Overview

Dataset statistics

Number of variables29
Number of observations139
Missing cells1810
Missing cells (%)44.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.6 KiB
Average record size in memory239.9 B

Variable types

Numeric3
Text14
Unsupported4
Categorical7
DateTime1

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-13376/S/1/datasetView.do

Alerts

언어유형 has constant value ""Constant
제작일 has constant value ""Constant
유형 has constant value ""Constant
형식 has constant value ""Constant
안내서비스 has constant value ""Constant
이용요금 is highly imbalanced (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
제작일 has 39 (28.1%) 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
명칭 has unique valuesUnique
개요 has unique valuesUnique
관련항목 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시대분류 is an unsupported type, check if it needs cleaning or further analysisUnsupported
주제분류 is an unsupported type, check if it needs cleaning or further analysisUnsupported
지번주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 06:22:40.058336
Analysis finished2023-12-11 06:22:41.418512
Duration1.36 second
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%
Mean425.93525
Minimum301
Maximum716
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T15:22:41.510520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum301
5-th percentile307.9
Q1335.5
median370
Q3541.5
95-th percentile681.5
Maximum716
Range415
Interquartile range (IQR)206

Descriptive statistics

Standard deviation127.48766
Coefficient of variation (CV)0.29931231
Kurtosis-0.46484715
Mean425.93525
Median Absolute Deviation (MAD)39
Skewness1.0512624
Sum59205
Variance16253.104
MonotonicityNot monotonic
2023-12-11T15:22:41.687720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
301 1
 
0.7%
398 1
 
0.7%
392 1
 
0.7%
393 1
 
0.7%
394 1
 
0.7%
395 1
 
0.7%
396 1
 
0.7%
397 1
 
0.7%
399 1
 
0.7%
390 1
 
0.7%
Other values (129) 129
92.8%
ValueCountFrequency (%)
301 1
0.7%
302 1
0.7%
303 1
0.7%
304 1
0.7%
305 1
0.7%
306 1
0.7%
307 1
0.7%
308 1
0.7%
309 1
0.7%
310 1
0.7%
ValueCountFrequency (%)
716 1
0.7%
711 1
0.7%
706 1
0.7%
701 1
0.7%
696 1
0.7%
691 1
0.7%
686 1
0.7%
681 1
0.7%
676 1
0.7%
671 1
0.7%

관리번호
Text

UNIQUE 

Distinct139
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-11T15:22:42.069645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

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

Unique

Unique139 ?
Unique (%)100.0%

Sample

1st rowJGS_000001
2nd rowJGS_000002
3rd rowJGS_000003
4th rowJGS_000004
5th rowJGS_000005
ValueCountFrequency (%)
jgs_000001 1
 
0.7%
jgs_000106 1
 
0.7%
jgs_000104 1
 
0.7%
jgs_000103 1
 
0.7%
jgs_000102 1
 
0.7%
jgs_000101 1
 
0.7%
jgs_000100 1
 
0.7%
jgs_000099 1
 
0.7%
jgs_000098 1
 
0.7%
jgs_000072 1
 
0.7%
Other values (129) 129
92.8%
2023-12-11T15:22:42.619634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

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

Most occurring scripts

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

Most frequent character per script

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

Most occurring blocks

ValueCountFrequency (%)
ASCII 1390
100.0%

Most frequent character per block

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

명칭
Text

UNIQUE 

Distinct139
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-11T15:22:42.914568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length23
Mean length10.086331
Min length3

Characters and Unicode

Total characters1402
Distinct characters376
Distinct categories8 ?
Distinct scripts6 ?
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??宮
2nd row??宮重明殿
3rd row옠丘壇
4th row?ロシア公使館
5th row貞洞第一??
ValueCountFrequency (%)
宮 1
 
0.7%
光熙洞中央アジア通り 1
 
0.7%
川（チョンゲチョン）の?史 1
 
0.7%
聖公?聖家修道院 1
 
0.7%
南山芸術センタ 1
 
0.7%
長通橋（ジャントンギョ 1
 
0.7%
中華料理店雅?園のスト?リ?,チャイナタウン 1
 
0.7%
明洞の洋씉店 1
 
0.7%
1950?60年代の「明洞の流行とファッション」 1
 
0.7%
1950年代の明洞の一日（東?日報1957年記事） 1
 
0.7%
Other values (136) 136
93.2%
2023-12-11T15:22:43.361722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 108
 
7.7%
ン 61
 
4.4%
（ 36
 
2.6%
） 34
 
2.4%
ョ 33
 
2.4%
の 30
 
2.1%
ル 24
 
1.7%
橋 23
 
1.6%
館 22
 
1.6%
洞 21
 
1.5%
Other values (366) 1010
72.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1146
81.7%
Other Punctuation 127
 
9.1%
Open Punctuation 45
 
3.2%
Close Punctuation 44
 
3.1%
Decimal Number 29
 
2.1%
Space Separator 8
 
0.6%
Dash Punctuation 2
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ン 61
 
5.3%
ョ 33
 
2.9%
の 30
 
2.6%
ル 24
 
2.1%
橋 23
 
2.0%
館 22
 
1.9%
洞 21
 
1.8%
ギ 20
 
1.7%
ウ 20
 
1.7%
ソ 18
 
1.6%
Other values (346) 874
76.3%
Decimal Number
ValueCountFrequency (%)
0 9
31.0%
1 6
20.7%
9 5
17.2%
5 4
13.8%
6 2
 
6.9%
7 2
 
6.9%
8 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
? 108
85.0%
· 10
 
7.9%
, 8
 
6.3%
、 1
 
0.8%
Open Punctuation
ValueCountFrequency (%)
（ 36
80.0%
( 8
 
17.8%
「 1
 
2.2%
Close Punctuation
ValueCountFrequency (%)
） 34
77.3%
) 9
 
20.5%
」 1
 
2.3%
Space Separator
ValueCountFrequency (%)
8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 675
48.1%
Katakana 415
29.6%
Common 255
 
18.2%
Hiragana 54
 
3.9%
Hangul 2
 
0.1%
Latin 1
 
0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
橋 23
 
3.4%
館 22
 
3.3%
洞 21
 
3.1%
明 16
 
2.4%
場 11
 
1.6%
門 10
 
1.5%
大 10
 
1.5%
川 9
 
1.3%
堂 9
 
1.3%
物 8
 
1.2%
Other values (258) 536
79.4%
Katakana
ValueCountFrequency (%)
ン 61
 
14.7%
ョ 33
 
8.0%
ル 24
 
5.8%
ギ 20
 
4.8%
ウ 20
 
4.8%
ソ 18
 
4.3%
ァ 12
 
2.9%
シ 10
 
2.4%
ジ 10
 
2.4%
ス 10
 
2.4%
Other values (58) 197
47.5%
Common
ValueCountFrequency (%)
? 108
42.4%
（ 36
 
14.1%
） 34
 
13.3%
· 10
 
3.9%
) 9
 
3.5%
0 9
 
3.5%
, 8
 
3.1%
8
 
3.1%
( 8
 
3.1%
1 6
 
2.4%
Other values (9) 19
 
7.5%
Hiragana
ValueCountFrequency (%)
の 30
55.6%
と 4
 
7.4%
た 3
 
5.6%
り 2
 
3.7%
び 2
 
3.7%
げ 1
 
1.9%
ち 1
 
1.9%
は 1
 
1.9%
し 1
 
1.9%
い 1
 
1.9%
Other values (8) 8
 
14.8%
Hangul
ValueCountFrequency (%)
씉 1
50.0%
옠 1
50.0%
Latin
ValueCountFrequency (%)
N 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 675
48.1%
Katakana 415
29.6%
ASCII 173
 
12.3%
None 83
 
5.9%
Hiragana 54
 
3.9%
Hangul 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 108
62.4%
) 9
 
5.2%
0 9
 
5.2%
, 8
 
4.6%
8
 
4.6%
( 8
 
4.6%
1 6
 
3.5%
9 5
 
2.9%
5 4
 
2.3%
6 2
 
1.2%
Other values (4) 6
 
3.5%
Katakana
ValueCountFrequency (%)
ン 61
 
14.7%
ョ 33
 
8.0%
ル 24
 
5.8%
ギ 20
 
4.8%
ウ 20
 
4.8%
ソ 18
 
4.3%
ァ 12
 
2.9%
シ 10
 
2.4%
ジ 10
 
2.4%
ス 10
 
2.4%
Other values (58) 197
47.5%
None
ValueCountFrequency (%)
（ 36
43.4%
） 34
41.0%
· 10
 
