Overview

Dataset statistics

Number of variables6
Number of observations67
Missing cells23
Missing cells (%)5.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory50.0 B

Variable types

Text4
Categorical2

Dataset

Description식생활교육기관의 명칭, 주소, 연락처 등의 정보
Author농림축산식품부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20150108000000000415

Alerts

?식생활교육기관 지정 현황(2021.12월 기준) has 1 (1.5%) missing valuesMissing
Unnamed: 3 has 1 (1.5%) missing valuesMissing
Unnamed: 4 has 20 (29.9%) missing valuesMissing
Unnamed: 5 has 1 (1.5%) missing valuesMissing

Reproduction

Analysis started2023-12-11 03:35:17.789522
Analysis finished2023-12-11 03:35:18.623155
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

?식생활교육기관 지정 현황(2021.12월 기준)
Text

MISSING 

Distinct66
Distinct (%)100.0%
Missing1
Missing (%)1.5%
Memory size668.0 B
2023-12-11T12:35:18.853963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length1.8939394
Min length1

Characters and Unicode

Total characters125
Distinct characters14
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

Unique66 ?
Unique (%)100.0%

Sample

1st row지정번호
2nd row1
3rd row2
4th row3
5th row4
ValueCountFrequency (%)
16 1
 
1.5%
33 1
 
1.5%
35 1
 
1.5%
36 1
 
1.5%
37 1
 
1.5%
38 1
 
1.5%
39 1
 
1.5%
40 1
 
1.5%
41 1
 
1.5%
42 1
 
1.5%
Other values (56) 56
84.8%
2023-12-11T12:35:19.357020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
13.6%
2 17
13.6%
3 17
13.6%
4 17
13.6%
5 17
13.6%
6 12
9.6%
7 6
 
4.8%
8 6
 
4.8%
9 6
 
4.8%
0 6
 
4.8%
Other values (4) 4
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 121
96.8%
Other Letter 4
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
14.0%
2 17
14.0%
3 17
14.0%
4 17
14.0%
5 17
14.0%
6 12
9.9%
7 6
 
5.0%
8 6
 
5.0%
9 6
 
5.0%
0 6
 
5.0%
Other Letter
ValueCountFrequency (%)
지 1
25.0%
정 1
25.0%
번 1
25.0%
호 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 121
96.8%
Hangul 4
 
3.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
14.0%
2 17
14.0%
3 17
14.0%
4 17
14.0%
5 17
14.0%
6 12
9.9%
7 6
 
5.0%
8 6
 
5.0%
9 6
 
5.0%
0 6
 
5.0%
Hangul
ValueCountFrequency (%)
지 1
25.0%
정 1
25.0%
번 1
25.0%
호 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 121
96.8%
Hangul 4
 
3.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
14.0%
2 17
14.0%
3 17
14.0%
4 17
14.0%
5 17
14.0%
6 12
9.9%
7 6
 
5.0%
8 6
 
5.0%
9 6
 
5.0%
0 6
 
5.0%
Hangul
ValueCountFrequency (%)
지 1
25.0%
정 1
25.0%
번 1
25.0%
호 1
25.0%

Unnamed: 1
Categorical

Distinct18
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Memory size668.0 B
서울
14 
전북
8 
경기
7 
경북
5 
부산
4 
Other values (13)
29 

Length

Max length4
Median length2
Mean length2.0298507
Min length2

Unique

Unique4 ?
Unique (%)6.0%

Sample

1st row<NA>
2nd row지역
3rd row서울
4th row부산
5th row광주

Common Values

ValueCountFrequency (%)
서울 14
20.9%
전북 8
11.9%
경기 7
10.4%
경북 5
 
7.5%
부산 4
 
6.0%
충남 4
 
6.0%
충북 3
 
4.5%
대전 3
 
4.5%
강원 3
 
4.5%
전남 3
 
4.5%
Other values (8) 13
19.4%

Length

2023-12-11T12:35:19.534904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울 14
20.9%
전북 8
11.9%
경기 7
10.4%
경북 5
 
7.5%
부산 4
 
6.0%
충남 4
 
6.0%
강원 3
 
4.5%
경남 3
 
4.5%
전남 3
 
4.5%
대전 3
 
4.5%
Other values (8) 13
19.4%

Unnamed: 2
Categorical

Distinct22
Distinct (%)32.8%
Missing0
Missing (%)0.0%
Memory size668.0 B
2013-11-19
23 
2010-08-10
11 
2012-11-07
3 
2010-11-29
3 
2011-04-08
3 
Other values (17)
24 

