Overview

Dataset statistics

Number of variables9
Number of observations49
Missing cells53
Missing cells (%)12.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory75.7 B

Variable types

Categorical2
Text6
DateTime1

Dataset

Description경기도 이천시 소재의 국가지정유형문화재, 도지정유형문화재, 국가지정등록문화재, 도지정무형문화재, 시지정유형문화재에 대한 데이터입니다.
URLhttps://www.data.go.kr/data/15103278/fileData.do

Alerts

수량 is highly imbalanced (59.2%)Imbalance
관리자 has 11 (22.4%) missing valuesMissing
비고 has 42 (85.7%) missing valuesMissing
문화재명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:20:38.015826
Analysis finished2023-12-12 10:20:39.042431
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct5
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size524.0 B
시지정유형문화재
22 
도지정유형문화재
9 
국가지정유형문화재
7 
도지정무형문화재
6 
국가지정등록문화재
5 

Length

Max length9
Median length8
Mean length8.244898
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
시지정유형문화재 22
44.9%
도지정유형문화재 9
18.4%
국가지정유형문화재 7
 
14.3%
도지정무형문화재 6
 
12.2%
국가지정등록문화재 5
 
10.2%

Length

2023-12-12T19:20:39.127567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:20:39.285833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시지정유형문화재 22
44.9%
도지정유형문화재 9
18.4%
국가지정유형문화재 7
 
14.3%
도지정무형문화재 6
 
12.2%
국가지정등록문화재 5
 
10.2%

지정번호
Text

Distinct48
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-12T19:20:39.574430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.8571429
Min length5

Characters and Unicode

Total characters385
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)95.9%

Sample

1st row사적 제423호
2nd row보물822호
3rd row보물982호
4th row보물제1573호
5th row천연기념물 제253호
ValueCountFrequency (%)
무형문화재 6
 
9.1%
문화재자료 3
 
4.5%
유형문화재 3
 
4.5%
제26호 2
 
3.0%
제41호 2
 
3.0%
기념물 2
 
3.0%
향토유적11호 1
 
1.5%
향토유적12호 1
 
1.5%
제63호 1
 
1.5%
향토유적4호 1
 
1.5%
Other values (44) 44
66.7%
2023-12-12T19:20:40.021147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
호 49
 
12.7%
제 25
 
6.5%
1 25
 
6.5%
유 25
 
6.5%
적 23
 
6.0%
향 22
 
5.7%
토 22
 
5.7%
2 20
 
5.2%
17
 
4.4%
재 12
 
3.1%
Other values (26) 145
37.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 256
66.5%
Decimal Number 110
28.6%
Space Separator 17
 
4.4%
Dash Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 49
19.1%
제 25
9.8%
유 25
9.8%
적 23
9.0%
향 22
8.6%
토 22
8.6%
재 12
 
4.7%
화 12
 
4.7%
문 12
 
4.7%
형 9
 
3.5%
Other values (14) 45
17.6%
Decimal Number
ValueCountFrequency (%)
1 25
22.7%
2 20
18.2%
6 11
10.0%
5 11
10.0%
7 9
 
8.2%
0 8
 
7.3%
3 8
 
7.3%
4 7
 
6.4%
9 6
 
5.5%
8 5
 
4.5%
Space Separator
ValueCountFrequency (%)
17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 256
66.5%
Common 129
33.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 49
19.1%
제 25
9.8%
유 25
9.8%
적 23
9.0%
향 22
8.6%
토 22
8.6%
재 12
 
4.7%
화 12
 
4.7%
문 12
 
4.7%
형 9
 
3.5%
Other values (14) 45
17.6%
Common
ValueCountFrequency (%)
1 25
19.4%
2 20
15.5%
17
13.2%
6 11
8.5%
5 11
8.5%
7 9
 
7.0%
0 8
 
6.2%
3 8
 
6.2%
4 7
 
5.4%
9 6
 
4.7%
Other values (2) 7
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 256
66.5%
ASCII 129
33.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
호 49
19.1%
제 25
9.8%
유 25
9.8%
적 23
9.0%
향 22
8.6%
토 22
8.6%
재 12
 
