Overview

Dataset statistics

Number of variables29
Number of observations100
Missing cells1225
Missing cells (%)42.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.5 KiB
Average record size in memory240.3 B

Variable types

Numeric3
Text14
Unsupported4
Categorical7
DateTime1

Dataset

Description서울틀별시 중구 스토리텔링 정보를 영어,일본어,중국어_간체,중국어_번체,한국어로 제공
Author서울특별시 중구
URLhttps://www.data.go.kr/data/15045492/fileData.do

Alerts

제공기관 has constant value ""Constant
언어유형 has constant value ""Constant
제작일 has constant value ""Constant
유형 has constant value ""Constant
형식 has constant value ""Constant
안내서비스 has constant value ""Constant
이용요금 is highly imbalanced (71.9%)Imbalance
주차 is highly imbalanced (50.0%)Imbalance
관련항목 has 100 (100.0%) missing valuesMissing
연계자원 has 15 (15.0%) missing valuesMissing
이명칭 has 95 (95.0%) missing valuesMissing
시대분류 has 100 (100.0%) missing valuesMissing
주제분류 has 100 (100.0%) missing valuesMissing
지번주소 has 100 (100.0%) missing valuesMissing
전화번호 has 68 (68.0%) missing valuesMissing
지정현황 has 80 (80.0%) missing valuesMissing
휴무일 has 86 (86.0%) missing valuesMissing
이용시간 has 91 (91.0%) missing valuesMissing
장애인 편의시설 has 97 (97.0%) missing valuesMissing
체험안내 has 97 (97.0%) missing valuesMissing
안내서비스 has 99 (99.0%) missing valuesMissing
예약 has 97 (97.0%) missing valuesMissing
상세고유순번 has unique valuesUnique
관리번호 has unique valuesUnique
명칭 has unique valuesUnique
개요 has unique valuesUnique
관련항목 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시대분류 is an unsupported type, check if it needs cleaning or further analysisUnsupported
주제분류 is an unsupported type, check if it needs cleaning or further analysisUnsupported
지번주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 11:56:55.985929
Analysis finished2023-12-12 11:56:57.005883
Duration1.02 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상세고유순번
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-12T20:56:57.122032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median50.5
Q375.25
95-th percentile95.05
Maximum100
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityNot monotonic
2023-12-12T20:56:57.290011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
19 1
 
1.0%
29 1
 
1.0%
28 1
 
1.0%
27 1
 
1.0%
26 1
 
1.0%
25 1
 
1.0%
24 1
 
1.0%
23 1
 
1.0%
22 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

관리번호
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-12T20:56:57.662578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1000
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowJGS_000001
2nd rowJGS_000002
3rd rowJGS_000003
4th rowJGS_000004
5th rowJGS_000005
ValueCountFrequency (%)
jgs_000001 1
 
1.0%
jgs_000017 1
 
1.0%
jgs_000028 1
 
1.0%
jgs_000027 1
 
1.0%
jgs_000026 1
 
1.0%
jgs_000025 1
 
1.0%
jgs_000024 1
 
1.0%
jgs_000023 1
 
1.0%
jgs_000022 1
 
1.0%
jgs_000021 1
 
1.0%
Other values (90) 90
90.0%
2023-12-12T20:56:58.255064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 419
41.9%
J 100
 
10.0%
G 100
 
10.0%
S 100
 
10.0%
_ 100
 
10.0%
1 21
 
2.1%
4 20
 
2.0%
3 20
 
2.0%
5 20
 
2.0%
6 20
 
2.0%
Other values (4) 80
 
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 600
60.0%
Uppercase Letter 300
30.0%
Connector Punctuation 100
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 419
69.8%
1 21
 
3.5%
4 20
 
3.3%
3 20
 
3.3%
5 20
 
3.3%
6 20
 
3.3%
7 20
 
3.3%
8 20
 
3.3%
9 20
 
3.3%
2 20
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
J 100
33.3%
G 100
33.3%
S 100
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 700
70.0%
Latin 300
30.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 419
59.9%
_ 100
 
14.3%
1 21
 
3.0%
4 20
 
2.9%
3 20
 
2.9%
5 20
 
2.9%
6 20
 
2.9%
7 20
 
2.9%
8 20
 
2.9%
9 20
 
2.9%
Latin
ValueCountFrequency (%)
J 100
33.3%
G 100
33.3%
S 100
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 419
41.9%
J 100
 
10.0%
G 100
 
10.0%
S 100
 
10.0%
_ 100
 
10.0%
1 21
 
2.1%
4 20
 
2.0%
3 20
 
2.0%
5 20
 
2.0%
6 20
 
2.0%
Other values (4) 80
 
8.0%

명칭
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-12T20:56:58.655366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length22
Mean length9.96
Min length3

Characters and Unicode

Total characters996
Distinct characters237
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row덕수궁
2nd row덕수궁 중명전
3rd row환구단(원구단)
4th row구 러시아공사관
5th row정동제일교회
ValueCountFrequency (%)
8
 
4.1%
명동의 7
 
3.6%
덕수궁 4
 
2.0%
동상 4
 
2.0%
3
 
1.5%
남산 2
 
1.0%
서울 2
 
1.0%
거리 2
 
1.0%
명동 2
 
1.0%
이화여고 2
 
1.0%
Other values (161) 161
81.7%
2023-12-12T20:56:59.153406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
97
 
9.7%
36
 
3.6%
25
 
2.5%
( 20
 
2.0%
20
 
2.0%
) 20
 
2.0%
18
 
1.8%
17
 
1.7%
16
 
1.6%
16
 
1.6%
Other values (227) 711
71.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 812
81.5%
Space Separator 97
 
9.7%
Decimal Number 31
 
3.1%
Open Punctuation 20
 
2.0%
Close Punctuation 20
 
2.0%
Other Punctuation 11
 
1.1%
Math Symbol 3
 
0.3%
Uppercase Letter 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
36
 
4.4%
25
 
3.1%
20
 
2.5%
18
 
2.2%
17
 
2.1%
16
 
2.0%
16
 
2.0%
16
 
2.0%
15
 
1.8%
15
 
1.8%
Other values (210) 618
76.1%
Decimal Number
ValueCountFrequency (%)
0 9
29.0%
1 7
22.6%
9 5
16.1%
5 4
12.9%
7 2
 
6.5%
6 2
 
6.5%
3 1
 
3.2%
8 1
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 8
72.7%
' 2
 
18.2%
· 1
 
9.1%
Space Separator
ValueCountFrequency (%)
97
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 812
81.5%
Common 183
 
18.4%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
36
 
4.4%
25
 
3.1%
20
 
2.5%
18
 
2.2%
17
 
2.1%
16
 
2.0%
16
 
2.0%
16
 
2.0%
15
 
1.8%
15
 
1.8%
Other values (210) 618
76.1%
Common
ValueCountFrequency (%)
97
53.0%
( 20
 
10.9%
) 20
 
10.9%
0 9
 
4.9%
, 8
 
4.4%
1 7
 
3.8%
9 5
 
2.7%
5 4
 
2.2%
~ 3
 
1.6%
7 2
 
1.1%
Other values (6) 8
 
4.4%
Latin
ValueCountFrequency (%)
N 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 812
81.5%
ASCII 183
 
