Overview

Dataset statistics

Number of variables15
Number of observations171
Missing cells201
Missing cells (%)7.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.5 KiB
Average record size in memory134.8 B

Variable types

Categorical5
Numeric9
Unsupported1

Dataset

Description도내 문화재(국가지정,지방지정 등) 통계
Author강원도
URLhttps://www.data.go.kr/data/3082811/fileData.do

Alerts

국가지정문화재(보물) is highly overall correlated with 문화재자료 and 3 other fieldsHigh correlation
국가지정문화재(사적 및 명승) is highly overall correlated with 문화재자료 and 3 other fieldsHigh correlation
국가지정문화재(천연기념물) is highly overall correlated with 기관명High correlation
지방지정문화재(시도유형문화재) is highly overall correlated with 지방지정문화재(시도무형문화재) and 4 other fieldsHigh correlation
지방지정문화재(시도무형문화재) is highly overall correlated with 지방지정문화재(시도유형문화재) and 3 other fieldsHigh correlation
지방지정문화재(시도기념물) is highly overall correlated with 문화재자료 and 4 other fieldsHigh correlation
문화재자료 is highly overall correlated with 국가지정문화재(보물) and 6 other fieldsHigh correlation
등록문화재 is highly overall correlated with 기관명 and 3 other fieldsHigh correlation
기관명 is highly overall correlated with 국가지정문화재(보물) and 11 other fieldsHigh correlation
국가지정문화재(국보) is highly overall correlated with 국가지정문화재(보물) and 5 other fieldsHigh correlation
국가지정문화재(국가무형문화재) is highly overall correlated with 국가지정문화재(보물) and 8 other fieldsHigh correlation
국가지정문화재(국가민속문화재) is highly overall correlated with 국가지정문화재(사적 및 명승) and 4 other fieldsHigh correlation
지방지정문화재(시도민속문화재) is highly overall correlated with 지방지정문화재(시도기념물) and 3 other fieldsHigh correlation
국가지정문화재(보물) has 4 (2.3%) missing valuesMissing
국가지정문화재(사적 및 명승) has 6 (3.5%) missing valuesMissing
국가지정문화재(천연기념물) has 3 (1.8%) missing valuesMissing
지방지정문화재(시도유형문화재) has 2 (1.2%) missing valuesMissing
지방지정문화재(시도무형문화재) has 5 (2.9%) missing valuesMissing
지방지정문화재(시도기념물) has 2 (1.2%) missing valuesMissing
등록문화재 has 7 (4.1%) missing valuesMissing
Unnamed: 14 has 171 (100.0%) missing valuesMissing
Unnamed: 14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
국가지정문화재(보물) has 32 (18.7%) zerosZeros
국가지정문화재(사적 및 명승) has 53 (31.0%) zerosZeros
국가지정문화재(천연기념물) has 28 (16.4%) zerosZeros
지방지정문화재(시도유형문화재) has 12 (7.0%) zerosZeros
지방지정문화재(시도무형문화재) has 54 (31.6%) zerosZeros
지방지정문화재(시도기념물) has 16 (9.4%) zerosZeros
문화재자료 has 8 (4.7%) zerosZeros
등록문화재 has 60 (35.1%) zerosZeros

Reproduction

Analysis started2023-12-11 23:02:16.870366
Analysis finished2023-12-11 23:02:26.208689
Duration9.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
강원도
 
9
춘천시
 
9
원주시
 
9
강릉시
 
9
동해시
 
9
Other values (14)
126 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원도
2nd row춘천시
3rd row원주시
4th row강릉시
5th row동해시

Common Values

ValueCountFrequency (%)
강원도 9
 
5.3%
춘천시 9
 
5.3%
원주시 9
 
5.3%
강릉시 9
 
5.3%
동해시 9
 
5.3%
태백시 9
 
5.3%
속초시 9
 
5.3%
삼척시 9
 
5.3%
홍천군 9
 
5.3%
횡성군 9
 
5.3%
Other values (9) 81
47.4%

Length

2023-12-12T08:02:26.279855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강원도 9
 
5.3%
영월군 9
 
5.3%
고성군 9
 
5.3%
인제군 9
 
5.3%
양구군 9
 
5.3%
화천군 9
 
5.3%
철원군 9
 
5.3%
정선군 9
 
5.3%
평창군 9
 
5.3%
횡성군 9
 
5.3%
Other values (9) 81
47.4%

연도별
Real number (ℝ)