4.7%
화 12
 
4.7%
문 12
 
4.7%
형 9
 
3.5%
Other values (14) 45
17.6%
ASCII
ValueCountFrequency (%)
1 25
19.4%
2 20
15.5%
17
13.2%
6 11
8.5%
5 11
8.5%
7 9
 
7.0%
0 8
 
6.2%
3 8
 
6.2%
4 7
 
5.4%
9 6
 
4.7%
Other values (2) 7
 
5.4%

문화재명
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-12T19:20:40.316019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length7.6530612
Min length3

Characters and Unicode

Total characters375
Distinct characters131
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)100.0%

Sample

1st row이천설봉산성
2nd row영월암마애여래입상
3rd row이천 장암리 마애보살반가상
4th row청자양각연판문접시
5th row이천백송
ValueCountFrequency (%)
묘역 4
 
5.1%
및 3
 
3.8%
설봉서원 2
 
2.6%
이천 2
 
2.6%
묘비 2
 
2.6%
금성 2
 
2.6%
이천설봉산성 1
 
1.3%
영원사 1
 
1.3%
석조여래입상 1
 
1.3%
대포리 1
 
1.3%
Other values (59) 59
75.6%
2023-12-12T19:20:40.736749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
 
7.7%
석 16
 
4.3%
리 14
 
3.7%
이 12
 
3.2%
상 12
 
3.2%
묘 9
 
2.4%
천 9
 
2.4%
성 8
 
2.1%
장 8
 
2.1%
입 8
 
2.1%
Other values (121) 250
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 323
86.1%
Space Separator 29
 
7.7%
Decimal Number 12
 
3.2%
Uppercase Letter 7
 
1.9%
Dash Punctuation 4
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
석 16
 
5.0%
리 14
 
4.3%
이 12
 
3.7%
상 12
 
3.7%
묘 9
 
2.8%
천 9
 
2.8%
성 8
 
2.5%
장 8
 
2.5%
입 8
 
2.5%
고 7
 
2.2%
Other values (106) 220
68.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
14.3%
P 1
14.3%
W 1
14.3%
D 1
14.3%
V 1
14.3%
R 1
14.3%
G 1
14.3%
Decimal Number
ValueCountFrequency (%)
1 6
50.0%
0 2
 
16.7%
8 1
 
8.3%
9 1
 
8.3%
2 1
 
8.3%
5 1
 
8.3%
Space Separator
ValueCountFrequency (%)
29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 323
86.1%
Common 45
 
12.0%
Latin 7
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
석 16
 
5.0%
리 14
 
4.3%
이 12
 
3.7%
상 12
 
3.7%
묘 9
 
2.8%
천 9
 
2.8%
성 8
 
2.5%
장 8
 
2.5%
입 8
 
2.5%
고 7
 
2.2%
Other values (106) 220
68.1%
Common
ValueCountFrequency (%)
29
64.4%
1 6
 
13.3%
- 4
 
8.9%
0 2
 
4.4%
8 1
 
2.2%
9 1
 
2.2%
2 1
 
2.2%
5 1
 
2.2%
Latin
ValueCountFrequency (%)
A 1
14.3%
P 1
14.3%
W 1
14.3%
D 1
14.3%
V 1
14.3%
R 1
14.3%
G 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 323
86.1%
ASCII 52
 
13.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29
55.8%
1 6
 
11.5%
- 4
 
7.7%
0 2
 
3.8%
A 1
 
1.9%
8 1
 
1.9%
P 1
 
1.9%
W 1
 
1.9%
9 1
 
1.9%
D 1
 
1.9%
Other values (5) 5
 
9.6%
Hangul
ValueCountFrequency (%)
석 16
 
5.0%
리 14
 
4.3%
이 12
 
3.7%
상 12
 
3.7%
묘 9
 
2.8%
천 9
 
2.8%
성 8
 
2.5%
장 8
 
2.5%
입 8
 
2.5%
고 7
 
2.2%
Other values (106) 220
68.1%

수량
Categorical

IMBALANCE 

Distinct4
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size524.0 B
1
41 
<NA>
6 
3
 