18.4%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
97
53.0%
( 20
 
10.9%
) 20
 
10.9%
0 9
 
4.9%
, 8
 
4.4%
1 7
 
3.8%
9 5
 
2.7%
5 4
 
2.2%
~ 3
 
1.6%
7 2
 
1.1%
Other values (6) 8
 
4.4%
Hangul
ValueCountFrequency (%)
36
 
4.4%
25
 
3.1%
20
 
2.5%
18
 
2.2%
17
 
2.1%
16
 
2.0%
16
 
2.0%
16
 
2.0%
15
 
1.8%
15
 
1.8%
Other values (210) 618
76.1%
None
ValueCountFrequency (%)
· 1
100.0%

관련항목
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

연계자원
Text

MISSING 

Distinct85
Distinct (%)100.0%
Missing15
Missing (%)15.0%
Memory size932.0 B
2023-12-12T20:56:59.446729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters850
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)100.0%

Sample

1st rowJGH_000370
2nd rowJGH_000350
3rd rowJGH_000335
4th rowJGH_000355
5th rowJGH_000367
ValueCountFrequency (%)
jgh_000750 1
 
1.2%
jgh_000024 1
 
1.2%
jgh_000360 1
 
1.2%
jgh_001121 1
 
1.2%
jgh_000154 1
 
1.2%
jgh_000174 1
 
1.2%
jgh_001146 1
 
1.2%
jgh_000177 1
 
1.2%
jgh_000365 1
 
1.2%
jgh_000364 1
 
1.2%
Other values (75) 75
88.2%
2023-12-12T20:56:59.846595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 276
32.5%
J 85
 
10.0%
G 85
 
10.0%
H 85
 
10.0%
_ 85
 
10.0%
1 46
 
5.4%
4 32
 
3.8%
3 30
 
3.5%
5 28
 
3.3%
7 27
 
3.2%
Other values (4) 71
 
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 510
60.0%
Uppercase Letter 255
30.0%
Connector Punctuation 85
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 276
54.1%
1 46
 
9.0%
4 32
 
6.3%
3 30
 
5.9%
5 28
 
5.5%
7 27
 
5.3%
2 26
 
5.1%
6 23
 
4.5%
8 12
 
2.4%
9 10
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
J 85
33.3%
G 85
33.3%
H 85
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 85
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 595
70.0%
Latin 255
30.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 276
46.4%
_ 85
 
14.3%
1 46
 
7.7%
4 32
 
5.4%
3 30
 
5.0%
5 28
 
4.7%
7 27
 
4.5%
2 26
 
4.4%
6 23
 
3.9%
8 12
 
2.0%
Latin
ValueCountFrequency (%)
J 85
33.3%
G 85
33.3%
H 85
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 850
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 276
32.5%
J 85
 
10.0%
G 85
 
10.0%
H 85
 
10.0%
_ 85
 
10.0%
1 46
 
5.4%
4 32
 
3.8%
3 30
 
3.5%
5 28
 
3.3%
7 27
 
3.2%
Other values (4) 71
 
8.4%

경도정보(127.XX)
Real number (ℝ)

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98703
Minimum126.97063
Maximum127.01503
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-12T20:57:00.001636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.97063
5-th percentile126.97235
Q1126.97777
median126.98452
Q3126.99397
95-th percentile127.01012
Maximum127.01503
Range0.0444
Interquartile range (IQR)0.016195

Descriptive statistics

Standard deviation0.011950712
Coefficient of variation (CV)9.410971 × 10-5
Kurtosis-0.57579731
Mean126.98703
Median Absolute Deviation (MAD)0.007955
Skewness0.70772526
Sum12698.703
Variance0.00014281953
MonotonicityNot monotonic
2023-12-12T20:57:00.157182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.98378 2
 
2.0%
126.97063 2
 
2.0%
126.97653 1
 
1.0%
126.9756 1
 
1.0%
126.97923 1
 
1.0%
126.9805 1
 
1.0%
126.99352 1
 
1.0%
126.9938 1
 
1.0%
126.99447 1
 
1.0%
126.98747 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
126.97063 2
2.0%
126.97133 1
1.0%
126.97146 1
1.0%
126.97217 1
1.0%
126.97236 1
1.0%
126.97252 1
1.0%
126.97262 1
1.0%
126.97285 1
1.0%
126.97294 1
1.0%
126.97337 1
1.0%
ValueCountFrequency (%)
127.01503 1
1.0%
127.01131 1
1.0%
127.01123 1
1.0%
127.01084 1
1.0%
127.01035 1
1.0%
127.01011 1
1.0%
127.00999 1
1.0%
127.0095 1
1.0%
127.00864 1
1.0%
127.00564 1
1.0%

위도정보(36.XXX)
Real number (ℝ)

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.561391
Minimum37.55116
Maximum37.56866
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-12T20:57:00.339394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.55116
5-th percentile37.552002
Q137.55821
median37.56265
Q337.565345
95-th percentile37.567613
Maximum37.56866
Range0.0175
Interquartile range (IQR)0.007135

Descriptive statistics

Standard deviation0.0049571847
Coefficient of variation (CV)0.00013197554
Kurtosis-0.84308738
Mean37.561391
Median Absolute Deviation (MAD)0.00357
Skewness-0.54117521
Sum3756.1391
Variance2.457368 × 10-5
MonotonicityNot monotonic
2023-12-12T20:57:00.488739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.56339 3
 
3.0%
37.5662 2
 
2.0%
37.56502 1
 
1.0%
37.56589 1
 
1.0%
37.55384 1
 
1.0%
37.5585 1
 
1.0%
37.55737 1
 
1.0%
37.55931 1
 
1.0%
37.55201 1
 
1.0%
37.55743 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
37.55116 1
1.0%
37.55139 1
1.0%
37.55159 1
1.0%
37.55164 1
1.0%
37.55184 1
1.0%
37.55201 1
1.0%
37.55235 1
1.0%
37.55254 1
1.0%
37.55284 1
1.0%
37.55347 1
1.0%
ValueCountFrequency (%)
37.56866 1
1.0%
37.56856 1
1.0%
37.56825 1
1.0%
37.56796 1
1.0%
37.56766 1
1.0%
37.56761 1
1.0%
37.56753 1
1.0%
37.56747 1
1.0%
37.56727 1
1.0%
37.56711 1
1.0%

이명칭
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing95
Missing (%)95.0%
Memory size932.0 B
2023-12-12T20:57:00.702577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length10.2
Min length6

Characters and Unicode

Total characters51
Distinct characters33
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

Unique5 ?
Unique (%)100.0%

Sample

1st row경운궁, 정릉동행궁, 서궁
2nd row한국자유총연맹
3rd row대한성공회 서울성당
4th row미소 전용관
5th row이왕가미술관, 이왕직미술관
ValueCountFrequency (%)
경운궁 1
10.0%
정릉동행궁 1
10.0%
서궁 1
10.0%
한국자유총연맹 1
10.0%
대한성공회 1
10.0%
서울성당 1
10.0%
미소 1
10.0%
전용관 1
10.0%
이왕가미술관 1
10.0%
이왕직미술관 1
10.0%
2023-12-12T20:57:01.413130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
 
9.8%
3
 
5.9%
, 3
 
5.9%
3
 
5.9%
3
 
5.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
2
 
3.9%
Other values (23) 24
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43
84.3%
Space Separator 5
 
9.8%
Other Punctuation 3
 
5.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
 
7.0%
3
 
7.0%
3
 
7.0%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
1
 
2.3%
Other values (21) 21
48.8%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43
84.3%
Common 8
 
