Overview

Dataset statistics

Number of variables18
Number of observations152
Missing cells303
Missing cells (%)11.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.7 KiB
Average record size in memory145.9 B

Variable types

Numeric1
Categorical9
Text7
DateTime1

Dataset

Description서울특별시 서대문구 관내에 보호되고 있는 문화재 현황(명칭, 지정일, 분류, 수량 등)에 대한 데이터를 제공합니다.
Author서울특별시 서대문구
URLhttps://www.data.go.kr/data/3080309/fileData.do

Alerts

소재시도 has constant value ""Constant
순번 is highly overall correlated with 종목 and 2 other fieldsHigh correlation
종목 is highly overall correlated with 순번 and 5 other fieldsHigh correlation
분야(소분류) is highly overall correlated with 종목 and 4 other fieldsHigh correlation
재료 is highly overall correlated with 순번 and 7 other fieldsHigh correlation
형식-형태 is highly overall correlated with 순번 and 6 other fieldsHigh correlation
종교 is highly overall correlated with 재료 and 1 other fieldsHigh correlation
년대-시대 is highly overall correlated with 종목 and 4 other fieldsHigh correlation
시군구 is highly overall correlated with 재료High correlation
부동산-동산 is highly overall correlated with 종목 and 4 other fieldsHigh correlation
시군구 is highly imbalanced (87.6%)Imbalance
부동산-동산 is highly imbalanced (59.5%)Imbalance
구조 has 110 (72.4%) missing valuesMissing
규격-크기 has 72 (47.4%) missing valuesMissing
수량-면적 has 2 (1.3%) missing valuesMissing
(제)작자 has 119 (78.3%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-13 00:04:56.010113
Analysis finished2023-12-13 00:04:58.077168
Duration2.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct152
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.5
Minimum1
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T09:04:58.131498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.55
Q138.75
median76.5
Q3114.25
95-th percentile144.45
Maximum152
Range151
Interquartile range (IQR)75.5

Descriptive statistics

Standard deviation44.022721
Coefficient of variation (CV)0.57546041
Kurtosis-1.2
Mean76.5
Median Absolute Deviation (MAD)38
Skewness0
Sum11628
Variance1938
MonotonicityStrictly increasing
2023-12-13T09:04:58.239270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
106 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
104 1
 
0.7%
105 1
 
0.7%
107 1
 
0.7%
Other values (142) 142
93.4%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
152 1
0.7%
151 1
0.7%
150 1
0.7%
149 1
0.7%
148 1
0.7%
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%
143 1
0.7%

종목
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
보물
51 
시도유형문화재
39 
국가등록문화재
37 
국보
6 
사적
6 
Other values (5)
13 

Length

Max length7
Median length7
Mean length4.8355263
Min length2

Unique

Unique3 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
보물 51
33.6%
시도유형문화재 39
25.7%
국가등록문화재 37
24.3%
국보 6
 
3.9%
사적 6
 
3.9%
문화재자료 6
 
3.9%
국가민속문화재 4
 
2.6%
국가무형문화재 1
 
0.7%
시도무형문화재 1
 
0.7%
시도기념물 1
 
0.7%

Length

2023-12-13T09:04:58.341350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:04:58.439646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보물 51
33.6%
시도유형문화재 39
25.7%
국가등록문화재 37
24.3%
국보 6
 
3.9%
사적 6
 
3.9%
문화재자료 6
 
3.9%
국가민속문화재 4
 
2.6%
국가무형문화재 1
 
0.7%
시도무형문화재 1
 
0.7%
시도기념물 1
 
0.7%

지정번호
Text

Distinct149
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T09:04:58.696990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.2631579
Min length4

Characters and Unicode

Total characters800
Distinct characters13
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

Unique146 ?
Unique (%)96.1%

Sample

1st row제107호
2nd row제202호
3rd row제250호
4th row제251호
5th row제306-3호
ValueCountFrequency (%)
제33호 2
 
1.3%
제326호 2
 
1.3%
제324호 2
 
1.3%
제770호 1
 
0.7%
제712호 1
 
0.7%
제78호 1
 
0.7%
제473호 1
 
0.7%
제107호 1
 
0.7%
제476호 1
 
0.7%
제466호 1
 
0.7%
Other values (139) 139
91.4%
2023-12-13T09:04:59.047574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 152
19.0%
호 152
19.0%
1 76
9.5%
4 65
8.1%
5 51
 
6.4%
2 50
 
6.2%
6 48
 
6.0%
3 47
 
5.9%
7 39
 
4.9%
0 38
 
4.8%
Other values (3) 82
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 477
59.6%
Other Letter 304
38.0%
Dash Punctuation 19
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 76
15.9%
4 65
13.6%
5 51
10.7%
2 50
10.5%
6 48
10.1%
3 47
9.9%
7 39
8.2%
0 38
8.0%
8 34
7.1%
9 29
 
6.1%
Other Letter
ValueCountFrequency (%)
제 152
50.0%
호 152
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 496
62.0%
Hangul 304
38.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 76
15.3%
4 65
13.1%
5 51
10.3%
2 50
10.1%
6 48
9.7%
3 47
9.5%
7 39
7.9%
0 38
7.7%
8 34
6.9%
9 29
 
5.8%
Hangul
ValueCountFrequency (%)
제 152
50.0%
호 152
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 496
62.0%
Hangul 304
38.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 152
50.0%
호 152
50.0%
ASCII
ValueCountFrequency (%)
1 76
15.3%
4 65
13.1%
5 51
10.3%
2 50
10.1%
6 48
9.7%
3 47
9.5%
7 39
7.9%
0 38
7.7%
8 34
6.9%
9 29
 
5.8%

문화재명
Text

Distinct150
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T09:04:59.271985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length24
Mean length10.802632
Min length3

Characters and Unicode

Total characters1642
Distinct characters298
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique148 ?
Unique (%)97.4%

Sample

1st row백자 철화포도문 항아리
2nd row대방광불화엄경 진본 권37
3rd row이원길 개국원종공신녹권
4th row초조본 대승아비달마잡집론 권14
5th row삼국유사 권1~2
ValueCountFrequency (%)
봉원사 14
 
4.0%
서울 13
 
3.7%
연세대학교 7
 
2.0%
및 6
 
1.7%
백범 6
 
1.7%
김구 6
 
1.7%
항아리 5
 
1.4%
백자 4
 
1.1%
묘법연화경 4
 
1.1%
초조본 4
 
1.1%
Other values (255) 282
80.3%
2023-12-13T09:04:59.591464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
199
 