1
4
 
1

Length

Max length4
Median length1
Mean length1.3673469
Min length1

Unique

Unique2 ?
Unique (%)4.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 41
83.7%
<NA> 6
 
12.2%
3 1
 
2.0%
4 1
 
2.0%

Length

2023-12-12T19:20:40.880679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:20:40.989177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 41
83.7%
na 6
 
12.2%
3 1
 
2.0%
4 1
 
2.0%

소유자
Text

Distinct33
Distinct (%)67.3%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-12T19:20:41.198642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length3
Mean length4.1836735
Min length2

Characters and Unicode

Total characters205
Distinct characters89
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)55.1%

Sample

1st row이천시
2nd row영월암
3rd row국유
4th row이천시
5th row이천시
ValueCountFrequency (%)
이천시 6
 
10.5%
국유 5
 
8.8%
㈜lg 4
 
7.0%
영월암 3
 
5.3%
영원사 2
 
3.5%
㈜사우스스프링스 2
 
3.5%
종중 2
 
3.5%
이천서씨 1
 
1.8%
청풍김씨 1
 
1.8%
서광수 1
 
1.8%
Other values (30) 30
52.6%
2023-12-12T19:20:41.575184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 11
 
5.4%
씨 10
 
4.9%
8
 
3.9%
천 7
 
3.4%
영 7
 
3.4%
사 7
 
3.4%
시 6
 
2.9%
㈜ 6
 
2.9%
스 6
 
2.9%
종 5
 
2.4%
Other values (79) 132
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 182
88.8%
Space Separator 8
 
3.9%
Uppercase Letter 8
 
3.9%
Other Symbol 6
 
2.9%
Decimal Number 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 11
 
6.0%
씨 10
 
5.5%
천 7
 
3.8%
영 7
 
3.8%
사 7
 
3.8%
시 6
 
3.3%
스 6
 
3.3%
종 5
 
2.7%
김 5
 
2.7%
유 5
 
2.7%
Other values (74) 113
62.1%
Uppercase Letter
ValueCountFrequency (%)
G 4
50.0%
L 4
50.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 188
91.7%
Common 9
 
4.4%
Latin 8
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 11
 
5.9%
씨 10
 
5.3%
천 7
 
3.7%
영 7
 
3.7%
사 7
 
3.7%
시 6
 
3.2%
㈜ 6
 
3.2%
스 6
 
3.2%
종 5
 
2.7%
김 5
 
2.7%
Other values (75) 118
62.8%
Common
ValueCountFrequency (%)
8
88.9%
1 1
 
11.1%
Latin
ValueCountFrequency (%)
G 4
50.0%
L 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 182
88.8%
ASCII 17
 
8.3%
None 6
 
2.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 11
 
6.0%
씨 10
 
5.5%
천 7
 
3.8%
영 7
 
3.8%
사 7
 
3.8%
시 6
 
3.3%
스 6
 
3.3%
종 5
 
2.7%
김 5
 
2.7%
유 5
 
2.7%
Other values (74) 113
62.1%
ASCII
ValueCountFrequency (%)
8
47.1%
G 4
23.5%
L 4
23.5%
1 1
 
5.9%
None
ValueCountFrequency (%)
㈜ 6
100.0%

소재지
Text

Distinct42
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-12T19:20:41.866935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length20.122449
Min length13

Characters and Unicode

Total characters986
Distinct characters87
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)75.5%

Sample

1st row경기도 이천시 사음동 산24
2nd row경기도 이천시 경충대로2709번길388
3rd row경기도 이천시 마장면 장암리 183-4
4th row경기도 이천시 부악로 40
5th row경기도 이천시 백사면 신대리 산 32
ValueCountFrequency (%)
경기도 49
21.7%
이천시 49
21.7%
백사면 7
 