12.0%
、 1
 
1.2%
「 1
 
1.2%
」 1
 
1.2%
Hiragana
ValueCountFrequency (%)
の 30
55.6%
と 4
 
7.4%
た 3
 
5.6%
り 2
 
3.7%
び 2
 
3.7%
げ 1
 
1.9%
ち 1
 
1.9%
は 1
 
1.9%
し 1
 
1.9%
い 1
 
1.9%
Other values (8) 8
 
14.8%
CJK
ValueCountFrequency (%)
橋 23
 
3.4%
館 22
 
3.3%
洞 21
 
3.1%
明 16
 
2.4%
場 11
 
1.6%
門 10
 
1.5%
大 10
 
1.5%
川 9
 
1.3%
堂 9
 
1.3%
物 8
 
1.2%
Other values (258) 536
79.4%
Hangul
ValueCountFrequency (%)
씉 1
50.0%
옠 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
2023-12-11T15:22:43.702235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

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

Unique

Unique85 ?
Unique (%)100.0%

Sample

1st rowJGH_000370
2nd rowJGH_000350
3rd rowJGH_000335
4th rowJGH_000355
5th rowJGH_000367
ValueCountFrequency (%)
jgh_000360 1
 
1.2%
jgh_001149 1
 
1.2%
jgh_000669 1
 
1.2%
jgh_000820 1
 
1.2%
jgh_000381 1
 
1.2%
jgh_000018 1
 
1.2%
jgh_000036 1
 
1.2%
jgh_000462 1
 
1.2%
jgh_000526 1
 
1.2%
jgh_000097 1
 
1.2%
Other values (75) 75
88.2%
2023-12-11T15:22:44.181165image/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
2023-12-11T15:22:44.366096image/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
2023-12-11T15:22:44.583329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.98378 2
 
1.4%
126.98187 2
 
1.4%
126.97063 2
 
1.4%
126.98283 1
 
0.7%
126.98517 1
 
0.7%
126.98468 1
 
0.7%
126.98509 1
 
0.7%
126.9846 1
 
0.7%
126.98455 1
 
0.7%
126.9849 1
 
0.7%
Other values (126) 126
90.6%
ValueCountFrequency (%)
126.97063 2
1.4%
126.97133 1
0.7%
126.97146 1
0.7%
126.97217 1
0.7%
126.97236 1
0.7%
126.97252 1
0.7%
126.97262 1
0.7%
126.97285 1
0.7%
126.97294 1
0.7%
126.97337 1
0.7%
ValueCountFrequency (%)
127.037931 1
0.7%
127.033545 1
0.7%
127.030354 1
0.7%
127.026658 1
0.7%
127.025354 1
0.7%
127.023407 1
0.7%
127.01905 1
0.7%
127.017441 1
0.7%
127.015917 1
0.7%
127.01503 1
0.7%

위도정보(36.XXX)
Real number (ℝ)

Distinct134
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.563656
Minimum37.55116
Maximum37.572332
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T15:22:44.801865image/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
2023-12-11T15:22:44.950199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.56339 3
 
2.2%
37.569794 2
 
1.4%
37.568862 2
 
1.4%
37.5662 2
 
1.4%
37.56394 1
 
0.7%
37.56255 1
 
0.7%
37.56231 1
 
0.7%
37.56125 1
 
0.7%
37.56275 1
 
0.7%
37.56303 1
 
0.7%
Other values (124) 124
89.2%
ValueCountFrequency (%)
37.55116 1
0.7%
37.55139 1
0.7%
37.55159 1
0.7%
37.55164 1
0.7%
37.55184 1
0.7%
37.55201 1
0.7%
37.55235 1
0.7%
37.55254 1
0.7%
37.55284 1
0.7%
37.55347 1
0.7%
ValueCountFrequency (%)
37.572332 1
0.7%
37.571725 1
0.7%
37.571037 1
0.7%
37.571027 1
0.7%
37.570804 1
0.7%
37.57076 1
0.7%
37.570278 1
0.7%
37.569842 1
0.7%
37.569826 1
0.7%
37.569794 2
1.4%

이명칭
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing134
Missing (%)96.4%
Memory size1.2 KiB
2023-12-11T15:22:45.157087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length10
Min length5

Characters and Unicode

Total characters50
Distinct characters32
Distinct categories3 ?
Distinct scripts3 ?
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慶運宮, 貞陵洞行宮, 西宮
2nd row大韓聖公?ソウル聖堂
3rd row美笑?用館
4th row李王家美術館, 李王職美術館
5th row韓?自由?連盟
ValueCountFrequency (%)
慶運宮 1
12.5%
貞陵洞行宮 1
12.5%
西宮 1
12.5%
大韓聖公?ソウル聖堂 1
12.5%
美笑?用館 1
12.5%
李王家美術館 1
12.5%
李王職美術館 1
12.5%
韓?自由?連盟 1
12.5%
2023-12-11T15:22:45.492703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 4
 
8.0%
宮 3
 
6.0%
, 3
 
6.0%
3
 
6.0%
館 3
 
6.0%
美 3
 
6.0%
術 2
 
4.0%
聖 2
 
4.0%
李 2
 
4.0%
王 2
 
4.0%
Other values (22) 23
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 40
80.0%
Other Punctuation 7
 
14.0%
Space Separator 3
 
6.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
宮 3
 
7.5%
館 3
 
7.5%
美 3
 
7.5%
術 2
 
5.0%
聖 2
 
5.0%
李 2
 
5.0%
王 2
 
5.0%
韓 2
 
5.0%
用 1
 
2.5%
慶 1
 
2.5%
Other values (19) 19
47.5%
Other Punctuation
ValueCountFrequency (%)
? 4
57.1%
, 3
42.9%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 37
74.0%
Common 10
 
20.0%
Katakana 3
 
6.0%

Most frequent character per script

Han
ValueCountFrequency (%)
宮 3
 
8.1%
館 3
 
8.1%
美 3
 
8.1%
術 2
 
5.4%
聖 2
 
5.4%
李 2
 
5.4%
王 2
 
5.4%
韓 2
 
5.4%
用 1
 
2.7%
慶 1
 
2.7%
Other values (16) 16
43.2%
Common
ValueCountFrequency (%)
? 4
40.0%
, 3
30.0%
3
30.0%
Katakana
ValueCountFrequency (%)
ウ 1
33.3%
ル 1
33.3%
ソ 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
CJK 37
74.0%
ASCII 10
 
20.0%
Katakana 3
 
6.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 4
40.0%
, 3
30.0%
3
30.0%
CJK
ValueCountFrequency (%)
宮 3
 
8.1%
館 3
 
8.1%
美 3
 
8.1%
術 2
 
5.4%
聖 2
 
5.4%
李 2
 
5.4%
王 2
 
5.4%
韓 2
 
5.4%
用 1
 
2.7%
慶 1
 
2.7%
Other values (16) 16
43.2%
Katakana
ValueCountFrequency (%)
ウ 1
33.3%
ル 1
33.3%
ソ 1
33.3%

개요
Text

UNIQUE 

Distinct139
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-11T15:22:45.842087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length385
Median length99
Mean length76.841727
Min length7

Characters and Unicode

Total characters10681
Distinct characters910
Distinct categories13 ?
Distinct scripts6 ?
Distinct blocks9 ?
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昔の名?は慶運宮でしたが1907年から??宮と呼ばれるようなりました。 6万1500㎡の面積に大漢門、中和門、光明門、中和殿、浚明堂、昔御堂、石造殿、咸寧殿、??堂などの殿閣が?っています。
2nd row1901年に建てられた重明殿は、今の??宮である慶運宮に含まれている建物で、接見所と宴?場、?書館として使用されていました。1907年に皇太子の嘉?の宴?が行われた場所で、乙巳?約が締結された悲運の場所でもあります。日本統治期の1915年から外?人に貸され、京城??部が利用しました。
3rd row옠丘壇は皇帝が天に祭祀を捧げる祭壇のことです。ここは朝鮮を引き?いだ大韓帝?の高宗皇帝が天に祭祀を捧げげ場所です。1897年に完成した옠丘壇は、?時、皇室最高の建築家だった沈宜錫設計しました。
4th row1890（高宗27）年にロシア人のサバティン（AISabatin）が設計したルネッサンス?式の建物です。本館は朝鮮??で?れ、現在は3階建ての塔だけが?っています。高宗が日本の武力の?迫を避けた露館播遷の現場として有名です。
5th row貞洞一番??は1895（高宗32）年に着工し1897（光武1）年10月に竣工したプロテスタント??の??堂です。
ValueCountFrequency (%)
昔の名?は慶運宮でしたが1907年から??宮と呼ばれるようなりました。 1
 
