Overview

Dataset statistics

Number of variables6
Number of observations97
Missing cells83
Missing cells (%)14.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 KiB
Average record size in memory50.4 B

Variable types

Numeric1
Categorical2
Text2
DateTime1

Dataset

Description2017년 10월 경상남도 무형문화재 현황입니다. 명칭, 보유자 성명, 성별, 보유종별, 지정일 등의 데이터를 포함하고 있습니다.
Author경상남도
URLhttps://www.data.go.kr/data/15056108/fileData.do

Alerts

지정번호 is highly overall correlated with 명 칭High correlation
명 칭 is highly overall correlated with 지정번호 and 1 other fieldsHigh correlation
성별 is highly overall correlated with 명 칭High correlation
보유자 성명 has 29 (29.9%) missing valuesMissing
보유종별 has 53 (54.6%) missing valuesMissing
지정일 has 1 (1.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 09:15:53.078315
Analysis finished2023-12-12 09:15:53.930937
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지정번호
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.917526
Minimum2
Maximum42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-12T18:15:54.012460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.8
Q111
median20
Q329
95-th percentile37.2
Maximum42
Range40
Interquartile range (IQR)18

Descriptive statistics

Standard deviation11.562935
Coefficient of variation (CV)0.58054072
Kurtosis-1.1772161
Mean19.917526
Median Absolute Deviation (MAD)9
Skewness0.027159938
Sum1932
Variance133.70146
MonotonicityIncreasing
2023-12-12T18:15:54.178620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
3 6
 
6.2%
2 5
 
5.2%
6 5
 
5.2%
20 5
 
5.2%
17 4
 
4.1%
27 4
 
4.1%
30 4
 
4.1%
12 4
 
4.1%
19 4
 
4.1%
29 4
 
4.1%
Other values (27) 52
53.6%
ValueCountFrequency (%)
2 5
5.2%
3 6
6.2%
5 2
 
2.1%
6 5
5.2%
7 3
3.1%
8 1
 
1.0%
9 1
 
1.0%
10 1
 
1.0%
11 3
3.1%
12 4
4.1%
ValueCountFrequency (%)
42 1
 
1.0%
41 1
 
1.0%
40 1
 
1.0%
39 1
 
1.0%
38 1
 
1.0%
37 3
3.1%
36 2
2.1%
35 2
2.1%
34 1
 
1.0%
33 3
3.1%

명 칭
Categorical

HIGH CORRELATION 

Distinct37
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
한량무
 
6
마산 농청놀이
 
5
의령 큰줄땡기기
 
5
용호놀이
 
5
가야진용신제
 
4
Other values (32)
72 

Length

Max length13
Median length9
Mean length6.2474227
Min length2

Unique

Unique11 ?
Unique (%)11.3%

Sample

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

Common Values

ValueCountFrequency (%)
한량무 6
 
6.2%
마산 농청놀이 5
 
5.2%
의령 큰줄땡기기 5
 
5.2%
용호놀이 5
 
5.2%
가야진용신제 4
 
4.1%
거창 일소리 4
 
4.1%
소목장 4
 
4.1%
진주 오광대 4
 
4.1%
진주 포구락무 4
 
4.1%
거창 삼베일소리 4
 
4.1%
Other values (27) 52
53.6%

Length

2023-12-12T18:15:54.357297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
진주 9
 
6.0%
거창 8
 
5.3%
함안 6
 
4.0%
한량무 6
 
4.0%
큰줄땡기기 5
 
3.3%
농청놀이 5
 
3.3%
의령 5
 
3.3%
마산 5
 
3.3%
용호놀이 5
 
3.3%
오광대 4
 
2.7%
Other values (40) 92
61.3%

보유자 성명
Text

MISSING 

Distinct47
Distinct (%)69.1%
Missing29
Missing (%)29.9%
Memory size908.0 B
2023-12-12T18:15:54.583150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.0588235
Min length3

