Overview

Dataset statistics

Number of variables6
Number of observations23
Missing cells40
Missing cells (%)29.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory53.7 B

Variable types

Text5
Categorical1

Dataset

Description활력2전북농촌유학시설현황20176월기준★
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202929

Alerts

Unnamed: 5 has constant value ""Constant
전라북도 농촌유학시설 현황 has 14 (60.9%) missing valuesMissing
Unnamed: 1 has 1 (4.3%) missing valuesMissing
Unnamed: 2 has 2 (8.7%) missing valuesMissing
Unnamed: 4 has 1 (4.3%) missing valuesMissing
Unnamed: 5 has 22 (95.7%) missing valuesMissing

Reproduction

Analysis started2024-03-14 02:36:19.910122
Analysis finished2024-03-14 02:36:20.420282
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전라북도 농촌유학시설 현황
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing14
Missing (%)60.9%
Memory size316.0 B
2024-03-14T11:36:20.503553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.6666667
Min length3

Characters and Unicode

Total characters33
Distinct characters25
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

Unique9 ?
Unique (%)100.0%

Sample

1st row시군(개)
2nd row7시군(20)
3rd row익산1
4th row정읍5
5th row김제5
ValueCountFrequency (%)
시군(개 1
11.1%
7시군(20 1
11.1%
익산1 1
11.1%
정읍5 1
11.1%
김제5 1
11.1%
완주1 1
11.1%
장수1 1
11.1%
임실6 1
11.1%
고창1 1
11.1%
2024-03-14T11:36:20.755994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
 
12.1%
시 2
 
6.1%
( 2
 
6.1%
) 2
 
6.1%
군 2
 
6.1%
5 2
 
6.1%
제 1
 
3.0%
고 1
 
3.0%
6 1
 
3.0%
실 1
 
3.0%
Other values (15) 15
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19
57.6%
Decimal Number 10
30.3%
Open Punctuation 2
 
6.1%
Close Punctuation 2
 
6.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 2
 
10.5%
군 2
 
10.5%
제 1
 
5.3%
고 1
 
5.3%
실 1
 
5.3%
임 1
 
5.3%
수 1
 
5.3%
장 1
 
5.3%
주 1
 
5.3%
완 1
 
5.3%
Other values (7) 7
36.8%
Decimal Number
ValueCountFrequency (%)
1 4
40.0%
5 2
20.0%
6 1
 
10.0%
0 1
 
10.0%
2 1
 
10.0%
7 1
 
10.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19
57.6%
Common 14
42.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 2
 
10.5%
군 2
 
10.5%
제 1
 
5.3%
고 1
 
5.3%
실 1
 
5.3%
임 1
 
5.3%
수 1
 
5.3%
장 1
 
5.3%
주 1
 
5.3%
완 1
 
5.3%
Other values (7) 7
36.8%
Common
ValueCountFrequency (%)
1 4
28.6%
( 2
14.3%
) 2
14.3%
5 2
14.3%
6 1
 
7.1%
0 1
 
7.1%
2 1
 
7.1%
7 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19
57.6%
ASCII 14
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
28.6%
( 2
14.3%
) 2
14.3%
5 2
14.3%
6 1
 
7.1%
0 1
 
7.1%
2 1
 
7.1%
7 1
 
7.1%
Hangul
ValueCountFrequency (%)
시 2
 
10.5%
군 2
 
10.5%
제 1
 
5.3%
고 1
 
5.3%
실 1
 
5.3%
임 1
 
5.3%
수 1
 
5.3%
장 1
 
5.3%
주 1
 
5.3%
완 1
 
5.3%
Other values (7) 7
36.8%

Unnamed: 1
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing1
Missing (%)4.3%
Memory size316.0 B
2024-03-14T11:36:20.945788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length19.772727
Min length1

Characters and Unicode

Total characters435
Distinct characters96
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

Unique22 ?
Unique (%)100.0%

Sample

1st row유학시설명
2nd row계
3rd row망성소망센터(망성면석곡길41-20)
4th row산적소굴 산촌유학(칠보면 칠보산로 1016-87)
5th row정읍자연학교(칠보면 동막길 129)
ValueCountFrequency (%)
등용마을(봉남면 2
 
