Overview

Dataset statistics

Number of variables29
Number of observations139
Missing cells1771
Missing cells (%)43.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.6 KiB
Average record size in memory239.9 B

Variable types

Numeric3
Text14
Unsupported4
Categorical8

Dataset

Description상세고유순번,관리번호,명칭,관련항목,연계자원,경도정보(127.XX),위도정보(36.XXX),이명칭,개요,시대분류,주제분류,지번주소,도로명주소,지역,제공기관,언어유형,제작일,유형,형식,전화번호,지정현황,휴무일,이용시간,이용요금,주차,장애인 편의시설,체험안내,안내서비스,예약
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-13375/S/1/datasetView.do

Alerts

언어유형 has constant value ""Constant
유형 has constant value ""Constant
형식 has constant value ""Constant
안내서비스 has constant value ""Constant
이용요금 is highly imbalanced (78.0%)Imbalance
주차 is highly imbalanced (60.1%)Imbalance
관련항목 has 139 (100.0%) missing valuesMissing
연계자원 has 54 (38.8%) missing valuesMissing
이명칭 has 134 (96.4%) missing valuesMissing
시대분류 has 139 (100.0%) missing valuesMissing
주제분류 has 139 (100.0%) missing valuesMissing
지번주소 has 139 (100.0%) missing valuesMissing
전화번호 has 107 (77.0%) missing valuesMissing
지정현황 has 119 (85.6%) missing valuesMissing
휴무일 has 125 (89.9%) missing valuesMissing
이용시간 has 130 (93.5%) missing valuesMissing
장애인 편의시설 has 136 (97.8%) missing valuesMissing
체험안내 has 136 (97.8%) missing valuesMissing
안내서비스 has 138 (99.3%) missing valuesMissing
예약 has 136 (97.8%) missing valuesMissing
상세고유순번 has unique valuesUnique
관리번호 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 started2024-04-18 07:54:49.412316
Analysis finished2024-04-18 07:54:49.964224
Duration0.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상세고유순번
Real number (ℝ)

UNIQUE 

Distinct139
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean497.53237
Minimum401
Maximum715
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-18T16:54:50.026811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum401
5-th percentile407.9
Q1435.5
median470
Q3540.5
95-th percentile680.5
Maximum715
Range314
Interquartile range (IQR)105

Descriptive statistics

Standard deviation85.318865
Coefficient of variation (CV)0.17148405
Kurtosis0.098230719
Mean497.53237
Median Absolute Deviation (MAD)38
Skewness1.1097904
Sum69157
Variance7279.3087
MonotonicityNot monotonic
2024-04-18T16:54:50.155944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
401 1
 
0.7%
498 1
 
0.7%
492 1
 
0.7%
493 1
 
0.7%
494 1
 
0.7%
495 1
 
0.7%
496 1
 
0.7%
497 1
 
0.7%
499 1
 
0.7%
490 1
 
0.7%
Other values (129) 129
92.8%
ValueCountFrequency (%)
401 1
0.7%
402 1
0.7%
403 1
0.7%
404 1
0.7%
405 1
0.7%
406 1
0.7%
407 1
0.7%
408 1
0.7%
409 1
0.7%
410 1
0.7%
ValueCountFrequency (%)
715 1
0.7%
710 1
0.7%
705 1
0.7%
700 1
0.7%
695 1
0.7%
690 1
0.7%
685 1
0.7%
680 1
0.7%
675 1
0.7%
670 1
0.7%

관리번호
Text

UNIQUE 

Distinct139
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-18T16:54:50.437763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1390
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

Unique139 ?
Unique (%)100.0%

Sample

1st rowJGS_000001
2nd rowJGS_000002
3rd rowJGS_000003
4th rowJGS_000004
5th rowJGS_000005
ValueCountFrequency (%)
jgs_000001 1
 
0.7%
jgs_000106 1
 
0.7%
jgs_000104 1
 
0.7%
jgs_000103 1
 
0.7%
jgs_000102 1
 
0.7%
jgs_000101 1
 
0.7%
jgs_000100 1
 
0.7%
jgs_000099 1
 
0.7%
jgs_000098 1
 
0.7%
jgs_000072 1
 
0.7%
Other values (129) 129
92.8%
2024-04-18T16:54:50.834262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 548
39.4%
J 139
 
10.0%
G 139
 
10.0%
S 139
 
10.0%
_ 139
 
10.0%
1 74
 
5.3%
3 34
 
2.4%
2 34
 
2.4%
6 24
 
1.7%
5 24
 
1.7%
Other values (4) 96
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 834
60.0%
Uppercase Letter 417
30.0%
Connector Punctuation 139
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 548
65.7%
1 74
 
8.9%
3 34
 
4.1%
2 34
 
4.1%
6 24
 
2.9%
5 24
 
2.9%
4 24
 
2.9%
9 24
 
2.9%
7 24
 
2.9%
8 24
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
J 139
33.3%
G 139
33.3%
S 139
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 139
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 973
70.0%
Latin 417
30.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 548
56.3%
_ 139
 
14.3%
1 74
 
7.6%
3 34
 
3.5%
2 34
 
3.5%
6 24
 
2.5%
5 24
 
2.5%
4 24
 
2.5%
9 24
 
2.5%
7 24
 
2.5%
Latin
ValueCountFrequency (%)
J 139
33.3%
G 139
33.3%
S 139
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1390
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 548
39.4%
J 139
 
10.0%
G 139
 
10.0%
S 139
 
10.0%
_ 139
 
10.0%
1 74
 
5.3%
3 34
 
2.4%
2 34
 
2.4%
6 24
 
1.7%
5 24
 
1.7%
Other values (4) 96
 
6.9%

명칭
Text

Distinct138
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-18T16:54:51.135087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length94
Median length55
Mean length31.769784
Min length10

Characters and Unicode

Total characters4416
Distinct characters67
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique137 ?
Unique (%)98.6%

Sample

1st rowDeoksugung Palace
2nd rowJungmyeongjeon Hall of Deoksugung Palace
3rd rowHwangudan (Wongudan)
4th rowFormer Russian Legation
5th rowChungdong First Methodist Church
ValueCountFrequency (%)
of 54
 
8.5%
bridge 24
 
3.8%
the 16
 
2.5%
seoul 14
 
2.2%
myeong-dong 13
 
2.1%
and 10
 
1.6%
former 10
 
1.6%
museum 10
 
1.6%
korea 8
 
1.3%
statue 7
 
1.1%
Other values (322) 468
73.8%
2024-04-18T16:54:51.577561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
495
 
11.2%
e 405
 
9.2%
o 360
 
8.2%
n 343
 
7.8%
a 297
 
6.7%
g 213
 
4.8%
r 197
 
4.5%
i 197
 
4.5%
t 174
 
3.9%
u 145
 
3.3%
Other values (57) 1590
36.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3240
73.4%
Uppercase Letter 531
 
12.0%
Space Separator 495
 
11.2%
Dash Punctuation 40
 
0.9%
Decimal Number 29
 
0.7%
Other Punctuation 28
 
0.6%
Open Punctuation 24
 
0.5%
Close Punctuation 24
 
0.5%
Math Symbol 3
 
0.1%
Final Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 405
12.5%
o 360
11.1%
n 343
10.6%
a 297
 
9.2%
g 213
 
6.6%
r 197
 
6.1%
i 197
 
6.1%
t 174
 
5.4%
u 145
 
4.5%
l 129
 
4.0%
Other values (16) 780
24.1%
Uppercase Letter
ValueCountFrequency (%)
S 75
14.1%
M 55
 
