Overview

Dataset statistics

Number of variables22
Number of observations796
Missing cells3554
Missing cells (%)20.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory140.1 KiB
Average record size in memory180.2 B

Variable types

Text13
Numeric2
Unsupported1
Categorical6

Dataset

Description관리번호,명칭,관련항목,연계자원,경도정보(127.XX),위도정보(36.XXX),이명칭,지역,지번주소,도로명주소,개요,역사정보,시대분류,주제분류,시작일(발생일),인물,제공기관,언어유형,제작일,유형,형식,등록일
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-13372/S/1/datasetView.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
관련항목 has 424 (53.3%) missing valuesMissing
연계자원 has 711 (89.3%) missing valuesMissing
경도정보(127.XX) has 72 (9.0%) missing valuesMissing
위도정보(36.XXX) has 72 (9.0%) missing valuesMissing
이명칭 has 635 (79.8%) missing valuesMissing
지번주소 has 796 (100.0%) missing valuesMissing
역사정보 has 45 (5.7%) missing valuesMissing
시작일(발생일) has 9 (1.1%) missing valuesMissing
인물 has 790 (99.2%) missing valuesMissing
경도정보(127.XX) is highly skewed (γ1 = -26.90650144)Skewed
위도정보(36.XXX) is highly skewed (γ1 = 26.90715382)Skewed
관리번호 has unique valuesUnique
지번주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 05:32:40.855754
Analysis finished2023-12-11 05:32:44.179066
Duration3.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct796
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2023-12-11T14:32:44.448103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters7960
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

Unique796 ?
Unique (%)100.0%

Sample

1st rowJGH_000073
2nd rowJGH_000529
3rd rowJGH_000551
4th rowJGH_000386
5th rowJGH_000570
ValueCountFrequency (%)
jgh_000073 1
 
0.1%
jgh_000747 1
 
0.1%
jgh_000634 1
 
0.1%
jgh_000834 1
 
0.1%
jgh_000789 1
 
0.1%
jgh_000059 1
 
0.1%
jgh_000646 1
 
0.1%
jgh_000793 1
 
0.1%
jgh_000893 1
 
0.1%
jgh_000426 1
 
0.1%
Other values (786) 786
98.7%
2023-12-11T14:32:44.948873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2619
32.9%
J 796
 
10.0%
G 796
 
10.0%
H 796
 
10.0%
_ 796
 
10.0%
1 268
 
3.4%
5 257
 
3.2%
7 255
 
3.2%
6 254
 
3.2%
4 250
 
3.1%
Other values (4) 873
 
11.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4776
60.0%
Uppercase Letter 2388
30.0%
Connector Punctuation 796
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2619
54.8%
1 268
 
5.6%
5 257
 
5.4%
7 255
 
5.3%
6 254
 
5.3%
4 250
 
5.2%
3 240
 
5.0%
8 233
 
4.9%
2 229
 
4.8%
9 171
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
J 796
33.3%
G 796
33.3%
H 796
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 796
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5572
70.0%
Latin 2388
30.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2619
47.0%
_ 796
 
14.3%
1 268
 
4.8%
5 257
 
4.6%
7 255
 
4.6%
6 254
 
4.6%
4 250
 
4.5%
3 240
 
4.3%
8 233
 
4.2%
2 229
 
4.1%
Latin
ValueCountFrequency (%)
J 796
33.3%
G 796
33.3%
H 796
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7960
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2619
32.9%
J 796
 
10.0%
G 796
 
10.0%
H 796
 
10.0%
_ 796
 
10.0%
1 268
 
3.4%
5 257
 
3.2%
7 255
 
3.2%
6 254
 
3.2%
4 250
 
3.1%
Other values (4) 873
 
11.0%

명칭
Text

Distinct794
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2023-12-11T14:32:45.339595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length6.9874372
Min length2

Characters and Unicode

Total characters5562
Distinct characters938
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique792 ?
Unique (%)99.5%

Sample

1st row電視劇中心
2nd row大使酒店
3rd row茶山洞居民中心
4th row昌慶宮自擊漏
5th row東國大學
ValueCountFrequency (%)
大方廣佛華嚴經 8
 
1.0%
忠洞2街 7
 
0.8%
大佛頂如來密因修證了義諸菩薩萬行首楞嚴經(諺解) 4
 
0.5%
溪川 3
 
0.4%
卷3 2
 
0.2%
卷7、8 2
 
0.2%
三國史記 2
 
0.2%
平和市場 2
 
0.2%
明洞街 2
 
0.2%
周本卷6 2
 
0.2%
Other values (795) 795
95.9%
2023-12-11T14:32:45.905674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
175
 
3.1%
171
 
3.1%
? 151
 
2.7%
100
 
1.8%
96
 
1.7%
91
 
1.6%
73
 
1.3%
65
 
1.2%
61
 
1.1%
56
 
1.0%
Other values (928) 4523
81.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4951
89.0%
Other Punctuation 159
 
2.9%
Decimal Number 141
 
2.5%
Uppercase Letter 81
 
1.5%
Lowercase Letter 70
 
1.3%
Close Punctuation 53
 
1.0%
Open Punctuation 53
 
1.0%
Space Separator 33
 
0.6%
Dash Punctuation 21
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
175
 
3.5%
171
 
3.5%
100
 
2.0%
96
 
1.9%
91
 
1.8%
73
 
1.5%
65
 
1.3%
61
 
1.2%
56
 
1.1%
54
 
1.1%
Other values (862) 4009
81.0%
Uppercase Letter
ValueCountFrequency (%)
M 8
 
9.9%
C 7
 
8.6%
T 6
 
7.4%
A 6
 
7.4%
P 6
 
7.4%
E 6
 
7.4%
N 5
 
6.2%
B 5
 
6.2%
O 5
 
6.2%
S 4
 
4.9%
Other values (13) 23
28.4%
Lowercase Letter
ValueCountFrequency (%)
e 10
14.3%
n 8
11.4%
o 7
10.0%
i 7
10.0%
l 6
8.6%
u 4
 
5.7%
a 4
 
5.7%
t 4
 
5.7%
d 3
 
4.3%
s 3
 
4.3%
Other values (9) 14
20.0%
Decimal Number
ValueCountFrequency (%)
2 39
27.7%
1 31
22.0%
3 14
 
9.9%
8 12
 
8.5%
6 10
 
7.1%
9 9
 
6.4%
4 8
 
5.7%
7 8
 
5.7%
0 6
 
4.3%
5 4
 
2.8%
Other Punctuation
ValueCountFrequency (%)
? 151
95.0%
2
 
1.3%
. 2
 
1.3%
2
 
1.3%
: 1
 
0.6%
1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
48
90.6%
) 4
 
7.5%
] 1
 
1.9%
Open Punctuation
ValueCountFrequency (%)
48
90.6%
( 4
 
7.5%
[ 1
 
1.9%
Space Separator
ValueCountFrequency (%)
33
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 4944
88.9%
Common 460
 
8.3%
Latin 151
 
2.7%
Hangul 7
 
0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
175
 
3.5%
171
 
3.5%
100
 
2.0%
96
 
1.9%
91
 
1.8%
73
 
1.5%
65
 
1.3%
61
 
1.2%
56
 
1.1%
54
 
1.1%
Other values (858) 4002
80.9%
Latin
ValueCountFrequency (%)
e 10
 
6.6%
M 8
 
5.3%
n 8
 
5.3%
o 7
 
4.6%
C 7
 
4.6%
i 7
 
4.6%
T 6
 
4.0%
A 6
 
4.0%
P 6
 
4.0%
E 6
 
4.0%
Other values (32) 80
53.0%
Common
ValueCountFrequency (%)
? 151
32.8%
48
 
10.4%
48
 
10.4%
2 39
 
8.5%
33
 
7.2%
1 31
 
6.7%
- 21
 
4.6%
3 14
 
3.0%
8 12
 
2.6%
6 10
 
2.2%
Other values (14) 53
 
11.5%
Hangul
ValueCountFrequency (%)
3
42.9%
2
28.6%
1
 
14.3%
1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
CJK 4931
88.7%
ASCII 510
 
9.2%
None 101
 
1.8%
CJK Compat Ideographs 13
 
0.2%
Hangul 7
 
0.1%

Most frequent character per block

CJK
ValueCountFrequency (%)
175
 
3.5%
171
 
3.5%
100
 
2.0%
96
 
1.9%
91
 
1.8%
73
 
1.5%
65
 
1.3%
61
 
1.2%
56
 
1.1%
54
 
1.1%
Other values (852) 3989
80.9%
ASCII
ValueCountFrequency (%)
? 151
29.6%
2 39
 
7.6%
33
 
6.5%
1 31
 
6.1%
- 21
 
4.1%
3 14
 
2.7%
8 12
 
2.4%
6 10
 
2.0%
e 10
 
2.0%
9 9
 
1.8%
Other values (51) 180
35.3%
None
ValueCountFrequency (%)
48
47.5%
48
47.5%
2
 
2.0%
2
 
2.0%
1
 
1.0%
CJK Compat Ideographs
ValueCountFrequency (%)
4
30.8%
3
23.1%
3
23.1%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Hangul
ValueCountFrequency (%)
3
42.9%
2
28.6%
1
 
14.3%
1
 
14.3%

관련항목
Text

MISSING 

Distinct282
Distinct (%)75.8%
Missing424
Missing (%)53.3%
Memory size6.3 KiB
2023-12-11T14:32:46.163412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length164
Median length10
Mean length19.897849
Min length10

Characters and Unicode

Total characters7402
Distinct characters16
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

Unique254 ?
Unique (%)68.3%

Sample

1st rowJGH_000625
2nd rowJGH_000913
3rd rowJGH_000370
4th rowJGH_000571,JGH_000612,JGH_000612,JGH_000682
5th rowJGH_000103,JGH_000700,JGH_000701,JGH_000702,JGH_000703,JGH_000722
ValueCountFrequency (%)
jgh_000444 21
 