Distinct9
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014
Minimum2010
Maximum2018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T08:02:26.410170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2010
5-th percentile2010
Q12012
median2014
Q32016
95-th percentile2018
Maximum2018
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.5895718
Coefficient of variation (CV)0.0012857854
Kurtosis-1.2308115
Mean2014
Median Absolute Deviation (MAD)2
Skewness0
Sum344394
Variance6.7058824
MonotonicityIncreasing
2023-12-12T08:02:26.547821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2010 19
11.1%
2011 19
11.1%
2012 19
11.1%
2013 19
11.1%
2014 19
11.1%
2015 19
11.1%
2016 19
11.1%
2017 19
11.1%
2018 19
11.1%
ValueCountFrequency (%)
2010 19
11.1%
2011 19
11.1%
2012 19
11.1%
2013 19
11.1%
2014 19
11.1%
2015 19
11.1%
2016 19
11.1%
2017 19
11.1%
2018 19
11.1%
ValueCountFrequency (%)
2018 19
11.1%
2017 19
11.1%
2016 19
11.1%
2015 19
11.1%
2014 19
11.1%
2013 19
11.1%
2012 19
11.1%
2011 19
11.1%
2010 19
11.1%

국가지정문화재(국보)
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
108 
1
36 
<NA>
13 
4
 
7
2
 
5

Length

Max length4
Median length1
Mean length1.2280702
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 108
63.2%
1 36
 
21.1%
<NA> 13
 
7.6%
4 7
 
4.1%
2 5
 
2.9%
5 2
 
1.2%

Length

2023-12-12T08:02:26.717514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:02:26.834829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 108
63.2%
1 36
 
21.1%
na 13
 
7.6%
4 7
 
4.1%
2 5
 
2.9%
5 2
 
1.2%

국가지정문화재(보물)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct13
Distinct (%)7.8%
Missing4
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean3.7904192
Minimum0
Maximum16
Zeros32
Zeros (%)18.7%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T08:02:26.928560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile14.8
Maximum16
Range16
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.4799854
Coefficient of variation (CV)1.1819235
Kurtosis1.035174
Mean3.7904192
Median Absolute Deviation (MAD)2
Skewness1.4388835
Sum633
Variance20.070269
MonotonicityNot monotonic
2023-12-12T08:02:27.041143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 43
25.1%
0 32
18.7%
2 20
11.7%
3 16
 
9.4%
4 15
 
8.8%
16 9
 
5.3%
11 9
 
5.3%
9 8
 
4.7%
12 5
 
2.9%
8 4
 
2.3%
Other values (3) 6
 
3.5%
(Missing) 4
 
2.3%
ValueCountFrequency (%)
0 32
18.7%
1 43
25.1%
2 20
11.7%
3 16
 
9.4%
4 15
 
8.8%
5 2
 
1.2%
6 3
 
1.8%
7 1
 
0.6%
8 4
 
2.3%
9 8
 
4.7%
ValueCountFrequency (%)
16 9
5.3%
12 5
 
2.9%
11 9
5.3%
9 8
4.7%
8 4
 
2.3%
7 1
 
0.6%
6 3
 
1.8%
5 2
 
1.2%
4 15
8.8%
3 16
9.4%

국가지정문화재(사적 및 명승)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct8
Distinct (%)4.8%
Missing6
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean2.0727273
Minimum0
Maximum7
Zeros53
Zeros (%)31.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T08:02:27.187842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile6.8
Maximum7
Range7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.1935705
Coefficient of variation (CV)1.0583016
Kurtosis-0.57715695
Mean2.0727273
Median Absolute Deviation (MAD)1
Skewness0.83610695
Sum342
Variance4.8117517
MonotonicityNot monotonic
2023-12-12T08:02:27.329008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 53
31.0%
1 40
23.4%
5 18
 
10.5%
2 17
 
9.9%
4 16
 
9.4%
7 9
 
5.3%
3 7
 
4.1%
6 5
 
2.9%
(Missing) 6
 
3.5%
ValueCountFrequency (%)
0 53
31.0%
1 40
23.4%
2 17
 
9.9%
3 7
 
4.1%
4 16
 
9.4%
5 18
 
10.5%
6 5
 
2.9%
7 9
 
5.3%
ValueCountFrequency (%)
7 9
 
5.3%
6 5
 
2.9%
5 18
 
10.5%
4 16
 
9.4%
3 7
 
4.1%
2 17
 
9.9%
1 40
23.4%
0 53
31.0%

국가지정문화재(천연기념물)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct7
Distinct (%)4.2%
Missing3
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean2.2380952
Minimum0
Maximum6
Zeros28
Zeros (%)16.4%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T08:02:27.451053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile5
Maximum6
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7923259
Coefficient of variation (CV)0.80082648
Kurtosis-1.0233793
Mean2.2380952
Median Absolute Deviation (MAD)1
Skewness0.50156669
Sum376
Variance3.2124323
MonotonicityNot monotonic
2023-12-12T08:02:27.576296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 48
28.1%
2 29
17.0%
0 28
16.4%
5 28
16.4%
3 18
 
