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-13371/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 636 (79.9%) missing valuesMissing
지번주소 has 796 (100.0%) missing valuesMissing
역사정보 has 45 (5.7%) missing valuesMissing
시작일(발생일) has 8 (1.0%) 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 07:10:53.430647
Analysis finished2023-12-11 07:10:55.973861
Duration2.54 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
2023-12-11T16:10:56.197415image/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_000021
2nd rowJGH_000532
3rd rowJGH_000501
4th rowJGH_000431
5th rowJGH_000719
ValueCountFrequency (%)
jgh_000021 1
 
0.1%
jgh_000692 1
 
0.1%
jgh_000694 1
 
0.1%
jgh_000014 1
 
0.1%
jgh_000411 1
 
0.1%
jgh_000327 1
 
0.1%
jgh_000328 1
 
0.1%
jgh_000422 1
 
0.1%
jgh_000695 1
 
0.1%
jgh_000826 1
 
0.1%
Other values (786) 786
98.7%
2023-12-11T16:10:56.664396image/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

Distinct777
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2023-12-11T16:10:56.931067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length6.9849246
Min length2

Characters and Unicode

Total characters5560
Distinct characters671
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

Unique759 ?
Unique (%)95.4%

Sample

1st row木?山烽火台?址
2nd row首?俱?部
3rd row梁?之故居是
4th row南山谷公?
5th row哈?APM
ValueCountFrequency (%)
大方?佛 8
 
1.0%
7
 
0.8%
溪川 7
 
0.8%
忠洞2街 7
 
0.8%
大 5
 
0.6%
大佛?如?密因修?了??菩?万行首楞??（?解） 4
 
0.5%
址 4
 
0.5%
洞 3
 
0.4%
平和市 3
 
0.4%
三?史 2
 
0.2%
Other values (762) 779
94.0%
2023-12-11T16:10:57.396555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 1914
34.4%
址 170
 
3.1%
洞 100
 
1.8%
大 97
 
1.7%
中 73
 
1.3%
南 61
 
1.1%
街 54
 
1.0%
山 52
 
0.9%
川 52
 
0.9%
公 51
 
0.9%
Other values (661) 2936
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3186
57.3%
Other Punctuation 1922
34.6%
Decimal Number 141
 
2.5%
Uppercase Letter 81
 
1.5%
Lowercase Letter 70
 
1.3%
Open Punctuation 53
 
1.0%
Close Punctuation 53
 
1.0%
Space Separator 33
 
0.6%
Dash Punctuation 21
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
址 170
 
5.3%
洞 100
 
3.1%
大 97
 
3.0%
中 73
 
2.3%
南 61
 
1.9%
街 54
 
1.7%
山 52
 
1.6%
川 52
 
1.6%
公 51
 
1.6%
首 51
 
1.6%
Other values (595) 2425
76.1%
Uppercase Letter
ValueCountFrequency (%)
M 8
 
9.9%
C 7
 
8.6%
A 6
 
7.4%
T 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%
i 7
10.0%
o 7
10.0%
l 6
8.6%
t 4
 
5.7%
u 4
 
5.7%
a 4
 
5.7%
d 3
 
4.3%
m 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 (%)
? 1914
99.6%
、 2
 
0.1%
， 2
 
0.1%
. 2
 
0.1%
: 1
 
0.1%
！ 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
（ 48
90.6%
( 4
 
7.5%
[ 1
 
1.9%
Close 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 3176
57.1%
Common 2223
40.0%
Latin 151
 
2.7%
Hangul 10
 
0.2%

Most frequent character per script

Han
ValueCountFrequency (%)
址 170
 
5.4%
洞 100
 
3.1%
大 97
 
3.1%
中 73
 
2.3%
南 61
 
1.9%
街 54
 
1.7%
山 52
 
1.6%
川 52
 
1.6%
公 51
 
1.6%
首 51
 
1.6%
Other values (590) 2415
76.0%
Latin
ValueCountFrequency (%)
e 10
 
6.6%
n 8
 
5.3%
M 8
 
5.3%
C 7
 
4.6%
i 7
 
4.6%
o 7
 
4.6%
A 6
 
4.0%
T 6
 
4.0%
P 6
 
4.0%
l 6
 
4.0%
Other values (32) 80
53.0%
Common
ValueCountFrequency (%)
? 1914
86.1%
（ 48
 
2.2%
） 48
 
2.2%
2 39
 
1.8%
33
 
1.5%
1 31
 
1.4%
- 21
 
0.9%
3 14
 
0.6%
8 12
 
0.5%
6 10
 
0.4%
Other values (14) 53
 
2.4%
Hangul
ValueCountFrequency (%)
쎱 3
30.0%
옠 3
30.0%
씉 2
20.0%
얎 1
 
10.0%
쒛 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 3163
56.9%
ASCII 2273
40.9%
None 101
 
1.8%
CJK Compat Ideographs 13
 
0.2%
Hangul 10
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 1914
84.2%
2 39
 
1.7%
33
 
1.5%
1 31
 
1.4%
- 21
 
0.9%
3 14
 
0.6%
8 12
 
0.5%
e 10
 
0.4%
6 10
 
0.4%
9 9
 
0.4%
Other values (51) 180
 
7.9%
CJK
ValueCountFrequency (%)
址 170
 
5.4%
洞 100
 
3.2%
大 97
 
3.1%
中 73
 
2.3%
南 61
 
1.9%
街 54
 
1.7%
山 52
 
1.6%
川 52
 
1.6%
公 51
 
1.6%
首 51
 
1.6%
Other values (584) 2402
75.9%
None
ValueCountFrequency (%)
（ 48
47.5%
） 48
47.5%
、 2
 
2.0%
， 2
 
2.0%
！ 1
 
1.0%
CJK Compat Ideographs
ValueCountFrequency (%)
李 4
30.8%
若 3
23.1%
金 3
23.1%
蠟 1
 
7.7%
柳 1
 
7.7%
略 1
 
7.7%
Hangul
ValueCountFrequency (%)
쎱 3
30.0%
옠 3
30.0%
씉 2
20.0%
얎 1
 
10.0%
쒛 1
 
10.0%

관련항목
Text

MISSING 

Distinct282
Distinct (%)75.8%
Missing424
Missing (%)53.3%
Memory size6.3 KiB
2023-12-11T16:10:57.597205image/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_000444
2nd rowJGH_000009,JGH_000010,JGH_000011
3rd rowJGH_000444,JGH_000445
4th rowJGH_000077
5th rowJGH_000715,JGH_000721
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_000456 3
 
0.8%
jgh_000131 3
 
0.8%
jgh_000431 2
 
0.5%
Other values (272) 290
78.0%
2023-12-11T16:10:58.003497image/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
2023-12-11T16:10:58.354882image/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_000024
2nd rowJGS_000010
3rd rowJGS_000026
4th rowJGS_000036
5th rowJGS_000030
ValueCountFrequency (%)
jgs_000069 1
 
1.2%
jgs_000038 1
 
1.2%
jgs_000076 1
 
1.2%
jgs_000027 1
 
1.2%
jgs_000072 1
 
1.2%
jgs_000014 1
 
1.2%
jgs_000077 1
 
1.2%
jgs_000007 1
 
1.2%
jgs_000022 1
 
1.2%
jgs_000049 1
 
1.2%
Other values (75) 75
88.2%
2023-12-11T16:10:58.905992image/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%
2 19
 
2.2%
1 19
 
2.2%
4 19
 
2.2%
6 18
 
2.1%
7 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%
2 19
 
3.7%
1 19
 
3.7%
4 19
 
3.7%
6 18
 
3.5%
7 18
 
3.5%
5 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%
2 19
 
3.2%
1 19
 
3.2%
4 19
 
3.2%
6 18
 
3.0%
7 18
 
3.0%
5 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%
2 19
 
2.2%
1 19
 
2.2%
4 19
 
2.2%
6 18
 
2.1%
7 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
2023-12-11T16:10:59.151945image/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
2023-12-11T16:10:59.368898image/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%
126.9817309 5
 
0.6%
126.9847708 5
 
0.6%
126.9805213 5
 
0.6%
127.0097934 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
2023-12-11T16:10:59.541551image/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
2023-12-11T16:10:59.745058image/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%
37.5647524 5
 
