Overview

Dataset statistics

Number of variables5
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory993.0 B
Average record size in memory47.3 B

Variable types

Numeric1
Text3
DateTime1

Dataset

Description2017년 10월 기준 경상남도 민속문화재 현황입니다. (명칭, 수량, 면적, 소재지, 지정일등의 데이터를 포함하고있습니다.)
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15056107

Alerts

지정번호 has unique valuesUnique
명칭 has unique valuesUnique

Reproduction

Analysis started2023-12-10 22:54:10.086836
Analysis finished2023-12-10 22:54:10.518366
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지정번호
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.666667
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T07:54:10.610099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median12
Q317
95-th percentile21
Maximum22
Range21
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.6055532
Coefficient of variation (CV)0.56619028
Kurtosis-1.2402113
Mean11.666667
Median Absolute Deviation (MAD)6
Skewness-0.075459541
Sum245
Variance43.633333
MonotonicityStrictly increasing
2023-12-11T07:54:10.701752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 1
 
4.8%
2 1
 
4.8%
22 1
 
4.8%
21 1
 
4.8%
20 1
 
4.8%
19 1
 
4.8%
18 1
 
4.8%
17 1
 
4.8%
16 1
 
4.8%
15 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
1 1
4.8%
2 1
4.8%
3 1
4.8%
4 1
4.8%
5 1
4.8%
6 1
4.8%
7 1
4.8%
9 1
4.8%
10 1
4.8%
11 1
4.8%
ValueCountFrequency (%)
22 1
4.8%
21 1
4.8%
20 1
4.8%
19 1
4.8%
18 1
4.8%
17 1
4.8%
16 1
4.8%
15 1
4.8%
14 1
4.8%
13 1
4.8%

명칭
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T07:54:10.922920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length19.142857
Min length10

Characters and Unicode

Total characters402
Distinct characters157
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row馬岩面 石馬(마암면 석마)
2nd row碧松寺 木長丞(벽송사 목장승)
3rd row駕山里 石長丞(가산리 석장승)
4th row山淸 丹溪 朴氏古家(산청 단계 박씨고가)
5th row金冠朝服(금관조복)
ValueCountFrequency (%)
居昌 4
 
4.8%
석장승 3
 
3.6%
宜寧 2
 
2.4%
馬岩面 1
 
1.2%
裵氏古家(고성 1
 
1.2%
신씨고가 1
 
1.2%
황산리 1
 
1.2%
愼氏古家(거창 1
 
1.2%
黃山里 1
 
1.2%
배씨고가 1
 
1.2%
Other values (67) 67
80.7%
2023-12-11T07:54:11.324191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
62
 
15.4%
( 21
 
5.2%
) 21
 
5.2%
가 11
 
2.7%
고 11
 
2.7%
리 10
 
2.5%
古 9
 
2.2%
里 9
 
2.2%
家 8
 
2.0%
씨 8
 
2.0%
Other values (147) 232
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 298
74.1%
Space Separator 62
 
15.4%
Open Punctuation 21
 
5.2%
Close Punctuation 21
 
5.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 11
 
3.7%
고 11
 
3.7%
리 10
 
3.4%
古 9
 
3.0%
里 9
 
3.0%
家 8
 
2.7%
씨 8
 
2.7%
氏 8
 
2.7%
석 6
 
2.0%
石 6
 
2.0%
Other values (144) 212
71.1%
Space Separator
ValueCountFrequency (%)
62
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 154
38.3%
Han 144
35.8%
Common 104
25.9%

Most frequent character per script

Han
ValueCountFrequency (%)
古 9
 
6.2%
里 9
 
6.2%
家 8
 
5.6%
氏 8
 
5.6%
石 6
 
4.2%
山 4
 
2.8%
居 4
 
2.8%
長 4
 
2.8%
昌 4
 
2.8%
丞 4
 
2.8%
Other values (73) 84
58.3%
Hangul
ValueCountFrequency (%)
가 11
 
7.1%
고 11
 
7.1%
리 10
 
6.5%
씨 8
 
5.2%
석 6
 
3.9%
거 5
 
3.2%
성 4
 
2.6%
산 4
 
2.6%
승 4
 
2.6%
장 4
 
2.6%
Other values (61) 87
56.5%
Common
ValueCountFrequency (%)
62
59.6%
( 21
 
20.2%
) 21
 
20.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 154
38.3%
CJK 138
34.3%
ASCII 104
25.9%
CJK Compat Ideographs 6
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
62
59.6%
( 21
 