Characters and Unicode

Total characters208
Distinct characters74
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

Unique46 ?
Unique (%)67.6%

Sample

1st row보존회
2nd row정영선
3rd row조희윤
4th row이우택
5th row보존회
ValueCountFrequency (%)
보존회 22
32.4%
박종섭 1
 
1.5%
김필연 1
 
1.5%
강순영 1
 
1.5%
김찬중 1
 
1.5%
강동욱 1
 
1.5%
하계윤 1
 
1.5%
박용준 1
 
1.5%
정진호 1
 
1.5%
김동귀 1
 
1.5%
Other values (37) 37
54.4%
2023-12-12T18:15:54.985843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
보 23
 
11.1%
회 23
 
11.1%
존 23
 
11.1%
이 11
 
5.3%
정 9
 
4.3%
김 9
 
4.3%
박 6
 
2.9%
용 4
 
1.9%
순 4
 
1.9%
연 4
 
1.9%
Other values (64) 92
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 207
99.5%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 23
 
11.1%
회 23
 
11.1%
존 23
 
11.1%
이 11
 
5.3%
정 9
 
4.3%
김 9
 
4.3%
박 6
 
2.9%
용 4
 
1.9%
순 4
 
1.9%
연 4
 
1.9%
Other values (63) 91
44.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 207
99.5%
Common 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 23
 
11.1%
회 23
 
11.1%
존 23
 
11.1%
이 11
 
5.3%
정 9
 
4.3%
김 9
 
4.3%
박 6
 
2.9%
용 4
 
1.9%
순 4
 
1.9%
연 4
 
1.9%
Other values (63) 91
44.0%
Common
ValueCountFrequency (%)
, 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 207
99.5%
ASCII 1
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
보 23
 
11.1%
회 23
 
11.1%
존 23
 
11.1%
이 11
 
5.3%
정 9
 
4.3%
김 9
 
4.3%
박 6
 
2.9%
용 4
 
1.9%
순 4
 
1.9%
연 4
 
1.9%
Other values (63) 91
44.0%
ASCII
ValueCountFrequency (%)
, 1
100.0%

성별
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
<NA>
53 
남
30 
여
14 

Length

Max length4
Median length4
Mean length2.6391753
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row남
4th row남
5th row남

Common Values

ValueCountFrequency (%)
<NA> 53
54.6%
남 30
30.9%
여 14
 
14.4%

Length

2023-12-12T18:15:55.184021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:15:55.301726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 53
54.6%
남 30
30.9%
여 14
 
14.4%

보유종별
Text

MISSING 

Distinct38
Distinct (%)86.4%
Missing53
Missing (%)54.6%
Memory size908.0 B
2023-12-12T18:15:55.494217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length9
Mean length4.1818182
Min length2

Characters and Unicode

Total characters184
Distinct characters90
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)77.3%

Sample

1st row소도구제작
2nd row소도구제작
3rd row꽹과리
4th row색씨
5th row주모
ValueCountFrequency (%)
소도구제작 3
 
6.0%
소목장 3
 
6.0%
일소리 2
 
4.0%
소리 2
 
4.0%
상쇠 2
 
4.0%
삼베길쌈 1
 
2.0%
앞소리꾼 1
 
2.0%
모심기노래 1
 
2.0%
가야금산조 1
 
2.0%
줄끗기 1
 
2.0%
Other values (33) 33
66.0%
2023-12-12T18:15:55.924780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 12
 
6.5%
리 7
 
3.8%
기 7
 
3.8%
제 7
 
3.8%
장 7
 
3.8%
, 6
 
3.3%
상 6
 
3.3%
6
 
3.3%
작 5
 
2.7%
구 4
 
2.2%
Other values (80) 117
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162
88.0%
Other Punctuation 7
 