10.4%
C 52
 
9.8%
B 42
 
7.9%
P 30
 
5.6%
A 26
 
4.9%
T 25
 
4.7%
H 24
 
4.5%
D 23
 
4.3%
F 21
 
4.0%
Other values (14) 158
29.8%
Decimal Number
ValueCountFrequency (%)
0 9
31.0%
1 6
20.7%
9 5
17.2%
5 4
13.8%
6 2
 
6.9%
7 2
 
6.9%
8 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 14
50.0%
' 10
35.7%
& 2
 
7.1%
. 2
 
7.1%
Space Separator
ValueCountFrequency (%)
495
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3771
85.4%
Common 645
 
14.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 405
 
10.7%
o 360
 
9.5%
n 343
 
9.1%
a 297
 
7.9%
g 213
 
5.6%
r 197
 
5.2%
i 197
 
5.2%
t 174
 
4.6%
u 145
 
3.8%
l 129
 
3.4%
Other values (40) 1311
34.8%
Common
ValueCountFrequency (%)
495
76.7%
- 40
 
6.2%
( 24
 
3.7%
) 24
 
3.7%
, 14
 
2.2%
' 10
 
1.6%
0 9
 
1.4%
1 6
 
0.9%
9 5
 
0.8%
5 4
 
0.6%
Other values (7) 14
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4414
> 99.9%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
495
 
11.2%
e 405
 
9.2%
o 360
 
8.2%
n 343
 
7.8%
a 297
 
6.7%
g 213
 
4.8%
r 197
 
4.5%
i 197
 
4.5%
t 174
 
3.9%
u 145
 
3.3%
Other values (56) 1588
36.0%
Punctuation
ValueCountFrequency (%)
2
100.0%

관련항목
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing139
Missing (%)100.0%
Memory size1.4 KiB

연계자원
Text

MISSING 

Distinct85
Distinct (%)100.0%
Missing54
Missing (%)38.8%
Memory size1.2 KiB
2024-04-18T16:54:51.839713image/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_000360 1
 
1.2%
jgh_001149 1
 
1.2%
jgh_000669 1
 
1.2%
jgh_000820 1
 
1.2%
jgh_000381 1
 
1.2%
jgh_000018 1
 
1.2%
jgh_000036 1
 
1.2%
jgh_000462 1
 
1.2%
jgh_000526 1
 
1.2%
jgh_000097 1
 
1.2%
Other values (75) 75
88.2%
2024-04-18T16:54:52.220741image/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)

Distinct136
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.99109
Minimum126.97063
Maximum127.03793
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-18T16:54:52.362914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.97063
5-th percentile126.97261
Q1126.98046
median126.98598
Q3127.00282
95-th percentile127.0176
Maximum127.03793
Range0.067301
Interquartile range (IQR)0.022365

Descriptive statistics

Standard deviation0.015043339
Coefficient of variation (CV)0.0001184598
Kurtosis0.11521607
Mean126.99109
Median Absolute Deviation (MAD)0.00938
Skewness0.87087351
Sum17651.761
Variance0.00022630206
MonotonicityNot monotonic
2024-04-18T16:54:52.496171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.98378 2
 
1.4%
126.98187 2
 
1.4%
126.97063 2
 
1.4%
126.98283 1
 
0.7%
126.98517 1
 
0.7%
126.98468 1
 
0.7%
126.98509 1
 
0.7%
126.9846 1
 
0.7%
126.98455 1
 
0.7%
126.9849 1
 
0.7%
Other values (126) 126
90.6%
ValueCountFrequency (%)
126.97063 2
1.4%
126.97133 1
0.7%
126.97146 1
0.7%
126.97217 1
0.7%
126.97236 1
0.7%
126.97252 1
0.7%
126.97262 1
0.7%
126.97285 1
0.7%
126.97294 1
0.7%
126.97337 1
0.7%
ValueCountFrequency (%)
127.037931 1
0.7%
127.033545 1
0.7%
127.030354 1
0.7%
127.026658 1
0.7%
127.025354 1
0.7%
127.023407 1
0.7%
127.01905 1
0.7%
127.017441 1
0.7%
127.015917 1
0.7%
127.01503 1
0.7%

위도정보(36.XXX)
Real number (ℝ)

Distinct134
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.563656
Minimum37.55116
Maximum37.572332
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-18T16:54:52.632747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.55116
5-th percentile37.552521
Q137.559335
median37.56481
Q337.56853
95-th percentile37.569886
Maximum37.572332
Range0.021172
Interquartile range (IQR)0.0091955

Descriptive statistics

Standard deviation0.0055815617
Coefficient of variation (CV)0.00014858941
Kurtosis-0.6104961
Mean37.563656
Median Absolute Deviation (MAD)0.00385
Skewness-0.66687544
Sum5221.3482
Variance3.1153831 × 10-5
MonotonicityNot monotonic
2024-04-18T16:54:52.756797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.56339 3
 
2.2%
37.569794 2
 
1.4%
37.568862 2
 
1.4%
37.5662 2
 
1.4%
37.56394 1
 
0.7%
37.56255 1
 
0.7%
37.56231 1
 
0.7%
37.56125 1
 
0.7%
37.56275 1
 
0.7%
37.56303 1
 
0.7%
Other values (124) 124
89.2%
ValueCountFrequency (%)
37.55116 1
0.7%
37.55139 1
0.7%
37.55159 1
0.7%
37.55164 1
0.7%
37.55184 1
0.7%
37.55201 1
0.7%
37.55235 1
0.7%
37.55254 1
0.7%
37.55284 1
0.7%
37.55347 1
0.7%
ValueCountFrequency (%)
37.572332 1
0.7%
37.571725 1
0.7%
37.571037 1
0.7%
37.571027 1
0.7%
37.570804 1
0.7%
37.57076 1
0.7%
37.570278 1
0.7%
37.569842 1
0.7%
37.569826 1
0.7%
37.569794 2
1.4%

이명칭
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing134
Missing (%)96.4%
Memory size1.2 KiB
2024-04-18T16:54:52.909968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length39
Mean length33.6
Min length12

Characters and Unicode

Total characters168
Distinct characters35
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
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 rowGyeongungung Palace, Temporary Palace at Jeongneung-dong, West Palace
2nd rowSeoul Anglican Cathedral
3rd rowMISO Theater
4th rowYi Royal Family Museum, Yi Royal Museum
5th rowKorea Freedom Federation
ValueCountFrequency (%)
palace 3
 
13.0%
museum 2
 
8.7%
royal 2
 
8.7%
yi 2
 
8.7%
gyeongungung 1
 
4.3%
freedom 1
 
4.3%
korea 1
 
4.3%
family 1
 
4.3%
theater 1
 
4.3%
miso 1
 
4.3%
Other values (8) 8
34.8%
2024-04-18T16:54:53.195460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 19
 
11.3%
18
 
10.7%
a 17
 
10.1%
o 10
 
6.0%
n 10
 
6.0%
l 9
 
5.4%
u 8
 
4.8%
r 7
 
4.2%
g 7
 
4.2%
t 5
 
3.0%
Other values (25) 58
34.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 121
72.0%
Uppercase Letter 25
 
14.9%
Space Separator 18
 
10.7%
Other Punctuation 3
 
1.8%
Dash Punctuation 1
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 19
15.7%
a 17
14.0%
o 10
8.3%
n 10
8.3%
l 9
 
7.4%
u 8
 
6.6%
r 7
 
5.8%
g 7
 
5.8%
t 5
 
4.1%
i 5
 
4.1%
Other values (7) 24
19.8%
Uppercase Letter
ValueCountFrequency (%)
M 3
12.0%
F 3
12.0%
P 3
12.0%
R 2
 
