Overview

Dataset statistics

Number of variables5
Number of observations55
Missing cells1
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory43.3 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description전북특별자치도 전통한옥체험 프로그램 안내(시설명, 위치, 프로그램 등)우리기관에서는 더 이상 생성 불가 데이터입니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055601/fileData.do

Alerts

주소 has 1 (1.8%) missing valuesMissing

Reproduction

Analysis started2024-03-14 17:32:41.991521
Analysis finished2024-03-14 17:32:43.733398
Duration1.74 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

Distinct8
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2011.7636
Minimum2006
Maximum2015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size623.0 B
2024-03-15T02:32:43.862077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2006
5-th percentile2009
Q12010
median2012
Q32013
95-th percentile2015
Maximum2015
Range9
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.9903809
Coefficient of variation (CV)0.00098937115
Kurtosis-0.13819293
Mean2011.7636
Median Absolute Deviation (MAD)1
Skewness-0.34749021
Sum110647
Variance3.9616162
MonotonicityIncreasing
2024-03-15T02:32:44.164463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2013 12
21.8%
2012 11
20.0%
2010 9
16.4%
2009 7
12.7%
2011 5
9.1%
2014 5
9.1%
2015 5
9.1%
2006 1
 
1.8%
ValueCountFrequency (%)
2006 1
 
1.8%
2009 7
12.7%
2010 9
16.4%
2011 5
9.1%
2012 11
20.0%
2013 12
21.8%
2014 5
9.1%
2015 5
9.1%
ValueCountFrequency (%)
2015 5
9.1%
2014 5
9.1%
2013 12
21.8%
2012 11
20.0%
2011 5
9.1%
2010 9
16.4%
2009 7
12.7%
2006 1
 
1.8%

시군명
Categorical

Distinct8
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Memory size568.0 B
전주시
37 
완주군
6 
전주시
5 
김제시
 
2
정읍시
 
2
Other values (3)
 
3

Length

Max length4
Median length3
Mean length3.0909091
Min length3

Unique

Unique3 ?
Unique (%)5.5%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 37
67.3%
완주군 6
 
10.9%
전주시 5
 
9.1%
김제시 2
 
3.6%
정읍시 2
 
3.6%
진안군 1
 
1.8%
부안군 1
 
1.8%
남원시 1
 
1.8%

Length

2024-03-15T02:32:44.575863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:32:45.020052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전주시 42
76.4%
완주군 6
 
10.9%
김제시 2
 
3.6%
정읍시 2
 
3.6%
진안군 1
 
1.8%
부안군 1
 
1.8%
남원시 1
 
1.8%

업체명
Text

Distinct40
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Memory size568.0 B
2024-03-15T02:32:46.068556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.6909091
Min length2

Characters and Unicode

Total characters258
Distinct characters81
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

Unique29 ?
Unique (%)52.7%

Sample

1st row한옥생활체험관
2nd row동 락 원
3rd row양 사 재
4th row아 세 헌
5th row설 예 원
ValueCountFrequency (%)
헌 6
 
6.1%
원 5
 
5.1%
당 4
 
4.0%
고택 4
 
4.0%
한옥생활체험관 3
 
3.0%
세 3
 
3.0%
학 3
 
3.0%
인 3
 
3.0%
양 3
 
3.0%
사 3
 
3.0%
Other values (47) 62
62.6%
2024-03-15T02:32:47.656722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44
 
17.1%
헌 11
 
4.3%
당 10
 
3.9%
옥 9
 
3.5%
한 7
 
2.7%
고 7
 
2.7%
원 7
 
2.7%
재 7
 
2.7%
사 6
 
2.3%
아 6
 
2.3%
Other values (71) 144
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 214
82.9%
Space Separator 44
 
17.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
헌 11
 
5.1%
당 10
 
4.7%
옥 9
 
4.2%
한 7
 
3.3%
고 7
 
3.3%
원 7
 
3.3%
재 7
 
3.3%
사 6
 
2.8%
아 6
 
2.8%
체 5
 
2.3%
Other values (70) 139
65.0%
Space Separator
ValueCountFrequency (%)
44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 214
82.9%
Common 44
 
17.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
헌 11
 
5.1%
당 10
 
4.7%
옥 9
 
4.2%
한 7
 
3.3%
고 7
 
3.3%
원 7
 
3.3%
재 7
 
3.3%
사 6
 
2.8%
아 6
 
2.8%
체 5
 
2.3%
Other values (70) 139
65.0%
Common
ValueCountFrequency (%)
44
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 214
82.9%
ASCII 44
 
17.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44
100.0%
Hangul
ValueCountFrequency (%)
헌 11
 
