Overview

Dataset statistics

Number of variables7
Number of observations43
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory59.1 B

Variable types

Categorical3
Text3
DateTime1

Dataset

Description부산 동래구 관내 문화재 현황에 대한 데이터로 종류, 종별, 문화재명, 지정번호, 지정일, 소재지 정보, 관리주체 등의 항목을 제공합니다.
Author부산광역시 동래구
URLhttps://www.data.go.kr/data/15032284/fileData.do

Alerts

관리주체 has constant value ""Constant
종별 is highly overall correlated with 종류High correlation
종류 is highly overall correlated with 종별High correlation
종류 is highly imbalanced (52.3%)Imbalance
문화재명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:55:13.607357
Analysis finished2023-12-12 08:55:14.213905
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
시지정문화재
35 
국가지정문화재
시문화재자료
 
3
국가등록문화재
 
1

Length

Max length7
Median length6
Mean length6.1162791
Min length6

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row국가지정문화재
2nd row국가지정문화재
3rd row국가지정문화재
4th row국가지정문화재
5th row시지정문화재

Common Values

ValueCountFrequency (%)
시지정문화재 35
81.4%
국가지정문화재 4
 
9.3%
시문화재자료 3
 
7.0%
국가등록문화재 1
 
2.3%

Length

2023-12-12T17:55:14.291233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:55:14.417945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시지정문화재 35
81.4%
국가지정문화재 4
 
9.3%
시문화재자료 3
 
7.0%
국가등록문화재 1
 
2.3%

종별
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Memory size476.0 B
유형문화재
16 
무형문화재
기념물
민속자료
문화재자료
Other values (4)

Length

Max length7
Median length5
Mean length4.5813953
Min length3

Unique

Unique3 ?
Unique (%)7.0%

Sample

1st row국가보물
2nd row국가사적
3rd row국가사적
4th row중요무형문화재
5th row유형문화재

Common Values

ValueCountFrequency (%)
유형문화재 16
37.2%
무형문화재 8
18.6%
기념물 8
18.6%
민속자료 3
 
7.0%
문화재자료 3
 
7.0%
국가사적 2
 
4.7%
국가보물 1
 
2.3%
중요무형문화재 1
 
2.3%
국가등록문화재 1
 
2.3%

Length

2023-12-12T17:55:14.565301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:55:14.702463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유형문화재 16
37.2%
무형문화재 8
18.6%
기념물 8
18.6%
민속자료 3
 
7.0%
문화재자료 3
 
7.0%
국가사적 2
 
4.7%
국가보물 1
 
2.3%
중요무형문화재 1
 
2.3%
국가등록문화재 1
 
2.3%
Distinct33
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-12T17:55:14.908733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4
Min length3

Characters and Unicode

Total characters172
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

Unique25 ?
Unique (%)58.1%

Sample

1st row제2020호
2nd row제192호
3rd row제273호
4th row제18호
5th row제1호
ValueCountFrequency (%)
제4호 3
 
7.0%
제5호 3
 
7.0%
제8호 2
 
4.7%
제21호 2
 
4.7%
제14호 2
 
4.7%
제16호 2
 
4.7%
제128호 2
 
4.7%
제3호 2
 
4.7%
제61호 1
 
2.3%
제2020호 1
 
2.3%
Other values (23) 23
53.5%
2023-12-12T17:55:15.289585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43
25.0%
43
25.0%
1 25
14.5%
2 11
 
6.4%
6 10
 
5.8%
3 9
 
5.2%
5 8
 
4.7%
4 6
 
3.5%
8 5
 
2.9%
9 4
 
2.3%
Other values (2) 8
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 86
50.0%
Decimal Number 86
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 25
29.1%
2 11
12.8%
6 10
 
11.6%
3 9
 
10.5%
5 8
 
9.3%
4 6
 
7.0%
8 5
 
5.8%
9 4
 
4.7%
7 4
 
4.7%
0 4
 
4.7%
Other Letter
ValueCountFrequency (%)
43
50.0%
43
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 86
50.0%
Common 86
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 25
29.1%
2 11
12.8%
6 10
 
11.6%
3 9
 
10.5%
5 8
 
9.3%
4 6
 
7.0%
8 5
 
5.8%
9 4
 
4.7%
7 4
 
4.7%
0 4
 
4.7%
Hangul
ValueCountFrequency (%)
43
50.0%
43
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 86
50.0%
ASCII 86
50.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
43
50.0%
43
50.0%
ASCII
ValueCountFrequency (%)
1 25
29.1%
2 11
12.8%
6 10
 