5.6%
jgh_001181 19
 
5.1%
jgh_000370 13
 
3.5%
jgh_000010 7
 
1.9%
jgh_000447 6
 
1.6%
jgh_000727 4
 
1.1%
jgh_000400 4
 
1.1%
jgh_000131 3
 
0.8%
jgh_000456 3
 
0.8%
jgh_000570 2
 
0.5%
Other values (272) 290
78.0%
2023-12-11T14:32:46.549452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2423
32.7%
J 706
 
9.5%
G 706
 
9.5%
H 706
 
9.5%
_ 706
 
9.5%
, 335
 
4.5%
4 322
 
4.4%
1 246
 
3.3%
8 230
 
3.1%
7 226
 
3.1%
Other values (6) 796
 
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4242
57.3%
Uppercase Letter 2118
28.6%
Connector Punctuation 706
 
9.5%
Other Punctuation 335
 
4.5%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2423
57.1%
4 322
 
7.6%
1 246
 
5.8%
8 230
 
5.4%
7 226
 
5.3%
3 203
 
4.8%
6 192
 
4.5%
5 153
 
3.6%
2 128
 
3.0%
9 119
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
J 706
33.3%
G 706
33.3%
H 706
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 706
100.0%
Other Punctuation
ValueCountFrequency (%)
, 335
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5284
71.4%
Latin 2118
28.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2423
45.9%
_ 706
 
13.4%
, 335
 
6.3%
4 322
 
6.1%
1 246
 
4.7%
8 230
 
4.4%
7 226
 
4.3%
3 203
 
3.8%
6 192
 
3.6%
5 153
 
2.9%
Other values (3) 248
 
4.7%
Latin
ValueCountFrequency (%)
J 706
33.3%
G 706
33.3%
H 706
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7402
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2423
32.7%
J 706
 
9.5%
G 706
 
9.5%
H 706
 
9.5%
_ 706
 
9.5%
, 335
 
4.5%
4 322
 
4.4%
1 246
 
3.3%
8 230
 
3.1%
7 226
 
3.1%
Other values (6) 796
 
10.8%

연계자원
Text

MISSING 

Distinct85
Distinct (%)100.0%
Missing711
Missing (%)89.3%
Memory size6.3 KiB
2023-12-11T14:32:46.939079image/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 rowJGS_000022
2nd rowJGS_000002
3rd rowJGS_000051
4th rowJGS_000006
5th rowJGS_000019
ValueCountFrequency (%)
jgs_000081 1
 
1.2%
jgs_000027 1
 
1.2%
jgs_000038 1
 
1.2%
jgs_000015 1
 
1.2%
jgs_000067 1
 
1.2%
jgs_000047 1
 
1.2%
jgs_000076 1
 
1.2%
jgs_000037 1
 
1.2%
jgs_000012 1
 
1.2%
jgs_000070 1
 
1.2%
Other values (75) 75
88.2%
2023-12-11T14:32:47.431517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 357
42.0%
J 85
 
10.0%
G 85
 
10.0%
S 85
 
10.0%
_ 85
 
10.0%
1 19
 
2.2%
2 19
 
2.2%
4 19
 
2.2%
5 18
 
2.1%
6 18
 
2.1%
Other values (4) 60
 
7.1%

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 (%)
0 357
70.0%
1 19
 
3.7%
2 19
 
3.7%
4 19
 
3.7%
5 18
 
3.5%
6 18
 
3.5%
7 18
 
3.5%
3 17
 
3.3%
8 14
 
2.7%
9 11
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
J 85
33.3%
G 85
33.3%
S 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 (%)
0 357
60.0%
_ 85
 
14.3%
1 19
 
3.2%
2 19
 
3.2%
4 19
 
3.2%
5 18
 
3.0%
6 18
 
3.0%
7 18
 
3.0%
3 17
 
2.9%
8 14
 
2.4%
Latin
ValueCountFrequency (%)
J 85
33.3%
G 85
33.3%
S 85
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 850
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 357
42.0%
J 85
 
10.0%
G 85
 
10.0%
S 85
 
10.0%
_ 85
 
10.0%
1 19
 
2.2%
2 19
 
2.2%
4 19
 
2.2%
5 18
 
2.1%
6 18
 
2.1%
Other values (4) 60
 
7.1%

경도정보(127.XX)
Real number (ℝ)

MISSING  SKEWED 

Distinct519
Distinct (%)71.7%
Missing72
Missing (%)9.0%
Infinite0
Infinite (%)0.0%
Mean126.8658
Minimum37.55317
Maximum127.025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2023-12-11T14:32:47.604237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.55317
5-th percentile126.96902
Q1126.9766
median126.9876
Q3127.00086
95-th percentile127.01322
Maximum127.025
Range89.471834
Interquartile range (IQR)0.0242592

Descriptive statistics

Standard deviation3.3238993
Coefficient of variation (CV)0.026200122
Kurtosis723.97318
Mean126.8658
Median Absolute Deviation (MAD)0.01157995
Skewness-26.906501
Sum91850.837
Variance11.048307
MonotonicityNot monotonic
2023-12-11T14:32:47.787733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9760655 21
 
2.6%
126.9990619 17
 
2.1%
126.993561 12
 
1.5%
127.0001869 10
 
1.3%
126.9902669 9
 
1.1%
126.9663687 7
 
0.9%
126.9805213 5
 
0.6%
126.9847708 5
 
0.6%
127.0097934 5
 
0.6%
126.988092 5
 
0.6%
Other values (509) 628
78.9%
(Missing) 72
 
9.0%
ValueCountFrequency (%)
37.5531696 1
 
0.1%
126.9618745 1
 
0.1%
126.9628 1
 
0.1%
126.963323 1
 
0.1%
126.9641106 1
 
0.1%
126.9641308 1
 
0.1%
126.966205 2
 
0.3%
126.9662871 1
 
0.1%
126.9663687 7
0.9%
126.9669871 3
0.4%
ValueCountFrequency (%)
127.0250041 1
0.1%
127.0233836 1
0.1%
127.022704 1
0.1%
127.0218852 1
0.1%
127.0218074 1
0.1%
127.0217663 1
0.1%
127.0212812 1
0.1%
127.0210984 1
0.1%
127.0204904 1
0.1%
127.020038 1
0.1%

위도정보(36.XXX)
Real number (ℝ)

MISSING  SKEWED 

Distinct520
Distinct (%)71.8%
Missing72
Missing (%)9.0%
Infinite0
Infinite (%)0.0%
Mean37.68558
Minimum37.54712
Maximum127.0062
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2023-12-11T14:32:47.946936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.54712
5-th percentile37.552697
Q137.558319
median37.562313
Q337.566464
95-th percentile37.568884
Maximum127.0062
Range89.459085
Interquartile range (IQR)0.008145475

Descriptive statistics

Standard deviation3.3241701
Coefficient of variation (CV)0.088208014
Kurtosis723.99661
Mean37.68558
Median Absolute Deviation (MAD)0.0040486
Skewness26.907154
Sum27284.36
Variance11.050107
MonotonicityNot monotonic
2023-12-11T14:32:48.114817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5676649 21
 
2.6%
37.5579682 17
 
2.1%
37.5584554 12
 
1.5%
37.5582582 10
 
1.3%
37.5591077 9
 
1.1%
37.5569261 7
 
0.9%
37.5519464 5
 
0.6%
37.5669654 5
 
0.6%
37.5647524 5
 
0.6%
37.5620607 5
 
0.6%
Other values (510) 628
78.9%
(Missing) 72
 
9.0%
ValueCountFrequency (%)
37.54712 1
0.1%
37.5479206 1
0.1%
37.5481408 1
0.1%
37.548707 1
0.1%
37.549492 1
0.1%
37.5496721 1
0.1%
37.5500121 2
0.3%
37.550071 2
0.3%
37.5501776 1
0.1%
37.5510742 1
0.1%
ValueCountFrequency (%)
127.0062047 1
0.1%
37.5783108 1
0.1%
37.5717155 1
0.1%
37.5713556 1
0.1%
37.5710754 1
0.1%
37.5709405 1
0.1%
37.5698371 1
0.1%
37.569775 1
0.1%
37.5697667 1
0.1%
37.5697285 1
0.1%

이명칭
Text

MISSING 

Distinct150
Distinct (%)93.2%
Missing635
Missing (%)79.8%
Memory size6.3 KiB
2023-12-11T14:32:48.394838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length21
Mean length7.9440994
Min length2

Characters and Unicode

Total characters1279
Distinct characters430
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique146 ?
Unique (%)90.7%

Sample

1st row東朗劇場、南山藝術中心
2nd row首爾?爾曼大使酒店
3rd row舊新堂第2洞居民中心
4th row德壽宮報漏閣自擊漏
5th row?塔(DOOTA)
ValueCountFrequency (%)
忠洞2街文化住宅 6
 
3.5%
楞嚴經 4
 
2.3%
大佛頂首楞嚴經 4
 
2.3%
金剛經 3
 
1.7%
新平和市場 2
 
1.2%
1
 
0.6%
孫澤賓館舊址 1
 
0.6%
芳山市場 1
 
0.6%
中區文化財團忠武藝術廳 1
 
0.6%
仇里介橋舊址 1
 
0.6%
Other values (148) 148
86.0%
2023-12-11T14:32:48.925089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 72
 
5.6%
27
 
2.1%
26
 
2.0%
24
 
1.9%
24
 
1.9%
22
 
1.7%
22
 
1.7%
20
 
1.6%
17
 
1.3%
17
 
1.3%
Other values (420) 1008
78.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1072
83.8%
Other Punctuation 119
 
