Overview

Dataset statistics

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

Variable types

Numeric3
Text14
Unsupported4
Categorical8

Dataset

Description상세고유순번,관리번호,명칭,관련항목,연계자원,경도정보(127.XX),위도정보(36.XXX),이명칭,개요,시대분류,주제분류,지번주소,도로명주소,지역,제공기관,언어유형,제작일,유형,형식,전화번호,지정현황,휴무일,이용시간,이용요금,주차,장애인 편의시설,체험안내,안내서비스,예약
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-13377/S/1/datasetView.do

Alerts

언어유형 has constant value ""Constant
유형 has constant value ""Constant
형식 has constant value ""Constant
안내서비스 has constant value ""Constant
이용요금 is highly imbalanced (78.0%)Imbalance
주차 is highly imbalanced (60.1%)Imbalance
관련항목 has 139 (100.0%) missing valuesMissing
연계자원 has 54 (38.8%) missing valuesMissing
이명칭 has 134 (96.4%) missing valuesMissing
시대분류 has 139 (100.0%) missing valuesMissing
주제분류 has 139 (100.0%) missing valuesMissing
지번주소 has 139 (100.0%) missing valuesMissing
전화번호 has 107 (77.0%) missing valuesMissing
지정현황 has 119 (85.6%) missing valuesMissing
휴무일 has 125 (89.9%) missing valuesMissing
이용시간 has 130 (93.5%) missing valuesMissing
장애인 편의시설 has 136 (97.8%) missing valuesMissing
체험안내 has 136 (97.8%) missing valuesMissing
안내서비스 has 138 (99.3%) missing valuesMissing
예약 has 136 (97.8%) missing valuesMissing
상세고유순번 has unique valuesUnique
관리번호 has unique valuesUnique
개요 has unique valuesUnique
관련항목 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시대분류 is an unsupported type, check if it needs cleaning or further analysisUnsupported
주제분류 is an unsupported type, check if it needs cleaning or further analysisUnsupported
지번주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-22 00:33:50.136782
Analysis finished2024-04-22 00:33:50.838172
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상세고유순번
Real number (ℝ)

UNIQUE 

Distinct139
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean282.34532
Minimum101
Maximum717
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-22T09:33:50.901369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile107.9
Q1135.5
median170
Q3542.5
95-th percentile682.5
Maximum717
Range616
Interquartile range (IQR)407

Descriptive statistics

Standard deviation215.52621
Coefficient of variation (CV)0.76334258
Kurtosis-0.82576961
Mean282.34532
Median Absolute Deviation (MAD)39
Skewness1.0116155
Sum39246
Variance46451.547
MonotonicityStrictly increasing
2024-04-22T09:33:51.035365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
101 1
 
0.7%
197 1
 
0.7%
191 1
 
0.7%
192 1
 
0.7%
193 1
 
0.7%
194 1
 
0.7%
195 1
 
0.7%
196 1
 
0.7%
198 1
 
0.7%
189 1
 
0.7%
Other values (129) 129
92.8%
ValueCountFrequency (%)
101 1
0.7%
102 1
0.7%
103 1
0.7%
104 1
0.7%
105 1
0.7%
106 1
0.7%
107 1
0.7%
108 1
0.7%
109 1
0.7%
110 1
0.7%
ValueCountFrequency (%)
717 1
0.7%
712 1
0.7%
707 1
0.7%
702 1
0.7%
697 1
0.7%
692 1
0.7%
687 1
0.7%
682 1
0.7%
677 1
0.7%
672 1
0.7%

관리번호
Text

UNIQUE 

Distinct139
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-22T09:33:51.335412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1390
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique139 ?
Unique (%)100.0%

Sample

1st rowJGS_000001
2nd rowJGS_000002
3rd rowJGS_000003
4th rowJGS_000004
5th rowJGS_000005
ValueCountFrequency (%)
jgs_000001 1
 
0.7%
jgs_000105 1
 
0.7%
jgs_000103 1
 
0.7%
jgs_000102 1
 
0.7%
jgs_000101 1
 
0.7%
jgs_000100 1
 
0.7%
jgs_000099 1
 
0.7%
jgs_000098 1
 
0.7%
jgs_000097 1
 
0.7%
jgs_000071 1
 
0.7%
Other values (129) 129
92.8%
2024-04-22T09:33:51.746600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

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

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 548
56.3%
_ 139
 
14.3%
1 74
 
7.6%
3 34
 
3.5%
2 34
 
3.5%
6 24
 
2.5%
5 24
 
2.5%
4 24
 
2.5%
9 24
 
2.5%
8 24
 
2.5%
Latin
ValueCountFrequency (%)
J 139
33.3%
G 139
33.3%
S 139
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1390
100.0%

Most frequent character per block

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

명칭
Text

Distinct135
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-22T09:33:51.995984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length8.4172662
Min length2

Characters and Unicode

Total characters1170
Distinct characters297
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)94.2%

Sample

1st row德??
2nd row德??重明殿
3rd row옠丘?（?丘?）
4th row原俄?斯公使?
5th row?洞第一??
ValueCountFrequency (%)
4
 
2.7%
水 3
 
2.0%
五?水 2
 
1.4%
通 2
 
1.4%
倒立的?像 1
 
0.7%
忠?公 1
 
0.7%
1970~80年代?씉和流行的空?明洞(原?吉他和?年文化 1
 
0.7%
明洞的小??(三一路????等 1
 
0.7%
明洞的一天(??日?1957年新 1
 
0.7%
1950年代 1
 
0.7%
Other values (130) 130
88.4%
2024-04-22T09:33:52.367901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 391
33.4%
) 28
 
2.4%
( 28
 
2.4%
洞 22
 
1.9%
的 22
 
1.9%
明 18
 
1.5%
首 14
 
1.2%
大 14
 
1.2%
公 10
 
0.9%
年 10
 
0.9%
Other values (287) 613
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 640
54.7%
Other Punctuation 403
34.4%
Close Punctuation 34
 
2.9%
Open Punctuation 34
 
2.9%
Decimal Number 31
 
2.6%
Lowercase Letter 11
 
0.9%
Space Separator 8
 
0.7%
Math Symbol 3
 
0.3%
Uppercase Letter 3
 
0.3%
Initial Punctuation 1
 
0.1%
Other values (2) 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
洞 22
 
3.4%
的 22
 
3.4%
明 18
 
2.8%
首 14
 
2.2%
大 14
 
2.2%
公 10
 
1.6%
年 10
 
1.6%
中 9
 
1.4%
堂 9
 
1.4%
川 9
 
1.4%
Other values (251) 503
78.6%
Lowercase Letter
ValueCountFrequency (%)
i 2
18.2%
c 2
18.2%
e 1
9.1%
l 1
9.1%
m 1
9.1%
p 1
9.1%
s 1
9.1%
o 1
9.1%
n 1
9.1%
Decimal Number
ValueCountFrequency (%)
0 9
29.0%
1 7
22.6%
9 5
16.1%
5 4
12.9%
6 2
 
6.5%
7 2
 
6.5%
8 1
 
3.2%
3 1
 
3.2%
Other Punctuation
ValueCountFrequency (%)
? 391
97.0%
， 6
 
1.5%
, 3
 
0.7%
' 2
 
0.5%
. 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 28
82.4%
） 4
 
11.8%
》 2
 
5.9%
Open Punctuation
ValueCountFrequency (%)
( 28
82.4%
（ 4
 
11.8%
《 2
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
M 1
33.3%
N 1
33.3%
S 1
33.3%
Space Separator
ValueCountFrequency (%)
8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
” 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 634
54.2%
Common 516
44.1%
Latin 14
 