11.6%
3 9
 
10.5%
5 8
 
9.3%
4 6
 
7.0%
8 5
 
5.8%
9 4
 
4.7%
7 4
 
4.7%
0 4
 
4.7%

문화재명
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-12T17:55:15.508580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length13
Mean length7.3023256
Min length3

Characters and Unicode

Total characters314
Distinct characters126
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)100.0%

Sample

1st row부산 복천동 38호분 출토 철제갑옷 일괄
2nd row부산동래 패총
3rd row부산복천동고분군
4th row동래야류
5th row동래부 동헌 충신당
ValueCountFrequency (%)
동래향교 4
 
5.8%
부산 2
 
2.9%
동래영 2
 
2.9%
동헌 2
 
2.9%
동래부 2
 
2.9%
갑주 2
 
2.9%
자비암 2
 
2.9%
송공단 1
 
1.4%
임진동래의총 1
 
1.4%
동래한량춤 1
 
1.4%
Other values (50) 50
72.5%
2023-12-12T17:55:15.820984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26
 
8.3%
25
 
8.0%
23
 
7.3%
8
 
2.5%
8
 
2.5%
7
 
2.2%
5
 
1.6%
5
 
1.6%
5
 
1.6%
5
 
1.6%
Other values (116) 197
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 284
90.4%
Space Separator 26
 
8.3%
Decimal Number 2
 
0.6%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
25
 
8.8%
23
 
8.1%
8
 
2.8%
8
 
2.8%
7
 
2.5%
5
 
1.8%
5
 
1.8%
5
 
1.8%
5
 
1.8%
5
 
1.8%
Other values (111) 188
66.2%
Decimal Number
ValueCountFrequency (%)
8 1
50.0%
3 1
50.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 284
90.4%
Common 30
 
9.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
25
 
8.8%
23
 
8.1%
8
 
2.8%
8
 
2.8%
7
 
2.5%
5
 
1.8%
5
 
1.8%
5
 
1.8%
5
 
1.8%
5
 
1.8%
Other values (111) 188
66.2%
Common
ValueCountFrequency (%)
26
86.7%
) 1
 
3.3%
( 1
 
3.3%
8 1
 
3.3%
3 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 284
90.4%
ASCII 30
 
9.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26
86.7%
) 1
 
3.3%
( 1
 
3.3%
8 1
 
3.3%
3 1
 
3.3%
Hangul
ValueCountFrequency (%)
25
 
8.8%
23
 
8.1%
8
 
2.8%
8
 
2.8%
7
 
2.5%
5
 
1.8%
5
 
1.8%
5
 
1.8%
5
 
1.8%
5
 
1.8%
Other values (111) 188
66.2%
Distinct31
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-12T17:55:16.083071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length33
Mean length29.209302
Min length18

Characters and Unicode

Total characters1256
Distinct characters83
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

Unique25 ?
Unique (%)58.1%

Sample

1st row부산광역시 동래구 복천로 63(복천동, 복천박물관)
2nd row부산광역시 동래구 온천천로319번길60 (낙민동)
3rd row부산광역시 동래구 복천로 66 (복천동)
4th row부산광역시 동래구 우장춘로 195-46 (온천동,부산민속예술보존협회)
5th row부산광역시 동래구 명륜로112번길 61 (수안동)
ValueCountFrequency (%)
부산광역시 43
18.9%
동래구 43
18.9%
온천동 11
 
4.8%
안락동 11
 
4.8%
복천동 5
 
2.2%
수안동 5
 
2.2%
충렬대로345 5
 
2.2%
우장춘로195-46 4
 
1.8%
명륜동 4
 
1.8%
우장춘로 4
 
1.8%
Other values (61) 92
40.5%
2023-12-12T17:55:16.592258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
185
 
14.7%
93
 
7.4%
50
 
4.0%
50
 
4.0%
48
 
3.8%
44
 
3.5%
43
 
3.4%
43
 
3.4%
43
 
3.4%
1 39
 
3.1%
Other values (73) 618
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 786
62.6%
Space Separator 185
 
14.7%
Decimal Number 165
 
13.1%
Open Punctuation 39
 
3.1%
Close Punctuation 39
 
3.1%
Other Punctuation 25
 
2.0%
Dash Punctuation 17
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
93
 
