Overview

Dataset statistics

Number of variables9
Number of observations541
Missing cells123
Missing cells (%)2.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory38.2 KiB
Average record size in memory72.2 B

Variable types

Categorical4
Text5

Dataset

Description전라남도 도 문화재 지정 현황(도 지정, 도 문화재자료 등)에 대한 내용으로 문화재명, 종목, 년대, 시군 등을 알 수 있는 내용입니다.
Author전라남도
URLhttps://www.data.go.kr/data/15069199/fileData.do

Alerts

종목 is highly overall correlated with 년대_시대 and 1 other fieldsHigh correlation
년대_시대 is highly overall correlated with 종목High correlation
종교 is highly overall correlated with 종목High correlation
수량_면적 has 49 (9.1%) missing valuesMissing
한자명 has 23 (4.3%) missing valuesMissing
분야(소분류) has 51 (9.4%) missing valuesMissing
문화재명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:58:46.095409
Analysis finished2023-12-12 04:58:47.751642
Duration1.66 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

종목
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
시도유형문화재
251 
시도기념물
195 
시도무형문화재
53 
시도민속문화재
42 

Length

Max length7
Median length7
Mean length6.2791128
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
시도유형문화재 251
46.4%
시도기념물 195
36.0%
시도무형문화재 53
 
9.8%
시도민속문화재 42
 
7.8%

Length

2023-12-12T13:58:47.885696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:58:48.016344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시도유형문화재 251
46.4%
시도기념물 195
36.0%
시도무형문화재 53
 
9.8%
시도민속문화재 42
 
7.8%

지정번호
Text

Distinct331
Distinct (%)61.2%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2023-12-12T13:58:48.311433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.5748614
Min length3

Characters and Unicode

Total characters2475
Distinct characters12
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

Unique171 ?
Unique (%)31.6%

Sample

1st row제5호
2nd row제10호
3rd row제12호
4th row제13호
5th row제17호
ValueCountFrequency (%)
제49호 4
 
0.7%
제43호 4
 
0.7%
제45호 4
 
0.7%
제19호 4
 
0.7%
제20호 4
 
0.7%
제22호 4
 
0.7%
제46호 4
 
0.7%
제28호 4
 
0.7%
제40호 4
 
0.7%
제35호 4
 
0.7%
Other values (321) 501
92.6%
2023-12-12T13:58:48.879988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 541
21.9%
호 541
21.9%
1 280
11.3%
2 248
10.0%
3 174
 
7.0%
4 123
 
5.0%
5 113
 
4.6%
0 97
 
3.9%
8 92
 
3.7%
6 90
 
3.6%
Other values (2) 176
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1393
56.3%
Other Letter 1082
43.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 280
20.1%
2 248
17.8%
3 174
12.5%
4 123
8.8%
5 113
8.1%
0 97
 
7.0%
8 92
 
6.6%
6 90
 
6.5%
9 88
 
6.3%
7 88
 
6.3%
Other Letter
ValueCountFrequency (%)
제 541
50.0%
호 541
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1393
56.3%
Hangul 1082
43.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 280
20.1%
2 248
17.8%
3 174
12.5%
4 123
8.8%
5 113
8.1%
0 97
 
7.0%
8 92
 
6.6%
6 90
 
6.5%
9 88
 
6.3%
7 88
 
6.3%
Hangul
ValueCountFrequency (%)
제 541
50.0%
호 541
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1393
56.3%
Hangul 1082
43.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 541
50.0%
호 541
50.0%
ASCII
ValueCountFrequency (%)
1 280
20.1%
2 248
17.8%
3 174
12.5%
4 123
8.8%
5 113
8.1%
0 97
 
7.0%
8 92
 
6.6%
6 90
 
6.5%
9 88
 
6.3%
7 88
 
6.3%

문화재명
Text

UNIQUE 

Distinct541
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2023-12-12T13:58:49.246446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length9.0055453
Min length2

Characters and Unicode

Total characters4872
Distinct characters336
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique541 ?
Unique (%)100.0%

Sample

1st row광양성황리삼층석탑
2nd row진도상만리오층석탑
3rd row구례사도리삼층석탑
4th row장성원덕리미륵석불
5th row용장사석불좌상
ValueCountFrequency (%)
보성 11
 
