Overview

Dataset statistics

Number of variables4
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory35.7 B

Variable types

Text4

Dataset

Description전북특별자치도 미곡종합처리장(미곡종합처리장명, 미곡종합처리장 소재지, 연락처 등)전북특별자치도 미곡종합처리장의 이름, 전북특별자치도 미곡종합처리장의 브랜드 명칭, 전북특별자치도 미곡종합처리장의 연락처
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055752/fileData.do

Alerts

미곡종합처리장명 has unique valuesUnique
미곡종합처리장 소재지 has unique valuesUnique
브랜드명 has unique valuesUnique
연락처 has unique valuesUnique

Reproduction

Analysis started2024-03-15 00:47:27.245551
Analysis finished2024-03-15 00:47:27.952983
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

미곡종합처리장명
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size408.0 B
2024-03-15T09:47:28.639722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length4
Mean length4.6
Min length4

Characters and Unicode

Total characters161
Distinct characters74
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row에브라임코리아
2nd row대야농협
3rd row옥구농협
4th row회현농협
5th row익산농협
ValueCountFrequency (%)
에브라임코리아 1
 
2.9%
백구농협 1
 
2.9%
이택영농 1
 
2.9%
유)옥정영농 1
 
2.9%
완주영농 1
 
2.9%
장수농협 1
 
2.9%
임실통합 1
 
2.9%
동계농협 1
 
2.9%
새만금농산 1
 
2.9%
고창통합 1
 
2.9%
Other values (25) 25
71.4%
2024-03-15T09:47:29.965604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 24
 
14.9%
협 16
 
9.9%
영 7
 
4.3%
합 6
 
3.7%
통 6
 
3.7%
산 4
 
2.5%
) 3
 
1.9%
이 3
 
1.9%
동 3
 
1.9%
( 3
 
1.9%
Other values (64) 86
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 149
92.5%
Uppercase Letter 6
 
3.7%
Close Punctuation 3
 
1.9%
Open Punctuation 3
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 24
 
16.1%
협 16
 
10.7%
영 7
 
4.7%
합 6
 
4.0%
통 6
 
4.0%
산 4
 
2.7%
이 3
 
2.0%
동 3
 
2.0%
라 3
 
2.0%
부 2
 
1.3%
Other values (59) 75
50.3%
Uppercase Letter
ValueCountFrequency (%)
R 2
33.3%
P 2
33.3%
C 2
33.3%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 149
92.5%
Common 6
 
3.7%
Latin 6
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 24
 
16.1%
협 16
 
10.7%
영 7
 
4.7%
합 6
 
4.0%
통 6
 
4.0%
산 4
 
2.7%
이 3
 
2.0%
동 3
 
2.0%
라 3
 
2.0%
부 2
 
1.3%
Other values (59) 75
50.3%
Latin
ValueCountFrequency (%)
R 2
33.3%
P 2
33.3%
C 2
33.3%
Common
ValueCountFrequency (%)
) 3
50.0%
( 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 149
92.5%
ASCII 12
 
7.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 24
 
16.1%
협 16
 
10.7%
영 7
 
4.7%
합 6
 
4.0%
통 6
 
4.0%
산 4
 
2.7%
이 3
 
2.0%
동 3
 
2.0%
라 3
 
2.0%
부 2
 
1.3%
Other values (59) 75
50.3%
ASCII
ValueCountFrequency (%)
) 3
25.0%
( 3
25.0%
R 2
16.7%
P 2
16.7%
C 2
16.7%

미곡종합처리장 소재지
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size408.0 B
2024-03-15T09:47:31.151546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length14.342857
Min length12

Characters and Unicode

Total characters502
Distinct characters98
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

Unique35 ?
Unique (%)100.0%

Sample

1st row전주 완산구 천잠로 185
2nd row군산 대야면 만경로 1807
3rd row군산 옥구읍 옥구로 288
4th row군산 회현면 회미로 455
5th row익산 금강동 강경1길 27
ValueCountFrequency (%)
김제 8
 
5.7%
부안 6
 
4.3%
익산 6
 
4.3%
고창 3
 
2.1%
남원 3
 
2.1%
군산 3
 
2.1%
동계면 2
 
1.4%
망성면 2
 
1.4%
24 2
 
1.4%
함낭로 2
 
1.4%
Other values (103) 103
73.6%
2024-03-15T09:47:32.870354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
105
20.9%
면 28
 