0.6%
果物を?る毛廛がいた毛廛橋、今はパルソクダム(八石潭)で願いをする場所 1
 
0.6%
この記念館は、日本統治時代の1925年5月24日に竣工し、2007年12月に撤去された東大門運動場で行われた試合や集?に?連する記?と東大門運動場の?部施設などを保管、展示しています。 1
 
0.6%
漢陽都城の東大門の下にあった五間水門のすぐ南にあった水門です。南山から流れ出た水は二間水門を通って都城の外で??川の本流と合流しました。2つの虹霓門からできていることから二間水門と呼ばれました。 1
 
0.6%
昔の東大門運動場に建てられた東大門デザインプラザは、2009年4月に着工し、2014年3月に開館した複合文化空間です。 1
 
0.6%
日本統治時代から解放期、朝鮮??を?て、1960年代に至るまで、明洞の喫茶店は文化人や芸術家が集まって議論し、作業して休んでいく場所でした。 1
 
0.6%
喫茶店は日本統治時代に初めて作られ、開放と朝鮮??を?て、芸術家たちが活動する?合芸術の場となります。1970年代に入り、ヒッピ?文化を?しむ若者たちが集まりました。 1
 
0.6%
1970年代明洞は、全?で最も地?が高く、最新のファッションが流行していた街でした。若者たちは西?から入ってきたヒッピ?文化を喫茶店やビアホ?ルで?しみました。 1
 
0.6%
通橋の石築と橋脚の意味 1
 
0.6%
神?(シントク)王侯陵の飾り石で造った?通橋 1
 
0.6%
Other values (164) 164
94.3%
2023-12-11T15:22:46.420043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 658
 
6.2%
の 363
 
3.4%
、 290
 
2.7%
た 285
 
2.7%
し 279
 
2.6%
に 258
 
2.4%
で 200
 
1.9%
。 197
 
1.8%
1 181
 
1.7%
ま 175
 
1.6%
Other values (900) 7795
73.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8445
79.1%
Other Punctuation 1178
 
11.0%
Decimal Number 753
 
7.0%
Lowercase Letter 122
 
1.1%
Open Punctuation 53
 
0.5%
Close Punctuation 53
 
0.5%
Space Separator 37
 
0.3%
Uppercase Letter 28
 
0.3%
Math Symbol 5
 
< 0.1%
Initial Punctuation 3
 
< 0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
の 363
 
4.3%
た 285
 
3.4%
し 279
 
3.3%
に 258
 
3.1%
で 200
 
2.4%
ま 175
 
2.1%
て 160
 
1.9%
年 152
 
1.8%
す 151
 
1.8%
を 143
 
1.7%
Other values (834) 6279
74.4%
Lowercase Letter
ValueCountFrequency (%)
e 14
11.5%
o 14
11.5%
r 12
9.8%
a 11
9.0%
m 10
 
8.2%
l 10
 
8.2%
i 8
 
6.6%
s 7
 
5.7%
n 7
 
5.7%
p 4
 
3.3%
Other values (12) 25
20.5%
Uppercase Letter
ValueCountFrequency (%)
H 5
17.9%
S 5
17.9%
C 3
10.7%
N 3
10.7%
M 2
 
7.1%
G 2
 
7.1%
A 2
 
7.1%
E 1
 
3.6%
B 1
 
3.6%
R 1
 
3.6%
Other values (3) 3
10.7%
Decimal Number
ValueCountFrequency (%)
1 181
24.0%
9 140
18.6%
0 115
15.3%
2 60
 
8.0%
5 50
 
6.6%
3 48
 
6.4%
6 45
 
6.0%
7 44
 
5.8%
8 41
 
5.4%
4 29
 
3.9%
Other Punctuation
ValueCountFrequency (%)
? 658
55.9%
、 290
24.6%
。 197
 
16.7%
· 16
 
1.4%
' 7
 
0.6%
. 4
 
0.3%
, 4
 
0.3%
＇ 1
 
0.1%
! 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
（ 32
60.4%
( 16
30.2%
「 5
 
9.4%
Close Punctuation
ValueCountFrequency (%)
） 31
58.5%
) 17
32.1%
」 5
 
9.4%
Space Separator
ValueCountFrequency (%)
37
100.0%
Math Symbol
ValueCountFrequency (%)
∼ 5
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 3
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 4012
37.6%
Hiragana 3489
32.7%
Common 2086
19.5%
Katakana 931
 
8.7%
Latin 150
 
1.4%
Hangul 13
 
0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
年 152
 
3.8%
建 73
 
1.8%
場 71
 
1.8%
代 53
 
1.3%
韓 51
 
1.3%
館 50
 
1.2%
物 46
 
1.1%
門 44
 
1.1%
大 43
 
1.1%
立 43
 
1.1%
Other values (700) 3386
84.4%
Katakana
ValueCountFrequency (%)
ン 104
 
11.2%
ル 81
 
8.7%
ソ 41
 
4.4%
ウ 40
 
4.3%
ア 32
 
3.4%
ス 32
 
3.4%
タ 30
 
3.2%
リ 24
 
2.6%
プ 24
 
2.6%
ム 24
 
2.6%
Other values (62) 499
53.6%
Hiragana
ValueCountFrequency (%)
の 363
 
10.4%
た 285
 
8.2%
し 279
 
8.0%
に 258
 
7.4%
で 200
 
5.7%
ま 175
 
5.0%
て 160
 
4.6%
す 151
 
4.3%
を 143
 
4.1%
は 136
 
3.9%
Other values (46) 1339
38.4%
Latin
ValueCountFrequency (%)
e 14
 
9.3%
o 14
 
9.3%
r 12
 
8.0%
a 11
 
7.3%
m 10
 
6.7%
l 10
 
6.7%
i 8
 
5.3%
s 7
 
4.7%
n 7
 
4.7%
H 5
 
3.3%
Other values (25) 52
34.7%
Common
ValueCountFrequency (%)
? 658
31.5%
、 290
13.9%
。 197
 
9.4%
1 181
 
8.7%
9 140
 
6.7%
0 115
 
5.5%
2 60
 
2.9%
5 50
 
2.4%
3 48
 
2.3%
6 45
 
2.2%
Other values (21) 302
14.5%
Hangul
ValueCountFrequency (%)
씉 5
38.5%
앬 3
23.1%
옠 2
 
15.4%
쑿 1
 
7.7%
싲 1
 
7.7%
쑒 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
CJK 4012
37.6%
Hiragana 3489
32.7%
ASCII 1648
15.4%
Katakana 931
 
8.7%
None 577
 
5.4%
Hangul 13
 
0.1%
Math Operators 5
 
< 0.1%
Punctuation 4
 
< 0.1%
CJK Compat 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 658
39.9%
1 181
 
11.0%
9 140
 
8.5%
0 115
 
7.0%
2 60
 
3.6%
5 50
 
3.0%
3 48
 
2.9%
6 45
 
2.7%
7 44
 
2.7%
8 41
 
2.5%
Other values (44) 266
16.1%
Hiragana
ValueCountFrequency (%)
の 363
 
10.4%
た 285
 
8.2%
し 279
 
8.0%
に 258
 
7.4%
で 200
 
5.7%
ま 175
 
5.0%
て 160
 
4.6%
す 151
 
4.3%
を 143
 
4.1%
は 136
 
3.9%
Other values (46) 1339
38.4%
None
ValueCountFrequency (%)
、 290
50.3%
。 197
34.1%
（ 32
 
5.5%
） 31
 
5.4%
· 16
 
2.8%
」 5
 
0.9%
「 5
 
0.9%
＇ 1
 
0.2%
CJK
ValueCountFrequency (%)
年 152
 
3.8%
建 73
 
1.8%
場 71
 
1.8%
代 53
 
1.3%
韓 51
 
1.3%
館 50
 
1.2%
物 46
 
1.1%
門 44
 
1.1%
大 43
 
1.1%
立 43
 
1.1%
Other values (700) 3386
84.4%
Katakana
ValueCountFrequency (%)
ン 104
 
11.2%
ル 81
 
8.7%
ソ 41
 
4.4%
ウ 40
 
4.3%
ア 32
 
3.4%
ス 32
 
3.4%
タ 30
 
3.2%
リ 24
 
2.6%
プ 24
 
2.6%
ム 24
 
2.6%
Other values (62) 499
53.6%
Math Operators
ValueCountFrequency (%)
∼ 5
100.0%
Hangul
ValueCountFrequency (%)
씉 5
38.5%
앬 3
23.1%
옠 2
 
