Overview

Dataset statistics

Number of variables6
Number of observations55
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory50.4 B

Variable types

Categorical2
DateTime1
Text3

Dataset

Description차·전통주·김치 전문인력 양성 및 교육훈련기관 지정에 대한 현황(구분, 지정번호, 지정일자, 법인_단체명, 소재지, 인력양성분야)
Author국립농산물품질관리원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220711000000002152

Reproduction

Analysis started2023-12-11 03:31:00.895219
Analysis finished2023-12-11 03:31:01.557375
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct6
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size572.0 B
전통주 교육훈련기관
18 
김치 교육훈련기관
16 
차 교육훈련기관
차 전문인력 양성기관
전통주 전문인력 양석기관

Length

Max length13
Median length12
Mean length9.9454545
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row차 전문인력 양성기관
2nd row차 전문인력 양성기관
3rd row차 전문인력 양성기관
4th row차 전문인력 양성기관
5th row차 전문인력 양성기관

Common Values

ValueCountFrequency (%)
전통주 교육훈련기관 18
32.7%
김치 교육훈련기관 16
29.1%
차 교육훈련기관 7
 
12.7%
차 전문인력 양성기관 6
 
10.9%
전통주 전문인력 양석기관 5
 
9.1%
김치 전문인력 양성기관 3
 
5.5%

Length

2023-12-11T12:31:01.655700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:31:01.783962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교육훈련기관 41
33.1%
전통주 23
18.5%
김치 19
15.3%
전문인력 14
 
11.3%
13
 
10.5%
양성기관 9
 
7.3%
양석기관 5
 
4.0%

지정번호
Categorical

Distinct20
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Memory size572.0 B
제2호
제4호
제5호
제3호
제6호
Other values (15)
29 

Length

Max length4
Median length3
Mean length3.3272727
Min length3

Unique

Unique5 ?
Unique (%)9.1%

Sample

1st row제2호
2nd row제3호
3rd row제4호
4th row제5호
5th row제6호

Common Values

ValueCountFrequency (%)
제2호 6
 
10.9%
제4호 6
 
10.9%
제5호 5
 
9.1%
제3호 5
 
9.1%
제6호 4
 
7.3%
제7호 4
 
7.3%
제1호 4
 
7.3%
제16호 2
 
3.6%
제8호 2
 
3.6%
제14호 2
 
3.6%
Other values (10) 15
27.3%

Length

2023-12-11T12:31:02.172093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제2호 6
 
10.9%
제4호 6
 
10.9%
제5호 5
 
9.1%
제3호 5
 
9.1%
제6호 4
 
7.3%
제7호 4
 
7.3%
제1호 4
 
7.3%
제17호 2
 
3.6%
제15호 2
 
3.6%
제19호 2
 
3.6%
Other values (10) 15
27.3%
Distinct32
Distinct (%)58.2%
Missing0
Missing (%)0.0%
Memory size572.0 B
Minimum2012-04-09 00:00:00
Maximum2022-03-04 00:00:00
2023-12-11T12:31:02.327228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:31:02.464446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
Distinct46
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Memory size572.0 B
2023-12-11T12:31:02.667628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length9.3636364
Min length3

Characters and Unicode

Total characters515
Distinct characters121
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)67.3%

Sample

1st row사)푸른차연구원
2nd row재)명원문화재단
3rd row사)한국티협회
4th row사)한국차인연합회
5th row사)고려천태국제선차연구보존회
ValueCountFrequency (%)
농업회사법인 5
 
7.9%
사)푸른차연구원 2
 
3.2%
재)명원문화재단 2
 
3.2%
사)광주김치아카데미 2
 
3.2%
사)고려천태국제선차연구보존회 2
 
3.2%
사)우리차문화연합회 2
 
3.2%
대경대학교 2
 
3.2%
사)한국전통음식연구소 2
 
3.2%
사)전통우리음식진흥회 2
 
3.2%
한국가양주연구소 2
 
3.2%
Other values (39) 40
63.5%
2023-12-11T12:31:03.107299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 27
 
5.2%
25
 
4.9%
20
 
3.9%
17
 
3.3%
16
 
3.1%
16
 
3.1%
16
 
3.1%
16
 
3.1%
( 15
 
2.9%
12
 
2.3%
Other values (111) 335
65.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 459
89.1%
Close Punctuation 27
 
