Overview

Dataset statistics

Number of variables6
Number of observations23
Missing cells26
Missing cells (%)18.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory53.7 B

Variable types

Text4
Categorical1
Unsupported1

Dataset

Description전북농촌유학시설현황20166월기준
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202769

Alerts

전라북도 농촌유학시설 현황 has 13 (56.5%) 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 9 (39.1%) missing valuesMissing
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 00:31:58.732906
Analysis finished2024-03-14 00:31:59.235543
Duration0.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전라북도 농촌유학시설 현황
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing13
Missing (%)56.5%
Memory size316.0 B
2024-03-14T09:31:59.317187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.6
Min length3

Characters and Unicode

Total characters36
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

Unique10 ?
Unique (%)100.0%

Sample

1st row시군(개)
2nd row8시군(20)
3rd row익산1
4th row정읍6
5th row김제2
ValueCountFrequency (%)
시군(개 1
10.0%
8시군(20 1
10.0%
익산1 1
10.0%
정읍6 1
10.0%
김제2 1
10.0%
완주2 1
10.0%
무주1 1
10.0%
장수1 1
10.0%
임실6 1
10.0%
고창1 1
10.0%
2024-03-14T09:31:59.587745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
 
11.1%
2 3
 
8.3%
시 2
 
5.6%
( 2
 
5.6%
) 2
 
5.6%
군 2
 
5.6%
6 2
 
5.6%
주 2
 
5.6%
완 1
 
2.8%
고 1
 
2.8%
Other values (15) 15
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21
58.3%
Decimal Number 11
30.6%
Open Punctuation 2
 
5.6%
Close Punctuation 2
 
5.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 2
 
9.5%
군 2
 
9.5%
주 2
 
9.5%
완 1
 
4.8%
고 1
 
4.8%
실 1
 
4.8%
임 1
 
4.8%
수 1
 
4.8%
장 1
 
4.8%
무 1
 
4.8%
Other values (8) 8
38.1%
Decimal Number
ValueCountFrequency (%)
1 4
36.4%
2 3
27.3%
6 2
18.2%
0 1
 
9.1%
8 1
 
9.1%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21
58.3%
Common 15
41.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 2
 
9.5%
군 2
 
9.5%
주 2
 
9.5%
완 1
 
4.8%
고 1
 
4.8%
실 1
 
4.8%
임 1
 
4.8%
수 1
 
4.8%
장 1
 
4.8%
무 1
 
4.8%
Other values (8) 8
38.1%
Common
ValueCountFrequency (%)
1 4
26.7%
2 3
20.0%
( 2
13.3%
) 2
13.3%
6 2
13.3%
0 1
 
6.7%
8 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21
58.3%
ASCII 15
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
26.7%
2 3
20.0%
( 2
13.3%
) 2
13.3%
6 2
13.3%
0 1
 
6.7%
8 1
 
6.7%
Hangul
ValueCountFrequency (%)
시 2
 
9.5%
군 2
 
9.5%
주 2
 
9.5%
완 1
 
4.8%
고 1
 
4.8%
실 1
 
4.8%
임 1
 
4.8%
수 1
 
4.8%
장 1
 
4.8%
무 1
 
4.8%
Other values (8) 8
38.1%

Unnamed: 1
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing1
Missing (%)4.3%
Memory size316.0 B
2024-03-14T09:31:59.811837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25.5
Mean length20.545455
Min length1

Characters and Unicode

Total characters452
Distinct characters107
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 (%)
산촌유학(칠보면 2
 
2.9%
칠보산로 2
 
2.9%
유학시설명 1
 
1.4%
58 1
 
1.4%
657 1
 
1.4%
불재로 1
 
1.4%
불재뫔인재학당(신덕면 1
 
1.4%
197-1 1
 
1.4%
대리로 1
 
1.4%
대리마을농촌유학센터(신평면 1
 
1.4%
Other values (57) 57
82.6%
2024-03-14T09:32:00.153456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47
 
10.4%
( 20
 
4.4%
학 20
 
4.4%
) 20
 
4.4%
면 19
 
4.2%
1 19
 
4.2%
유 15
 
3.3%
길 12
 
2.7%
촌 11
 
2.4%
센 10
 
2.2%
Other values (97) 259
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 286
63.3%
Decimal Number 70
 
15.5%
Space Separator 47
 
10.4%
Open Punctuation 20
 
4.4%
Close Punctuation 20
 
4.4%
Dash Punctuation 9
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 20
 
7.0%
면 19
 
6.6%
유 15
 
5.2%
길 12
 
4.2%
촌 11
 
3.8%
센 10
 
3.5%
터 10
 
3.5%
산 10
 
3.5%
성 8
 
2.8%
로 8
 
2.8%
Other values (83) 163
57.0%
Decimal Number
ValueCountFrequency (%)
1 19
27.1%
3 10
14.3%
2 8
11.4%
5 7
 