5.6%
로 27
 
5.4%
1 20
 
4.0%
산 17
 
3.4%
8 16
 
3.2%
5 12
 
2.4%
6 12
 
2.4%
4 12
 
2.4%
3 11
 
2.2%
Other values (88) 242
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 286
57.0%
Decimal Number 108
 
21.5%
Space Separator 105
 
20.9%
Dash Punctuation 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 28
 
9.8%
로 27
 
9.4%
산 17
 
5.9%
동 9
 
3.1%
김 8
 
2.8%
길 8
 
2.8%
부 8
 
2.8%
제 8
 
2.8%
안 8
 
2.8%
익 6
 
2.1%
Other values (76) 159
55.6%
Decimal Number
ValueCountFrequency (%)
1 20
18.5%
8 16
14.8%
5 12
11.1%
6 12
11.1%
4 12
11.1%
3 11
10.2%
2 9
8.3%
0 8
 
7.4%
7 4
 
3.7%
9 4
 
3.7%
Space Separator
ValueCountFrequency (%)
105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 286
57.0%
Common 216
43.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 28
 
9.8%
로 27
 
9.4%
산 17
 
5.9%
동 9
 
3.1%
김 8
 
2.8%
길 8
 
2.8%
부 8
 
2.8%
제 8
 
2.8%
안 8
 
2.8%
익 6
 
2.1%
Other values (76) 159
55.6%
Common
ValueCountFrequency (%)
105
48.6%
1 20
 
9.3%
8 16
 
7.4%
5 12
 
5.6%
6 12
 
5.6%
4 12
 
5.6%
3 11
 
5.1%
2 9
 
4.2%
0 8
 
3.7%
7 4
 
1.9%
Other values (2) 7
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 286
57.0%
ASCII 216
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
105
48.6%
1 20
 
9.3%
8 16
 
7.4%
5 12
 
5.6%
6 12
 
5.6%
4 12
 
5.6%
3 11
 
5.1%
2 9
 
4.2%
0 8
 
3.7%
7 4
 
1.9%
Other values (2) 7
 
3.2%
Hangul
ValueCountFrequency (%)
면 28
 
9.8%
로 27
 
9.4%
산 17
 
5.9%
동 9
 
3.1%
김 8
 
2.8%
길 8
 
2.8%
부 8
 
2.8%
제 8
 
2.8%
안 8
 
2.8%
익 6
 
2.1%
Other values (76) 159
55.6%

브랜드명
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size408.0 B
2024-03-15T09:47:33.699295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.0571429
Min length3

Characters and Unicode

Total characters177
Distinct characters98
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

Unique35 ?
Unique (%)100.0%

Sample

1st row맛좋은신동진
2nd row큰들의꿈
3rd row못잊어신동진
4th row옥토진미
5th row옥야수미 신동진
ValueCountFrequency (%)
상상예찬 2
 
5.1%
무량쌀 1
 
2.6%
십장생신동진쌀 1
 
2.6%
방아찧는날 1
 
2.6%
전국쌀자랑 1
 
2.6%
완전한완주신동진 1
 
2.6%
장수만세 1
 
2.6%
신동진쌀 1
 
2.6%
해보드미 1
 
2.6%
맛좋은신동진 1
 
2.6%
Other values (28) 28
71.8%
2024-03-15T09:47:35.176057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
쌀 10
 
5.6%
신 8
 
4.5%
동 8
 
4.5%
진 8
 
4.5%
미 8
 
4.5%
풍 4
 
2.3%
지 4
 
2.3%
4
 
2.3%
상 4
 
2.3%
은 3
 
1.7%
Other values (88) 116
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 173
97.7%
Space Separator 4
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
쌀 10
 
5.8%
신 8
 
4.6%
동 8
 
4.6%
진 8
 
4.6%
미 8
 
4.6%
풍 4
 
2.3%
지 4
 
2.3%
상 4
 
2.3%
은 3
 
1.7%
해 3
 
1.7%
Other values (87) 113
65.3%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 173
97.7%
Common 4
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
쌀 10
 
5.8%
신 8
 
4.6%
동 8
 
4.6%
진 8
 
4.6%
미 8
 
4.6%
풍 4
 
2.3%
지 4
 
2.3%
상 4
 
2.3%
은 3
 
1.7%
해 3
 
1.7%
Other values (87) 113
65.3%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 173
97.7%
ASCII 4
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
쌀 10
 