10.5%
4 13
 
7.6%
6 4
 
2.3%
(Missing) 3
 
1.8%
ValueCountFrequency (%)
0 28
16.4%
1 48
28.1%
2 29
17.0%
3 18
 
10.5%
4 13
 
7.6%
5 28
16.4%
6 4
 
2.3%
ValueCountFrequency (%)
6 4
 
2.3%
5 28
16.4%
4 13
 
7.6%
3 18
 
10.5%
2 29
17.0%
1 48
28.1%
0 28
16.4%

국가지정문화재(국가무형문화재)
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
131 
<NA>
16 
1
15 
2
 
9

Length

Max length4
Median length1
Mean length1.2807018
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row2
5th row0

Common Values

ValueCountFrequency (%)
0 131
76.6%
<NA> 16
 
9.4%
1 15
 
8.8%
2 9
 
5.3%

Length

2023-12-12T08:02:27.725441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:02:27.867410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 131
76.6%
na 16
 
9.4%
1 15
 
8.8%
2 9
 
5.3%

국가지정문화재(국가민속문화재)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
96 
1
45 
<NA>
12 
4
 
9
2
 
9

Length

Max length4
Median length1
Mean length1.2105263
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 96
56.1%
1 45
26.3%
<NA> 12
 
7.0%
4 9
 
5.3%
2 9
 
5.3%

Length

2023-12-12T08:02:28.017494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:02:28.131145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 96
56.1%
1 45
26.3%
na 12
 
7.0%
4 9
 
5.3%
2 9
 
5.3%

지방지정문화재(시도유형문화재)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct21
Distinct (%)12.4%
Missing2
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean8.3136095
Minimum0
Maximum39
Zeros12
Zeros (%)7.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T08:02:28.247801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q310
95-th percentile33.8
Maximum39
Range39
Interquartile range (IQR)9

Descriptive statistics

Standard deviation10.110808
Coefficient of variation (CV)1.2161755
Kurtosis2.237163
Mean8.3136095
Median Absolute Deviation (MAD)4
Skewness1.7667601
Sum1405
Variance102.22844
MonotonicityNot monotonic
2023-12-12T08:02:28.352996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 39
22.8%
5 23
13.5%
8 17
9.9%
0 12
 
7.0%
10 12
 
7.0%
2 10
 
5.8%
6 9
 
5.3%
3 9
 
5.3%
23 5
 
2.9%
11 5
 
2.9%
Other values (11) 28
16.4%
ValueCountFrequency (%)
0 12
 
7.0%
1 39
22.8%
2 10
 
5.8%
3 9
 
5.3%
4 1
 
0.6%
5 23
13.5%
6 9
 
5.3%
7 4
 
2.3%
8 17
9.9%
10 12
 
7.0%
ValueCountFrequency (%)
39 4
2.3%
38 2
 
1.2%
37 3
1.8%
29 3
1.8%
28 2
 
1.2%
26 3
1.8%
24 4
2.3%
23 5
2.9%
20 1
 
0.6%
12 1
 
0.6%

지방지정문화재(시도무형문화재)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct7
Distinct (%)4.2%
Missing5
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean1.313253
Minimum0
Maximum6
Zeros54
Zeros (%)31.6%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T08:02:28.442852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile5
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4806036
Coefficient of variation (CV)1.1274321
Kurtosis1.4010275
Mean1.313253
Median Absolute Deviation (MAD)1
Skewness1.4420323
Sum218
Variance2.1921869
MonotonicityNot monotonic
2023-12-12T08:02:28.527506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 66
38.6%
0 54
31.6%
2 19
 