20.2%
) 21
 
20.2%
Hangul
ValueCountFrequency (%)
가 11
 
7.1%
고 11
 
7.1%
리 10
 
6.5%
씨 8
 
5.2%
석 6
 
3.9%
거 5
 
3.2%
성 4
 
2.6%
산 4
 
2.6%
승 4
 
2.6%
장 4
 
2.6%
Other values (61) 87
56.5%
CJK
ValueCountFrequency (%)
古 9
 
6.5%
里 9
 
6.5%
家 8
 
5.8%
氏 8
 
5.8%
石 6
 
4.3%
山 4
 
2.9%
居 4
 
2.9%
長 4
 
2.9%
昌 4
 
2.9%
丞 4
 
2.9%
Other values (68) 78
56.5%
CJK Compat Ideographs
ValueCountFrequency (%)
寧 2
33.3%
異 1
16.7%
靈 1
16.7%
林 1
16.7%
宅 1
16.7%

수량 및 면적
Text

Distinct18
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T07:54:11.541826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length2
Mean length4.7619048
Min length2

Characters and Unicode

Total characters100
Distinct characters20
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)71.4%

Sample

1st row3기
2nd row2기
3rd row6기, 25.5㎡
4th row1동, 1,375㎡
5th row13점
ValueCountFrequency (%)
1동 3
 
10.3%
2기 3
 
10.3%
1기 2
 
6.9%
5동 2
 
6.9%
4동 2
 
6.9%
43㎡ 1
 
3.4%
3기 1
 
3.4%
2,565㎡ 1
 
3.4%
2구 1
 
3.4%
7동 1
 
3.4%
Other values (12) 12
41.4%
2023-12-11T07:54:12.126657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 10
10.0%
2 10
10.0%
, 10
10.0%
㎡ 9
9.0%
1 8
8.0%
5 8
8.0%
8
8.0%
3 7
 
7.0%
기 7
 
7.0%
4 4
 
4.0%
Other values (10) 19
19.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49
49.0%
Other Letter 20
20.0%
Other Punctuation 12
 
12.0%
Other Symbol 9
 
9.0%
Space Separator 8
 
8.0%
Open Punctuation 1
 
1.0%
Close Punctuation 1
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 10
20.4%
1 8
16.3%
5 8
16.3%
3 7
14.3%
4 4
 
8.2%
6 3
 
6.1%
7 3
 
6.1%
0 2
 
4.1%
8 2
 
4.1%
9 2
 
4.1%
Other Letter
ValueCountFrequency (%)
동 10
50.0%
기 7
35.0%
구 2
 
10.0%
점 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 10
83.3%
. 2
 
16.7%
Other Symbol
ValueCountFrequency (%)
㎡ 9
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 80
80.0%
Hangul 20
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 10
12.5%
, 10
12.5%
㎡ 9
11.2%
1 8
10.0%
5 8
10.0%
8
10.0%
3 7
8.8%
4 4
 
5.0%
6 3
 
3.8%
7 3
 
3.8%
Other values (6) 10
12.5%
Hangul
ValueCountFrequency (%)
동 10
50.0%
기 7
35.0%
구 2
 
10.0%
점 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
71.0%
Hangul 20
 
20.0%
CJK Compat 9
 
9.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 10
50.0%
기 7
35.0%
구 2
 
10.0%
점 1
 
5.0%
ASCII
ValueCountFrequency (%)
2 10
14.1%
, 10
14.1%
1 8
11.3%
5 8
11.3%
8
11.3%
3 7
9.9%
4 4
 
5.6%
6 3
 
4.2%
7 3
 
4.2%
. 2
 
2.8%
Other values (5) 8
11.3%
CJK Compat
ValueCountFrequency (%)
㎡ 9
100.0%

소재지
Text

Distinct12
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T07:54:12.311524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters63
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)33.3%

Sample

1st row고성군
2nd row함양군
3rd row사천시
4th row산청군
5th row산청군
ValueCountFrequency (%)
거창군 4
19.0%
고성군 3
14.3%
산청군 3
14.3%
함양군 2
9.5%
의령군 2
9.5%
사천시 1
 
