Overview

Dataset statistics

Number of variables10
Number of observations81
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 KiB
Average record size in memory81.6 B

Variable types

Categorical8
Text2

Dataset

Description시군별농촌체험휴양마을지정현황2014
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202294

Alerts

체험 has constant value ""Constant
시군명 is highly overall correlated with 음식High correlation
음식 is highly overall correlated with 시군명High correlation
숙박 is highly imbalanced (83.3%)Imbalance
음식 is highly imbalanced (57.6%)Imbalance
마을명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 02:19:28.235502
Analysis finished2024-03-14 02:19:28.985778
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size780.0 B
남원시
12 
진안군
10 
무주군
정읍시
김제시
Other values (8)
35 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
남원시 12
14.8%
진안군 10
12.3%
무주군 9
11.1%
정읍시 8
9.9%
김제시 7
8.6%
완주군 7
8.6%
임실군 6
7.4%
부안군 6
7.4%
순창군 5
6.2%
익산시 4
 
4.9%
Other values (3) 7
8.6%

Length

2024-03-14T11:19:29.058843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
남원시 12
14.8%
진안군 10
12.3%
무주군 9
11.1%
정읍시 8
9.9%
김제시 7
8.6%
완주군 7
8.6%
임실군 6
7.4%
부안군 6
7.4%
순창군 5
6.2%
익산시 4
 
4.9%
Other values (3) 7
8.6%

마을명
Text

UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size780.0 B
2024-03-14T11:19:29.231698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length6.5679012
Min length4

Characters and Unicode

Total characters532
Distinct characters163
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)100.0%

Sample

1st row학전마을
2nd row성당포구마을
3rd row검지마을
4th row두동편백
5th row산들강웅포마을(고창)
ValueCountFrequency (%)
마을 2
 
2.3%
학전마을 1
 
1.2%
용계(당그래)마을 1
 
1.2%
논개생가(주촌)마을 1
 
1.2%
원촌마을 1
 
1.2%
치목삼베마을 1
 
1.2%
덕유산신선명품마을 1
 
1.2%
후도마을 1
 
1.2%
休무풍승지(철목)마을 1
 
1.2%
미항마을 1
 
1.2%
Other values (75) 75
87.2%
2024-03-14T11:19:29.542129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
 
16.2%
86
 
16.2%
) 27
 
5.1%
( 27
 
5.1%
8
 
1.5%
7
 
1.3%
6
 
1.1%
6
 
1.1%
5
 
0.9%
5
 
0.9%
Other values (153) 269
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 473
88.9%
Close Punctuation 27
 
5.1%
Open Punctuation 27
 
5.1%
Space Separator 5
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
86
 
18.2%
86
 
18.2%
8
 
1.7%
7
 
1.5%
6
 
1.3%
6
 
1.3%
5
 
1.1%
5
 
1.1%
5
 
1.1%
5
 
1.1%
Other values (150) 254
53.7%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 472
88.7%
Common 59
 
11.1%
Han 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
86
 
18.2%
86
 
18.2%
8
 
1.7%
7
 
1.5%
6
 
1.3%
6
 
1.3%
5
 
1.1%
5
 
1.1%
5
 
1.1%
5
 
1.1%
Other values (149) 253
53.6%
Common
ValueCountFrequency (%)
) 27
45.8%
( 27
45.8%
5
 
8.5%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 472
88.7%
ASCII 59
 
11.1%
CJK 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
86
 
18.2%
86
 
18.2%
8
 
1.7%
7
 
1.5%
6
 
1.3%
6
 
1.3%
5
 
1.1%
5
 
1.1%
5
 
1.1%
5
 
1.1%
Other values (149) 253
53.6%
ASCII
ValueCountFrequency (%)
) 27
45.8%
( 27
45.8%
5
 
8.5%
CJK
ValueCountFrequency (%)
1
100.0%

조성유형
Categorical

Distinct18
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size780.0 B
녹색농촌
28 
전통테마
11 
녹색농촌종합개발
10 
지자체
10 
종합개발
Other values (13)
17 

