Overview

Dataset statistics

Number of variables7
Number of observations42
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory59.1 B

Variable types

Categorical3
Text3
DateTime1

Dataset

Description부산광역시_동래구_문화재현황_20220913
Author부산광역시 동래구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15032284

Alerts

관리주체 has constant value ""Constant
종류 is highly overall correlated with 종별High correlation
종별 is highly overall correlated with 종류High correlation
종류 is highly imbalanced (56.0%)Imbalance
문화재명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:48:36.059231
Analysis finished2023-12-10 17:48:37.204029
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size468.0 B
시지정문화재
35 
국가지정문화재
시문화재자료
 
2
국가등록문화재
 
1

Length

Max length7
Median length6
Mean length6.1190476
Min length6

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
시지정문화재 35
83.3%
국가지정문화재 4
 
9.5%
시문화재자료 2
 
4.8%
국가등록문화재 1
 
2.4%

Length

2023-12-11T02:48:37.376871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:48:37.682853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시지정문화재 35
83.3%
국가지정문화재 4
 
9.5%
시문화재자료 2
 
4.8%
국가등록문화재 1
 
2.4%

종별
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
유형문화재
16 
무형문화재
기념물
민속자료
국가사적
Other values (4)

Length

Max length7
Median length5
Mean length4.5
Min length3

Unique

Unique3 ?
Unique (%)7.1%

Sample

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

Common Values

ValueCountFrequency (%)
유형문화재 16
38.1%
무형문화재 8
19.0%
기념물 8
19.0%
민속자료 3
 
7.1%
국가사적 2
 
4.8%
문화재자료 2
 
4.8%
국가보물 1
 
2.4%
중요무형문화재 1
 
2.4%
<NA> 1
 
2.4%

Length

2023-12-11T02:48:38.058549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:48:38.408323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유형문화재 16
38.1%
무형문화재 8
19.0%
기념물 8
19.0%
민속자료 3
 
7.1%
국가사적 2
 
4.8%
문화재자료 2
 
4.8%
국가보물 1
 
2.4%
중요무형문화재 1
 
2.4%
na 1
 
2.4%
Distinct33
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-11T02:48:38.898523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.9761905
Min length3

Characters and Unicode

Total characters167
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

Unique26 ?
Unique (%)61.9%

Sample

1st row제2020호
2nd row제192호
3rd row제273호
4th row제18호
5th row제1호
ValueCountFrequency (%)
제5호 3
 
7.1%
제4호 3
 
7.1%
제8호 2
 
4.8%
제14호 2
 
4.8%
제16호 2
 
4.8%
제21호 2
 
4.8%
제3호 2
 
4.8%
제11호 1
 
2.4%
제2020호 1
 
2.4%
제69호 1
 
2.4%
Other values (23) 23
54.8%
2023-12-11T02:48:39.690979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
25.1%
42
25.1%
1 24
14.4%
6 10
 
6.0%
2 10
 
6.0%
3 9
 
5.4%
5 8
 
4.8%
4 6
 
3.6%
8 4
 
2.4%
9 4
 
2.4%
Other values (2) 8
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84
50.3%
Decimal Number 83
49.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24
28.9%
6 10
12.0%
2 10
12.0%
3 9
 
10.8%
5 8
 
9.6%
4 6
 
7.2%
8 4
 
4.8%
9 4
 
4.8%
7 4
 
4.8%
0 4
 
4.8%
Other Letter
ValueCountFrequency (%)
42
50.0%
42
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 84
50.3%
Common 83
49.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 24
28.9%
6 10
12.0%
2 10
12.0%
3 9
 
10.8%
5 8
 
9.6%
4 6
 
7.2%
8 4
 
4.8%
9 4
 
4.8%
7 4
 
4.8%
0 4
 
4.8%
Hangul
ValueCountFrequency (%)
42
50.0%
42
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 84
50.3%
ASCII 83
49.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
42
50.0%
42
50.0%
ASCII
ValueCountFrequency (%)
1 24
28.9%
6 10
12.0%
2 10
12.0%
3 9
 
10.8%
5 8
 
9.6%
4 6
 
7.2%
8 4
 
4.8%
9 4
 
4.8%
7 4
 
4.8%
0 4
 
4.8%

문화재명
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-11T02:48:40.186673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length11.5
Mean length6.9047619
Min length3

Characters and Unicode

Total characters290
Distinct characters112
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

Unique42 ?
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
 
5.9%
부산 2
 
2.9%
동래부 2
 
2.9%
자비암 2
 
2.9%
갑주 2
 
2.9%
동헌 2
 
2.9%
동래영 2
 
2.9%
온정개건비 1
 
1.5%
임진동래의총 1
 
1.5%
동래학춤 1
 
1.5%
Other values (49) 49
72.1%
2023-12-11T02:48:41.247928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26
 
9.0%
25
 
8.6%
22
 
7.6%
8
 
2.8%
8
 
2.8%
7
 
2.4%
5
 
1.7%
5
 
1.7%
5
 
1.7%
5
 
1.7%
Other values (102) 174
60.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 262
90.3%
Space Separator 26
 
9.0%
Decimal Number 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
25
 
9.5%
22
 
8.4%
8
 
3.1%
8
 
3.1%
7
 
2.7%
5
 
1.9%
5
 
1.9%
5
 
1.9%
5
 
1.9%
4
 
1.5%
Other values (99) 168
64.1%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
8 1
50.0%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 262
90.3%
Common 28
 