0.6%
37.5656187 5
 
0.6%
37.5620607 5
 
0.6%
37.5669654 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 

Distinct149
Distinct (%)93.1%
Missing636
Missing (%)79.9%
Memory size6.3 KiB
2023-12-11T16:11:00.056801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length21
Mean length7.975
Min length2

Characters and Unicode

Total characters1276
Distinct characters310
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

Unique145 ?
Unique (%)90.6%

Sample

1st row南山烽火台?址
2nd row?代海上大厦
3rd row斗塔(DOOTA)
4th row虎岩山泉水，?岩山泉水
5th row派拉蒙??
ValueCountFrequency (%)
忠洞2街文化住宅 6
 
3.5%
楞 4
 
2.3%
大佛?首楞 4
 
2.3%
金 3
 
1.7%
址 2
 
1.2%
新平和市 2
 
1.2%
南山 1
 
0.6%
光熙??服?商 1
 
0.6%
南平和商街 1
 
0.6%
南平和服 1
 
0.6%
Other values (147) 147
85.5%
2023-12-11T16:11:00.664286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 428
33.5%
大 27
 
2.1%
洞 26
 
2.0%
、 24
 
1.9%
址 22
 
1.7%
南 20
 
1.6%
山 17
 
1.3%
首 17
 
1.3%
街 15
 
1.2%
， 14
 
1.1%
Other values (300) 666
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 712
55.8%
Other Punctuation 475
37.2%
Uppercase Letter 34
 
2.7%
Lowercase Letter 16
 
1.3%
Decimal Number 15
 
1.2%
Space Separator 12
 
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 (%)
大 27
 
3.8%
洞 26
 
3.7%
址 22
 
3.1%
南 20
 
2.8%
山 17
 
2.4%
首 17
 
2.4%
街 15
 
2.1%
堂 14
 
2.0%
中 13
 
1.8%
公 12
 
1.7%
Other values (259) 529
74.3%
Uppercase Letter
ValueCountFrequency (%)
O 6
17.6%
P 4
11.8%
A 4
11.8%
T 4
11.8%
L 2
 
5.9%
N 2
 
5.9%
C 2
 
5.9%
S 2
 
5.9%
B 1
 
2.9%
E 1
 
2.9%
Other values (6) 6
17.6%
Lowercase Letter
ValueCountFrequency (%)
o 2
12.5%
n 2
12.5%
z 2
12.5%
u 2
12.5%
e 2
12.5%
a 1
6.2%
k 1
6.2%
y 1
6.2%
g 1
6.2%
w 1
6.2%
Other Punctuation
ValueCountFrequency (%)
? 428
90.1%
、 24
 
5.1%
， 14
 
2.9%
, 6
 
1.3%
/ 3
 
0.6%
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 (%)
12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 706
55.3%
Common 514
40.3%
Latin 50
 
3.9%
Hangul 6
 
0.5%

Most frequent character per script

Han
ValueCountFrequency (%)
大 27
 
3.8%
洞 26
 
3.7%
址 22
 
3.1%
南 20
 
2.8%
山 17
 
2.4%
首 17
 
2.4%
街 15
 
2.1%
堂 14
 
2.0%
中 13
 
1.8%
公 12
 
1.7%
Other values (254) 523
74.1%
Latin
ValueCountFrequency (%)
O 6
 
12.0%
P 4
 
8.0%
A 4
 
8.0%
T 4
 
8.0%
L 2
 
4.0%
o 2
 
4.0%
N 2
 
4.0%
n 2
 
4.0%
z 2
 
4.0%
C 2
 
4.0%
Other values (17) 20
40.0%
Common
ValueCountFrequency (%)
? 428
83.3%
、 24
 
4.7%
， 14
 
2.7%
12
 
2.3%
2 10
 
1.9%
, 6
 
1.2%
（ 4
 
0.8%
1 4
 
0.8%
） 4
 
0.8%
/ 3
 
0.6%
Other values (4) 5
 
1.0%
Hangul
ValueCountFrequency (%)
씉 2
33.3%
싢 1
16.7%
옠 1
16.7%
쎱 1
16.7%
쎇 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
CJK 706
55.3%
ASCII 518
40.6%
None 46
 
3.6%
Hangul 6
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 428
82.6%
12
 
2.3%
2 10
 
1.9%
, 6
 
1.2%
O 6
 
1.2%
1 4
 
0.8%
P 4
 
0.8%
A 4
 
0.8%
T 4
 
0.8%
/ 3
 
0.6%
Other values (27) 37
 
7.1%
CJK
ValueCountFrequency (%)
大 27
 
3.8%
洞 26
 
3.7%
址 22
 
3.1%
南 20
 
2.8%
山 17
 
2.4%
首 17
 
2.4%
街 15
 
2.1%
堂 14
 
2.0%
中 13
 
1.8%
公 12
 
1.7%
Other values (254) 523
74.1%
None
ValueCountFrequency (%)
、 24
52.2%
， 14
30.4%
（ 4
 
8.7%
） 4
 
8.7%
Hangul
ValueCountFrequency (%)
씉 2
33.3%
싢 1
16.7%
옠 1
16.7%
쎱 1
16.7%
쎇 1
16.7%

지역
Text

Distinct189
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2023-12-11T16:11:00.937519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length11.103015
Min length7

Characters and Unicode

Total characters8838
Distinct characters97
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

Unique86 ?
Unique (%)10.8%

Sample

1st row首?特?市中???洞
2nd row首?特?市中??忠?路
3rd row首?特?市 中? 草洞
4th row首?特?市中?退溪路
5th row首?特?市 中? 乙支路6街
ValueCountFrequency (%)
首?特?市 219
17.6%
中 214
 
17.2%
首?特?市中 50
 
4.0%
首?特?市中?退溪路 46
 
3.7%
洞 35
 
2.8%
首?特?市中?世宗大路 31
 
2.5%
首?特?市中??洞路 28
 
2.3%
忠洞2街 28
 
2.3%
首?特?市中?乙支路 24
 
1.9%
首?特?市中??湖路 22
 
1.8%
Other values (180) 544
43.8%
2023-12-11T16:11:01.407351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 2852
32.3%
市 797
 
9.0%
首 796
 
9.0%
特 796
 
9.0%
中 787
 
8.9%
路 448
 
5.1%
445
 
5.0%
洞 352
 
4.0%
街 225
 
2.5%
忠 86
 
1.0%
Other values (87) 1254
14.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5308
60.1%
Other Punctuation 2855
32.3%
Space Separator 445
 
5.0%
Decimal Number 222
 
2.5%
Close Punctuation 3
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
市 797
15.0%
首 796
15.0%
特 796
15.0%
中 787
14.8%
路 448
8.4%
洞 352
6.6%
街 225
 
4.2%
忠 86
 
1.6%
大 77
 
1.5%
南 66
 
1.2%
Other values (71) 878
16.5%
Decimal Number
ValueCountFrequency (%)
2 85
38.3%
1 62
27.9%
3 26
 
11.7%
5 22
 
9.9%
6 13
 
5.9%
4 10
 
4.5%
0 2
 
0.9%
7 1
 
0.5%
8 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
? 2852
99.9%
， 2
 
0.1%
, 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
445
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 5308
60.1%
Common 3530
39.9%

Most frequent character per script

Han
ValueCountFrequency (%)
市 797
15.0%
首 796
15.0%
特 796
15.0%
中 787
14.8%
路 448
8.4%
洞 352
6.6%
街 225
 
4.2%
忠 86
 
1.6%
大 77
 
1.5%
南 66
 
1.2%
Other values (71) 878
16.5%
Common
ValueCountFrequency (%)
? 2852
80.8%
445
 
12.6%
2 85
 
2.4%
1 62
 
1.8%
3 26
 
0.7%
5 22
 
0.6%
6 13
 
0.4%
4 10
 
0.3%
） 3
 
0.1%
- 3
 
0.1%
Other values (6) 9
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
CJK 5308
60.1%
ASCII 3523
39.9%
None 7
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 2852
81.0%
445
 