1.2%
Hangul 6
 
0.5%

Most frequent character per script

Han
ValueCountFrequency (%)
洞 22
 
3.5%
的 22
 
3.5%
明 18
 
2.8%
首 14
 
2.2%
大 14
 
2.2%
公 10
 
1.6%
年 10
 
1.6%
中 9
 
1.4%
堂 9
 
1.4%
川 9
 
1.4%
Other values (248) 497
78.4%
Common
ValueCountFrequency (%)
? 391
75.8%
) 28
 
5.4%
( 28
 
5.4%
0 9
 
1.7%
8
 
1.6%
1 7
 
1.4%
， 6
 
1.2%
9 5
 
1.0%
5 4
 
0.8%
（ 4
 
0.8%
Other values (14) 26
 
5.0%
Latin
ValueCountFrequency (%)
i 2
14.3%
c 2
14.3%
M 1
7.1%
e 1
7.1%
l 1
7.1%
N 1
7.1%
S 1
7.1%
m 1
7.1%
p 1
7.1%
s 1
7.1%
Other values (2) 2
14.3%
Hangul
ValueCountFrequency (%)
씉 4
66.7%
싲 1
 
16.7%
옠 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
CJK 634
54.2%
ASCII 510
43.6%
None 18
 
1.5%
Hangul 6
 
0.5%
Punctuation 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 391
76.7%
) 28
 
5.5%
( 28
 
5.5%
0 9
 
1.8%
8
 
1.6%
1 7
 
1.4%
9 5
 
1.0%
5 4
 
0.8%
, 3
 
0.6%
~ 3
 
0.6%
Other values (19) 24
 
4.7%
CJK
ValueCountFrequency (%)
洞 22
 
3.5%
的 22
 
3.5%
明 18
 
2.8%
首 14
 
2.2%
大 14
 
2.2%
公 10
 
1.6%
年 10
 
1.6%
中 9
 
1.4%
堂 9
 
1.4%
川 9
 
1.4%
Other values (248) 497
78.4%
None
ValueCountFrequency (%)
， 6
33.3%
（ 4
22.2%
） 4
22.2%
》 2
 
11.1%
《 2
 
11.1%
Hangul
ValueCountFrequency (%)
씉 4
66.7%
싲 1
 
16.7%
옠 1
 
16.7%
Punctuation
ValueCountFrequency (%)
“ 1
50.0%
” 1
50.0%

관련항목
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

연계자원
Text

MISSING 

Distinct85
Distinct (%)100.0%
Missing54
Missing (%)38.8%
Memory size1.2 KiB
2024-04-22T09:33:52.626561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

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

Unique

Unique85 ?
Unique (%)100.0%

Sample

1st rowJGH_000370
2nd rowJGH_000350
3rd rowJGH_000335
4th rowJGH_000355
5th rowJGH_000367
ValueCountFrequency (%)
jgh_000360 1
 
1.2%
jgh_000120 1
 
1.2%
jgh_000127 1
 
1.2%
jgh_000381 1
 
1.2%
jgh_000018 1
 
1.2%
jgh_000036 1
 
1.2%
jgh_000462 1
 
1.2%
jgh_000526 1
 
1.2%
jgh_000097 1
 
1.2%
jgh_000141 1
 
1.2%
Other values (75) 75
88.2%
2024-04-22T09:33:52.997729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

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

Most occurring scripts

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

Most frequent character per script

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

Most occurring blocks

ValueCountFrequency (%)
ASCII 850
100.0%

Most frequent character per block

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

경도정보(127.XX)
Real number (ℝ)

Distinct136
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.99109
Minimum126.97063
Maximum127.03793
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-22T09:33:53.149152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation0.015043339
Coefficient of variation (CV)0.0001184598
Kurtosis0.11521607
Mean126.99109
Median Absolute Deviation (MAD)0.00938
Skewness0.87087351
Sum17651.761
Variance0.00022630206
MonotonicityNot monotonic
2024-04-22T09:33:53.313497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.98378 2
 
1.4%
126.97063 2
 
1.4%
126.98187 2
 
1.4%
126.97653 1
 
0.7%
126.9846 1
 
0.7%
126.98789 1
 
0.7%
126.98517 1
 
0.7%
126.98468 1
 
0.7%
126.98509 1
 
0.7%
126.98455 1
 
0.7%
Other values (126) 126
90.6%
ValueCountFrequency (%)
126.97063 2
1.4%
126.97133 1
0.7%
126.97146 1
0.7%
126.97217 1
0.7%
126.97236 1
0.7%
126.97252 1
0.7%
126.97262 1
0.7%
126.97285 1
0.7%
126.97294 1
0.7%
126.97337 1
0.7%
ValueCountFrequency (%)
127.037931 1
0.7%
127.033545 1
0.7%
127.030354 1
0.7%
127.026658 1
0.7%
127.025354 1
0.7%
127.023407 1
0.7%
127.01905 1
0.7%
127.017441 1
0.7%
127.015917 1
0.7%
127.01503 1
0.7%

위도정보(36.XXX)
Real number (ℝ)

Distinct134
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.563656
Minimum37.55116
Maximum37.572332
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-22T09:33:53.465300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation0.0055815617
Coefficient of variation (CV)0.00014858941
Kurtosis-0.6104961
Mean37.563656
Median Absolute Deviation (MAD)0.00385
Skewness-0.66687544
Sum5221.3482
Variance3.1153831 × 10-5
MonotonicityNot monotonic
2024-04-22T09:33:53.588542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.56339 3
 
2.2%
37.569794 2
 
1.4%
37.5662 2
 
1.4%
37.568862 2
 
1.4%
37.56502 1
 
0.7%
37.56125 1
 
0.7%
37.5634 1
 
0.7%
37.56255 1
 
0.7%
37.56231 1
 
0.7%
37.56275 1
 
0.7%
Other values (124) 124
89.2%
ValueCountFrequency (%)
37.55116 1
0.7%
37.55139 1
0.7%
37.55159 1
0.7%
37.55164 1
0.7%
37.55184 1
0.7%
37.55201 1
0.7%
37.55235 1
0.7%
37.55254 1
0.7%
37.55284 1
0.7%
37.55347 1
0.7%
ValueCountFrequency (%)
37.572332 1
0.7%
37.571725 1
0.7%
37.571037 1
0.7%
37.571027 1
0.7%
37.570804 1
0.7%
37.57076 1
0.7%
37.570278 1
0.7%
37.569842 1
0.7%
37.569826 1
0.7%
37.569794 2
1.4%

이명칭
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing134
Missing (%)96.4%
Memory size1.2 KiB
2024-04-22T09:33:53.754173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length9.4
Min length5

Characters and Unicode

Total characters47
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row?云?,正陵同行?，西?
2nd row大??公? 首??堂
3rd row美笑?用?
4th row李王家美??,李王?美??
5th row??自由??盟
ValueCountFrequency (%)
云?,正陵同行?，西 1
16.7%
大??公 1
16.7%
首??堂 1
16.7%
美笑?用 1
16.7%
李王家美??,李王?美 1
16.7%
自由??盟 1
16.7%
2024-04-22T09:33:54.053810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 20
42.6%
美 3
 