5.1%
당 10
 
4.7%
옥 9
 
4.2%
한 7
 
3.3%
고 7
 
3.3%
원 7
 
3.3%
재 7
 
3.3%
사 6
 
2.8%
아 6
 
2.8%
체 5
 
2.3%
Other values (70) 139
65.0%

주소
Text

MISSING 

Distinct35
Distinct (%)64.8%
Missing1
Missing (%)1.8%
Memory size568.0 B
2024-03-15T02:32:48.727449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length15.37037
Min length12

Characters and Unicode

Total characters830
Distinct characters70
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)46.3%

Sample

1st row전주시 완산구 어진길29
2nd row전주시 완산구 은행로 33-6
3rd row전주시 완산구 오목대길 40
4th row전주시 완산구 은행로 39
5th row전주시 완산구 전동 74
ValueCountFrequency (%)
전주시 42
20.0%
완산구 42
20.0%
은행로 11
 
5.2%
향교길 10
 
4.8%
완주군 6
 
2.9%
39 5
 
2.4%
45 4
 
1.9%
최명희길 4
 
1.9%
40 3
 
1.4%
어진길 3
 
1.4%
Other values (58) 80
38.1%
2024-03-15T02:32:51.104883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
157
18.9%
주 51
 
6.1%
완 48
 
5.8%
전 46
 
5.5%
시 46
 
5.5%
산 46
 
5.5%
구 44
 
5.3%
길 35
 
4.2%
- 23
 
2.8%
1 23
 
2.8%
Other values (60) 311
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 504
60.7%
Space Separator 157
 
18.9%
Decimal Number 146
 
17.6%
Dash Punctuation 23
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 51
 
10.1%
완 48
 
9.5%
전 46
 
9.1%
시 46
 
9.1%
산 46
 
9.1%
구 44
 
8.7%
길 35
 
6.9%
로 16
 
3.2%
은 12
 
2.4%
행 11
 
2.2%
Other values (48) 149
29.6%
Decimal Number
ValueCountFrequency (%)
1 23
15.8%
3 20
13.7%
5 20
13.7%
2 17
11.6%
4 17
11.6%
9 17
11.6%
0 9
 
6.2%
8 9
 
6.2%
7 8
 
5.5%
6 6
 
4.1%
Space Separator
ValueCountFrequency (%)
157
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 504
60.7%
Common 326
39.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 51
 
10.1%
완 48
 
9.5%
전 46
 
9.1%
시 46
 
9.1%
산 46
 
9.1%
구 44
 
8.7%
길 35
 
6.9%
로 16
 
3.2%
은 12
 
2.4%
행 11
 
2.2%
Other values (48) 149
29.6%
Common
ValueCountFrequency (%)
157
48.2%
- 23
 
7.1%
1 23
 
7.1%
3 20
 
6.1%
5 20
 
6.1%
2 17
 
5.2%
4 17
 
5.2%
9 17
 
5.2%
0 9
 
2.8%
8 9
 
2.8%
Other values (2) 14
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 504
60.7%
ASCII 326
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
157
48.2%
- 23
 
7.1%
1 23
 
7.1%
3 20
 
6.1%
5 20
 
6.1%
2 17
 
5.2%
4 17
 
5.2%
9 17
 
5.2%
0 9
 
2.8%
8 9
 
2.8%
Other values (2) 14
 
4.3%
Hangul
ValueCountFrequency (%)
주 51
 
10.1%
완 48
 
9.5%
전 46
 
9.1%
시 46
 
9.1%
산 46
 
9.1%
구 44
 
8.7%
길 35
 
6.9%
로 16
 
3.2%
은 12
 
2.4%
행 11
 
2.2%
Other values (48) 149
29.6%

세부사업명
Text

Distinct42
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Memory size568.0 B
2024-03-15T02:32:53.064863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length8.7818182
Min length2

Characters and Unicode

Total characters483
Distinct characters94
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)58.2%

Sample

1st row한지공예외 9건
2nd row비빕밥외 5건
3rd row한지엽서쓰기외 1건
4th row우리소리외 2건
5th row생활예절외 2건
ValueCountFrequency (%)
외 18
 
14.5%
2건 14
 
11.3%
1건 12
 
9.7%
한지엽서쓰기외 3
 
2.4%
다래외 3
 
2.4%
6건 3
 
2.4%
우리소리외 3
 
2.4%
전통놀이체험 3
 
2.4%
체험 2
 
1.6%
등 2
 
1.6%
Other values (49) 61
49.2%
2024-03-15T02:32:55.420216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
70
 