1.4%
장흥 10
 
1.2%
해남 10
 
1.2%
목조 9
 
1.1%
여수 9
 
1.1%
및 9
 
1.1%
곡성 9
 
1.1%
화순 7
 
0.9%
담양 7
 
0.9%
복장유물 7
 
0.9%
Other values (644) 723
89.1%
2023-12-12T13:58:49.770341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
270
 
5.5%
사 218
 
4.5%
장 130
 
2.7%
리 119
 
2.4%
상 99
 
2.0%
성 94
 
1.9%
고 92
 
1.9%
석 84
 
1.7%
도 84
 
1.7%
흥 74
 
1.5%
Other values (326) 3608
74.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4588
94.2%
Space Separator 270
 
5.5%
Other Punctuation 4
 
0.1%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%
Decimal Number 2
 
< 0.1%
Final Punctuation 1
 
< 0.1%
Initial Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 218
 
4.8%
장 130
 
2.8%
리 119
 
2.6%
상 99
 
2.2%
성 94
 
2.0%
고 92
 
2.0%
석 84
 
1.8%
도 84
 
1.8%
흥 74
 
1.6%
영 74
 
1.6%
Other values (316) 3520
76.7%
Other Punctuation
ValueCountFrequency (%)
· 2
50.0%
. 1
25.0%
, 1
25.0%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
270
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4587
94.2%
Common 284
 
5.8%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 218
 
4.8%
장 130
 
2.8%
리 119
 
2.6%
상 99
 
2.2%
성 94
 
2.0%
고 92
 
2.0%
석 84
 
1.8%
도 84
 
1.8%
흥 74
 
1.6%
영 74
 
1.6%
Other values (315) 3519
76.7%
Common
ValueCountFrequency (%)
270
95.1%
( 3
 
1.1%
) 3
 
1.1%
· 2
 
0.7%
. 1
 
0.4%
2 1
 
0.4%
, 1
 
0.4%
1 1
 
0.4%
’ 1
 
0.4%
‘ 1
 
0.4%
Han
ValueCountFrequency (%)
王 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4586
94.1%
ASCII 280
 
5.7%
None 2
 
< 0.1%
Punctuation 2
 
< 0.1%
CJK 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
270
96.4%
( 3
 
1.1%
) 3
 
1.1%
. 1
 
0.4%
2 1
 
0.4%
, 1
 
0.4%
1 1
 
0.4%
Hangul
ValueCountFrequency (%)
사 218
 
4.8%
장 130
 
2.8%
리 119
 
2.6%
상 99
 
2.2%
성 94
 
2.0%
고 92
 
2.0%
석 84
 
1.8%
도 84
 
1.8%
흥 74
 
1.6%
영 74
 
1.6%
Other values (314) 3518
76.7%
None
ValueCountFrequency (%)
· 2
100.0%
Punctuation
ValueCountFrequency (%)
’ 1
50.0%
‘ 1
50.0%
CJK
ValueCountFrequency (%)
王 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

년대_시대
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
조선시대
233 
<NA>
188 
고려시대
68 
선사시대
 
12
삼국시대
 
10
Other values (7)
30 

Length

Max length6
Median length4
Mean length4.0184843
Min length2

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
조선시대 233
43.1%
<NA> 188
34.8%
고려시대 68
 
12.6%
선사시대 12
 
2.2%
삼국시대 10
 
1.8%
일제강점기 8
 
1.5%
백제시대 7
 
1.3%
통일신라시대 6
 
1.1%
기타 5
 
0.9%
대한제국 2
 
0.4%
Other values (2) 2
 
0.4%

Length

2023-12-12T13:58:49.946039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
조선시대 233
43.1%
na 188
34.8%
고려시대 68
 
12.6%
선사시대 12
 
2.2%
삼국시대 10
 
1.8%
일제강점기 8
 
1.5%
백제시대 7
 
1.3%
통일신라시대 6
 
1.1%
기타 5
 
0.9%
대한제국 2
 
0.4%
Other values (2) 2
 
0.4%

수량_면적
Text

MISSING 

Distinct221
Distinct (%)44.9%
Missing49
Missing (%)9.1%
Memory size4.4 KiB
2023-12-12T13:58:50.247929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length2
Mean length5.2743902
Min length1

