Overview

Dataset statistics

Number of variables9
Number of observations325
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.6 KiB
Average record size in memory74.4 B

Variable types

Numeric2
Categorical5
Text2

Dataset

Description제주특별자치도에서 지정하는 문화재위원의 임기연도, 위원분류, 구분, 위원명, 전공분야, 임기시작일, 임기완료일 정보를 제공합니다.
Author제주특별자치도
URLhttps://www.data.go.kr/data/15062348/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
임기시작일 is highly overall correlated with 임기시작연도 and 2 other fieldsHigh correlation
임기완료일 is highly overall correlated with 임기시작연도 and 2 other fieldsHigh correlation
임기시작연도 is highly overall correlated with 임기종료연도 and 2 other fieldsHigh correlation
임기종료연도 is highly overall correlated with 임기시작연도 and 2 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 09:22:38.841758
Analysis finished2023-12-12 09:22:40.363907
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

임기시작연도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2010.5108
Minimum2006
Maximum2016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-12T18:22:40.419243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2006
5-th percentile2006
Q12008
median2010
Q32014
95-th percentile2016
Maximum2016
Range10
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.1929766
Coefficient of variation (CV)0.001588142
Kurtosis-1.1630888
Mean2010.5108
Median Absolute Deviation (MAD)2
Skewness0.084634674
Sum653416
Variance10.1951
MonotonicityIncreasing
2023-12-12T18:22:40.573946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2006 60
18.5%
2012 60
18.5%
2008 59
18.2%
2010 59
18.2%
2014 59
18.2%
2016 28
8.6%
ValueCountFrequency (%)
2006 60
18.5%
2008 59
18.2%
2010 59
18.2%
2012 60
18.5%
2014 59
18.2%
2016 28
8.6%
ValueCountFrequency (%)
2016 28
8.6%
2014 59
18.2%
2012 60
18.5%
2010 59
18.2%
2008 59
18.2%
2006 60
18.5%

임기종료연도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2012.5108
Minimum2008
Maximum2018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-12T18:22:40.734035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2008
5-th percentile2008
Q12010
median2012
Q32016
95-th percentile2018
Maximum2018
Range10
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.1929766
Coefficient of variation (CV)0.0015865637
Kurtosis-1.1630888
Mean2012.5108
Median Absolute Deviation (MAD)2
Skewness0.084634674
Sum654066
Variance10.1951
MonotonicityIncreasing
2023-12-12T18:22:40.889030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2008 60
18.5%
2014 60
18.5%
2010 59
18.2%
2012 59
18.2%
2016 59
18.2%
2018 28
8.6%
ValueCountFrequency (%)
2008 60
18.5%
2010 59
18.2%
2012 59
18.2%
2014 60
18.5%
2016 59
18.2%
2018 28
8.6%
ValueCountFrequency (%)
2018 28
8.6%
2016 59
18.2%
2014 60
18.5%
2012 59
18.2%
2010 59
18.2%
2008 60
18.5%

위원분류
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
문화재위원
177 
전문위원
148 

Length

Max length5
Median length5
Mean length4.5446154
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
문화재위원 177
54.5%
전문위원 148
45.5%

Length

2023-12-12T18:22:41.041358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:22:41.179583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화재위원 177
54.5%
전문위원 148
45.5%

구분
Categorical

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
제1분과(유형)
109 
제2분과(무형)
108 
제3분과(기념물)
108 

Length

Max length9
Median length8
Mean length8.3323077
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제1분과(유형)
2nd row제1분과(유형)
3rd row제1분과(유형)
4th row제1분과(유형)
5th row제1분과(유형)

Common Values

ValueCountFrequency (%)
제1분과(유형) 109
33.5%
제2분과(무형) 108
33.2%
제3분과(기념물) 108
33.2%

Length

2023-12-12T18:22:41.334461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:22:41.470912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제1분과(유형 109
33.5%
제2분과(무형 108
33.2%
제3분과(기념물 108
33.2%

위원명
Text

Distinct144
Distinct (%)44.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-12T18:22:41.905603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0030769
Min length3

Characters and Unicode

Total characters976
Distinct characters135
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

Unique63 ?
Unique (%)19.4%

Sample

1st row홍순만
2nd row고창석
3rd row김석윤
4th row김익수
5th row김찬흡
ValueCountFrequency (%)
고창석 6
 