14.5%
외 42
 
8.7%
건 38
 
7.9%
험 21
 
4.3%
체 20
 
4.1%
1 15
 
3.1%
2 15
 
3.1%
다 13
 
2.7%
리 10
 
2.1%
예 9
 
1.9%
Other values (84) 230
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 364
75.4%
Space Separator 70
 
14.5%
Decimal Number 42
 
8.7%
Other Punctuation 7
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
외 42
 
11.5%
건 38
 
10.4%
험 21
 
5.8%
체 20
 
5.5%
다 13
 
3.6%
리 10
 
2.7%
예 9
 
2.5%
전 8
 
2.2%
통 8
 
2.2%
공 8
 
2.2%
Other values (75) 187
51.4%
Decimal Number
ValueCountFrequency (%)
1 15
35.7%
2 15
35.7%
6 3
 
7.1%
3 3
 
7.1%
4 2
 
4.8%
9 2
 
4.8%
5 2
 
4.8%
Space Separator
ValueCountFrequency (%)
70
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 364
75.4%
Common 119
 
24.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
외 42
 
11.5%
건 38
 
10.4%
험 21
 
5.8%
체 20
 
5.5%
다 13
 
3.6%
리 10
 
2.7%
예 9
 
2.5%
전 8
 
2.2%
통 8
 
2.2%
공 8
 
2.2%
Other values (75) 187
51.4%
Common
ValueCountFrequency (%)
70
58.8%
1 15
 
12.6%
2 15
 
12.6%
, 7
 
5.9%
6 3
 
2.5%
3 3
 
2.5%
4 2
 
1.7%
9 2
 
1.7%
5 2
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 364
75.4%
ASCII 119
 
24.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
70
58.8%
1 15
 
12.6%
2 15
 
12.6%
, 7
 
5.9%
6 3
 
2.5%
3 3
 
2.5%
4 2
 
1.7%
9 2
 
1.7%
5 2
 
1.7%
Hangul
ValueCountFrequency (%)
외 42
 
11.5%
건 38
 
10.4%
험 21
 
5.8%
체 20
 
5.5%
다 13
 
3.6%
리 10
 
2.7%
예 9
 
2.5%
전 8
 
2.2%
통 8
 
2.2%
공 8
 
2.2%
Other values (75) 187
51.4%

Interactions

2024-03-15T02:32:42.590576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T02:32:55.793433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도시군명업체명주소세부사업명
연도1.0000.6020.0000.0000.000
시군명0.6021.0000.9880.9790.970
업체명0.0000.9881.0001.0000.996
주소0.0000.9791.0001.0000.997
세부사업명0.0000.9700.9960.9971.000
2024-03-15T02:32:56.121348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도시군명
연도1.0000.319
시군명0.3191.000

Missing values

2024-03-15T02:32:43.004776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T02:32:43.551240image/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

연도시군명업체명주소세부사업명
02006전주시한옥생활체험관전주시 완산구 어진길29한지공예외 9건
12009전주시동 락 원전주시 완산구 은행로 33-6비빕밥외 5건
22009전주시양 사 재전주시 완산구 오목대길 40한지엽서쓰기외 1건
32009전주시아 세 헌전주시 완산구 은행로 39우리소리외 2건
42009전주시설 예 원전주시 완산구 전동 74생활예절외 2건
52009전주시풍 남 헌전주시 완산구 은행로 35녹차만들기외 1건
62009전주시학 인 당전주시 완산구 향교길 45다래외 6건
72009김제시소 묵 헌<NA>다도
82010전주시한옥생활체험관전주시 완산구 어진길29한지공예외 9건
92010전주시양 사 재전주시 완산구 오목대길 40한지엽서쓰기외 1건
연도시군명업체명주소세부사업명
452014전주시전주한옥생활체험관전주시 완산구 어진길 29한복체험외1
462014전주시삼도헌전주시 완산구 최명희길 12-8소리체험외2
472014전주시싸목싸목전주시 완산구 향교길 97-18다도체험외1
482014전주시귀거래사전주시 완산구 향교길 97-30대청음악회 출연료,
492014전주시청명헌전주시 완산구 은행로 39공연,슬로푸드외3
502015전주시이오당전주시 완산구 향교길 85-9문화예술공연, 전통차, 다과
512015전주시이화고택전주시 완산구 한지길 91우리집표 음식만들기 체험
522015전주시예 다 원전주시 완산구 향교길 85-34한복체험, 다도다식체험 등
532015전주시향 촌전주시 완산구 어진길 65향음다래체험
542015완주군행복드림한옥완주군 용진면 봉서안길 181-21전통놀이체험 등