8.0%
Y 2
 
8.0%
S 2
 
8.0%
T 2
 
8.0%
O 1
 
4.0%
I 1
 
4.0%
G 1
 
4.0%
Other values (5) 5
20.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 146
86.9%
Common 22
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 19
 
13.0%
a 17
 
11.6%
o 10
 
6.8%
n 10
 
6.8%
l 9
 
6.2%
u 8
 
5.5%
r 7
 
4.8%
g 7
 
4.8%
t 5
 
3.4%
i 5
 
3.4%
Other values (22) 49
33.6%
Common
ValueCountFrequency (%)
18
81.8%
, 3
 
13.6%
- 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 168
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 19
 
11.3%
18
 
10.7%
a 17
 
10.1%
o 10
 
6.0%
n 10
 
6.0%
l 9
 
5.4%
u 8
 
4.8%
r 7
 
4.2%
g 7
 
4.2%
t 5
 
3.0%
Other values (25) 58
34.5%

개요
Text

UNIQUE 

Distinct139
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-18T16:54:53.542304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length878
Median length250
Mean length226.13669
Min length30

Characters and Unicode

Total characters31433
Distinct characters84
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique139 ?
Unique (%)100.0%

Sample

1st rowIt was originally called Gyeongungung Palace but has been called Deoksugung Palace since 1907. Gates, pavilions and halls including Daehanmun Gate, Junghwamun Gate, Gwangmyeongmun Gate, Junghwajeong Hall, Junmyeongdang Hall, Seogeodang Hall, Seokjojeon Hall, Hamnyeongjeon Hall, and Jeukjodang Hall still remain in 61,500㎡ land.
2nd rowJungmyeongjeon Hall, constructed in 1901, is a part of Gyeongungung which is today’s Deoksugung Palace, and it was used as the reception hall, banquet hall, and library. This was the place the banquet was held during the wedding ceremony of the Crown Prince (Sunjong) and Crown Princess Yun in 1907 and also the unfortunate place where the Japan-Korea Treaty of 1905 was concluded by force. It had been leased to foreigners in 1915 during Japanese colonial era and used as Seoul Club building.
3rd rowHwangudan Altar is the space where the emperor held memorial service for heaven. This is where Emperor Gwangmu of the Korean Empire which succeeded to the Joseon Empire held memorial service for heaven. Hwangudan Altar was completed in 1897 and was designed by Sim Eui-seok, the master builder for the imperial family at the time.
4th rowThis is the renaissance style building designed by A. I. Sabatin of Russia in 1890 (Gojong 27). The main building was destroyed during the Korean War, and currently only the 3-story tower remains. This is famous for King Gojong’s refuge to avoid Japan’s pressure using force.
5th rowChungdong First Methodist Church is a protestant church chapel, and construction of the church began in 1895 (Gojong 32) and was completed in October 1897 (Gwangmu 1).
ValueCountFrequency (%)
the 436
 
8.4%
of 247
 
4.8%
and 211
 
4.1%
in 197
 
3.8%
was 131
 
2.5%
to 81
 
1.6%
it 78
 
1.5%
a 77
 
1.5%
is 71
 
1.4%
for 56
 
1.1%
Other values (1454) 3575
69.3%
2024-04-18T16:54:54.078516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5021
16.0%
e 3009
 
9.6%
a 2126
 
6.8%
n 2112
 
6.7%
o 1972
 
6.3%
t 1946
 
6.2%
i 1658
 
5.3%
r 1428
 
4.5%
s 1409
 
4.5%
h 1059
 
3.4%
Other values (74) 9693
30.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 23670
75.3%
Space Separator 5021
 
16.0%
Uppercase Letter 1320
 
4.2%
Decimal Number 741
 
2.4%
Other Punctuation 449
 
1.4%
Dash Punctuation 93
 
0.3%
Final Punctuation 51
 
0.2%
Open Punctuation 30
 
0.1%
Close Punctuation 30
 
0.1%
Initial Punctuation 15
 
< 0.1%
Other values (4) 13
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3009
12.7%
a 2126
 
9.0%
n 2112
 
8.9%
o 1972
 
8.3%
t 1946
 
8.2%
i 1658
 
7.0%
r 1428
 
6.0%
s 1409
 
6.0%
h 1059
 
4.5%
d 988
 
4.2%
Other values (16) 5963
25.2%
Uppercase Letter
ValueCountFrequency (%)
S 161
12.2%
C 113
 
8.6%
T 112
 
8.5%
M 99
 
7.5%
K 96
 
7.3%
J 94
 
7.1%
G 78
 
5.9%
H 64
 
4.8%
I 64
 
4.8%
N 61
 
4.6%
Other values (15) 378
28.6%
Decimal Number
ValueCountFrequency (%)
1 174
23.5%
9 146
19.7%
0 111
15.0%
2 56
 
7.6%
5 50
 
6.7%
8 47
 
6.3%
6 43
 
5.8%
7 43
 
5.8%
3 42
 
5.7%
4 29
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 221
49.2%
. 215
47.9%
' 11
 
2.4%
: 2
 
0.4%
Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Math Symbol
ValueCountFrequency (%)
~ 5
71.4%
> 1
 
14.3%
< 1
 
14.3%
Final Punctuation
ValueCountFrequency (%)
50
98.0%
1
 
2.0%
Open Punctuation
ValueCountFrequency (%)
( 29
96.7%
1
 
3.3%
Close Punctuation
ValueCountFrequency (%)
) 29
96.7%
1
 
3.3%
Initial Punctuation
ValueCountFrequency (%)
12
80.0%
3
 
20.0%
Space Separator
ValueCountFrequency (%)
5021
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 93
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Other Number
ValueCountFrequency (%)
² 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24990
79.5%
Common 6439
 
20.5%
Han 4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3009
12.0%
a 2126
 
8.5%
n 2112
 
8.5%
o 1972
 
7.9%
t 1946
 
7.8%
i 1658
 
6.6%
r 1428
 
5.7%
s 1409
 
5.6%
h 1059
 
4.2%
d 988
 
4.0%
Other values (41) 7283
29.1%
Common
ValueCountFrequency (%)
5021
78.0%
, 221
 
3.4%
. 215
 
3.3%
1 174
 
2.7%
9 146
 
2.3%
0 111
 
1.7%
- 93
 
1.4%
2 56
 
0.9%
50
 
0.8%
5 50
 
0.8%
Other values (19) 302
 
4.7%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31359
99.8%
Punctuation 66
 
0.2%
CJK 4
 
< 0.1%
None 3
 
< 0.1%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5021
16.0%
e 3009
 
9.6%
a 2126
 
6.8%
n 2112
 
6.7%
o 1972
 
6.3%
t 1946
 
6.2%
i 1658
 
5.3%
r 1428
 
4.6%
s 1409
 
4.5%
h 1059
 
3.4%
Other values (62) 9619
30.7%
Punctuation
ValueCountFrequency (%)
50
75.8%
12
 
18.2%
3
 
4.5%
1
 
1.5%
None
ValueCountFrequency (%)
1
33.3%
1
33.3%
² 1
33.3%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
CJK Compat
ValueCountFrequency (%)
1
100.0%

시대분류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing139
Missing (%)100.0%
Memory size1.4 KiB

주제분류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing139
Missing (%)100.0%
Memory size1.4 KiB

지번주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing139
Missing (%)100.0%
Memory size1.4 KiB
Distinct87
Distinct (%)62.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-18T16:54:54.280417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length64
Mean length34.172662
Min length14

Characters and Unicode

Total characters4750
Distinct characters61
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