15.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
 
7.0%
3
 
7.0%
3
 
7.0%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
1
 
2.3%
Other values (21) 21
48.8%
Common
ValueCountFrequency (%)
5
62.5%
, 3
37.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43
84.3%
ASCII 8
 
15.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
62.5%
, 3
37.5%
Hangul
ValueCountFrequency (%)
3
 
7.0%
3
 
7.0%
3
 
7.0%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
1
 
2.3%
Other values (21) 21
48.8%

개요
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-12T20:57:01.845126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length348
Median length133
Mean length111.16
Min length43

Characters and Unicode

Total characters11116
Distinct characters622
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row옛 명칭은 경운궁이었는데 1907년부터 덕수궁으로 불리게 되었습니다. 6만 1500㎡의 면적에 대한문, 중화문, 광명문과 중화전, 준명당, 석어당, 석조전, 함녕전, 즉조당 등의 전각이 남아있습니다.
2nd row1901년에 지어진 중명전은 지금의 덕수궁인 경운궁에 포함된 건물로서 접견소 및 연회장, 도서관으로 사용되었습니다. 1907년에 황태자 가례의 연회가 거행된 장소이며, 을사늑약이 체결되었던 비운의 장소이기도 합니다. 일제강점기인 1915년부터 외국인에 임대되어 경성구락부로 이용되었습니다.
3rd row환구단은 황제가 하늘에 제사를 올리는 제단을 말합니다. 이곳은 조선을 이은 대한제국의 고종황제가 하늘에 제를 올린 곳입니다. 1897년 완공된 환구단은 당시 황실 최고의 도편수였던 심의석이 설계했습니다.
4th row1890년(고종 27)에 러시아인 사바틴(A.I.Sabatin)이 설계한 르네상스 양식의 건물입니다. 본관은 6·25전쟁 때 파괴되었고, 현재는 3층 규모의 탑만이 남았습니다. 고종이 일본의 무력 압박을 피한 아관파천의 현장으로 유명합니다.
5th row정동제일교회는 1895년(고종 32) 착공하여 1897년(광무 1) 10월에 준공된 개신교 교회 예배당입니다.
ValueCountFrequency (%)
있습니다 24
 
1.1%
위해 15
 
0.7%
11
 
0.5%
10
 
0.4%
10
 
0.4%
10
 
0.4%
있는 10
 
0.4%
이후 9
 
0.4%
광복 9
 
0.4%
명동의 8
 
0.4%
Other values (1723) 2129
94.8%
2023-12-12T20:57:02.498317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2151
 
19.4%
221
 
2.0%
196
 
1.8%
. 196
 
1.8%
193
 
1.7%
185
 
1.7%
1 182
 
1.6%
147
 
1.3%
146
 
1.3%
9 141
 
1.3%
Other values (612) 7358
66.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7628
68.6%
Space Separator 2151
 
19.4%
Decimal Number 772
 
6.9%
Other Punctuation 312
 
2.8%
Lowercase Letter 121
 
1.1%
Open Punctuation 40
 
0.4%
Close Punctuation 40
 
0.4%
Uppercase Letter 31
 
0.3%
Math Symbol 7
 
0.1%
Modifier Symbol 6
 
0.1%
Other values (5) 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
221
 
2.9%
196
 
2.6%
193
 
2.5%
185
 
2.4%
147
 
1.9%
146
 
1.9%
129
 
1.7%
119
 
1.6%
115
 
1.5%
113
 
1.5%
Other values (544) 6064
79.5%
Lowercase Letter
ValueCountFrequency (%)
e 14
11.6%
o 14
11.6%
r 12
9.9%
a 11
9.1%
l 10
8.3%
m 10
8.3%
i 8
 
6.6%
n 7
 
5.8%
s 7
 
5.8%
y 4
 
3.3%
Other values (12) 24
19.8%
Uppercase Letter
ValueCountFrequency (%)
S 5
16.1%
H 5
16.1%
N 3
9.7%
C 3
9.7%
M 2
 
6.5%
G 2
 
6.5%
J 2
 
6.5%
A 2
 
6.5%
B 1
 
3.2%
R 1
 
3.2%
Other values (5) 5
16.1%
Decimal Number
ValueCountFrequency (%)
1 182
23.6%
9 141
18.3%
0 108
14.0%
2 67
 
8.7%
5 56
 
7.3%
6 53
 
6.9%
3 50
 
6.5%
7 43
 
5.6%
8 41
 
5.3%
4 31
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 196
62.8%
, 86
27.6%
· 28
 
9.0%
' 2
 
0.6%
Math Symbol
ValueCountFrequency (%)
~ 5
71.4%
< 1
 
14.3%
> 1
 
14.3%
Modifier Symbol
ValueCountFrequency (%)
˝ 2
33.3%
˚ 2
33.3%
´ 2
33.3%
Open Punctuation
ValueCountFrequency (%)
( 39
97.5%
1
 
2.5%
Close Punctuation
ValueCountFrequency (%)
) 39
97.5%
1
 
2.5%
Other Symbol
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
2151
100.0%
Initial Punctuation
ValueCountFrequency (%)
2
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%
Other Number
ValueCountFrequency (%)
² 1
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7595
68.3%
Common 3336
30.0%
Latin 152
 
1.4%
Han 33
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
221
 
2.9%
196
 
2.6%
193
 
2.5%
185
 
2.4%
147
 
1.9%
146
 
1.9%
129
 
1.7%
119
 
1.6%
115
 
1.5%
113
 
1.5%
Other values (515) 6031
79.4%
Latin
ValueCountFrequency (%)
e 14
 
9.2%
o 14
 
9.2%
r 12
 
7.9%
a 11
 
7.2%
l 10
 
6.6%
m 10
 
6.6%
i 8
 
5.3%
n 7
 
4.6%
s 7
 
4.6%
S 5
 
3.3%
Other values (27) 54
35.5%
Common
ValueCountFrequency (%)
2151
64.5%
. 196
 
5.9%
1 182
 
5.5%
9 141
 
4.2%
0 108
 
3.2%
, 86
 
2.6%
2 67
 
2.0%
5 56
 
1.7%
6 53
 
1.6%
3 50
 
1.5%
Other values (21) 246
 
7.4%
Han
ValueCountFrequency (%)
2
 
6.1%
2
 
6.1%
2
 
6.1%
2
 
6.1%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
Other values (19) 19
57.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7595
68.3%
ASCII 3445
31.0%
None 33
 
0.3%
CJK 32
 
0.3%
Modifier Letters 4
 
< 0.1%
Punctuation 4
 
< 0.1%
CJK Compat 2
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2151
62.4%
. 196
 
5.7%
1 182
 
5.3%
9 141
 
4.1%
0 108
 
3.1%
, 86
 
2.5%
2 67
 
1.9%
5 56
 
1.6%
6 53
 
1.5%
3 50
 
1.5%
Other values (47) 355
 
10.3%
Hangul
ValueCountFrequency (%)
221
 
2.9%
196
 
2.6%
193
 
2.5%
185
 
2.4%
147
 
1.9%
146
 
1.9%
129
 
1.7%
119
 
1.6%
115
 
1.5%
113
 
1.5%
Other values (515) 6031
79.4%
None
ValueCountFrequency (%)
· 28
84.8%
´ 2
 
6.1%
1
 
3.0%
1
 
3.0%
² 1
 
3.0%
Modifier Letters
ValueCountFrequency (%)
˝ 2
50.0%
˚ 2
50.0%
Punctuation
ValueCountFrequency (%)
2
50.0%
2
50.0%
CJK
ValueCountFrequency (%)
2
 