6.4%
, 2
 
4.3%
王 2
 
4.3%
李 2
 
4.3%
首 1
 
2.1%
由 1
 
2.1%
自 1
 
2.1%
家 1
 
2.1%
用 1
 
2.1%
Other values (13) 13
27.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 23
48.9%
Other Letter 23
48.9%
Space Separator 1
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
美 3
 
13.0%
王 2
 
8.7%
李 2
 
8.7%
首 1
 
4.3%
由 1
 
4.3%
自 1
 
4.3%
家 1
 
4.3%
用 1
 
4.3%
笑 1
 
4.3%
堂 1
 
4.3%
Other values (9) 9
39.1%
Other Punctuation
ValueCountFrequency (%)
? 20
87.0%
, 2
 
8.7%
， 1
 
4.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24
51.1%
Han 23
48.9%

Most frequent character per script

Han
ValueCountFrequency (%)
美 3
 
13.0%
王 2
 
8.7%
李 2
 
8.7%
首 1
 
4.3%
由 1
 
4.3%
自 1
 
4.3%
家 1
 
4.3%
用 1
 
4.3%
笑 1
 
4.3%
堂 1
 
4.3%
Other values (9) 9
39.1%
Common
ValueCountFrequency (%)
? 20
83.3%
, 2
 
8.3%
1
 
4.2%
， 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23
48.9%
CJK 23
48.9%
None 1
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 20
87.0%
, 2
 
8.7%
1
 
4.3%
CJK
ValueCountFrequency (%)
美 3
 
13.0%
王 2
 
8.7%
李 2
 
8.7%
首 1
 
4.3%
由 1
 
4.3%
自 1
 
4.3%
家 1
 
4.3%
用 1
 
4.3%
笑 1
 
4.3%
堂 1
 
4.3%
Other values (9) 9
39.1%
None
ValueCountFrequency (%)
， 1
100.0%

개요
Text

UNIQUE 

Distinct139
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-22T09:33:54.259252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length146
Median length88
Mean length56.971223
Min length6

Characters and Unicode

Total characters7919
Distinct characters731
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique139 ?
Unique (%)100.0%

Sample

1st row?名?是???，但1907年?始被??德??。 6万1500㎡面?上?留着大??，中和?，光明?和中和殿，浚?堂，昔御堂，石造殿，咸?殿，卽祚堂等殿?。
2nd row1901年建造的重明殿是?在德??的????包含的建筑，被用作接?所及宴??，???。是1907年皇太子的?典宴??行的?所，也是??乙巳勒?的悲??所。日本帝?主??代的1915年?始被外?人租?后使用?京城俱?部。
3rd row옠丘?是皇帝向天祭祀的祭?。?里是?承朝?的大?帝?高宗皇帝向天祭祀的地方。1897年完工的옠丘?是??皇室中最高都?首的沈宜?所??。
4th row1890年（高宗 27）俄?斯人?巴?尼(A.I.Sabatin)??的文????格的建筑。6?25???期本?被破?，?在只留下了3??模的塔。被有名?高宗避?日本武力威?的俄?播???。
5th row?洞第一??是在1895年(高宗 32 )?工, 1897年(光武 1 ) 10月竣工的改新敎???拜堂。
ValueCountFrequency (%)
名?是???，但1907年?始被??德??。 1
 
0.5%
6?25??成?文化??家?活?的?合??的?所。到了1970年代喜?嬉皮士文化的年?人光?。 1
 
0.5%
新堂洞炒年?胡同是?1950年代?始的。辣椒?和?面?混在一起?出的辣??而咸??而?津津的味道具有中毒性。是外?人??的旅游?地。 1
 
0.5%
是位于首?特?市中?的?史文化主?公?。是建于?大?????址的?大?????的一部分，是展示建筑????的?物、?迹。?外，?可?察?去在?大?????行?的比?。 1
 
0.5%
此?念?是保管、展示在曾竣工于日帝强占期1925年5月24日后于2007年12月被앯的?大?????行?的比?及集?????物和?大?????部?施的地方。 1
 
0.5%
原位于??都城?大?下面的无?水?就是原在南面的水?。?南山流下?的水流提供二?水???溪川主流合流。因作成2?霓虹??照二?水?。 1
 
0.5%
建于??大????的?大?????是于2009年4月?工，于2014年3月??的?合文化空?。 1
 
0.5%
大??씉城是指??路5街?藏市?到?溪8街新??合市??止?2km?的?溪川路左右和相?胡同，?有分布于?仁?路左右一?的市???。 1
 
0.5%
1943年?始?事每日新??者的李?九是在明洞活?的文人。 1
 
0.5%
日帝强占期到解放,??6?25??到1960年代?止明洞的茶?是文化??家聚集在一起?行??、工作、休息的?所。 1
 
0.5%
Other values (175) 175
94.6%
2024-04-22T09:33:54.592184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 1937
24.5%
的 352
 
4.4%
。 196
 
2.5%
1 177
 
2.2%
年 145
 
1.8%
9 135
 
1.7%
于 126
 
1.6%
是 116
 
1.5%
， 112
 
1.4%
0 103
 
1.3%
Other values (721) 4520
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4512
57.0%
Other Punctuation 2323
29.3%
Decimal Number 741
 
9.4%
Lowercase Letter 133
 
1.7%
Space Separator 49
 
0.6%
Uppercase Letter 32
 
0.4%
Open Punctuation 31
 
0.4%
Close Punctuation 31
 
0.4%
Initial Punctuation 26
 
0.3%
Final Punctuation 25
 
0.3%
Other values (3) 16
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
的 352
 
7.8%
年 145
 
3.2%
于 126
 
2.8%
是 116
 
2.6%
建 94
 
2.1%
在 73
 
1.6%
大 51
 
1.1%
立 47
 
1.0%
和 46
 
1.0%
地 45
 
1.0%
Other values (647) 3417
75.7%
Lowercase Letter
ValueCountFrequency (%)
e 17
12.8%
o 14
10.5%
r 12
9.0%
n 11
8.3%
a 11
8.3%
i 10
 
7.5%
m 10
 
7.5%
l 9
 
6.8%
s 7
 
5.3%
p 5
 
3.8%
Other values (13) 27
20.3%
Uppercase Letter
ValueCountFrequency (%)
S 7
21.9%
H 5
15.6%
C 3
9.4%
M 3
9.4%
N 3
9.4%
G 2
 
6.2%
A 2
 
6.2%
F 1
 
3.1%
R 1
 
3.1%
I 1
 
3.1%
Other values (4) 4
12.5%
Decimal Number
ValueCountFrequency (%)
1 177
23.9%
9 135
18.2%
0 103
13.9%
2 64
 
8.6%
5 53
 
7.2%
6 52
 
7.0%
3 49
 
6.6%
7 42
 
5.7%
8 39
 
5.3%
4 27
 
3.6%
Other Punctuation
ValueCountFrequency (%)
? 1937
83.4%
。 196
 
8.4%
， 112
 
4.8%
、 49
 
2.1%
, 13
 
0.6%
. 10
 
0.4%
' 3
 
0.1%
； 2
 
0.1%
！ 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 18
58.1%
（ 10
32.3%
《 2
 
6.5%
「 1
 
3.2%
Close Punctuation
ValueCountFrequency (%)
) 18
58.1%
） 10
32.3%
》 2
 
6.5%
」 1
 
3.2%
Math Symbol
ValueCountFrequency (%)
~ 5
71.4%
> 1
 
14.3%
< 1
 
14.3%
Initial Punctuation
ValueCountFrequency (%)
“ 21
80.8%
‘ 5
 
19.2%
Final Punctuation
ValueCountFrequency (%)
” 20
80.0%
’ 5
 
20.0%
Space Separator
ValueCountFrequency (%)
49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 4494
56.7%
Common 3242
40.9%
Latin 165
 