Unique74 ?
Unique (%)53.2%

Sample

1st row99, Sejong-daero, Jung-gu, Seoul
2nd row41-11, Jeongdong-gil, Jung-gu, Seoul
3rd row106, Sogong-ro, Jung-gu, Seoul
4th rowJeong-dong Park, 21-18, Jeongdong-gil, Jung-gu, Seoul
5th rowChungdong First Methodist Church, 46, Jeongdong-gil, Jung-gu, Seoul
ValueCountFrequency (%)
seoul 140
24.9%
jung-gu 101
18.0%
jung-gu/jongno-gu 19
 
3.4%
myeong-dong 13
 
2.3%
sejong-daero 10
 
1.8%
toegye-ro 9
 
1.6%
cheonggyecheon 9
 
1.6%
jeongdong-gil 8
 
1.4%
2-ga 8
 
1.4%
jangchung-dong 7
 
1.2%
Other values (136) 238
42.3%
2024-04-18T16:54:54.604654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
g 536
11.3%
u 465
 
9.8%
o 431
 
9.1%
423
 
8.9%
n 392
 
8.3%
, 346
 
7.3%
- 313
 
6.6%
e 287
 
6.0%
l 197
 
4.1%
S 175
 
3.7%
Other values (51) 1185
24.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2866
60.3%
Uppercase Letter 475
 
10.0%
Space Separator 423
 
8.9%
Other Punctuation 373
 
7.9%
Dash Punctuation 313
 
6.6%
Decimal Number 290
 
6.1%
Close Punctuation 5
 
0.1%
Open Punctuation 5
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
g 536
18.7%
u 465
16.2%
o 431
15.0%
n 392
13.7%
e 287
10.0%
l 197
 
6.9%
a 113
 
3.9%
d 89
 
3.1%
r 70
 
2.4%
i 54
 
1.9%
Other values (12) 232
8.1%
Uppercase Letter
ValueCountFrequency (%)
S 175
36.8%
J 168
35.4%
M 22
 
4.6%
D 15
 
3.2%
C 14
 
2.9%
N 14
 
2.9%
T 11
 
2.3%
I 9
 
1.9%
E 9
 
1.9%
P 8
 
1.7%
Other values (10) 30
 
6.3%
Decimal Number
ValueCountFrequency (%)
1 69
23.8%
2 51
17.6%
5 29
10.0%
3 22
 
7.6%
4 22
 
7.6%
0 21
 
7.2%
6 20
 
6.9%
9 20
 
6.9%
7 19
 
6.6%
8 17
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 346
92.8%
/ 24
 
6.4%
. 1
 
0.3%
& 1
 
0.3%
' 1
 
0.3%
Space Separator
ValueCountFrequency (%)
423
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 313
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3341
70.3%
Common 1409
29.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
g 536
16.0%
u 465
13.9%
o 431
12.9%
n 392
11.7%
e 287
8.6%
l 197
 
5.9%
S 175
 
5.2%
J 168
 
5.0%
a 113
 
3.4%
d 89
 
2.7%
Other values (32) 488
14.6%
Common
ValueCountFrequency (%)
423
30.0%
, 346
24.6%
- 313
22.2%
1 69
 
4.9%
2 51
 
3.6%
5 29
 
2.1%
/ 24
 
1.7%
3 22
 
1.6%
4 22
 
1.6%
0 21
 
1.5%
Other values (9) 89
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4750
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
g 536
11.3%
u 465
 
9.8%
o 431
 
9.1%
423
 
8.9%
n 392
 
8.3%
, 346
 
7.3%
- 313
 
6.6%
e 287
 
6.0%
l 197
 
4.1%
S 175
 
3.7%
Other values (51) 1185
24.9%

지역
Categorical

Distinct23
Distinct (%)16.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
39 
Myeong-dong, Jung-gu, Seoul
13 
Sejong-daero, Jung-gu, Seoul
10 
Toegye-ro, Jung-gu, Seoul
Jeongdong-gil, Jung-gu, Seoul
Other values (18)
60 

Length

Max length33
Median length31
Mean length20.870504
Min length4

Unique

Unique3 ?
Unique (%)2.2%

Sample

1st rowSejong-daero, Jung-gu, Seoul
2nd rowJeongdong-gil, Jung-gu, Seoul
3rd rowSogong-ro, Jung-gu, Seoul
4th rowJeongdong-gil, Jung-gu, Seoul
5th rowJeongdong-gil, Jung-gu, Seoul

Common Values

ValueCountFrequency (%)
<NA> 39
28.1%
Myeong-dong, Jung-gu, Seoul 13
 
9.4%
Sejong-daero, Jung-gu, Seoul 10
 
7.2%
Toegye-ro, Jung-gu, Seoul 9
 
6.5%
Jeongdong-gil, Jung-gu, Seoul 8
 
5.8%
Sopa-ro, Jung-gu, Seoul 6
 
4.3%
Myeongdong-gil, Jung-gu, Seoul 6
 
4.3%
Eulji-ro, Jung-gu, Seoul 5
 
3.6%
Jangchungdan-ro, Jung-gu, Seoul 5
 
3.6%
Jangchung-dong, Jung-gu, Seoul 5
 
3.6%
Other values (13) 33
23.7%

Length

2024-04-18T16:54:54.731045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
jung-gu 100
29.4%
seoul 100
29.4%
na 39
 
11.5%
myeong-dong 13
 
3.8%
sejong-daero 10
 
2.9%
toegye-ro 9
 
2.6%
jeongdong-gil 8
 
2.4%
sopa-ro 6
 
1.8%
myeongdong-gil 6
 
1.8%
eulji-ro 5
 
1.5%
Other values (16) 44
12.9%

제공기관
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Jung-gu?Office?Seoul?
100 
Seoul Metropolitan Government
39 

Length

Max length29
Median length21
Mean length23.244604
Min length21

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJung-gu?Office?Seoul?
2nd rowJung-gu?Office?Seoul?
3rd rowJung-gu?Office?Seoul?
4th rowJung-gu?Office?Seoul?
5th rowJung-gu?Office?Seoul?

Common Values

ValueCountFrequency (%)
Jung-gu?Office?Seoul? 100
71.9%
Seoul Metropolitan Government 39
 
28.1%

Length

2024-04-18T16:54:54.849024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:54:54.948811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
jung-gu?office?seoul 100
46.1%
seoul 39
 
18.0%
metropolitan 39
 
18.0%
government 39
 
18.0%

언어유형
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
ENG
139 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
ENG 139
100.0%

Length

2024-04-18T16:54:55.054504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:54:55.140204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
eng 139
100.0%

제작일
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2015-12-30
100 
<NA>
39 

Length

Max length10
Median length10
Mean length8.3165468
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015-12-30
2nd row2015-12-30
3rd row2015-12-30
4th row2015-12-30
5th row2015-12-30

Common Values

ValueCountFrequency (%)
2015-12-30 100
71.9%
<NA> 39
 
28.1%

Length

2024-04-18T16:54:55.234374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:54:55.327670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015-12-30 100
71.9%
na 39
 
28.1%

유형
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
DATA
139 

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 139
100.0%

Length

2024-04-18T16:54:55.429080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:54:55.524163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
data 139
100.0%

형식
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
HTML
139 

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 139
100.0%

Length

2024-04-18T16:54:55.615617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:54:55.712033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
html 139
100.0%

전화번호
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing107
Missing (%)77.0%
Memory size1.2 KiB
2024-04-18T16:54:55.920042image/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 row02-730-6611
5th row02-777-4258
ValueCountFrequency (%)
02-753-2403 1
 