Length

Max length12
Median length4
Mean length4.962963
Min length3

Unique

Unique9 ?
Unique (%)11.1%

Sample

1st row정보화
2nd row전통테마
3rd row녹색농촌
4th row정보화
5th row녹색농촌종합개발

Common Values

ValueCountFrequency (%)
녹색농촌 28
34.6%
전통테마 11
 
13.6%
녹색농촌종합개발 10
 
12.3%
지자체 10
 
12.3%
종합개발 5
 
6.2%
정보화 2
 
2.5%
산촌생태 2
 
2.5%
농촌종합 2
 
2.5%
정보화녹색농촌 2
 
2.5%
정보화녹색농촌종합개발 1
 
1.2%
Other values (8) 8
 
9.9%

Length

2024-03-14T11:19:29.662865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
녹색농촌 28
34.6%
전통테마 11
 
13.6%
녹색농촌종합개발 10
 
12.3%
지자체 10
 
12.3%
종합개발 5
 
6.2%
정보화 2
 
2.5%
산촌생태 2
 
2.5%
농촌종합 2
 
2.5%
정보화녹색농촌 2
 
2.5%
녹색농촌산촌생태 1
 
1.2%
Other values (8) 8
 
9.9%

조성년도
Categorical

Distinct12
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size780.0 B
2007년
14 
2008년
10 
2006년
2010년
2005년
Other values (7)
31 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2005년
2nd row2006년
3rd row2010년
4th row2008년
5th row2007년

Common Values

ValueCountFrequency (%)
2007년 14
17.3%
2008년 10
12.3%
2006년 9
11.1%
2010년 9
11.1%
2005년 8
9.9%
2009년 8
9.9%
2011년 7
8.6%
2012년 5
 
6.2%
2004년 4
 
4.9%
2002년 3
 
3.7%
Other values (2) 4
 
4.9%

Length

2024-03-14T11:19:29.755080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2007년 14
17.3%
2008년 10
12.3%
2006년 9
11.1%
2010년 9
11.1%
2005년 8
9.9%
2009년 8
9.9%
2011년 7
8.6%
2012년 5
 
6.2%
2004년 4
 
4.9%
2002년 3
 
3.7%
Other values (2) 4
 
4.9%

주소
Text

Distinct80
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size780.0 B
2024-03-14T11:19:30.084658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length7
Mean length8.1975309
Min length6

Characters and Unicode

Total characters664
Distinct characters136
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

Unique79 ?
Unique (%)97.5%

Sample

1st row완산구 원당동
2nd row성당면 성당리
3rd row삼기면 오룡리
4th row성당면 두동리
5th row웅포면 강변로 284
ValueCountFrequency (%)
산내면 4
 
2.2%
안성면 3
 
1.7%
운봉읍 3
 
1.7%
보절면 2
 
1.1%
구이면 2
 
1.1%
계북면 2
 
1.1%
삼계면 2
 
1.1%
무풍면 2
 
1.1%
보안면 2
 
1.1%
부귀면 2
 
1.1%
Other values (146) 155
86.6%
2024-03-14T11:19:30.587428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
105
 
15.8%
69
 
10.4%
61
 
9.2%
16
 
2.4%
2 15
 
2.3%
12
 
1.8%
1 12
 
1.8%
12
 
1.8%
12
 
1.8%
11
 
1.7%
Other values (126) 339
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 487
73.3%
Space Separator 105
 
15.8%
Decimal Number 63
 
9.5%
Dash Punctuation 9
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
69
 
14.2%
61
 
12.5%
16
 
3.3%
12
 
2.5%
12
 
2.5%
12
 
2.5%
11
 
2.3%
10
 
2.1%
9
 
1.8%
9
 
1.8%
Other values (115) 266
54.6%
Decimal Number
ValueCountFrequency (%)
2 15
23.8%
1 12
19.0%
4 8
12.7%
0 5
 