Length

Max length10
Median length10
Mean length9.8059701
Min length3

Unique

Unique11 ?
Unique (%)16.4%

Sample

1st row<NA>
2nd row지정일
3rd row2010-08-10
4th row2010-08-10
5th row2010-08-10

Common Values

ValueCountFrequency (%)
2013-11-19 23
34.3%
2010-08-10 11
16.4%
2012-11-07 3
 
4.5%
2010-11-29 3
 
4.5%
2011-04-08 3
 
4.5%
2014-12-31 3
 
4.5%
2020-07-10 2
 
3.0%
2015-07-28 2
 
3.0%
2021-06-04 2
 
3.0%
2011-01-31 2
 
3.0%
Other values (12) 13
19.4%

Length

2023-12-11T12:35:19.696175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2013-11-19 23
34.3%
2010-08-10 11
16.4%
2012-11-07 3
 
4.5%
2010-11-29 3
 
4.5%
2011-04-08 3
 
4.5%
2014-12-31 3
 
4.5%
2020-07-10 2
 
3.0%
2015-07-28 2
 
3.0%
2021-06-04 2
 
3.0%
2011-01-31 2
 
3.0%
Other values (12) 13
19.4%

Unnamed: 3
Text

MISSING 

Distinct66
Distinct (%)100.0%
Missing1
Missing (%)1.5%
Memory size668.0 B
2023-12-11T12:35:20.010381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19.5
Mean length11.272727
Min length3

Characters and Unicode

Total characters744
Distinct characters136
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)100.0%

Sample

1st row기관명
2nd row숙명여자대학교 한국음식연구원
3rd row부산교육대학교
4th row광주교육대학교
5th row서울교육대학교 교육연수원
ValueCountFrequency (%)
소비자생활협동조합 3
 
2.9%
아이쿱 2
 
1.9%
대한영양사협회 2
 
1.9%
교육연수원 2
 
1.9%
산학협력단 2
 
1.9%
농업기술센터 2
 
1.9%
사범대학 2
 
1.9%
식생활교육기관 2
 
1.9%
식생활교육센터 2
 
1.9%
한국전통식품합천연수원 1
 
1.0%
Other values (83) 83
80.6%
2023-12-11T12:35:20.485749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 59
 
7.9%
학 42
 
5.6%
38
 
5.1%
대 38
 
5.1%
육 28
 
3.8%
생 27
 
3.6%
식 24
 
3.2%
활 24
 
3.2%
원 17
 
2.3%
협 15
 
2.0%
Other values (126) 432
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 693
93.1%
Space Separator 38
 
5.1%
Uppercase Letter 8
 
1.1%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 59
 
8.5%
학 42
 
6.1%
대 38
 
5.5%
육 28
 
4.0%
생 27
 
3.9%
식 24
 
3.5%
활 24
 
3.5%
원 17
 
2.5%
협 15
 
2.2%
연 15
 
2.2%
Other values (116) 404
58.3%
Uppercase Letter
ValueCountFrequency (%)
O 2
25.0%
C 2
25.0%
A 1
12.5%
Y 1
12.5%
W 1
12.5%
P 1
12.5%
Space Separator
ValueCountFrequency (%)
38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
i 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 693
93.1%
Common 42
 
5.6%
Latin 9
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 59
 
8.5%
학 42
 
6.1%
대 38
 
5.5%
육 28
 
4.0%
생 27
 
3.9%
식 24
 
3.5%
활 24
 
3.5%
원 17
 
2.5%
협 15
 
2.2%
연 15
 
2.2%
Other values (116) 404
58.3%
Latin
ValueCountFrequency (%)
O 2
22.2%
C 2
22.2%
A 1
11.1%
Y 1
11.1%
W 1
11.1%
i 1
11.1%
P 1
11.1%
Common
ValueCountFrequency (%)
38
90.5%
) 2
 
4.8%
( 2
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 693
93.1%
ASCII 51
 
6.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 59
 
8.5%
학 42
 
6.1%
대 38
 
5.5%
육 28
 
4.0%
생 27
 
3.9%
식 24
 
3.5%
활 24
 
3.5%
원 17
 
2.5%
협 15
 
2.2%
연 15
 
2.2%
Other values (116) 404
58.3%
ASCII
ValueCountFrequency (%)
38
74.5%
) 2
 
3.9%
( 2
 
3.9%
O 2
 
3.9%
C 2
 
3.9%
A 1
 
2.0%
Y 1
 
2.0%
W 1
 
2.0%
i 1
 
2.0%
P 1
 
2.0%

Unnamed: 4
Text

MISSING 

Distinct47
Distinct (%)100.0%
Missing20
Missing (%)29.9%
Memory size668.0 B
2023-12-11T12:35:20.819687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.787234
Min length5

Characters and Unicode

Total characters554
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)100.0%

Sample

1st row유선번호1
2nd row051-500-7285
3rd row062-520-4190
4th row041-850-1373
5th row053-620-1395
ValueCountFrequency (%)
유선번호1 1
 