11.8%
50
 
6.4%
50
 
6.4%
48
 
6.1%
44
 
5.6%
43
 
5.5%
43
 
5.5%
43
 
5.5%
38
 
4.8%
28
 
3.6%
Other values (58) 306
38.9%
Decimal Number
ValueCountFrequency (%)
1 39
23.6%
5 22
13.3%
3 21
12.7%
4 20
12.1%
6 20
12.1%
2 20
12.1%
9 8
 
4.8%
7 7
 
4.2%
0 7
 
4.2%
8 1
 
0.6%
Space Separator
ValueCountFrequency (%)
185
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Other Punctuation
ValueCountFrequency (%)
, 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 786
62.6%
Common 470
37.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
93
 
11.8%
50
 
6.4%
50
 
6.4%
48
 
6.1%
44
 
5.6%
43
 
5.5%
43
 
5.5%
43
 
5.5%
38
 
4.8%
28
 
3.6%
Other values (58) 306
38.9%
Common
ValueCountFrequency (%)
185
39.4%
1 39
 
8.3%
( 39
 
8.3%
) 39
 
8.3%
, 25
 
5.3%
5 22
 
4.7%
3 21
 
4.5%
4 20
 
4.3%
6 20
 
4.3%
2 20
 
4.3%
Other values (5) 40
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 786
62.6%
ASCII 470
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
185
39.4%
1 39
 
8.3%
( 39
 
8.3%
) 39
 
8.3%
, 25
 
5.3%
5 22
 
4.7%
3 21
 
4.5%
4 20
 
4.3%
6 20
 
4.3%
2 20
 
4.3%
Other values (5) 40
 
8.5%
Hangul
ValueCountFrequency (%)
93
 
11.8%
50
 
6.4%
50
 
6.4%
48
 
6.1%
44
 
5.6%
43
 
5.5%
43
 
5.5%
43
 
5.5%
38
 
4.8%
28
 
3.6%
Other values (58) 306
38.9%
Distinct24
Distinct (%)55.8%
Missing0
Missing (%)0.0%
Memory size476.0 B
Minimum1967-12-21 00:00:00
Maximum2023-05-24 00:00:00
2023-12-12T17:55:16.752803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:55:16.943288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

관리주체
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
43 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
43
100.0%

Length

2023-12-12T17:55:17.104959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:55:17.227337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
43
100.0%

Correlations

2023-12-12T17:55:17.309092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종류종별지정번호문화재명소재지지정일자
종류1.0001.0000.9701.0001.0000.980
종별1.0001.0000.8711.0000.9920.970
지정번호0.9700.8711.0001.0000.8690.688
문화재명1.0001.0001.0001.0001.0001.000
소재지1.0000.9920.8691.0001.0000.975
지정일자0.9800.9700.6881.0000.9751.000
2023-12-12T17:55:17.458911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종별종류
종별1.0000.934
종류0.9341.000
2023-12-12T17:55:17.549965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종류종별
종류1.0000.934
종별0.9341.000

Missing values

2023-12-12T17:55:14.021571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:55:14.161308image/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.

Sample

종류종별지정번호문화재명소재지지정일자관리주체
0국가지정문화재국가보물제2020호부산 복천동 38호분 출토 철제갑옷 일괄부산광역시 동래구 복천로 63(복천동, 복천박물관)2019-03-06
1국가지정문화재국가사적제192호부산동래 패총부산광역시 동래구 온천천로319번길60 (낙민동)1970-04-25
2국가지정문화재국가사적제273호부산복천동고분군부산광역시 동래구 복천로 66 (복천동)1981-06-09
3국가지정문화재중요무형문화재제18호동래야류부산광역시 동래구 우장춘로 195-46 (온천동,부산민속예술보존협회)1967-12-21
4시지정문화재유형문화재제1호동래부 동헌 충신당부산광역시 동래구 명륜로112번길 61 (수안동)1972-06-26
5시지정문화재유형문화재제4호망미루부산광역시 동래구 명륜로112번길 61 (수안동)1972-06-26
6시지정문화재유형문화재제5호동래부 동헌 외대문부산광역시 동래구 명륜로112번길 61 (수안동)1972-06-26
7시지정문화재유형문화재제6호동래향교 대성전부산광역시 동래구 동래로 103 (명륜동)1972-06-26
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