12.6%
2 85
 
2.4%
1 62
 
1.8%
3 26
 
0.7%
5 22
 
0.6%
6 13
 
0.4%
4 10
 
0.3%
- 3
 
0.1%
0 2
 
0.1%
Other values (3) 3
 
0.1%
CJK
ValueCountFrequency (%)
市 797
15.0%
首 796
15.0%
特 796
15.0%
中 787
14.8%
路 448
8.4%
洞 352
6.6%
街 225
 
4.2%
忠 86
 
1.6%
大 77
 
1.5%
南 66
 
1.2%
Other values (71) 878
16.5%
None
ValueCountFrequency (%)
） 3
42.9%
， 2
28.6%
（ 2
28.6%

지번주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing796
Missing (%)100.0%
Memory size7.1 KiB

도로명주소
Text

Distinct649
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2023-12-11T16:11:01.688810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length38
Mean length24.170854
Min length7

Characters and Unicode

Total characters19240
Distinct characters253
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

Unique583 ?
Unique (%)73.2%

Sample

1st row首?特?市中???洞8-1
2nd row首?特?市中??忠?路86（?忠洞2街208）
3rd row首?特?市 中? 忠武路 42(草洞 18-15)
4th row首?特?市中?退溪路34街28（?洞2街84-1）
5th row首?特?市 中? ?忠?路 253(乙支路6街 18-35)
ValueCountFrequency (%)
首?特?市 216
 
12.6%
中 210
 
12.2%
首?特?市中 48
 
2.8%
一 30
 
1.7%
大 22
 
1.3%
世宗大路21路22(太平路1街 12
 
0.7%
60-17 12
 
0.7%
성암고서博物 12
 
0.7%
首?特?市中?世宗大路99（?洞5-1） 12
 
0.7%
洞路1路30(?洞3街 12
 
0.7%
Other values (840) 1129
65.8%
2023-12-11T16:11:02.120737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 3718
19.3%
1 1129
 
5.9%
路 995
 
5.2%
919
 
4.8%
2 864
 
4.5%
中 803
 
4.2%
市 800
 
4.2%
首 799
 
4.2%
特 796
 
4.1%
洞 678
 
3.5%
Other values (243) 7739
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8037
41.8%
Decimal Number 4627
24.0%
Other Punctuation 3728
19.4%
Space Separator 919
 
4.8%
Close Punctuation 653
 
3.4%
Open Punctuation 652
 
3.4%
Dash Punctuation 587
 
3.1%
Lowercase Letter 17
 
0.1%
Uppercase Letter 13
 
0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
路 995
12.4%
中 803
 
10.0%
市 800
 
10.0%
首 799
 
9.9%
特 796
 
9.9%
洞 678
 
8.4%
街 533
 
6.6%
大 189
 
2.4%
忠 176
 
2.2%
一 133
 
1.7%
Other values (203) 2135
26.6%
Decimal Number
ValueCountFrequency (%)
1 1129
24.4%
2 864
18.7%
3 424
 
9.2%
5 372
 
8.0%
4 349
 
7.5%
6 346
 
7.5%
0 345
 
7.5%
7 278
 
6.0%
8 264
 
5.7%
9 256
 
5.5%
Lowercase Letter
ValueCountFrequency (%)
n 3
17.6%
o 3
17.6%
m 2
11.8%
a 2
11.8%
i 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%
W 1
 
7.7%
D 1
 
7.7%
Y 1
 
7.7%
G 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
? 3718
99.7%
， 4
 
0.1%
, 4
 
0.1%
、 2
 
0.1%
Open Punctuation
ValueCountFrequency (%)
（ 504
77.3%
( 148
 
22.7%
Close Punctuation
ValueCountFrequency (%)
） 503
77.0%
) 150
 
23.0%
Space Separator
ValueCountFrequency (%)
919
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 587
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11173
58.1%
Han 7854
40.8%
Hangul 183
 
1.0%
Latin 30
 
0.2%

Most frequent character per script

Han
ValueCountFrequency (%)
路 995
12.7%
中 803
10.2%
市 800
10.2%
首 799
10.2%
特 796
10.1%
洞 678
 
8.6%
街 533
 
6.8%
大 189
 
2.4%
忠 176
 
2.2%
一 133
 
1.7%
Other values (134) 1952
24.9%
Hangul
ValueCountFrequency (%)
로 16
 
8.7%
서 15
 
8.2%
고 12
 
6.6%
암 12
 
6.6%
성 12
 
6.6%
층 5
 
2.7%
장 5
 
2.7%
입 5
 
2.7%
구 5
 
2.7%
국 4
 
2.2%
Other values (59) 92
50.3%
Common
ValueCountFrequency (%)
? 3718
33.3%
1 1129
 
10.1%
919
 
8.2%
2 864
 
7.7%
- 587
 
5.3%
（ 504
 
4.5%
） 503
 
4.5%
3 424
 
3.8%
5 372
 
3.3%
4 349
 
3.1%
Other values (11) 1804
16.1%
Latin
ValueCountFrequency (%)
n 3
 
10.0%
o 3
 
10.0%
M 3
 
10.0%
m 2
 
6.7%
a 2
 
6.7%
A 2
 
6.7%
i 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 (%)
ASCII 10190
53.0%
CJK 7854
40.8%
None 1013
 
5.3%
Hangul 183
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 3718
36.5%
1 1129
 
11.1%
919
 
9.0%
2 864
 
8.5%
- 587
 
5.8%
3 424
 
4.2%
5 372
 
3.7%
4 349
 
3.4%
6 346
 
3.4%
0 345
 
3.4%
Other values (26) 1137
 
11.2%
CJK
ValueCountFrequency (%)
路 995
12.7%
中 803
10.2%
市 800
10.2%
首 799
10.2%
特 796
10.1%
洞 678
 
8.6%
街 533
 
6.8%
大 189
 
2.4%
忠 176
 
2.2%
一 133
 
1.7%
Other values (134) 1952
24.9%
None
ValueCountFrequency (%)
（ 504
49.8%
） 503
49.7%
， 4
 
0.4%
、 2
 
0.2%
Hangul
ValueCountFrequency (%)
로 16
 
8.7%
서 15
 
8.2%
고 12
 
6.6%
암 12
 
6.6%
성 12
 
6.6%
층 5
 
2.7%
장 5
 
2.7%
입 5
 
2.7%
구 5
 
2.7%
국 4
 
2.2%
Other values (59) 92
50.3%

개요
Text

Distinct795
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2023-12-11T16:11:02.335978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length369
Median length159
Mean length105.23618
Min length29

Characters and Unicode

Total characters83768
Distinct characters1471
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木?山烽火台?址是朝??代的中央烽火台，?南山烽火台的?址。木?山烽火台是朝?太祖于1394年（太祖3年）???定?都城?首次所?，直到1895年（高宗32年）?因甲午改革?致烽燧制被?止，共存?了500余年。自?向西，共?有5?，在?今的位置上修?了1?，于1993年9月20日被指定?首?特?市?念物第14?。
2nd row首?俱?部（Seoul Club） 是1904年高宗?了促?外?人?本?人的文化交流而建立的。成立至今?止，首?俱?部作???制社交俱?部，外?人和??人??各占一半。占地1400多坪，由健身中心、酒?、游泳池、?球?、?童游??等?成。
3rd row梁?之故居是朝??期作?文臣及?者的梁?之（1415~1482）居住?的地方。?位于首?特??中??武路42?。梁?之自??到高?史的改?以?，生平致力于?籍的?纂及?行，曾任弘文?的大提?一?。
4th row南山谷公?是?了重新?原因受日本殖民政府?制的??文化，以及由于市中心?展而?毁的南山。朝??代，?里曾?南??所在地方，日本殖民?治?期朝??兵大司令部居于此?，光?后?由首?市?入了彼?首都防?司令部所在的土地，??其重新改?展示??文化的空?。
5th row哈?APM（Hello APM）是位于首?特?市中?乙支路六街的?大?的商?，2002年??。???哈服?/??씉、?口多功能服、女씉、男씉、?씉??、皮革??等，有?院、???施和?公?字?等。
ValueCountFrequency (%)
7
 