Characters and Unicode

Total characters2595
Distinct characters138
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique196 ?
Unique (%)39.8%

Sample

1st row1기
2nd row1기
3rd row1기
4th row1구
5th row1구
ValueCountFrequency (%)
1기 57
 
9.9%
일곽 42
 
7.3%
일원 41
 
7.1%
1동 40
 
6.9%
1구 40
 
6.9%
1점 13
 
2.3%
2기 12
 
2.1%
1책 9
 
1.6%
1폭 6
 
1.0%
3구 6
 
1.0%
Other values (266) 310
53.8%
2023-12-12T13:58:50.840612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 317
 
12.2%
일 123
 
4.7%
2 121
 
4.7%
터 111
 
4.3%
미 111
 
4.3%
기 104
 
4.0%
, 101
 
3.9%
제 100
 
3.9%
곱 97
 
3.7%
3 88
 
3.4%
Other values (128) 1322
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1269
48.9%
Decimal Number 978
37.7%
Other Punctuation 118
 
4.5%
Space Separator 86
 
3.3%
Open Punctuation 56
 
2.2%
Close Punctuation 56
 
2.2%
Connector Punctuation 23
 
0.9%
Lowercase Letter 8
 
0.3%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 123
 
9.7%
터 111
 
8.7%
미 111
 
8.7%
기 104
 
8.2%
제 100
 
7.9%
곱 97
 
7.6%
원 73
 
5.8%
구 62
 
4.9%
동 53
 
4.2%
곽 43
 
3.4%
Other values (109) 392
30.9%
Decimal Number
ValueCountFrequency (%)
1 317
32.4%
2 121
 
12.4%
3 88
 
9.0%
4 78
 
8.0%
6 68
 
7.0%
0 67
 
6.9%
8 65
 
6.6%
5 63
 
6.4%
9 60
 
6.1%
7 51
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 101
85.6%
. 17
 
14.4%
Lowercase Letter
ValueCountFrequency (%)
m 5
62.5%
x 3
37.5%
Space Separator
ValueCountFrequency (%)
86
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 23
100.0%
Other Symbol
ValueCountFrequency (%)
㎞ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1318
50.8%
Hangul 1262
48.6%
Latin 8
 
0.3%
Han 7
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 123
 
9.7%
터 111
 
8.8%
미 111
 
8.8%
기 104
 
8.2%
제 100
 
7.9%
곱 97
 
7.7%
원 73
 
5.8%
구 62
 
4.9%
동 53
 
4.2%
곽 43
 
3.4%
Other values (106) 385
30.5%
Common
ValueCountFrequency (%)
1 317
24.1%
2 121
 
9.2%
, 101
 
7.7%
3 88
 
6.7%
86
 
6.5%
4 78
 
5.9%
6 68
 
5.2%
0 67
 
5.1%
8 65
 
4.9%
5 63
 
4.8%
Other values (7) 264
20.0%
Han
ValueCountFrequency (%)
軀 3
42.9%
棟 3
42.9%
株 1
 
14.3%
Latin
ValueCountFrequency (%)
m 5
62.5%
x 3
37.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1325
51.1%
Hangul 1262
48.6%
CJK 7
 
0.3%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 317
23.9%
2 121
 
9.1%
, 101
 
7.6%
3 88
 
6.6%
86
 
6.5%
4 78
 
5.9%
6 68
 
5.1%
0 67
 
5.1%
8 65
 
4.9%
5 63
 
4.8%
Other values (8) 271
20.5%
Hangul
ValueCountFrequency (%)
일 123
 
9.7%
터 111
 
8.8%
미 111
 
8.8%
기 104
 
8.2%
제 100
 
7.9%
곱 97
 
7.7%
원 73
 
5.8%
구 62
 
4.9%
동 53
 
4.2%
곽 43
 
3.4%
Other values (106) 385
30.5%
CJK
ValueCountFrequency (%)
軀 3
42.9%
棟 3
42.9%
株 1
 
14.3%
CJK Compat
ValueCountFrequency (%)
㎞ 1
100.0%

시군구
Categorical

Distinct23
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
순천시
43 
장흥군
43 
영암군
39 
화순군
39 
나주시
37 
Other values (18)
340 