6.2%
2
 
6.2%
2
 
6.2%
2
 
6.2%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
Other values (18) 18
56.2%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
CJK Compat
ValueCountFrequency (%)
1
50.0%
1
50.0%

시대분류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

주제분류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

지번주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB
Distinct83
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-12T20:57:02.893098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length29
Mean length18.49
Min length11

Characters and Unicode

Total characters1849
Distinct characters91
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

Unique76 ?
Unique (%)76.0%

Sample

1st row서울특별시 중구 세종대로 99
2nd row서울특별시 중구 정동길 41-11
3rd row서울특별시 중구 소공로 106
4th row서울특별시 중구 정동길 21-18 정동공원
5th row서울특별시 중구 정동길 46 정동교회
ValueCountFrequency (%)
서울특별시 100
22.7%
중구 99
22.5%
일대 16
 
3.6%
명동 13
 
3.0%
정동길 8
 
1.8%
세종대로 7
 
1.6%
명동길 6
 
1.4%
소파로 6
 
1.4%
퇴계로 5
 
1.1%
을지로 5
 
1.1%
Other values (116) 175
39.8%
2023-12-12T20:57:03.354514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
341
18.4%
102
 
5.5%
102
 
5.5%
102
 
5.5%
101
 
5.5%
101
 
5.5%
101
 
5.5%
99
 
5.4%
1 69
 
3.7%
53
 
2.9%
Other values (81) 678
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1172
63.4%
Space Separator 341
 
18.4%
Decimal Number 288
 
15.6%
Dash Punctuation 25
 
1.4%
Uppercase Letter 11
 
0.6%
Close Punctuation 5
 
0.3%
Open Punctuation 5
 
0.3%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
102
 
8.7%
102
 
8.7%
102
 
8.7%
101
 
8.6%
101
 
8.6%
101
 
8.6%
99
 
8.4%
53
 
4.5%
52
 
4.4%
35
 
3.0%
Other values (57) 324
27.6%
Decimal Number
ValueCountFrequency (%)
1 69
24.0%
2 50
17.4%
5 29
10.1%
3 22
 
7.6%
4 22
 
7.6%
0 21
 
7.3%
9 20
 
6.9%
7 19
 
6.6%
6 19
 
6.6%
8 17
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
A 3
27.3%
U 1
 
9.1%
T 1
 
9.1%
I 1
 
9.1%
R 1
 
9.1%
C 1
 
9.1%
W 1
 
9.1%
Y 1
 
9.1%
M 1
 
9.1%
Space Separator
ValueCountFrequency (%)
341
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1172
63.4%
Common 666
36.0%
Latin 11
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
102
 
8.7%
102
 
8.7%
102
 
8.7%
101
 
8.6%
101
 
8.6%
101
 
8.6%
99
 
8.4%
53
 
4.5%
52
 
4.4%
35
 
3.0%
Other values (57) 324
27.6%
Common
ValueCountFrequency (%)
341
51.2%
1 69
 
10.4%
2 50
 
7.5%
5 29
 
4.4%
- 25
 
3.8%
3 22
 
3.3%
4 22
 
3.3%
0 21
 
3.2%
9 20
 
3.0%
7 19
 
2.9%
Other values (5) 48
 
7.2%
Latin
ValueCountFrequency (%)
A 3
27.3%
U 1
 
9.1%
T 1
 
9.1%
I 1
 
9.1%
R 1
 
9.1%
C 1
 
9.1%
W 1
 
9.1%
Y 1
 
9.1%
M 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1172
63.4%
ASCII 677
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
341
50.4%
1 69
 
10.2%
2 50
 
7.4%
5 29
 
4.3%
- 25
 
3.7%
3 22
 
3.2%
4 22
 
3.2%
0 21
 
3.1%
9 20
 
3.0%
7 19
 
2.8%
Other values (14) 59
 
8.7%
Hangul
ValueCountFrequency (%)
102
 
8.7%
102
 
8.7%
102
 
8.7%
101
 
8.6%
101
 
8.6%
101
 
8.6%
99
 
8.4%
53
 
4.5%
52
 
4.4%
35
 
3.0%
Other values (57) 324
27.6%

지역
Categorical

Distinct24
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시 중구 명동
13 
서울특별시 중구 세종대로
서울특별시 중구 퇴계로
서울특별시 중구 정동길
서울특별시 중구 소파로
Other values (19)
55 

Length

Max length15
Median length12
Mean length12.19
Min length11

Unique

Unique5 ?
Unique (%)5.0%

Sample

1st row서울특별시 중구 세종대로
2nd row서울특별시 중구 정동길
3rd row서울특별시 중구 소공로
4th row서울특별시 중구 정동길
5th row서울특별시 중구 정동길

Common Values

ValueCountFrequency (%)
서울특별시 중구 명동 13
13.0%
서울특별시 중구 세종대로 9
 
9.0%
서울특별시 중구 퇴계로 9
 
9.0%
서울특별시 중구 정동길 8
 
8.0%
서울특별시 중구 소파로 6
 
6.0%
서울특별시 중구 명동길 6
 
6.0%
서울특별시 중구 장충단로 5
 
5.0%
서울특별시 중구 장충동 5
 
5.0%
서울특별시 중구 을지로 5
 
5.0%
서울특별시 중구 동호로 4
 
4.0%
Other values (14) 30
30.0%

Length

2023-12-12T20:57:03.521915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 100
33.3%
중구 99
33.0%
명동 13
 
4.3%
세종대로 10
 
3.3%
퇴계로 9
 
3.0%
정동길 8
 
2.7%
소파로 6
 
2.0%
명동길 6
 
2.0%
장충단로 5
 
1.7%
장충동 5
 
1.7%
Other values (15) 39
 
13.0%

제공기관
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울시 중구청
100 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울시 중구청
2nd row서울시 중구청
3rd row서울시 중구청
4th row서울시 중구청
5th row서울시 중구청

Common Values

ValueCountFrequency (%)
서울시 중구청 100
100.0%

Length

2023-12-12T20:57:03.670409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:57:03.769920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울시 100
50.0%
중구청 100
50.0%

언어유형
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KOR
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
KOR 100
100.0%

Length

2023-12-12T20:57:03.882402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:57:03.978866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kor 100
100.0%

제작일
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2015-12-30 00:00:00
Maximum2015-12-30 00:00:00
2023-12-12T20:57:04.056861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:57:04.166089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

유형
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
DATA
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
DATA 100
100.0%

Length

2023-12-12T20:57:04.277982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:57:04.409452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
data 100
100.0%

형식
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
HTML
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
HTML 100
100.0%

Length

2023-12-12T20:57:04.524593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:57:04.654940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
html 100
100.0%

전화번호
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing68
Missing (%)68.0%
Memory size932.0 B
2023-12-12T20:57:04.894492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length11.46875
Min length6

Characters and Unicode

Total characters367
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row02-771-9951
2nd row02-2124-8800
3rd row02-720-9494
4th row02-2280-4114
5th row02-774-1784
ValueCountFrequency (%)
02-120 1
 
3.0%
02-2261-0512 1
 
3.0%
02-742-7601 1
 
3.0%
02-2022-0600 1
 
3.0%
042-481-4650 1
 
3.0%
02-724-0274~6 1
 
3.0%
02-2261-0511 1
 
3.0%
02-2264-4412 1
 
3.0%
02-771-9951 1
 
3.0%
02-751-1500 1
 
3.0%
Other values (23) 23
69.7%
2023-12-12T20:57:05.422776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 67
18.3%
2 63
17.2%
- 61
16.6%
1 30
8.2%
7 29
7.9%
4 26
 