0.7%
里原是日帝强占期日本人的公墓，但在1936年?解?首?人口?密化而?行的城市??整理?程中搬?墓地和火葬?建成文化住宅??。 3
 
0.3%
此?典是在?庵古?博物?里保管的《大方?佛???》周本卷6。是木版寺刹本，1卷1?。 2
 
0.2%
henry 2
 
0.2%
fletcher 2
 
0.2%
club 2
 
0.2%
spa 2
 
0.2%
seoul 2
 
0.2%
宣武祠?址是朝??代宣武祠曾?的所在地，相?于今首?特?市中?西小?路106一?。1598年建成的宣武祠是?念壬辰倭???援救朝?而出兵的明朝??荊芥???的祠堂。宣武祠建筑在日本殖民?治?期被全部앯除，1970年代初因修建停??而消失。 1
 
0.1%
（energy）的?育。 1
 
0.1%
Other values (995) 995
97.6%
2023-12-11T16:11:02.737216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 21387
25.5%
的 2698
 
3.2%
。 2029
 
2.4%
， 2025
 
2.4%
1 1838
 
2.2%
年 1201
 
1.4%
是 1193
 
1.4%
9 1171
 
1.4%
0 898
 
1.1%
于 847
 
1.0%
Other values (1461) 48481
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47155
56.3%
Other Punctuation 26239
31.3%
Decimal Number 7290
 
8.7%
Lowercase Letter 1021
 
1.2%
Uppercase Letter 455
 
0.5%
Open Punctuation 428
 
0.5%
Close Punctuation 428
 
0.5%
Space Separator 223
 
0.3%
Dash Punctuation 131
 
0.2%
Math Symbol 127
 
0.2%
Other values (3) 271
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
的 2698
 
5.7%
年 1201
 
2.5%
是 1193
 
2.5%
于 847
 
1.8%
中 805
 
1.7%
建 739
 
1.6%
在 719
 
1.5%
首 631
 
1.3%
大 590
 
1.3%
路 552
 
1.2%
Other values (1360) 37180
78.8%
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%
H 23
 
5.1%
T 23
 
5.1%
N 22
 
4.8%
B 22
 
4.8%
E 21
 
4.6%
P 21
 
4.6%
Other values (16) 158
34.7%
Other Punctuation
ValueCountFrequency (%)
? 21387
81.5%
。 2029
 
7.7%
， 2025
 
7.7%
、 588
 
2.2%
, 120
 
0.5%
. 71
 
0.3%
； 7
 
< 0.1%
& 4
 
< 0.1%
' 3
 
< 0.1%
: 2
 
< 0.1%
Other values (3) 3
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 1838
25.2%
9 1171
16.1%
0 898
12.3%
2 764
10.5%
6 497
 
6.8%
8 471
 
6.5%
5 465
 
6.4%
3 422
 
5.8%
7 399
 
5.5%
4 365
 
5.0%
Open Punctuation
ValueCountFrequency (%)
（ 306
71.5%
( 66
 
15.4%
《 47
 
11.0%
〈 8
 
1.9%
〔 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
） 303
70.8%
) 69
 
16.1%
》 47
 
11.0%
〉 8
 
1.9%
〕 1
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 124
97.6%
< 1
 
0.8%
> 1
 
0.8%
∼ 1
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 103
78.6%
－ 18
 
13.7%
― 10
 
7.6%
Other Symbol
ValueCountFrequency (%)
㎢ 14
41.2%
㎞ 11
32.4%
㎡ 9
26.5%
Final Punctuation
ValueCountFrequency (%)
” 75
64.1%
’ 42
35.9%
Initial Punctuation
ValueCountFrequency (%)
“ 74
61.7%
‘ 46
38.3%
Space Separator
ValueCountFrequency (%)
223
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 46957
56.1%
Common 35137
41.9%
Latin 1476
 
1.8%
Hangul 198
 
0.2%

Most frequent character per script

Han
ValueCountFrequency (%)
的 2698
 
5.7%
年 1201
 
2.6%
是 1193
 
2.5%
于 847
 
1.8%
中 805
 
1.7%
建 739
 
1.6%
在 719
 
1.5%
首 631
 
1.3%
大 590
 
1.3%
路 552
 
1.2%
Other values (1335) 36982
78.8%
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 (%)
? 21387
60.9%
。 2029
 
5.8%
， 2025
 
5.8%
1 1838
 
5.2%
9 1171
 
3.3%
0 898
 
2.6%
2 764
 
2.2%
、 588
 
1.7%
6 497
 
1.4%
8 471
 
1.3%
Other values (38) 3469
 
9.9%
Hangul
ValueCountFrequency (%)
씉 82
41.4%
앯 48
24.2%
쎇 15
 
7.6%
쎱 9
 
4.5%
옠 8
 
4.0%
쎦 5
 
2.5%
싢 5
 
2.5%
얎 3
 
1.5%
앀 3
 
1.5%
앒 2
 
1.0%
Other values (15) 18
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
CJK 46917
56.0%
ASCII 30935
36.9%
None 5396
 
6.4%
Punctuation 247
 
0.3%
Hangul 198
 
0.2%
CJK Compat Ideographs 40
 
< 0.1%
CJK Compat 34
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 21387
69.1%
1 1838
 
5.9%
9 1171
 
3.8%
0 898
 
2.9%
2 764
 
2.5%
6 497
 
1.6%
8 471
 
1.5%
5 465
 
1.5%
3 422
 
1.4%
7 399
 
1.3%
Other values (66) 2623
 
8.5%
CJK
ValueCountFrequency (%)
的 2698
 
5.8%
年 1201
 
2.6%
是 1193
 
2.5%
于 847
 
1.8%
中 805
 
1.7%
建 739
 
1.6%
在 719
 
1.5%
首 631
 
1.3%
大 590
 
1.3%
路 552
 
1.2%
Other values (1322) 36942
78.7%
None
ValueCountFrequency (%)
。 2029
37.6%
， 2025
37.5%
、 588
 
10.9%
（ 306
 
5.7%
） 303
 
5.6%
》 47
 
0.9%
《 47
 
0.9%
－ 18
 
0.3%
〉 8
 
0.1%
〈 8
 
0.1%
Other values (6) 17
 
0.3%
Hangul
ValueCountFrequency (%)
씉 82
41.4%
앯 48
24.2%
쎇 15
 
7.6%
쎱 9
 
4.5%
옠 8
 
4.0%
쎦 5
 
2.5%
싢 5
 
2.5%
얎 3
 
1.5%
앀 3
 
1.5%
앒 2
 
1.0%
Other values (15) 18
 
9.1%
Punctuation
ValueCountFrequency (%)
” 75
30.4%
“ 74
30.0%
‘ 46
18.6%
’ 42
17.0%
― 10
 
4.0%
CJK Compat Ideographs
ValueCountFrequency (%)
李 17
42.5%
烈 6
 
15.0%
金 5
 
12.5%
路 2
 
5.0%
柳 2
 
5.0%
蠟 1
 
2.5%
盧 1
 
2.5%
閭 1
 
2.5%
聯 1
 
2.5%
老 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
2023-12-11T16:11:03.138149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length547
Median length213
Mean length87.198402
Min length7

Characters and Unicode

Total characters65486
Distinct characters1224
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 row1394年 ?木?山烽火台 1993年 木?山烽火台?址被指定?首?特?市?念物第14?
2nd row1904年 ?促???及外?人文化交流，由高宗?立 2015年 ???一千余名的??及外?人??制社交俱?部
3rd row1415 出生 1441 司??及第后又中科? 1481 ?????地??的?纂 1482 死亡
4th row1989年9月25日 ?入首都防?司令部土地 1990年 南山原貌?原工程基本方??定 南山原貌?原工程100人?成市民委?? 1993年 地形?原及??庭院修建?目?? 1994年 首?千年???念碑???用?式和埋入?式 1995年 南山谷?屋村修建?目 1998年 南山谷?屋村?放
5th row2002 商家 ??
ValueCountFrequency (%)
2009年 47
 
0.7%
1945年 44
 
0.7%
2005年 43
 
0.6%
39
 
0.6%
1946年 38
 
0.6%
2008年 37
 
0.6%
2010年 35
 
0.5%
2012年 34
 
0.5%
2000年 33
 
0.5%
2013年 33
 
0.5%
Other values (3814) 6270
94.2%
2023-12-11T16:11:03.794073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 14911
22.8%
6144
 