Length

Max length11
Median length3
Mean length3.0443623
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광양시
2nd row진도군
3rd row구례군
4th row장성군
5th row진도군

Common Values

ValueCountFrequency (%)
순천시 43
 
7.9%
장흥군 43
 
7.9%
영암군 39
 
7.2%
화순군 39
 
7.2%
나주시 37
 
6.8%
담양군 37
 
6.8%
고흥군 35
 
6.5%
해남군 33
 
6.1%
강진군 29
 
5.4%
영광군 27
 
5.0%
Other values (13) 179
33.1%

Length

2023-12-12T13:58:51.061484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
순천시 43
 
7.9%
장흥군 43
 
7.9%
영암군 39
 
7.2%
화순군 39
 
7.2%
나주시 37
 
6.8%
담양군 37
 
6.8%
고흥군 35
 
6.4%
해남군 33
 
6.1%
강진군 29
 
5.3%
영광군 27
 
5.0%
Other values (14) 182
33.5%

한자명
Text

MISSING 

Distinct518
Distinct (%)100.0%
Missing23
Missing (%)4.3%
Memory size4.4 KiB
2023-12-12T13:58:51.363978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length8.957529
Min length2

Characters and Unicode

Total characters4640
Distinct characters840
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique518 ?
Unique (%)100.0%

Sample

1st row光陽城隍里三層石塔
2nd row珍島上萬里五層石塔
3rd row求禮沙圖里三層石塔
4th row長城院德里彌勒石佛
5th row龍蔣寺石佛坐像
ValueCountFrequency (%)
木造 9
 
1.2%
長興 9
 
1.2%
和順 9
 
1.2%
및 8
 
1.0%
麗水 8
 
1.0%
羅州 8
 
1.0%
谷城 8
 
1.0%
寶城 8
 
1.0%
靈光 7
 
0.9%
長城 6
 
0.8%
Other values (632) 702
89.8%
2023-12-12T13:58:51.916658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
269
 
5.8%
寺 133
 
2.9%
里 100
 
2.2%
城 81
 
1.7%
像 76
 
1.6%
石 74
 
1.6%
興 68
 
1.5%
長 54
 
1.2%
山 54
 
1.2%
靈 51
 
1.1%
Other values (830) 3680
79.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4357
93.9%
Space Separator 269
 
5.8%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%
Other Punctuation 4
 
0.1%
Final Punctuation 1
 
< 0.1%
Initial Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
寺 133
 
3.1%
里 100
 
2.3%
城 81
 
1.9%
像 76
 
1.7%
石 74
 
1.7%
興 68
 
1.6%
長 54
 
1.2%
山 54
 
1.2%
靈 51
 
1.2%
順 49
 
1.1%
Other values (822) 3617
83.0%
Other Punctuation
ValueCountFrequency (%)
· 2
50.0%
. 1
25.0%
, 1
25.0%
Space Separator
ValueCountFrequency (%)
269
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 4082
88.0%
Common 283
 
6.1%
Hangul 275
 
5.9%

Most frequent character per script

Han
ValueCountFrequency (%)
寺 133
 
3.3%
里 100
 
2.4%
城 81
 
2.0%
像 76
 
1.9%
石 74
 
1.8%
興 68
 
1.7%
長 54
 
1.3%
山 54
 
1.3%
靈 51
 
1.2%
順 49
 
1.2%
Other values (712) 3342
81.9%
Hangul
ValueCountFrequency (%)
및 22
 
8.0%
무 15
 
5.5%
리 13
 
4.7%
나 12
 
4.4%
래 10
 
3.6%
노 9
 
3.3%
이 8
 
2.9%
들 7
 
2.5%
생 7
 
2.5%
의 6
 
2.2%
Other values (100) 166
60.4%
Common
ValueCountFrequency (%)
269
95.1%
) 4
 
1.4%
( 4
 
1.4%
· 2
 
0.7%
. 1
 
0.4%
, 1
 
0.4%
’ 1
 
0.4%
‘ 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
CJK 3882
83.7%
ASCII 279
 
6.0%
Hangul 274
 
5.9%
CJK Compat Ideographs 200
 
4.3%
None 2
 
< 0.1%
Punctuation 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
269
96.4%
) 4
 