11.1%
5 10
 
5.8%
3 8
 
4.7%
4 7
 
4.1%
6 2
 
1.2%
(Missing) 5
 
2.9%
ValueCountFrequency (%)
0 54
31.6%
1 66
38.6%
2 19
 
11.1%
3 8
 
4.7%
4 7
 
4.1%
5 10
 
5.8%
6 2
 
1.2%
ValueCountFrequency (%)
6 2
 
1.2%
5 10
 
5.8%
4 7
 
4.1%
3 8
 
4.7%
2 19
 
11.1%
1 66
38.6%
0 54
31.6%

지방지정문화재(시도기념물)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct13
Distinct (%)7.7%
Missing2
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean4.2130178
Minimum0
Maximum15
Zeros16
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T08:02:28.615916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q36
95-th percentile12.6
Maximum15
Range15
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.7593782
Coefficient of variation (CV)0.89232433
Kurtosis1.2830868
Mean4.2130178
Median Absolute Deviation (MAD)2
Skewness1.3814651
Sum712
Variance14.132925
MonotonicityNot monotonic
2023-12-12T08:02:28.714909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
3 35
20.5%
2 34
19.9%
6 18
10.5%
1 18
10.5%
5 18
10.5%
0 16
9.4%
12 9
 
5.3%
8 7
 
4.1%
15 4
 
2.3%
14 4
 
2.3%
Other values (3) 6
 
3.5%
ValueCountFrequency (%)
0 16
9.4%
1 18
10.5%
2 34
19.9%
3 35
20.5%
4 3
 
1.8%
5 18
10.5%
6 18
10.5%
8 7
 
4.1%
9 2
 
1.2%
12 9
 
5.3%
ValueCountFrequency (%)
15 4
 
2.3%
14 4
 
2.3%
13 1
 
0.6%
12 9
 
5.3%
9 2
 
1.2%
8 7
 
4.1%
6 18
10.5%
5 18
10.5%
4 3
 
1.8%
3 35
20.5%

지방지정문화재(시도민속문화재)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0
120 
1
36 
<NA>
15 

Length

Max length4
Median length1
Mean length1.2631579
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 120
70.2%
1 36
 
21.1%
<NA> 15
 
8.8%

Length

2023-12-12T08:02:28.822333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:02:28.912611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 120
70.2%
1 36
 
21.1%
na 15
 
8.8%

문화재자료
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)10.6%
Missing1
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean7.1058824
Minimum0
Maximum36
Zeros8
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T08:02:28.995808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median5
Q310
95-th percentile23.8
Maximum36
Range36
Interquartile range (IQR)8

Descriptive statistics

Standard deviation7.533002
Coefficient of variation (CV)1.0601079
Kurtosis6.8215393
Mean7.1058824
Median Absolute Deviation (MAD)3
Skewness2.4785244
Sum1208
Variance56.746119
MonotonicityNot monotonic
2023-12-12T08:02:29.301016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
3 28
16.4%
10 24
14.0%
1 19
11.1%
2 17
9.9%
6 12
7.0%
9 11
 
6.4%
5 10
 
5.8%
8 9
 
5.3%
0 8
 
4.7%
7 6
 
3.5%
Other values (8) 26
15.2%
ValueCountFrequency (%)
0 8
 
4.7%
1 19
11.1%
2 17
9.9%
3 28
16.4%
4 4
 
2.3%
5 10
 
5.8%
6 12
7.0%
7 6
 
3.5%
8 9
 
5.3%
9 11
 
6.4%
ValueCountFrequency (%)
36 4
 
2.3%
35 2
 
1.2%
32 2
 
1.2%
31 1
 
0.6%
15 5
 
2.9%
13 4
 
2.3%
11 4
 
2.3%
10 24
14.0%
9 11
6.4%
8 9
 
5.3%

등록문화재
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct7
Distinct (%)4.3%
Missing7
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean2.0121951
Minimum0
Maximum8
Zeros60
Zeros (%)35.1%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T08:02:29.387167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile8
Maximum8
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.2264109
Coefficient of variation (CV)1.1064588
Kurtosis1.0887408
Mean2.0121951
Median Absolute Deviation (MAD)2
Skewness1.2371997
Sum330
Variance4.9569056
MonotonicityNot monotonic
2023-12-12T08:02:29.476568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 60
35.1%
2 31
18.1%
1 19
 
11.1%
3 18
 
10.5%
4 18
 
10.5%
8 11
 
6.4%
5 7
 
4.1%
(Missing) 7
 
4.1%
ValueCountFrequency (%)
0 60
35.1%
1 19
 
11.1%
2 31
18.1%
3 18
 
10.5%
4 18
 
10.5%
5 7
 
4.1%
8 11
 
6.4%
ValueCountFrequency (%)
8 11
 
6.4%
5 7
 
4.1%
4 18
 
10.5%
3 18
 
10.5%
2 31
18.1%
1 19
 
11.1%
0 60
35.1%

Unnamed: 14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing171
Missing (%)100.0%
Memory size1.6 KiB

