 2
 
4.5%
ク 2
 
4.5%
キ 1
 
2.3%
Other values (14) 14
31.8%
ASCII
ValueCountFrequency (%)
( 4
30.8%
) 4
30.8%
8 2
15.4%
1 2
15.4%
5 1
 
7.7%
CJK Compat Ideographs
ValueCountFrequency (%)
良 1
33.3%
龍 1
33.3%
樂 1
33.3%
None
ValueCountFrequency (%)
· 1
100.0%
Hiragana
ValueCountFrequency (%)
と 1
100.0%

중국어 상점명
Text

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T15:25:48.157559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length8
Mean length5.4
Min length1

Characters and Unicode

Total characters135
Distinct characters84
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
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 row仁川善洞共和春
2nd row日本首先株式公司
3rd row仁川府舍
4th row物浦高中堂
5th row仁川大和事所(cafe pot-R)
ValueCountFrequency (%)
寺 2
 
7.7%
虹霓 1
 
3.8%
仁川日本18行支店 1
 
3.8%
能仁敎堂王 1
 
3.8%
炳秀家屋 1
 
3.8%
三木先史居住址 1
 
3.8%
仁川畓洞堂 1
 
3.8%
日租界地分界石 1
 
3.8%
良柱星金碑 1
 
3.8%
寺水月音 1
 
3.8%
Other values (15) 15
57.7%
2023-12-12T15:25:48.521006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
仁 12
 
8.9%
川 10
 
7.4%
日 5
 
3.7%
堂 4
 
3.0%
洞 4
 
3.0%
本 4
 
3.0%
行 3
 
2.2%
支 3
 
2.2%
店 3
 
2.2%
寺 3
 
2.2%
Other values (74) 84
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 118
87.4%
Lowercase Letter 7
 
5.2%
Decimal Number 5
 
3.7%
Space Separator 1
 
0.7%
Open Punctuation 1
 
0.7%
Dash Punctuation 1
 
0.7%
Uppercase Letter 1
 
0.7%
Close Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
仁 12
 
10.2%
川 10
 
8.5%
日 5
 
4.2%
堂 4
 
3.4%
洞 4
 
3.4%
本 4
 
3.4%
行 3
 
2.5%
支 3
 
2.5%
店 3
 
2.5%
寺 3
 
2.5%
Other values (59) 67
56.8%
Lowercase Letter
ValueCountFrequency (%)
c 1
14.3%
a 1
14.3%
f 1
14.3%
e 1
14.3%
p 1
14.3%
o 1
14.3%
t 1
14.3%
Decimal Number
ValueCountFrequency (%)
8 2
40.0%
1 2
40.0%
5 1
20.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 118
87.4%
Common 9
 
6.7%
Latin 8
 
5.9%

Most frequent character per script

Han
ValueCountFrequency (%)
仁 12
 
10.2%
川 10
 
8.5%
日 5
 
4.2%
堂 4
 
3.4%
洞 4
 
3.4%
本 4
 
3.4%
行 3
 
2.5%
支 3
 
2.5%
店 3
 
2.5%
寺 3
 
2.5%
Other values (59) 67
56.8%
Latin
ValueCountFrequency (%)
c 1
12.5%
a 1
12.5%
f 1
12.5%
e 1
12.5%
p 1
12.5%
o 1
12.5%
t 1
12.5%
R 1
12.5%
Common
ValueCountFrequency (%)
8 2
22.2%
1 2
22.2%
5 1
11.1%
1
11.1%
( 1
11.1%
- 1
11.1%
) 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
CJK 116
85.9%
ASCII 17
 
12.6%
CJK Compat Ideographs 2
 
1.5%

Most frequent character per block

CJK
ValueCountFrequency (%)
仁 12
 
10.3%
川 10
 
8.6%
日 5
 
4.3%
堂 4
 
3.4%
洞 4
 
3.4%
本 4
 
3.4%
行 3
 
2.6%
支 3
 
2.6%
店 3
 
2.6%
寺 3
 
2.6%
Other values (57) 65
56.0%
ASCII
ValueCountFrequency (%)
8 2
 
11.8%
1 2
 
11.8%
5 1
 
5.9%
1
 
5.9%
( 1
 
5.9%
c 1
 
5.9%
a 1
 
5.9%
f 1
 
5.9%
e 1
 
5.9%
p 1
 
5.9%
Other values (5) 5
29.4%
CJK Compat Ideographs
ValueCountFrequency (%)
良 1
50.0%
金 1
50.0%