7.9%
3 5
 
7.9%
6 5
 
7.9%
8 5
 
7.9%
5 4
 
6.3%
7 4
 
6.3%
Space Separator
ValueCountFrequency (%)
105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 487
73.3%
Common 177
 
26.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
69
 
14.2%
61
 
12.5%
16
 
3.3%
12
 
2.5%
12
 
2.5%
12
 
2.5%
11
 
2.3%
10
 
2.1%
9
 
1.8%
9
 
1.8%
Other values (115) 266
54.6%
Common
ValueCountFrequency (%)
105
59.3%
2 15
 
8.5%
1 12
 
6.8%
- 9
 
5.1%
4 8
 
4.5%
0 5
 
2.8%
3 5
 
2.8%
6 5
 
2.8%
8 5
 
2.8%
5 4
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 487
73.3%
ASCII 177
 
26.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
105
59.3%
2 15
 
8.5%
1 12
 
6.8%
- 9
 
5.1%
4 8
 
4.5%
0 5
 
2.8%
3 5
 
2.8%
6 5
 
2.8%
8 5
 
2.8%
5 4
 
2.3%
Hangul
ValueCountFrequency (%)
69
 
14.2%
61
 
12.5%
16
 
3.3%
12
 
2.5%
12
 
2.5%
12
 
2.5%
11
 
2.3%
10
 
2.1%
9
 
1.8%
9
 
1.8%
Other values (115) 266
54.6%

지정연도
Categorical

Distinct7
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size780.0 B
2011년
34 
2012년
24 
2010년
11 
2013년
2014년
 
2
Other values (2)
 
2

Length

Max length6
Median length5
Mean length5.0123457
Min length5

Unique

Unique2 ?
Unique (%)2.5%

Sample

1st row2011년
2nd row2009년
3rd row2011년
4th row2011년
5th row2012년

Common Values

ValueCountFrequency (%)
2011년 34
42.0%
2012년 24
29.6%
2010년 11
 
13.6%
2013년 8
 
9.9%
2014년 2
 
2.5%
2009년 1
 
1.2%
2013년 1
 
1.2%

Length

2024-03-14T11:19:31.121468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:19:31.260388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2011년 34
42.0%
2012년 24
29.6%
2010년 11
 
13.6%
2013년 9
 
11.1%
2014년 2
 
2.5%
2009년 1
 
1.2%

지정월
Categorical

Distinct12
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size780.0 B
11월
16 
10월
11 
3월
10 
1월
2월
Other values (7)
29 

Length

Max length3
Median length2
Mean length2.4197531
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11월
2nd row9월
3rd row11월
4th row11월
5th row3월

Common Values

ValueCountFrequency (%)
11월 16
19.8%
10월 11
13.6%
3월 10
12.3%
1월 8
9.9%
2월 7
8.6%
12월 7
8.6%
8월 4
 
4.9%
6월 4
 
4.9%
7월 4
 
4.9%
4월 4
 
4.9%
Other values (2) 6
 
7.4%

Length

2024-03-14T11:19:31.373194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
11월 16
19.8%
10월 11
13.6%
3월 10
12.3%
1월 8
9.9%
2월 7
8.6%
12월 7
8.6%
8월 4
 
4.9%
6월 4
 
4.9%
7월 4
 
4.9%
4월 4
 
4.9%
Other values (2) 6
 
7.4%

숙박
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size780.0 B
79 
-
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
79
97.5%
- 2
 
2.5%

Length

2024-03-14T11:19:31.473706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:19:31.550310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
79
97.5%
2
 
2.5%

체험
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size780.0 B
81 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
81
100.0%

Length

2024-03-14T11:19:31.630256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:19:31.706979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
81
100.0%

음식
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size780.0 B
74 
-
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
74
91.4%
- 7
 
8.6%

Length

2024-03-14T11:19:31.781504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:19:31.858838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
74
91.4%
7
 