5.8%
신 8
 
4.6%
동 8
 
4.6%
진 8
 
4.6%
미 8
 
4.6%
풍 4
 
2.3%
지 4
 
2.3%
상 4
 
2.3%
은 3
 
1.7%
해 3
 
1.7%
Other values (87) 113
65.3%
ASCII
ValueCountFrequency (%)
4
100.0%

연락처
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size408.0 B
2024-03-15T09:47:35.966783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters420
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row063-221-4064
2nd row063-451-6674
3rd row063-471-4471
4th row063-466-8323
5th row063-858-8658
ValueCountFrequency (%)
063-221-4064 1
 
2.9%
063-545-3946 1
 
2.9%
063-544-7715 1
 
2.9%
063-547-9253 1
 
2.9%
063-262-2733 1
 
2.9%
063-351-8949 1
 
2.9%
063-642-8880 1
 
2.9%
063-653-4805 1
 
2.9%
063-543-7100 1
 
2.9%
063-561-0008 1
 
2.9%
Other values (25) 25
71.4%
2024-03-15T09:47:37.178483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 72
17.1%
- 70
16.7%
3 60
14.3%
0 53
12.6%
5 42
10.0%
4 33
7.9%
8 25
 
6.0%
2 19
 
4.5%
1 19
 
4.5%
7 16
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 350
83.3%
Dash Punctuation 70
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 72
20.6%
3 60
17.1%
0 53
15.1%
5 42
12.0%
4 33
9.4%
8 25
 
7.1%
2 19
 
5.4%
1 19
 
5.4%
7 16
 
4.6%
9 11
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 420
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 72
17.1%
- 70
16.7%
3 60
14.3%
0 53
12.6%
5 42
10.0%
4 33
7.9%
8 25
 
6.0%
2 19
 
4.5%
1 19
 
4.5%
7 16
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 420
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 72
17.1%
- 70
16.7%
3 60
14.3%
0 53
12.6%
5 42
10.0%
4 33
7.9%
8 25
 
6.0%
2 19
 
4.5%
1 19
 
4.5%
7 16
 
3.8%

Correlations

2024-03-15T09:47:37.440684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
미곡종합처리장명미곡종합처리장 소재지브랜드명연락처
미곡종합처리장명1.0001.0001.0001.000
미곡종합처리장 소재지1.0001.0001.0001.000
브랜드명1.0001.0001.0001.000
연락처1.0001.0001.0001.000

Missing values

2024-03-15T09:47:27.721795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:47:27.890604image/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

미곡종합처리장명미곡종합처리장 소재지브랜드명연락처
0에브라임코리아전주 완산구 천잠로 185맛좋은신동진063-221-4064
1대야농협군산 대야면 만경로 1807큰들의꿈063-451-6674
2옥구농협군산 옥구읍 옥구로 288못잊어신동진063-471-4471
3회현농협군산 회현면 회미로 455옥토진미063-466-8323
4익산농협익산 금강동 강경1길 27옥야수미 신동진063-858-8658
5익산통합(농협양곡)익산 함열읍 함낭로 428탑마루063-861-0609
6황등농협익산 황등면 황등서로 146서동미063-856-4665
7명천영농익산 낭산면 함낭로 861탑마루골드라이스063-861-5213
8중신영농익산 망성면 여강로 639참조은신동진063-861-3564
9(유)이삭익산 망성면 무형길 412질풍노도063-837-1369
미곡종합처리장명미곡종합처리장 소재지브랜드명연락처
25동계농협순창 동계면 동계면 동계1길31무량쌀063-653-4805
26고창통합고창 흥덕면 죽정길 6황토배기063-561-0008
27한결영농고창 대산면 대산길 45십장생신동진쌀063-562-4176
28오성RPC고창 해리면 동서대로 435서해해풍청결미063-563-6770
29계화농협부안 계화면 새포로 388신바람빛063-581-2325
30부안중앙농협부안 행안면 행안중앙로 153추생미063-581-1207
31부안농협부안 백산면 부평로 191풍작소리063-584-6301
32등룡RPC부안 하서면 석불로 4부안계화도쌀063-583-9606
33동진협동부안 동진면 문포로 88간척지쌀063-584-6426
34라이스프라자부안 주산면 선돌로 663명심계화063-582-4086