2.1%
063-430-8632 1
 
2.1%
02-3435-0223 1
 
2.1%
02-3290-5383 1
 
2.1%
051-343-2220 1
 
2.1%
053-564-9090 1
 
2.1%
032-516-2212 1
 
2.1%
031-426-6423 1
 
2.1%
031-870-3510 1
 
2.1%
031-272-9572 1
 
2.1%
Other values (37) 37
78.7%
2023-12-11T12:35:21.295994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 92
16.6%
0 84
15.2%
2 59
10.6%
3 55
9.9%
5 54
9.7%
1 48
8.7%
6 42
7.6%
4 37
6.7%
8 34
 
6.1%
7 27
 
4.9%
Other values (5) 22
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 458
82.7%
Dash Punctuation 92
 
16.6%
Other Letter 4
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 84
18.3%
2 59
12.9%
3 55
12.0%
5 54
11.8%
1 48
10.5%
6 42
9.2%
4 37
8.1%
8 34
7.4%
7 27
 
5.9%
9 18
 
3.9%
Other Letter
ValueCountFrequency (%)
유 1
25.0%
선 1
25.0%
번 1
25.0%
호 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 550
99.3%
Hangul 4
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
- 92
16.7%
0 84
15.3%
2 59
10.7%
3 55
10.0%
5 54
9.8%
1 48
8.7%
6 42
7.6%
4 37
6.7%
8 34
 
6.2%
7 27
 
4.9%
Hangul
ValueCountFrequency (%)
유 1
25.0%
선 1
25.0%
번 1
25.0%
호 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 550
99.3%
Hangul 4
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 92
16.7%
0 84
15.3%
2 59
10.7%
3 55
10.0%
5 54
9.8%
1 48
8.7%
6 42
7.6%
4 37
6.7%
8 34
 
6.2%
7 27
 
4.9%
Hangul
ValueCountFrequency (%)
유 1
25.0%
선 1
25.0%
번 1
25.0%
호 1
25.0%

Unnamed: 5
Text

MISSING 

Distinct66
Distinct (%)100.0%
Missing1
Missing (%)1.5%
Memory size668.0 B
2023-12-11T12:35:21.646787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length34
Mean length27.590909
Min length2

Characters and Unicode

Total characters1821
Distinct characters215
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)100.0%

Sample

1st row주소
2nd row서울특별시 용산구 청파로 47길 100
3rd row부산광역시 연제구 교대로 24(거제동)
4th row광주광역시 북구 필문대로 55(풍향동)
5th row서울특별시 서초구 서초중앙로 96 서울교육대학교 생활과학교육과
ValueCountFrequency (%)
서울특별시 13
 
3.4%
경기도 7
 
1.8%
전라북도 7
 
1.8%
부산광역시 4
 
1.0%
경상북도 4
 
1.0%
4층 4
 
1.0%
충청남도 4
 
1.0%
북구 4
 
1.0%
대학로 4
 
1.0%
수원시 3
 
0.8%
Other values (299) 331
86.0%
2023-12-11T12:35:22.204319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
323
 
17.7%
로 61
 
3.3%
시 58
 
3.2%
1 50
 
2.7%
대 43
 
2.4%
구 42
 
2.3%
도 40
 
2.2%
2 37
 
2.0%
학 35
 
1.9%
동 33
 
1.8%
Other values (205) 1099
60.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1180
64.8%
Space Separator 323
 
17.7%
Decimal Number 259
 
14.2%
Close Punctuation 18
 
1.0%
Open Punctuation 18
 
1.0%
Dash Punctuation 10
 
0.5%
Other Punctuation 7
 
0.4%
Uppercase Letter 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 61
 
5.2%
시 58
 
4.9%
대 43
 
3.6%
구 42
 
3.6%
도 40
 
3.4%
학 35
 
3.0%
동 33
 
2.8%
서 29
 
2.5%
교 26
 
2.2%
산 25
 
2.1%
Other values (184) 788
66.8%
Decimal Number
ValueCountFrequency (%)
1 50
19.3%
2 37
14.3%
5 29
11.2%
0 26
10.0%
4 24
9.3%
3 22
8.5%
9 21
8.1%
7 19
 
7.3%
6 17
 
6.6%
8 14
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
C 1
16.7%
Y 1
16.7%
A 1
16.7%
W 1
16.7%
T 1
16.7%
K 1
16.7%
Space Separator
ValueCountFrequency (%)
323
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1180
64.8%
Common 635
34.9%
Latin 6
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 61
 