3.8%
Space Separator 6
 
3.3%
Close Punctuation 4
 
2.2%
Open Punctuation 4
 
2.2%
Decimal Number 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 12
 
7.4%
리 7
 
4.3%
기 7
 
4.3%
제 7
 
4.3%
장 7
 
4.3%
상 6
 
3.7%
작 5
 
3.1%
구 4
 
2.5%
목 4
 
2.5%
줄 4
 
2.5%
Other values (74) 99
61.1%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
? 1
 
14.3%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162
88.0%
Common 22
 
12.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 12
 
7.4%
리 7
 
4.3%
기 7
 
4.3%
제 7
 
4.3%
장 7
 
4.3%
상 6
 
3.7%
작 5
 
3.1%
구 4
 
2.5%
목 4
 
2.5%
줄 4
 
2.5%
Other values (74) 99
61.1%
Common
ValueCountFrequency (%)
, 6
27.3%
6
27.3%
) 4
18.2%
( 4
18.2%
? 1
 
4.5%
1 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 162
88.0%
ASCII 22
 
12.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 12
 
7.4%
리 7
 
4.3%
기 7
 
4.3%
제 7
 
4.3%
장 7
 
4.3%
상 6
 
3.7%
작 5
 
3.1%
구 4
 
2.5%
목 4
 
2.5%
줄 4
 
2.5%
Other values (74) 99
61.1%
ASCII
ValueCountFrequency (%)
, 6
27.3%
6
27.3%
) 4
18.2%
( 4
18.2%
? 1
 
4.5%
1 1
 
4.5%

지정일
Date

MISSING 

Distinct38
Distinct (%)39.6%
Missing1
Missing (%)1.0%
Memory size908.0 B
Minimum1977-06-18 00:00:00
Maximum2017-10-12 00:00:00
2023-12-12T18:15:56.109097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:15:56.317702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

Interactions

2023-12-12T18:15:53.488310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:15:56.475523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정번호명 칭보유자 성명성별보유종별지정일
지정번호1.0001.0000.1000.5360.9880.987
명 칭1.0001.0000.3370.9520.9950.989
보유자 성명0.1000.3371.0001.0001.0000.812
성별0.5360.9521.0001.0001.0000.955
보유종별0.9880.9951.0001.0001.0000.927
지정일0.9870.9890.8120.9550.9271.000
2023-12-12T18:15:56.617863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
명 칭성별
명 칭1.0000.577
성별0.5771.000
2023-12-12T18:15:56.713617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정번호명 칭성별
지정번호1.0000.8300.286
명 칭0.8301.0000.577
성별0.2860.5771.000

Missing values

2023-12-12T18:15:53.618883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:15:53.737035image/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.
2023-12-12T18:15:53.847148image/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

지정번호명 칭보유자 성명성별보유종별지정일
02용호놀이<NA><NA><NA>1977-06-18
12용호놀이보존회<NA><NA>1991-12-23
22용호놀이정영선남소도구제작1991-12-23
32용호놀이조희윤남소도구제작2011-08-04
42용호놀이이우택남꽹과리2014-03-13
53한량무<NA><NA><NA>1979-05-02
63한량무보존회<NA><NA>1979-05-02
73한량무정행금여색씨1979-05-02
83한량무김연이여주모1979-05-02
93한량무서정남여별감1979-05-02
지정번호명 칭보유자 성명성별보유종별지정일
8736거창삼베길쌈보존회<NA><NA>2013-01-03
8836거창삼베길쌈이옥수여삼베길쌈2013-01-03
8937김해오광대보존회<NA><NA>2015-03-05
9037김해오광대이명식남노름꾼1,상여소리,상주선산양반, 봉사2015-03-05
9137김해오광대정용근남종가양반, 영감2015-03-05
9238마산성신대제보존회<NA><NA>2016-05-04
9339함안농요보존회<NA><NA>2016-09-01
9440거창상여디딜방아액막이소리이정민<NA><NA>2016-12-15
9541불모산영산재보존회,홍복남<NA><NA>2016-12-15
9642염색장(쪽물장)김광수남쪽물2017-10-12