2.1%
Hangul 18
 
0.2%

Most frequent character per script

Han
ValueCountFrequency (%)
的 352
 
7.8%
年 145
 
3.2%
于 126
 
2.8%
是 116
 
2.6%
建 94
 
2.1%
在 73
 
1.6%
大 51
 
1.1%
立 47
 
1.0%
和 46
 
1.0%
地 45
 
1.0%
Other values (640) 3399
75.6%
Common
ValueCountFrequency (%)
? 1937
59.7%
。 196
 
6.0%
1 177
 
5.5%
9 135
 
4.2%
， 112
 
3.5%
0 103
 
3.2%
2 64
 
2.0%
5 53
 
1.6%
6 52
 
1.6%
49
 
1.5%
Other values (27) 364
 
11.2%
Latin
ValueCountFrequency (%)
e 17
 
10.3%
o 14
 
8.5%
r 12
 
7.3%
n 11
 
6.7%
a 11
 
6.7%
i 10
 
6.1%
m 10
 
6.1%
l 9
 
5.5%
s 7
 
4.2%
S 7
 
4.2%
Other values (27) 57
34.5%
Hangul
ValueCountFrequency (%)
씉 9
50.0%
앯 3
 
16.7%
옠 2
 
11.1%
싲 1
 
5.6%
앀 1
 
5.6%
쑒 1
 
5.6%
슾 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
CJK 4494
56.7%
ASCII 2969
37.5%
None 386
 
4.9%
Punctuation 51
 
0.6%
Hangul 18
 
0.2%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 1937
65.2%
1 177
 
6.0%
9 135
 
4.5%
0 103
 
3.5%
2 64
 
2.2%
5 53
 
1.8%
6 52
 
1.8%
49
 
1.7%
3 49
 
1.7%
7 42
 
1.4%
Other values (48) 308
 
10.4%
CJK
ValueCountFrequency (%)
的 352
 
7.8%
年 145
 
3.2%
于 126
 
2.8%
是 116
 
2.6%
建 94
 
2.1%
在 73
 
1.6%
大 51
 
1.1%
立 47
 
1.0%
和 46
 
1.0%
地 45
 
1.0%
Other values (640) 3399
75.6%
None
ValueCountFrequency (%)
。 196
50.8%
， 112
29.0%
、 49
 
12.7%
（ 10
 
2.6%
） 10
 
2.6%
； 2
 
0.5%
《 2
 
0.5%
》 2
 
0.5%
！ 1
 
0.3%
「 1
 
0.3%
Punctuation
ValueCountFrequency (%)
“ 21
41.2%
” 20
39.2%
’ 5
 
9.8%
‘ 5
 
9.8%
Hangul
ValueCountFrequency (%)
씉 9
50.0%
앯 3
 
16.7%
옠 2
 
11.1%
싲 1
 
5.6%
앀 1
 
5.6%
쑒 1
 
5.6%
슾 1
 
5.6%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%

시대분류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

주제분류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

지번주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

도로명주소
Text

Distinct89
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-22T09:33:54.848157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length29
Mean length16.330935
Min length8

Characters and Unicode

Total characters2270
Distinct characters76
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)56.1%

Sample

1st row首?特?市 中? 世宗大路 99
2nd row首?特?市 中? ?洞路 41-11
3rd row首?特?市 中? 小公路 106
4th row首?特?市 中? ?洞路 21-18 ?洞公?
5th row首?特?市 中? ?洞路 46 ?洞??
ValueCountFrequency (%)
首?特?市 139
27.5%
中 100
19.8%
中?/?路 19
 
3.8%
一 16
 
3.2%
明洞 12
 
2.4%
溪川 9
 
1.8%
洞路 8
 
1.6%
世宗大路 7
 
1.4%
明洞路 6
 
1.2%
小波路 6
 
1.2%
Other values (116) 183
36.2%
2024-04-22T09:33:55.504542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 597
26.3%
367
16.2%
市 141
 
6.2%
首 140
 
6.2%
特 140
 
6.2%
中 120
 
5.3%
路 111
 
4.9%
1 69
 
3.0%
2 50
 
2.2%
洞 48
 
2.1%
Other values (66) 487
21.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 946
41.7%
Other Punctuation 623
27.4%
Space Separator 367
 
16.2%
Decimal Number 288
 
12.7%
Dash Punctuation 25
 
1.1%
Uppercase Letter 11
 
0.5%
Close Punctuation 5
 
0.2%
Open Punctuation 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
市 141
14.9%
首 140
14.8%
特 140
14.8%
中 120
12.7%
路 111
11.7%
洞 48
 
5.1%
大 20
 
2.1%
明 19
 
2.0%
溪 18
 
1.9%
一 16
 
1.7%
Other values (40) 173
18.3%
Decimal Number
ValueCountFrequency (%)
1 69
24.0%
2 50
17.4%
5 29
10.1%
4 22
 
7.6%
3 22
 
7.6%
0 21
 
7.3%
9 20
 
6.9%
7 19
 
6.6%
6 19
 
6.6%
8 17
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
A 3
27.3%
W 1
 
9.1%
C 1
 
9.1%
Y 1
 
9.1%
U 1
 
9.1%
R 1
 
9.1%
I 1
 
9.1%
T 1
 
9.1%
M 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
? 597
95.8%
/ 24
 
3.9%
, 2
 
0.3%
Space Separator
ValueCountFrequency (%)
367
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1313
57.8%
Han 946
41.7%
Latin 11
 
0.5%

Most frequent character per script

Han
ValueCountFrequency (%)
市 141
14.9%
首 140
14.8%
特 140
14.8%
中 120
12.7%
路 111
11.7%
洞 48
 
5.1%
大 20
 
2.1%
明 19
 
2.0%
溪 18
 
1.9%
一 16
 
1.7%
Other values (40) 173
18.3%
Common
ValueCountFrequency (%)
? 597
45.5%
367
28.0%
1 69
 
5.3%
2 50
 
3.8%
5 29
 
2.2%
- 25
 
1.9%
/ 24
 
1.8%
4 22
 
1.7%
3 22
 
1.7%
0 21
 
1.6%
Other values (7) 87
 
6.6%
Latin
ValueCountFrequency (%)
A 3
27.3%
W 1
 
9.1%
C 1
 
9.1%
Y 1
 
9.1%
U 1
 
9.1%
R 1
 
9.1%
I 1
 
9.1%
T 1
 
9.1%
M 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1324
58.3%
CJK 946
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 597
45.1%
367
27.7%
1 69
 
5.2%
2 50
 
3.8%
5 29
 
2.2%
- 25
 
1.9%
/ 24
 
1.8%
4 22
 
1.7%
3 22
 
1.7%
0 21
 
1.6%
Other values (16) 98
 
7.4%
CJK
ValueCountFrequency (%)
市 141
14.9%
首 140
14.8%
特 140
14.8%
中 120
12.7%
路 111
11.7%
洞 48
 
5.1%
大 20
 
2.1%
明 19
 
2.0%
溪 18
 
1.9%
一 16
 
1.7%
Other values (40) 173
18.3%

지역
Categorical

Distinct23
Distinct (%)16.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
39 
首?特?市 中? 明洞
13 
首?特?市 中? 退溪路
9 
首?特?市 中? ?洞路
9 
首?特?市 中? 世宗大路
9 
Other values (18)
60 