12.1%
사 40
 
2.4%
도 34
 
2.1%
대 33
 
2.0%
권 28
 
1.7%
원 26
 
1.6%
경 24
 
1.5%
1 23
 
1.4%
화 23
 
1.4%
문 22
 
1.3%
Other values (288) 1190
72.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1304
79.4%
Space Separator 199
 
12.1%
Decimal Number 85
 
5.2%
Other Punctuation 23
 
1.4%
Math Symbol 11
 
0.7%
Open Punctuation 9
 
0.5%
Close Punctuation 9
 
0.5%
Final Punctuation 1
 
0.1%
Initial Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 40
 
3.1%
도 34
 
2.6%
대 33
 
2.5%
권 28
 
2.1%
원 26
 
2.0%
경 24
 
1.8%
화 23
 
1.8%
문 22
 
1.7%
상 21
 
1.6%
서 20
 
1.5%
Other values (270) 1033
79.2%
Decimal Number
ValueCountFrequency (%)
1 23
27.1%
4 16
18.8%
3 9
 
10.6%
2 9
 
10.6%
9 8
 
9.4%
0 6
 
7.1%
7 6
 
7.1%
5 3
 
3.5%
6 3
 
3.5%
8 2
 
2.4%
Other Punctuation
ValueCountFrequency (%)
, 17
73.9%
· 6
 
26.1%
Space Separator
ValueCountFrequency (%)
199
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1284
78.2%
Common 338
 
20.6%
Han 20
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 40
 
3.1%
도 34
 
2.6%
대 33
 
2.6%
권 28
 
2.2%
원 26
 
2.0%
경 24
 
1.9%
화 23
 
1.8%
문 22
 
1.7%
상 21
 
1.6%
서 20
 
1.6%
Other values (253) 1013
78.9%
Common
ValueCountFrequency (%)
199
58.9%
1 23
 
6.8%
, 17
 
5.0%
4 16
 
4.7%
~ 11
 
3.3%
( 9
 
2.7%
) 9
 
2.7%
3 9
 
2.7%
2 9
 
2.7%
9 8
 
2.4%
Other values (8) 28
 
8.3%
Han
ValueCountFrequency (%)
金 2
 
10.0%
九 2
 
10.0%
獨 2
 
10.0%
聞 1
 
5.0%
和 1
 
5.0%
寬 1
 
5.0%
之 1
 
5.0%
邪 1
 
5.0%
印 1
 
5.0%
無 1
 
5.0%
Other values (7) 7
35.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1284
78.2%
ASCII 330
 
20.1%
CJK 18
 
1.1%
None 6
 
0.4%
CJK Compat Ideographs 2
 
0.1%
Punctuation 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
199
60.3%
1 23
 
7.0%
, 17
 
5.2%
4 16
 
4.8%
~ 11
 
3.3%
( 9
 
2.7%
) 9
 
2.7%
3 9
 
2.7%
2 9
 
2.7%
9 8
 
2.4%
Other values (5) 20
 
6.1%
Hangul
ValueCountFrequency (%)
사 40
 
3.1%
도 34
 
2.6%
대 33
 
2.6%
권 28
 
2.2%
원 26
 
2.0%
경 24
 
1.9%
화 23
 
1.8%
문 22
 
1.7%
상 21
 
1.6%
서 20
 
1.6%
Other values (253) 1013
78.9%
None
ValueCountFrequency (%)
· 6
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
金 2
100.0%
CJK
ValueCountFrequency (%)
九 2
 
11.1%
獨 2
 
11.1%
聞 1
 
5.6%
和 1
 
5.6%
寬 1
 
5.6%
之 1
 
5.6%
邪 1
 
5.6%
印 1
 
5.6%
無 1
 
5.6%
思 1
 
5.6%
Other values (6) 6
33.3%
Punctuation
ValueCountFrequency (%)
’ 1
50.0%
‘ 1
50.0%

지정일
Date

Distinct76
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1962-12-20 00:00:00
Maximum2021-04-05 00:00:00
2023-12-13T09:04:59.699268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:04:59.808923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

분야(소분류)
Categorical

HIGH CORRELATION 

Distinct43
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
목판본류
33 
전적류
17 
유물,유품
16 
민속자료기타
15 
불화
10 
Other values (38)
61 

Length

Max length8
Median length6
Mean length3.8223684
Min length2

Unique

Unique24 ?
Unique (%)15.8%

Sample

1st row백자
2nd row목판본류
3rd row교서
4th row목판본류
5th row목판본류

Common Values

ValueCountFrequency (%)
목판본류 33
21.7%
전적류 17
 
11.2%
유물,유품 16
 
10.5%
민속자료기타 15
 
9.9%
불화 10
 
6.6%
백자 4
 
2.6%
복식 4
 
2.6%
독립유적지 3
 
2.0%
목불 3
 
2.0%
초상화 3
 
2.0%
Other values (33) 44
28.9%

Length

2023-12-13T09:04:59.921701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
목판본류 33
21.7%
전적류 17
 
11.2%
유물,유품 16
 
10.5%
민속자료기타 15
 
9.9%
불화 10
 
6.6%
백자 4
 
2.6%
복식 4
 
2.6%
독립유적지 3
 
2.0%
목불 3
 
2.0%
초상화 3
 
2.0%
Other values (33) 44
28.9%

재료
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
65 
저지(楮紙)
25 
저지
10 
종이
7 
지류
 
5
Other values (30)
40 

Length

Max length21
Median length19
Mean length4.2105263
Min length2

Unique

Unique22 ?
Unique (%)14.5%

Sample

1st row흙(土)
2nd row지류
3rd row저지(楮紙)
4th row장지(壯紙)
5th row저지(楮紙)

Common Values

ValueCountFrequency (%)
<NA> 65
42.8%
저지(楮紙) 25
 
16.4%
저지 10
 
6.6%
종이 7
 
4.6%
지류 5
 
3.3%
섬유류 3
 
2.0%
도자 3
 
2.0%
금속 2
 
1.3%
비단(絹) 2
 
1.3%
석재 2
 
1.3%
Other values (25) 28
18.4%

Length

2023-12-13T09:05:00.030666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 65
40.1%
저지(楮紙 27
16.7%
저지 10
 
6.2%
종이 7
 
4.3%
지류 5
 
3.1%
섬유류 3
 
1.9%
도자 3
 
1.9%
화강석 2
 
1.2%
2
 
1.2%
목조 2
 
1.2%
Other values (30) 36
22.2%

구조
Text

MISSING 

Distinct21
Distinct (%)50.0%
Missing110
Missing (%)72.4%
Memory size1.3 KiB
2023-12-13T09:05:00.232060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length58.5
Mean length10.452381
Min length2