9.4%
1 3455
 
5.3%
9 2804
 
4.3%
年 2548
 
3.9%
0 1963
 
3.0%
2 1350
 
2.1%
8 900
 
1.4%
6 837
 
1.3%
5 775
 
1.2%
Other values (1214) 29799
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27794
42.4%
Other Punctuation 15644
23.9%
Decimal Number 14033
21.4%
Space Separator 6144
 
9.4%
Uppercase Letter 432
 
0.7%
Lowercase Letter 384
 
0.6%
Close Punctuation 343
 
0.5%
Open Punctuation 341
 
0.5%
Initial Punctuation 138
 
0.2%
Final Punctuation 128
 
0.2%
Other values (3) 105
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
年 2548
 
9.2%
建 659
 
2.4%
立 498
 
1.8%
大 429
 
1.5%
的 379
 
1.4%
中 340
 
1.2%
名 334
 
1.2%
首 329
 
1.2%
工 324
 
1.2%
被 315
 
1.1%
Other values (1116) 21639
77.9%
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%
T 27
 
6.2%
B 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 (%)
? 14911
95.3%
， 403
 
2.6%
、 167
 
1.1%
, 91
 
0.6%
. 26
 
0.2%
。 21
 
0.1%
: 10
 
0.1%
！ 4
 
< 0.1%
/ 3
 
< 0.1%
／ 2
 
< 0.1%
Other values (4) 6
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 3455
24.6%
9 2804
20.0%
0 1963
14.0%
2 1350
 
9.6%
8 900
 
6.4%
6 837
 
6.0%
5 775
 
5.5%
4 722
 
5.1%
7 673
 
4.8%
3 554
 
3.9%
Math Symbol
ValueCountFrequency (%)
~ 42
85.7%
< 2
 
4.1%
→ 2
 
4.1%
≪ 1
 
2.0%
≫ 1
 
2.0%
> 1
 
2.0%
Close Punctuation
ValueCountFrequency (%)
） 216
63.0%
》 76
 
22.2%
) 46
 
13.4%
〉 4
 
1.2%
] 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
（ 215
63.0%
《 75
 
22.0%
( 47
 
13.8%
〈 3
 
0.9%
[ 1
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 49
90.7%
－ 4
 
7.4%
― 1
 
1.9%
Initial Punctuation
ValueCountFrequency (%)
“ 74
53.6%
‘ 64
46.4%
Final Punctuation
ValueCountFrequency (%)
” 67
52.3%
’ 61
47.7%
Space Separator
ValueCountFrequency (%)
6144
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36876
56.3%
Han 27594
42.1%
Latin 816
 
1.2%
Hangul 200
 
0.3%

Most frequent character per script

Han
ValueCountFrequency (%)
年 2548
 
9.2%
建 659
 
2.4%
立 498
 
1.8%
大 429
 
1.6%
的 379
 
1.4%
中 340
 
1.2%
名 334
 
1.2%
首 329
 
1.2%
工 324
 
1.2%
被 315
 
1.1%
Other values (1099) 21439
77.7%
Common
ValueCountFrequency (%)
? 14911
40.4%
6144
16.7%
1 3455
 
9.4%
9 2804
 
7.6%
0 1963
 
5.3%
2 1350
 
3.7%
8 900
 
2.4%
6 837
 
2.3%
5 775
 
2.1%
4 722
 
2.0%
Other values (39) 3015
 
8.2%
Latin
ValueCountFrequency (%)
e 48
 
5.9%
M 41
 
5.0%
o 37
 
4.5%
C 34
 
4.2%
l 33
 
4.0%
n 30
 
3.7%
E 30
 
3.7%
s 30
 
3.7%
S 29
 
3.6%
i 28
 
3.4%
Other values (39) 476
58.3%
Hangul
ValueCountFrequency (%)
앯 102
51.0%
씉 30
 
15.0%
쎇 16
 
8.0%
옠 15
 
7.5%
쎦 10
 
5.0%
싢 8
 
4.0%
쎱 6
 
3.0%
싲 3
 
1.5%
앧 2
 
1.0%
앀 1
 
0.5%
Other values (7) 7
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36227
55.3%
CJK 27579
42.1%
None 1192
 
1.8%
Punctuation 267
 
0.4%
Hangul 200
 
0.3%
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 (%)
? 14911
41.2%
6144
17.0%
1 3455
 
9.5%
9 2804
 
7.7%
0 1963
 
5.4%
2 1350
 
3.7%
8 900
 
2.5%
6 837
 
2.3%
5 775
 
2.1%
4 722
 
2.0%
Other values (65) 2366
 
6.5%
CJK
ValueCountFrequency (%)
年 2548
 
9.2%
建 659
 
2.4%
立 498
 
1.8%
大 429
 
1.6%
的 379
 
1.4%
中 340
 
1.2%
名 334
 
1.2%
首 329
 
1.2%
工 324
 
1.2%
被 315
 
1.1%
Other values (1096) 21424
77.7%
None
ValueCountFrequency (%)
， 403
33.8%
） 216
18.1%
（ 215
18.0%
、 167
14.0%
》 76
 
6.4%
《 75
 
6.3%
。 21
 
1.8%
！ 4
 
0.3%
〉 4
 
0.3%
－ 4
 
0.3%
Other values (4) 7
 
0.6%
Hangul
ValueCountFrequency (%)
앯 102
51.0%
씉 30
 
15.0%
쎇 16
 
8.0%
옠 15
 
7.5%
쎦 10
 
5.0%
싢 8
 
4.0%
쎱 6
 
3.0%
싲 3
 
1.5%
앧 2
 
1.0%
앀 1
 
0.5%
Other values (7) 7
 
3.5%
Punctuation
ValueCountFrequency (%)
“ 74
27.7%
” 67
25.1%
‘ 64
24.0%
’ 61
22.8%
― 1
 
0.4%
CJK Compat Ideographs
ValueCountFrequency (%)
李 7
46.7%
金 6
40.0%
勒 2
 
13.3%
CJK Compat
ValueCountFrequency (%)
㎡ 2
100.0%
Arrows
ValueCountFrequency (%)
→ 2
100.0%
Math Operators
ValueCountFrequency (%)
≪ 1
50.0%
≫ 1
50.0%

시대분류
Text

Distinct311
Distinct (%)39.1%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2023-12-11T16:11:04.063571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length7
Mean length8.5502513
Min length2

Characters and Unicode

Total characters6806
Distinct characters90
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique173 ?
Unique (%)21.7%

Sample

1st row朝?/1394
2nd row大?帝?/1904
3rd row朝?/1415
4th row?代/1994
5th row?代/2002
ValueCountFrequency (%)
朝?/不 54
 
6.7%
代/2005 26
 
3.2%
代/2000 20
 
2.5%
代/2009 14
 
1.7%
代/1970 11
 
1.4%
代/1962 11
 
1.4%
代/1968 11
 
1.4%
代/1971 9
 
1.1%
代/1946 9
 
1.1%
代/1960年代 8
 
1.0%
Other values (307) 638
78.7%
2023-12-11T16:11:04.533783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 1089
16.0%
/ 805
11.8%
1 705
 
10.4%
9 592
 
8.7%
代 504
 
7.4%
0 444
 
6.5%
2 217
 
3.2%
6 203
 
3.0%
朝 194
 
2.9%
8 178
 
2.6%
Other values (80) 1875
27.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2903
42.7%
Other Punctuation 1913
28.1%
Other Letter 1785
26.2%
Open Punctuation 91
 
1.3%
Close Punctuation 90
 
1.3%
Space Separator 15
 
0.2%
Math Symbol 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
代 504
28.2%
朝 194
 
10.9%
期 97
 
5.4%
日 89
 
5.0%
年 81
 
4.5%
不 77
 
4.3%
本 74
 
4.1%
帝 71
 
4.0%
殖 68
 
3.8%
民 68
 
3.8%
Other values (59) 462
25.9%
Decimal Number
ValueCountFrequency (%)
1 705
24.3%
9 592
20.4%
0 444
15.3%
2 217
 