Interactions

2023-12-12T15:25:41.159456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:41.019654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:41.228051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:41.084472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:25:48.637308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호문화재명지정번호소재지도로명지번건립연도지정연도문화재사진명영어 상점명일본어 상점명중국어 상점명
일련번호1.0001.0001.0000.8200.7470.820NaN0.9211.0001.0001.0000.914
문화재명1.0001.0001.0001.0001.0001.000NaN1.0001.0001.0001.0001.000
지정번호1.0001.0001.0001.0001.0001.000NaN1.0001.0001.0001.0001.000
소재지0.8201.0001.0001.0001.0001.000NaN0.9621.0001.0001.0000.977
도로명0.7471.0001.0001.0001.0001.000NaN0.9441.0001.0001.0001.000
지번0.8201.0001.0001.0001.0001.000NaN0.9621.0001.0001.0000.977
건립연도NaNNaNNaNNaNNaNNaN1.000NaNNaNNaNNaNNaN
지정연도0.9211.0001.0000.9620.9440.962NaN1.0001.0001.0001.0001.000
문화재사진명1.0001.0001.0001.0001.0001.000NaN1.0001.0001.0001.0001.000
영어 상점명1.0001.0001.0001.0001.0001.000NaN1.0001.0001.0001.0001.000
일본어 상점명1.0001.0001.0001.0001.0001.000NaN1.0001.0001.0001.0001.000
중국어 상점명0.9141.0001.0000.9771.0000.977NaN1.0001.0001.0001.0001.000
2023-12-12T15:25:48.768444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호건립연도
일련번호1.000-0.379
건립연도-0.3791.000

Missing values

2023-12-12T15:25:41.324018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:25:41.457283image/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.
2023-12-12T15:25:41.543586image/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