10.0%
6 5
 
7.1%
7 5
 
7.1%
9 5
 
7.1%
0 4
 
5.7%
8 4
 
5.7%
4 3
 
4.3%
Space Separator
ValueCountFrequency (%)
47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 286
63.3%
Common 166
36.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 20
 
7.0%
면 19
 
6.6%
유 15
 
5.2%
길 12
 
4.2%
촌 11
 
3.8%
센 10
 
3.5%
터 10
 
3.5%
산 10
 
3.5%
성 8
 
2.8%
로 8
 
2.8%
Other values (83) 163
57.0%
Common
ValueCountFrequency (%)
47
28.3%
( 20
12.0%
) 20
12.0%
1 19
11.4%
3 10
 
6.0%
- 9
 
5.4%
2 8
 
4.8%
5 7
 
4.2%
6 5
 
3.0%
7 5
 
3.0%
Other values (4) 16
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 286
63.3%
ASCII 166
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47
28.3%
( 20
12.0%
) 20
12.0%
1 19
11.4%
3 10
 
6.0%
- 9
 
5.4%
2 8
 
4.8%
5 7
 
4.2%
6 5
 
3.0%
7 5
 
3.0%
Other values (4) 16
 
9.6%
Hangul
ValueCountFrequency (%)
학 20
 
7.0%
면 19
 
6.6%
유 15
 
5.2%
길 12
 
4.2%
촌 11
 
3.8%
센 10
 
3.5%
터 10
 
3.5%
산 10
 
3.5%
성 8
 
2.8%
로 8
 
2.8%
Other values (83) 163
57.0%

Unnamed: 2
Text

MISSING 

Distinct20
Distinct (%)95.2%
Missing2
Missing (%)8.7%
Memory size316.0 B
2024-03-14T09:32:00.300658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters63
Distinct characters43
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%
유영일 1
 
4.5%
유영배 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%
2024-03-14T09:32:00.541278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 6
 
9.5%
정 4
 
6.3%
현 4
 
6.3%
영 3
 
4.8%
유 3
 
4.8%
이 2
 
3.2%
주 2
 
3.2%
태 2
 
3.2%
민 2
 
3.2%
숙 2
 
3.2%
Other values (33) 33
52.4%

Most occurring categories

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

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 6
 
9.7%
정 4
 
6.5%
현 4
 
6.5%
영 3
 
4.8%
유 3
 
4.8%
이 2
 
3.2%
주 2
 
3.2%
태 2
 
3.2%
민 2
 
3.2%
숙 2
 
3.2%
Other values (32) 32
51.6%
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 6
 
9.7%
정 4
 
6.5%
현 4
 
6.5%
영 3
 
4.8%
유 3
 
4.8%
이 2
 
3.2%
주 2
 
3.2%
태 2
 
3.2%
민 2
 
3.2%
숙 2
 
3.2%
Other values (32) 32
51.6%
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 6
 
9.7%
정 4
 
6.5%
현 4
 
6.5%
영 3
 
4.8%
유 3
 
4.8%
이 2
 
3.2%
주 2
 
3.2%
태 2
 
3.2%
민 2
 
3.2%
숙 2
 
3.2%
Other values (32) 32
51.6%
ASCII
ValueCountFrequency (%)
1
100.0%

Unnamed: 3
Categorical

Distinct11
Distinct (%)47.8%
Missing0
Missing (%)0.0%
Memory size316.0 B
센터형
9 
농가형
5 
<NA>
1 
유형
1 
20개소
1 
Other values (6)
6 

Length

Max length8
Median length3
Mean length4
Min length2

Unique

Unique9 ?
Unique (%)39.1%

Sample

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

Common Values

ValueCountFrequency (%)
센터형 9
39.1%
농가형 5
21.7%
<NA> 1
 
4.3%
유형 1
 
4.3%
20개소 1
 
4.3%
가족형 1
 
4.3%
가족형(5세대) 1
 
4.3%
가족형(7세대) 1
 
4.3%
가족형(2세대) 1
 
4.3%
가족형(3세대) 1
 
4.3%

Length

2024-03-14T09:32:00.653106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
센터형 9
39.1%
농가형 5
21.7%
na 1
 
4.3%
유형 1
 
4.3%
20개소 1
 
4.3%
가족형 1
 
4.3%
가족형(5세대 1
 
4.3%
가족형(7세대 1
 
4.3%
가족형(2세대 1
 
4.3%
가족형(3세대 1
 
4.3%

Unnamed: 4
Text

MISSING 

Distinct18
Distinct (%)81.8%
Missing1
Missing (%)4.3%
Memory size316.0 B
2024-03-14T09:32:00.795852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length9
Mean length5.4545455
Min length3

Characters and Unicode

Total characters120
Distinct characters48
Distinct categories6 ?
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 (%)68.2%

Sample

1st row연계학교
2nd row26개학교
3rd row망성초
4th row수곡초
5th row수곡초칠보중
ValueCountFrequency (%)
수곡초칠보중 3
 