Characters and Unicode

Total characters439
Distinct characters139
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

Unique18 ?
Unique (%)42.9%

Sample

1st row본활자(本活字) 및 목판(木板)
2nd row목판본(木版本)
3rd row[역설상경], [역설하경], [역설계사]로 구성
4th row우악보
5th row병진자 또는 갑진자의 사주쌍변 유계 10행 18자
ValueCountFrequency (%)
목판본 17
 
19.5%
목판본(木版本 6
 
6.9%
필사본(筆寫本 3
 
3.4%
및 2
 
2.3%
2
 
2.3%
활자본(活字本 2
 
2.3%
小字 1
 
1.1%
24行 1
 
1.1%
19字 1
 
1.1%
통하는 1
 
1.1%
Other values (51) 51
58.6%
2023-12-13T09:05:00.536611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
 
10.5%
본 33
 
7.5%
목 27
 
6.2%
판 25
 
5.7%
( 23
 
5.2%
) 23
 
5.2%
本 15
 
3.4%
, 13
 
3.0%
조 9
 
2.1%
자 8
 
1.8%
Other values (129) 217
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 300
68.3%
Space Separator 46
 
10.5%
Open Punctuation 26
 
5.9%
Close Punctuation 26
 
5.9%
Other Punctuation 18
 
4.1%
Decimal Number 18
 
4.1%
Math Symbol 3
 
0.7%
Lowercase Letter 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
본 33
 
11.0%
목 27
 
9.0%
판 25
 
8.3%
本 15
 
5.0%
조 9
 
3.0%
자 8
 
2.7%
字 8
 
2.7%
木 7
 
2.3%
版 6
 
2.0%
필 6
 
2.0%
Other values (107) 156
52.0%
Decimal Number
ValueCountFrequency (%)
1 5
27.8%
4 3
16.7%
5 2
 
11.1%
2 2
 
11.1%
0 2
 
11.1%
8 1
 
5.6%
9 1
 
5.6%
3 1
 
5.6%
6 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 13
72.2%
. 3
 
16.7%
: 2
 
11.1%
Math Symbol
ValueCountFrequency (%)
> 1
33.3%
< 1
33.3%
× 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 23
88.5%
[ 3
 
11.5%
Close Punctuation
ValueCountFrequency (%)
) 23
88.5%
] 3
 
11.5%
Lowercase Letter
ValueCountFrequency (%)
m 1
50.0%
c 1
50.0%
Space Separator
ValueCountFrequency (%)
46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 214
48.7%
Common 137
31.2%
Han 86
19.6%
Latin 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
본 33
 
15.4%
목 27
 
12.6%
판 25
 
11.7%
조 9
 
4.2%
자 8
 
3.7%
필 6
 
2.8%
사 5
 
2.3%
하 3
 
1.4%
에 3
 
1.4%
석 3
 
1.4%
Other values (68) 92
43.0%
Han
ValueCountFrequency (%)
本 15
17.4%
字 8
 
9.3%
木 7
 
8.1%
版 6
 
7.0%
筆 6
 
7.0%
活 3
 
3.5%
寫 3
 
3.5%
行 3
 
3.5%
半 2
 
2.3%
乙 2
 
2.3%
Other values (29) 31
36.0%
Common
ValueCountFrequency (%)
46
33.6%
( 23
16.8%
) 23
16.8%
, 13
 
9.5%
1 5
 
3.6%
. 3
 
2.2%
] 3
 
2.2%
4 3
 
2.2%
[ 3
 
2.2%
5 2
 
1.5%
Other values (10) 13
 
9.5%
Latin
ValueCountFrequency (%)
m 1
50.0%
c 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 214
48.7%
ASCII 138
31.4%
CJK 86
19.6%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46
33.3%
( 23
16.7%
) 23
16.7%
, 13
 
9.4%
1 5
 
3.6%
. 3
 
2.2%
] 3
 
2.2%
4 3
 
2.2%
[ 3
 
2.2%
5 2
 
1.4%
Other values (11) 14
 
10.1%
Hangul
ValueCountFrequency (%)
본 33
 
15.4%
목 27
 
12.6%
판 25
 
11.7%
조 9
 
4.2%
자 8
 
3.7%
필 6
 
2.8%
사 5
 
2.3%
하 3
 
1.4%
에 3
 
1.4%
석 3
 
1.4%
Other values (68) 92
43.0%
CJK
ValueCountFrequency (%)
本 15
17.4%
字 8
 
9.3%
木 7
 
8.1%
版 6
 
7.0%
筆 6
 
7.0%
活 3
 
3.5%
寫 3
 
3.5%
行 3
 
3.5%
半 2
 
2.3%
乙 2
 
2.3%
Other values (29) 31
36.0%
None
ValueCountFrequency (%)
× 1
100.0%

형식-형태
Categorical

HIGH CORRELATION 

Distinct36
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
60 
정치외교
13 
선장(線裝)
10 
교육예술
8 
과학기술
7 
Other values (31)
54 

Length

Max length15
Median length4
Mean length4.8552632
Min length1

Unique

Unique21 ?
Unique (%)13.8%

Sample

1st row항아리
2nd row권자장
3rd row권자장(卷子裝)
4th row첩장(帖裝)
5th row선장(線裝)

Common Values

ValueCountFrequency (%)
<NA> 60
39.5%
정치외교 13
 
8.6%
선장(線裝) 10
 
6.6%
교육예술 8
 
5.3%
과학기술 7
 
4.6%
선장 7
 
4.6%
선장(線) <오침(五針)> 5
 
3.3%
첩장(帖裝) 4
 
2.6%
사회생활 3
 
2.0%
교육시설 3
 
2.0%
Other values (26) 32
21.1%

Length

2023-12-13T09:05:00.651822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 60
36.8%
정치외교 13
 
8.0%
선장(線裝 12
 
7.4%
선장 11
 
6.7%
교육예술 8
 
4.9%
과학기술 7
 
4.3%
선장(線 5
 
3.1%
오침(五針 5
 
3.1%
첩장(帖裝 4
 
2.5%
사회생활 3
 
1.8%
Other values (26) 35
21.5%

규격-크기
Text

MISSING 

Distinct80
Distinct (%)100.0%
Missing72
Missing (%)47.4%
Memory size1.3 KiB
2023-12-13T09:05:00.842421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length46
Mean length18.5625
Min length4