1.4%
( 4
 
1.4%
. 1
 
0.4%
, 1
 
0.4%
CJK
ValueCountFrequency (%)
寺 133
 
3.4%
里 100
 
2.6%
城 81
 
2.1%
像 76
 
2.0%
石 74
 
1.9%
興 68
 
1.8%
長 54
 
1.4%
山 54
 
1.4%
順 49
 
1.3%
佛 46
 
1.2%
Other values (675) 3147
81.1%
CJK Compat Ideographs
ValueCountFrequency (%)
靈 51
25.5%
羅 34
17.0%
龍 13
 
6.5%
立 12
 
6.0%
李 11
 
5.5%
麗 10
 
5.0%
金 8
 
4.0%
樂 8
 
4.0%
宅 7
 
3.5%
烈 6
 
3.0%
Other values (27) 40
20.0%
Hangul
ValueCountFrequency (%)
및 22
 
8.0%
무 15
 
5.5%
리 13
 
4.7%
나 12
 
4.4%
래 10
 
3.6%
노 9
 
3.3%
이 8
 
2.9%
들 7
 
2.6%
생 7
 
2.6%
의 6
 
2.2%
Other values (99) 165
60.2%
None
ValueCountFrequency (%)
· 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%
Punctuation
ValueCountFrequency (%)
’ 1
50.0%
‘ 1
50.0%

분야(소분류)
Text

MISSING 

Distinct82
Distinct (%)16.7%
Missing51
Missing (%)9.4%
Memory size4.4 KiB
2023-12-12T13:58:52.254699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.5367347
Min length1

Characters and Unicode

Total characters1733
Distinct characters108
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)5.9%

Sample

1st row석탑
2nd row석탑
3rd row석탑
4th row석불(부동산)
5th row석불(부동산)
ValueCountFrequency (%)
석비 29
 
5.8%
식물 26
 
5.2%
성지(성곽 24
 
4.8%
고분 21
 
4.2%
가옥 21
 
4.2%
사묘,제단 21
 
4.2%
사찰건축 20
 
4.0%
서적류 20
 
4.0%
향교 18
 
3.6%
음악 18
 
3.6%
Other values (74) 278
56.0%
2023-12-12T13:58:52.680160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 88
 
5.1%
) 88
 
5.1%
석 86
 
5.0%
류 65
 
3.8%
지 63
 
3.6%
동 54
 
3.1%
불 54
 
3.1%
사 49
 
2.8%
성 48
 
2.8%
부 48
 
2.8%
Other values (98) 1090
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1509
87.1%
Open Punctuation 88
 
5.1%
Close Punctuation 88
 
5.1%
Other Punctuation 42
 
2.4%
Space Separator 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
석 86
 
5.7%
류 65
 
4.3%
지 63
 
4.2%
동 54
 
3.6%
불 54
 
3.6%
사 49
 
3.2%
성 48
 
3.2%
부 48
 
3.2%
산 47
 
3.1%
묘 44
 
2.9%
Other values (92) 951
63.0%
Other Punctuation
ValueCountFrequency (%)
, 24
57.1%
. 17
40.5%
· 1
 
2.4%
Open Punctuation
ValueCountFrequency (%)
( 88
100.0%
Close Punctuation
ValueCountFrequency (%)
) 88
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1509
87.1%
Common 224
 
12.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
석 86
 
5.7%
류 65
 
4.3%
지 63
 
4.2%
동 54
 
3.6%
불 54
 
3.6%
사 49
 
3.2%
성 48
 
3.2%
부 48
 
3.2%
산 47
 
3.1%
묘 44
 
2.9%
Other values (92) 951
63.0%
Common
ValueCountFrequency (%)
( 88
39.3%
) 88
39.3%
, 24
 
10.7%
. 17
 
7.6%
6
 
2.7%
· 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1509
87.1%
ASCII 223
 
12.9%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 88
39.5%
) 88
39.5%
, 24
 
10.8%
. 17
 
7.6%
6
 
2.7%
Hangul
ValueCountFrequency (%)
석 86
 
5.7%
류 65
 
4.3%
지 63
 
4.2%
동 54
 
3.6%
불 54
 
3.6%
사 49
 
3.2%
성 48
 
3.2%
부 48
 
3.2%
산 47
 
3.1%
묘 44
 
2.9%
Other values (92) 951
63.0%
None
ValueCountFrequency (%)
· 1
100.0%

종교
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
<NA>
342 
불교
132 
기타
63 
유교
 