Length

Max length15
Median length14
Mean length9.8920863
Min length4

Unique

Unique4 ?
Unique (%)2.9%

Sample

1st row首?特?市 中? 世宗大路
2nd row首?特?市 中? ?洞路
3rd row首?特?市 中? 小公路
4th row首?特?市 中? ?洞路
5th row首?特?市 中? ?洞路

Common Values

ValueCountFrequency (%)
<NA> 39
28.1%
首?特?市 中? 明洞 13
 
9.4%
首?特?市 中? 退溪路 9
 
6.5%
首?特?市 中? ?洞路 9
 
6.5%
首?特?市 中? 世宗大路 9
 
6.5%
首?特?市 中? 小波路 6
 
4.3%
首?特?市 中? 明洞路 6
 
4.3%
首?特?市 中? ?忠洞 5
 
3.6%
首?特?市 中? 乙支路 5
 
3.6%
首?特?市 中? ??洞 5
 
3.6%
Other values (13) 33
23.7%

Length

2024-04-22T09:33:55.641337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
首?特?市 100
29.5%
中 99
29.2%
na 39
 
11.5%
明洞 13
 
3.8%
世宗大路 10
 
2.9%
退溪路 9
 
2.7%
洞路 9
 
2.7%
洞 7
 
2.1%
明洞路 6
 
1.8%
小波路 6
 
1.8%
Other values (13) 41
12.1%

제공기관
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
首?市?中???
100 
首?特?市
39 

Length

Max length8
Median length8
Mean length7.1582734
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
首?市?中??? 100
71.9%
首?特?市 39
 
28.1%

Length

2024-04-22T09:33:55.756149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:33:55.849428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
首?市?中 100
71.9%
首?特?市 39
 
28.1%

언어유형
Categorical

CONSTANT 

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

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 139
100.0%

Length

2024-04-22T09:33:55.973070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:33:56.081565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
chn 139
100.0%

제작일
Categorical

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

Length

Max length10
Median length10
Mean length8.3165468
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

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

Length

2024-04-22T09:33:56.199532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:33:56.312459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015-12-30 100
71.9%
na 39
 
28.1%

유형
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
DATA 139
100.0%

Length

2024-04-22T09:33:56.421245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:33:56.511812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
data 139
100.0%

형식
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
HTML 139
100.0%

Length

2024-04-22T09:33:56.602044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:33:56.692442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
html 139
100.0%

전화번호
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing107
Missing (%)77.0%
Memory size1.2 KiB
2024-04-22T09:33:56.862787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length11.46875
Min length6

Characters and Unicode

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

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row02-771-9951
2nd row02-2124-8800
3rd row02-720-9494
4th row02-730-6611
5th row02-777-4258
ValueCountFrequency (%)
02-2266-0665 1
 
3.0%
02-759-4881 1
 
3.0%
02-3455-9277 1
 
3.0%
02-3455-8341 1
 
3.0%
02-779-6107 1
 
3.0%
02-753-2805 1
 
3.0%
02-2280-4114 1
 
3.0%
02-774-1784 1
 
3.0%
02-771-9951 1
 
3.0%
02-753-2403 1
 
3.0%
Other values (23) 23
69.7%
2024-04-22T09:33:57.223396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

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

Most occurring scripts

ValueCountFrequency (%)
Common 367
100.0%

Most frequent character per script

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

Most occurring blocks

ValueCountFrequency (%)
ASCII 367
100.0%

Most frequent character per block

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

지정현황
Text

MISSING 

Distinct19
Distinct (%)95.0%
Missing119
Missing (%)85.6%
Memory size1.2 KiB
2024-04-22T09:33:57.396403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length11.6
Min length6

Characters and Unicode

Total characters232
Distinct characters27
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

Unique18 ?
Unique (%)90.0%

Sample

1st row史迹 第124?
2nd row首?特?市 ?念物 第16?
3rd row登?文化?? 第237?
4th row登?文化?? 第267?
5th row登?文化?? 第402?
ValueCountFrequency (%)
登?文化 8
17.8%
首?特?市 5
 
11.1%
史迹 4
 
8.9%
念物 2
 
4.4%
第20 2
 
4.4%
有形文化 2
 
4.4%
第124 2
 
4.4%
首?市有形文化 2
 
4.4%
第1 2
 
4.4%
1
 
2.2%
Other values (15) 15
33.3%
2024-04-22T09:33:57.677115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 69
29.7%
26
 
11.2%
第 20
 
8.6%
化 12
 
5.2%
文 12
 
5.2%
1 10
 
4.3%
2 10
 
4.3%
登 8
 
3.4%
市 7
 
3.0%
首 7
 
3.0%
Other values (17) 51
22.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 94
40.5%
Other Punctuation 69
29.7%
Decimal Number 43
18.5%
Space Separator 26
 
11.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
第 20
21.3%
化 12
12.8%
文 12
12.8%
登 8
 
8.5%
市 7
 
7.4%
首 7
 
7.4%
特 5
 
5.3%
史 4
 
4.3%
迹 4
 
4.3%
形 4
 
4.3%
Other values (6) 11
11.7%
Decimal Number
ValueCountFrequency (%)
1 10
23.3%
2 10
23.3%
0 5
11.6%
3 4
 
9.3%
5 3
 
7.0%
8 3
 
7.0%
7 3
 
7.0%
4 3
 
7.0%
6 2
 
4.7%
Other Punctuation
ValueCountFrequency (%)
? 69
100.0%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 138
59.5%
Han 94
40.5%

Most frequent character per script

Han
ValueCountFrequency (%)
第 20
21.3%
化 12
12.8%
文 12
12.8%
登 8
 
8.5%
市 7
 
7.4%
首 7
 
7.4%
特 5
 
5.3%
史 4
 
4.3%
迹 4
 
4.3%
形 4
 
4.3%
Other values (6) 11
11.7%
Common
ValueCountFrequency (%)
? 69
50.0%
26
 
18.8%
1 10
 
7.2%
2 10
 
7.2%
0 5
 
3.6%
3 4
 
2.9%
5 3
 
2.2%
8 3
 
2.2%
7 3
 
2.2%
4 3
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 138
59.5%
CJK 94
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 69
50.0%
26
 
18.8%
1 10
 
7.2%
2 10
 
7.2%
0 5
 
3.6%
3 4
 
2.9%
5 3
 
2.2%
8 3
 
2.2%
7 3
 
2.2%
4 3
 
2.2%
CJK
ValueCountFrequency (%)
第 20
21.3%
化 12
12.8%
文 12
12.8%
登 8
 
8.5%
市 7
 
7.4%
首 7
 
7.4%
特 5
 
5.3%
史 4
 
4.3%
迹 4
 
4.3%
形 4
 
4.3%
Other values (6) 11
11.7%

휴무일
Text

MISSING 

Distinct10
Distinct (%)71.4%
Missing125
Missing (%)89.9%
Memory size1.2 KiB
2024-04-22T09:33:57.809474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length16
Mean length8.7142857
Min length3

Characters and Unicode

Total characters122
Distinct characters21
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)50.0%

Sample

1st row每周一
2nd row每周一,公休日
3rd row每周一, 1月1日
4th row每周日
5th row每周一, 1月1日
ValueCountFrequency (%)
每周一 9
36.0%
1月1日 3
 