9.3%
Uppercase Letter 34
 
2.7%
Lowercase Letter 16
 
1.3%
Decimal Number 15
 
1.2%
Space Separator 11
 
0.9%
Open Punctuation 5
 
0.4%
Close Punctuation 5
 
0.4%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
27
 
2.5%
26
 
2.4%
24
 
2.2%
22
 
2.1%
22
 
2.1%
20
 
1.9%
17
 
1.6%
17
 
1.6%
16
 
1.5%
16
 
1.5%
Other values (379) 865
80.7%
Uppercase Letter
ValueCountFrequency (%)
O 6
17.6%
P 4
11.8%
T 4
11.8%
A 4
11.8%
S 2
 
5.9%
C 2
 
5.9%
L 2
 
5.9%
N 2
 
5.9%
B 1
 
2.9%
M 1
 
2.9%
Other values (6) 6
17.6%
Lowercase Letter
ValueCountFrequency (%)
e 2
12.5%
n 2
12.5%
o 2
12.5%
z 2
12.5%
u 2
12.5%
a 1
6.2%
k 1
6.2%
y 1
6.2%
g 1
6.2%
r 1
6.2%
Other Punctuation
ValueCountFrequency (%)
? 72
60.5%
24
 
20.2%
14
 
11.8%
, 6
 
5.0%
/ 3
 
2.5%
Decimal Number
ValueCountFrequency (%)
2 10
66.7%
1 4
 
26.7%
4 1
 
6.7%
Open Punctuation
ValueCountFrequency (%)
4
80.0%
( 1
 
20.0%
Close Punctuation
ValueCountFrequency (%)
4
80.0%
) 1
 
20.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 1070
83.7%
Common 157
 
12.3%
Latin 50
 
3.9%
Hangul 2
 
0.2%

Most frequent character per script

Han
ValueCountFrequency (%)
27
 
2.5%
26
 
2.4%
24
 
2.2%
22
 
2.1%
22
 
2.1%
20
 
1.9%
17
 
1.6%
17
 
1.6%
16
 
1.5%
16
 
1.5%
Other values (377) 863
80.7%
Latin
ValueCountFrequency (%)
O 6
 
12.0%
P 4
 
8.0%
T 4
 
8.0%
A 4
 
8.0%
e 2
 
4.0%
S 2
 
4.0%
C 2
 
4.0%
L 2
 
4.0%
n 2
 
4.0%
o 2
 
4.0%
Other values (17) 20
40.0%
Common
ValueCountFrequency (%)
? 72
45.9%
24
 
15.3%
14
 
8.9%
11
 
7.0%
2 10
 
6.4%
, 6
 
3.8%
4
 
2.5%
4
 
2.5%
1 4
 
2.5%
/ 3
 
1.9%
Other values (4) 5
 
3.2%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 1070
83.7%
ASCII 161
 
12.6%
None 46
 
3.6%
Hangul 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 72
44.7%
11
 
6.8%
2 10
 
6.2%
O 6
 
3.7%
, 6
 
3.7%
P 4
 
2.5%
1 4
 
2.5%
T 4
 
2.5%
A 4
 
2.5%
/ 3
 
1.9%
Other values (27) 37
23.0%
CJK
ValueCountFrequency (%)
27
 
2.5%
26
 
2.4%
24
 
2.2%
22
 
2.1%
22
 
2.1%
20
 
1.9%
17
 
1.6%
17
 
1.6%
16
 
1.5%
16
 
1.5%
Other values (377) 863
80.7%
None
ValueCountFrequency (%)
24
52.2%
14
30.4%
4
 
8.7%
4
 
8.7%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

지역
Text

Distinct183
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2023-12-11T14:32:49.185700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length11.057789
Min length7

Characters and Unicode

Total characters8802
Distinct characters131
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)9.3%

Sample

1st row首爾特別市 中區 藝場洞
2nd row首爾特別市中區東湖路
3rd row首爾特別市中區東湖路
4th row首爾特別市 中區 貞洞
5th row首爾特別市中區?忠洞2街
ValueCountFrequency (%)
首爾特別市 219
 
18.1%
中區 214
 
17.7%
首爾特別市中區退溪路 50
 
4.1%
首爾特別市中區世宗大路 33
 
2.7%
忠洞2街 29
 
2.4%
首爾特別市中區乙支路 27
 
2.2%
首爾特別市中區小波路 21
 
1.7%
首爾特別市中區東湖路 20
 
1.7%
首爾特別市中區筆洞路 19
 
1.6%
首爾特別市中區小公洞 19
 
1.6%
Other values (175) 558
46.2%
2023-12-11T14:32:49.651853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
797
 
9.1%
796
 
9.0%
796
 
9.0%
795
 
9.0%
795
 
9.0%
791
 
9.0%
787
 
8.9%
445
 
5.1%
413
 
4.7%
354
 
4.0%
Other values (121) 2033
23.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8075
91.7%
Space Separator 413
 
4.7%
Decimal Number 223
 
2.5%
Other Punctuation 83
 
0.9%
Close Punctuation 3
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
797
9.9%
796
9.9%
796
9.9%
795
9.8%
795
9.8%
791
9.8%
787
9.7%
445
 
5.5%
354
 
4.4%
224
 
2.8%
Other values (105) 1495
18.5%
Decimal Number
ValueCountFrequency (%)
2 84
37.7%
1 62
27.8%
3 26
 
11.7%
5 22
 
9.9%
6 14
 
6.3%
4 11
 
4.9%
0 2
 
0.9%
8 1
 
0.4%
7 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
? 80
96.4%
2
 
2.4%
, 1
 
1.2%
Space Separator
ValueCountFrequency (%)
413
100.0%
Close Punctuation
ValueCountFrequency (%)
3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Open Punctuation
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 8075
91.7%
Common 727
 
8.3%

Most frequent character per script

Han
ValueCountFrequency (%)
797
9.9%
796
9.9%
796
9.9%
795
9.8%
795
9.8%
791
9.8%
787
9.7%
445
 
5.5%
354
 
4.4%
224
 
2.8%
Other values (105) 1495
18.5%
Common
ValueCountFrequency (%)
413
56.8%
2 84
 
11.6%
? 80
 
11.0%
1 62
 
8.5%
3 26
 
3.6%
5 22
 
3.0%
6 14
 
1.9%
4 11
 
1.5%
3
 
0.4%
- 3
 
0.4%
Other values (6) 9
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
CJK 8075
91.7%
ASCII 720
 
8.2%
None 7
 
0.1%

Most frequent character per block

CJK
ValueCountFrequency (%)
797
9.9%
796
9.9%
796
9.9%
795
9.8%
795
9.8%
791
9.8%
787
9.7%
445
 
5.5%
354
 
4.4%
224
 
2.8%
Other values (105) 1495
18.5%
ASCII
ValueCountFrequency (%)
413
57.4%
2 84
 
11.7%
? 80
 
11.1%
1 62
 
8.6%
3 26
 
3.6%
5 22
 
3.1%
6 14
 
1.9%
4 11
 
1.5%
- 3
 
0.4%
0 2
 
0.3%
Other values (3) 3
 
0.4%
None
ValueCountFrequency (%)
3
42.9%
2
28.6%
2
28.6%

지번주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing796
Missing (%)100.0%
Memory size7.1 KiB
Distinct643
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2023-12-11T14:32:49.960303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length37
Mean length24.125628
Min length7

Characters and Unicode

Total characters19204
Distinct characters322
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique573 ?
Unique (%)72.0%

Sample

1st row首爾特別市 中區 소파로 138(藝場洞 8-19)
2nd row首爾特別市中區東湖路287(?忠洞2街186-54)
3rd row首爾特別市中區東湖路15路50(新堂洞432-24)
4th row首爾特別市 中區 世宗大路 99(貞洞 5-1)
5th row首爾特別市中區筆洞路1路30(?忠洞2街192-5)
ValueCountFrequency (%)
首爾特別市 214
 
12.7%
中區 208
 
12.4%
一帶 29
 
1.7%
首爾特別市中區 15
 
0.9%
忠壇路 14
 
0.8%
東湖路 13
 
0.8%
60-17 12
 
0.7%
26 12
 
0.7%
世宗大路21路22(太平路1街 12
 
0.7%
首爾特別市中區世宗大路99(貞洞5-1) 12
 
0.7%
Other values (832) 1138
67.8%
2023-12-11T14:32:50.454166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1129
 
5.9%
998
 
5.2%
883
 
4.6%
2 864
 
4.5%
803
 
4.2%
801
 
4.2%
799
 
4.2%
796
 
4.1%
795
 
4.1%
793
 
4.1%
Other values (312) 10543
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11578
60.3%
Decimal Number 4633
24.1%
Space Separator 883
 
4.6%
Close Punctuation 652
 
3.4%
Open Punctuation 651
 
3.4%
Dash Punctuation 589
 
3.1%
Other Punctuation 181
 
0.9%
Lowercase Letter 17
 
0.1%
Uppercase Letter 13
 
0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
998
 
8.6%
803
 
6.9%
801
 
6.9%
799
 
6.9%
796
 
6.9%
795
 
6.9%
793
 
6.8%
793
 
6.8%
677
 
5.8%
526
 
4.5%
Other values (272) 3797
32.8%
Decimal Number
ValueCountFrequency (%)
1 1129
24.4%
2 864
18.6%
3 426
 
9.2%
5 371
 
8.0%
4 350
 
7.6%
6 348
 
7.5%
0 346
 
7.5%
7 278
 
6.0%
8 265
 
5.7%
9 256
 
5.5%
Lowercase Letter
ValueCountFrequency (%)
o 3
17.6%
n 3
17.6%
a 2
11.8%
i 2
11.8%
m 2
11.8%
y 1
 
5.9%
t 1
 
5.9%
g 1
 
5.9%
r 1
 
5.9%
d 1
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
M 3
23.1%
A 2
15.4%
C 2
15.4%
S 1
 