4

Length

Max length4
Median length4
Mean length3.2643253
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 342
63.2%
불교 132
 
24.4%
기타 63
 
11.6%
유교 4
 
0.7%

Length

2023-12-12T13:58:52.856334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:58:53.021725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 342
63.2%
불교 132
 
24.4%
기타 63
 
11.6%
유교 4
 
0.7%

Correlations

2023-12-12T13:58:53.135020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종목년대_시대시군구분야(소분류)종교
종목1.0000.7420.3850.9970.585
년대_시대0.7421.0000.3410.8960.432
시군구0.3850.3411.0000.6440.387
분야(소분류)0.9970.8960.6441.0000.989
종교0.5850.4320.3870.9891.000
2023-12-12T13:58:53.254549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종교종목년대_시대시군구
종교1.0000.5950.3180.206
종목0.5951.0000.5510.210
년대_시대0.3180.5511.0000.107
시군구0.2060.2100.1071.000
2023-12-12T13:58:53.364995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종목년대_시대시군구종교
종목1.0000.5510.2100.595
년대_시대0.5511.0000.1070.318
시군구0.2100.1071.0000.206
종교0.5950.3180.2061.000

Missing values

2023-12-12T13:58:47.341009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:58:47.549808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T13:58:47.678145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

종목지정번호문화재명년대_시대수량_면적시군구한자명분야(소분류)종교
0시도유형문화재제5호광양성황리삼층석탑고려시대1기광양시光陽城隍里三層石塔석탑불교
1시도유형문화재제10호진도상만리오층석탑고려시대1기진도군珍島上萬里五層石塔석탑불교
2시도유형문화재제12호구례사도리삼층석탑고려시대1기구례군求禮沙圖里三層石塔석탑불교
3시도유형문화재제13호장성원덕리미륵석불고려시대1구장성군長城院德里彌勒石佛석불(부동산)불교
4시도유형문화재제17호용장사석불좌상고려시대1구진도군龍蔣寺石佛坐像석불(부동산)불교
5시도유형문화재제18호자정국사사리함고려시대1개순천시慈精國師舍利函공예류불교
6시도유형문화재제19호능견난사고려시대1착순천시能見難思유물,유품불교
7시도유형문화재제20호선암사금동향로고려시대1점순천시仙岩寺金銅香爐공예류불교
8시도유형문화재제21호전도선국사직인통고려시대1개순천시傳道詵國師職印筒공예류불교
9시도유형문화재제22호송광사금강저고려시대1개순천시松廣寺金剛杵공예류불교
종목지정번호문화재명년대_시대수량_면적시군구한자명분야(소분류)종교
531시도민속문화재제41호창평장전이씨고택백제시대1,802제곱미터담양군昌平 長田 李氏古宅고가<NA>
532시도민속문화재제42호창평춘강고정주고택<NA>2,314제곱미터담양군昌平 春崗 高鼎柱古宅고가<NA>
533시도민속문화재제43호장흥호계리별신제와동계문서<NA>동계문서 등 18건, 별신제장흥군長興 虎溪里 別神祭와 洞契文書<NA><NA>
534시도민속문화재제44호여수 영당지<NA>909제곱미터여수시麗水 影堂址<NA><NA>
535시도민속문화재제45호여수 악공청 관련자료일괄<NA>4점여수시麗水 樂工廳 關聯資料一括<NA><NA>
536시도민속문화재제46호장흥 방촌리 근암고택백제시대887제곱미터장흥군長興 傍村里 勤庵古宅<NA><NA>
537시도민속문화재제47호강진 효정재<NA>1강진군康津 孝亭齋고가<NA>
538시도민속문화재제48호보성 충의당일제강점기3,293제곱미터보성군寶城 忠義堂가옥<NA>
539시도민속문화재제49호장흥 백수장 별묘조선시대면 1칸, 측면 1칸, 맞배지붕_1동 9.61제곱미터장흥군長興 白壽長 別廟민속자료<NA>
540시도민속문화재제50호장성 추원재<NA>667제곱미터장성군長城 追遠齋목조문화재<NA>