15.4%
쑿 1
 
7.7%
싲 1
 
7.7%
쑒 1
 
7.7%
Punctuation
ValueCountFrequency (%)
‘ 3
75.0%
’ 1
 
25.0%
CJK Compat
ValueCountFrequency (%)
㎡ 2
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
2023-12-11T15:22:46.722971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length15
Min length8

Characters and Unicode

Total characters2085
Distinct characters99
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks4 ?
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ソウル特別市中?世宗大路99
2nd rowソウル特別市中?貞洞ギル41-11
3rd rowソウル特別市中?小公路106
4th rowソウル特別市中?貞洞ギル21-18 貞洞公園
5th rowソウル特別市中?貞洞ギル46 貞洞??
ValueCountFrequency (%)
ソウル特別市中?/鍾路 19
 
11.6%
ソウル特別市中?明洞一 12
 
7.3%
ソウル特別市 9
 
5.5%
川 9
 
5.5%
ソウル特別市鍾路 5
 
3.0%
ソウル特別市東大門?/城東 4
 
2.4%
ソウル特別市中?退?路34ギル28 3
 
1.8%
ソウル特別市中?素月路91 2
 
1.2%
ソウル特別市中?明洞ギル26 2
 
1.2%
ソウル特別市中??忠壇路59 2
 
1.2%
Other values (89) 97
59.1%
2023-12-11T15:22:47.213738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 238
 
11.4%
ル 177
 
8.5%
ウ 141
 
6.8%
市 141
 
6.8%
ソ 140
 
6.7%
別 140
 
6.7%
特 140
 
6.7%
中 120
 
5.8%
路 77
 
3.7%
1 67
 
3.2%
Other values (89) 704
33.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1480
71.0%
Decimal Number 276
 
13.2%
Other Punctuation 264
 
12.7%
Space Separator 25
 
1.2%
Dash Punctuation 23
 
1.1%
Uppercase Letter 11
 
0.5%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ル 177
12.0%
ウ 141
9.5%
市 141
9.5%
ソ 140
9.5%
別 140
9.5%
特 140
9.5%
中 120
 
8.1%
路 77
 
5.2%
洞 45
 
3.0%
ギ 35
 
2.4%
Other values (63) 324
21.9%
Decimal Number
ValueCountFrequency (%)
1 67
24.3%
2 48
17.4%
5 27
9.8%
3 22
 
8.0%
4 21
 
7.6%
6 20
 
7.2%
9 19
 
6.9%
0 19
 
6.9%
8 17
 
6.2%
7 16
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
A 3
27.3%
I 1
 
9.1%
U 1
 
9.1%
T 1
 
9.1%
R 1
 
9.1%
Y 1
 
9.1%
W 1
 
9.1%
C 1
 
9.1%
M 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
? 238
90.2%
/ 24
 
9.1%
, 2
 
0.8%
Space Separator
ValueCountFrequency (%)
25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Open Punctuation
ValueCountFrequency (%)
（ 3
100.0%
Close Punctuation
ValueCountFrequency (%)
） 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 978
46.9%
Common 594
28.5%
Katakana 502
24.1%
Latin 11
 
0.5%

Most frequent character per script

Han
ValueCountFrequency (%)
市 141
14.4%
別 140
14.3%
特 140
14.3%
中 120
12.3%
路 77
 
7.9%
洞 45
 
4.6%
鍾 24
 
2.5%
大 20
 
2.0%
明 19
 
1.9%
一 16
 
1.6%
Other values (50) 236
24.1%
Common
ValueCountFrequency (%)
? 238
40.1%
1 67
 
11.3%
2 48
 
8.1%
5 27
 
4.5%
25
 
4.2%
/ 24
 
4.0%
- 23
 
3.9%
3 22
 
3.7%
4 21
 
3.5%
6 20
 
3.4%
Other values (7) 79
 
13.3%
Katakana
ValueCountFrequency (%)
ル 177
35.3%
ウ 141
28.1%
ソ 140
27.9%
ギ 35
 
7.0%
ネ 1
 
0.2%
ユ 1
 
0.2%
ス 1
 
0.2%
コ 1
 
0.2%
ガ 1
 
0.2%
ト 1
 
0.2%
Other values (3) 3
 
0.6%
Latin
ValueCountFrequency (%)
A 3
27.3%
I 1
 
9.1%
U 1
 
9.1%
T 1
 
9.1%
R 1
 
9.1%
Y 1
 
9.1%
W 1
 
9.1%
C 1
 
9.1%
M 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
CJK 978
46.9%
ASCII 599
28.7%
Katakana 502
24.1%
None 6
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 238
39.7%
1 67
 
11.2%
2 48
 
8.0%
5 27
 
4.5%
25
 
4.2%
/ 24
 
4.0%
- 23
 
3.8%
3 22
 
3.7%
4 21
 
3.5%
6 20
 
3.3%
Other values (14) 84
 
14.0%
Katakana
ValueCountFrequency (%)
ル 177
35.3%
ウ 141
28.1%
ソ 140
27.9%
ギ 35
 
7.0%
ネ 1
 
0.2%
ユ 1
 
0.2%
ス 1
 
0.2%
コ 1
 
0.2%
ガ 1
 
0.2%
ト 1
 
0.2%
Other values (3) 3
 
0.6%
CJK
ValueCountFrequency (%)
市 141
14.4%
別 140
14.3%
特 140
14.3%
中 120
12.3%
路 77
 
7.9%
洞 45
 
4.6%
鍾 24
 
2.5%
大 20
 
2.0%
明 19
 
1.9%
一 16
 
1.6%
Other values (50) 236
24.1%
None
ValueCountFrequency (%)
（ 3
50.0%
） 3
50.0%

지역
Categorical

Distinct24
Distinct (%)17.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
39 
ソウル特別市中?明洞
13 
ソウル特別市中?世宗大路
10 
ソウル特別市中?退?路
9 
ソウル特別市中?貞洞ギル
8 
Other values (19)
60 

Length

Max length15
Median length14
Mean length9.3165468
Min length4

Unique

Unique4 ?
Unique (%)2.9%

Sample

1st rowソウル特別市中?世宗大路
2nd rowソウル特別市中?貞洞ギル
3rd rowソウル特別市中?小公路
4th rowソウル特別市中?貞洞ギル
5th rowソウル特別市中?貞洞ギル

Common Values

ValueCountFrequency (%)
<NA> 39
28.1%
ソウル特別市中?明洞 13
 
9.4%
ソウル特別市中?世宗大路 10
 
7.2%
ソウル特別市中?退?路 9
 
6.5%
ソウル特別市中?貞洞ギル 8
 
5.8%
ソウル特別市中?小波路 6
 
4.3%
ソウル特別市中?明洞ギル 6
 
4.3%
ソウル特別市中??忠壇路 5
 
3.6%
ソウル特別市中??忠洞 5
 
3.6%
ソウル特別市中?乙支路 5
 
3.6%
Other values (14) 33
23.7%

Length

2023-12-11T15:22:47.379110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 39
28.1%
ソウル特別市中?明洞 13
 
9.4%
ソウル特別市中?世宗大路 10
 
7.2%
ソウル特別市中?退?路 9
 
6.5%
ソウル特別市中?貞洞ギル 8
 
5.8%
ソウル特別市中?小波路 6
 
4.3%
ソウル特別市中?明洞ギル 6
 
4.3%
ソウル特別市中??忠壇路 5
 
3.6%
ソウル特別市中??忠洞 5
 
3.6%
ソウル特別市中?乙支路 5
 
3.6%
Other values (14) 33
23.7%

제공기관
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
ソウル中???
100 
ソウル特別市
39 

Length

Max length7
Median length7
Mean length6.7194245
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowソウル中???
2nd rowソウル中???
3rd rowソウル中???
4th rowソウル中???
5th rowソウル中???