12.0%
每周日 3
 
12.0%
公休日 2
 
8.0%
每周一,公休日 1
 
4.0%
每周二 1
 
4.0%
1月1日,春?,中秋 1
 
4.0%
春?及中秋??休 1
 
4.0%
12月29日~下年1月 1
 
4.0%
2日 1
 
4.0%
Other values (2) 2
 
8.0%
2024-04-22T09:33:58.068386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
每 14
11.5%
周 14
11.5%
, 13
10.7%
日 13
10.7%
11
9.0%
一 10
8.2%
1 10
8.2%
? 9
7.4%
月 6
 
4.9%
休 4
 
3.3%
Other values (11) 18
14.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74
60.7%
Other Punctuation 22
 
18.0%
Decimal Number 14
 
11.5%
Space Separator 11
 
9.0%
Math Symbol 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
每 14
18.9%
周 14
18.9%
日 13
17.6%
一 10
13.5%
月 6
8.1%
休 4
 
5.4%
公 3
 
4.1%
春 2
 
2.7%
中 2
 
2.7%
秋 2
 
2.7%
Other values (4) 4
 
5.4%
Decimal Number
ValueCountFrequency (%)
1 10
71.4%
2 3
 
21.4%
9 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 13
59.1%
? 9
40.9%
Space Separator
ValueCountFrequency (%)
11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 74
60.7%
Common 48
39.3%

Most frequent character per script

Han
ValueCountFrequency (%)
每 14
18.9%
周 14
18.9%
日 13
17.6%
一 10
13.5%
月 6
8.1%
休 4
 
5.4%
公 3
 
4.1%
春 2
 
2.7%
中 2
 
2.7%
秋 2
 
2.7%
Other values (4) 4
 
5.4%
Common
ValueCountFrequency (%)
, 13
27.1%
11
22.9%
1 10
20.8%
? 9
18.8%
2 3
 
6.2%
~ 1
 
2.1%
9 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
CJK 74
60.7%
ASCII 48
39.3%

Most frequent character per block

CJK
ValueCountFrequency (%)
每 14
18.9%
周 14
18.9%
日 13
17.6%
一 10
13.5%
月 6
8.1%
休 4
 
5.4%
公 3
 
4.1%
春 2
 
2.7%
中 2
 
2.7%
秋 2
 
2.7%
Other values (4) 4
 
5.4%
ASCII
ValueCountFrequency (%)
, 13
27.1%
11
22.9%
1 10
20.8%
? 9
18.8%
2 3
 
6.2%
~ 1
 
2.1%
9 1
 
2.1%

이용시간
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing130
Missing (%)93.5%
Memory size1.2 KiB
2024-04-22T09:33:58.206504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length40
Mean length22.222222
Min length13

Characters and Unicode

Total characters200
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)100.0%

Sample

1st row?票及入??? 09:00 ~ 20:00 退??? 09:00 ~ 21:00
2nd row明日 10:00 ~ 17:00
3rd row平日 09:00 ~ 21:00
4th row09:00 ~ 18:00
5th row每周二 ~ 周日 10:00 ~ 18:00
ValueCountFrequency (%)
10
23.8%
17:00 5
11.9%
10:00 5
11.9%
09:00 4
 
9.5%
20:00 3
 
7.1%
18:00 3
 
7.1%
21:00 2
 
4.8%
周日 1
 
2.4%
周六 1
 
2.4%
周一~周五,周日及公休日 1
 
2.4%
Other values (7) 7
16.7%
2024-04-22T09:33:58.506220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 58
29.0%
33
16.5%
: 23
 
11.5%
1 16
 
8.0%
~ 12
 
6.0%
周 8
 
4.0%
? 7
 
3.5%
日 6
 
3.0%
7 5
 
2.5%
2 5
 
2.5%
Other values (17) 27
13.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 92
46.0%
Other Punctuation 34
 
17.0%
Space Separator 33
 
16.5%
Other Letter 29
 
14.5%
Math Symbol 12
 
6.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
周 8
27.6%
日 6
20.7%
及 2
 
6.9%
二 2
 
6.9%
一 1
 
3.4%
六 1
 
3.4%
休 1
 
3.4%
公 1
 
3.4%
五 1
 
3.4%
每 1
 
3.4%
Other values (5) 5
17.2%
Decimal Number
ValueCountFrequency (%)
0 58
63.0%
1 16
 
17.4%
7 5
 
5.4%
2 5
 
5.4%
9 4
 
4.3%
8 3
 
3.3%
4 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
: 23
67.6%
? 7
 
20.6%
, 4
 
11.8%
Space Separator
ValueCountFrequency (%)
33
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 171
85.5%
Han 29
 
14.5%

Most frequent character per script

Han
ValueCountFrequency (%)
周 8
27.6%
日 6
20.7%
及 2
 
6.9%
二 2
 
6.9%
一 1
 
3.4%
六 1
 
3.4%
休 1
 
3.4%
公 1
 
3.4%
五 1
 
3.4%
每 1
 
3.4%
Other values (5) 5
17.2%
Common
ValueCountFrequency (%)
0 58
33.9%
33
19.3%
: 23
 
13.5%
1 16
 
9.4%
~ 12
 
7.0%
? 7
 
4.1%
7 5
 
2.9%
2 5
 
2.9%
9 4
 
2.3%
, 4
 
2.3%
Other values (2) 4
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 171
85.5%
CJK 29
 
14.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 58
33.9%
33
19.3%
: 23
 
13.5%
1 16
 
9.4%
~ 12
 
7.0%
? 7
 
4.1%
7 5
 
2.9%
2 5
 
2.9%
9 4
 
2.3%
, 4
 
2.3%
Other values (2) 4
 
2.3%
CJK
ValueCountFrequency (%)
周 8
27.6%
日 6
20.7%
及 2
 
6.9%
二 2
 
6.9%
一 1
 
3.4%
六 1
 
3.4%
休 1
 
3.4%
公 1
 
3.4%
五 1
 
3.4%
每 1
 
3.4%
Other values (5) 5
17.2%

이용요금
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
131 
免?
 
7
大人(?25?以上) 1,000?元 ??大人(10人以上) 800?元
 
1

Length

Max length36
Median length4
Mean length4.1294964
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row大人(?25?以上) 1,000?元 ??大人(10人以上) 800?元
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 131
94.2%
免? 7
 
5.0%
大人(?25?以上) 1,000?元 ??大人(10人以上) 800?元 1
 
0.7%

Length

2024-04-22T09:33:58.638588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:33:58.745277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 131
92.3%
免 7
 
4.9%
大人(?25?以上 1
 
0.7%
1,000?元 1
 
0.7%
大人(10人以上 1
 
0.7%
800?元 1
 
0.7%

주차
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
128 
有停??
 