7.1%
5 22
 
6.0%
8 20
 
5.4%
6 19
 
5.2%
3 16
 
4.4%
Other values (4) 14
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 302
82.3%
Dash Punctuation 61
 
16.6%
Math Symbol 2
 
0.5%
Other Punctuation 1
 
0.3%
Space Separator 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 67
22.2%
2 63
20.9%
1 30
9.9%
7 29
9.6%
4 26
 
8.6%
5 22
 
7.3%
8 20
 
6.6%
6 19
 
6.3%
3 16
 
5.3%
9 10
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 367
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 67
18.3%
2 63
17.2%
- 61
16.6%
1 30
8.2%
7 29
7.9%
4 26
 
7.1%
5 22
 
6.0%
8 20
 
5.4%
6 19
 
5.2%
3 16
 
4.4%
Other values (4) 14
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 367
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 67
18.3%
2 63
17.2%
- 61
16.6%
1 30
8.2%
7 29
7.9%
4 26
 
7.1%
5 22
 
6.0%
8 20
 
5.4%
6 19
 
5.2%
3 16
 
4.4%
Other values (4) 14
 
3.8%

지정현황
Text

MISSING 

Distinct19
Distinct (%)95.0%
Missing80
Missing (%)80.0%
Memory size932.0 B
2023-12-12T20:57:05.702114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length10.9
Min length6

Characters and Unicode

Total characters218
Distinct characters35
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

Unique18 ?
Unique (%)90.0%

Sample

1st row사적 제124호
2nd row서울특별시 기념물 제16호
3rd row등록문화재 제237호
4th row등록문화재 제267호
5th row등록문화재 제402호
ValueCountFrequency (%)
등록문화재 8
17.8%
서울특별시 5
 
11.1%
사적 4
 
8.9%
기념물 2
 
4.4%
서울유형문화재 2
 
4.4%
제20호 2
 
4.4%
유형문화재 2
 
4.4%
제124호 2
 
4.4%
제1호 2
 
4.4%
제10호 1
 
2.2%
Other values (15) 15
33.3%
2023-12-12T20:57:06.149292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26
 
11.9%
20
 
9.2%
20
 
9.2%
12
 
5.5%
12
 
5.5%
12
 
5.5%
1 10
 
4.6%
2 10
 
4.6%
8
 
3.7%
8
 
3.7%
Other values (25) 80
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 149
68.3%
Decimal Number 43
 
19.7%
Space Separator 26
 
11.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
20
13.4%
20
13.4%
12
 
8.1%
12
 
8.1%
12
 
8.1%
8
 
5.4%
8
 
5.4%
7
 
4.7%
7
 
4.7%
5
 
3.4%
Other values (15) 38
25.5%
Decimal Number
ValueCountFrequency (%)
1 10
23.3%
2 10
23.3%
0 5
11.6%
3 4
 
9.3%
7 3
 
7.0%
8 3
 
7.0%
4 3
 
7.0%
5 3
 
7.0%
6 2
 
4.7%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 149
68.3%
Common 69
31.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
20
13.4%
20
13.4%
12
 
8.1%
12
 
8.1%
12
 
8.1%
8
 
5.4%
8
 
5.4%
7
 
4.7%
7
 
4.7%
5
 
3.4%
Other values (15) 38
25.5%
Common
ValueCountFrequency (%)
26
37.7%
1 10
 
14.5%
2 10
 
14.5%
0 5
 
7.2%
3 4
 
5.8%
7 3
 
4.3%
8 3
 
4.3%
4 3
 
4.3%
5 3
 
4.3%
6 2
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 149
68.3%
ASCII 69
31.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26
37.7%
1 10
 
14.5%
2 10
 
14.5%
0 5
 
7.2%
3 4
 
5.8%
7 3
 
4.3%
8 3
 
4.3%
4 3
 
4.3%
5 3
 
4.3%
6 2
 
2.9%
Hangul
ValueCountFrequency (%)
20
13.4%
20
13.4%
12
 
8.1%
12
 
8.1%
12
 
8.1%
8
 
5.4%
8
 
5.4%
7
 
4.7%
7
 
4.7%
5
 
3.4%
Other values (15) 38
25.5%

휴무일
Text

MISSING 

Distinct9
Distinct (%)64.3%
Missing86
Missing (%)86.0%
Memory size932.0 B
2023-12-12T20:57:06.390167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length21
Mean length12.714286
Min length6

Characters and Unicode

Total characters178
Distinct characters29
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

Unique5 ?
Unique (%)35.7%

Sample

1st row매주 월요일
2nd row매주 월요일, 공휴일
3rd row매주 월요일, 1월 1일
4th row매주 월요일, 설연휴 및 추석연휴, 12월 29일~다음해 1월 2일
5th row매주 월요일, 명절
ValueCountFrequency (%)
매주 14
27.5%
월요일 10
19.6%
1월 5
 
9.8%
1일 4
 
7.8%
공휴일 3
 
5.9%
일요일 3
 
5.9%
명절 1
 
2.0%
설날 1
 
2.0%
화요일 1
 
2.0%
1
 
2.0%
Other values (8) 8
15.7%
2023-12-12T20:57:06.795226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37
20.8%
26
14.6%
16
9.0%
14
 
7.9%
14
 
7.9%
14
 
7.9%
, 13
 
7.3%
1 10
 
5.6%
5
 
2.8%
3
 
1.7%
Other values (19) 26
14.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 113
63.5%
Space Separator 37
 
20.8%
Decimal Number 14
 
7.9%
Other Punctuation 13
 
7.3%
Math Symbol 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
26
23.0%
16
14.2%
14
12.4%
14
12.4%
14
12.4%
5
 
4.4%
3
 
2.7%
2
 
1.8%
2
 
1.8%
2
 
1.8%
Other values (13) 15
13.3%
Decimal Number
ValueCountFrequency (%)
1 10
71.4%
2 3
 
21.4%
9 1
 
7.1%
Space Separator
ValueCountFrequency (%)
37
100.0%
Other Punctuation
ValueCountFrequency (%)
, 13
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 113
63.5%
Common 65
36.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
26
23.0%
16
14.2%
14
12.4%
14
12.4%
14
12.4%
5
 
4.4%
3
 
2.7%
2
 
1.8%
2
 
1.8%
2
 
1.8%
Other values (13) 15
13.3%
Common
ValueCountFrequency (%)
37
56.9%
, 13
 
20.0%
1 10
 
15.4%
2 3
 
4.6%
9 1
 
1.5%
~ 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 113
63.5%
ASCII 65
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37
56.9%
, 13
 
20.0%
1 10
 
15.4%
2 3
 
4.6%
9 1
 
1.5%
~ 1
 
1.5%
Hangul
ValueCountFrequency (%)
26
23.0%
16
14.2%
14
12.4%
14
12.4%
14
12.4%
5
 
4.4%
3
 
2.7%
2
 
1.8%
2
 
1.8%
2
 
1.8%
Other values (13) 15
13.3%

이용시간
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing91
Missing (%)91.0%
Memory size932.0 B
2023-12-12T20:57:07.024696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length43
Mean length23.111111
Min length13

Characters and Unicode

Total characters208
Distinct characters30
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