7.5%
6 203
 
7.0%
8 178
 
6.1%
7 166
 
5.7%
5 153
 
5.3%
4 132
 
4.5%
3 113
 
3.9%
Other Punctuation
ValueCountFrequency (%)
? 1089
56.9%
/ 805
42.1%
， 12
 
0.6%
, 6
 
0.3%
、 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
（ 55
60.4%
( 36
39.6%
Close Punctuation
ValueCountFrequency (%)
） 54
60.0%
) 36
40.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5021
73.8%
Han 1784
 
26.2%
Hangul 1
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
代 504
28.3%
朝 194
 
10.9%
期 97
 
5.4%
日 89
 
5.0%
年 81
 
4.5%
不 77
 
4.3%
本 74
 
4.1%
帝 71
 
4.0%
殖 68
 
3.8%
民 68
 
3.8%
Other values (58) 461
25.8%
Common
ValueCountFrequency (%)
? 1089
21.7%
/ 805
16.0%
1 705
14.0%
9 592
11.8%
0 444
8.8%
2 217
 
4.3%
6 203
 
4.0%
8 178
 
3.5%
7 166
 
3.3%
5 153
 
3.0%
Other values (11) 469
9.3%
Hangul
ValueCountFrequency (%)
쎱 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4899
72.0%
CJK 1784
 
26.2%
None 122
 
1.8%
Hangul 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 1089
22.2%
/ 805
16.4%
1 705
14.4%
9 592
12.1%
0 444
9.1%
2 217
 
4.4%
6 203
 
4.1%
8 178
 
3.6%
7 166
 
3.4%
5 153
 
3.1%
Other values (7) 347
 
7.1%
CJK
ValueCountFrequency (%)
代 504
28.3%
朝 194
 
10.9%
期 97
 
5.4%
日 89
 
5.0%
年 81
 
4.5%
不 77
 
4.3%
本 74
 
4.1%
帝 71
 
4.0%
殖 68
 
3.8%
民 68
 
3.8%
Other values (58) 461
25.8%
None
ValueCountFrequency (%)
（ 55
45.1%
） 54
44.3%
， 12
 
9.8%
、 1
 
0.8%
Hangul
ValueCountFrequency (%)
쎱 1
100.0%

주제분류
Text

Distinct82
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2023-12-11T16:11:04.852752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length34
Mean length16.13191
Min length7

Characters and Unicode

Total characters12841
Distinct characters155
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文化/?址、史迹/烽火台
2nd row?地及?施/休?、?育?施/其他
3rd row文化/人物/故居(址)
4th row?地及?施/公?/城市公?(城市自然公?, 市民公?, ?童公?等)
5th row?地及?施/?物/其他
ValueCountFrequency (%)
文化/?址、史迹/史址、殿址、?址、原址 148
 
16.8%
地及?施/其他周??施/其他 123
 
14.0%
地及?施/交通/其他 41
 
4.7%
文化/建筑/其他 32
 
3.6%
地及?施/?物/其他 28
 
3.2%
地及?施/公?/城市公?(城市自然公 27
 
3.1%
市民公 27
 
3.1%
童公?等 27
 
3.1%
文化/活字、陶器、?器?/活字本 25
 
2.8%
文化/建筑 24
 
2.7%
Other values (76) 379
43.0%
2023-12-11T16:11:05.408754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 2694
21.0%
/ 1594
 
12.4%
、 882
 
6.9%
址 799
 
6.2%
施 620
 
4.8%
及 428
 
3.3%
地 426
 
3.3%
文 411
 
3.2%
他 409
 
3.2%
其 409
 
3.2%
Other values (145) 4169
32.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7264
56.6%
Other Punctuation 5238
40.8%
Open Punctuation 127
 
1.0%
Close Punctuation 127
 
1.0%
Space Separator 85
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
址 799
 
11.0%
施 620
 
8.5%
及 428
 
5.9%
地 426
 
5.9%
文 411
 
5.7%
他 409
 
5.6%
其 409
 
5.6%
化 403
 
5.5%
史 320
 
4.4%
迹 172
 
2.4%
Other values (136) 2867
39.5%
Other Punctuation
ValueCountFrequency (%)
? 2694
51.4%
/ 1594
30.4%
、 882
 
16.8%
, 68
 
1.3%
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 7264
56.6%
Common 5577
43.4%

Most frequent character per script

Han
ValueCountFrequency (%)
址 799
 
11.0%
施 620
 
8.5%
及 428
 
5.9%
地 426
 
5.9%
文 411
 
5.7%
他 409
 
5.6%
其 409
 
5.6%
化 403
 
5.5%
史 320
 
4.4%
迹 172
 
2.4%
Other values (136) 2867
39.5%
Common
ValueCountFrequency (%)
? 2694
48.3%
/ 1594
28.6%
、 882
 
15.8%
( 125
 
2.2%
) 125
 
2.2%
85
 
1.5%
, 68
 
1.2%
（ 2
 
< 0.1%
） 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
CJK 7264
56.6%
ASCII 4691
36.5%
None 886
 
6.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 2694
57.4%
/ 1594
34.0%
( 125
 
2.7%
) 125
 
2.7%
85
 
1.8%
, 68
 
1.4%
None
ValueCountFrequency (%)
、 882
99.5%
（ 2
 
0.2%
） 2
 
0.2%
CJK
ValueCountFrequency (%)
址 799
 
11.0%
施 620
 
8.5%
及 428
 
5.9%
地 426
 
5.9%
文 411
 
5.7%
他 409
 
5.6%
其 409
 
5.6%
化 403
 
5.5%
史 320
 
4.4%
迹 172
 
2.4%
Other values (136) 2867
39.5%

시작일(발생일)
Text

MISSING 

Distinct258
Distinct (%)32.7%
Missing8
Missing (%)1.0%
Memory size6.3 KiB
2023-12-11T16:11:05.767325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length5
Mean length5.2373096
Min length2

Characters and Unicode

Total characters4127
Distinct characters67
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

Unique133 ?
Unique (%)16.9%

Sample

1st row1394年
2nd row1904年
3rd row1415年
4th row1994年
5th row2002年
ValueCountFrequency (%)
不 72
 
9.1%
2005年 26
 
3.3%
未 21
 
2.6%
2000年 21
 
2.6%
2009年 14
 
1.8%
1970年 11
 
1.4%
1968年 11
 
1.4%
1962年 11
 
1.4%
1930年代 10
 
1.3%
1946年 9
 
1.1%
Other values (252) 588
74.1%
2023-12-11T16:11:06.229270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
年 702
17.0%
1 681
16.5%
9 586
14.2%
0 438
10.6%
2 214
 
5.2%
6 196
 
4.7%
8 173
 
4.2%
7 159
 
3.9%
5 144
 
3.5%
? 133
 
3.2%
Other values (57) 701
17.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2827
68.5%
Other Letter 1028
 
24.9%
Other Punctuation 148
 
3.6%
Open Punctuation 59
 
1.4%
Close Punctuation 58
 
1.4%
Space Separator 6
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
年 702
68.3%
不 72
 
7.0%
代 57
 
5.5%
后 23
 
2.2%
定 22
 
2.1%
未 21
 
2.0%
制 16
 
1.6%
以 11
 
1.1%
前 9
 
0.9%
名 9
 
0.9%
Other values (36) 86
 
8.4%
Decimal Number
ValueCountFrequency (%)
1 681
24.1%
9 586
20.7%
0 438
15.5%
2 214
 
7.6%
6 196
 
6.9%
8 173
 
6.1%
7 159
 
5.6%
5 144
 
5.1%
4 126
 
4.5%
3 110
 
3.9%
Other Punctuation
ValueCountFrequency (%)
? 133
89.9%
， 8
 
5.4%
, 4
 
2.7%
. 2
 
1.4%
/ 1
 
0.7%
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 3099
75.1%
Han 1028
 
24.9%

Most frequent character per script

Han
ValueCountFrequency (%)
年 702
68.3%
不 72
 
7.0%
代 57
 
5.5%
后 23
 
2.2%
定 22
 
2.1%
未 21
 
2.0%
制 16
 
1.6%
以 11
 
1.1%
前 9
 
0.9%
名 9
 
0.9%
Other values (36) 86
 
8.4%
Common
ValueCountFrequency (%)
1 681
22.0%
9 586
18.9%
0 438
14.1%
2 214
 
6.9%
6 196
 
6.3%
8 173
 
5.6%
7 159
 
5.1%
5 144
 
4.6%
? 133
 
4.3%
4 126
 
4.1%
Other values (11) 249
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3043
73.7%
CJK 1028
 