5.2%
시 58
 
4.9%
대 43
 
3.6%
구 42
 
3.6%
도 40
 
3.4%
학 35
 
3.0%
동 33
 
2.8%
서 29
 
2.5%
교 26
 
2.2%
산 25
 
2.1%
Other values (184) 788
66.8%
Common
ValueCountFrequency (%)
323
50.9%
1 50
 
7.9%
2 37
 
5.8%
5 29
 
4.6%
0 26
 
4.1%
4 24
 
3.8%
3 22
 
3.5%
9 21
 
3.3%
7 19
 
3.0%
) 18
 
2.8%
Other values (5) 66
 
10.4%
Latin
ValueCountFrequency (%)
C 1
16.7%
Y 1
16.7%
A 1
16.7%
W 1
16.7%
T 1
16.7%
K 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1180
64.8%
ASCII 641
35.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
323
50.4%
1 50
 
7.8%
2 37
 
5.8%
5 29
 
4.5%
0 26
 
4.1%
4 24
 
3.7%
3 22
 
3.4%
9 21
 
3.3%
7 19
 
3.0%
) 18
 
2.8%
Other values (11) 72
 
11.2%
Hangul
ValueCountFrequency (%)
로 61
 
5.2%
시 58
 
4.9%
대 43
 
3.6%
구 42
 
3.6%
도 40
 
3.4%
학 35
 
3.0%
동 33
 
2.8%
서 29
 
2.5%
교 26
 
2.2%
산 25
 
2.1%
Other values (184) 788
66.8%

Correlations

2023-12-11T12:35:22.352683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
?식생활교육기관 지정 현황(2021.12월 기준)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
?식생활교육기관 지정 현황(2021.12월 기준)1.0001.0001.0001.0001.0001.000
Unnamed: 11.0001.0000.6321.0001.0001.000
Unnamed: 21.0000.6321.0001.0001.0001.000
Unnamed: 31.0001.0001.0001.0001.0001.000
Unnamed: 41.0001.0001.0001.0001.0001.000
Unnamed: 51.0001.0001.0001.0001.0001.000
2023-12-11T12:35:22.476154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 1
Unnamed: 21.0000.219
Unnamed: 10.2191.000
2023-12-11T12:35:22.597137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2
Unnamed: 11.0000.219
Unnamed: 20.2191.000

Missing values

2023-12-11T12:35:18.234981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:35:18.384886image/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.
2023-12-11T12:35:18.522206image/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

?식생활교육기관 지정 현황(2021.12월 기준)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
0<NA><NA><NA><NA><NA><NA>
1지정번호지역지정일기관명유선번호1주소
21서울2010-08-10숙명여자대학교 한국음식연구원<NA>서울특별시 용산구 청파로 47길 100
32부산2010-08-10부산교육대학교051-500-7285부산광역시 연제구 교대로 24(거제동)
43광주2010-08-10광주교육대학교062-520-4190광주광역시 북구 필문대로 55(풍향동)
54서울2010-08-10서울교육대학교 교육연수원<NA>서울특별시 서초구 서초중앙로 96 서울교육대학교 생활과학교육과
65충남2010-08-10공주교육대학교041-850-1373충청남도 공주시 웅진로 27(봉활동)
76대구2010-08-10대구교육대학교053-620-1395대구광역시 남구 중앙대로 219(대명동)
87인천2010-08-10경인교육대학교 식생활교육연구소032-540-1280인천광역시 계양구 계산로 62 경인교육대학교 생활과학교육과
98충북2010-08-10청주교육대학교 교육연수원043-299-0655충청북도 청주시 흥덕구 청남로 2065(수곡동)
?식생활교육기관 지정 현황(2021.12월 기준)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
5756경기2016-05-17(사)식생활교육문화협회 식생활교육관031-254-7730경기도 수원시 팔달구 우만동 526-12
5857경기2016-11-18수원전통문화관031-247-5612경기도 수원시 팔달구 정조로 893
5958세종2017-05-01세종특별자치시농업기술센터044-301-2532세종특별자치시 연서면 월하천로 289
6059대전2017-12-29밥상살림식생활센터042-488-0561대전광역시 서구 한밭대로 707번길 13, 5층(월평동)
6160대전2018-03-21배재대학교 산학협력단042-520-5551대전광역시 서구 배재로(도마동)155-40 배재대학교 산학협력단
6261충북2018-07-25세명대학교 산학협력단043-649-1126충청북도 제천시 세명로 65 세명대학교 산학협력단
6362서울2020-07-10푸드포체인지<NA>서울시 마포구 성미산로 25-4 우성빌딩 1층
6463경북2020-07-10경북사회적농업전문가협회<NA>경북 포항시 북구 흥해읍 동해대로1459번길 16-55
6564부산2021-06-04부산광역시교육청 영양교육체험관<NA>부산광역시 금정구 금사로 217
6665전북2021-06-04(사)자연음식문화원<NA>전북 전주시 덕진구 태진로 77, 농협 7층