3.1%
관고동 5
 
2.2%
신둔면 4
 
1.8%
지산로 4
 
1.8%
167-72 4
 
1.8%
모가면 3
 
1.3%
부발읍 3
 
1.3%
마장면 3
 
1.3%
Other values (84) 95
42.0%
2023-12-12T19:20:42.340339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
177
18.0%
경 53
 
5.4%
도 52
 
5.3%
이 50
 
5.1%
기 49
 
5.0%
천 49
 
5.0%
시 49
 
5.0%
1 36
 
3.7%
2 30
 
3.0%
- 28
 
2.8%
Other values (77) 413
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 565
57.3%
Decimal Number 213
 
21.6%
Space Separator 177
 
18.0%
Dash Punctuation 28
 
2.8%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 53
 
9.4%
도 52
 
9.2%
이 50
 
8.8%
기 49
 
8.7%
천 49
 
8.7%
시 49
 
8.7%
리 25
 
4.4%
면 22
 
3.9%
로 19
 
3.4%
산 16
 
2.8%
Other values (62) 181
32.0%
Decimal Number
ValueCountFrequency (%)
1 36
16.9%
2 30
14.1%
4 27
12.7%
7 26
12.2%
3 25
11.7%
6 17
8.0%
0 17
8.0%
5 13
 
6.1%
8 12
 
5.6%
9 10
 
4.7%
Space Separator
ValueCountFrequency (%)
177
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 565
57.3%
Common 421
42.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 53
 
9.4%
도 52
 
9.2%
이 50
 
8.8%
기 49
 
8.7%
천 49
 
8.7%
시 49
 
8.7%
리 25
 
4.4%
면 22
 
3.9%
로 19
 
3.4%
산 16
 
2.8%
Other values (62) 181
32.0%
Common
ValueCountFrequency (%)
177
42.0%
1 36
 
8.6%
2 30
 
7.1%
- 28
 
6.7%
4 27
 
6.4%
7 26
 
6.2%
3 25
 
5.9%
6 17
 
4.0%
0 17
 
4.0%
5 13
 
3.1%
Other values (5) 25
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 565
57.3%
ASCII 421
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
177
42.0%
1 36
 
8.6%
2 30
 
7.1%
- 28
 
6.7%
4 27
 
6.4%
7 26
 
6.2%
3 25
 
5.9%
6 17
 
4.0%
0 17
 
4.0%
5 13
 
3.1%
Other values (5) 25
 
5.9%
Hangul
ValueCountFrequency (%)
경 53
 
9.4%
도 52
 
9.2%
이 50
 
8.8%
기 49
 
8.7%
천 49
 
8.7%
시 49
 
8.7%
리 25
 
4.4%
면 22
 
3.9%
로 19
 
3.4%
산 16
 
2.8%
Other values (62) 181
32.0%

지정일
Date

Distinct29
Distinct (%)59.2%
Missing0
Missing (%)0.0%
Memory size524.0 B
Minimum1908-08-28 00:00:00
Maximum2020-04-01 00:00:00
2023-12-12T19:20:42.500018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:20:42.644817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

관리자
Text

MISSING 

Distinct19
Distinct (%)50.0%
Missing11
Missing (%)22.4%
Memory size524.0 B
2023-12-12T19:20:42.842767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length3
Mean length4.7105263
Min length2

Characters and Unicode

Total characters179
Distinct characters53
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

Unique16 ?
Unique (%)42.1%

Sample

1st row이천시
2nd row영월암
3rd row이천시
4th row이천시
5th row이천시
ValueCountFrequency (%)
이천시 19
43.2%
군사시설보호구역 4
 
9.1%
영월암 3
 
6.8%
신흥사 1
 
2.3%
영월엄씨종중 1
 
2.3%
청풍김씨 1
 
2.3%
나주나씨 1
 
2.3%
광주이씨 1
 
2.3%
김해김씨 1
 
2.3%
대종회 1
 
2.3%
Other values (11) 11
25.0%
2023-12-12T19:20:43.163312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 23
 