Common Values

ValueCountFrequency (%)
ソウル中??? 100
71.9%
ソウル特別市 39
 
28.1%

Length

2023-12-11T15:22:47.515560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:22:47.632455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ソウル中 100
71.9%
ソウル特別市 39
 
28.1%

언어유형
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
JPN 139
100.0%

Length

2023-12-11T15:22:47.767363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:22:47.876484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
jpn 139
100.0%

제작일
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)1.0%
Missing39
Missing (%)28.1%
Memory size1.2 KiB
Minimum2015-12-30 00:00:00
Maximum2015-12-30 00:00:00
2023-12-11T15:22:47.965796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:22:48.073074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=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

2023-12-11T15:22:48.215432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:22:48.324713image/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

2023-12-11T15:22:48.457550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:22:48.569399image/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
2023-12-11T15:22:48.753065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length11.46875
Min length6

Characters and Unicode

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

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row02-771-9951
2nd row02-2124-8800
3rd row02-720-9494
4th row02-730-6611
5th row02-777-4258
ValueCountFrequency (%)
02-753-2403 1
 
3.0%
1588-1234 1
 
3.0%
02-3455-8341 1
 
3.0%
02-779-6107 1
 
3.0%
02-753-2805 1
 
3.0%
02-2280-4114 1
 
3.0%
02-774-1784 1
 
3.0%
02-759-4881 1
 
3.0%
02-771-9951 1
 
3.0%
02-3455-9277 1
 
3.0%
Other values (23) 23
69.7%
2023-12-11T15:22:49.131106image/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
2023-12-11T15:22:49.356783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length10.3
Min length5

Characters and Unicode

Total characters206
Distinct characters33
Distinct categories3 ?
Distinct scripts4 ?
Distinct blocks4 ?
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史跡第124?
2nd rowソウル特別市記念物第16?
3rd row登?文化財第237?
4th row登?文化財第267?
5th row登?文化財第402?
ValueCountFrequency (%)
史跡第124 2
 
10.0%
登?文化財第238 1
 
5.0%
登?文化財第1 1
 
5.0%
ソウル特別市民俗資料第제5 1
 
5.0%
ソウル特別市有形文化財第71 1
 
5.0%
史跡第280 1
 
5.0%
ソウル特別市有形文化財第18 1
 
5.0%
ソウル特別市有形文化財第20 1
 
5.0%
第1 1
 
5.0%
登?文化財第52 1
 
5.0%
Other values (9) 9
45.0%
2023-12-11T15:22:49.686673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 30
 
14.6%
第 20
 
9.7%
財 12
 
5.8%
化 12
 
5.8%
文 12
 
5.8%
1 10
 
4.9%
2 10
 
4.9%
登 8
 
3.9%
市 7
 
3.4%
ソ 7
 
3.4%
Other values (23) 78
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133
64.6%
Decimal Number 43
 
20.9%
Other Punctuation 30
 
14.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
第 20
15.0%
財 12
 
9.0%
化 12
 
9.0%
文 12
 
9.0%
登 8
 
6.0%
市 7
 
5.3%
ソ 7
 
5.3%
ウ 7
 
5.3%
ル 7
 
5.3%
特 7
 
5.3%
Other values (13) 34
25.6%
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%
4 3
 
7.0%
7 3
 
7.0%
6 2
 
4.7%
Other Punctuation
ValueCountFrequency (%)
? 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 111
53.9%
Common 73
35.4%
Katakana 21
 
10.2%
Hangul 1
 
0.5%

Most frequent character per script

Han
ValueCountFrequency (%)
第 20
18.0%
財 12
10.8%
化 12
10.8%
文 12
10.8%
登 8
 
7.2%
市 7
 
6.3%
特 7
 
6.3%
別 7
 
6.3%
形 4
 
3.6%
跡 4
 
3.6%
Other values (9) 18
16.2%
Common
ValueCountFrequency (%)
? 30
41.1%
1 10
 
13.7%
2 10
 
13.7%
0 5
 
6.8%
3 4
 
5.5%
5 3
 
4.1%
8 3
 
4.1%
4 3
 
4.1%
7 3
 
4.1%
6 2
 
2.7%
Katakana
ValueCountFrequency (%)
ソ 7
33.3%
ウ 7
33.3%
ル 7
33.3%
Hangul
ValueCountFrequency (%)
제 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 111
53.9%
ASCII 73
35.4%
Katakana 21
 
10.2%
Hangul 1
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 30
41.1%
1 10
 
13.7%
2 10
 
13.7%
0 5
 
6.8%
3 4
 
5.5%
5 3
 
4.1%
8 3
 
4.1%
4 3
 
4.1%
7 3
 
4.1%
6 2
 
2.7%
CJK
ValueCountFrequency (%)
第 20
18.0%
財 12
10.8%
化 12
10.8%
文 12
10.8%
登 8
 
7.2%
市 7
 
6.3%
特 7
 
6.3%
別 7
 
6.3%
形 4
 
3.6%
跡 4
 
3.6%
Other values (9) 18
16.2%
Katakana
ValueCountFrequency (%)
ソ 7
33.3%
ウ 7
33.3%
ル 7
33.3%
Hangul
ValueCountFrequency (%)
제 1
100.0%

휴무일
Text

MISSING 

Distinct9
Distinct (%)64.3%
Missing125
Missing (%)89.9%
Memory size1.2 KiB
2023-12-11T15:22:49.849503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length21
Mean length11.214286
Min length5

Characters and Unicode

Total characters157
Distinct characters27
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)35.7%

Sample

1st row?週月曜日
2nd row?週月曜日, 休日
3rd row?週月曜日, 1月1日
4th row?週日曜日
5th row?週月曜日, 1月1日
ValueCountFrequency (%)
週月曜日 10
37.0%
1月1日 4
 
14.8%
休日 3
 
11.1%
週日曜日 3
 
11.1%
週火曜日 1
 
3.7%
陰?正月 1
 
3.7%
秋夕 1
 
3.7%
陰?正月連休および秋夕連休 1
 
3.7%
12月29日?翌年1月2日 1
 
3.7%
名節 1
 
3.7%
2023-12-11T15:22:50.206774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
日 27
17.2%
? 18
11.5%
月 18
11.5%
曜 14
8.9%
週 14
8.9%
, 13
8.3%
13
8.3%
1 10
 
6.4%
休 5
 
3.2%
2 3
 
1.9%
Other values (17) 22
14.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99
63.1%
Other Punctuation 31
 
19.7%
Decimal Number 14
 
8.9%
Space Separator 13
 
8.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
日 27
27.3%
月 18
18.2%
曜 14
14.1%
週 14
14.1%
休 5
 
5.1%
秋 2
 
2.0%
連 2
 
2.0%
夕 2
 
2.0%
正 2
 
2.0%
陰 2
 
2.0%
Other values (11) 11
11.1%
Decimal Number
ValueCountFrequency (%)
1 10
71.4%
2 3
 
21.4%
9 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
? 18
58.1%
, 13
41.9%
Space Separator
ValueCountFrequency (%)
13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 95
60.5%
Common 58
36.9%
Hiragana 4
 
2.5%

Most frequent character per script

Han
ValueCountFrequency (%)
日 27
28.4%
月 18
18.9%
曜 14
14.7%
週 14
14.7%
休 5
 
5.3%
秋 2
 
2.1%
連 2
 
2.1%
夕 2
 
2.1%
正 2
 
2.1%
陰 2
 
2.1%
Other values (7) 7
 
7.4%
Common
ValueCountFrequency (%)
? 18
31.0%
, 13
22.4%
13
22.4%
1 10
17.2%
2 3
 
5.2%
9 1
 
1.7%
Hiragana
ValueCountFrequency (%)
お 1
25.0%
よ 1
25.0%
び 1
25.0%
の 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 95
60.5%
ASCII 58
36.9%
Hiragana 4
 
2.5%

Most frequent character per block

CJK
ValueCountFrequency (%)
日 27
28.4%
月 18
18.9%
曜 14
14.7%
週 14
14.7%
休 5
 
5.3%
秋 2
 
2.1%
連 2
 
2.1%
夕 2
 
2.1%
正 2
 
2.1%
陰 2
 
2.1%
Other values (7) 7
 
7.4%
ASCII
ValueCountFrequency (%)
? 18
31.0%
, 13
22.4%
13
22.4%
1 10
17.2%
2 3
 
5.2%
9 1
 
1.7%
Hiragana
ValueCountFrequency (%)
お 1
25.0%
よ 1
25.0%
び 1
25.0%
の 1
25.0%

이용시간
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing130
Missing (%)93.5%
Memory size1.2 KiB
2023-12-11T15:22:50.380187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length46
Mean length23.222222
Min length13