3.0%
1588-1234 1
 
3.0%
02-3455-8341 1
 
3.0%
02-779-6107 1
 
3.0%
02-753-2805 1
 
3.0%
02-2280-4114 1
 
3.0%
02-774-1784 1
 
3.0%
02-759-4881 1
 
3.0%
02-771-9951 1
 
3.0%
02-3455-9277 1
 
3.0%
Other values (23) 23
69.7%
2024-04-18T16:54:56.265382image/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%
Missing119
Missing (%)85.6%
Memory size1.2 KiB
2024-04-18T16:54:56.435073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length35
Mean length31.75
Min length21

Characters and Unicode

Total characters635
Distinct characters36
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
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 rowHistorical Site No. 124
2nd rowSeoul Monument No. 16
3rd rowRegistered Cultural Heritage No. 237
4th rowRegistered Cultural Heritage No. 267
5th rowRegistered Cultural Heritage No. 402
ValueCountFrequency (%)
no 20
19.8%
cultural 12
11.9%
heritage 12
11.9%
registered 8
 
7.9%
seoul 7
 
6.9%
historical 4
 
4.0%
site 4
 
4.0%
tangible 4
 
4.0%
of 4
 
4.0%
20 2
 
2.0%
Other values (21) 24
23.8%
2024-04-18T16:54:56.706524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
81
12.8%
e 69
 
10.9%
t 44
 
6.9%
l 43
 
6.8%
o 40
 
6.3%
r 40
 
6.3%
i 38
 
6.0%
a 37
 
5.8%
u 34
 
5.4%
g 24
 
3.8%
Other values (26) 185
29.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 414
65.2%
Space Separator 81
 
12.8%
Uppercase Letter 77
 
12.1%
Decimal Number 43
 
6.8%
Other Punctuation 20
 
3.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 69
16.7%
t 44
10.6%
l 43
10.4%
o 40
9.7%
r 40
9.7%
i 38
9.2%
a 37
8.9%
u 34
8.2%
g 24
 
5.8%
s 13
 
3.1%
Other values (7) 32
7.7%
Decimal Number
ValueCountFrequency (%)
1 10
23.3%
2 10
23.3%
0 5
11.6%
3 4
 
9.3%
8 3
 
7.0%
5 3
 
7.0%
7 3
 
7.0%
4 3
 
7.0%
6 2
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
N 21
27.3%
H 16
20.8%
C 12
15.6%
S 11
14.3%
R 8
 
10.4%
T 5
 
6.5%
M 3
 
3.9%
F 1
 
1.3%
Space Separator
ValueCountFrequency (%)
81
100.0%
Other Punctuation
ValueCountFrequency (%)
. 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 491
77.3%
Common 144
 
22.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 69
14.1%
t 44
9.0%
l 43
8.8%
o 40
 
8.1%
r 40
 
8.1%
i 38
 
7.7%
a 37
 
7.5%
u 34
 
6.9%
g 24
 
4.9%
N 21
 
4.3%
Other values (15) 101
20.6%
Common
ValueCountFrequency (%)
81
56.2%
. 20
 
13.9%
1 10
 
6.9%
2 10
 
6.9%
0 5
 
3.5%
3 4
 
2.8%
8 3
 
2.1%
5 3
 
2.1%
7 3
 
2.1%
4 3
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 635
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
81
12.8%
e 69
 
10.9%
t 44
 
6.9%
l 43
 
6.8%
o 40
 
6.3%
r 40
 
6.3%
i 38
 
6.0%
a 37
 
5.8%
u 34
 
5.4%
g 24
 
3.8%
Other values (26) 185
29.1%

휴무일
Text

MISSING 

Distinct9
Distinct (%)64.3%
Missing125
Missing (%)89.9%
Memory size1.2 KiB
2024-04-18T16:54:56.868079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length97
Median length38.5
Mean length22.785714
Min length7

Characters and Unicode

Total characters319
Distinct characters38
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
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 rowMondays
2nd rowMondays, Holidays
3rd rowMondays, January 1
4th rowSundays
5th rowMondays, January 1
ValueCountFrequency (%)
mondays 10
21.3%
holidays 5
10.6%
1 4
 
8.5%
january 4
 
8.5%
sundays 3
 
6.4%
day 3
 
6.4%
year's 2
 
4.3%
chuseok 2
 
4.3%
new 2
 
4.3%
lunar 2
 
4.3%
Other values (10) 10
21.3%
2024-04-18T16:54:57.126718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 40
12.5%
33
 
10.3%
y 28
 
8.8%
s 26
 
8.2%
n 22
 
6.9%
o 20
 
6.3%
d 20
 
6.3%
e 13
 
4.1%
u 13
 
4.1%
, 13
 
4.1%
Other values (28) 91
28.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 222
69.6%
Uppercase Letter 41
 
12.9%
Space Separator 33
 
10.3%
Other Punctuation 15
 
4.7%
Decimal Number 7
 
2.2%
Math Symbol 1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 40
18.0%
y 28
12.6%
s 26
11.7%
n 22
9.9%
o 20
9.0%
d 20
9.0%
e 13
 
5.9%
u 13
 
5.9%
r 12
 
5.4%
l 7
 
3.2%
Other values (10) 21
9.5%
Uppercase Letter
ValueCountFrequency (%)
M 10
24.4%
J 5
12.2%
H 5
12.2%
D 5
12.2%
Y 3
 
7.3%
L 3
 
7.3%
S 3
 
7.3%
N 2
 
4.9%
C 2
 
4.9%
F 2
 
4.9%
Decimal Number
ValueCountFrequency (%)
1 4
57.1%
2 2
28.6%
9 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
, 13
86.7%
' 2
 
13.3%
Space Separator
ValueCountFrequency (%)
33
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 263
82.4%
Common 56
 
17.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 40
15.2%
y 28
10.6%
s 26
9.9%
n 22
 
8.4%
o 20
 
7.6%
d 20
 
7.6%
e 13
 
4.9%
u 13
 
4.9%
r 12
 
4.6%
M 10
 
3.8%
Other values (21) 59
22.4%
Common
ValueCountFrequency (%)
33
58.9%
, 13
 
23.2%
1 4
 
7.1%
' 2
 
3.6%
2 2
 
3.6%
~ 1
 
1.8%
9 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 40
12.5%
33
 
10.3%
y 28
 
8.8%
s 26
 
8.2%
n 22
 
6.9%
o 20
 
6.3%
d 20
 
6.3%
e 13
 
4.1%
u 13
 
4.1%
, 13
 
4.1%
Other values (28) 91
28.5%

이용시간
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing130
Missing (%)93.5%
Memory size1.2 KiB
2024-04-18T16:54:57.272024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length69
Mean length32.444444
Min length13

Characters and Unicode

Total characters292
Distinct characters37
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
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 rowTicketing and Admission Time 09:00 ~ 20:00 Closing Time 09:00 ~ 21:00
2nd rowEveryday 10:00 ~ 17:00
3rd rowWeekdays 09:00 ~ 21:00
4th row09:00 ~ 18:00
5th rowTuesday ~ Sunday 10:00 ~ 18:00
ValueCountFrequency (%)
12
22.6%
10:00 5
9.4%
17:00 5
9.4%
09:00 4
 
7.5%
sunday 3
 
5.7%
20:00 3
 
5.7%
18:00 3
 
5.7%
time 2
 
3.8%
21:00 2
 
3.8%
and 2
 
3.8%
Other values (11) 12
22.6%
2024-04-18T16:54:57.544403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 58
19.9%
46
15.8%
: 23
 
7.9%
1 16
 
5.5%
a 14
 
4.8%
d 14
 
4.8%
~ 12
 
4.1%
y 12
 
4.1%
n 9
 
3.1%
i 9
 
3.1%
Other values (27) 79
27.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 99
33.9%
Decimal Number 92
31.5%
Space Separator 46
15.8%
Other Punctuation 27
 