1.8%
변성구 5
 
1.5%
부애진 5
 
1.5%
최광식 5
 
1.5%
박찬식 5
 
1.5%
김미영 5
 
1.5%
현승환 5
 
1.5%
고재원 5
 
1.5%
임춘배 5
 
1.5%
오창명 5
 
1.5%
Other values (135) 276
84.4%
2023-12-12T18:22:42.556462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 86
 
8.8%
석 30
 
3.1%
영 27
 
2.8%
고 23
 
2.4%
현 23
 
2.4%
강 23
 
2.4%
식 22
 
2.3%
문 21
 
2.2%
재 20
 
2.0%
창 20
 
2.0%
Other values (125) 681
69.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 974
99.8%
Space Separator 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 86
 
8.8%
석 30
 
3.1%
영 27
 
2.8%
고 23
 
2.4%
현 23
 
2.4%
강 23
 
2.4%
식 22
 
2.3%
문 21
 
2.2%
재 20
 
2.1%
창 20
 
2.1%
Other values (124) 679
69.7%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 974
99.8%
Common 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 86
 
8.8%
석 30
 
3.1%
영 27
 
2.8%
고 23
 
2.4%
현 23
 
2.4%
강 23
 
2.4%
식 22
 
2.3%
문 21
 
2.2%
재 20
 
2.1%
창 20
 
2.1%
Other values (124) 679
69.7%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 974
99.8%
ASCII 2
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 86
 
8.8%
석 30
 
3.1%
영 27
 
2.8%
고 23
 
2.4%
현 23
 
2.4%
강 23
 
2.4%
식 22
 
2.3%
문 21
 
2.2%
재 20
 
2.1%
창 20
 
2.1%
Other values (124) 679
69.7%
ASCII
ValueCountFrequency (%)
2
100.0%

전공분야
Text

Distinct84
Distinct (%)25.8%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-12T18:22:42.905636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.5784615
Min length2

Characters and Unicode

Total characters838
Distinct characters87
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

Unique42 ?
Unique (%)12.9%

Sample

1st row향토사
2nd row역사
3rd row건축
4th row향토사(전적)
5th row향토사
ValueCountFrequency (%)
역사 24
 
7.4%
민속 22
 
6.7%
식물 21
 
6.4%
건축 18
 
5.5%
민요 16
 
4.9%
공예 15
 
4.6%
고고 14
 
4.3%
고고학 11
 
3.4%
복식 10
 
3.1%
방언 9
 
2.8%
Other values (73) 166
50.9%
2023-12-12T18:22:43.430929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
고 69
 
8.2%
사 56
 
6.7%
민 42
 
5.0%
식 37
 
4.4%
물 37
 
4.4%
역 30
 
3.6%
속 28
 
3.3%
건 26
 
3.1%
축 26
 
3.1%
조 23
 
2.7%
Other values (77) 464
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 794
94.7%
Open Punctuation 20
 
2.4%
Close Punctuation 20
 
2.4%
Uppercase Letter 3
 
0.4%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 69
 
8.7%
사 56
 
7.1%
민 42
 
5.3%
식 37
 
4.7%
물 37
 
4.7%
역 30
 
3.8%
속 28
 
3.5%
건 26
 
3.3%
축 26
 
3.3%
조 23
 
2.9%
Other values (71) 420
52.9%
Uppercase Letter
ValueCountFrequency (%)
O 1
33.3%
G 1
33.3%
N 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 794
94.7%
Common 41
 
4.9%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 69
 
8.7%
사 56
 
7.1%
민 42
 
5.3%
식 37
 
4.7%
물 37
 
4.7%
역 30
 
3.8%
속 28
 
3.5%
건 26
 
3.3%
축 26
 
3.3%
조 23
 
2.9%
Other values (71) 420
52.9%
Common
ValueCountFrequency (%)
( 20
48.8%
) 20
48.8%
1
 
2.4%
Latin
ValueCountFrequency (%)
O 1
33.3%
G 1
33.3%
N 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 794
94.7%
ASCII 44
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
고 69
 
8.7%
사 56
 
7.1%
민 42
 
5.3%
식 37
 
4.7%
물 37
 
4.7%
역 30
 
3.8%
속 28
 
3.5%
건 26
 
3.3%
축 26
 
3.3%
조 23
 
2.9%
Other values (71) 420
52.9%
ASCII
ValueCountFrequency (%)
( 20
45.5%
) 20
45.5%
1
 