Unique9 ?
Unique (%)100.0%

Sample

1st row매표 및 입장시간 09:00 ~ 20:00 퇴장시간 09:00 ~ 21:00
2nd row매일 10:00 ~ 17:00
3rd row화요일~일요일 10:00 ~ 17:00
4th row10:00 ~ 17:00
5th row월~금, 일 및 공휴일 17:00, 20:00 토 14:00, 17:00, 20:00
ValueCountFrequency (%)
10
20.8%
10:00 5
10.4%
17:00 5
10.4%
09:00 4
 
8.3%
20:00 3
 
6.2%
18:00 3
 
6.2%
21:00 2
 
4.2%
2
 
4.2%
매표 1
 
2.1%
1
 
2.1%
Other values (12) 12
25.0%
2023-12-12T20:57:07.472155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 58
27.9%
39
18.8%
: 23
 
11.1%
1 16
 
7.7%
~ 12
 
5.8%
10
 
4.8%
2 5
 
2.4%
7 5
 
2.4%
, 4
 
1.9%
4
 
1.9%
Other values (20) 32
15.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 92
44.2%
Space Separator 39
18.8%
Other Letter 37
17.8%
Other Punctuation 27
 
13.0%
Math Symbol 12
 
5.8%
Control 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10
27.0%
4
 
10.8%
3
 
8.1%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
1
 
2.7%
1
 
2.7%
Other values (8) 8
21.6%
Decimal Number
ValueCountFrequency (%)
0 58
63.0%
1 16
 
17.4%
2 5
 
5.4%
7 5
 
5.4%
9 4
 
4.3%
8 3
 
3.3%
4 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
: 23
85.2%
, 4
 
14.8%
Space Separator
ValueCountFrequency (%)
39
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 171
82.2%
Hangul 37
 
17.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10
27.0%
4
 
10.8%
3
 
8.1%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
1
 
2.7%
1
 
2.7%
Other values (8) 8
21.6%
Common
ValueCountFrequency (%)
0 58
33.9%
39
22.8%
: 23
 
13.5%
1 16
 
9.4%
~ 12
 
7.0%
2 5
 
2.9%
7 5
 
2.9%
, 4
 
2.3%
9 4
 
2.3%
8 3
 
1.8%
Other values (2) 2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 171
82.2%
Hangul 37
 
17.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 58
33.9%
39
22.8%
: 23
 
13.5%
1 16
 
9.4%
~ 12
 
7.0%
2 5
 
2.9%
7 5
 
2.9%
, 4
 
2.3%
9 4
 
2.3%
8 3
 
1.8%
Other values (2) 2
 
1.2%
Hangul
ValueCountFrequency (%)
10
27.0%
4
 
10.8%
3
 
8.1%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
1
 
2.7%
1
 
2.7%
Other values (8) 8
21.6%

이용요금
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
92 
무료
 
7
대인(만25세이상) 1,000원단체 대인(10인이상) 800원
 
1

Length

Max length34
Median length4
Mean length4.16
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row대인(만25세이상) 1,000원단체 대인(10인이상) 800원
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 92
92.0%
무료 7
 
7.0%
대인(만25세이상) 1,000원단체 대인(10인이상) 800원 1
 
1.0%

Length

2023-12-12T20:57:07.715043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:57:07.873994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 92
89.3%
무료 7
 
6.8%
대인(만25세이상 1
 
1.0%
1,000원단체 1
 
1.0%
대인(10인이상 1
 
1.0%
800원 1
 
1.0%

주차
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
89 
주차가능
11 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row주차가능

Common Values

ValueCountFrequency (%)
<NA> 89
89.0%
주차가능 11
 
11.0%

Length

2023-12-12T20:57:08.020010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:57:08.182528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 89
89.0%
주차가능 11
 
11.0%
Distinct3
Distinct (%)100.0%
Missing97
Missing (%)97.0%
Memory size932.0 B
2023-12-12T20:57:08.372128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length18
Min length5

Characters and Unicode

Total characters54
Distinct characters30
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

Unique3 ?
Unique (%)100.0%

Sample

1st row휠체어대여
2nd row장애인 단체관람 가능, 안내 점자 책자 구비
3rd row장애인 화장실 구비, 장애인용 엘리베이터 구비
ValueCountFrequency (%)
구비 3
21.4%
장애인 2
14.3%
휠체어대여 1
 
7.1%
단체관람 1
 
7.1%
가능 1
 
7.1%
안내 1
 
7.1%
점자 1
 
7.1%
책자 1
 
7.1%
화장실 1
 
7.1%
장애인용 1
 
7.1%
2023-12-12T20:57:08.839576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
20.4%
4
 
7.4%
3
 
5.6%
3
 
5.6%
3
 
5.6%
3
 
5.6%
2
 
3.7%
, 2
 
3.7%
2
 
3.7%
1
 
1.9%
Other values (20) 20
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41
75.9%
Space Separator 11
 
20.4%
Other Punctuation 2
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4
 
9.8%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
2
 
4.9%
2
 
4.9%
1
 
2.4%
1
 
2.4%
1
 
2.4%
Other values (18) 18
43.9%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41
75.9%
Common 13
 
24.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4
 
9.8%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
2
 
4.9%
2
 
4.9%
1
 
2.4%
1
 
2.4%
1
 
2.4%
Other values (18) 18
43.9%
Common
ValueCountFrequency (%)
11
84.6%
, 2
 
15.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41
75.9%
ASCII 13
 
24.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11
84.6%
, 2
 
15.4%
Hangul
ValueCountFrequency (%)
4
 
9.8%
3
 
7.3%
3
 
7.3%
3
 
7.3%
3
 
7.3%
2
 
4.9%
2
 
4.9%
1
 
2.4%
1
 
2.4%
1
 
2.4%
Other values (18) 18
43.9%

체험안내
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing97
Missing (%)97.0%
Memory size932.0 B
2023-12-12T20:57:09.099403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length22
Mean length20
Min length4

Characters and Unicode

Total characters60
Distinct characters40
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

Unique3 ?
Unique (%)100.0%

Sample

1st row전통의상 입어보기, 수문장 교대의식 체험
2nd row장구체험
3rd row한풍문화마실, 사진촬영서비스, 짚공예 시연, 전통문화 유산해설
ValueCountFrequency (%)
전통의상 1
8.3%
입어보기 1
8.3%
수문장 1
8.3%
교대의식 1
8.3%
체험 1
8.3%
장구체험 1
8.3%
한풍문화마실 1
8.3%
사진촬영서비스 1
8.3%
짚공예 1
8.3%
시연 1
8.3%
Other values (2) 2
16.7%
2023-12-12T20:57:09.519808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
 
15.0%
, 4
 
6.7%
3
 
5.0%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
Other values (30) 30
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47
78.3%
Space Separator 9
 
15.0%
Other Punctuation 4
 
6.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
 
6.4%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
1
 
2.1%
1
 
2.1%
Other values (28) 28
59.6%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47
78.3%
Common 13
 
21.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
 
6.4%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
1
 
2.1%
1
 
2.1%
Other values (28) 28
59.6%
Common
ValueCountFrequency (%)
9
69.2%
, 4
30.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47
78.3%
ASCII 13
 
21.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9
69.2%
, 4
30.8%
Hangul
ValueCountFrequency (%)
3
 
6.4%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
1
 
2.1%
1
 
2.1%
Other values (28) 28
59.6%

안내서비스
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing99
Missing (%)99.0%
Memory size932.0 B
2023-12-12T20:57:09.702286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters12
Distinct characters11
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

