Overview

Dataset statistics

Number of variables5
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory45.6 B

Variable types

Numeric1
Text2
Categorical2

Dataset

Description경상남도 소재한 축산가공업 현황정보 제공합니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3083318

Alerts

순번 is highly overall correlated with 영업의종류High correlation
영업의종류 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
품목분류 is highly overall correlated with 영업의종류High correlation
순번 has unique valuesUnique
허가번호 has unique valuesUnique
사업장명칭 has unique valuesUnique

Reproduction

Analysis started2023-12-10 22:44:37.743126
Analysis finished2023-12-10 22:44:38.153070
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15
Minimum1
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-11T07:44:38.201448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.4
Q18
median15
Q322
95-th percentile27.6
Maximum29
Range28
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.5146932
Coefficient of variation (CV)0.56764621
Kurtosis-1.2
Mean15
Median Absolute Deviation (MAD)7
Skewness0
Sum435
Variance72.5
MonotonicityStrictly increasing
2023-12-11T07:44:38.305513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 1
 
3.4%
2 1
 
3.4%
29 1
 
3.4%
28 1
 
3.4%
27 1
 
3.4%
26 1
 
3.4%
25 1
 
3.4%
24 1
 
3.4%
23 1
 
3.4%
22 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
1 1
3.4%
2 1
3.4%
3 1
3.4%
4 1
3.4%
5 1
3.4%
6 1
3.4%
7 1
3.4%
8 1
3.4%
9 1
3.4%
10 1
3.4%
ValueCountFrequency (%)
29 1
3.4%
28 1
3.4%
27 1
3.4%
26 1
3.4%
25 1
3.4%
24 1
3.4%
23 1
3.4%
22 1
3.4%
21 1
3.4%
20 1
3.4%

허가번호
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-11T07:44:38.469116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters348
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

Unique29 ?
Unique (%)100.0%

Sample

1st row1978-0575001
2nd row1979-0575001
3rd row1979-0575002
4th row1985-0575001
5th row1993-0575002
ValueCountFrequency (%)
1978-0575001 1
 
3.4%
2011-0575003 1
 
3.4%
2016-0575001 1
 
3.4%
2015-0575004 1
 
3.4%
2015-0575002 1
 
3.4%
2015-0575001 1
 
3.4%
2014-0575003 1
 
3.4%
2014-0575002 1
 
3.4%
2014-0575001 1
 
3.4%
2013-0575003 1
 
3.4%
Other values (19) 19
65.5%
2023-12-11T07:44:38.741313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 112
32.2%
5 63
18.1%
1 42
 
12.1%
7 34
 
9.8%
2 30
 
8.6%
- 29
 
8.3%
9 16
 
4.6%
3 8
 
2.3%
4 8
 
2.3%
8 3
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319
91.7%
Dash Punctuation 29
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 112
35.1%
5 63
19.7%
1 42
 
13.2%
7 34
 
10.7%
2 30
 
9.4%
9 16
 
5.0%
3 8
 
2.5%
4 8
 
2.5%
8 3
 
0.9%
6 3
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 348
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 112
32.2%
5 63
18.1%
1 42
 
12.1%
7 34
 
9.8%
2 30
 
8.6%
- 29
 
8.3%
9 16
 
4.6%
3 8
 
2.3%
4 8
 
2.3%
8 3
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 112
32.2%
5 63
18.1%
1 42
 
12.1%
7 34
 
9.8%
2 30
 
8.6%
- 29
 
8.3%
9 16
 
4.6%
3 8
 
2.3%
4 8
 
2.3%
8 3
 
0.9%

사업장명칭
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-11T07:44:38.908947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length7.2758621
Min length3

Characters and Unicode

Total characters211
Distinct characters90
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row롯데제과
2nd row(주)한국야쿠르트양산공장
3rd row(주)희창유업
4th row(주)엠에스씨
5th row오경식품
ValueCountFrequency (%)
영농조합법인 2
 
5.7%
주식회사 2
 
5.7%
주 2
 
5.7%
금와목장 1
 
2.9%
농업회사법인(주)새한푸드 1
 
2.9%
한내에프에스 1
 
2.9%
오경농장(주 1
 
2.9%
계림에프앤씨 1
 
2.9%
g푸드 1
 
2.9%
두빈목장 1
 
2.9%
Other values (22) 22
62.9%
2023-12-11T07:44:39.167096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 12
 
5.7%
) 10
 
4.7%
( 9
 
4.3%
인 7
 
3.3%
유 7
 
3.3%
장 7
 
3.3%
농 7
 
3.3%
합 6
 
2.8%
법 6
 
2.8%
조 6
 
2.8%
Other values (80) 134
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 185
87.7%
Close Punctuation 10
 
4.7%
Open Punctuation 9
 
4.3%
Space Separator 6
 
2.8%
Uppercase Letter 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 12
 
6.5%
인 7
 
3.8%
유 7
 
3.8%
장 7
 
3.8%
농 7
 
3.8%
합 6
 
3.2%
법 6
 
3.2%
조 6
 
3.2%
업 6
 
3.2%
영 5
 
2.7%
Other values (76) 116
62.7%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Uppercase Letter
ValueCountFrequency (%)
G 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 185
87.7%
Common 25
 