7.7%
E 1
 
7.7%
D 1
 
7.7%
W 1
 
7.7%
Y 1
 
7.7%
G 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
? 171
94.5%
4
 
2.2%
, 4
 
2.2%
2
 
1.1%
Open Punctuation
ValueCountFrequency (%)
494
75.9%
( 157
 
24.1%
Close Punctuation
ValueCountFrequency (%)
494
75.8%
) 158
 
24.2%
Space Separator
ValueCountFrequency (%)
883
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 589
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 11382
59.3%
Common 7596
39.6%
Hangul 196
 
1.0%
Latin 30
 
0.2%

Most frequent character per script

Han
ValueCountFrequency (%)
998
 
8.8%
803
 
7.1%
801
 
7.0%
799
 
7.0%
796
 
7.0%
795
 
7.0%
793
 
7.0%
793
 
7.0%
677
 
5.9%
526
 
4.6%
Other values (201) 3601
31.6%
Hangul
ValueCountFrequency (%)
20
 
10.2%
15
 
7.7%
12
 
6.1%
12
 
6.1%
12
 
6.1%
6
 
3.1%
5
 
2.6%
5
 
2.6%
5
 
2.6%
5
 
2.6%
Other values (61) 99
50.5%
Common
ValueCountFrequency (%)
1 1129
14.9%
883
11.6%
2 864
11.4%
- 589
 
7.8%
494
 
6.5%
494
 
6.5%
3 426
 
5.6%
5 371
 
4.9%
4 350
 
4.6%
6 348
 
4.6%
Other values (11) 1648
21.7%
Latin
ValueCountFrequency (%)
M 3
 
10.0%
o 3
 
10.0%
n 3
 
10.0%
a 2
 
6.7%
i 2
 
6.7%
m 2
 
6.7%
A 2
 
6.7%
C 2
 
6.7%
S 1
 
3.3%
E 1
 
3.3%
Other values (9) 9
30.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 11382
59.3%
ASCII 6632
34.5%
None 994
 
5.2%
Hangul 196
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1129
17.0%
883
13.3%
2 864
13.0%
- 589
8.9%
3 426
 
6.4%
5 371
 
5.6%
4 350
 
5.3%
6 348
 
5.2%
0 346
 
5.2%
7 278
 
4.2%
Other values (26) 1048
15.8%
CJK
ValueCountFrequency (%)
998
 
8.8%
803
 
7.1%
801
 
7.0%
799
 
7.0%
796
 
7.0%
795
 
7.0%
793
 
7.0%
793
 
7.0%
677
 
5.9%
526
 
4.6%
Other values (201) 3601
31.6%
None
ValueCountFrequency (%)
494
49.7%
494
49.7%
4
 
0.4%
2
 
0.2%
Hangul
ValueCountFrequency (%)
20
 
10.2%
15
 
7.7%
12
 
6.1%
12
 
6.1%
12
 
6.1%
6
 
3.1%
5
 
2.6%
5
 
2.6%
5
 
2.6%
5
 
2.6%
Other values (61) 99
50.5%

개요
Text

Distinct795
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2023-12-11T14:32:50.695993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length369
Median length157
Mean length105.24623
Min length29

Characters and Unicode

Total characters83776
Distinct characters2063
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique794 ?
Unique (%)99.7%

Sample

1st row電視劇中心是導演兼編劇柳致?從美國洛克菲勒基金會爭取資金支持建造的?劇專用劇場。該電視劇中心由金重業(1922年-1988年) 設計建成?於1962年正式開館。以財團法人韓國?劇?究所?起點的電視劇中心?是韓國現代劇運動的發源地,也是發揮重要作用的組織機構。自20世紀80年代起,電視劇中心也被用作首爾藝術大學主要的實習舞臺。2001年首爾藝術大學搬遷至安山,首爾市租賃該電視劇中心?於2009年6月以南山藝術中心的名義重新開館運營。
2nd row大使酒店是擁有60多年歷史的特1級觀光酒店,是大使集團的連鎖公司。
3rd row茶山洞居民中心是面積0.51㎢,處理金湖洞路以南和茶山路以西地區新堂洞行政業務與居民申請業務的地方行政機構。營運時間?周一到周五上午9點到下午6點,位於地鐵3、6號線藥水站8號出口,步行約4分鐘距離。
4th row自擊漏是朝鮮時代的國家標準鐘?,每個時辰水鐘自動響鐘報時。1536年(中宗31),模?1434年(世宗16)蔣英實製造的水鐘製成了昌慶宮自擊漏。該水鐘先是保存在昌慶宮報漏閣,現在轉至德壽宮保管。1985年自擊漏被認定?韓國國寶第229號。
5th row東國大學是一所位於中區的綜合私立大學,前身是佛?界於1906年創立的明進學校。1946年升格?東國大學,設有11所專科院系、?究所以及54所?究機構。位於首爾市中區筆洞路1路30。
ValueCountFrequency (%)
7
 
0.7%
這裡原是日帝??期日本人的公墓,但在1936年?解決首爾人口過密化而進行的城市規劃整理過程中搬遷墓地和火葬場建成文化住宅園區。 3
 
0.3%
fletcher 2
 
0.2%
henry 2
 
0.2%
seoul 2
 
0.2%
club 2
 
0.2%
spa 2
 
0.2%
此經典是在誠庵古書博物館裡保管的《大方廣佛華嚴經》周本卷6。是木版寺刹本,1卷1軸。 2
 
0.2%
wall)和韻律壁川。 1
 
0.1%
溪川黃鶴橋位於?溪8街十字路口的南邊,南北向連接蘭溪路。這裡設置有通向散步路的電梯,再往前走一程就是可換乘首爾地鐵1、2號線的新設洞站。沿著?溪川散步路向東(下游),設有濟州道民廣場、願望牆(wishing 1
 
0.1%
Other values (995) 995
97.6%
2023-12-11T14:32:51.133477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2696
 
3.2%
? 2345
 
2.8%
2029
 
2.4%
2024
 
2.4%
1 1837
 
2.2%
1200
 
1.4%
1193
 
1.4%
9 1170
 
1.4%
0 897
 
1.1%
875
 
1.0%
Other values (2053) 67510
80.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66256
79.1%
Decimal Number 7259
 
8.7%
Other Punctuation 7197
 
8.6%
Lowercase Letter 1021
 
1.2%
Close Punctuation 484
 
0.6%
Open Punctuation 471
 
0.6%
Uppercase Letter 455
 
0.5%
Space Separator 223
 
0.3%
Dash Punctuation 132
 
0.2%
Math Symbol 126
 
0.2%
Other values (3) 152
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2696
 
4.1%
1200
 
1.8%
1193
 
1.8%
875
 
1.3%
804
 
1.2%
736
 
1.1%
717
 
1.1%
673
 
1.0%
632
 
1.0%
588
 
0.9%
Other values (1950) 56142
84.7%
Lowercase Letter
ValueCountFrequency (%)
e 130
12.7%
n 104
10.2%
a 91
8.9%
m 90
 
8.8%
o 88
 
8.6%
r 70
 
6.9%
l 64
 
6.3%
i 60
 
5.9%
t 52
 
5.1%
s 46
 
4.5%
Other values (17) 226
22.1%
Uppercase Letter
ValueCountFrequency (%)
S 46
 
10.1%
C 45
 
9.9%
A 41
 
9.0%
M 33
 
7.3%
T 23
 
5.1%
H 23
 
5.1%
N 22
 
4.8%
B 22
 
4.8%
P 21
 
4.6%
E 21
 
4.6%
Other values (16) 158
34.7%
Other Punctuation
ValueCountFrequency (%)
? 2345
32.6%
2029
28.2%
2024
28.1%
590
 
8.2%
, 120
 
1.7%
. 70
 
1.0%
7
 
0.1%
& 4
 
0.1%
' 3
 
< 0.1%
: 2
 
< 0.1%
Other values (3) 3
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 1837
25.3%
9 1170
16.1%
0 897
12.4%
2 755
10.4%
6 488
 
6.7%
8 471
 
6.5%
5 455
 
6.3%
3 422
 
5.8%
7 399
 
5.5%
4 365
 
5.0%
Open Punctuation
ValueCountFrequency (%)
306
65.0%
( 66
 
14.0%
47
 
10.0%
43
 
9.1%
8
 
1.7%
1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
303
62.6%
) 69
 
14.3%
56
 
11.6%
47
 
9.7%
8
 
1.7%
1
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 123
97.6%
> 1
 
0.8%
< 1
 
0.8%
1
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 102
77.3%
20
 
15.2%
10
 
7.6%
Other Symbol
ValueCountFrequency (%)
14
41.2%
11
32.4%
9
26.5%
Initial Punctuation
ValueCountFrequency (%)
33
55.0%
27
45.0%
Final Punctuation
ValueCountFrequency (%)
30
51.7%
28
48.3%
Space Separator
ValueCountFrequency (%)
223
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 66142
79.0%
Common 16044
 
19.2%
Latin 1476
 
1.8%
Hangul 114
 
0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
2696
 
4.1%
1200
 
1.8%
1193
 
1.8%
875
 
1.3%
804
 
1.2%
736
 
1.1%
717
 
1.1%
673
 
1.0%
632
 
1.0%
588
 
0.9%
Other values (1924) 56028
84.7%
Latin
ValueCountFrequency (%)
e 130
 
8.8%
n 104
 
7.0%
a 91
 
6.2%
m 90
 
6.1%
o 88
 
6.0%
r 70
 
4.7%
l 64
 
4.3%
i 60
 
4.1%
t 52
 
3.5%
s 46
 
3.1%
Other values (43) 681
46.1%
Common
ValueCountFrequency (%)
? 2345
14.6%
2029
12.6%
2024
12.6%
1 1837
11.4%
9 1170
 