Characters and Unicode

Total characters1485
Distinct characters95
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)100.0%

Sample

1st row높이(高) 53.3cm
2nd row29.5cm×768.3cm
3rd row30.4 × 372cm
4th row가로31cm x 세로12.2cm
5th row세로 31.1(24.0) × 가로 20.1(17.1) ㎝
ValueCountFrequency (%)
x 20
 
7.5%
× 15
 
5.6%
8
 
3.0%
높이 7
 
2.6%
등 5
 
1.9%
4면 4
 
1.5%
가로 4
 
1.5%
29 4
 
1.5%
세로 3
 
1.1%
내외 2
 
0.7%
Other values (182) 195
73.0%
2023-12-13T09:05:01.163452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
191
 
12.9%
. 138
 
9.3%
m 129
 
8.7%
c 96
 
6.5%
2 95
 
6.4%
1 92
 
6.2%
5 69
 
4.6%
3 63
 
4.2%
× 61
 
4.1%
0 47
 
3.2%
Other values (85) 504
33.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 574
38.7%
Lowercase Letter 245
16.5%
Space Separator 191
 
12.9%
Other Punctuation 184
 
12.4%
Other Letter 175
 
11.8%
Math Symbol 63
 
4.2%
Close Punctuation 16
 
1.1%
Open Punctuation 16
 
1.1%
Other Symbol 11
 
0.7%
Uppercase Letter 4
 
0.3%
Other values (2) 6
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 13
 
7.4%
높 11
 
6.3%
로 11
 
6.3%
면 8
 
4.6%
등 8
 
4.6%
지 8
 
4.6%
권 8
 
4.6%
가 6
 
3.4%
장 6
 
3.4%
세 5
 
2.9%
Other values (53) 91
52.0%
Decimal Number
ValueCountFrequency (%)
2 95
16.6%
1 92
16.0%
5 69
12.0%
3 63
11.0%
0 47
8.2%
4 46
8.0%
7 44
7.7%
8 41
7.1%
6 39
6.8%
9 38
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 138
75.0%
, 30
 
16.3%
: 9
 
4.9%
/ 5
 
2.7%
· 2
 
1.1%
Other Number
ValueCountFrequency (%)
① 1
25.0%
② 1
25.0%
③ 1
25.0%
④ 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
m 129
52.7%
c 96
39.2%
x 20
 
8.2%
Math Symbol
ValueCountFrequency (%)
× 61
96.8%
∼ 1
 
1.6%
~ 1
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
X 3
75.0%
M 1
 
25.0%
Space Separator
ValueCountFrequency (%)
191
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Other Symbol
ValueCountFrequency (%)
㎝ 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1061
71.4%
Latin 249
 
16.8%
Hangul 174
 
11.7%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 13
 
7.5%
높 11
 
6.3%
로 11
 
6.3%
면 8
 
4.6%
등 8
 
4.6%
지 8
 
4.6%
권 8
 
4.6%
가 6
 
3.4%
장 6
 
3.4%
세 5
 
2.9%
Other values (52) 90
51.7%
Common
ValueCountFrequency (%)
191
18.0%
. 138
13.0%
2 95
9.0%
1 92
8.7%
5 69
 
6.5%
3 63
 
5.9%
× 61
 
5.7%
0 47
 
4.4%
4 46
 
4.3%
7 44
 
4.1%
Other values (17) 215
20.3%
Latin
ValueCountFrequency (%)
m 129
51.8%
c 96
38.6%
x 20
 
8.0%
X 3
 
1.2%
M 1
 
0.4%
Han
ValueCountFrequency (%)
高 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1231
82.9%
Hangul 174
 
11.7%
None 63
 
4.2%
CJK Compat 11
 
0.7%
Enclosed Alphanum 4
 
0.3%
Math Operators 1
 
0.1%
CJK 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
191
15.5%
. 138
11.2%
m 129
10.5%
c 96
 
7.8%
2 95
 
7.7%
1 92
 
7.5%
5 69
 
5.6%
3 63
 
5.1%
0 47
 
3.8%
4 46
 
3.7%
Other values (14) 265
21.5%
None
ValueCountFrequency (%)
× 61
96.8%
· 2
 
3.2%
Hangul
ValueCountFrequency (%)
이 13
 
7.5%
높 11
 
6.3%
로 11
 
6.3%
면 8
 
4.6%
등 8
 
4.6%
지 8
 
4.6%
권 8
 
4.6%
가 6
 
3.4%
장 6
 
3.4%
세 5
 
2.9%
Other values (52) 90
51.7%
CJK Compat
ValueCountFrequency (%)
㎝ 11
100.0%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%
CJK
ValueCountFrequency (%)
高 1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 1
25.0%
② 1
25.0%
③ 1
25.0%
④ 1
25.0%

수량-면적
Text

MISSING 

Distinct82
Distinct (%)54.7%
Missing2
Missing (%)1.3%
Memory size1.3 KiB
2023-12-13T09:05:01.426240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length2
Mean length5.8666667
Min length2

Characters and Unicode

Total characters880
Distinct characters103
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)45.3%

Sample

1st row1개
2nd row1권1축
3rd row1축
4th row1권 1첩
5th row2권 1책
ValueCountFrequency (%)
1점 36
 
14.2%
1책 28
 
11.1%
1권 12
 
4.7%
1건 6
 
2.4%
2책 6
 
2.4%
1식 5
 
2.0%
1동 5
 
2.0%
1개 5
 
2.0%
1축 5
 
2.0%
2권 4
 
1.6%
Other values (117) 141
55.7%
2023-12-13T09:05:01.808973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 166
18.9%
111
 
12.6%
책 49
 
5.6%
점 48
 
5.5%
2 38
 
4.3%
권 38
 
4.3%
4 26
 
3.0%
3 26
 
3.0%
, 21
 
2.4%
. 20
 
2.3%
Other values (93) 337
38.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 328
37.3%
Other Letter 316
35.9%
Space Separator 111
 
12.6%
Other Punctuation 51
 
5.8%
Open Punctuation 20
 
2.3%
Close Punctuation 20
 
2.3%
Other Symbol 19
 
2.2%
Lowercase Letter 9
 
1.0%
Math Symbol 5
 
0.6%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
책 49
 
15.5%
점 48
 
15.2%
권 38
 
12.0%
건 13
 
4.1%
장 9
 
2.8%
동 7
 
2.2%
지 7
 
2.2%
축 6
 
1.9%
개 6
 
1.9%
구 5
 
1.6%
Other values (66) 128
40.5%
Decimal Number
ValueCountFrequency (%)
1 166
50.6%
2 38
 