12.8%
이 21
 
11.7%
천 20
 
11.2%
씨 9
 
5.0%
사 8
 
4.5%
6
 
3.4%
영 6
 
3.4%
군 5
 
2.8%
역 4
 
2.2%
월 4
 
2.2%
Other values (43) 73
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 173
96.6%
Space Separator 6
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 23
 
13.3%
이 21
 
12.1%
천 20
 
11.6%
씨 9
 
5.2%
사 8
 
4.6%
영 6
 
3.5%
군 5
 
2.9%
역 4
 
2.3%
월 4
 
2.3%
김 4
 
2.3%
Other values (42) 69
39.9%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 173
96.6%
Common 6
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 23
 
13.3%
이 21
 
12.1%
천 20
 
11.6%
씨 9
 
5.2%
사 8
 
4.6%
영 6
 
3.5%
군 5
 
2.9%
역 4
 
2.3%
월 4
 
2.3%
김 4
 
2.3%
Other values (42) 69
39.9%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 173
96.6%
ASCII 6
 
3.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 23
 
13.3%
이 21
 
12.1%
천 20
 
11.6%
씨 9
 
5.2%
사 8
 
4.6%
영 6
 
3.5%
군 5
 
2.9%
역 4
 
2.3%
월 4
 
2.3%
김 4
 
2.3%
Other values (42) 69
39.9%
ASCII
ValueCountFrequency (%)
6
100.0%

비고
Text

MISSING 

Distinct6
Distinct (%)85.7%
Missing42
Missing (%)85.7%
Memory size524.0 B
2023-12-12T19:20:43.336686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters21
Distinct characters19
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

Unique5 ?
Unique (%)71.4%

Sample

1st row광주요
2nd row벼루
3rd row벼루
4th row순백자
5th row목조각
ValueCountFrequency (%)
벼루 2
25.0%
광주요 1
12.5%
순백자 1
12.5%
목조각 1
12.5%
놀이와 1
12.5%
의식 1
12.5%
지화 1
12.5%
2023-12-12T19:20:43.664511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
벼 2
 
9.5%
루 2
 
9.5%
각 1
 
4.8%
지 1
 
4.8%
식 1
 
4.8%
의 1
 
4.8%
1
 
4.8%
와 1
 
4.8%
이 1
 
4.8%
놀 1
 
4.8%
Other values (9) 9
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20
95.2%
Space Separator 1
 
4.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
벼 2
 
10.0%
루 2
 
10.0%
각 1
 
5.0%
지 1
 
5.0%
식 1
 
5.0%
의 1
 
5.0%
와 1
 
5.0%
이 1
 
5.0%
놀 1
 
5.0%
조 1
 
5.0%
Other values (8) 8
40.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20
95.2%
Common 1
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
벼 2
 
10.0%
루 2
 
10.0%
각 1
 
5.0%
지 1
 
5.0%
식 1
 
5.0%
의 1
 
5.0%
와 1
 
5.0%
이 1
 
5.0%
놀 1
 
5.0%
조 1
 
5.0%
Other values (8) 8
40.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20
95.2%
ASCII 1
 
4.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
벼 2
 
10.0%
루 2
 
10.0%
각 1
 
5.0%
지 1
 
5.0%
식 1
 
5.0%
의 1
 
5.0%
와 1
 
5.0%
이 1
 
5.0%
놀 1
 
5.0%
조 1
 
5.0%
Other values (8) 8
40.0%
ASCII
ValueCountFrequency (%)
1
100.0%

Correlations

2023-12-12T19:20:43.796750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분지정번호문화재명수량소유자소재지지정일관리자비고
구분1.0001.0001.0000.0000.8810.9701.0000.4771.000
지정번호1.0001.0001.0001.0000.9450.9820.8711.0001.000
문화재명1.0001.0001.0001.0001.0001.0001.0001.0001.000
수량0.0001.0001.0001.0000.0001.0000.3540.487NaN
소유자0.8810.9451.0000.0001.0001.0000.9550.9901.000
소재지0.9700.9821.0001.0001.0001.0000.9960.9691.000
지정일1.0000.8711.0000.3540.9550.9961.0000.7481.000
관리자0.4771.0001.0000.4870.9900.9690.7481.000NaN
비고1.0001.0001.000NaN1.0001.0001.000NaN1.000
2023-12-12T19:20:43.934457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수량구분
수량1.0000.000
구분0.0001.000
2023-12-12T19:20:44.019932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분수량
구분1.0000.000
수량0.0001.000