11

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 128
92.1%
有停?? 11
 
7.9%

Length

2024-04-22T09:33:58.851924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:33:58.945967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 128
92.1%
有停 11
 
7.9%

장애인 편의시설
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing136
Missing (%)97.8%
Memory size1.2 KiB
2024-04-22T09:33:59.073818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length13.666667
Min length4

Characters and Unicode

Total characters41
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row出借?椅
2nd row?疾人可以????,具?盲文指南手?
3rd row具??疾人?生?, 具??疾人?用?梯
ValueCountFrequency (%)
出借?椅 1
25.0%
疾人可以????,具?盲文指南手 1
25.0%
具??疾人?生 1
25.0%
具??疾人?用?梯 1
25.0%
2024-04-22T09:33:59.425774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 16
39.0%
具 3
 
7.3%
疾 3
 
7.3%
人 3
 
7.3%
, 2
 
4.9%
指 1
 
2.4%
用 1
 
2.4%
1
 
2.4%
生 1
 
2.4%
手 1
 
2.4%
Other values (9) 9
22.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22
53.7%
Other Punctuation 18
43.9%
Space Separator 1
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
具 3
13.6%
疾 3
13.6%
人 3
13.6%
指 1
 
4.5%
用 1
 
4.5%
生 1
 
4.5%
手 1
 
4.5%
南 1
 
4.5%
出 1
 
4.5%
文 1
 
4.5%
Other values (6) 6
27.3%
Other Punctuation
ValueCountFrequency (%)
? 16
88.9%
, 2
 
11.1%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 22
53.7%
Common 19
46.3%

Most frequent character per script

Han
ValueCountFrequency (%)
具 3
13.6%
疾 3
13.6%
人 3
13.6%
指 1
 
4.5%
用 1
 
4.5%
生 1
 
4.5%
手 1
 
4.5%
南 1
 
4.5%
出 1
 
4.5%
文 1
 
4.5%
Other values (6) 6
27.3%
Common
ValueCountFrequency (%)
? 16
84.2%
, 2
 
10.5%
1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
CJK 22
53.7%
ASCII 19
46.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 16
84.2%
, 2
 
10.5%
1
 
5.3%
CJK
ValueCountFrequency (%)
具 3
13.6%
疾 3
13.6%
人 3
13.6%
指 1
 
4.5%
用 1
 
4.5%
生 1
 
4.5%
手 1
 
4.5%
南 1
 
4.5%
出 1
 
4.5%
文 1
 
4.5%
Other values (6) 6
27.3%

체험안내
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing136
Missing (%)97.8%
Memory size1.2 KiB
2024-04-22T09:33:59.656008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length16
Mean length16
Min length4

Characters and Unicode

Total characters48
Distinct characters20
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row?穿??服씉、??守?????式
2nd row?鼓??
3rd row??文化村,?影服?, 稻草工?演示, ??文化??解?
ValueCountFrequency (%)
穿??服씉、??守?????式 1
20.0%
鼓 1
20.0%
文化村,?影服 1
20.0%
稻草工?演示 1
20.0%
文化??解 1
20.0%
2024-04-22T09:33:59.939821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 23
47.9%
, 3
 
6.2%
服 2
 
4.2%
文 2
 
4.2%
化 2
 
4.2%
2
 
4.2%
影 1
 
2.1%
示 1
 
2.1%
演 1
 
2.1%
工 1
 
2.1%
Other values (10) 10
20.8%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 27
56.2%
Other Letter 19
39.6%
Space Separator 2
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
服 2
 
10.5%
文 2
 
10.5%
化 2
 
10.5%
影 1
 
5.3%
示 1
 
5.3%
演 1
 
5.3%
工 1
 
5.3%
草 1
 
5.3%
稻 1
 
5.3%
村 1
 
5.3%
Other values (6) 6
31.6%
Other Punctuation
ValueCountFrequency (%)
? 23
85.2%
, 3
 
11.1%
、 1
 
3.7%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29
60.4%
Han 18
37.5%
Hangul 1
 
2.1%

Most frequent character per script

Han
ValueCountFrequency (%)
服 2
 
11.1%
文 2
 
11.1%
化 2
 
11.1%
影 1
 
5.6%
示 1
 
5.6%
演 1
 
5.6%
工 1
 
5.6%
草 1
 
5.6%
稻 1
 
5.6%
村 1
 
5.6%
Other values (5) 5
27.8%
Common
ValueCountFrequency (%)
? 23
79.3%
, 3
 
10.3%
2
 
6.9%
、 1
 
3.4%
Hangul
ValueCountFrequency (%)
씉 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28
58.3%
CJK 18
37.5%
None 1
 
2.1%
Hangul 1
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 23
82.1%
, 3
 
10.7%
2
 
7.1%
CJK
ValueCountFrequency (%)
服 2
 
11.1%
文 2
 
11.1%
化 2
 
11.1%
影 1
 
5.6%
示 1
 
5.6%
演 1
 
5.6%
工 1
 
5.6%
草 1
 
5.6%
稻 1
 
5.6%
村 1
 
5.6%
Other values (5) 5
27.8%
None
ValueCountFrequency (%)
、 1
100.0%
Hangul
ValueCountFrequency (%)
씉 1
100.0%

안내서비스
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing138
Missing (%)99.3%
Memory size1.2 KiB
2024-04-22T09:34:00.086050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters6
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row具?多???音?游机
ValueCountFrequency (%)
具?多???音?游机 1
100.0%
2024-04-22T09:34:00.329828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 5
50.0%
具 1
 
10.0%
多 1
 
10.0%
音 1
 
10.0%
游 1
 
10.0%
机 1
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 5
50.0%
Other Letter 5
50.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
具 1
20.0%
多 1
20.0%
音 1
20.0%
游 1
20.0%
机 1
20.0%
Other Punctuation
ValueCountFrequency (%)
? 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
50.0%
Han 5
50.0%

Most frequent character per script

Han
ValueCountFrequency (%)
具 1
20.0%
多 1
20.0%
音 1
20.0%
游 1
20.0%
机 1
20.0%
Common
ValueCountFrequency (%)
? 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
50.0%
CJK 5
50.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 5
100.0%
CJK
ValueCountFrequency (%)
具 1
20.0%
多 1
20.0%
音 1
20.0%
游 1
20.0%
机 1
20.0%

예약
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing136
Missing (%)97.8%
Memory size1.2 KiB
2024-04-22T09:34:00.461027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length12.666667
Min length8

Characters and Unicode

Total characters38
Distinct characters8
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row??、手机、??、???? 可能
2nd row??、????，????可能
3rd row??????可能
ValueCountFrequency (%)
可能 2
50.0%
、手机、??、 1
25.0%
、????，????可能 1
25.0%
2024-04-22T09:34:00.713192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 24
63.2%
、 4
 
10.5%
可 3
 
7.9%
能 3
 
7.9%
手 1
 
2.6%
机 1
 
2.6%
1
 
2.6%
， 1
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 29
76.3%
Other Letter 8
 
21.1%
Space Separator 1
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
可 3
37.5%
能 3
37.5%
手 1
 