8.6%

Correlations

2024-03-14T11:19:31.933792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명마을명조성유형조성년도주소지정연도지정월숙박음식
시군명1.0001.0000.3940.0001.0000.4740.2400.0000.581
마을명1.0001.0001.0001.0001.0001.0001.0001.0001.000
조성유형0.3941.0001.0000.0000.9930.6920.6800.0000.462
조성년도0.0001.0000.0001.0000.9750.6650.6820.0000.277
주소1.0001.0000.9930.9751.0000.9830.9600.0001.000
지정연도0.4741.0000.6920.6650.9831.0000.6060.0000.000
지정월0.2401.0000.6800.6820.9600.6061.0000.0000.440
숙박0.0001.0000.0000.0000.0000.0000.0001.0000.000
음식0.5811.0000.4620.2771.0000.0000.4400.0001.000
2024-03-14T11:19:32.040487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조성년도조성유형음식시군명숙박지정연도지정월
조성년도1.0000.0000.1970.0000.0000.3870.251
조성유형0.0001.0000.3230.1300.0000.3640.282
음식0.1970.3231.0000.5040.0000.0000.317
시군명0.0000.1300.5041.0000.0000.2290.081
숙박0.0000.0000.0000.0001.0000.0000.000
지정연도0.3870.3640.0000.2290.0001.0000.336
지정월0.2510.2820.3170.0810.0000.3361.000
2024-03-14T11:19:32.134103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명조성유형조성년도지정연도지정월숙박음식
시군명1.0000.1300.0000.2290.0810.0000.504
조성유형0.1301.0000.0000.3640.2820.0000.323
조성년도0.0000.0001.0000.3870.2510.0000.197
지정연도0.2290.3640.3871.0000.3360.0000.000
지정월0.0810.2820.2510.3361.0000.0000.317
숙박0.0000.0000.0000.0000.0001.0000.000
음식0.5040.3230.1970.0000.3170.0001.000

Missing values

2024-03-14T11:19:28.826082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:19:28.940530image/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

시군명마을명조성유형조성년도주소지정연도지정월숙박체험음식
0전주시학전마을정보화2005년완산구 원당동2011년11월
1익산시성당포구마을전통테마2006년성당면 성당리2009년9월
2익산시검지마을녹색농촌2010년삼기면 오룡리2011년11월
3익산시두동편백정보화2008년성당면 두동리2011년11월
4익산시산들강웅포마을(고창)녹색농촌종합개발2007년웅포면 강변로 2842012년3월
5정읍시천단마을녹색농촌종합개발2007년신태인읍 백산리2010년11월
6정읍시공동마을녹색농촌2005년산외면 오공리2010년11월
7정읍시사교마을(달고운마을)녹색농촌2008년산내면 두월리2011년2월
8정읍시신기마을(십장생마을)녹색농촌2005년산내면 능교리2011년2월
9정읍시종성마을(산호수마을)녹색농촌2006년산내면 종성리2011년11월
시군명마을명조성유형조성년도주소지정연도지정월숙박체험음식
71순창군도라지마을건강장수종합개발2005년팔덕면 평창길 42013년9월
72순창군종곡마을종합개발2013년쌍치면 순정로 12532014년1월
73고창군고색창연마을전통테마2007년신림면 가평리 651-42011년12월
74고창군고산돌맹(상금)마을녹색농촌2011년대산면 상금리 28-112012년11월
75부안군우동우리밀마을녹색농촌종합개발2007년보안면 우동리2011년3월
76부안군사랑감(용사만회)마을녹색농촌2007년보안면 남포리2011년9월
77부안군계화도(계상)마을녹색농촌종합개발2006년계화면 계상길2012년10월
78부안군각동마을녹색농촌2010년줄포면 선돌로2012년10월
79부안군운호(구름호수)마을녹색농촌2007년진서면 운호길2012년10월
80부안군후촌 갈대숲 마을녹색농촌2007년줄포면 후촌길 672012년12월