2.3%
O 1
 
2.3%
G 1
 
2.3%
N 1
 
2.3%

임기시작일
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2006-04-28
60 
2012-08-17
60 
2008-04-28
59 
2010-08-01
59 
2014-08-17
59 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2006-04-28
2nd row2006-04-28
3rd row2006-04-28
4th row2006-04-28
5th row2006-04-28

Common Values

ValueCountFrequency (%)
2006-04-28 60
18.5%
2012-08-17 60
18.5%
2008-04-28 59
18.2%
2010-08-01 59
18.2%
2014-08-17 59
18.2%
2016-08-17 28
8.6%

Length

2023-12-12T18:22:43.628119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:22:43.764308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2006-04-28 60
18.5%
2012-08-17 60
18.5%
2008-04-28 59
18.2%
2010-08-01 59
18.2%
2014-08-17 59
18.2%
2016-08-17 28
8.6%

임기완료일
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2008-04-27
60 
2014-08-16
60 
2010-04-27
59 
2012-07-31
59 
2016-08-16
59 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2008-04-27
2nd row2008-04-27
3rd row2008-04-27
4th row2008-04-27
5th row2008-04-27

Common Values

ValueCountFrequency (%)
2008-04-27 60
18.5%
2014-08-16 60
18.5%
2010-04-27 59
18.2%
2012-07-31 59
18.2%
2016-08-16 59
18.2%
2018-08-16 28
8.6%

Length

2023-12-12T18:22:43.926393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:22:44.051234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2008-04-27 60
18.5%
2014-08-16 60
18.5%
2010-04-27 59
18.2%
2012-07-31 59
18.2%
2016-08-16 59
18.2%
2018-08-16 28
8.6%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2020-01-06
325 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-01-06
2nd row2020-01-06
3rd row2020-01-06
4th row2020-01-06
5th row2020-01-06

Common Values

ValueCountFrequency (%)
2020-01-06 325
100.0%

Length

2023-12-12T18:22:44.223519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:22:44.351090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-01-06 325
100.0%

Interactions

2023-12-12T18:22:39.531729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:39.342540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:39.633169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:39.433508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:22:44.428068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
임기시작연도임기종료연도위원분류구분전공분야임기시작일임기완료일
임기시작연도1.0001.0000.2330.0000.0001.0001.000
임기종료연도1.0001.0000.2330.0000.0001.0001.000
위원분류0.2330.2331.0000.0000.5360.3530.353
구분0.0000.0000.0001.0000.9700.0000.000
전공분야0.0000.0000.5360.9701.0000.0000.000
임기시작일1.0001.0000.3530.0000.0001.0001.000
임기완료일1.0001.0000.3530.0000.0001.0001.000
2023-12-12T18:22:44.549477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위원분류임기시작일임기완료일구분
위원분류1.0000.2520.2520.000
임기시작일0.2521.0001.0000.000
임기완료일0.2521.0001.0000.000
구분0.0000.0000.0001.000
2023-12-12T18:22:44.676459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
임기시작연도임기종료연도위원분류구분임기시작일임기완료일
임기시작연도1.0001.0000.2520.0001.0001.000
임기종료연도1.0001.0000.2520.0001.0001.000
위원분류0.2520.2521.0000.0000.2520.252
구분0.0000.0000.0001.0000.0000.000
임기시작일1.0001.0000.2520.0001.0001.000
임기완료일1.0001.0000.2520.0001.0001.000

Missing values

2023-12-12T18:22:40.092441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:22:40.301255image/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

임기시작연도임기종료연도위원분류구분위원명전공분야임기시작일임기완료일데이터기준일자
020062008문화재위원제1분과(유형)홍순만향토사2006-04-282008-04-272020-01-06
120062008문화재위원제1분과(유형)고창석역사2006-04-282008-04-272020-01-06
220062008문화재위원제1분과(유형)김석윤건축2006-04-282008-04-272020-01-06
320062008문화재위원제1분과(유형)김익수향토사(전적)2006-04-282008-04-272020-01-06
420062008문화재위원제1분과(유형)김찬흡향토사2006-04-282008-04-272020-01-06
520062008문화재위원제1분과(유형)문기선조각 회화2006-04-282008-04-272020-01-06
620062008문화재위원제1분과(유형)박현영공예2006-04-282008-04-272020-01-06
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