Missing values

2023-12-12T19:20:38.662677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:20:38.846535image/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.
2023-12-12T19:20:38.978343image/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

구분지정번호문화재명수량소유자소재지지정일관리자비고
0국가지정유형문화재사적 제423호이천설봉산성1이천시경기도 이천시 사음동 산242000-09-16이천시<NA>
1국가지정유형문화재보물822호영월암마애여래입상1영월암경기도 이천시 경충대로2709번길3881984-12-02영월암<NA>
2국가지정유형문화재보물982호이천 장암리 마애보살반가상1국유경기도 이천시 마장면 장암리 183-41989-04-10이천시<NA>
3국가지정유형문화재보물제1573호청자양각연판문접시1이천시경기도 이천시 부악로 401908-08-28이천시<NA>
4국가지정유형문화재천연기념물 제253호이천백송1이천시경기도 이천시 백사면 신대리 산 321976-06-23이천시<NA>
5국가지정유형문화재천연기념물제381호반룡송1신동명경기도 이천시 백사면 도립리 201-11996-12-30이천시<NA>
6국가지정유형문화재중요민속자료제127호어재연장군생가1어 홍경기도 이천시 율면 일생로 897번길22-471984-01-10어홍<NA>
7도지정유형문화재유형문화재 제106호이천중리삼층석탑1국유경기도 이천시 서희로 271981-07-16이천시<NA>
8도지정유형문화재유형문화재 제107호이천어석리석불입상1은진송씨복초공파종중경기도 이천시 장호원읍 어석리 565-11981-07-16이천시<NA>
9도지정유형문화재유형문화재 제119호소고리마애여래좌상1㈜사우스스프링스경기도 이천시 모가면 소고리 640-71984-09-12이천시 군사시설보호구역<NA>
구분지정번호문화재명수량소유자소재지지정일관리자비고
39시지정유형문화재향토유적15호애련정1이천시경기도 이천시 안흥동 4041997-08-01이천시<NA>
40시지정유형문화재향토유적16호권균 묘역1안동권씨경기도 이천시 모가면 산내리 산33-11998-02-13안동권씨<NA>
41시지정유형문화재향토유적17호서신일 묘역1이천서씨 대종회경기도 이천시 부발읍 산촌리 산192007-09-20이천서씨 대종회<NA>
42시지정유형문화재향토유적18호설봉서원1이천시경기도 이천시 관고동 437-12007-09-20이천시<NA>
43시지정유형문화재향토유적19호설봉서원 절목1이천시경기도 이천시 관고동 437-12007-09-20이천시<NA>
44시지정유형문화재향토유적20호김해묘역1김해김씨경기도 이천시 백사면 도지리산332012-03-20김해김씨<NA>
45시지정유형문화재향토유적21호이점신도비1광주이씨경기도 이천시 마장면 관리 218-32012-03-20광주이씨<NA>
46시지정유형문화재향토유적22호숙의나주나씨 묘역 및 묘비4나주나씨경기도 이천시 부발읍 무촌리 산 4672015-01-05나주나씨<NA>
47시지정유형문화재향토유적23호청풍김씨 김길통 묘역 및 묘비1청풍김씨경기도 이천시 신둔면 수광리 398-92017-11-10청풍김씨<NA>
48시지정유형문화재향토유적24호오성리 조시한 정려각1풍양조씨경기도 이천시 율면 오성리 102-12020-04-01풍양조씨<NA>