9.2%
Uppercase Letter 16
 
5.5%
Math Symbol 12
 
4.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 14
14.1%
d 14
14.1%
y 12
12.1%
n 9
9.1%
i 9
9.1%
e 8
8.1%
s 7
7.1%
u 6
6.1%
o 4
 
4.0%
r 3
 
3.0%
Other values (7) 13
13.1%
Uppercase Letter
ValueCountFrequency (%)
T 5
31.2%
S 4
25.0%
E 1
 
6.2%
W 1
 
6.2%
C 1
 
6.2%
M 1
 
6.2%
F 1
 
6.2%
A 1
 
6.2%
H 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
0 58
63.0%
1 16
 
17.4%
7 5
 
5.4%
2 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 (%)
46
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 177
60.6%
Latin 115
39.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 14
12.2%
d 14
12.2%
y 12
10.4%
n 9
 
7.8%
i 9
 
7.8%
e 8
 
7.0%
s 7
 
6.1%
u 6
 
5.2%
T 5
 
4.3%
S 4
 
3.5%
Other values (16) 27
23.5%
Common
ValueCountFrequency (%)
0 58
32.8%
46
26.0%
: 23
 
13.0%
1 16
 
9.0%
~ 12
 
6.8%
7 5
 
2.8%
2 5
 
2.8%
9 4
 
2.3%
, 4
 
2.3%
8 3
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 292
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 58
19.9%
46
15.8%
: 23
 
7.9%
1 16
 
5.5%
a 14
 
4.8%
d 14
 
4.8%
~ 12
 
4.1%
y 12
 
4.1%
n 9
 
3.1%
i 9
 
3.1%
Other values (27) 79
27.1%

이용요금
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
131 
Free
 
7
Adult (25 or over) 1,000 wonAdult Group (10 or more) 800 won
 
1

Length

Max length60
Median length4
Mean length4.4028777
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st rowAdult (25 or over) 1,000 wonAdult Group (10 or more) 800 won
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 131
94.2%
Free 7
 
5.0%
Adult (25 or over) 1,000 wonAdult Group (10 or more) 800 won 1
 
0.7%

Length

2024-04-18T16:54:57.668132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:54:57.767818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 131
87.3%
free 7
 
4.7%
or 2
 
1.3%
adult 1
 
0.7%
25 1
 
0.7%
over 1
 
0.7%
1,000 1
 
0.7%
wonadult 1
 
0.7%
group 1
 
0.7%
10 1
 
0.7%
Other values (3) 3
 
2.0%

주차
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
128 
Parking space available
 
11

Length

Max length23
Median length4
Mean length5.5035971
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th rowParking space available

Common Values

ValueCountFrequency (%)
<NA> 128
92.1%
Parking space available 11
 
7.9%

Length

2024-04-18T16:54:58.212111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:54:58.321646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 128
79.5%
parking 11
 
6.8%
space 11
 
6.8%
available 11
 
6.8%
Distinct3
Distinct (%)100.0%
Missing136
Missing (%)97.8%
Memory size1.2 KiB
2024-04-18T16:54:58.461161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length41
Mean length39.666667
Min length17

Characters and Unicode

Total characters119
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
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 rowWheelchair rental
2nd rowGroup visit by challenged people, braille guidebook available
3rd rowToilet and elevator for challenged people
ValueCountFrequency (%)
challenged 2
12.5%
people 2
12.5%
wheelchair 1
 
6.2%
rental 1
 
6.2%
group 1
 
6.2%
visit 1
 
6.2%
by 1
 
6.2%
braille 1
 
6.2%
guidebook 1
 
6.2%
available 1
 
6.2%
Other values (4) 4
25.0%
2024-04-18T16:54:58.724779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 17
14.3%
l 14
11.8%
13
10.9%
a 10
 
8.4%
o 8
 
6.7%
i 7
 
5.9%
r 6
 
5.0%
p 5
 
4.2%
h 4
 
3.4%
b 4
 
3.4%
Other values (15) 31
26.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 102
85.7%
Space Separator 13
 
10.9%
Uppercase Letter 3
 
2.5%
Other Punctuation 1
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 17
16.7%
l 14
13.7%
a 10
9.8%
o 8
 
7.8%
i 7
 
6.9%
r 6
 
5.9%
p 5
 
4.9%
h 4
 
3.9%
b 4
 
3.9%
t 4
 
3.9%
Other values (10) 23
22.5%
Uppercase Letter
ValueCountFrequency (%)
T 1
33.3%
W 1
33.3%
G 1
33.3%
Space Separator
ValueCountFrequency (%)
13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 105
88.2%
Common 14
 
11.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 17
16.2%
l 14
13.3%
a 10
 
9.5%
o 8
 
7.6%
i 7
 
6.7%
r 6
 
5.7%
p 5
 
4.8%
h 4
 
3.8%
b 4
 
3.8%
t 4
 
3.8%
Other values (13) 26
24.8%
Common
ValueCountFrequency (%)
13
92.9%
, 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 119
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 17
14.3%
l 14
11.8%
13
10.9%
a 10
 
8.4%
o 8
 
6.7%
i 7
 
5.9%
r 6
 
5.0%
p 5
 
4.2%
h 4
 
3.4%
b 4
 
3.4%
Other values (15) 31
26.1%

체험안내
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing136
Missing (%)97.8%
Memory size1.2 KiB
2024-04-18T16:54:58.893397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length127
Median length63
Mean length73
Min length29

Characters and Unicode

Total characters219
Distinct characters32
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
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 rowTry Korean Traditional Clothes, Changing of the Guards Ceremony
2nd rowDouble-headed drum experience
3rd rowHanpung Cultural Experience, photograph shooting service, straw crafts demonstration, comments on traditional cultural heritage
ValueCountFrequency (%)
experience 2
 
7.7%
traditional 2
 
7.7%
cultural 2
 
7.7%
hanpung 1
 
3.8%
on 1
 
3.8%
comments 1
 
3.8%
demonstration 1
 
3.8%
crafts 1
 
3.8%
straw 1
 
3.8%
service 1
 
3.8%
Other values (13) 13
50.0%
2024-04-18T16:54:59.168471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23
 
10.5%
e 21
 
9.6%
r 17
 
7.8%
a 16
 
7.3%
o 15
 
6.8%
n 15
 
6.8%
t 15
 
6.8%
i 11
 
5.0%
s 8
 
3.7%
u 8
 
3.7%
Other values (22) 70
32.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 180
82.2%
Space Separator 23
 
10.5%
Uppercase Letter 11
 
5.0%
Other Punctuation 4
 
1.8%
Dash Punctuation 1
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 21
11.7%
r 17
 
9.4%
a 16
 
8.9%
o 15
 
8.3%
n 15
 
8.3%
t 15
 
8.3%
i 11
 
6.1%
s 8
 
4.4%
u 8
 
4.4%
l 8
 
4.4%
Other values (12) 46
25.6%
Uppercase Letter
ValueCountFrequency (%)
C 4
36.4%
T 2
18.2%
G 1
 
9.1%
D 1
 
9.1%
K 1
 
9.1%
H 1
 
9.1%
E 1
 
9.1%
Space Separator
ValueCountFrequency (%)
23
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 191
87.2%
Common 28
 
12.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 21
 
11.0%
r 17
 
8.9%
a 16
 
8.4%
o 15
 
7.9%
n 15
 
7.9%
t 15
 
7.9%
i 11
 
5.8%
s 8
 
4.2%
u 8
 
4.2%
l 8
 
4.2%
Other values (19) 57
29.8%
Common
ValueCountFrequency (%)
23
82.1%
, 4
 
14.3%
- 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 219
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23
 