24.9%
None 56
 
1.4%

Most frequent character per block

CJK
ValueCountFrequency (%)
年 702
68.3%
不 72
 
7.0%
代 57
 
5.5%
后 23
 
2.2%
定 22
 
2.1%
未 21
 
2.0%
制 16
 
1.6%
以 11
 
1.1%
前 9
 
0.9%
名 9
 
0.9%
Other values (36) 86
 
8.4%
ASCII
ValueCountFrequency (%)
1 681
22.4%
9 586
19.3%
0 438
14.4%
2 214
 
7.0%
6 196
 
6.4%
8 173
 
5.7%
7 159
 
5.2%
5 144
 
4.7%
? 133
 
4.4%
4 126
 
4.1%
Other values (8) 193
 
6.3%
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
2023-12-11T16:11:06.414996image/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 row1713年~1791年
2nd row?~1786年
3rd row1561年~1637年
4th row1570年~1652年
5th row1417年~1456年
ValueCountFrequency (%)
1713年~1791年 1
16.7%
1786年 1
16.7%
1561年~1637年 1
16.7%
1570年~1652年 1
16.7%
1417年~1456年 1
16.7%
1416年~1465年 1
16.7%
2023-12-11T16:11:06.749350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
25.8%
年 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 (%)
年 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 (%)
年 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 (%)
年 11
100.0%

제공기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
首?市 中區廳
796 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row首?市 中區廳
2nd row首?市 中區廳
3rd row首?市 中區廳
4th row首?市 中區廳
5th row首?市 中區廳

Common Values

ValueCountFrequency (%)
首?市 中區廳 796
100.0%

Length

2023-12-11T16:11:06.874154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:11:06.991199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
首?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
CHN
796 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
CHN 796
100.0%

Length

2023-12-11T16:11:07.141023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:11:07.255608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
chn 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

2023-12-11T16:11:07.400343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:11:07.778059image/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

2023-12-11T16:11:07.877831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:11:07.983662image/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

2023-12-11T16:11:08.108295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:11:08.227821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
html 796
100.0%

등록일
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2016-02-03 15:41:17.0
440 
2016-02-03 15:41:16.0
342 
2016-02-03 15:41:18.0
 
14

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2016-02-03 15:41:16.0
2nd row2016-02-03 15:41:17.0
3rd row2016-02-03 15:41:17.0
4th row2016-02-03 15:41:16.0
5th row2016-02-03 15:41:17.0

Common Values

ValueCountFrequency (%)
2016-02-03 15:41:17.0 440
55.3%
2016-02-03 15:41:16.0 342
43.0%
2016-02-03 15:41:18.0 14
 
1.8%

Length

2023-12-11T16:11:08.338034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:11:08.447842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2016-02-03 796
50.0%
15:41:17.0 440
27.6%
15:41:16.0 342
21.5%
15:41:18.0 14
 
