Overview

Dataset statistics

Number of variables3
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory990.0 B
Average record size in memory30.0 B

Variable types

Text1
Numeric2

Dataset

Description2014년도 농림축산식품부 (한국식품 연구원 국가별 유기가공식품 업체 인증) 현황 정보 제공 제공 항목 : 국가, 업체수, 제품수
Author농림축산식품부
URLhttps://www.data.go.kr/data/15002218/fileData.do

Alerts

업체수 is highly overall correlated with 제품수High correlation
제품수 is highly overall correlated with 업체수High correlation
국가 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:07:08.176154
Analysis finished2023-12-12 00:07:08.735451
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

국가
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-12T09:07:08.896667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.9090909
Min length2

Characters and Unicode

Total characters96
Distinct characters66
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row한국
2nd row미국
3rd row캐나다
4th row멕시코
5th row쿠바
ValueCountFrequency (%)
한국 1
 
3.0%
파키스탄 1
 
3.0%
남아공 1
 
3.0%
뉴질랜드 1
 
3.0%
호주 1
 
3.0%
영국 1
 
3.0%
스위스 1
 
3.0%
벨기에 1
 
3.0%
러시아 1
 
3.0%
오스트리아 1
 
3.0%
Other values (23) 23
69.7%
2023-12-12T09:07:09.350690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
 
6.2%
6
 
6.2%
5
 
5.2%
3
 
3.1%
2
 
2.1%
2
 
2.1%
2
 
2.1%
2
 
2.1%
2
 
2.1%
2
 
2.1%
Other values (56) 64
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 96
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6
 
6.2%
6
 
6.2%
5
 
5.2%
3
 
3.1%
2
 
2.1%
2
 
2.1%
2
 
2.1%
2
 
2.1%
2
 
2.1%
2
 
2.1%
Other values (56) 64
66.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 96
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6
 
6.2%
6
 
6.2%
5
 
5.2%
3
 
3.1%
2
 
2.1%
2
 
2.1%
2
 
2.1%
2
 
2.1%
2
 
2.1%
2
 
2.1%
Other values (56) 64
66.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 96
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6
 
6.2%
6
 
6.2%
5
 
5.2%
3
 
3.1%
2
 
2.1%
2
 
2.1%
2
 
2.1%
2
 
2.1%
2
 
2.1%
2
 
2.1%
Other values (56) 64
66.7%

업체수
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.212121
Minimum1
Maximum529
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T09:07:09.497534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median4
Q37
95-th percentile15
Maximum529
Range528
Interquartile range (IQR)6

Descriptive statistics

Standard deviation91.421331
Coefficient of variation (CV)4.5230944
Kurtosis32.865559
Mean20.212121
Median Absolute Deviation (MAD)3
Skewness5.7276656
Sum667
Variance8357.8598
MonotonicityNot monotonic
2023-12-12T09:07:09.618946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 11
33.3%
2 4
 
12.1%
4 4
 
12.1%
5 3
 
9.1%
9 2
 
6.1%
8 2
 
6.1%
7 2
 
6.1%
529 1
 
3.0%
13 1
 
3.0%
6 1
 
3.0%
Other values (2) 2
 
6.1%
ValueCountFrequency (%)
1 11
33.3%
2 4
 
12.1%
3 1
 
3.0%
4 4
 
12.1%
5 3
 
9.1%
6 1
 
3.0%
7 2
 
6.1%
8 2
 
6.1%
9 2
 
6.1%
13 1
 
3.0%
ValueCountFrequency (%)
529 1
 
3.0%
18 1
 
3.0%
13 1
 
3.0%
9 2
6.1%
8 2
6.1%
7 2
6.1%
6 1
 
3.0%
5 3
9.1%
4 4
12.1%
3 1
 
3.0%

제품수
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean105.24242
Minimum1
Maximum2726
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T09:07:09.740268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median9
Q333
95-th percentile128.8
Maximum2726
Range2725
Interquartile range (IQR)31

Descriptive statistics

Standard deviation471.7759
Coefficient of variation (CV)4.482754
Kurtosis32.601017
Mean105.24242
Median Absolute Deviation (MAD)8
Skewness5.6951575
Sum3473
Variance222572.5
MonotonicityNot monotonic
2023-12-12T09:07:09.875719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 5
 
15.2%
2 4
 
12.1%
8 2
 
6.1%
2726 1
 
3.0%
169 1
 
3.0%
18 1
 
3.0%
102 1
 
3.0%
4 1
 
3.0%
10 1
 
3.0%
20 1
 
3.0%
Other values (15) 15
45.5%
ValueCountFrequency (%)
1 5
15.2%
2 4
12.1%
3 1
 
3.0%
4 1
 
3.0%
5 1
 
3.0%
6 1
 
3.0%
7 1
 
3.0%
8 2
 
6.1%
9 1
 
3.0%
10 1
 
3.0%
ValueCountFrequency (%)
2726 1
3.0%
169 1
3.0%
102 1
3.0%
71 1
3.0%
67 1
3.0%
38 1
3.0%
36 1
3.0%
34 1
3.0%
33 1
3.0%
32 1
3.0%

Interactions

2023-12-12T09:07:08.439842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:07:08.269642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:07:08.518129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:07:08.352989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:07:09.975744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
국가업체수제품수
국가1.0001.0001.000
업체수1.0001.0000.660
제품수1.0000.6601.000
2023-12-12T09:07:10.056760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체수제품수
업체수1.0000.866
제품수0.8661.000

Missing values

2023-12-12T09:07:08.634907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:07:08.707783image/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

국가업체수제품수
0한국5292726
1미국1371
2캐나다57
3멕시코636
4쿠바11
5브라질933
6콜롬비아938
7아르헨티나11
8페루19
9파라과이11
국가업체수제품수
23프랑스520
24오스트리아410
25러시아12
26벨기에14
27스위스12
28영국11
29호주7102
30뉴질랜드318
31남아공48
32수단11