Unique1 ?
Unique (%)100.0%

Sample

1st row다국어 음성안내기 구비
ValueCountFrequency (%)
다국어 1
33.3%
음성안내기 1
33.3%
구비 1
33.3%
2023-12-12T20:57:10.016929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
16.7%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10
83.3%
Space Separator 2
 
16.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10
83.3%
Common 2
 
16.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10
83.3%
ASCII 2
 
16.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2
100.0%
Hangul
ValueCountFrequency (%)
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%

예약
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing97
Missing (%)97.0%
Memory size932.0 B
2023-12-12T20:57:10.217103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length16.333333
Min length9

Characters and Unicode

Total characters49
Distinct characters27
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

Unique3 ?
Unique (%)100.0%

Sample

1st row인터넷, 모바일, 전화, 방문예메 가능
2nd row온라인, 전화 예매, 현장구매 가능
3rd row단체관람예약 가능
ValueCountFrequency (%)
가능 3
25.0%
전화 2
16.7%
인터넷 1
 
8.3%
모바일 1
 
8.3%
방문예메 1
 
8.3%
온라인 1
 
8.3%
예매 1
 
8.3%
현장구매 1
 
8.3%
단체관람예약 1
 
8.3%
2023-12-12T20:57:10.606149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
18.4%
, 5
 
10.2%
3
 
6.1%
3
 
6.1%
3
 
6.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
2
 
4.1%
1
 
2.0%
Other values (17) 17
34.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35
71.4%
Space Separator 9
 
18.4%
Other Punctuation 5
 
10.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
 
8.6%
3
 
8.6%
3
 
8.6%
2
 
5.7%
2
 
5.7%
2
 
5.7%
2
 
5.7%
1
 
2.9%
1
 
2.9%
1
 
2.9%
Other values (15) 15
42.9%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35
71.4%
Common 14
 
28.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
 
8.6%
3
 
8.6%
3
 
8.6%
2
 
5.7%
2
 
5.7%
2
 
5.7%
2
 
5.7%
1
 
2.9%
1
 
2.9%
1
 
2.9%
Other values (15) 15
42.9%
Common
ValueCountFrequency (%)
9
64.3%
, 5
35.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35
71.4%
ASCII 14
 
28.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9
64.3%
, 5
35.7%
Hangul
ValueCountFrequency (%)
3
 