11.8%
Latin 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 12
 
6.5%
인 7
 
3.8%
유 7
 
3.8%
장 7
 
3.8%
농 7
 
3.8%
합 6
 
3.2%
법 6
 
3.2%
조 6
 
3.2%
업 6
 
3.2%
영 5
 
2.7%
Other values (76) 116
62.7%
Common
ValueCountFrequency (%)
) 10
40.0%
( 9
36.0%
6
24.0%
Latin
ValueCountFrequency (%)
G 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 185
87.7%
ASCII 26
 
12.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 12
 
6.5%
인 7
 
3.8%
유 7
 
3.8%
장 7
 
3.8%
농 7
 
3.8%
합 6
 
3.2%
법 6
 
3.2%
조 6
 
3.2%
업 6
 
3.2%
영 5
 
2.7%
Other values (76) 116
62.7%
ASCII
ValueCountFrequency (%)
) 10
38.5%
( 9
34.6%
6
23.1%
G 1
 
3.8%

영업의종류
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
유가공업
20 
알가공업
9 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row유가공업
2nd row유가공업
3rd row유가공업
4th row유가공업
5th row알가공업

Common Values

ValueCountFrequency (%)
유가공업 20
69.0%
알가공업 9
31.0%

Length

2023-12-11T07:44:39.272222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:44:39.352521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유가공업 20
69.0%
알가공업 9
31.0%

품목분류
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)48.3%
Missing0
Missing (%)0.0%
Memory size364.0 B
알가공품
9 
발효유류,가공치즈
8 
우유류,아이스크림류
1 
발효유류
1 
분유류,아이스크림분말류
1 
Other values (9)
9 

Length

Max length20
Median length19
Mean length8.0689655
Min length3

Unique

Unique12 ?
Unique (%)41.4%

Sample

1st row우유류,아이스크림류
2nd row발효유류
3rd row분유류,아이스크림분말류
4th row유단백가수분해식품
5th row알가공품

Common Values

ValueCountFrequency (%)
알가공품 9
31.0%
발효유류,가공치즈 8
27.6%
우유류,아이스크림류 1
 
3.4%
발효유류 1
 
3.4%
분유류,아이스크림분말류 1
 
3.4%
유단백가수분해식품 1
 
3.4%
가공치즈,분유류 1
 
3.4%
우유류,저지방우유류,가공유류 1
 
3.4%
우유류,가공류,발효유류,아이스크림류 1
 
3.4%
분유류 1
 
3.4%
Other values (4) 4
13.8%

Length

2023-12-11T07:44:39.442817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
알가공품 9
31.0%
발효유류,가공치즈 8
27.6%
우유류,아이스크림류 1
 
3.4%
발효유류 1
 
3.4%
분유류,아이스크림분말류 1
 
3.4%
유단백가수분해식품 1
 
3.4%
가공치즈,분유류 1
 
3.4%
우유류,저지방우유류,가공유류 1
 
3.4%
우유류,가공류,발효유류,아이스크림류 1
 
3.4%
분유류 1
 
3.4%
Other values (4) 4
13.8%

Interactions

2023-12-11T07:44:37.943948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:44:39.511496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번허가번호사업장명칭영업의종류품목분류
순번1.0001.0001.0000.8940.714
허가번호1.0001.0001.0001.0001.000
사업장명칭1.0001.0001.0001.0001.000
영업의종류0.8941.0001.0001.0001.000
품목분류0.7141.0001.0001.0001.000
2023-12-11T07:44:39.587598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업의종류품목분류
영업의종류1.0000.745
품목분류0.7451.000
2023-12-11T07:44:39.649129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번영업의종류품목분류
순번1.0000.6080.313
영업의종류0.6081.0000.745
품목분류0.3130.7451.000

Missing values

2023-12-11T07:44:38.041792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:44:38.121551image/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

순번허가번호사업장명칭영업의종류품목분류
011978-0575001롯데제과유가공업우유류,아이스크림류
121979-0575001(주)한국야쿠르트양산공장유가공업발효유류
231979-0575002(주)희창유업유가공업분유류,아이스크림분말류
341985-0575001(주)엠에스씨유가공업유단백가수분해식품
451993-0575002오경식품알가공업알가공품
561994-0575001서강유업(주)유가공업가공치즈,분유류
671994-0575002주식회사 제이웰알가공업알가공품
781997-0575001부산우유협동조합유가공업우유류,저지방우유류,가공유류
891998-0575001(주)빙그레김해공장유가공업우유류,가공류,발효유류,아이스크림류
9102001-0575004(주)동진유업유가공업분유류
순번허가번호사업장명칭영업의종류품목분류
19202013-0575002주) 선인유가공업자연치즈,가공치즈
20212013-0575003아침마당영농조합법인유가공업발효유류,가공치즈
21222014-0575001요요유업유가공업발효유류,가공치즈
22232014-0575002두빈목장유가공업발효유류,가공치즈
23242014-0575003G푸드알가공업알가공품
24252015-0575001계림에프앤씨알가공업알가공품
25262015-0575002오경농장(주)알가공업알가공품
26272015-0575004주식회사 한내에프에스알가공업알가공품
27282016-0575001농업회사법인(주)새한푸드알가공업알가공품
28292016-0575002너란나란알가공업알가공품