Characters and Unicode

Total characters209
Distinct characters39
Distinct categories5 ?
Distinct scripts5 ?
Distinct blocks5 ?
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入場チケット販?および入場時間 09:00 ~ 20:00 퇴장시간 09:00 ~ 21:00
2nd row?日10:00 ~ 17:00
3rd row平日09:00 ~ 21:00
4th row09:00 ~ 18:00
5th row?週火曜日 ~ 일요일 10:00 ~ 18:00
ValueCountFrequency (%)
10
24.4%
17:00 5
12.2%
10:00 4
 
9.8%
18:00 3
 
7.3%
20:00 3
 
7.3%
09:00 3
 
7.3%
21:00 2
 
4.9%
토 1
 
2.4%
日および休日 1
 
2.4%
月~金 1
 
2.4%
Other values (8) 8
19.5%
2023-12-11T15:22:50.716975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 58
27.8%
32
15.3%
: 23
 
11.0%
1 16
 
7.7%
~ 12
 
5.7%
日 8
 
3.8%
2 5
 
2.4%
7 5
 
2.4%
9 4
 
1.9%
, 4
 
1.9%
Other values (29) 42
20.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 92
44.0%
Other Letter 43
20.6%
Space Separator 32
 
15.3%
Other Punctuation 30
 
14.4%
Math Symbol 12
 
5.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
日 8
18.6%
曜 3
 
7.0%
お 2
 
4.7%
よ 2
 
4.7%
火 2
 
4.7%
場 2
 
4.7%
入 2
 
4.7%
일 2
 
4.7%
び 2
 
4.7%
月 1
 
2.3%
Other values (17) 17
39.5%
Decimal Number
ValueCountFrequency (%)
0 58
63.0%
1 16
 
17.4%
2 5
 
5.4%
7 5
 
5.4%
9 4
 
4.3%
8 3
 
3.3%
4 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
: 23
76.7%
, 4
 
13.3%
? 3
 
10.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 166
79.4%
Han 25
 
12.0%
Hangul 8
 
3.8%
Hiragana 6
 
2.9%
Katakana 4
 
1.9%

Most frequent character per script

Han
ValueCountFrequency (%)
日 8
32.0%
曜 3
 
12.0%
火 2
 
8.0%
場 2
 
8.0%
入 2
 
8.0%
月 1
 
4.0%
週 1
 
4.0%
休 1
 
4.0%
金 1
 
4.0%
平 1
 
4.0%
Other values (3) 3
 
12.0%
Common
ValueCountFrequency (%)
0 58
34.9%
32
19.3%
: 23
 
13.9%
1 16
 
9.6%
~ 12
 
7.2%
2 5
 
3.0%
7 5
 
3.0%
9 4
 
2.4%
, 4
 
2.4%
8 3
 
1.8%
Other values (2) 4
 
2.4%
Hangul
ValueCountFrequency (%)
일 2
25.0%
요 1
12.5%
토 1
12.5%
퇴 1
12.5%
간 1
12.5%
시 1
12.5%
장 1
12.5%
Katakana
ValueCountFrequency (%)
ト 1
25.0%
ッ 1
25.0%
ケ 1
25.0%
チ 1
25.0%
Hiragana
ValueCountFrequency (%)
お 2
33.3%
よ 2
33.3%
び 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 166
79.4%
CJK 25
 
12.0%
Hangul 8
 
3.8%
Hiragana 6
 
2.9%
Katakana 4
 
1.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 58
34.9%
32
19.3%
: 23
 
13.9%
1 16
 
9.6%
~ 12
 
7.2%
2 5
 
3.0%
7 5
 
3.0%
9 4
 
2.4%
, 4
 
2.4%
8 3
 
1.8%
Other values (2) 4
 
2.4%
CJK
ValueCountFrequency (%)
日 8
32.0%
曜 3
 
12.0%
火 2
 
8.0%
場 2
 
8.0%
入 2
 
8.0%
月 1
 
4.0%
週 1
 
4.0%
休 1
 
4.0%
金 1
 
4.0%
平 1
 
4.0%
Other values (3) 3
 
12.0%
Hiragana
ValueCountFrequency (%)
お 2
33.3%
よ 2
33.3%
び 2
33.3%
Hangul
ValueCountFrequency (%)
일 2
25.0%
요 1
12.5%
토 1
12.5%
퇴 1
12.5%
간 1
12.5%
시 1
12.5%
장 1
12.5%
Katakana
ValueCountFrequency (%)
ト 1
25.0%
ッ 1
25.0%
ケ 1
25.0%
チ 1
25.0%

이용요금
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
131 
無料
 
7
大人（?25?以上）1,000ウォン　??大人（10人以上）800ウォン
 
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ウォン　??大人（10人以上）800ウォン
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

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

Length

2023-12-11T15:22:50.853632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:22:50.965766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 131
93.6%
無料 7
 
5.0%
大人（?25?以上）1,000ウォン 1
 
0.7%
大人（10人以上）800ウォン 1
 
0.7%

주차
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
128 
駐車可能
 
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駐車可能

Common Values

ValueCountFrequency (%)
<NA> 128
92.1%
駐車可能 11
 
7.9%

Length

2023-12-11T15:22:51.085720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:22:51.191567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 128
92.1%
駐車可能 11
 
7.9%

장애인 편의시설
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing136
Missing (%)97.8%
Memory size1.2 KiB
2023-12-11T15:22:51.352138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length16
Min length5

Characters and Unicode

Total characters48
Distinct characters27
Distinct categories3 ?
Distinct scripts4 ?
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車椅子貸出
2nd row障がい者????可能, 案?点字本具備
3rd row障がい者トイレ具備, 障がい者用エレベ?タ?具備
ValueCountFrequency (%)
車椅子貸出 1
20.0%
障がい者????可能 1
20.0%
案?点字本具備 1
20.0%
障がい者トイレ具備 1
20.0%
障がい者用エレベ?タ?具備 1
20.0%
2023-12-11T15:22:51.755772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 7
14.6%
障 3
 
6.2%
が 3
 
6.2%
い 3
 
6.2%
者 3
 
6.2%
備 3
 
6.2%
具 3
 
6.2%
2
 
4.2%
レ 2
 
4.2%
, 2
 
4.2%
Other values (17) 17
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37
77.1%
Other Punctuation 9
 
18.8%
Space Separator 2
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
障 3
 
8.1%
が 3
 
8.1%
い 3
 
8.1%
者 3
 
8.1%
備 3
 
8.1%
具 3
 
8.1%
レ 2
 
5.4%
本 1
 
2.7%
ベ 1
 
2.7%
エ 1
 
2.7%
Other values (14) 14
37.8%
Other Punctuation
ValueCountFrequency (%)
? 7
77.8%
, 2
 
22.2%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 24
50.0%
Common 11
22.9%
Katakana 7
 
14.6%
Hiragana 6
 
12.5%

Most frequent character per script

Han
ValueCountFrequency (%)
障 3
12.5%
者 3
12.5%
備 3
12.5%
具 3
12.5%
本 1
 
4.2%
用 1
 
4.2%
車 1
 
4.2%
字 1
 
4.2%
点 1
 
4.2%
案 1
 
4.2%
Other values (6) 6
25.0%
Katakana
ValueCountFrequency (%)
レ 2
28.6%
ベ 1
14.3%
エ 1
14.3%
イ 1
14.3%
ト 1
14.3%
タ 1
14.3%
Common
ValueCountFrequency (%)
? 7
63.6%
2
 
18.2%
, 2
 
18.2%
Hiragana
ValueCountFrequency (%)
が 3
50.0%
い 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 24
50.0%
ASCII 11
22.9%
Katakana 7
 
14.6%
Hiragana 6
 
12.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 7
63.6%
2
 
18.2%
, 2
 
18.2%
CJK
ValueCountFrequency (%)
障 3
12.5%
者 3
12.5%
備 3
12.5%
具 3
12.5%
本 1
 
4.2%
用 1
 
4.2%
車 1
 
4.2%
字 1
 
4.2%
点 1
 
4.2%
案 1
 
4.2%
Other values (6) 6
25.0%
Hiragana
ValueCountFrequency (%)
が 3
50.0%
い 3
50.0%
Katakana
ValueCountFrequency (%)
レ 2
28.6%
ベ 1
14.3%
エ 1
14.3%
イ 1
14.3%
ト 1
14.3%
タ 1
14.3%