8.6%
3
 
8.6%
3
 
8.6%
2
 
5.7%
2
 
5.7%
2
 
5.7%
2
 
5.7%
1
 
2.9%
1
 
2.9%
1
 
2.9%
Other values (15) 15
42.9%

Sample

상세고유순번관리번호명칭관련항목연계자원경도정보(127.XX)위도정보(36.XXX)이명칭개요시대분류주제분류지번주소도로명주소지역제공기관언어유형제작일유형형식전화번호지정현황휴무일이용시간이용요금주차장애인 편의시설체험안내안내서비스예약
01JGS_000001덕수궁<NA>JGH_000370126.9765337.56502경운궁, 정릉동행궁, 서궁옛 명칭은 경운궁이었는데 1907년부터 덕수궁으로 불리게 되었습니다. 6만 1500㎡의 면적에 대한문, 중화문, 광명문과 중화전, 준명당, 석어당, 석조전, 함녕전, 즉조당 등의 전각이 남아있습니다.<NA><NA><NA>서울특별시 중구 세종대로 99서울특별시 중구 세종대로서울시 중구청KOR2015-12-30DATAHTML02-771-9951사적 제124호매주 월요일매표 및 입장시간 09:00 ~ 20:00 퇴장시간 09:00 ~ 21:00대인(만25세이상) 1,000원단체 대인(10인이상) 800원<NA>휠체어대여전통의상 입어보기, 수문장 교대의식 체험<NA><NA>
12JGS_000002덕수궁 중명전<NA>JGH_000350126.9725237.56659<NA>1901년에 지어진 중명전은 지금의 덕수궁인 경운궁에 포함된 건물로서 접견소 및 연회장, 도서관으로 사용되었습니다. 1907년에 황태자 가례의 연회가 거행된 장소이며, 을사늑약이 체결되었던 비운의 장소이기도 합니다. 일제강점기인 1915년부터 외국인에 임대되어 경성구락부로 이용되었습니다.<NA><NA><NA>서울특별시 중구 정동길 41-11서울특별시 중구 정동길서울시 중구청KOR2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23JGS_000003환구단(원구단)<NA>JGH_000335126.9796937.56506<NA>환구단은 황제가 하늘에 제사를 올리는 제단을 말합니다. 이곳은 조선을 이은 대한제국의 고종황제가 하늘에 제를 올린 곳입니다. 1897년 완공된 환구단은 당시 황실 최고의 도편수였던 심의석이 설계했습니다.<NA><NA><NA>서울특별시 중구 소공로 106서울특별시 중구 소공로서울시 중구청KOR2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34JGS_000004구 러시아공사관<NA>JGH_000355126.9714637.56825<NA>1890년(고종 27)에 러시아인 사바틴(A.I.Sabatin)이 설계한 르네상스 양식의 건물입니다. 본관은 6·25전쟁 때 파괴되었고, 현재는 3층 규모의 탑만이 남았습니다. 고종이 일본의 무력 압박을 피한 아관파천의 현장으로 유명합니다.<NA><NA><NA>서울특별시 중구 정동길 21-18 정동공원서울특별시 중구 정동길서울시 중구청KOR2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45JGS_000005정동제일교회<NA>JGH_000367126.9723637.56542<NA>정동제일교회는 1895년(고종 32) 착공하여 1897년(광무 1) 10월에 준공된 개신교 교회 예배당입니다.<NA><NA><NA>서울특별시 중구 정동길 46 정동교회서울특별시 중구 정동길서울시 중구청KOR2015-12-30DATAHTML<NA><NA><NA><NA><NA>주차가능<NA><NA><NA><NA>
56JGS_000006구 배재학당 동관(배재학당 역사박물관)<NA>JGH_000368126.9726237.56378<NA>이 건물은 1916년 준공하여 배재중·고등학교가 1984년 강동구로 이전하기 전까지 교사로 사용한 곳입니다. 배재학당은 선교사 아펜젤러(Henry Gerhard Appenzeller)가 1885년 8월에 세운 학교로 처음에는 주변의 민가를 사들여 교사(校舍)로 사용했습니다.<NA><NA><NA>서울특별시 중구 서소문로 11길 19서울특별시 중구 서소문로서울시 중구청KOR2015-12-30DATAHTML<NA>서울특별시 기념물 제16호매주 월요일, 공휴일매일 10:00 ~ 17:00무료<NA><NA><NA><NA><NA>
67JGS_000007서울시립미술관<NA>JGH_000313126.9737737.56402<NA>이곳은 육영공원과 독일공사관, 경성재판소가 있던 자리입니다. 광복 후에는 대한민국의 대법원 건물이 되었으며 2002년에 서울시립미술관으로 개관하였습니다.<NA><NA><NA>서울특별시 중구 덕수궁길 61서울특별시 중구 덕수궁길서울시 중구청KOR2015-12-30DATAHTML02-2124-8800등록문화재 제237호매주 월요일, 1월 1일<NA><NA>주차가능<NA><NA><NA><NA>
78JGS_000008경운궁 양이재<NA>JGH_000361126.9754437.56694<NA>대화재로 불탔던 경운궁(덕수궁)을 다시 지을 때 같이 지은 건물로 1905년에 완공되었습니다. 대한제국 황족과 귀족들의 근대식 교육을 담당했던 곳이었으며 현재는 대한성공회 주교 집무실로 사용되고 있습니다.<NA><NA><NA>서울특별시 중구 세종대로21길 15서울특별시 중구 세종대로서울시 중구청KOR2015-12-30DATAHTML<NA>등록문화재 제267호<NA><NA><NA><NA><NA><NA><NA><NA>
89JGS_000009구 신아일보사 별관<NA>JGH_000354126.9721737.56619<NA>1930년대 지하 1층, 지상 2층으로 건축된 철근콘크리트 건물로 미국기업인 싱어미싱회사 한국지부로 사용되다가, 1963년 신아일보가 매입하여 1975년 3, 4층을 증축하여 별관으로 사용합니다. 신아일보는 1980년 신군부의 언론통폐합으로 경향신문에 흡수·통합되었습니다.<NA><NA><NA>서울특별시 중구 정동길 33서울특별시 중구 정동길서울시 중구청KOR2015-12-30DATAHTML<NA>등록문화재 제402호<NA><NA><NA><NA><NA><NA><NA><NA>
910JGS_000010구세군중앙회관<NA>JGH_000352126.973637.56761<NA>구세군중앙회관은 구세군의 사관 양성과 선교활동 사회사업의 근거지로 사용하기 위해 1928년에 준공되었습니다.<NA><NA><NA>서울특별시 중구 덕수궁길 130서울특별시 중구 덕수궁길서울시 중구청KOR2015-12-30DATAHTML02-720-9494서울특별시 기념물 제20호<NA><NA><NA><NA><NA><NA><NA><NA>
상세고유순번관리번호명칭관련항목연계자원경도정보(127.XX)위도정보(36.XXX)이명칭개요시대분류주제분류지번주소도로명주소지역제공기관언어유형제작일유형형식전화번호지정현황휴무일이용시간이용요금주차장애인 편의시설체험안내안내서비스예약
9091JGS_000091명동의 소극장들<NA><NA>126.9878937.5634<NA>6·25전쟁 후 국립극장이 명동 시공관에 자리를 잡습니다. 이후 명동은 공연예술의 중심지가 됩니다. 하지만 1970년대 들어 국립극장이 이전하면서 명동에 하나둘씩 생기기 시작한 소극장이 공연예술을 이끕니다. 대표적인 극단으로 자유극단과 삼일로 창고극장이 있습니다.<NA><NA><NA>서울특별시 중구 명동 일대서울특별시 중구 명동서울시 중구청KOR2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9192JGS_000092명동의 유일한 쉼터, 명동공원<NA><NA>126.9851737.56255<NA>1950년대에 만들어진 명동공원은 상업시설로 번잡했던 명동의 오아시스였습니다. 근처에 살던 아이들의 놀이터가 되기도 하였고, 근처 상가나 회사에 근무하던 직장인들이 잠시 쉬던 곳이기도 했습니다. 그리고 거나하게 취한 명동 술꾼들이 집에 가기 전 술을 깨는 장소이기도 했습니다.<NA><NA><NA>서울특별시 중구 명동 일대서울특별시 중구 명동서울시 중구청KOR2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9293JGS_000093요절한 예술인들(박인환, 전혜린, 윤용하, 이중섭, 김관식)<NA><NA>126.9846837.56231<NA>1950년대 명동의 예술가들은 치열하게 예술혼을 불태우며 작품을 남겼습니다. 그 중에는 강렬하게 타오르다 너무 일찍 세상을 떠난 예술가들도 있었습니다.<NA><NA><NA>서울특별시 중구 명동 일대서울특별시 중구 명동서울시 중구청KOR2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9394JGS_0000941950년대 명동의 하루(동아일보 1957년 기사)<NA><NA>126.9850937.56125<NA>1950년대의 명동은 일제강점기와 6·25전쟁 동안 억눌렸던 사람들의 소비 욕구가 분출되던 곳이었습니다. 1957년 명동의 번잡한 하루를 자료를 기반으로 구성해 보았습니다. (동아일보 1957.11.25 「서울의 축소판 명동의 하루」 기사 참조)<NA><NA><NA>서울특별시 중구 명동 일대서울특별시 중구 명동서울시 중구청KOR2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9495JGS_0000951950~60년대 '명동의 유행과 패션'<NA><NA>126.984637.56275<NA>6·25전쟁을 거치면서 한국 여성들은 한복의 불편함을 깨닫고 양장을 선호하게 됩니다. 1950년대부터 명동에서는 여성들의 기호에 맞는 옷을 파는 양장점과 미장원이 들어서기 시작합니다.<NA><NA><NA>서울특별시 중구 명동 일대서울특별시 중구 명동서울시 중구청KOR2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9596JGS_000096명동의 양장점<NA><NA>126.9845537.56303<NA>1950년대 말부터 명동지역에 양복점, 양장점, 양화점, 미용점 등이 집중적으로 생기고 그에 따라 명동을 중심으로 양장점과 미장원 관련 학원·학교들도 많이 들어섰습니다. 당시 양장점은 여성들에게 새로운 패션을 알려주는 공간이었습니다.<NA><NA><NA>서울특별시 중구 명동 일대서울특별시 중구 명동서울시 중구청KOR2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9697JGS_000097은성주점, 명동샹송-세월이 가면(박인환)<NA>JGH_000489126.984937.56206<NA>탤런트 최불암의 어머니가 운영했던 은성주점은 1950~60년대 명동의 문화예술가들이 자주 찾던 술집입니다. 다른 술집에 비해 정갈하여 각양각색의 사람들이 모였습니다.<NA><NA><NA>서울특별시 중구 명동 1가 59-7 ARITAUM 앞서울특별시 중구 명동서울시 중구청KOR2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9798JGS_000098중식당 아서원 이야기, 중국인 거리<NA><NA>126.9828737.56199<NA>아서원은 1950~60년대를 대표하는 화교 경영 중화요리점이며 유명 정치인과 경영인들의 회합장소로 많이 쓰였습니다. 명동의 서측 끝 남대문로와 접해있는 삼각형의 블록과 눈스퀘어에서 중앙우체국 뒤로 가면 개화기 때 형성된 중국인 거리가 나타납니다. 이곳에는 오래된 중국인 음식점과 중국 물품을 파는 상점이 있습니다.<NA><NA><NA>서울특별시 중구 명동 일대서울특별시 중구 명동서울시 중구청KOR2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9899JGS_000099남산예술센터<NA>JGH_000625126.9882437.55881<NA>1962년에 드라마센터로 문을 연 남산예술센터는 리모델링 공사를 거쳐 2009년 6월에 현대적인 공연장으로 재개관하였습니다.<NA><NA><NA>서울특별시 중구 소파로 138서울특별시 중구 소파로서울시 중구청KOR2015-12-30DATAHTML02-758-2000<NA><NA><NA><NA><NA><NA><NA><NA><NA>
99100JGS_000100성공회 성가수녀원<NA><NA>126.9753337.56753<NA>대한성공회 성가수녀원(Society of Holy Cross)은 1925년 9월 14일 조마가 주교에 의해 창립되었습니다. 6·25전쟁 때 허물어졌다가 1960년에 대한성공회에서 수녀원을 신축했습니다.<NA><NA><NA>서울특별시 중구 정동서울특별시 중구 정동서울시 중구청KOR2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>