3.0%
산촌유학(칠보면 2
 
3.0%
칠보산로 2
 
3.0%
유학시설명 1
 
1.5%
657 1
 
1.5%
불재로 1
 
1.5%
불재뫔인재학당(신덕면 1
 
1.5%
197-1 1
 
1.5%
대리로 1
 
1.5%
647 1
 
1.5%
Other values (53) 53
80.3%
2024-03-14T11:36:21.357136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44
 
10.1%
( 20
 
4.6%
) 20
 
4.6%
면 20
 
4.6%
1 19
 
4.4%
학 16
 
3.7%
길 12
 
2.8%
유 12
 
2.8%
- 10
 
2.3%
3 9
 
2.1%
Other values (86) 253
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 267
61.4%
Decimal Number 74
 
17.0%
Space Separator 44
 
10.1%
Open Punctuation 20
 
4.6%
Close Punctuation 20
 
4.6%
Dash Punctuation 10
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 20
 
7.5%
학 16
 
6.0%
길 12
 
4.5%
유 12
 
4.5%
을 8
 
3.0%
성 8
 
3.0%
마 8
 
3.0%
촌 8
 
3.0%
센 7
 
2.6%
보 7
 
2.6%
Other values (72) 161
60.3%
Decimal Number
ValueCountFrequency (%)
1 19
25.7%
3 9
12.2%
2 9
12.2%
7 7
 
9.5%
5 6
 
8.1%
9 6
 
8.1%
4 5
 
6.8%
6 5
 
6.8%
0 4
 
5.4%
8 4
 
5.4%
Space Separator
ValueCountFrequency (%)
44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 267
61.4%
Common 168
38.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 20
 
7.5%
학 16
 
6.0%
길 12
 
4.5%
유 12
 
4.5%
을 8
 
3.0%
성 8
 
3.0%
마 8
 
3.0%
촌 8
 
3.0%
센 7
 
2.6%
보 7
 
2.6%
Other values (72) 161
60.3%
Common
ValueCountFrequency (%)
44
26.2%
( 20
11.9%
) 20
11.9%
1 19
11.3%
- 10
 
6.0%
3 9
 
5.4%
2 9
 
5.4%
7 7
 
4.2%
5 6
 
3.6%
9 6
 
3.6%
Other values (4) 18
10.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 267
61.4%
ASCII 168
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44
26.2%
( 20
11.9%
) 20
11.9%
1 19
11.3%
- 10
 
6.0%
3 9
 
5.4%
2 9
 
5.4%
7 7
 
4.2%
5 6
 
3.6%
9 6
 
3.6%
Other values (4) 18
10.7%
Hangul
ValueCountFrequency (%)
면 20
 
7.5%
학 16
 
6.0%
길 12
 
4.5%
유 12
 
4.5%
을 8
 
3.0%
성 8
 
3.0%
마 8
 
3.0%
촌 8
 
3.0%
센 7
 
2.6%
보 7
 
2.6%
Other values (72) 161
60.3%

Unnamed: 2
Text

MISSING 

Distinct20
Distinct (%)95.2%
Missing2
Missing (%)8.7%
Memory size316.0 B
2024-03-14T11:36:21.598528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters63
Distinct characters48
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

Unique19 ?
Unique (%)90.5%

Sample

1st row대표자
2nd row김사랑
3rd row장보영
4th row정현숙
5th row김현정
ValueCountFrequency (%)
정현숙 2
 
9.1%
백미화 1
 
4.5%
정동석 1
 
4.5%
김주현 1
 
4.5%
채규상 1
 
4.5%
최광식 1
 
4.5%
민 1
 
4.5%
박 1
 
4.5%
이병창 1
 
4.5%
양성주 1
 
4.5%
Other values (11) 11
50.0%
2024-03-14T11:36:21.939123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 7
 
11.1%
정 5
 
7.9%
현 4
 
6.3%
숙 2
 
3.2%
주 2
 
3.2%
유 1
 
1.6%
박 1
 
1.6%
미 1
 
1.6%
화 1
 
1.6%
양 1
 
1.6%
Other values (38) 38
60.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62
98.4%
Space Separator 1
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 7
 