체험안내
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing136
Missing (%)97.8%
Memory size1.2 KiB
2023-12-11T15:22:51.989404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length17
Mean length18.333333
Min length4

Characters and Unicode

Total characters55
Distinct characters35
Distinct categories3 ?
Distinct scripts4 ?
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?統衣씉試着, 守門?交代儀式??
2nd row杖鼓??
3rd row韓風文化マシル, ??撮影サ?ビス, 藁工芸試演, ?統文化遺産解?
ValueCountFrequency (%)
統衣씉試着 1
14.3%
守門?交代儀式 1
14.3%
杖鼓 1
14.3%
韓風文化マシル 1
14.3%
撮影サ?ビス 1
14.3%
藁工芸試演 1
14.3%
統文化遺産解 1
14.3%
2023-12-11T15:22:52.380239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 11
20.0%
, 4
 
7.3%
4
 
7.3%
文 2
 
3.6%
統 2
 
3.6%
化 2
 
3.6%
試 2
 
3.6%
演 1
 
1.8%
芸 1
 
1.8%
工 1
 
1.8%
Other values (25) 25
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36
65.5%
Other Punctuation 15
27.3%
Space Separator 4
 
7.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
文 2
 
5.6%
統 2
 
5.6%
化 2
 
5.6%
試 2
 
5.6%
演 1
 
2.8%
芸 1
 
2.8%
工 1
 
2.8%
シ 1
 
2.8%
ス 1
 
2.8%
ビ 1
 
2.8%
Other values (22) 22
61.1%
Other Punctuation
ValueCountFrequency (%)
? 11
73.3%
, 4
 
26.7%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 29
52.7%
Common 19
34.5%
Katakana 6
 
10.9%
Hangul 1
 
1.8%

Most frequent character per script

Han
ValueCountFrequency (%)
文 2
 
6.9%
統 2
 
6.9%
化 2
 
6.9%
試 2
 
6.9%
演 1
 
3.4%
芸 1
 
3.4%
工 1
 
3.4%
影 1
 
3.4%
撮 1
 
3.4%
遺 1
 
3.4%
Other values (15) 15
51.7%
Katakana
ValueCountFrequency (%)
シ 1
16.7%
ス 1
16.7%
ビ 1
16.7%
サ 1
16.7%
ル 1
16.7%
マ 1
16.7%
Common
ValueCountFrequency (%)
? 11
57.9%
, 4
 
21.1%
4
 
21.1%
Hangul
ValueCountFrequency (%)
씉 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 29
52.7%
ASCII 19
34.5%
Katakana 6
 
10.9%
Hangul 1
 
1.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 11
57.9%
, 4
 
21.1%
4
 
21.1%
CJK
ValueCountFrequency (%)
文 2
 
6.9%
統 2
 
6.9%
化 2
 
6.9%
試 2
 
6.9%
演 1
 
3.4%
芸 1
 
3.4%
工 1
 
3.4%
影 1
 
3.4%
撮 1
 
3.4%
遺 1
 
3.4%
Other values (15) 15
51.7%
Katakana
ValueCountFrequency (%)
シ 1
16.7%
ス 1
16.7%
ビ 1
16.7%
サ 1
16.7%
ル 1
16.7%
マ 1
16.7%
Hangul
ValueCountFrequency (%)
씉 1
100.0%

안내서비스
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing138
Missing (%)99.3%
Memory size1.2 KiB
2023-12-11T15:22:52.573902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters8
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多?語音?案?機具備
ValueCountFrequency (%)
多?語音?案?機具備 1
100.0%
2023-12-11T15:22:52.907935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 3
30.0%
多 1
 
10.0%
語 1
 
10.0%
音 1
 
10.0%
案 1
 
10.0%
機 1
 
10.0%
具 1
 
10.0%
備 1
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
70.0%
Other Punctuation 3
30.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
多 1
14.3%
語 1
14.3%
音 1
14.3%
案 1
14.3%
機 1
14.3%
具 1
14.3%
備 1
14.3%
Other Punctuation
ValueCountFrequency (%)
? 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 7
70.0%
Common 3
30.0%

Most frequent character per script

Han
ValueCountFrequency (%)
多 1
14.3%
語 1
14.3%
音 1
14.3%
案 1
14.3%
機 1
14.3%
具 1
14.3%
備 1
14.3%
Common
ValueCountFrequency (%)
? 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 7
70.0%
ASCII 3
30.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 3
100.0%
CJK
ValueCountFrequency (%)
多 1
14.3%
語 1
14.3%
音 1
14.3%
案 1
14.3%
機 1
14.3%
具 1
14.3%
備 1
14.3%

예약
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing136
Missing (%)97.8%
Memory size1.2 KiB
2023-12-11T15:22:53.138441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length18.666667
Min length8

Characters and Unicode

Total characters56
Distinct characters25
Distinct categories3 ?
Distinct scripts3 ?
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インタ?ネット, モバイル, 電話, 訪問予約購入可能
2nd rowオンライン, 電話予約購入, ?日購入可能
3rd row????予約可能
ValueCountFrequency (%)
インタ?ネット 1
12.5%
モバイル 1
12.5%
電話 1
12.5%
訪問予約購入可能 1
12.5%
オンライン 1
12.5%
電話予約購入 1
12.5%
日購入可能 1
12.5%
予約可能 1
12.5%
2023-12-11T15:22:53.819859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 6
 
10.7%
, 5
 
8.9%
5
 
8.9%
イ 3
 
5.4%
ン 3
 
5.4%
能 3
 
5.4%
可 3
 
5.4%
入 3
 
5.4%
購 3
 
5.4%
約 3
 
5.4%
Other values (15) 19
33.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 40
71.4%
Other Punctuation 11
 
19.6%
Space Separator 5
 
8.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
イ 3
 
7.5%
ン 3
 
7.5%
能 3
 
7.5%
可 3
 
7.5%
入 3
 
7.5%
購 3
 
7.5%
約 3
 
7.5%
予 3
 
7.5%
話 2
 
5.0%
電 2
 
5.0%
Other values (12) 12
30.0%
Other Punctuation
ValueCountFrequency (%)
? 6
54.5%
, 5
45.5%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 25
44.6%
Common 16
28.6%
Katakana 15
26.8%

Most frequent character per script

Katakana
ValueCountFrequency (%)
イ 3
20.0%
ン 3
20.0%
ル 1
 
6.7%
バ 1
 
6.7%
モ 1
 
6.7%
ト 1
 
6.7%
ッ 1
 
6.7%
ネ 1
 
6.7%
タ 1
 
6.7%
オ 1
 
6.7%
Han
ValueCountFrequency (%)
能 3
12.0%
可 3
12.0%
入 3
12.0%
購 3
12.0%
約 3
12.0%
予 3
12.0%
話 2
8.0%
電 2
8.0%
訪 1
 
4.0%
問 1
 
4.0%
Common
ValueCountFrequency (%)
? 6
37.5%
, 5
31.2%
5
31.2%

Most occurring blocks

ValueCountFrequency (%)
CJK 25
44.6%
ASCII 16
28.6%
Katakana 15
26.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 6
37.5%
, 5
31.2%
5
31.2%
Katakana
ValueCountFrequency (%)
イ 3
20.0%
ン 3
20.0%
ル 1
 
6.7%
バ 1
 
6.7%
モ 1
 
6.7%
ト 1
 
6.7%
ッ 1
 
6.7%
ネ 1
 
6.7%
タ 1
 
6.7%
オ 1
 
6.7%
CJK
ValueCountFrequency (%)
能 3
12.0%
可 3
12.0%
入 3
12.0%
購 3
12.0%
約 3
12.0%
予 3
12.0%
話 2
8.0%
電 2
8.0%
訪 1
 