11.6%
4 26
 
7.9%
3 26
 
7.9%
0 17
 
5.2%
5 13
 
4.0%
6 12
 
3.7%
8 12
 
3.7%
9 12
 
3.7%
7 6
 
1.8%
Other Punctuation
ValueCountFrequency (%)
, 21
41.2%
. 20
39.2%
/ 6
 
11.8%
: 4
 
7.8%
Math Symbol
ValueCountFrequency (%)
× 2
40.0%
∼ 2
40.0%
~ 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 19
95.0%
[ 1
 
5.0%
Close Punctuation
ValueCountFrequency (%)
) 19
95.0%
] 1
 
5.0%
Other Symbol
ValueCountFrequency (%)
㎡ 17
89.5%
㎝ 2
 
10.5%
Lowercase Letter
ValueCountFrequency (%)
m 6
66.7%
c 3
33.3%
Space Separator
ValueCountFrequency (%)
111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 555
63.1%
Hangul 310
35.2%
Latin 9
 
1.0%
Han 6
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
책 49
15.8%
점 48
 
15.5%
권 38
 
12.3%
건 13
 
4.2%
장 9
 
2.9%
동 7
 
2.3%
지 7
 
2.3%
축 6
 
1.9%
개 6
 
1.9%
구 5
 
1.6%
Other values (62) 122
39.4%
Common
ValueCountFrequency (%)
1 166
29.9%
111
20.0%
2 38
 
6.8%
4 26
 
4.7%
3 26
 
4.7%
, 21
 
3.8%
. 20
 
3.6%
( 19
 
3.4%
) 19
 
3.4%
0 17
 
3.1%
Other values (15) 92
16.6%
Han
ValueCountFrequency (%)
基 2
33.3%
軀 2
33.3%
点 1
16.7%
冊 1
16.7%
Latin
ValueCountFrequency (%)
m 6
66.7%
c 3
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 541
61.5%
Hangul 310
35.2%
CJK Compat 19
 
2.2%
CJK 6
 
0.7%
None 2
 
0.2%
Math Operators 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 166
30.7%
111
20.5%
2 38
 
7.0%
4 26
 
4.8%
3 26
 
4.8%
, 21
 
3.9%
. 20
 
3.7%
( 19
 
3.5%
) 19
 
3.5%
0 17
 
3.1%
Other values (13) 78
14.4%
Hangul
ValueCountFrequency (%)
책 49
15.8%
점 48
 
15.5%
권 38
 
12.3%
건 13
 
4.2%
장 9
 
2.9%
동 7
 
2.3%
지 7
 
2.3%
축 6
 
1.9%
개 6
 
1.9%
구 5
 
1.6%
Other values (62) 122
39.4%
CJK Compat
ValueCountFrequency (%)
㎡ 17
89.5%
㎝ 2
 
10.5%
None
ValueCountFrequency (%)
× 2
100.0%
Math Operators
ValueCountFrequency (%)
∼ 2
100.0%
CJK
ValueCountFrequency (%)
基 2
33.3%
軀 2
33.3%
点 1
16.7%
冊 1
16.7%

(제)작자
Text

MISSING 

Distinct30
Distinct (%)90.9%
Missing119
Missing (%)78.3%
Memory size1.3 KiB
2023-12-13T09:05:02.027511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length20
Mean length18.636364
Min length2

Characters and Unicode

Total characters615
Distinct characters194
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)81.8%

Sample

1st row불타발타라 역
2nd row최길회
3rd row권근
4th row송(宋) 주희
5th row권근
ValueCountFrequency (%)
당(唐 7
 
7.9%
역(譯 5
 
5.6%
구마라십(鳩摩羅什 4
 
4.5%
송(宋 4
 
4.5%
후진(後秦 3
 
3.4%
술(述 3
 
3.4%
정원(淨源 3
 
3.4%
h 2
 
2.2%
n 2
 
2.2%
고려(高麗 2
 
2.2%
Other values (48) 54
60.7%
2023-12-13T09:05:02.351356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 72
 
11.7%
) 72
 
11.7%
56
 
9.1%
> 18
 
2.9%
< 18
 
2.9%
구 9
 
1.5%
라 9
 
1.5%
당 8
 
1.3%
唐 8
 
1.3%
羅 7
 
1.1%
Other values (184) 338
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 324
52.7%
Open Punctuation 72
 
11.7%
Close Punctuation 72
 
11.7%
Space Separator 56
 
9.1%
Math Symbol 37
 
6.0%
Uppercase Letter 25
 
4.1%
Other Punctuation 13
 
2.1%
Lowercase Letter 8
 
1.3%
Decimal Number 8
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 9
 
2.8%
라 9
 
2.8%
당 8
 
2.5%
唐 8
 
2.5%
羅 7
 
2.2%
마 7
 
2.2%
십 7
 
2.2%
역 6
 
1.9%
주 6
 
1.9%
什 6
 
1.9%
Other values (151) 251
77.5%
Uppercase Letter
ValueCountFrequency (%)
A 4
16.0%
L 3
12.0%
N 3
12.0%
H 2
 
8.0%
I 2
 
8.0%
E 2
 
8.0%
G 1
 
4.0%
S 1
 
4.0%
C 1
 
4.0%
T 1
 
4.0%
Other values (5) 5
20.0%
Decimal Number
ValueCountFrequency (%)
1 3
37.5%
3 2
25.0%
7 1
 
12.5%
8 1
 
12.5%
4 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 5
38.5%
. 5
38.5%
: 2
 
15.4%
& 1
 
7.7%
Math Symbol
ValueCountFrequency (%)
> 18
48.6%
< 18
48.6%
∼ 1
 
2.7%
Lowercase Letter
ValueCountFrequency (%)
l 4
50.0%
n 2
25.0%
e 2
25.0%
Open Punctuation
ValueCountFrequency (%)
( 72
100.0%
Close Punctuation
ValueCountFrequency (%)
) 72
100.0%
Space Separator
ValueCountFrequency (%)
56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 258
42.0%
Hangul 180
29.3%
Han 144
23.4%
Latin 33
 