4.8%
창녕군 1
 
4.8%
양산시 1
 
4.8%
함안군 1
 
4.8%
진주시 1
 
4.8%
Other values (2) 2
9.5%
2023-12-11T07:54:12.603134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 18
28.6%
창 5
 
7.9%
거 4
 
6.3%
산 4
 
6.3%
고 3
 
4.8%
성 3
 
4.8%
청 3
 
4.8%
함 3
 
4.8%
양 3
 
4.8%
시 3
 
4.8%
Other values (11) 14
22.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 18
28.6%
창 5
 
7.9%
거 4
 
6.3%
산 4
 
6.3%
고 3
 
4.8%
성 3
 
4.8%
청 3
 
4.8%
함 3
 
4.8%
양 3
 
4.8%
시 3
 
4.8%
Other values (11) 14
22.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 18
28.6%
창 5
 
7.9%
거 4
 
6.3%
산 4
 
6.3%
고 3
 
4.8%
성 3
 
4.8%
청 3
 
4.8%
함 3
 
4.8%
양 3
 
4.8%
시 3
 
4.8%
Other values (11) 14
22.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 18
28.6%
창 5
 
7.9%
거 4
 
6.3%
산 4
 
6.3%
고 3
 
4.8%
성 3
 
4.8%
청 3
 
4.8%
함 3
 
4.8%
양 3
 
4.8%
시 3
 
4.8%
Other values (11) 14
22.2%

지정일(확대지정)
Date

Distinct15
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum1974-02-16 00:00:00
Maximum2011-07-14 00:00:00
2023-12-11T07:54:12.739059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:54:12.866273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)

Interactions

2023-12-11T07:54:10.314811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:54:12.939373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정번호명칭수량 및 면적소재지지정일(확대지정)
지정번호1.0001.0000.8390.6360.944
명칭1.0001.0001.0001.0001.000
수량 및 면적0.8391.0001.0000.8440.935
소재지0.6361.0000.8441.0000.867
지정일(확대지정)0.9441.0000.9350.8671.000

Missing values

2023-12-11T07:54:10.399696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:54:10.478582image/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

지정번호명칭수량 및 면적소재지지정일(확대지정)
01馬岩面 石馬(마암면 석마)3기고성군1974-02-16
12碧松寺 木長丞(벽송사 목장승)2기함양군1974-12-24
23駕山里 石長丞(가산리 석장승)6기, 25.5㎡사천시1974-12-24
34山淸 丹溪 朴氏古家(산청 단계 박씨고가)1동, 1,375㎡산청군1983-08-06
45金冠朝服(금관조복)13점산청군1983-08-06
56觀龍寺 石長丞(관룡사 석장승)2기, 200㎡창녕군1983-08-06
67伽倻津祠(가야진사)1동양산시1983-12-20
79居昌 葛溪里 林氏古家(거창 갈계리 임씨고가)4동거창군1985-01-14
810咸安 舞沂里 周氏古家(함안 무기리 주씨고가)1동함안군1985-01-14
911宜寧 德橋里 姜氏古家(의령 덕교리 강씨고가)5동, 388㎡의령군1986-08-06
지정번호명칭수량 및 면적소재지지정일(확대지정)
1113南海 加川 암수바위(남해 가천 암수바위)2기, 2,565㎡남해군1990-01-16
1214智異山 聖母像(지리산 성모상)1구, 43㎡산청군1991-12-23
1315宜寧 上井里 曺氏古家(의령 상정리 조씨고가)9동, 579㎡의령군1993-12-27
1416固城 鳳東里 裵氏古家(고성 봉동리 배씨고가)3동고성군1994-07-04
1517居昌 黃山里 愼氏古家(거창 황산리 신씨고가)7동거창군1994-07-04
1618陜川 八尋里 尹氏古家(합천 팔심리 윤씨고가)4동합천군1995-05-02
1719靈隱寺址 石長丞(영은사지 석장승)2구함양군1996-03-11
1820居昌 渠基里 城隍壇(거창 거기리 성황단)1기거창군1998-01-15
1921居昌 堂洞 堂집(거창 당동 당집)1기거창군1998-01-15
2022고성 최필간 고택(固城 崔必侃 古宅)5동, (246㎡)고성군2011-07-14