0.9%

Sample

관리번호명칭관련항목연계자원경도정보(127.XX)위도정보(36.XXX)이명칭지역지번주소도로명주소개요역사정보시대분류주제분류시작일(발생일)인물제공기관언어유형제작일유형형식등록일
0JGH_000021木?山烽火台?址JGH_000444JGS_000024126.9876237.551742南山烽火台?址首?特?市中???洞<NA>首?特?市中???洞8-1木?山烽火台?址是朝??代的中央烽火台，?南山烽火台的?址。木?山烽火台是朝?太祖于1394年（太祖3年）???定?都城?首次所?，直到1895年（高宗32年）?因甲午改革?致烽燧制被?止，共存?了500余年。自?向西，共?有5?，在?今的位置上修?了1?，于1993年9月20日被指定?首?特?市?念物第14?。1394年 ?木?山烽火台 1993年 木?山烽火台?址被指定?首?特?市?念物第14?朝?/1394文化/?址、史迹/烽火台1394年<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:16.0
1JGH_000532首?俱?部<NA><NA>127.0037437.553215<NA>首?特?市中??忠?路<NA>首?特?市中??忠?路86（?忠洞2街208）首?俱?部（Seoul Club） 是1904年高宗?了促?外?人?本?人的文化交流而建立的。成立至今?止，首?俱?部作???制社交俱?部，外?人和??人??各占一半。占地1400多坪，由健身中心、酒?、游泳池、?球?、?童游??等?成。1904年 ?促???及外?人文化交流，由高宗?立 2015年 ???一千余名的??及外?人??制社交俱?部大?帝?/1904?地及?施/休?、?育?施/其他1904年<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:17.0
2JGH_000501梁?之故居是<NA><NA>126.99298837.564855<NA>首?特?市 中? 草洞<NA>首?特?市 中? 忠武路 42(草洞 18-15)梁?之故居是朝??期作?文臣及?者的梁?之（1415~1482）居住?的地方。?位于首?特??中??武路42?。梁?之自??到高?史的改?以?，生平致力于?籍的?纂及?行，曾任弘文?的大提?一?。1415 出生 1441 司??及第后又中科? 1481 ?????地??的?纂 1482 死亡朝?/1415文化/人物/故居(址)1415年<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:17.0
3JGH_000431南山谷公?JGH_000009,JGH_000010,JGH_000011<NA>126.99356137.558455<NA>首?特?市中?退溪路<NA>首?特?市中?退溪路34街28（?洞2街84-1）南山谷公?是?了重新?原因受日本殖民政府?制的??文化，以及由于市中心?展而?毁的南山。朝??代，?里曾?南??所在地方，日本殖民?治?期朝??兵大司令部居于此?，光?后?由首?市?入了彼?首都防?司令部所在的土地，??其重新改?展示??文化的空?。1989年9月25日 ?入首都防?司令部土地 1990年 南山原貌?原工程基本方??定 南山原貌?原工程100人?成市民委?? 1993年 地形?原及??庭院修建?目?? 1994年 首?千年???念碑???用?式和埋入?式 1995年 南山谷?屋村修建?目 1998年 南山谷?屋村?放?代/1994?地及?施/公?/城市公?(城市自然公?, 市民公?, ?童公?等)1994年<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:16.0
4JGH_000719哈?APM<NA><NA>127.00808537.567502<NA>首?特?市 中? 乙支路6街<NA>首?特?市 中? ?忠?路 253(乙支路6街 18-35)哈?APM（Hello APM）是位于首?特?市中?乙支路六街的?大?的商?，2002年??。???哈服?/??씉、?口多功能服、女씉、男씉、?씉??、皮革??等，有?院、???施和?公?字?等。2002 商家 ???代/2002?地及?施/?物/其他2002年<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:17.0
5JGH_000743白凡??白凡金九像JGH_000444,JGH_000445<NA>126.97990937.555047<NA>首?特?市 中? ??洞1街<NA>首?特?市 中? ??洞1街 100-115白凡??白凡金九像是1969年白凡金九先生?念事??，?了?念?立??家和?育家、政治家金九（1876~1949），在抗日救???和建立?一?家中，表?出的??精神，在南山公?白凡??里面?立的?像，1876 金九 出生 1896 ?了?明成皇后被?之仇??倭兵中尉 1907 ?山?校成立 1909 ??新民? 1919 任上海大?民???政府受邀警?局? 1928 ???立?建싢 1931 ???人??? 1939 任大?民???政府主席 1940 ????光?? 1948 ?展反?信托?治??,主?建立自主?立的南北??一政府 1949 金九 去世 1962 追授建?功??章 1969 白凡??白凡金九像建立?代/1969文化/建筑/ ?像1969年<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:17.0
6JGH_000143??大厦<NA><NA>126.98219637.562277?代海上大厦首?特?市中?明洞二街<NA>首?特?市中?明洞二路20（明洞二街92-3）??大厦都是建筑家席??雄(1938~2011)??,1972年,首?市建筑竣工的首?中?明洞2街。?大厦竣工以后在?方海上火?保?建筑物,1985年?代集?,因此?在出??代海上火?保?公司明洞大?使用。1972年 建筑家??雄??竣工?代/1972?地及?施/其他周??施/其他1972年<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:16.0
7JGH_000076首?浸????育?JGH_000077<NA>126.99867937.561808<NA>首?特?市中?忠武路5街<NA>首?特?市中?西厓路3（忠武路5街55-1）首?浸????育?于1962年完工，是位于首?特?市中?西厓路的首?浸???的附?建筑。首?浸???是625??后南浸???首次在???立的??，?是基督???浸??的母??，也是中心??。首?浸????育?是附?于首?浸???的??，是以?少年和信徒家人??象的?拜和?育空?。?育?1?是??部室，2?是?童部室和家庭部室，3?是?少年?拜室及?少年部室。1946年 ?立?洞浸??? 1949年 更名?大?基督?浸??首??洞?? 1954年 ??拜堂竣工 1962年 建成?育??代/1962文化/建筑/大型??1962年<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:16.0
8JGH_000720斗山塔JGH_000715,JGH_000721<NA>127.00877937.568894斗塔(DOOTA)首?特?市 中? 乙支路6街<NA>首?特?市 中? ?忠?路 275(乙支路6街 18-12)斗山塔（Doosan Tower）是位于首?特?市中?乙支路六街的?씉???物中心，于1999年??。由斗山塔（株）??，?常叫‘斗塔（DOOTA）’。 ??男씉、女씉、?씉??等，日?客量?10万多人，是首?有名的地方。1998 建筑物 完工 1999 商家 ?店， ?立斗山塔（株） 2002 行?最初?施??价 ?示制 2009 重新 ???代/1999?地及?施/?物/其他1999年<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:17.0
9JGH_000346西小?外殉?者??塔JGH_000513,JGH_000672<NA>126.96894637.560534<NA>首?特?市中??州路2街<NA>首?特?市中?七牌路5（?州路2街16-4）西小?公??西小?外殉?者??塔是??念1801年辛酉邪?至1866年丙寅邪?期?在西小?外殉?的天主?徒中被推???人的44人而建的??塔。?位于西小??史公??，?在的塔?1999年重建。1801至1866年 103名天主?徒被?死 1984年 建成殉?者??塔 1999年 重建殉?者??塔 2014年 正在?行?史公?建??目?代/1984（建成），?代/1999（重建）文化/建筑/塔1984年（建成），1999年（重建）<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:16.0
관리번호명칭관련항목연계자원경도정보(127.XX)위도정보(36.XXX)이명칭지역지번주소도로명주소개요역사정보시대분류주제분류시작일(발생일)인물제공기관언어유형제작일유형형식등록일
786JGH_000870大方?佛??? 晋本卷28JGH_000867,JGH_000868,JGH_000869,JGH_000871,JGH_000872,JGH_000873,JGH_000874<NA>126.97606637.567665<NA>首?特?市 中? 太平路1街<NA>首?特?市 中? 世宗大路21路22(太平路1街 60-17) 성암고서博物?此?典是在?庵古?博物?里保管的《大方?佛???》晋本卷28。是木版寺刹本，1卷1?。1981 ?物第686?指定高?/未?文化/活字、陶器、?器?/活字本未?<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:17.0
787JGH_000871大方?佛??? 周本卷66JGH_000867,JGH_000868,JGH_000869,JGH_000870,JGH_000872,JGH_000873,JGH_000874<NA>126.97606637.567665<NA>首?特?市 中? 太平路1街<NA>首?特?市 中? 世宗大路21路22(太平路1街 60-17) 성암고서博物?此?典是在?庵古?博物?里保管的《大方?佛???》周本卷66。是木版寺刹本，1卷1?。1981 ?物第687?指定高?/未?文化/活字、陶器、?器?/活字本未?<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:17.0
788JGH_000872大方?佛??? 周本卷17JGH_000867,JGH_000868,JGH_000869,JGH_000870,JGH_000871,JGH_000873,JGH_000874<NA>126.97606637.567665<NA>首?特?市 中? 太平路1街<NA>首?特?市 中? 世宗大路21路22(太平路1街 60-17) 성암고서博物?此?典是在?庵古?博物?里保管的《大方?佛???》周本卷17, 52。是木版寺刹本，2卷2?。1981 ?物第688?指定高?/未?文化/活字、陶器、?器?/活字本未?<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:17.0
789JGH_000873大方?佛??? 周本卷6JGH_000867,JGH_000868,JGH_000869,JGH_000870,JGH_000871,JGH_000872,JGH_000874<NA>126.97606637.567665<NA>首?特?市 中? 太平路1街<NA>首?特?市 中? 世宗大路21路22(太平路1街 60-17) 성암고서博物?此?典是在?庵古?博物?里保管的《大方?佛???》周本卷6。是木版寺刹本，1卷1?。1981 ?物第690?指定高?/未?文化/活字、陶器、?器?/活字本未?<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:17.0
790JGH_000874大方?佛??? ?元本卷7JGH_000867,JGH_000868,JGH_000869,JGH_000870,JGH_000871,JGH_000872,JGH_000873<NA>126.97606637.567665<NA>首?特?市 中? 太平路1街<NA>首?特?市 中? 世宗大路21路22(太平路1街 60-17) 성암고서博物?此?典是在?庵古?博物?里保管的《大方?佛???》?元本卷7。是木版寺刹本，1卷1?。1981 ?物第689?指定高?/未?文化/活字、陶器、?器?/活字本未?<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:17.0
791JGH_000875三?史? 卷44?50JGH_000887<NA>126.97606637.567665<NA>首?特?市 中? 太平路1街<NA>首?特?市 中? 世宗大路21路22(太平路1街 60-17) 성암고서博物?此?是在?庵古?博物?里保管的木版本《三?史?》7卷1本。由高??代地方官署??，是?究??古代史重要的?料。1981 ?物第722?指定高?/1145文化/活字、陶器、?器?/活字本1145年<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:17.0
792JGH_000876三?史?JGH_000887<NA>126.97606637.567665<NA>首?特?市 中? 太平路1街<NA>首?特?市 中? 世宗大路21路22(太平路1街 60-17) 성암고서博物?此?是在?庵古?博物?里保管的木版本《三?史?》50卷 第9本。由高??代地方官署??，是?究??古代史重要的?料。1981 ?物第723?指定高?/1145文化/活字、陶器、?器?/活字本1145年<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:17.0
793JGH_000235?里?洞川??院??址<NA><NA>127.00533537.569232<NA>首?特?市中?乙支路<NA>首?特?市中?乙支路39路29（乙支路6街1-1）?里?洞川是?南山流入?溪川的小溪，??院?是曾架?于??小溪上的?墩。目前?里?洞川已被全部?平，无法?到?去溪流的痕迹。1465年 ?城府所有地??置里? 1592年 壬辰倭??致里?消失朝?/不?文化/?址、史迹/史址、殿址、?址、原址不?<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:16.0
794JGH_000504三一?立???念?址JGH_000288,JGH_000505<NA>126.98052237.562073<NA>首?特?市中?南大?路<NA>首?特?市中?南大?路39（南大?路2街110）一?南大?路2街???行前面的三一?立???念?址是1919年三一????，?千人市民??生聚集在一起，展?第一??立万?示威??的?所。1919.02.08 二八?立宣言 1919.03.01 三一?立??日本殖民?治?期/1919文化/?址、史迹/?立?址1919年<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:17.0
795JGH_000579Lila小?<NA><NA>126.98791237.557824<NA>首?特?市中?小波路<NA>首?特?市中?小波路2街7（??洞8）Lila小?是位于首?特?市中?小波路2街的私立小?。?校?始人??八于1964年?得成立?可，?于1965年?校。校名据?是取自?始人??八的子女名，建校理念是?。1964年 ?批成立 1965年 ?校 1996年 校名?Lila?民?校改?Lila小??代/1965?地及?施/其他周??施/其他1965年<NA>首?市 中區廳CHN4DATAHTML2016-02-03 15:41:17.0