5.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 9
 
5.0%
라 9
 
5.0%
당 8
 
4.4%
마 7
 
3.9%
십 7
 
3.9%
역 6
 
3.3%
주 6
 
3.3%
집 6
 
3.3%
송 5
 
2.8%
원 5
 
2.8%
Other values (76) 112
62.2%
Han
ValueCountFrequency (%)
唐 8
 
5.6%
羅 7
 
4.9%
什 6
 
4.2%
鳩 6
 
4.2%
摩 6
 
4.2%
集 5
 
3.5%
譯 5
 
3.5%
宋 4
 
2.8%
淨 4
 
2.8%
經 4
 
2.8%
Other values (65) 89
61.8%
Latin
ValueCountFrequency (%)
l 4
12.1%
A 4
12.1%
L 3
 
9.1%
N 3
 
9.1%
H 2
 
6.1%
I 2
 
6.1%
E 2
 
6.1%
n 2
 
6.1%
e 2
 
6.1%
G 1
 
3.0%
Other values (8) 8
24.2%
Common
ValueCountFrequency (%)
( 72
27.9%
) 72
27.9%
56
21.7%
> 18
 
7.0%
< 18
 
7.0%
, 5
 
1.9%
. 5
 
1.9%
1 3
 
1.2%
: 2
 
0.8%
3 2
 
0.8%
Other values (5) 5
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 290
47.2%
Hangul 180
29.3%
CJK 141
22.9%
CJK Compat Ideographs 3
 
0.5%
Math Operators 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 72
24.8%
) 72
24.8%
56
19.3%
> 18
 
6.2%
< 18
 
6.2%
, 5
 
1.7%
. 5
 
1.7%
l 4
 
1.4%
A 4
 
1.4%
1 3
 
1.0%
Other values (22) 33
11.4%
Hangul
ValueCountFrequency (%)
구 9
 
5.0%
라 9
 
5.0%
당 8
 
4.4%
마 7
 
3.9%
십 7
 
3.9%
역 6
 
3.3%
주 6
 
3.3%
집 6
 
3.3%
송 5
 
2.8%
원 5
 
2.8%
Other values (76) 112
62.2%
CJK
ValueCountFrequency (%)
唐 8
 
5.7%
羅 7
 
5.0%
什 6
 
4.3%
鳩 6
 
4.3%
摩 6
 
4.3%
集 5
 
3.5%
譯 5
 
3.5%
宋 4
 
2.8%
淨 4
 
2.8%
經 4
 
2.8%
Other values (62) 86
61.0%
CJK Compat Ideographs
ValueCountFrequency (%)
龜 1
33.3%
李 1
33.3%
梁 1
33.3%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%

종교
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
82 
불교
39 
기타
24 
개신교
 
4
유교
 
3

Length

Max length4
Median length4
Mean length3.1052632
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row불교
3rd row기타
4th row불교
5th row기타

Common Values

ValueCountFrequency (%)
<NA> 82
53.9%
불교 39
25.7%
기타 24
 
15.8%
개신교 4
 
2.6%
유교 3
 
2.0%

Length

2023-12-13T09:05:02.465009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:05:02.572315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 82
53.9%
불교 39
25.7%
기타 24
 
15.8%
개신교 4
 
2.6%
유교 3
 
2.0%

년대-시대
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
조선시대
78 
고려시대
22 
일제강점기
21 
대한제국시대
15 
<NA>
14 
Other values (2)
 
2

Length

Max length6
Median length4
Mean length4.3421053
Min length4

Unique

Unique2 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
조선시대 78
51.3%
고려시대 22
 
14.5%
일제강점기 21
 
13.8%
대한제국시대 15
 
9.9%
<NA> 14
 
9.2%
고구려시대 1
 
0.7%
삼국시대 1
 
0.7%

Length

2023-12-13T09:05:02.689649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:05:02.788326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조선시대 78
51.3%
고려시대 22
 
14.5%
일제강점기 21
 
13.8%
대한제국시대 15
 
9.9%
na 14
 
9.2%
고구려시대 1
 
0.7%
삼국시대 1
 
0.7%

소재시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
서울특별시
152 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 152
100.0%

Length

2023-12-13T09:05:02.892039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:05:02.970125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 152
100.0%

시군구
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
서대문구
148 
서울특별시(특정 불가)
 
3
용산구
 
1

Length

Max length12
Median length4
Mean length4.1513158
Min length3

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
서대문구 148
97.4%
서울특별시(특정 불가) 3
 
2.0%
용산구 1
 
0.7%

Length

2023-12-13T09:05:03.052895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:05:03.141414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서대문구 148
95.5%
서울특별시(특정 3
 
1.9%
불가 3
 
1.9%
용산구 1
 
0.6%

소재지
Text

Distinct61
Distinct (%)40.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T09:05:03.290683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length46
Mean length36.888158
Min length5

Characters and Unicode

Total characters5607
Distinct characters118
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)19.1%

Sample

1st row[도로]서울 서대문구 이화여대길 52, 박물관 (신촌동)
2nd row[도로]서울특별시 서대문구 충정로9길 10-10 (충정로2가, (재)현담문고)
3rd row[도로]서울특별시 서대문구 충정로9길 10-10 (충정로2가, (재)현담문고)
4th row[도로]서울특별시 서대문구 충정로9길 10-10 (충정로2가, (재)현담문고)
5th row[도로]서울특별시 서대문구 연세로 50 (신촌동, 연세대학교) 연세대학교박물관
ValueCountFrequency (%)
서대문구 152
16.8%
도로]서울특별시 104
 
11.5%
연세로 43
 
4.8%
충정로2가 41
 
4.5%
충정로9길 40
 
4.4%
10-10 40
 
4.4%
신촌동 39
 
4.3%
50 38
 
4.2%
연세대학교 30
 
3.3%
재)현담문고 29
 
3.2%
Other values (86) 349
38.6%
2023-12-13T09:05:03.579370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
804
 
14.3%
서 310
 
5.5%
로 263
 
4.7%
대 262
 
4.7%
문 184
 
3.3%
) 159
 
2.8%
( 159
 
2.8%
0 154
 
2.7%
구 153
 
2.7%
[ 152
 
2.7%
Other values (108) 3007
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3454
61.6%
Space Separator 804
 
14.3%
Decimal Number 548
 
9.8%
Close Punctuation 311
 
5.5%
Open Punctuation 311
 
5.5%
Other Punctuation 113
 
2.0%
Dash Punctuation 61
 
1.1%
Uppercase Letter 4
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 310
 
9.0%
로 263
 
7.6%
대 262
 
7.6%
문 184
 
5.3%
구 153
 
4.4%
울 152
 
4.4%
도 136
 
3.9%
시 121
 
3.5%
특 121
 
3.5%
별 121
 
3.5%
Other values (84) 1631
47.2%
Decimal Number
ValueCountFrequency (%)
0 154
28.1%
1 131
23.9%
2 90
16.4%
5 83
15.1%
9 43
 
