Overview

Dataset statistics

Number of variables5
Number of observations636
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory25.0 KiB
Average record size in memory40.2 B

Variable types

DateTime1
Categorical3
Boolean1

Dataset

Description충청남도 청양군에 소재하는 청양군백제문화체험박물관의 휴관일에 관한 정보를 제공하는 데이터로 휴관일, 휴관명칭, 등록일자, 수정일자 등으로 되어 있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=380&beforeMenuCd=DOM_000000201001001000&publicdatapk=15062665

Alerts

삭제여부 has constant value ""Constant
수정일자 is highly overall correlated with 휴관명칭 and 1 other fieldsHigh correlation
등록일자 is highly overall correlated with 휴관명칭 and 1 other fieldsHigh correlation
휴관명칭 is highly overall correlated with 등록일자 and 1 other fieldsHigh correlation
휴관명칭 is highly imbalanced (94.1%)Imbalance
등록일자 is highly imbalanced (93.0%)Imbalance
수정일자 is highly imbalanced (93.0%)Imbalance
휴관일 has unique valuesUnique

Reproduction

Analysis started2024-01-09 19:58:16.484173
Analysis finished2024-01-09 19:58:16.950088
Duration0.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

휴관일
Date

UNIQUE 

Distinct636
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
Minimum2017-01-02 00:00:00
Maximum2028-12-25 00:00:00
2024-01-10T04:58:17.085525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:58:17.287327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴관명칭
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct8
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
휴관
624 
박물관 내부공사
 
6
추석 연휴
 
1
추석
 
1
대체휴관
 
1
Other values (3)
 
3

Length

Max length8
Median length2
Mean length2.0754717
Min length2

Unique

Unique6 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
휴관 624
98.1%
박물관 내부공사 6
 
0.9%
추석 연휴 1
 
0.2%
추석 1
 
0.2%
대체휴관 1
 
0.2%
추석휴관 1
 
0.2%
설 휴관 1
 
0.2%
대체 휴관 1
 
0.2%

Length

2024-01-10T04:58:17.519298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:58:17.722910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휴관 626
97.1%
박물관 6
 
0.9%
내부공사 6
 
0.9%
추석 2
 
0.3%
연휴 1
 
0.2%
대체휴관 1
 
0.2%
추석휴관 1
 
0.2%
설 1
 
0.2%
대체 1
 
0.2%

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size768.0 B
False
636 
ValueCountFrequency (%)
False 636
100.0%
2024-01-10T04:58:17.883475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

등록일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct11
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2017-03-28
620 
2019-12-10
 
6
2020-01-16
 
2
2017-09-14
 
1
2017-06-21
 
1
Other values (6)
 
6

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique8 ?
Unique (%)1.3%

Sample

1st row2017-03-28
2nd row2017-03-28
3rd row2017-03-28
4th row2017-03-28
5th row2017-03-28

Common Values

ValueCountFrequency (%)
2017-03-28 620
97.5%
2019-12-10 6
 
0.9%
2020-01-16 2
 
0.3%
2017-09-14 1
 
0.2%
2017-06-21 1
 
0.2%
2017-09-19 1
 
0.2%
2017-12-20 1
 
0.2%
2018-01-02 1
 
0.2%
2018-05-02 1
 
0.2%
2019-05-03 1
 
0.2%

Length

2024-01-10T04:58:18.038857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2017-03-28 620
97.5%
2019-12-10 6
 
0.9%
2020-01-16 2
 
0.3%
2017-09-14 1
 
0.2%
2017-06-21 1
 
0.2%
2017-09-19 1
 
0.2%
2017-12-20 1
 
0.2%
2018-01-02 1
 
0.2%
2018-05-02 1
 
0.2%
2019-05-03 1
 
0.2%

수정일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct11
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2017-03-28
620 
2019-12-10
 
6
2020-01-16
 
2
2017-09-14
 
1
2017-06-21
 
1
Other values (6)
 
6

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique8 ?
Unique (%)1.3%

Sample

1st row2017-03-28
2nd row2017-03-28
3rd row2017-03-28
4th row2017-03-28
5th row2017-03-28

Common Values

ValueCountFrequency (%)
2017-03-28 620
97.5%
2019-12-10 6
 
0.9%
2020-01-16 2
 
0.3%
2017-09-14 1
 
0.2%
2017-06-21 1
 
0.2%
2017-09-19 1
 
0.2%
2017-12-20 1
 
0.2%
2018-01-02 1
 
0.2%
2018-05-02 1
 
0.2%
2019-05-03 1
 
0.2%

Length

2024-01-10T04:58:18.243124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2017-03-28 620
97.5%
2019-12-10 6
 
0.9%
2020-01-16 2
 
0.3%
2017-09-14 1
 
0.2%
2017-06-21 1
 
0.2%
2017-09-19 1
 
0.2%
2017-12-20 1
 
0.2%
2018-01-02 1
 
0.2%
2018-05-02 1
 
0.2%
2019-05-03 1
 
0.2%

Correlations

2024-01-10T04:58:18.368053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
휴관명칭등록일자수정일자
휴관명칭1.0000.9730.973
등록일자0.9731.0001.000
수정일자0.9731.0001.000
2024-01-10T04:58:18.519618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수정일자등록일자휴관명칭
수정일자1.0001.0000.922
등록일자1.0001.0000.922
휴관명칭0.9220.9221.000
2024-01-10T04:58:18.656961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
휴관명칭등록일자수정일자
휴관명칭1.0000.9220.922
등록일자0.9221.0001.000
수정일자0.9221.0001.000

Missing values

2024-01-10T04:58:16.733931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T04:58:16.892254image/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

휴관일휴관명칭삭제여부등록일자수정일자
02017-01-02휴관N2017-03-282017-03-28
12017-01-09휴관N2017-03-282017-03-28
22017-01-16휴관N2017-03-282017-03-28
32017-01-23휴관N2017-03-282017-03-28
42017-01-30휴관N2017-03-282017-03-28
52017-02-06휴관N2017-03-282017-03-28
62017-02-13휴관N2017-03-282017-03-28
72017-02-20휴관N2017-03-282017-03-28
82017-02-27휴관N2017-03-282017-03-28
92017-03-06휴관N2017-03-282017-03-28
휴관일휴관명칭삭제여부등록일자수정일자
6262028-10-23휴관N2017-03-282017-03-28
6272028-10-30휴관N2017-03-282017-03-28
6282028-11-06휴관N2017-03-282017-03-28
6292028-11-13휴관N2017-03-282017-03-28
6302028-11-20휴관N2017-03-282017-03-28
6312028-11-27휴관N2017-03-282017-03-28
6322028-12-04휴관N2017-03-282017-03-28
6332028-12-11휴관N2017-03-282017-03-28
6342028-12-18휴관N2017-03-282017-03-28
6352028-12-25휴관N2017-03-282017-03-28