10.5%
e 21
 
9.6%
r 17
 
7.8%
a 16
 
7.3%
o 15
 
6.8%
n 15
 
6.8%
t 15
 
6.8%
i 11
 
5.0%
s 8
 
3.7%
u 8
 
3.7%
Other values (22) 70
32.0%

안내서비스
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing138
Missing (%)99.3%
Memory size1.2 KiB
2024-04-18T16:54:59.301481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length34
Mean length34
Min length34

Characters and Unicode

Total characters34
Distinct characters17
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

Unique1 ?
Unique (%)100.0%

Sample

1st rowMultilingual Voice Guide available
ValueCountFrequency (%)
multilingual 1
25.0%
voice 1
25.0%
guide 1
25.0%
available 1
25.0%
2024-04-18T16:54:59.545922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 5
14.7%
i 5
14.7%
a 4
11.8%
3
8.8%
u 3
8.8%
e 3
8.8%
c 1
 
2.9%
v 1
 
2.9%
d 1
 
2.9%
G 1
 
2.9%
Other values (7) 7
20.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 28
82.4%
Space Separator 3
 
8.8%
Uppercase Letter 3
 
8.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 5
17.9%
i 5
17.9%
a 4
14.3%
u 3
10.7%
e 3
10.7%
c 1
 
3.6%
v 1
 
3.6%
d 1
 
3.6%
o 1
 
3.6%
g 1
 
3.6%
Other values (3) 3
10.7%
Uppercase Letter
ValueCountFrequency (%)
G 1
33.3%
M 1
33.3%
V 1
33.3%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 31
91.2%
Common 3
 
8.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 5
16.1%
i 5
16.1%
a 4
12.9%
u 3
9.7%
e 3
9.7%
c 1
 
3.2%
v 1
 
3.2%
d 1
 
3.2%
G 1
 
3.2%
M 1
 
3.2%
Other values (6) 6
19.4%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 5
14.7%
i 5
14.7%
a 4
11.8%
3
8.8%
u 3
8.8%
e 3
8.8%
c 1
 
2.9%
v 1
 
2.9%
d 1
 
2.9%
G 1
 
2.9%
Other values (7) 7
20.6%

예약
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing136
Missing (%)97.8%
Memory size1.2 KiB
2024-04-18T16:54:59.696903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length62
Mean length54.333333
Min length37

Characters and Unicode

Total characters163
Distinct characters25
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
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 rowInternet, mobile, telephone, and on-site reservation available
2nd rowOnline and telephone reservation, and on-site purchase available
3rd rowReservation for group visit available
ValueCountFrequency (%)
and 3
15.0%
reservation 3
15.0%
available 3
15.0%
telephone 2
10.0%
on-site 2
10.0%
internet 1
 
5.0%
mobile 1
 
5.0%
online 1
 
5.0%
purchase 1
 
5.0%
for 1
 
5.0%
Other values (2) 2
10.0%
2024-04-18T16:54:59.964912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 22
13.5%
17
10.4%
a 16
9.8%
n 14
 
8.6%
i 12
 
7.4%
l 10
 
6.1%
t 10
 
6.1%
o 10
 
6.1%
r 9
 
5.5%
v 7
 
4.3%
Other values (15) 36
22.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 137
84.0%
Space Separator 17
 
10.4%
Other Punctuation 4
 
2.5%
Uppercase Letter 3
 
1.8%
Dash Punctuation 2
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 22
16.1%
a 16
11.7%
n 14
10.2%
i 12
8.8%
l 10
7.3%
t 10
7.3%
o 10
7.3%
r 9
6.6%
v 7
 
5.1%
s 7
 
5.1%
Other values (9) 20
14.6%
Uppercase Letter
ValueCountFrequency (%)
R 1
33.3%
I 1
33.3%
O 1
33.3%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 140
85.9%
Common 23
 
14.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 22
15.7%
a 16
11.4%
n 14
10.0%
i 12
8.6%
l 10
7.1%
t 10
7.1%
o 10
7.1%
r 9
 
6.4%
v 7
 
5.0%
s 7
 
5.0%
Other values (12) 23
16.4%
Common
ValueCountFrequency (%)
17
73.9%
, 4
 
17.4%
- 2
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 163
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 22
13.5%
17
10.4%
a 16
9.8%
n 14
 