4.0%
問 1
 
4.0%

Sample

상세고유순번관리번호명칭관련항목연계자원경도정보(127.XX)위도정보(36.XXX)이명칭개요시대분류주제분류지번주소도로명주소지역제공기관언어유형제작일유형형식전화번호지정현황휴무일이용시간이용요금주차장애인 편의시설체험안내안내서비스예약
0301JGS_000001??宮<NA>JGH_000370126.9765337.56502慶運宮, 貞陵洞行宮, 西宮昔の名?は慶運宮でしたが1907年から??宮と呼ばれるようなりました。 6万1500㎡の面積に大漢門、中和門、光明門、中和殿、浚明堂、昔御堂、石造殿、咸寧殿、??堂などの殿閣が?っています。<NA><NA><NA>ソウル特別市中?世宗大路99ソウル特別市中?世宗大路ソウル中???JPN2015-12-30DATAHTML02-771-9951史跡第124??週月曜日入場チケット販?および入場時間 09:00 ~ 20:00 퇴장시간 09:00 ~ 21:00大人（?25?以上）1,000ウォン　??大人（10人以上）800ウォン<NA>車椅子貸出?統衣씉試着, 守門?交代儀式??<NA><NA>
1302JGS_000002??宮重明殿<NA>JGH_000350126.9725237.56659<NA>1901年に建てられた重明殿は、今の??宮である慶運宮に含まれている建物で、接見所と宴?場、?書館として使用されていました。1907年に皇太子の嘉?の宴?が行われた場所で、乙巳?約が締結された悲運の場所でもあります。日本統治期の1915年から外?人に貸され、京城??部が利用しました。<NA><NA><NA>ソウル特別市中?貞洞ギル41-11ソウル特別市中?貞洞ギルソウル中???JPN2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2303JGS_000003옠丘壇<NA>JGH_000335126.9796937.56506<NA>옠丘壇は皇帝が天に祭祀を捧げる祭壇のことです。ここは朝鮮を引き?いだ大韓帝?の高宗皇帝が天に祭祀を捧げげ場所です。1897年に完成した옠丘壇は、?時、皇室最高の建築家だった沈宜錫設計しました。<NA><NA><NA>ソウル特別市中?小公路106ソウル特別市中?小公路ソウル中???JPN2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3304JGS_000004?ロシア公使館<NA>JGH_000355126.9714637.56825<NA>1890（高宗27）年にロシア人のサバティン（AISabatin）が設計したルネッサンス?式の建物です。本館は朝鮮??で?れ、現在は3階建ての塔だけが?っています。高宗が日本の武力の?迫を避けた露館播遷の現場として有名です。<NA><NA><NA>ソウル特別市中?貞洞ギル21-18 貞洞公園ソウル特別市中?貞洞ギルソウル中???JPN2015-12-30DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4305JGS_000005貞洞第一??<NA>JGH_000367126.9723637.56542<NA>貞洞一番??は1895（高宗32）年に着工し1897（光武1）年10月に竣工したプロテスタント??の??堂です。<NA><NA><NA>ソウル特別市中?貞洞ギル46 貞洞??ソウル特別市中?貞洞ギルソウル中???JPN2015-12-30DATAHTML<NA><NA><NA><NA><NA>駐車可能<NA><NA><NA><NA>
5306JGS_000006培材?堂?史博物館(?培材?堂東館)<NA>JGH_000368126.9726237.56378<NA>この建物は、1916年に竣工し培材中·高等?校が1984年に江東?に移?するまで校舍として使用されていました。培材?堂は宣?師アッペンツェラ?（Henry Gerhard Appenzeller）が1885年8月に設立した?校で、最初は周?の民家を買い取って校舍として使用しました。<NA><NA><NA>ソウル特別市中?西小門路11ギル19ソウル特別市中?西小門路ソウル中???JPN2015-12-30DATAHTML<NA>ソウル特別市記念物第16??週月曜日, 休日?日10:00 ~ 17:00無料<NA><NA><NA><NA><NA>
6307JGS_000007ソウル市立美術館<NA>JGH_000313126.9737737.56402<NA>ここは育英公院とドイツ公使館、京城裁判所があった場所です。解放後は大韓民?の最高裁判所の建物となり、2002年にソウル市立美術館として開館しました。<NA><NA><NA>ソウル特別市中???宮ギル61ソウル特別市中???宮ギルソウル中???JPN2015-12-30DATAHTML02-2124-8800登?文化財第237??週月曜日, 1月1日<NA><NA>駐車可能<NA><NA><NA><NA>
7308JGS_000008慶運宮養怡齋<NA>JGH_000361126.9754437.56694<NA>大火災で?けた慶運宮（??宮）を修築する際に建てられた建物で、1905年に完成しました。大韓帝?の皇族や貴族の近代式?育を?っていた場所で、現在は大韓聖公?の主?執務室として使われています。<NA><NA><NA>ソウル特別市中?世宗大路21ギル15ソウル特別市中?世宗大路ソウル中???JPN2015-12-30DATAHTML<NA>登?文化財第267?<NA><NA><NA><NA><NA><NA><NA><NA>
8309JGS_000009?新?日報別館<NA>JGH_000354126.9721737.56619<NA>1930年代に地下1階、地上2階で建築された?筋コンクリ?トの建物で、アメリカの企業であるシンガ?ミシン社の韓?支部として使われた後に、1963年に新?日報が買い取り、1975年3、4階を?築して別館として使用しました。新?日報は1980年、新軍部の言論統?合で京?新聞に吸?·統合されました。<NA><NA><NA>ソウル特別市中?貞洞ギル33ソウル特別市中?貞洞ギルソウル中???JPN2015-12-30DATAHTML<NA>登?文化財第402?<NA><NA><NA><NA><NA><NA><NA><NA>
9310JGS_000010救世軍中央?館<NA>JGH_000352126.973637.56761<NA>救世軍中央?館は救世軍の士官養成と宣?活動、社?事業の?点として使用するために1928年に竣工されました。<NA><NA><NA>ソウル特別市中???宮ギル130ソウル特別市中???宮ギルソウル中???JPN2015-12-30DATAHTML02-720-9494ソウル特別市記念物第20?<NA><NA><NA><NA><NA><NA><NA><NA>
상세고유순번관리번호명칭관련항목연계자원경도정보(127.XX)위도정보(36.XXX)이명칭개요시대분류주제분류지번주소도로명주소지역제공기관언어유형제작일유형형식전화번호지정현황휴무일이용시간이용요금주차장애인 편의시설체험안내안내서비스예약
129676JGS_000131燃燈（ヨンドゥン）遊び<NA><NA>126.9818737.568862<NA>??に福を祈る燃燈遊び<NA><NA><NA>ソウル特別市 ??川<NA>ソウル特別市JPN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
130681JGS_000132石合?<NA><NA>126.98433937.568659<NA>朝鮮の好?的な石合?<NA><NA><NA>ソウル特別市 ??川<NA>ソウル特別市JPN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
131686JGS_000133??川で脚戱(テッキョン)<NA><NA>127.00124237.569457<NA>朝鮮の最後のテッキョン修練の敷地と、仁寺洞(インサドン)テッキョンバトル<NA><NA><NA>ソウル特別市 ??川<NA>ソウル特別市JPN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
132691JGS_000134首善全?(スソンジョンド)<NA><NA>126.9848937.568552<NA>漢陽を描いた首善全?<NA><NA><NA>ソウル特別市鍾路?<NA>ソウル特別市JPN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
133696JGS_000135正祖大王稜行班次?（ヌンヘンバンチャド）<NA><NA>126.9852737.568509<NA>悲運に死んだ思悼世子(サドセジャ)の墓に??する正祖大王の行列<NA><NA><NA>ソウル特別市鍾路?<NA>ソウル特別市JPN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
134701JGS_000136英祖御筆, 濬川歌<NA><NA>127.00968237.569826<NA>英祖の整備工事にたいする喜びと蔡?恭の詩<NA><NA><NA>ソウル特別市鍾路?<NA>ソウル特別市JPN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
135706JGS_000137五間水門（オガンスムン）<NA><NA>127.01061437.569765<NA>??川の水路が出る漢陽の城壁、五間水門<NA><NA><NA>ソウル特別市鍾路?<NA>ソウル特別市JPN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
136711JGS_000138濬川圖<NA><NA>127.0096837.569675<NA>英祖の五間水門で濬川工事を督?する<NA><NA><NA>ソウル特別市中?<NA>ソウル特別市JPN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
137716JGS_000139??川の昔の姿の壁?<NA><NA>127.01377437.569842<NA>??川の昔の姿<NA><NA><NA>ソウル特別市鍾路?<NA>ソウル特別市JPN<NA>DATAHTML<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
138319JGS_000019セシル劇場<NA>JGH_001147126.9759937.56673<NA>1976年に大韓聖公?大聖堂の付?建物に開館した小劇場です。大韓民?演劇祭が1回から5回まで開催された小劇場で、1970年代の小劇場ブ?ムの中心でした。<NA><NA><NA>ソウル特別市中?世宗大路19ギル16ソウル特別市中?世宗大路ソウル中???JPN2015-12-30DATAHTML02-742-7601<NA><NA><NA><NA><NA><NA><NA><NA><NA>