7.3%
0 897
 
5.6%
2 755
 
4.7%
590
 
3.7%
6 488
 
3.0%
8 471
 
2.9%
Other values (40) 3438
21.4%
Hangul
ValueCountFrequency (%)
48
42.1%
12
 
10.5%
8
 
7.0%
8
 
7.0%
7
 
6.1%
5
 
4.4%
3
 
2.6%
3
 
2.6%
2
 
1.8%
2
 
1.8%
Other values (16) 16
 
14.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 66102
78.9%
ASCII 11859
 
14.2%
None 5498
 
6.6%
Punctuation 128
 
0.2%
Hangul 114
 
0.1%
CJK Compat Ideographs 40
 
< 0.1%
CJK Compat 34
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

CJK
ValueCountFrequency (%)
2696
 
4.1%
1200
 
1.8%
1193
 
1.8%
875
 
1.3%
804
 
1.2%
736
 
1.1%
717
 
1.1%
673
 
1.0%
632
 
1.0%
588
 
0.9%
Other values (1911) 55988
84.7%
ASCII
ValueCountFrequency (%)
? 2345
19.8%
1 1837
15.5%
9 1170
9.9%
0 897
 
7.6%
2 755
 
6.4%
6 488
 
4.1%
8 471
 
4.0%
5 455
 
3.8%
3 422
 
3.6%
7 399
 
3.4%
Other values (66) 2620
22.1%
None
ValueCountFrequency (%)
2029
36.9%
2024
36.8%
590
 
10.7%
306
 
5.6%
303
 
5.5%
56
 
1.0%
47
 
0.9%
47
 
0.9%
43
 
0.8%
20
 
0.4%
Other values (8) 33
 
0.6%
Hangul
ValueCountFrequency (%)
48
42.1%
12
 
10.5%
8
 
7.0%
8
 
7.0%
7
 
6.1%
5
 
4.4%
3
 
2.6%
3
 
2.6%
2
 
1.8%
2
 
1.8%
Other values (16) 16
 
14.0%
Punctuation
ValueCountFrequency (%)
33
25.8%
30
23.4%
28
21.9%
27
21.1%
10
 
7.8%
CJK Compat Ideographs
ValueCountFrequency (%)
17
42.5%
6
 
15.0%
5
 
12.5%
2
 
5.0%
2
 
5.0%
1
 
2.5%
1
 
2.5%
1
 
2.5%
1
 
2.5%
1
 
2.5%
Other values (3) 3
 
7.5%
CJK Compat
ValueCountFrequency (%)
14
41.2%
11
32.4%
9
26.5%
Math Operators
ValueCountFrequency (%)
1
100.0%

역사정보
Text

MISSING 

Distinct734
Distinct (%)97.7%
Missing45
Missing (%)5.7%
Memory size6.3 KiB
2023-12-11T14:32:51.481295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length547
Median length213
Mean length87.234354
Min length7

Characters and Unicode

Total characters65513
Distinct characters1771
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique726 ?
Unique (%)96.7%

Sample

1st row1962年竣工 2009年重新開館
2nd row1955年 錦繡莊酒店開業 1977年 升格?觀光酒店特級 1989年 與雅高集團簽署索菲特品牌特許經營協議 1993年 評價?首爾市綜合評價最優秀酒店 2008年 升格?特1級 2009年 更名??首爾?爾曼大使酒店」,與雅高集團簽署?爾曼品牌特許經營協議 2013年 大宴會廳쎦新
3rd row1434年蔣英實製造了自擊漏 1536年?照蔣英實自擊漏重新製作了自擊漏 1938年將昌慶宮報漏閣自擊漏移至德壽宮 1985年被認定?韓國國寶第229號
4th row1906年 設立佛?界明進學校 1946年 升格?東國大學 1940年 改稱惠化專科學校 1953年 改組?綜合大學 2014年 擁有11個院系和?究所、54個?究機構,學生人數達到1萬8924名
5th row1979平和市場開業 1997工程後再開業 2013傳統市場附設停車場委託業務相關的協議
ValueCountFrequency (%)
2009年 48
 
0.7%
1945年 44
 
0.7%
2005年 43
 
0.6%
1946年 39
 
0.6%
2008年 37
 
0.6%
2010年 35
 
0.5%
2012年 34
 
0.5%
2013年 33
 
0.5%
2004年 33
 
0.5%
2000年 33
 
0.5%
Other values (3867) 6307
94.3%
2023-12-11T14:32:52.001966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6176
 
9.4%
1 3453
 
5.3%
9 2801
 
4.3%
2547
 
3.9%
0 1961
 
3.0%
? 1938
 
3.0%
2 1335
 
2.0%
8 899
 
1.4%
6 818
 
1.2%
5 757
 
1.2%
Other values (1761) 42828
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 40859
62.4%
Decimal Number 13973
 
21.3%
Space Separator 6176
 
9.4%
Other Punctuation 2670
 
4.1%
Uppercase Letter 432
 
0.7%
Close Punctuation 406
 
0.6%
Lowercase Letter 384
 
0.6%
Open Punctuation 377
 
0.6%
Initial Punctuation 70
 
0.1%
Final Punctuation 61
 
0.1%
Other values (3) 105
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2547
 
6.2%
657
 
1.6%
548
 
1.3%
519
 
1.3%
499
 
1.2%
494
 
1.2%
462
 
1.1%
434
 
1.1%
377
 
0.9%
340
 
0.8%
Other values (1661) 33982
83.2%
Lowercase Letter
ValueCountFrequency (%)
e 48
12.5%
o 37
9.6%
l 33
 
8.6%
n 30
 
7.8%
s 30
 
7.8%
i 28
 
7.3%
t 27
 
7.0%
a 25
 
6.5%
r 19
 
4.9%
b 16
 
4.2%
Other values (15) 91
23.7%
Uppercase Letter
ValueCountFrequency (%)
M 41
 
9.5%
C 34
 
7.9%
E 30
 
6.9%
S 29
 
6.7%
B 27
 
6.2%
T 27
 
6.2%
O 25
 
5.8%
A 23
 
5.3%
D 22
 
5.1%
N 19
 
4.4%
Other values (14) 155
35.9%
Other Punctuation
ValueCountFrequency (%)
? 1938
72.6%
404
 
15.1%
167
 
6.3%
, 90
 
3.4%
. 24
 
0.9%
20
 
0.7%
: 10
 
0.4%
/ 4
 
0.1%
4
 
0.1%
' 3
 
0.1%
Other values (4) 6
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 3453
24.7%
9 2801
20.0%
0 1961
14.0%
2 1335
 
9.6%
8 899
 
6.4%
6 818
 
5.9%
5 757
 
5.4%
4 721
 
5.2%
7 673
 
4.8%
3 555
 
4.0%
Close Punctuation
ValueCountFrequency (%)
216
53.2%
80
 
19.7%
62
 
15.3%
) 43
 
10.6%
4
 
1.0%
] 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
215
57.0%
79
 
21.0%
( 44
 
11.7%
35
 
9.3%
3
 
0.8%
[ 1
 
0.3%
Math Symbol
ValueCountFrequency (%)
~ 42
85.7%
2
 
4.1%
< 2
 
4.1%
1
 
2.0%
1
 
2.0%
> 1
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 49
90.7%
4
 
7.4%
1
 
1.9%
Initial Punctuation
ValueCountFrequency (%)
45
64.3%
25
35.7%
Final Punctuation
ValueCountFrequency (%)
43
70.5%
18
29.5%
Space Separator
ValueCountFrequency (%)
6176
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 40717
62.2%
Common 23838
36.4%
Latin 816
 
1.2%
Hangul 142
 
0.2%

Most frequent character per script

Han
ValueCountFrequency (%)
2547
 
6.3%
657
 
1.6%
548
 
1.3%
519
 
1.3%
499
 
1.2%
494
 
1.2%
462
 
1.1%
434
 
1.1%
377
 
0.9%
340
 
0.8%
Other values (1646) 33840
83.1%
Common
ValueCountFrequency (%)
6176
25.9%
1 3453
14.5%
9 2801
11.8%
0 1961
 
8.2%
? 1938
 
8.1%
2 1335
 
5.6%
8 899
 
3.8%
6 818
 
3.4%
5 757
 
3.2%
4 721
 
3.0%
Other values (41) 2979
12.5%
Latin
ValueCountFrequency (%)
e 48
 
5.9%
M 41
 
5.0%
o 37
 
4.5%
C 34
 
4.2%
l 33
 
4.0%
E 30
 
3.7%
n 30
 
3.7%
s 30
 
3.7%
S 29
 
3.6%
i 28
 
3.4%
Other values (39) 476
58.3%
Hangul
ValueCountFrequency (%)
101
71.1%
15
 
10.6%
10
 
7.0%
4
 
2.8%
2
 
1.4%
1
 
0.7%
1
 
0.7%
1
 
0.7%
1
 
0.7%
1
 
0.7%
Other values (5) 5
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
CJK 40702
62.1%
ASCII 23219
35.4%
None 1297
 
2.0%
Hangul 142
 
0.2%
Punctuation 132
 
0.2%
CJK Compat Ideographs 15
 
< 0.1%
CJK Compat 2
 
< 0.1%
Arrows 2
 
< 0.1%
Math Operators 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6176
26.6%
1 3453
14.9%
9 2801
12.1%
0 1961
 
8.4%
? 1938
 
8.3%
2 1335
 
5.7%
8 899
 
3.9%
6 818
 
3.5%
5 757
 
3.3%
4 721
 
3.1%
Other values (65) 2360
 
10.2%
CJK
ValueCountFrequency (%)
2547
 
6.3%
657
 
1.6%
548
 
1.3%
519
 
1.3%
499
 
1.2%
494
 
1.2%
462
 
1.1%
434
 
1.1%
377
 
0.9%
340
 
0.8%
Other values (1643) 33825
83.1%
None
ValueCountFrequency (%)
404
31.1%
216
16.7%
215
16.6%
167
12.9%
80
 