11.3%
정 5
 
8.1%
현 4
 
6.5%
숙 2
 
3.2%
주 2
 
3.2%
유 1
 
1.6%
박 1
 
1.6%
미 1
 
1.6%
화 1
 
1.6%
양 1
 
1.6%
Other values (37) 37
59.7%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62
98.4%
Common 1
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 7
 
11.3%
정 5
 
8.1%
현 4
 
6.5%
숙 2
 
3.2%
주 2
 
3.2%
유 1
 
1.6%
박 1
 
1.6%
미 1
 
1.6%
화 1
 
1.6%
양 1
 
1.6%
Other values (37) 37
59.7%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62
98.4%
ASCII 1
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 7
 
11.3%
정 5
 
8.1%
현 4
 
6.5%
숙 2
 
3.2%
주 2
 
3.2%
유 1
 
1.6%
박 1
 
1.6%
미 1
 
1.6%
화 1
 
1.6%
양 1
 
1.6%
Other values (37) 37
59.7%
ASCII
ValueCountFrequency (%)
1
100.0%

Unnamed: 3
Categorical

Distinct10
Distinct (%)43.5%
Missing0
Missing (%)0.0%
Memory size316.0 B
농가형
10 
센터형
5 
<NA>
 
1
유형
 
1
20개소
 
1
Other values (5)
5 

Length

Max length8
Median length3
Mean length4
Min length2

Unique

Unique8 ?
Unique (%)34.8%

Sample

1st row<NA>
2nd row유형
3rd row20개소
4th row농가형
5th row농가형

Common Values

ValueCountFrequency (%)
농가형 10
43.5%
센터형 5
21.7%
<NA> 1
 
4.3%
유형 1
 
4.3%
20개소 1
 
4.3%
가족형(5세대) 1
 
4.3%
가족형(7세대) 1
 
4.3%
가족형(2세대) 1
 
4.3%
가족형(3세대) 1
 
4.3%
농가결합형 1
 
4.3%

Length

2024-03-14T11:36:22.098376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:36:22.209915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농가형 10
43.5%
센터형 5
21.7%
na 1
 
4.3%
유형 1
 
4.3%
20개소 1
 
4.3%
가족형(5세대 1
 
4.3%
가족형(7세대 1
 
4.3%
가족형(2세대 1
 
4.3%
가족형(3세대 1
 
4.3%
농가결합형 1
 
4.3%

Unnamed: 4
Text

MISSING 

Distinct17
Distinct (%)77.3%
Missing1
Missing (%)4.3%
Memory size316.0 B
2024-03-14T11:36:22.349418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11.5
Mean length5.5
Min length3

Characters and Unicode

Total characters121
Distinct characters44
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)59.1%

Sample

1st row연계학교
2nd row26개학교
3rd row망성초
4th row수곡초, 칠보중
5th row수곡초, 정산중
ValueCountFrequency (%)
수곡초 5
 
15.6%
봉남초 3
 
9.4%
성덕초 2
 
6.2%
정산중 2
 
6.2%
신덕초 1
 
3.1%
아산초 1
 
3.1%
관촌중 1
 
3.1%
대리초 1
 
3.1%
신평초 1
 
3.1%
성수중 1
 
3.1%
Other values (14) 14
43.8%
2024-03-14T11:36:22.603314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
초 20
16.5%
10
 
8.3%
, 9
 
7.4%
중 9
 
7.4%
수 6
 
5.0%
곡 5
 
4.1%
산 5
 
4.1%
성 4
 
3.3%
덕 4
 
3.3%
봉 3
 
2.5%
Other values (34) 46
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99
81.8%
Space Separator 10
 
8.3%
Other Punctuation 10
 
8.3%
Decimal Number 2
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
초 20
20.2%
중 9
 
9.1%
수 6
 
6.1%
곡 5
 
5.1%
산 5
 
5.1%
성 4
 
4.0%
덕 4
 
4.0%
봉 3
 
3.0%
암 3
 
3.0%
남 3
 
3.0%
Other values (29) 37
37.4%
Other Punctuation
ValueCountFrequency (%)
, 9
90.0%
· 1
 