8.6%
i 12
 
7.4%
l 10
 
6.1%
t 10
 
6.1%
o 10
 
6.1%
r 9
 
5.5%
v 7
 
4.3%
Other values (15) 36
22.1%

Sample

상세고유순번관리번호명칭관련항목연계자원경도정보(127.XX)위도정보(36.XXX)이명칭개요시대분류주제분류지번주소도로명주소지역제공기관언어유형제작일유형형식전화번호지정현황휴무일이용시간이용요금주차장애인 편의시설체험안내안내서비스예약
0401JGS_000001Deoksugung Palace<NA>JGH_000370126.9765337.56502Gyeongungung Palace, Temporary Palace at Jeongneung-dong, West PalaceIt was originally called Gyeongungung Palace but has been called Deoksugung Palace since 1907. Gates, pavilions and halls including Daehanmun Gate, Junghwamun Gate, Gwangmyeongmun Gate, Junghwajeong Hall, Junmyeongdang Hall, Seogeodang Hall, Seokjojeon Hall, Hamnyeongjeon Hall, and Jeukjodang Hall still remain in 61,500㎡ land.<NA><NA><NA>99, Sejong-daero, Jung-gu, SeoulSejong-daero, Jung-gu, SeoulJung-gu?Office?Seoul?ENG2015-12-30DATAHTML02-771-9951Historical Site No. 124MondaysTicketing and Admission Time 09:00 ~ 20:00 Closing Time 09:00 ~ 21:00Adult (25 or over) 1,000 wonAdult Group (10 or more) 800 won<NA>Wheelchair rentalTry Korean Traditional Clothes, Changing of the Guards Ceremony<NA><NA>
1402JGS_000002Jungmyeongjeon Hall of Deoksugung Palace<NA>JGH_000350126.9725237.56659<NA>Jungmyeongjeon Hall, constructed in 1901, is a part of Gyeongungung which is today’s Deoksugung Palace, and it was used as the reception hall, banquet hall, and library. This was the place the banquet was held during the wedding ceremony of the Crown Prince (Sunjong) and Crown Princess Yun in 1907 and also the unfortunate place where the Japan-Korea Treaty of 1905 was concluded by force. It had been leased to foreigners in 1915 during Japanese colonial era and used as Seoul Club building.<NA><NA><NA>41-11, Jeongdong-gil, Jung-gu, SeoulJeongdong-gil, Jung-gu, SeoulJung-gu?Office?Seoul?ENG2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2403JGS_000003Hwangudan (Wongudan)<NA>JGH_000335126.9796937.56506<NA>Hwangudan Altar is the space where the emperor held memorial service for heaven. This is where Emperor Gwangmu of the Korean Empire which succeeded to the Joseon Empire held memorial service for heaven. Hwangudan Altar was completed in 1897 and was designed by Sim Eui-seok, the master builder for the imperial family at the time.<NA><NA><NA>106, Sogong-ro, Jung-gu, SeoulSogong-ro, Jung-gu, SeoulJung-gu?Office?Seoul?ENG2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3404JGS_000004Former Russian Legation<NA>JGH_000355126.9714637.56825<NA>This is the renaissance style building designed by A. I. Sabatin of Russia in 1890 (Gojong 27). The main building was destroyed during the Korean War, and currently only the 3-story tower remains. This is famous for King Gojong’s refuge to avoid Japan’s pressure using force.<NA><NA><NA>Jeong-dong Park, 21-18, Jeongdong-gil, Jung-gu, SeoulJeongdong-gil, Jung-gu, SeoulJung-gu?Office?Seoul?ENG2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4405JGS_000005Chungdong First Methodist Church<NA>JGH_000367126.9723637.56542<NA>Chungdong First Methodist Church is a protestant church chapel, and construction of the church began in 1895 (Gojong 32) and was completed in October 1897 (Gwangmu 1).<NA><NA><NA>Chungdong First Methodist Church, 46, Jeongdong-gil, Jung-gu, SeoulJeongdong-gil, Jung-gu, SeoulJung-gu?Office?Seoul?ENG2015-12-30DATAHTML<NA><NA><NA><NA><NA>Parking space available<NA><NA><NA><NA>
5406JGS_000006Appenzeller Noble Memorial Museum (Former East Wing of Pai Chai School)<NA>JGH_000368126.9726237.56378<NA>This building was completed in 1916 and was used as a school building until Pai Chai middle and high schools moved to Gangdong-gu in 1984. Pai Chai School was established by the missionary Henry Gerhard Appenzeller in August 1885, and in the beginning, he purchased private houses in the area and used them as school buildings.<NA><NA><NA>19, Seosomun-ro 11-gil, Jung-gu, SeoulSeosomun-ro, Jung-gu, SeoulJung-gu?Office?Seoul?ENG2015-12-30DATAHTML<NA>Seoul Monument No. 16Mondays, HolidaysEveryday 10:00 ~ 17:00Free<NA><NA><NA><NA><NA>
6407JGS_000007Seoul Museum of Art<NA>JGH_000313126.9737737.56402<NA>This place was previously occupied by Royal English Academy, German legation, and Gyeongseong District Court. After the liberation, the building was occupied by the Supreme Court of Korea and it reopened as Seoul Museum of Art from 2002.<NA><NA><NA>61, Deoksugung-gil, Jung-gu, SeoulDeoksugung-gil, Jung-gu, SeoulJung-gu?Office?Seoul?ENG2015-12-30DATAHTML02-2124-8800Registered Cultural Heritage No. 237Mondays, January 1<NA><NA>Parking space available<NA><NA><NA><NA>
7408JGS_000008Yangijae Gyeongungung Palace<NA>JGH_000361126.9754437.56694<NA>It was completed in 1905 while restoring Gyeongungung Palace (Deoksugung Palace) which was burned in a huge fire. It was in charge of the modern education of the imperial family and aristocrats of the Korean Empire and today it is used as the office of the bishop of the Anglican Church of Korea.<NA><NA><NA>15, Sejong-daero 21-gil, Jung-gu, SeoulSejong-daero, Jung-gu, SeoulJung-gu?Office?Seoul?ENG2015-12-30DATAHTML<NA>Registered Cultural Heritage No. 267<NA><NA><NA><NA><NA><NA><NA><NA>
8409JGS_000009Annex of Former Shina Daily News<NA>JGH_000354126.9721737.56619<NA>This is a 2-story reinforced concrete building with a basement constructed in the 1930's. The Korean branch of SINGER, an American company, initially used the building until Shina Daily News purchased the building in 1963. In 1975, Shina Daily News extended the building by adding 3rd and 4th floors and used it as the annex. Shina Daily News was incorporated into the Kyunghyang Shinmun during the merger of press by the new military regime in 1980.<NA><NA><NA>33, Jeongdong-gil, Jung-gu, SeoulJeongdong-gil, Jung-gu, SeoulJung-gu?Office?Seoul?ENG2015-12-30DATAHTML<NA>Registered Cultural Heritage No. 402<NA><NA><NA><NA><NA><NA><NA><NA>
9410JGS_000010Central Hall of the Korean Salvation Army<NA>JGH_000352126.973637.56761<NA>Central Hall of the Korean Salvation Army was completed in 1928 to be used as the base for fostering Salvation Army officials and leading mission work and social services.<NA><NA><NA>130, Deoksugung-gil, Jung-gu, SeoulDeoksugung-gil, Jung-gu, SeoulJung-gu?Office?Seoul?ENG2015-12-30DATAHTML02-720-9494Seoul Monument No. 20<NA><NA><NA><NA><NA><NA><NA><NA>
상세고유순번관리번호명칭관련항목연계자원경도정보(127.XX)위도정보(36.XXX)이명칭개요시대분류주제분류지번주소도로명주소지역제공기관언어유형제작일유형형식전화번호지정현황휴무일이용시간이용요금주차장애인 편의시설체험안내안내서비스예약
129675JGS_000131Lotus Lantern Festival<NA><NA>126.9818737.568862<NA>Lotus Lantern Festival, a festival where people pray to Buddha for fortune<NA><NA><NA>Cheonggyecheon, Seoul<NA>Seoul Metropolitan GovernmentENG<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
130680JGS_000132Mock fight with stones<NA><NA>126.98433937.568659<NA>Joseon’s warlike mock fight with stones<NA><NA><NA>Cheonggyecheon, Seoul<NA>Seoul Metropolitan GovernmentENG<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
131685JGS_000133Taekyun at Cheonggyecheon Stream<NA><NA>127.00124237.569457<NA>The last Taekyun training site and Taekyun Battle at Insa-dong<NA><NA><NA>Cheonggyecheon, Seoul<NA>Seoul Metropolitan GovernmentENG<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
132690JGS_000134Suseonjeondo<NA><NA>126.9848937.568552<NA>Suseonjeondo, a map of Hanyang<NA><NA><NA>Jongno-gu, Seoul<NA>Seoul Metropolitan GovernmentENG<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
133695JGS_000135Neunghaeng Banchado of King Jeongjo<NA><NA>126.9852737.568509<NA>King Jeongjo’s procession to pay respects at the Royal Tomb of Sado, a misfortunate prince<NA><NA><NA>Jongno-gu, Seoul<NA>Seoul Metropolitan GovernmentENG<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
134700JGS_000136King Yeongjo’s writing and Chae Jae-gong's Juncheonga<NA><NA>127.00968237.569826<NA>King Yeongjo’s joy toward Juncheon Construction and the poem of Chae Jae-gong<NA><NA><NA>Jongno-gu, Seoul<NA>Seoul Metropolitan GovernmentENG<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
135705JGS_000137Ogansumun Floodgate<NA><NA>127.01061437.569765<NA>Ogansumun Floodgate, the rampart of Hanyang and the exit of Cheonggyecheon Stream’s waterway<NA><NA><NA>Jongno-gu, Seoul<NA>Seoul Metropolitan GovernmentENG<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
136710JGS_000138Juncheondo<NA><NA>127.0096837.569675<NA>King Yeongjo encourages the dredging construction at the Ogansumun Floodgate.<NA><NA><NA>Jung-gu, Seoul<NA>Seoul Metropolitan GovernmentENG<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
137715JGS_000139A mural of the Cheonggyecheon Stream in the past<NA><NA>127.01377437.569842<NA>Traces of the Cheonggyecheon Stream in the past<NA><NA><NA>Jongno-gu, Seoul<NA>Seoul Metropolitan GovernmentENG<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
138419JGS_000019Cecil Theater<NA>JGH_001147126.9759937.56673<NA>This is a small theater that opened in the annex of Seoul Cathedral of the Anglican Church of Korea in 1976. It held the first to the fifth Drama Festival of the Republic of Korea and was the center of the small theater movement which swept the country in the 1970’s.<NA><NA><NA>16, Sejong-daero 19-gil, Jung-gu, SeoulSejong-daero, Jung-gu, SeoulJung-gu?Office?Seoul?ENG2015-12-30DATAHTML02-742-7601<NA><NA><NA><NA><NA><NA><NA><NA><NA>