7.8%
6 16
 
2.9%
4 12
 
2.2%
3 10
 
1.8%
7 5
 
0.9%
8 4
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
A 1
25.0%
F 1
25.0%
G 1
25.0%
L 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 111
98.2%
/ 1
 
0.9%
: 1
 
0.9%
Close Punctuation
ValueCountFrequency (%)
) 159
51.1%
] 152
48.9%
Open Punctuation
ValueCountFrequency (%)
( 159
51.1%
[ 152
48.9%
Space Separator
ValueCountFrequency (%)
804
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3454
61.6%
Common 2149
38.3%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 310
 
9.0%
로 263
 
7.6%
대 262
 
7.6%
문 184
 
5.3%
구 153
 
4.4%
울 152
 
4.4%
도 136
 
3.9%
시 121
 
3.5%
특 121
 
3.5%
별 121
 
3.5%
Other values (84) 1631
47.2%
Common
ValueCountFrequency (%)
804
37.4%
) 159
 
7.4%
( 159
 
7.4%
0 154
 
7.2%
[ 152
 
7.1%
] 152
 
7.1%
1 131
 
6.1%
, 111
 
5.2%
2 90
 
4.2%
5 83
 
3.9%
Other values (10) 154
 
7.2%
Latin
ValueCountFrequency (%)
A 1
25.0%
F 1
25.0%
G 1
25.0%
L 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3454
61.6%
ASCII 2153
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
804
37.3%
) 159
 
7.4%
( 159
 
7.4%
0 154
 
7.2%
[ 152
 
7.1%
] 152
 
7.1%
1 131
 
6.1%
, 111
 
5.2%
2 90
 
4.2%
5 83
 
3.9%
Other values (14) 158
 
7.3%
Hangul
ValueCountFrequency (%)
서 310
 
9.0%
로 263
 
7.6%
대 262
 
7.6%
문 184
 
5.3%
구 153
 
4.4%
울 152
 
4.4%
도 136
 
3.9%
시 121
 
3.5%
특 121
 
3.5%
별 121
 
3.5%
Other values (84) 1631
47.2%

부동산-동산
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
동산
131 
부동산
19 
무형
 
2

Length

Max length3
Median length2
Mean length2.125
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동산 131
86.2%
부동산 19
 
12.5%
무형 2
 
1.3%

Length

2023-12-13T09:05:03.691116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:05:03.770247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동산 131
86.2%
부동산 19
 
12.5%
무형 2
 
1.3%

Interactions

2023-12-13T09:04:57.324076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:05:03.841951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번종목지정일분야(소분류)재료구조형식-형태규격-크기수량-면적(제)작자종교년대-시대시군구소재지부동산-동산
순번1.0000.9240.9790.8600.9180.9740.9501.0000.8161.0000.6830.5960.2240.9390.419
종목0.9241.0000.9900.9790.9530.9720.9981.0000.8631.0000.5530.8270.0000.9860.878
지정일0.9790.9901.0000.9880.9730.9350.9751.0000.9730.8870.9750.8960.0000.9970.993
분야(소분류)0.8600.9790.9881.0000.9740.9970.9791.0000.8681.0000.8360.9380.4020.9820.999
재료0.9180.9530.9730.9741.0000.9590.9481.0000.9540.9790.8970.8961.0000.9880.997
구조0.9740.9720.9350.9970.9591.0000.9221.0000.8440.9590.9740.917NaN0.9831.000
형식-형태0.9500.9980.9750.9790.9480.9221.0001.0000.9800.9900.9210.8740.7770.9601.000
규격-크기1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
수량-면적0.8160.8630.9730.8680.9540.8440.9801.0001.0000.9250.9510.9200.0000.9760.991
(제)작자1.0001.0000.8871.0000.9790.9590.9901.0000.9251.0001.0000.8221.0000.9091.000
종교0.6830.5530.9750.8360.8970.9740.9211.0000.9511.0001.0000.7070.0000.9290.000
년대-시대0.5960.8270.8960.9380.8960.9170.8741.0000.9200.8220.7071.0000.0000.8640.955
시군구0.2240.0000.0000.4021.000NaN0.7771.0000.0001.0000.0000.0001.0000.0000.000
소재지0.9390.9860.9970.9820.9880.9830.9601.0000.9760.9090.9290.8640.0001.0000.991
부동산-동산0.4190.8780.9930.9990.9971.0001.0001.0000.9911.0000.0000.9550.0000.9911.000
2023-12-13T09:05:03.988681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구분야(소분류)종목종교형식-형태재료부동산-동산년대-시대
시군구1.0000.1710.0000.0000.4440.7900.0000.000
분야(소분류)0.1711.0000.7440.4740.6790.6350.8270.637
종목0.0000.7441.0000.4760.7580.6440.7940.582
종교0.0000.4740.4761.0000.5390.6260.0000.348
형식-형태0.4440.6790.7580.5391.0000.5200.7960.508
재료0.7900.6350.6440.6260.5201.0000.7530.539
부동산-동산0.0000.8270.7940.0000.7960.7531.0000.732
년대-시대0.0000.6370.5820.3480.5080.5390.7321.000
2023-12-13T09:05:04.084694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번종목분야(소분류)재료형식-형태종교년대-시대시군구부동산-동산
순번1.0000.5500.4480.5400.6140.4600.3590.1320.270
종목0.5501.0000.7440.6440.7580.4760.5820.0000.794
분야(소분류)0.4480.7441.0000.6350.6790.4740.6370.1710.827
재료0.5400.6440.6351.0000.5200.6260.5390.7900.753
형식-형태0.6140.7580.6790.5201.0000.5390.5080.4440.796
종교0.4600.4760.4740.6260.5391.0000.3480.0000.000
년대-시대0.3590.5820.6370.5390.5080.3481.0000.0000.732
시군구0.1320.0000.1710.7900.4440.0000.0001.0000.000
부동산-동산0.2700.7940.8270.7530.7960.0000.7320.0001.000

Missing values

2023-12-13T09:04:57.687894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:04:57.857080image/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.
2023-12-13T09:04:57.993397image/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