9.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
25
 
9.5%
22
 
8.4%
8
 
3.1%
8
 
3.1%
7
 
2.7%
5
 
1.9%
5
 
1.9%
5
 
1.9%
5
 
1.9%
4
 
1.5%
Other values (99) 168
64.1%
Common
ValueCountFrequency (%)
26
92.9%
3 1
 
3.6%
8 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 262
90.3%
ASCII 28
 
9.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26
92.9%
3 1
 
3.6%
8 1
 
3.6%
Hangul
ValueCountFrequency (%)
25
 
9.5%
22
 
8.4%
8
 
3.1%
8
 
3.1%
7
 
2.7%
5
 
1.9%
5
 
1.9%
5
 
1.9%
5
 
1.9%
4
 
1.5%
Other values (99) 168
64.1%
Distinct30
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-11T02:48:41.958920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length34
Mean length29.142857
Min length18

Characters and Unicode

Total characters1224
Distinct characters81
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

Unique24 ?
Unique (%)57.1%

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 42
18.9%
동래구 42
18.9%
온천동 11
 
5.0%
안락동 11
 
5.0%
수안동 5
 
2.3%
충렬대로345 5
 
2.3%
복천동 5
 
2.3%
우장춘로195-46 4
 
1.8%
부산민속예술보존협회 4
 
1.8%
명륜로112번길 4
 
1.8%
Other values (59) 89
40.1%
2023-12-11T02:48:42.995025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
181
 
14.8%
91
 
7.4%
49
 
4.0%
49
 
4.0%
47
 
3.8%
43
 
3.5%
42
 
3.4%
42
 
3.4%
42
 
3.4%
) 38
 
3.1%
Other values (71) 600
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 768
62.7%
Space Separator 181
 
14.8%
Decimal Number 159
 
13.0%
Close Punctuation 38
 
3.1%
Open Punctuation 38
 
3.1%
Other Punctuation 24
 
2.0%
Dash Punctuation 16
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
91
 
11.8%
49
 
6.4%
49
 
6.4%
47
 
6.1%
43
 
5.6%
42
 
5.5%
42
 
5.5%
42
 
5.5%
37
 
4.8%
27
 
3.5%
Other values (56) 299
38.9%
Decimal Number
ValueCountFrequency (%)
1 37
23.3%
5 21
13.2%
3 21
13.2%
2 20
12.6%
6 20
12.6%
4 19
11.9%
9 8
 
5.0%
0 7
 
4.4%
7 5
 
3.1%
8 1
 
0.6%
Space Separator
ValueCountFrequency (%)
181
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 768
62.7%
Common 456
37.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
91
 
11.8%
49
 
6.4%
49
 
6.4%
47
 
6.1%
43
 
5.6%
42
 
5.5%
42
 
5.5%
42
 
5.5%
37
 
4.8%
27
 
3.5%
Other values (56) 299
38.9%
Common
ValueCountFrequency (%)
181
39.7%
) 38
 
8.3%
( 38
 
8.3%
1 37
 
8.1%
, 24
 
5.3%
5 21
 
4.6%
3 21
 
4.6%
2 20
 
4.4%
6 20
 
4.4%
4 19
 
4.2%
Other values (5) 37
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 768
62.7%
ASCII 456
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
181
39.7%
) 38
 
8.3%
( 38
 
8.3%
1 37
 
8.1%
, 24
 
5.3%
5 21
 
4.6%
3 21
 
4.6%
2 20
 
4.4%
6 20
 
4.4%
4 19
 
4.2%
Other values (5) 37
 
8.1%
Hangul
ValueCountFrequency (%)
91
 
11.8%
49
 
6.4%
49
 
6.4%
47
 
6.1%
43
 
5.6%
42
 
5.5%
42
 
5.5%
42
 
5.5%
37
 
4.8%
27
 
3.5%
Other values (56) 299
38.9%
Distinct23
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
Minimum1967-12-21 00:00:00
Maximum2019-06-05 00:00:00
2023-12-11T02:48:43.306263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:48:43.720545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

관리주체
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
42 

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 (%)
42
100.0%

Length

2023-12-11T02:48:44.043840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:48:44.939082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
42
100.0%

Correlations

2023-12-11T02:48:45.179037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종류종별지정번호문화재명소재지지정일자
종류1.0001.0001.0001.0001.0000.909
종별1.0001.0000.8761.0000.9890.949
지정번호1.0000.8761.0001.0000.8680.673
문화재명1.0001.0001.0001.0001.0001.000
소재지1.0000.9890.8681.0001.0000.972
지정일자0.9090.9490.6731.0000.9721.000
2023-12-11T02:48:45.491294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종류종별
종류1.0000.932
종별0.9321.000
2023-12-11T02:48:45.687895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종류종별
종류1.0000.932
종별0.9321.000

Missing values

2023-12-11T02:48:36.855616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:48:37.109969image/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
8시지정문화재유형문화재제7호충렬사부산광역시 동래구 충렬대로345 (안락동)1972-06-26
9시지정문화재유형문화재제8호동래 장관청부산광역시 동래구 명륜로94번길 36-6 (수안동)1972-06-26
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