10.0%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
6 1
50.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 99
81.8%
Common 22
 
18.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
초 20
20.2%
중 9
 
9.1%
수 6
 
6.1%
곡 5
 
5.1%
산 5
 
5.1%
성 4
 
4.0%
덕 4
 
4.0%
봉 3
 
3.0%
암 3
 
3.0%
남 3
 
3.0%
Other values (29) 37
37.4%
Common
ValueCountFrequency (%)
10
45.5%
, 9
40.9%
2 1
 
4.5%
6 1
 
4.5%
· 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 99
81.8%
ASCII 21
 
17.4%
None 1
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
초 20
20.2%
중 9
 
9.1%
수 6
 
6.1%
곡 5
 
5.1%
산 5
 
5.1%
성 4
 
4.0%
덕 4
 
4.0%
봉 3
 
3.0%
암 3
 
3.0%
남 3
 
3.0%
Other values (29) 37
37.4%
ASCII
ValueCountFrequency (%)
10
47.6%
, 9
42.9%
2 1
 
4.8%
6 1
 
4.8%
None
ValueCountFrequency (%)
· 1
100.0%

Unnamed: 5
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing22
Missing (%)95.7%
Memory size316.0 B
2024-03-14T11:36:22.680933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
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

Unique1 ?
Unique (%)100.0%

Sample

1st row비고
ValueCountFrequency (%)
비고 1
100.0%
2024-03-14T11:36:22.838043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Correlations

2024-03-14T11:36:22.907284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전라북도 농촌유학시설 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4
전라북도 농촌유학시설 현황1.0001.0001.0001.0001.000
Unnamed: 11.0001.0001.0001.0001.000
Unnamed: 21.0001.0001.0000.7520.975
Unnamed: 31.0001.0000.7521.0000.961
Unnamed: 41.0001.0000.9750.9611.000

Missing values

2024-03-14T11:36:20.170980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:36:20.255268image/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.
2024-03-14T11:36:20.359853image/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

전라북도 농촌유학시설 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
0<NA><NA><NA><NA><NA><NA>
1시군(개)유학시설명대표자유형연계학교비고
27시군(20)계<NA>20개소26개학교<NA>
3익산1망성소망센터(망성면석곡길41-20)김사랑농가형망성초<NA>
4정읍5산적소굴 산촌유학(칠보면 칠보산로 1016-87)장보영농가형수곡초, 칠보중<NA>
5<NA>정읍자연학교(칠보면 동막길 129)정현숙농가형수곡초, 정산중<NA>
6<NA>고모샘네 마을배움 산촌유학(칠보면 석탄길 13-12)김현정농가형수곡초<NA>
7<NA>정읍농촌유학원(칠보면 칠보산로 1016-95)정현숙가족형(5세대)수곡초<NA>
8<NA>오리샘네(칠보면 동편길 81)김태오농가형수곡초, 정산중<NA>
9김제5학성강당농촌유학선비학교(성덕면 성동길 31-23)김종회센터형성덕초<NA>
전라북도 농촌유학시설 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
13<NA>상교마을(봉남면 접주2길 25)정동석농가형봉남초<NA>
14완주1열린마을 농촌유학센터(동상면 동상주천로 49)임진희센터형동상초, 고산중·고<NA>
15장수1광대마을(번암면 지지리 647)백미화농가형번암초 동화분교<NA>
16임실6대리마을농촌유학센터(신평면 대리로 197-1)양성주센터형대리초, 관촌중<NA>
17<NA>불재뫔인재학당(신덕면 불재로 657)이병창센터형신덕초, 마암초, 운암중<NA>
18<NA>덕치유학센터(덕치면 인덕로 1217)박 민가족형(7세대)덕치초, 섬진중<NA>
19<NA>지사초유학센터(지사면 방계3길 10)최광식가족형(2세대)지사초<NA>
20<NA>성수중유학센터(성수면 월삼로 354)채규상가족형(3세대)성수중<NA>
21<NA>신평농촌유학센터(신평면 호암 1길 35)김주현센터형신평초<NA>
22고창1온몸 농촌유학(아산면 영모정길 38-29)정유선농가결합형아산초, 아산중<NA>