Interactions

2023-12-12T08:02:24.517457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:17.690609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:18.466943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:19.526477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:20.218448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:20.893965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:21.578307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:22.284969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:23.460246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:24.636302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:17.794489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:18.566199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:19.607303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:20.291872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:20.970699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:21.653309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:22.382226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:23.583959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:24.740325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:17.886738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:18.656108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:19.685845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:20.366749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:21.050761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:21.742707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:22.481910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:23.695511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:24.842248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:17.975506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:18.995833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:19.759622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:20.439754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:21.126761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:21.821312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:22.575297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:23.797327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:24.940278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:18.058825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:19.078802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:19.831204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:20.507611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:21.200092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:21.895030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:22.677047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:23.892424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:25.066583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:18.143592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:19.167487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:19.911656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:20.590959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:21.277298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:21.971732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:22.777201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:24.013092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:25.187398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:18.223310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:19.248890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:19.984569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:20.674535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:21.351748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:22.041928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:22.868459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:24.152385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:25.298541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:18.301186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:19.353388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:20.074336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:20.750186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:21.423445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:22.122312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:22.966481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:24.283275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:25.392394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:18.381119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:19.445376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:20.145605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:20.819478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:21.502872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:22.198182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:23.365185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:02:24.387921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:02:29.562456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관명연도별국가지정문화재(국보)국가지정문화재(보물)국가지정문화재(사적 및 명승)국가지정문화재(천연기념물)국가지정문화재(국가무형문화재)국가지정문화재(국가민속문화재)지방지정문화재(시도유형문화재)지방지정문화재(시도무형문화재)지방지정문화재(시도기념물)지방지정문화재(시도민속문화재)문화재자료등록문화재
기관명1.0000.0000.9120.9530.9590.9600.9380.9560.9030.8770.9490.8900.9000.949
연도별0.0001.0000.0900.0000.0000.0000.1630.0000.0000.0000.0000.2980.0000.000
국가지정문화재(국보)0.9120.0901.0000.8720.5850.6360.5700.2860.7470.6940.5450.1730.7200.527
국가지정문화재(보물)0.9530.0000.8721.0000.7580.6770.9610.5070.8430.7070.8640.3570.8520.681
국가지정문화재(사적 및 명승)0.9590.0000.5850.7581.0000.6930.7150.8550.8170.5960.8000.5460.7490.652
국가지정문화재(천연기념물)0.9600.0000.6360.6770.6931.0000.5520.5760.6580.7840.6820.3840.7430.778
국가지정문화재(국가무형문화재)0.9380.1630.5700.9610.7150.5521.0000.3110.8610.7640.9660.1050.8750.668
국가지정문화재(국가민속문화재)0.9560.0000.2860.5070.8550.5760.3111.0000.5470.5150.8500.7890.5460.736
지방지정문화재(시도유형문화재)0.9030.0000.7470.8430.8170.6580.8610.5471.0000.7570.7850.3640.8230.865
지방지정문화재(시도무형문화재)0.8770.0000.6940.7070.5960.7840.7640.5150.7571.0000.6070.2340.8810.843
지방지정문화재(시도기념물)0.9490.0000.5450.8640.8000.6820.9660.8500.7850.6071.0000.7140.7410.784
지방지정문화재(시도민속문화재)0.8900.2980.1730.3570.5460.3840.1050.7890.3640.2340.7141.0000.3350.699
문화재자료0.9000.0000.7200.8520.7490.7430.8750.5460.8230.8810.7410.3351.0000.806
등록문화재0.9490.0000.5270.6810.6520.7780.6680.7360.8650.8430.7840.6990.8061.000
2023-12-12T08:02:29.691195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관명국가지정문화재(국가민속문화재)지방지정문화재(시도민속문화재)국가지정문화재(국보)국가지정문화재(국가무형문화재)
기관명1.0000.8240.7960.7080.808
국가지정문화재(국가민속문화재)0.8241.0000.5770.2360.299
지방지정문화재(시도민속문화재)0.7960.5771.0000.2090.172
국가지정문화재(국보)0.7080.2360.2091.0000.513
국가지정문화재(국가무형문화재)0.8080.2990.1720.5131.000
2023-12-12T08:02:29.785805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도별국가지정문화재(보물)국가지정문화재(사적 및 명승)국가지정문화재(천연기념물)지방지정문화재(시도유형문화재)지방지정문화재(시도무형문화재)지방지정문화재(시도기념물)문화재자료등록문화재기관명국가지정문화재(국보)국가지정문화재(국가무형문화재)국가지정문화재(국가민속문화재)지방지정문화재(시도민속문화재)
연도별1.0000.1360.2090.1070.0530.2030.0560.0870.1130.0000.0410.0780.0000.191
국가지정문화재(보물)0.1361.0000.487-0.0650.4620.3250.4430.6810.0680.7890.7310.7510.3650.348
국가지정문화재(사적 및 명승)0.2090.4871.0000.3180.4330.2680.2510.543-0.1190.8050.4050.5960.5250.403
국가지정문화재(천연기념물)0.107-0.0650.3181.0000.3060.2960.3240.108-0.0590.8170.4740.4350.4320.404
지방지정문화재(시도유형문화재)0.0530.4620.4330.3061.0000.6580.3850.7670.0700.6540.6020.8320.4050.383
지방지정문화재(시도무형문화재)0.2030.3250.2680.2960.6581.0000.1680.4960.0620.6190.5370.6910.3760.246
지방지정문화재(시도기념물)0.0560.4430.2510.3240.3850.1681.0000.5570.3740.7050.3420.7440.6730.503
문화재자료0.0870.6810.5430.1080.7670.4960.5571.0000.0680.6640.5690.8530.4040.352
등록문화재0.1130.068-0.119-0.0590.0700.0620.3740.0681.0000.7830.3710.5670.6050.743
기관명0.0000.7890.8050.8170.6540.6190.7050.6640.7831.0000.7080.8080.8240.796
국가지정문화재(국보)0.0410.7310.4050.4740.6020.5370.3420.5690.3710.7081.0000.5130.2360.209
국가지정문화재(국가무형문화재)0.0780.7510.5960.4350.8320.6910.7440.8530.5670.8080.5131.0000.2990.172
국가지정문화재(국가민속문화재)0.0000.3650.5250.4320.4050.3760.6730.4040.6050.8240.2360.2991.0000.577
지방지정문화재(시도민속문화재)0.1910.3480.4030.4040.3830.2460.5030.3520.7430.7960.2090.1720.5771.000