6.2%
79
 
6.1%
62
 
4.8%
35
 
2.7%
20
 
1.5%
4
 
0.3%
Other values (6) 15
 
1.2%
Hangul
ValueCountFrequency (%)
101
71.1%
15
 
10.6%
10
 
7.0%
4
 
2.8%
2
 
1.4%
1
 
0.7%
1
 
0.7%
1
 
0.7%
1
 
0.7%
1
 
0.7%
Other values (5) 5
 
3.5%
Punctuation
ValueCountFrequency (%)
45
34.1%
43
32.6%
25
18.9%
18
 
13.6%
1
 
0.8%
CJK Compat Ideographs
ValueCountFrequency (%)
7
46.7%
6
40.0%
2
 
13.3%
CJK Compat
ValueCountFrequency (%)
2
100.0%
Arrows
ValueCountFrequency (%)
2
100.0%
Math Operators
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct310
Distinct (%)38.9%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2023-12-11T14:32:52.221557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length7
Mean length8.5866834
Min length2

Characters and Unicode

Total characters6835
Distinct characters117
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique172 ?
Unique (%)21.6%

Sample

1st row現代/1962
2nd row現代/1955
3rd row現代/2013
4th row朝鮮時代/1536
5th row大韓帝國/1906
ValueCountFrequency (%)
朝鮮/不詳 54
 
6.7%
現代/2005 26
 
3.2%
現代/2000 20
 
2.5%
現代/2009 14
 
1.7%
現代/1962 11
 
1.4%
現代/1970 11
 
1.4%
現代/1968 11
 
1.4%
現代/1946 9
 
1.1%
現代/1971 9
 
1.1%
現代/2008 8
 
1.0%
Other values (306) 638
78.7%
2023-12-11T14:32:52.565164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 805
 
11.8%
1 704
 
10.3%
9 591
 
8.6%
502
 
7.3%
0 443
 
6.5%
442
 
6.5%
2 218
 
3.2%
6 204
 
3.0%
195
 
2.9%
195
 
2.9%
Other values (107) 2536
37.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2903
42.5%
Other Letter 2858
41.8%
Other Punctuation 868
 
12.7%
Close Punctuation 91
 
1.3%
Open Punctuation 91
 
1.3%
Space Separator 15
 
0.2%
Math Symbol 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
502
17.6%
442
15.5%
195
 
6.8%
195
 
6.8%
99
 
3.5%
98
 
3.4%
90
 
3.1%
82
 
2.9%
81
 
2.8%
78
 
2.7%
Other values (86) 996
34.8%
Decimal Number
ValueCountFrequency (%)
1 704
24.3%
9 591
20.4%
0 443
15.3%
2 218
 
7.5%
6 204
 
7.0%
8 179
 
6.2%
7 166
 
5.7%
5 153
 
5.3%
4 132
 
4.5%
3 113
 
3.9%
Other Punctuation
ValueCountFrequency (%)
/ 805
92.7%
? 44
 
5.1%
12
 
1.4%
, 6
 
0.7%
1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
57
62.6%
) 34
37.4%
Open Punctuation
ValueCountFrequency (%)
57
62.6%
( 34
37.4%
Space Separator
ValueCountFrequency (%)
15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3977
58.2%
Han 2858
41.8%

Most frequent character per script

Han
ValueCountFrequency (%)
502
17.6%
442
15.5%
195
 
6.8%
195
 
6.8%
99
 
3.5%
98
 
3.4%
90
 
3.1%
82
 
2.9%
81
 
2.8%
78
 
2.7%
Other values (86) 996
34.8%
Common
ValueCountFrequency (%)
/ 805
20.2%
1 704
17.7%
9 591
14.9%
0 443
11.1%
2 218
 
5.5%
6 204
 
5.1%
8 179
 
4.5%
7 166
 
4.2%
5 153
 
3.8%
4 132
 
3.3%
Other values (11) 382
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3850
56.3%
CJK 2858
41.8%
None 127
 
1.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 805
20.9%
1 704
18.3%
9 591
15.4%
0 443
11.5%
2 218
 
5.7%
6 204
 
5.3%
8 179
 
4.6%
7 166
 
4.3%
5 153
 
4.0%
4 132
 
3.4%
Other values (7) 255
 
6.6%
CJK
ValueCountFrequency (%)
502
17.6%
442
15.5%
195
 
6.8%
195
 
6.8%
99
 
3.5%
98
 
3.4%
90
 
3.1%
82
 
2.9%
81
 
2.8%
78
 
2.7%
Other values (86) 996
34.8%
None
ValueCountFrequency (%)
57
44.9%
57
44.9%
12
 
9.4%
1
 
0.8%
Distinct83
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2023-12-11T14:32:52.794605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length34
Mean length16.13191
Min length7

Characters and Unicode

Total characters12841
Distinct characters232
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)3.1%

Sample

1st row場地及設施/展示、觀纜設施/劇院、小劇場
2nd row場地及設施/住宿、?食/賓館
3rd row場地及設施/其他周邊設施/其他
4th row文化/活字、陶器、儀器類/科學儀器
5th row場地及設施/其他周邊設施/其他
ValueCountFrequency (%)
文化/遺址、史迹/史址、殿址、遺址、原址 148
 
16.8%
場地及設施/其他周邊設施/其他 123
 
14.0%
場地及設施/交通/其他 41
 
4.7%
文化/建築/其他 32
 
3.6%
場地及設施/購物/其他 28
 
3.2%
場地及設施/公園/城市公園(城市自然公園 27
 
3.1%
市民公園 27
 
3.1%
兒童公園等 27
 
3.1%
文化/活字、陶器、儀器類/活字本 25
 
2.8%
場地及設施/展示、觀纜設施/劇院、小劇場 22
 
2.5%
Other values (78) 381
43.2%
2023-12-11T14:32:53.148932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 1594
 
12.4%
882
 
6.9%
799
 
6.2%
620
 
4.8%
620
 
4.8%
445
 
3.5%
428
 
3.3%
426
 
3.3%
411
 
3.2%
409
 
3.2%
Other values (222) 6207
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9896
77.1%
Other Punctuation 2606
 
20.3%
Open Punctuation 127
 
1.0%
Close Punctuation 127
 
1.0%
Space Separator 85
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
799
 
8.1%
620
 
6.3%
620
 
6.3%
445
 
4.5%
428
 
4.3%
426
 
4.3%
411
 
4.2%
409
 
4.1%
409
 
4.1%
403
 
4.1%
Other values (213) 4926
49.8%
Other Punctuation
ValueCountFrequency (%)
/ 1594
61.2%
882
33.8%
, 68
 
2.6%
? 62
 
2.4%
Open Punctuation
ValueCountFrequency (%)
( 125
98.4%
2
 
1.6%
Close Punctuation
ValueCountFrequency (%)
) 125
98.4%
2
 
1.6%
Space Separator
ValueCountFrequency (%)
85
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 9896
77.1%
Common 2945
 
22.9%

Most frequent character per script

Han
ValueCountFrequency (%)
799
 
8.1%
620
 
6.3%
620
 
6.3%
445
 
4.5%
428
 
4.3%
426
 
4.3%
411
 
4.2%
409
 
4.1%
409
 
4.1%
403
 
4.1%
Other values (213) 4926
49.8%
Common
ValueCountFrequency (%)
/ 1594
54.1%
882
29.9%
( 125
 
4.2%
) 125
 
4.2%
85
 
2.9%
, 68
 
2.3%
? 62
 
2.1%
2
 
0.1%
2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
CJK 9896
77.1%
ASCII 2059
 
16.0%
None 886
 
6.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 1594
77.4%
( 125
 
6.1%
) 125
 
6.1%
85
 
4.1%
, 68
 
3.3%
? 62
 
3.0%
None
ValueCountFrequency (%)
882
99.5%
2
 
0.2%
2
 
0.2%
CJK
ValueCountFrequency (%)
799
 
8.1%
620
 
6.3%
620
 
6.3%
445
 
4.5%
428
 
4.3%
426
 
4.3%
411
 
4.2%
409
 
4.1%
409
 
4.1%
403
 
4.1%
Other values (213) 4926
49.8%

시작일(발생일)
Text

MISSING 

Distinct260
Distinct (%)33.0%
Missing9
Missing (%)1.1%
Memory size6.3 KiB
2023-12-11T14:32:53.392567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length5
Mean length5.2376112
Min length2

Characters and Unicode

Total characters4122
Distinct characters85
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique134 ?
Unique (%)17.0%

Sample

1st row1962年
2nd row1955.0
3rd row2013年
4th row1536年
5th row1906年
ValueCountFrequency (%)
不詳 67
 
8.4%
2005年 26
 
3.3%
未詳 21
 
2.6%
2000年 21
 
2.6%
2009年 14
 
1.8%
1962年 11
 
1.4%
1968年 11
 
1.4%
1970年 11
 
1.4%
1930年代 10
 
1.3%
1960年代 9
 
1.1%
Other values (254) 592
74.7%
2023-12-11T14:32:53.745003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
701
17.0%
1 680
16.5%
9 585
14.2%
0 438
10.6%
2 214
 
5.2%
6 195
 
4.7%
8 173
 
4.2%
7 159
 
3.9%
5 144
 
3.5%
4 126
 
3.1%
Other values (75) 707
17.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2823
68.5%
Other Letter 1147
27.8%
Open Punctuation 59
 
1.4%
Close Punctuation 58
 
1.4%
Other Punctuation 28
 
0.7%
Space Separator 6
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
701
61.1%
88
 