순번종목지정번호문화재명지정일분야(소분류)재료구조형식-형태규격-크기수량-면적(제)작자종교년대-시대소재시도시군구소재지부동산-동산
01국보제107호백자 철화포도문 항아리1962-12-20백자흙(土)<NA>항아리높이(高) 53.3cm1개<NA><NA>조선시대서울특별시서대문구[도로]서울 서대문구 이화여대길 52, 박물관 (신촌동)동산
12국보제202호대방광불화엄경 진본 권371981-03-18목판본류지류<NA>권자장29.5cm×768.3cm1권1축불타발타라 역불교고려시대서울특별시서대문구[도로]서울특별시 서대문구 충정로9길 10-10 (충정로2가, (재)현담문고)동산
23국보제250호이원길 개국원종공신녹권1989-08-01교서저지(楮紙)본활자(本活字) 및 목판(木板)권자장(卷子裝)30.4 × 372cm1축<NA>기타조선시대서울특별시서대문구[도로]서울특별시 서대문구 충정로9길 10-10 (충정로2가, (재)현담문고)동산
34국보제251호초조본 대승아비달마잡집론 권141989-08-01목판본류장지(壯紙)목판본(木版本)첩장(帖裝)가로31cm x 세로12.2cm1권 1첩<NA>불교고려시대서울특별시서대문구[도로]서울특별시 서대문구 충정로9길 10-10 (충정로2가, (재)현담문고)동산
45국보제306-3호삼국유사 권1~22018-02-22목판본류저지(楮紙)<NA>선장(線裝)세로 31.1(24.0) × 가로 20.1(17.1) ㎝2권 1책<NA>기타조선시대서울특별시서대문구[도로]서울특별시 서대문구 연세로 50 (신촌동, 연세대학교) 연세대학교박물관동산
56국보제326호청자 ‘순화4년’명 항아리2019-05-02청자도자<NA>항아리높이 35.2cm1개최길회<NA>고려시대서울특별시서대문구[도로]서울 서대문구 이화여대길 52, 박물관 (신촌동)동산
67보물제351호전 양평 보리사지 대경대사탑1963-01-21승탑화강석<NA>팔각원당형높이2.7m1기<NA>불교고려시대서울특별시서대문구[지번]서울 서대문구 대현동 산11-1번지 이화여자대학교부동산
78보물제352호감지은니 묘법연화경 권71963-01-21사경지류<NA>절첩장33.5cm×11.5cm1책<NA>불교고려시대서울특별시서대문구[도로]서울특별시 서대문구 이화여대길 52 (대현동, 이화여자대학교)동산
89보물제416호청자 투각고리문 의자1965-04-01청자토도<NA>돈① 49.5㎝, 38㎝ ② 48㎝, 38㎝ ③ 50㎝, 35㎝ ④ 48.5㎝, 34㎝4개<NA><NA>고려시대서울특별시서대문구[도로]서울 서대문구 이화여대길 52, 이화여자대학교박물관 (신촌동)동산
910보물제550호주역천견록1971-08-30목판본류지류[역설상경], [역설하경], [역설계사]로 구성선장25.2cm×19.1cm3책권근기타조선시대서울특별시서대문구[도로]서울특별시 서대문구 충정로9길 10-10 (충정로2가, (재)현담문고)동산
순번종목지정번호문화재명지정일분야(소분류)재료구조형식-형태규격-크기수량-면적(제)작자종교년대-시대소재시도시군구소재지부동산-동산
142143국가등록문화재제656호고종황제 하사 족자2016-02-11유물,유품<NA><NA>정치외교<NA>1점<NA><NA>대한제국시대서울특별시서대문구[도로]서울특별시 서대문구 연세로 50-1 (신촌동, 연세의료원) 동은의학박물관동산
143144국가등록문화재제665호발해태조건국지·명림답부전2016-10-20전적류<NA><NA>정치외교<NA>1권/세로 20.8×가로 14.9(㎝)<NA><NA>일제강점기서울특별시서대문구[도로]서울특별시 서대문구 연세로 50 (신촌동, 연세대학교) 박물관동산
144145국가등록문화재제669호예수성교전서2016-12-15전적류<NA><NA>사회생활<NA>1권/세로 20.5 × 가로 12.5㎝<NA>개신교조선시대서울특별시서대문구[도로]서울특별시 서대문구 연세로 50 (신촌동, 연세대학교) 학술정보원동산
145146국가등록문화재제679호서울 이화여자대학교 토마스홀2017-04-20석조문화재석재조적조(석재) 및 목조트러스교육시설3층(지하 1층, 지상 2층)1동/ 실측면적 542㎡<NA><NA>일제강점기서울특별시서대문구[도로]서울특별시 서대문구 이화여대길 52 (대현동, 이화여자대학교)부동산
146147국가등록문화재제685호천로역정(합질)2017-05-29전적류목판본 : 닥종이, 신활자본 : 중국지<NA>사회생활목판본(28.6×19.9㎝), 신활자본(세로 26.5 x 가로 19.3cm)5권(목판본:2질 4책, 신활자본:1책)<NA>개신교조선시대서울특별시서대문구[도로]서울특별시 서대문구 연세로 50 (신촌동, 연세대학교) 학술정보원동산
147148국가등록문화재제712호윤동주 친필원고2018-05-08전적류<NA><NA>교육예술<NA>6점(4책(시집 3책, 산문집 1책), 기타 낱장 모음 2종)<NA><NA>일제강점기서울특별시서대문구[도로]서울특별시 서대문구 연세로 50 (신촌동, 연세대학교) 연세대학교 학술정보원동산
148149국가등록문화재제770호서울 연세대학교 핀슨관2019-12-30석조기타<NA><NA>교육시설<NA>1동(344㎡)<NA><NA>일제강점기서울특별시서대문구[지번]서울특별시 서대문구 신촌동 134 연세대학교 핀슨관부동산
149150국가등록문화재제793-1호연세대학교 4월혁명연구반 4·19 혁명 참여자 조사서2020-08-12유물,유품<NA><NA>정치외교36.7cm × 26.5cm 등9건 195점<NA><NA><NA>서울특별시서대문구[도로]서울특별시 서대문구 연세로 50 (신촌동, 연세대학교박물관)동산
150151국가등록문화재제793-2호연세대학교 4월혁명연구반 4·19 혁명 계엄 포고문2020-08-12유물,유품<NA><NA>정치외교41 × 51cm 등19건 20점<NA><NA><NA>서울특별시서대문구[도로]서울특별시 서대문구 연세로 50 (신촌동, 연세대학교박물관)동산
151152국가등록문화재제807호서울 연세대학교 언더우드 가옥2021-04-05석조<NA><NA><NA><NA>2동/689.34㎡(전시실 642.31㎡, 별관 47.03㎡)<NA><NA>일제강점기서울특별시서대문구[도로]서울특별시 서대문구 연세로 50 (신촌동, 연세대학교)부동산