일련번호문화재명지정번호소재지도로명지번건립연도지정연도문화재사진명영어 상점명일본어 상점명중국어 상점명
01인천선린동공화춘등록문화재 제246호차이나타운로 56-14 (선린동 38-1/2)인천광역시 중구 차이나타운로 56-14인천광역시 중구 선린동 38-1/219052006-04-140002_인천선린동공화춘.pngIncheon Seonlindong Gonghwachun仁川善隣洞共和春仁川善洞共和春
12구일본우선주식회사등록문화재 제248호제물량로218번길 3 (해안동1가 9)인천광역시 중구 제물량로218번길 3인천광역시 중구 해안동1가 919332006-04-140003_구일본우선주식회사.pngOld Japan Useon corporation日本ウソン株式社日本首先株式公司
23구인천부청사등록문화재 제249호신포로27번길 80 (관동1가 9)인천광역시 중구 신포로27번길 80인천광역시 중구 관동1가 919332006-04-140004_구인천부청사.pngOld Incheon buGovernment Office仁川(インチョン)政府仁川府舍
34제물포고등학교강당등록문화재 제427호자유공원로 58-9 (전동 26)인천광역시 중구 자유공원로 58-9인천광역시 중구 전동 2619352008-10-270005_제물포고등학교강당.pngJemulpo High School Auditorium物浦高等校講堂物浦高中堂
45인천구대화조사무소(카페팟알)등록문화재 제567호신포로27번길 96-2 (관동1가 17)인천광역시 중구 신포로27번길 96-2인천광역시 중구 관동1가 1718922013-10-290006_인천구대화조사무소(카페팟알).pngIncheon Gu daeHwajo Office(cafe pot-R)仁川大和組事務所(カペパッアル)仁川大和事所(cafe pot-R)
56인천세관구창고와부속동등록문화재 제569호인중로 191-9 (항동7가 1-47)인천광역시 중구 인중로 191-9인천광역시 중구 항동7가 1-4719112013-08-290007_인천세관구창고와부속동.pngIncheon Customs warehouse , affiliate仁川倉庫と付棟仁川海附
67구인천일본제1은행지점유형문화재 제7호신포로23번길 89 (중앙동1가 9-2)인천광역시 중구 신포로23번길 89인천광역시 중구 중앙동1가 9-218831982-03-020008_구인천일본제1은행지점.pngOld Incheon Japan the first bank branch日本第1銀行支店仁川日本第1行支店
78인천우체국유형문화재 제8호제물량로 183 (항동6가 1)인천광역시 중구 제물량로 183인천광역시 중구 항동6가 119231982-03-020009_인천우체국.pngPost Office仁川郵便局仁川局
89용궁사유형문화재 제15호운남로 199-1 (운남동 667)인천광역시 중구 운남로 199-1인천광역시 중구 운남동 66718541990-11-090010_용궁사.pngYonggungsa Temple龍宮寺寺
910구제물포구락부유형문화재 제17호자유공원남로 25 (송학동 1가 11)인천광역시 중구 자유공원남로 25인천광역시 중구 송학동 1가 1119011993-07-060011_구제물포구락부.pngJemulpo Gulagbu Site物浦俱樂部物浦俱部
일련번호문화재명지정번호소재지도로명지번건립연도지정연도문화재사진명영어 상점명일본어 상점명중국어 상점명
1516능인교당신중탱화유형문화재 제61호우현로62번길 19 (용동 237 능인사)인천광역시 중구 우현로62번길 19인천광역시 중구 용동 23719222009-03-020017_능인교당신중탱화.pngNeunginGyoDang Sinjung Taenghwa能仁敎堂神衆幀能仁敎堂神
1617용궁사수월관음도유형문화재 제76호운남로 199-1 (운남동, 용궁사)인천광역시 중구 운남로 199-1인천광역시 중구 운남동18802016-02-240018_용궁사수월관음도.pngYonggungSa SUWol GwaneumDo龍宮寺水月音寺水月音
1718용궁사느티나무기념물 제9호운남로 199-1 (운남동, 용궁사)인천광역시 중구 운남로 199-1인천광역시 중구 운남동6901990-11-090019_용궁사느티나무.pngYonggungsa zelkova龍宮寺ケヤキ寺
1819양주성금속비기념물 제13호운중로 13-35 (운남동 444-3)인천광역시 중구 운중로 13-35인천광역시 중구 운남동 444-318781993-07-060020_양주성금속비.pngYeongjongcheomJeolje Sayang Juseong Metal Bi良柱星金碑良柱星金碑
1920청·일조계지경계계단기념물 제51호관동1가 24일원<NA>인천광역시 중구 관동1가 24<NA>2002-12-230021_청일조계지경계계단.pngCheong-il Jogye Ji Gyeonggye Gyedan·日租界地境界階段日租界地分界石
2021답동성당사적 제287호우현로 50번길 2 (답동 3-3)인천광역시 중구 우현로 50번길 2인천광역시 중구 답동 3-318951981-09-250001_답동성당.pngIncheon Dapdong Catholic Church塔洞聖堂仁川畓洞堂
2122삼목도선사주거지기념물 제55호운서동 1830-1 외<NA>인천광역시 중구 운서동 1830-1<NA>2006-09-110022_삼목도선사주거지.pngSammok Do Seonsa Dwelling Siteサムモクドソンサ住居址三木先史居住址
2223조병수가옥문화재자료 제16호용유로380번길 21 (남북동 868)인천광역시 중구 용유로380번길 21인천광역시 중구 남북동 86818901997-07-140023_조병수가옥.pngJungguNambuk Dongjo Byeongsu Houseゾビョンス家屋炳秀家屋
2324능인교당현왕탱화문화재자료 제24호우현로62번길 19 (용동 237 능인사)인천광역시 중구 우현로62번길 19인천광역시 중구 용동 23719322009-03-020024_능인교당현왕탱화.pngNeunginGyoDang hyeonWang Taenghwa能仁敎堂現王幀能仁敎堂王
2425용동큰우물민속자료 제2호인현동 90-13<NA>인천광역시 중구 인현동 90-1318831996-06-120025_용동큰우물.pngYongdong Keunumul龍洞クヌムル洞大井