7.7%
72
 
6.3%
57
 
5.0%
22
 
1.9%
21
 
1.8%
20
 
1.7%
15
 
1.3%
11
 
1.0%
9
 
0.8%
Other values (54) 131
 
11.4%
Decimal Number
ValueCountFrequency (%)
1 680
24.1%
9 585
20.7%
0 438
15.5%
2 214
 
7.6%
6 195
 
6.9%
8 173
 
6.1%
7 159
 
5.6%
5 144
 
5.1%
4 126
 
4.5%
3 109
 
3.9%
Other Punctuation
ValueCountFrequency (%)
? 13
46.4%
8
28.6%
, 4
 
14.3%
. 2
 
7.1%
/ 1
 
3.6%
Open Punctuation
ValueCountFrequency (%)
( 35
59.3%
24
40.7%
Close Punctuation
ValueCountFrequency (%)
) 34
58.6%
24
41.4%
Space Separator
ValueCountFrequency (%)
6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2975
72.2%
Han 1147
 
27.8%

Most frequent character per script

Han
ValueCountFrequency (%)
701
61.1%
88
 
7.7%
72
 
6.3%
57
 
5.0%
22
 
1.9%
21
 
1.8%
20
 
1.7%
15
 
1.3%
11
 
1.0%
9
 
0.8%
Other values (54) 131
 
11.4%
Common
ValueCountFrequency (%)
1 680
22.9%
9 585
19.7%
0 438
14.7%
2 214
 
7.2%
6 195
 
6.6%
8 173
 
5.8%
7 159
 
5.3%
5 144
 
4.8%
4 126
 
4.2%
3 109
 
3.7%
Other values (11) 152
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2919
70.8%
CJK 1147
 
27.8%
None 56
 
1.4%

Most frequent character per block

CJK
ValueCountFrequency (%)
701
61.1%
88
 
7.7%
72
 
6.3%
57
 
5.0%
22
 
1.9%
21
 
1.8%
20
 
1.7%
15
 
1.3%
11
 
1.0%
9
 
0.8%
Other values (54) 131
 
11.4%
ASCII
ValueCountFrequency (%)
1 680
23.3%
9 585
20.0%
0 438
15.0%
2 214
 
7.3%
6 195
 
6.7%
8 173
 
5.9%
7 159
 
5.4%
5 144
 
4.9%
4 126
 
4.3%
3 109
 
3.7%
Other values (8) 96
 
3.3%
None
ValueCountFrequency (%)
24
42.9%
24
42.9%
8
 
14.3%

인물
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing790
Missing (%)99.2%
Memory size6.3 KiB
2023-12-11T14:32:53.890024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.333333
Min length7

Characters and Unicode

Total characters62
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row1417年~1456年
2nd row1713年~1791年
3rd row1416年~1465年
4th row?~1786年
5th row1561年~1637年
ValueCountFrequency (%)
1417年~1456年 1
16.7%
1713年~1791年 1
16.7%
1416年~1465年 1
16.7%
1786年 1
16.7%
1561年~1637年 1
16.7%
1570年~1652年 1
16.7%
2023-12-11T14:32:54.173520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
25.8%
11
17.7%
6 7
11.3%
7 6
 
9.7%
~ 6
 
9.7%
5 5
 
8.1%
4 4
 
6.5%
3 2
 
3.2%
9 1
 
1.6%
? 1
 
1.6%
Other values (3) 3
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44
71.0%
Other Letter 11
 
17.7%
Math Symbol 6
 
9.7%
Other Punctuation 1
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
36.4%
6 7
15.9%
7 6
 
13.6%
5 5
 
11.4%
4 4
 
9.1%
3 2
 
4.5%
9 1
 
2.3%
8 1
 
2.3%
0 1
 
2.3%
2 1
 
2.3%
Other Letter
ValueCountFrequency (%)
11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51
82.3%
Han 11
 
17.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
31.4%
6 7
13.7%
7 6
 
11.8%
~ 6
 
11.8%
5 5
 
9.8%
4 4
 
7.8%
3 2
 
3.9%
9 1
 
2.0%
? 1
 
2.0%
8 1
 
2.0%
Other values (2) 2
 
3.9%
Han
ValueCountFrequency (%)
11
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51
82.3%
CJK 11
 
17.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
31.4%
6 7
13.7%
7 6
 
11.8%
~ 6
 
11.8%
5 5
 
9.8%
4 4
 
7.8%
3 2
 
3.9%
9 1
 
2.0%
? 1
 
2.0%
8 1
 
2.0%
Other values (2) 2
 
3.9%
CJK
ValueCountFrequency (%)
11
100.0%

제공기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
首爾市 中區廳
796 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row首爾市 中區廳
2nd row首爾市 中區廳
3rd row首爾市 中區廳
4th row首爾市 中區廳
5th row首爾市 中區廳

Common Values

ValueCountFrequency (%)
首爾市 中區廳 796
100.0%

Length

2023-12-11T14:32:54.298018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:32:54.389140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
首爾市 796
50.0%
中區廳 796
50.0%

언어유형
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
CHL
796 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
CHL 796
100.0%

Length

2023-12-11T14:32:54.556186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:32:54.659018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
chl 796
100.0%

제작일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
4
796 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4 796
100.0%

Length

2023-12-11T14:32:54.760129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:32:55.172559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 796
100.0%

유형
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
DATA
796 

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 796
100.0%

Length

2023-12-11T14:32:55.298025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:32:55.421091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
data 796
100.0%

형식
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
HTML
796 

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 796
100.0%

Length

2023-12-11T14:32:55.578517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:32:55.702967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
html 796
100.0%

등록일
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2016-02-03 15:41:24.0
697 
2016-02-03 15:41:25.0
99 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2016-02-03 15:41:24.0
2nd row2016-02-03 15:41:24.0
3rd row2016-02-03 15:41:24.0
4th row2016-02-03 15:41:24.0
5th row2016-02-03 15:41:24.0

Common Values

ValueCountFrequency (%)
2016-02-03 15:41:24.0 697
87.6%
2016-02-03 15:41:25.0 99
 
12.4%

Length

2023-12-11T14:32:55.834707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:32:55.956269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2016-02-03 796
50.0%
15:41:24.0 697
43.8%
15:41:25.0 99
 