5.2%
Open Punctuation 15
 
2.9%
Space Separator 8
 
1.6%
Other Symbol 6
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
25
 
5.4%
20
 
4.4%
17
 
3.7%
16
 
3.5%
16
 
3.5%
16
 
3.5%
16
 
3.5%
12
 
2.6%
11
 
2.4%
10
 
2.2%
Other values (107) 300
65.4%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Symbol
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 465
90.3%
Common 50
 
9.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
25
 
5.4%
20
 
4.3%
17
 
3.7%
16
 
3.4%
16
 
3.4%
16
 
3.4%
16
 
3.4%
12
 
2.6%
11
 
2.4%
10
 
2.2%
Other values (108) 306
65.8%
Common
ValueCountFrequency (%)
) 27
54.0%
( 15
30.0%
8
 
16.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 459
89.1%
ASCII 50
 
9.7%
None 6
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 27
54.0%
( 15
30.0%
8
 
16.0%
Hangul
ValueCountFrequency (%)
25
 
5.4%
20
 
4.4%
17
 
3.7%
16
 
3.5%
16
 
3.5%
16
 
3.5%
16
 
3.5%
12
 
2.6%
11
 
2.4%
10
 
2.2%
Other values (107) 300
65.4%
None
ValueCountFrequency (%)
6
100.0%
Distinct30
Distinct (%)54.5%
Missing0
Missing (%)0.0%
Memory size572.0 B
2023-12-11T12:31:03.325707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0181818
Min length5

Characters and Unicode

Total characters331
Distinct characters49
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

Unique20 ?
Unique (%)36.4%

Sample

1st row대구 수성구
2nd row서울 종로구
3rd row서울 강남구
4th row서울 종로구
5th row전남 순천시
ValueCountFrequency (%)
서울 21
19.1%
종로구 10
 
9.1%
경기 9
 
8.2%
전남 4
 
3.6%
강남구 4
 
3.6%
서초구 4
 
3.6%
대구 4
 
3.6%
수성구 4
 
3.6%
경북 3
 
2.7%
남구 3
 
2.7%
Other values (33) 44
40.0%
2023-12-11T12:31:03.730836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
56
16.9%
37
 
11.2%
26
 
7.9%
23
 
6.9%
18
 
5.4%
15
 
4.5%
14
 
4.2%
12
 
3.6%
10
 
3.0%
10
 
3.0%
Other values (39) 110
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 275
83.1%
Space Separator 56
 
16.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
37
 
13.5%
26
 
9.5%
23
 
8.4%
18
 
6.5%
15
 
5.5%
14
 
5.1%
12
 
4.4%
10
 
3.6%
10
 
3.6%
9
 
3.3%
Other values (38) 101
36.7%
Space Separator
ValueCountFrequency (%)
56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 275
83.1%
Common 56
 
16.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
37
 
13.5%
26
 
9.5%
23
 
8.4%
18
 
6.5%
15
 
5.5%
14
 
5.1%
12
 
4.4%
10
 
3.6%
10
 
3.6%
9
 
3.3%
Other values (38) 101
36.7%
Common
ValueCountFrequency (%)
56
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 275
83.1%
ASCII 56
 
16.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
56
100.0%
Hangul
ValueCountFrequency (%)
37
 
13.5%
26
 
9.5%
23
 
8.4%
18
 
6.5%
15
 
5.5%
14
 
5.1%
12
 
4.4%
10
 
3.6%
10
 
3.6%
9
 
3.3%
Other values (38) 101
36.7%
Distinct42
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Memory size572.0 B
2023-12-11T12:31:04.023359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length9.5818182
Min length4

Characters and Unicode

Total characters527
Distinct characters102
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

Unique40 ?
Unique (%)72.7%

Sample

1st row차 제조 교육 등
2nd row다도예절지도사
3rd row티 소믈리에
4th row다도교수
5th row전통차제다, 다도예절
ValueCountFrequency (%)
25
15.1%
김치 15
 
9.0%
담그기 15
 
9.0%
체험 14
 
8.4%
14
 
8.4%
제조 9
 
5.4%
주류 4
 
2.4%
전통주 3
 
1.8%
우리술 3
 
1.8%
발효 3
 
1.8%
Other values (53) 61
36.7%
2023-12-11T12:31:04.425565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
112
21.3%
26
 
4.9%
19
 
3.6%
19
 
3.6%
18
 
3.4%
17
 
3.2%
17
 
3.2%
16
 
3.0%
15
 
2.8%
15
 
2.8%
Other values (92) 253
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 411
78.0%
Space Separator 112
 
