Overview

Dataset statistics

Number of variables6
Number of observations103
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory49.3 B

Variable types

Text5
DateTime1

Dataset

Description지리적표시관리 인증, 심사 등의 업무 관리(등록번호, 등록명칭, 등록일자, 대상지역, 생산계획량, 구성현황 등)
Author국립농산물품질관리원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220204000000001691

Alerts

등록번호 has unique valuesUnique
등록명칭 has unique valuesUnique

Reproduction

Analysis started2024-03-23 07:27:57.045579
Analysis finished2024-03-23 07:27:59.410615
Duration2.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Text

UNIQUE 

Distinct103
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size956.0 B
2024-03-23T07:27:59.791242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.0485437
Min length3

Characters and Unicode

Total characters417
Distinct characters12
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

Unique103 ?
Unique (%)100.0%

Sample

1st row제1호
2nd row제2호
3rd row제3호
4th row제5호
5th row제6호
ValueCountFrequency (%)
제1호 1
 
1.0%
제88호 1
 
1.0%
제85호 1
 
1.0%
제84호 1
 
1.0%
제83호 1
 
1.0%
제82호 1
 
1.0%
제81호 1
 
1.0%
제80호 1
 
1.0%
제79호 1
 
1.0%
제78호 1
 
1.0%
Other values (93) 93
90.3%
2024-03-23T07:28:00.650564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
103
24.7%
103
24.7%
1 37
 
8.9%
8 21
 
5.0%
6 21
 
5.0%
7 21
 
5.0%
9 21
 
5.0%
0 21
 
5.0%
2 20
 
4.8%
3 18
 
4.3%
Other values (2) 31
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 211
50.6%
Other Letter 206
49.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 37
17.5%
8 21
10.0%
6 21
10.0%
7 21
10.0%
9 21
10.0%
0 21
10.0%
2 20
9.5%
3 18
8.5%
5 17
8.1%
4 14
 
6.6%
Other Letter
ValueCountFrequency (%)
103
50.0%
103
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 211
50.6%
Hangul 206
49.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 37
17.5%
8 21
10.0%
6 21
10.0%
7 21
10.0%
9 21
10.0%
0 21
10.0%
2 20
9.5%
3 18
8.5%
5 17
8.1%
4 14
 
6.6%
Hangul
ValueCountFrequency (%)
103
50.0%
103
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 211
50.6%
Hangul 206
49.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
103
50.0%
103
50.0%
ASCII
ValueCountFrequency (%)
1 37
17.5%
8 21
10.0%
6 21
10.0%
7 21
10.0%
9 21
10.0%
0 21
10.0%
2 20
9.5%
3 18
8.5%
5 17
8.1%
4 14
 
6.6%

등록명칭
Text

UNIQUE 

Distinct103
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size956.0 B
2024-03-23T07:28:01.095852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length4.815534
Min length3

Characters and Unicode

Total characters496
Distinct characters162
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)100.0%

Sample

1st row보성녹차
2nd row하동녹차
3rd row고창복분자주
4th row영양고춧가루
5th row의성마늘
ValueCountFrequency (%)
보성녹차 1
 
0.9%
김천포도 1
 
0.9%
거문도쑥 1
 
0.9%
진도검정쌀 1
 
0.9%
한우 1
 
0.9%
고흥 1
 
0.9%
창녕마늘 1
 
0.9%
나주배 1
 
0.9%
영광한우 1
 
0.9%
김포쌀 1
 
0.9%
Other values (97) 97
90.7%
2024-03-23T07:28:02.042323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30
 
6.0%
15
 
3.0%
12
 
2.4%
12
 
2.4%
12
 
2.4%
11
 
2.2%
11
 
2.2%
11
 
2.2%
11
 
2.2%
10
 
2.0%
Other values (152) 361
72.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 488
98.4%
Space Separator 4
 
0.8%
Other Punctuation 2
 
0.4%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
30
 
6.1%
15
 
3.1%
12
 
2.5%
12
 
2.5%
12
 
2.5%
11
 
2.3%
11
 
2.3%
11
 
2.3%
11
 
2.3%
10
 
2.0%
Other values (148) 353
72.3%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 488
98.4%
Common 8
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
30
 
6.1%
15
 
3.1%
12
 
2.5%
12
 
2.5%
12
 
2.5%
11
 
2.3%
11
 
2.3%
11
 
2.3%
11
 
2.3%
10
 
2.0%
Other values (148) 353
72.3%
Common
ValueCountFrequency (%)
4
50.0%
, 2
25.0%
( 1
 
12.5%
) 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 488
98.4%
ASCII 8
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
30
 
6.1%
15
 
3.1%
12
 
2.5%
12
 
2.5%
12
 
2.5%
11
 
2.3%
11
 
2.3%
11
 
2.3%
11
 
2.3%
10
 
2.0%
Other values (148) 353
72.3%
ASCII
ValueCountFrequency (%)
4
50.0%
, 2
25.0%
( 1
 
12.5%
) 1
 
12.5%
Distinct73
Distinct (%)70.9%
Missing0
Missing (%)0.0%
Memory size956.0 B
Minimum2002-01-25 00:00:00
Maximum2022-11-07 00:00:00
2024-03-23T07:28:02.545902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:28:03.042572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct74
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Memory size956.0 B
2024-03-23T07:28:03.619812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length39
Mean length15.776699
Min length2

Characters and Unicode

Total characters1625
Distinct characters105
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)56.3%

Sample

1st row행정구역상 전라남도 보성군 일원
2nd row행정구역상 경상남도 하동군 일원
3rd row행정구역상 전라북도 고창군 일원
4th row행정구역상 경상북도 영양군 일원
5th row행정구역상 경상북도 의성군 일원
ValueCountFrequency (%)
일원 87
22.3%
행정구역상 77
19.7%
전라남도 29
 
7.4%
강원도 14
 
3.6%
경상북도 9
 
2.3%
국내 8
 
2.0%
경상남도 8
 
2.0%
전라북도 7
 
1.8%
충청남도 7
 
1.8%
충청북도 6
 
1.5%
Other values (102) 139
35.5%
2024-03-23T07:28:04.609698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/