6.2%

Sample

관리번호명칭관련항목연계자원경도정보(127.XX)위도정보(36.XXX)이명칭지역지번주소도로명주소개요역사정보시대분류주제분류시작일(발생일)인물제공기관언어유형제작일유형형식등록일
0JGH_000073電視劇中心JGH_000625<NA>126.98824837.558777東朗劇場、南山藝術中心首爾特別市 中區 藝場洞<NA>首爾特別市 中區 소파로 138(藝場洞 8-19)電視劇中心是導演兼編劇柳致?從美國洛克菲勒基金會爭取資金支持建造的?劇專用劇場。該電視劇中心由金重業(1922年-1988年) 設計建成?於1962年正式開館。以財團法人韓國?劇?究所?起點的電視劇中心?是韓國現代劇運動的發源地,也是發揮重要作用的組織機構。自20世紀80年代起,電視劇中心也被用作首爾藝術大學主要的實習舞臺。2001年首爾藝術大學搬遷至安山,首爾市租賃該電視劇中心?於2009年6月以南山藝術中心的名義重新開館運營。1962年竣工 2009年重新開館現代/1962場地及設施/展示、觀纜設施/劇院、小劇場1962年<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:24.0
1JGH_000529大使酒店<NA><NA>127.00212437.560595首爾?爾曼大使酒店首爾特別市中區東湖路<NA>首爾特別市中區東湖路287(?忠洞2街186-54)大使酒店是擁有60多年歷史的特1級觀光酒店,是大使集團的連鎖公司。1955年 錦繡莊酒店開業 1977年 升格?觀光酒店特級 1989年 與雅高集團簽署索菲特品牌特許經營協議 1993年 評價?首爾市綜合評價最優秀酒店 2008年 升格?特1級 2009年 更名??首爾?爾曼大使酒店」,與雅高集團簽署?爾曼品牌特許經營協議 2013年 大宴會廳쎦新現代/1955場地及設施/住宿、?食/賓館1955.0<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:24.0
2JGH_000551茶山洞居民中心JGH_000913<NA>127.00827237.55433舊新堂第2洞居民中心首爾特別市中區東湖路<NA>首爾特別市中區東湖路15路50(新堂洞432-24)茶山洞居民中心是面積0.51㎢,處理金湖洞路以南和茶山路以西地區新堂洞行政業務與居民申請業務的地方行政機構。營運時間?周一到周五上午9點到下午6點,位於地鐵3、6號線藥水站8號出口,步行約4分鐘距離。<NA>現代/2013場地及設施/其他周邊設施/其他2013年<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:24.0
3JGH_000386昌慶宮自擊漏JGH_000370<NA>126.97483237.565801德壽宮報漏閣自擊漏首爾特別市 中區 貞洞<NA>首爾特別市 中區 世宗大路 99(貞洞 5-1)自擊漏是朝鮮時代的國家標準鐘?,每個時辰水鐘自動響鐘報時。1536年(中宗31),模?1434年(世宗16)蔣英實製造的水鐘製成了昌慶宮自擊漏。該水鐘先是保存在昌慶宮報漏閣,現在轉至德壽宮保管。1985年自擊漏被認定?韓國國寶第229號。1434年蔣英實製造了自擊漏 1536年?照蔣英實自擊漏重新製作了自擊漏 1938年將昌慶宮報漏閣自擊漏移至德壽宮 1985年被認定?韓國國寶第229號朝鮮時代/1536文化/活字、陶器、儀器類/科學儀器1536年<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:24.0
4JGH_000570東國大學JGH_000571,JGH_000612,JGH_000612,JGH_000682<NA>127.00018737.558258<NA>首爾特別市中區?忠洞2街<NA>首爾特別市中區筆洞路1路30(?忠洞2街192-5)東國大學是一所位於中區的綜合私立大學,前身是佛?界於1906年創立的明進學校。1946年升格?東國大學,設有11所專科院系、?究所以及54所?究機構。位於首爾市中區筆洞路1路30。1906年 設立佛?界明進學校 1946年 升格?東國大學 1940年 改稱惠化專科學校 1953年 改組?綜合大學 2014年 擁有11個院系和?究所、54個?究機構,學生人數達到1萬8924名大韓帝國/1906場地及設施/其他周邊設施/其他1906年<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:24.0
5JGH_000690第一平和市場JGH_000103,JGH_000700,JGH_000701,JGH_000702,JGH_000703,JGH_000722<NA>127.01140337.56854<NA>首爾特別市 中區 新堂洞<NA>首爾特別市 中區 馬場路 13(新堂洞 775)位於首爾特別市中區的舊東大門運動場周邊的新興以及傳統市場一帶已形成‘東大門服裝城觀光特區’。這裡的第一平和市場開業於1979年,是批發零?專門服裝城。1979平和市場開業 1997工程後再開業 2013傳統市場附設停車場委託業務相關的協議現代/1979場地及設施/購物/市場(傳統、藥材集市等)1979年<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:24.0
6JGH_000720?山塔JGH_000715,JGH_000721<NA>127.00877937.568894?塔(DOOTA)首爾特別市 中區 乙支路6街<NA>首爾特別市 中區 ?忠壇路 275(乙支路6街 18-12)?山塔(Doosan Tower)是位於首爾特別市中區乙支路六街的時裝專賣購物中心,於1999年開業。由?山塔(株)經營,經常叫‘?塔(DOOTA)’。 經銷男裝、女裝、時裝雜貨等,日顧客量?10萬多人,是首爾有名的地方。1998 建築物 完工 1999 商家 開店, 設立?山塔(株) 2002 行業最初實施銷?價 標示制 2009 重新 開業現代/1999場地及設施/購物/其他1999年<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:24.0
7JGH_000300崇禮門<NA>JGS_000022126.97532837.559992南大門首爾特別市中區南大門路4街<NA>首爾特別市中區世宗大路40(南大門路4街29)崇禮門是朝鮮前期的城門,位於首爾特別市中區南大門路4街。崇禮門是地處首爾都城南部的正門,故而亦稱南大門。崇禮門曾是朝鮮首都漢陽的主要關門。君王會在崇禮門迎接或餞送使臣與大臣;君王出行的御駕也會經過崇禮門回景福宮。崇禮門於1962年12月20日被指定?國寶第1號。1395年 崇禮門開工 1398年 崇禮門竣工 1447年 崇禮門改建 1479年 進行大規模維修工程 1962年 被指定?國寶第1號 2008年 發生火災 2010年 著手復原工作 2013年 ?行復原紀念式?對公?開放朝鮮時代/1398文化/建築/門1398年<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:24.0
8JGH_000279倉洞川水閣橋舊址<NA><NA>126.97682237.560756水閣大橋首爾特別市中區南大門路4街<NA>首爾特別市中區南大門路4街24-1一帶倉洞川水閣橋舊址是曾架設於倉洞川上的水閣橋所在地。倉洞川發源於首爾特別市中區南山西側山麓,流經市政廳前,流過武橋與小廣橋後最終匯入?溪川,倉洞川之名源於朝鮮時代曾建於此處的宣惠廳倉庫。水閣橋亦稱水閣大橋,現已被?平消失。朝鮮時代初期 建成水閣橋朝鮮/不詳文化/遺址、史迹/史址、殿址、遺址、原址不詳<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:24.0
9JGH_000866東萊先生校正北史詳節<NA><NA>126.97606637.567665<NA>首爾特別市 中區 太平路1街<NA>首爾特別市 中區 世宗大路21路22(太平路1街 60-17) 성암고서博物館此書是在誠庵古書博物館裡保管的1本《東萊先生校正北史詳節》卷6金屬活字版。對?究高麗和朝鮮時代的活字體?重要的資料。1973 國寶第149-2號指定朝鮮/1403文化/活字、陶器、儀器類/金屬活字1403年<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:25.0
관리번호명칭관련항목연계자원경도정보(127.XX)위도정보(36.XXX)이명칭지역지번주소도로명주소개요역사정보시대분류주제분류시작일(발생일)인물제공기관언어유형제작일유형형식등록일
786JGH_000850三尊佛碑像<NA><NA>126.99906237.557968<NA>首爾特別市中區筆洞路<NA>首爾特別市中區筆洞路1街30(?忠洞2街 山192-155) 東國大學圖書館東國大學圖書館收藏的統一新羅時代的石造佛像三尊佛碑像1件。1982年 指定?寶物第742號統一新羅/不詳文化/建築/佛像不詳<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:25.0
787JGH_000851月印釋譜 卷7、8<NA><NA>126.99906237.557968<NA>首爾特別市中區筆洞路<NA>首爾特別市中區筆洞路1街30(?忠洞2街92-155) 東國大學圖書館本書是東國大學圖書館收藏的《月印釋譜》木刻本2卷2冊-卷7與卷8,由朝鮮時代地方官署發行。1983年 指定?寶物第745-2號朝鮮/不詳文化/活字、陶器、儀器類/活字本不詳<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:25.0
788JGH_000868大方廣佛華嚴經 周本卷36JGH_000867,JGH_000869,JGH_000870,JGH_000871,JGH_000872,JGH_000873,JGH_000874<NA>126.97606637.567665<NA>首爾特別市 中區 太平路1街<NA>首爾特別市 中區 世宗大路21路22(太平路1街 60-17) 성암고서博物館此經典是在誠庵古書博物館裡保管的《大方廣佛華嚴經》周本卷36。是木版寺刹本,1卷1軸。1981 國寶第204號指定高麗/未詳文化/活字、陶器、儀器類/活字本未詳<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:25.0
789JGH_000872大方廣佛華嚴經 周本卷17JGH_000867,JGH_000868,JGH_000869,JGH_000870,JGH_000871,JGH_000873,JGH_000874<NA>126.97606637.567665<NA>首爾特別市 中區 太平路1街<NA>首爾特別市 中區 世宗大路21路22(太平路1街 60-17) 성암고서博物館此經典是在誠庵古書博物館裡保管的《大方廣佛華嚴經》周本卷17, 52。是木版寺刹本,2卷2軸。1981 寶物第688號指定高麗/未詳文化/活字、陶器、儀器類/活字本未詳<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:25.0
790JGH_000873大方廣佛華嚴經 周本卷6JGH_000867,JGH_000868,JGH_000869,JGH_000870,JGH_000871,JGH_000872,JGH_000874<NA>126.97606637.567665<NA>首爾特別市 中區 太平路1街<NA>首爾特別市 中區 世宗大路21路22(太平路1街 60-17) 성암고서博物館此經典是在誠庵古書博物館裡保管的《大方廣佛華嚴經》周本卷6。是木版寺刹本,1卷1軸。1981 寶物第690號指定高麗/未詳文化/活字、陶器、儀器類/活字本未詳<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:25.0
791JGH_000874大方廣佛華嚴經 貞元本卷7JGH_000867,JGH_000868,JGH_000869,JGH_000870,JGH_000871,JGH_000872,JGH_000873<NA>126.97606637.567665<NA>首爾特別市 中區 太平路1街<NA>首爾特別市 中區 世宗大路21路22(太平路1街 60-17) 성암고서博物館此經典是在誠庵古書博物館裡保管的《大方廣佛華嚴經》貞元本卷7。是木版寺刹本,1卷1軸。1981 寶物第689號指定高麗/未詳文化/活字、陶器、儀器類/活字本未詳<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:25.0
792JGH_000875三國史記 卷44?50JGH_000887<NA>126.97606637.567665<NA>首爾特別市 中區 太平路1街<NA>首爾特別市 中區 世宗大路21路22(太平路1街 60-17) 성암고서博物館此書是在誠庵古書博物館裡保管的木版本《三國史記》7卷1本。由高麗時代地方官署編寫,是?究韓國古代史重要的資料。1981 寶物第722號指定高麗/1145文化/活字、陶器、儀器類/活字本1145年<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:25.0
793JGH_000876三國史記JGH_000887<NA>126.97606637.567665<NA>首爾特別市 中區 太平路1街<NA>首爾特別市 中區 世宗大路21路22(太平路1街 60-17) 성암고서博物館此書是在誠庵古書博物館裡保管的木版本《三國史記》50卷 第9本。由高麗時代地方官署編寫,是?究韓國古代史重要的資料。1981 寶物第723號指定高麗/1145文化/活字、陶器、儀器類/活字本1145年<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:25.0
794JGH_000712三益服裝時?城<NA><NA>126.97894737.560169<NA>首爾特別市中區南倉洞<NA>首爾特別市中區南大門市場8路7(南倉洞5)三益服裝時?城是位於首爾特別市中區南倉洞的傳統市場。1985年對外開放的批發零?商街,銷?各種服裝、配飾、皮鞋、百貨等。1985年 三益服裝時?城對外營業 2004年 改建?現代建築現代/1985場地及設施/購物/市場(傳統、藥材集市等)1985年<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:24.0
795JGH_001118屍口門市場JGH_000101<NA>127.01000637.564353光熙門市場首爾特別市中區光熙洞<NA>首爾特別市中區光熙洞2街105光熙門前屍口門市場是首爾特別市中區光熙洞2街光熙門前的市場。光熙門是將都城內的屍體往城外搬運的必經之門,因此又被稱作屍口門。<NA>朝鮮/不詳文化/遺址、史迹/史址、殿址、遺址、原址不詳<NA>首爾市 中區廳CHL4DATAHTML2016-02-03 15:41:25.0