12.5%
机 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
? 24
82.8%
、 4
 
13.8%
， 1
 
3.4%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30
78.9%
Han 8
 
21.1%

Most frequent character per script

Common
ValueCountFrequency (%)
? 24
80.0%
、 4
 
13.3%
1
 
3.3%
， 1
 
3.3%
Han
ValueCountFrequency (%)
可 3
37.5%
能 3
37.5%
手 1
 
12.5%
机 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25
65.8%
CJK 8
 
21.1%
None 5
 
13.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 24
96.0%
1
 
4.0%
None
ValueCountFrequency (%)
、 4
80.0%
， 1
 
20.0%
CJK
ValueCountFrequency (%)
可 3
37.5%
能 3
37.5%
手 1
 
12.5%
机 1
 
12.5%

Sample

상세고유순번관리번호명칭관련항목연계자원경도정보(127.XX)위도정보(36.XXX)이명칭개요시대분류주제분류지번주소도로명주소지역제공기관언어유형제작일유형형식전화번호지정현황휴무일이용시간이용요금주차장애인 편의시설체험안내안내서비스예약
0101JGS_000001德??<NA>JGH_000370126.9765337.56502?云?,正陵同行?，西??名?是???，但1907年?始被??德??。 6万1500㎡面?上?留着大??，中和?，光明?和中和殿，浚?堂，昔御堂，石造殿，咸?殿，卽祚堂等殿?。<NA><NA><NA>首?特?市 中? 世宗大路 99首?特?市 中? 世宗大路首?市?中???CHN2015-12-30DATAHTML02-771-9951史迹 第124?每周一?票及入??? 09:00 ~ 20:00 退??? 09:00 ~ 21:00大人(?25?以上) 1,000?元 ??大人(10人以上) 800?元<NA>出借?椅?穿??服씉、??守?????式<NA><NA>
1102JGS_000002德??重明殿<NA>JGH_000350126.9725237.56659<NA>1901年建造的重明殿是?在德??的????包含的建筑，被用作接?所及宴??，???。是1907年皇太子的?典宴??行的?所，也是??乙巳勒?的悲??所。日本帝?主??代的1915年?始被外?人租?后使用?京城俱?部。<NA><NA><NA>首?特?市 中? ?洞路 41-11首?特?市 中? ?洞路首?市?中???CHN2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2103JGS_000003옠丘?（?丘?）<NA>JGH_000335126.9796937.56506<NA>옠丘?是皇帝向天祭祀的祭?。?里是?承朝?的大?帝?高宗皇帝向天祭祀的地方。1897年完工的옠丘?是??皇室中最高都?首的沈宜?所??。<NA><NA><NA>首?特?市 中? 小公路 106首?特?市 中? 小公路首?市?中???CHN2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3104JGS_000004原俄?斯公使?<NA>JGH_000355126.9714637.56825<NA>1890年（高宗 27）俄?斯人?巴?尼(A.I.Sabatin)??的文????格的建筑。6?25???期本?被破?，?在只留下了3??模的塔。被有名?高宗避?日本武力威?的俄?播???。<NA><NA><NA>首?特?市 中? ?洞路 21-18 ?洞公?首?特?市 中? ?洞路首?市?中???CHN2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4105JGS_000005?洞第一??<NA>JGH_000367126.9723637.56542<NA>?洞第一??是在1895年(高宗 32 )?工, 1897年(光武 1 ) 10月竣工的改新敎???拜堂。<NA><NA><NA>首?特?市 中? ?洞路 46 ?洞??首?特?市 中? ?洞路首?市?中???CHN2015-12-30DATAHTML<NA><NA><NA><NA><NA>有停??<NA><NA><NA><NA>
5106JGS_000006培材?堂?史博物?（?培材?堂??）<NA>JGH_000368126.9726237.56378<NA>此建筑物竣工于1916年，在1984年培才中?部及高中部?校舍?至江??前，其一直作?校舍使用。1885年8月??士亨利?格哈德?阿彭策?(Henry Gerhard Appenzeller)建立了培才?堂，建校初期以?置周?民宅作?校舍??。<NA><NA><NA>首?特?市 中? 西小?路11路 19首?特?市 中? 西小?路首?市?中???CHN2015-12-30DATAHTML<NA>首?特?市 ?念物 第16?每周一,公休日明日 10:00 ~ 17:00免?<NA><NA><NA><NA><NA>
6107JGS_000007首?市立美??<NA>JGH_000313126.9737737.56402<NA>?里是育英公院和德?公使?、京城裁判所的?址。解放后改作大?民?大法院，?于2002年作?首?市立美??重新??。<NA><NA><NA>首?特?市 中? 德??路 61首?特?市 中? 德??路首?市?中???CHN2015-12-30DATAHTML02-2124-8800登?文化?? 第237?每周一, 1月1日<NA><NA>有停??<NA><NA><NA><NA>
7108JGS_000008????怡?<NA>JGH_000361126.9754437.56694<NA>此建筑物竣工于1905年，?重建遭受重火?的???（德??）?同?期建筑。是大?帝?皇族和?族作??施近代式?育的?所，?作?大??公?主??公室使用。<NA><NA><NA>首?特?市 中? 世宗大路21路 15首?特?市 中? 世宗大路首?市?中???CHN2015-12-30DATAHTML<NA>登?文化?? 第267?<NA><NA><NA><NA><NA><NA><NA><NA>
8109JGS_000009?新?日?社分?<NA>JGH_000354126.9721737.56619<NA>?1930年建?的由地下一?和地上?????成的?筋混凝土建筑。原由美?企??家??机公司（SingerSewingMachineCompany）作???分公司使用，1963年被新?日????加高了3,4?后，作?其分?使用。新?日?在1980年新?部的整合媒?政策中，被?入到了京?新?中。<NA><NA><NA>首?特?市 中? ?洞路 33首?特?市 中? ?洞路首?市?中???CHN2015-12-30DATAHTML<NA>登?文化?? 第402?<NA><NA><NA><NA><NA><NA><NA><NA>
9110JGS_000010救世?中央??<NA>JGH_000352126.973637.56761<NA>救世?中央??竣工于1928年，作?救世?培?士官和??活?的社?事性?根据地建?。<NA><NA><NA>首?特?市 中? 德??路 130首?特?市 中? 德??路首?市?中???CHN2015-12-30DATAHTML02-720-9494首?特?市 ?念物 第20?<NA><NA><NA><NA><NA><NA><NA><NA>
상세고유순번관리번호명칭관련항목연계자원경도정보(127.XX)위도정보(36.XXX)이명칭개요시대분류주제분류지번주소도로명주소지역제공기관언어유형제작일유형형식전화번호지정현황휴무일이용시간이용요금주차장애인 편의시설체험안내안내서비스예약
129672JGS_000130放??<NA><NA>126.99129437.568252<NA>使用??消除叛?的金庾信，“送厄迎福”。<NA><NA><NA>首?特?市 ?溪川<NA>首?特?市CHN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
130677JGS_000131燃싲游?<NA><NA>126.9818737.568862<NA>向佛祖祈福的燃싲游?<NA><NA><NA>首?特?市 ?溪川<NA>首?特?市CHN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
131682JGS_000132石?<NA><NA>126.98433937.568659<NA>朝?“好?'性格的石?<NA><NA><NA>首?特?市 ?溪川<NA>首?特?市CHN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
132687JGS_000133?溪川的“跆?”<NA><NA>127.00124237.569457<NA>朝?最后的跆????及仁寺洞的跆???<NA><NA><NA>首?特?市 ?溪川<NA>首?特?市CHN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
133692JGS_000134首善全?<NA><NA>126.9848937.568552<NA>?出“??”的《首善全?》<NA><NA><NA>首?特?市 ?路?<NA>首?特?市CHN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
134697JGS_000135正祖大王的《陵行班次?》<NA><NA>126.9852737.568509<NA>祭拜死于悲?的“思悼世子”-正祖大王的?拜?伍<NA><NA><NA>首?特?市 ?路?<NA>首?特?市CHN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
135702JGS_000136英祖御?，《浚川歌》<NA><NA>127.00968237.569826<NA>英祖?浚川工程的喜?及蔡?恭的?<NA><NA><NA>首?特?市 ?路?<NA>首?特?市CHN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
136707JGS_000137五?水?<NA><NA>127.01061437.569765<NA>?溪川之河水通?的-??城?五?水?<NA><NA><NA>首?特?市 ?路?<NA>首?特?市CHN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
137712JGS_000138浚川?<NA><NA>127.0096837.569675<NA>英祖在五?水?鼓?浚川工程。<NA><NA><NA>首?特?市 中?<NA>首?特?市CHN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
138717JGS_000139?溪川的原貌及壁?<NA><NA>127.01377437.569842<NA>?溪川的原貌<NA><NA><NA>首?特?市 ?路?<NA>首?特?市CHN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>