13.0%
수곡초 2
 
8.7%
성덕초 2
 
8.7%
대리초관촌중성수중 1
 
4.3%
동화분교,번암중마사고(장수 1
 
4.3%
번암초 1
 
4.3%
신평초 1
 
4.3%
성수중 1
 
4.3%
지사초 1
 
4.3%
덕치초 1
 
4.3%
Other values (9) 9
39.1%
2024-03-14T09:32:01.314053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
초 19
 
15.8%
중 12
 
10.0%
수 8
 
6.7%
성 6
 
5.0%
곡 5
 
4.2%
덕 5
 
4.2%
암 4
 
3.3%
교 4
 
3.3%
고 4
 
3.3%
보 3
 
2.5%
Other values (38) 50
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 113
94.2%
Other Punctuation 2
 
1.7%
Decimal Number 2
 
1.7%
Close Punctuation 1
 
0.8%
Open Punctuation 1
 
0.8%
Space Separator 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
초 19
16.8%
중 12
 
10.6%
수 8
 
7.1%
성 6
 
5.3%
곡 5
 
4.4%
덕 5
 
4.4%
암 4
 
3.5%
교 4
 
3.5%
고 4
 
3.5%
보 3
 
2.7%
Other values (31) 43
38.1%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
· 1
50.0%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
6 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 113
94.2%
Common 7
 
5.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
초 19
16.8%
중 12
 
10.6%
수 8
 
7.1%
성 6
 
5.3%
곡 5
 
4.4%
덕 5
 
4.4%
암 4
 
3.5%
교 4
 
3.5%
고 4
 
3.5%
보 3
 
2.7%
Other values (31) 43
38.1%
Common
ValueCountFrequency (%)
) 1
14.3%
( 1
14.3%
, 1
14.3%
1
14.3%
2 1
14.3%
6 1
14.3%
· 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 113
94.2%
ASCII 6
 
5.0%
None 1
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
초 19
16.8%
중 12
 
10.6%
수 8
 
7.1%
성 6
 
5.3%
곡 5
 
4.4%
덕 5
 
4.4%
암 4
 
3.5%
교 4
 
3.5%
고 4
 
3.5%
보 3
 
2.7%
Other values (31) 43
38.1%
ASCII
ValueCountFrequency (%)
) 1
16.7%
( 1
16.7%
, 1
16.7%
1
16.7%
2 1
16.7%
6 1
16.7%
None
ValueCountFrequency (%)
· 1
100.0%

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9
Missing (%)39.1%
Memory size316.0 B

Correlations

2024-03-14T09:32:01.391716image/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: 21.0001.0001.0000.7881.000
Unnamed: 31.0001.0000.7881.0000.936
Unnamed: 41.0001.0001.0000.9361.000

Missing values

2024-03-14T09:31:59.005488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:31:59.093325image/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.
2024-03-14T09:31:59.177508image/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>NaN
1시군(개)유학시설명대표자유형연계학교비고
28시군(20)계<NA>20개소26개학교NaN
3익산1망성소망센터(망성면석곡길41-20)김사랑가족형망성초1
4정읍6산적소굴 산촌유학(칠보면 칠보산로 1016-87)장보영농가형수곡초3
5<NA>정읍자연학교(칠보면 동막길 129)정현숙농가형수곡초칠보중NaN
6<NA>고모샘네 마을배움 산촌유학(칠보면 석탄길 13-12)김현정농가형수곡초NaN
7<NA>정읍농촌유학원(칠보면 칠보산로 1016-95)정현숙가족형(5세대)수곡초칠보중NaN
8<NA>고산산촌유학센터(산내면 황토길 53-6)조태경센터형능교초NaN
9<NA>오리샘네(칠보면 동편길 81)김태오농가형수곡초칠보중NaN
전라북도 농촌유학시설 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
13<NA>안덕마을 농촌유학센터(구이면 장파길 72)유영배센터형대덕초구이중2
14무주1하늘섬 내도 산촌유학센터(무주읍 내도로 356)이민구센터형무주중안성고2
15장수1철딱서니학교(번암면 상동1길 58)유영일센터형번암초 동화분교,번암중마사고(장수)3
16임실6대리마을농촌유학센터(신평면 대리로 197-1)양성주센터형대리초관촌중성수중3
17<NA>불재뫔인재학당(신덕면 불재로 657)이병창센터형신덕초마암초운암중3
18<NA>덕치유학센터(덕치면 인덕로 1217)박 민가족형(7세대)덕치초1
19<NA>지사초유학센터(지사면 방계3길 10)최광식가족형(2세대)지사초1
20<NA>성수중유학센터(성수면 월삼로 354)채규상가족형(3세대)성수중NaN
21<NA>신평농촌유학센터(신평면 호암 1길 35)김주현센터형신평초1
22고창1온몸 농촌유학(아산면 영모정길 38-29)정유선농가결합형아산초아산중2