21.3%
Other Punctuation 4
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
26
 
6.3%
19
 
4.6%
19
 
4.6%
18
 
4.4%
17
 
4.1%
17
 
4.1%
16
 
3.9%
15
 
3.6%
15
 
3.6%
15
 
3.6%
Other values (90) 234
56.9%
Space Separator
ValueCountFrequency (%)
112
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 411
78.0%
Common 116
 
22.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
26
 
6.3%
19
 
4.6%
19
 
4.6%
18
 
4.4%
17
 
4.1%
17
 
4.1%
16
 
3.9%
15
 
3.6%
15
 
3.6%
15
 
3.6%
Other values (90) 234
56.9%
Common
ValueCountFrequency (%)
112
96.6%
, 4
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 411
78.0%
ASCII 116
 
22.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
112
96.6%
, 4
 
3.4%
Hangul
ValueCountFrequency (%)
26
 
6.3%
19
 
4.6%
19
 
4.6%
18
 
4.4%
17
 
4.1%
17
 
4.1%
16
 
3.9%
15
 
3.6%
15
 
3.6%
15
 
3.6%
Other values (90) 234
56.9%

Correlations

2023-12-11T12:31:04.556871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분지정번호지정일자법인_단체명소재지인력양성분야
구분1.0000.0000.7330.0000.0000.998
지정번호0.0001.0000.8840.9610.8590.000
지정일자0.7330.8841.0000.9870.8610.667
법인_단체명0.0000.9610.9871.0001.0000.886
소재지0.0000.8590.8611.0001.0000.000
인력양성분야0.9980.0000.6670.8860.0001.000
2023-12-11T12:31:04.690309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분지정번호
구분1.0000.000
지정번호0.0001.000
2023-12-11T12:31:04.793114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분지정번호
구분1.0000.000
지정번호0.0001.000

Missing values

2023-12-11T12:31:01.376227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:31:01.502562image/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

구분지정번호지정일자법인_단체명소재지인력양성분야
0차 전문인력 양성기관제2호2016-12-27사)푸른차연구원대구 수성구차 제조 교육 등
1차 전문인력 양성기관제3호2017-04-12재)명원문화재단서울 종로구다도예절지도사
2차 전문인력 양성기관제4호2017-05-12사)한국티협회서울 강남구티 소믈리에
3차 전문인력 양성기관제5호2017-06-15사)한국차인연합회서울 종로구다도교수
4차 전문인력 양성기관제6호2017-09-07사)고려천태국제선차연구보존회전남 순천시전통차제다, 다도예절
5차 전문인력 양성기관제7호2017-12-07사)우리차문화연합회대구 수성구차문화지도사 등
6차 교육훈련기관제1호2016-12-27사)푸른차연구원대구 수성구다도 예절사 등
7차 교육훈련기관제2호2016-12-27주)티립티 아카데미서울 종로구티 마스터 등
8차 교육훈련기관제3호2017-04-12재)명원문화재단서울 종로구다도예절지도사
9차 교육훈련기관제4호2017-05-12사)한국티협회서울 강남구티 스폐설리스트
구분지정번호지정일자법인_단체명소재지인력양성분야
45김치 교육훈련기관제8호2012-05-29봉우리영농조합경기 남양주시김치 담그기 체험
46김치 교육훈련기관제12호2013-07-30담다헌경기 의정부시김치 담그기 체헌
47김치 교육훈련기관제14호2013-12-18(재)국제한식문화재단전북 전주시김치 담그기 체험
48김치 교육훈련기관제15호2013-12-18문화요리학원부산 부산진구김치 담그기 체험
49김치 교육훈련기관제16호2014-03-03(사)한국전통음식연구소서울 종로구김치 담그기 체험
50김치 교육훈련기관제17호2014-03-03㈜해도지에프앤비울산 울주군김치 담그기 체험
51김치 교육훈련기관제18호2014-05-29대경대학교경북 경산시김치 담그기 체험
52김치 교육훈련기관제19호2014-05-29미추홀 전통음식문화연구원인천 중구김치 담그기 체험
53김치 교육훈련기관제20호2015-01-27(사)광주김치아카데미광주 남구김치 담그기 체험
54김치 교육훈련기관제23호2018-03-14보현자연수련원경북 영천시김치 담그기 체험