Overview

Dataset statistics

Number of variables5
Number of observations697
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.7 KiB
Average record size in memory42.2 B

Variable types

Categorical4
Numeric1

Dataset

Description- 시도별 문화재 지정 현황을 제공합니다. - 데이터 제공처: KOSIS 국가통계포털
Author제주특별자치도 미래성장과
URLhttps://www.jejudatahub.net/data/view/data/880

Alerts

문화재대분류 is highly overall correlated with 문화재소분류High correlation
문화재소분류 is highly overall correlated with 문화재대분류High correlation
등록건수 has 69 (9.9%) zerosZeros

Reproduction

Analysis started2023-12-11 20:11:09.669713
Analysis finished2023-12-11 20:11:10.313477
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준 연도
Categorical

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
2018
144 
2019
144 
2016
143 
2017
140 
2020
126 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2016
2nd row2016
3rd row2016
4th row2016
5th row2016

Common Values

ValueCountFrequency (%)
2018 144
20.7%
2019 144
20.7%
2016 143
20.5%
2017 140
20.1%
2020 126
18.1%

Length

2023-12-12T05:11:10.384785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T05:11:10.532078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 144
20.7%
2019 144
20.7%
2016 143
20.5%
2017 140
20.1%
2020 126
18.1%

시도
Categorical

Distinct18
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
서울
 
40
충남
 
40
광주
 
40
부산
 
40
강원
 
40
Other values (13)
497 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울 40
 
5.7%
충남 40
 
5.7%
광주 40
 
5.7%
부산 40
 
5.7%
강원 40
 
5.7%
충북 40
 
5.7%
경기 40
 
5.7%
전북 40
 
5.7%
전남 40
 
5.7%
경북 40
 
5.7%
Other values (8) 297
42.6%

Length

2023-12-12T05:11:10.669615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울 40
 
5.7%
경기 40
 
5.7%
경남 40
 
5.7%
충남 40
 
5.7%
전남 40
 
5.7%
전북 40
 
5.7%
경북 40
 
5.7%
충북 40
 
5.7%
강원 40
 
5.7%
부산 40
 
5.7%
Other values (8) 297
42.6%

문화재대분류
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
지정문화재
609 
국가등록문화재
88 

Length

Max length7
Median length5
Mean length5.2525108
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지정문화재 609
87.4%
국가등록문화재 88
 
12.6%

Length

2023-12-12T05:11:10.828126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T05:11:10.930564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지정문화재 609
87.4%
국가등록문화재 88
 
12.6%

문화재소분류
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
천연기념물
90 
보물
88 
사적
88 
국가민속문화재
88 
소계
88 
Other values (3)
255 

Length

Max length7
Median length2
Mean length3.6355811
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row국보
2nd row보물
3rd row사적
4th row명승
5th row천연기념물

Common Values

ValueCountFrequency (%)
천연기념물 90
12.9%
보물 88
12.6%
사적 88
12.6%
국가민속문화재 88
12.6%
소계 88
12.6%
국가무형문화재 86
12.3%
명승 85
12.2%
국보 84
12.1%

Length

2023-12-12T05:11:11.025569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T05:11:11.131509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
천연기념물 90
12.9%
보물 88
12.6%
사적 88
12.6%
국가민속문화재 88
12.6%
소계 88
12.6%
국가무형문화재 86
12.3%
명승 85
12.2%
국보 84
12.1%

등록건수
Real number (ℝ)

ZEROS 

Distinct119
Distinct (%)17.1%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean34.395115
Minimum0
Maximum716
Zeros69
Zeros (%)9.9%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2023-12-12T05:11:11.264658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median12
Q339.25
95-th percentile138.5
Maximum716
Range716
Interquartile range (IQR)36.25

Descriptive statistics

Standard deviation73.758485
Coefficient of variation (CV)2.1444465
Kurtosis47.561134
Mean34.395115
Median Absolute Deviation (MAD)10
Skewness6.0777316
Sum23939
Variance5440.3142
MonotonicityNot monotonic
2023-12-12T05:11:11.391974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 69
 
9.9%
2 53
 
7.6%
1 44
 
6.3%
3 31
 
4.4%
12 25
 
3.6%
8 23
 
3.3%
11 23
 
3.3%
5 20
 
2.9%
4 20
 
2.9%
21 16
 
2.3%
Other values (109) 372
53.4%
ValueCountFrequency (%)
0 69
9.9%
1 44
6.3%
2 53
7.6%
3 31
4.4%
4 20
 
2.9%
5 20
 
2.9%
6 16
 
2.3%
7 16
 
2.3%
8 23
 
3.3%
9 16
 
2.3%
ValueCountFrequency (%)
716 1
0.1%
712 1
0.1%
706 1
0.1%
683 1
0.1%
672 1
0.1%
364 1
0.1%
350 1
0.1%
341 1
0.1%
337 1
0.1%
327 1
0.1%

Interactions

2023-12-12T05:11:09.980382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T05:11:11.497838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준 연도시도문화재대분류문화재소분류등록건수
기준 연도1.0000.0000.0000.0000.000
시도0.0001.0000.0000.0000.492
문화재대분류0.0000.0001.0001.0000.109
문화재소분류0.0000.0001.0001.0000.392
등록건수0.0000.4920.1090.3921.000
2023-12-12T05:11:11.621949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도문화재대분류기준 연도문화재소분류
시도1.0000.0000.0000.000
문화재대분류0.0001.0000.0000.996
기준 연도0.0000.0001.0000.000
문화재소분류0.0000.9960.0001.000
2023-12-12T05:11:11.706615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록건수기준 연도시도문화재대분류문화재소분류
등록건수1.0000.0000.2430.1160.222
기준 연도0.0001.0000.0000.0000.000
시도0.2430.0001.0000.0000.000
문화재대분류0.1160.0000.0001.0000.996
문화재소분류0.2220.0000.0000.9961.000

Missing values

2023-12-12T05:11:10.162791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T05:11:10.273500image/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

기준 연도시도문화재대분류문화재소분류등록건수
02016서울지정문화재국보164
12016서울지정문화재보물672
22016서울지정문화재사적67
32016서울지정문화재명승3
42016서울지정문화재천연기념물12
52016서울지정문화재국가무형문화재29
62016서울지정문화재국가민속문화재41
72016서울국가등록문화재소계185
82016부산지정문화재국보5
92016부산지정문화재보물40
기준 연도시도문화재대분류문화재소분류등록건수
6872020경남국가등록문화재소계57
6882020제주지정문화재보물8
6892020제주지정문화재사적7
6902020제주지정문화재명승9
6912020제주지정문화재천연기념물49
6922020제주지정문화재국가무형문화재4
6932020제주지정문화재국가민속문화재9
6942020제주국가등록문화재소계25
6952020기타지정문화재천연기념물64
6962020기타지정문화재국가무형문화재32