Missing values

2023-12-12T08:02:25.597492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:02:25.840233image/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.
2023-12-12T08:02:26.035913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

기관명연도별국가지정문화재(국보)국가지정문화재(보물)국가지정문화재(사적 및 명승)국가지정문화재(천연기념물)국가지정문화재(국가무형문화재)국가지정문화재(국가민속문화재)지방지정문화재(시도유형문화재)지방지정문화재(시도무형문화재)지방지정문화재(시도기념물)지방지정문화재(시도민속문화재)문화재자료등록문화재Unnamed: 14
0강원도2010000400000000<NA>
1춘천시201004200150120103<NA>
2원주시201014431023530135<NA>
3강릉시20101165421373150311<NA>
4동해시2010021000403032<NA>
5태백시2010001201102114<NA>
6속초시2010011100510050<NA>
7삼척시2010012504819184<NA>
8홍천군201001100005060102<NA>
9횡성군20100001001021032<NA>
기관명연도별국가지정문화재(국보)국가지정문화재(보물)국가지정문화재(사적 및 명승)국가지정문화재(천연기념물)국가지정문화재(국가무형문화재)국가지정문화재(국가민속문화재)지방지정문화재(시도유형문화재)지방지정문화재(시도무형문화재)지방지정문화재(시도기념물)지방지정문화재(시도민속문화재)문화재자료등록문화재Unnamed: 14
161횡성군2018<NA><NA><NA>1<NA><NA>1021<NA>32<NA>
162영월군2018<NA>175<NA><NA>1215<NA>9<NA><NA>
163평창군20185613<NA>12843<NA>101<NA>
164정선군2018<NA>1<NA>6<NA>131512<NA><NA>
165철원군201811<NA>2<NA><NA>116<NA>28<NA>
166화천군2018<NA>1<NA>1<NA><NA>2<NA>2113<NA>
167양구군2018<NA><NA><NA>2<NA><NA>111<NA>3<NA><NA>
168인제군2018<NA>451<NA><NA><NA><NA>3<NA>3<NA><NA>
169고성군2018<NA>21<NA><NA>2222<NA>51<NA>
170양양군20181952<NA><NA>623<NA>9<NA><NA>