Overview

Dataset statistics

Number of variables5
Number of observations332
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.7 KiB
Average record size in memory42.4 B

Variable types

Numeric2
Text2
Categorical1

Dataset

Description농림수산식품교육문화정보원 농식품FTA활용정보 서비스에서 사용되는 농산물 축산물 임산물에 포함된 품목 정보 데이터
Author농림수산식품교육문화정보원
URLhttps://www.data.go.kr/data/15123584/fileData.do

Alerts

품목구분 is highly overall correlated with 품목코드 and 1 other fieldsHigh correlation
품목코드 is highly overall correlated with 품목구분 and 1 other fieldsHigh correlation
대분류 is highly overall correlated with 품목구분 and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 08:09:42.411439
Analysis finished2023-12-12 08:09:43.365792
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품목구분
Real number (ℝ)

HIGH CORRELATION 

Distinct57
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.777108
Minimum1
Maximum57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-12T17:09:43.435647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q113
median30.5
Q343
95-th percentile56
Maximum57
Range56
Interquartile range (IQR)30

Descriptive statistics

Standard deviation17.876676
Coefficient of variation (CV)0.62121169
Kurtosis-1.3590733
Mean28.777108
Median Absolute Deviation (MAD)15.5
Skewness-0.13510587
Sum9554
Variance319.57555
MonotonicityNot monotonic
2023-12-12T17:09:43.610410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
43 23
 
6.9%
14 21
 
6.3%
42 19
 
5.7%
44 19
 
5.7%
2 17
 
5.1%
57 16
 
4.8%
1 16
 
4.8%
50 13
 
3.9%
40 12
 
3.6%
5 9
 
2.7%
Other values (47) 167
50.3%
ValueCountFrequency (%)
1 16
4.8%
2 17
5.1%
3 4
 
1.2%
4 7
2.1%
5 9
2.7%
6 4
 
1.2%
7 1
 
0.3%
8 4
 
1.2%
9 4
 
1.2%
10 4
 
1.2%
ValueCountFrequency (%)
57 16
4.8%
56 4
 
1.2%
55 4
 
1.2%
54 2
 
0.6%
53 1
 
0.3%
52 2
 
0.6%
51 3
 
0.9%
50 13
3.9%
49 2
 
0.6%
48 3
 
0.9%

품목명
Text

Distinct57
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-12T17:09:43.894088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.3795181
Min length1

Characters and Unicode

Total characters790
Distinct characters86
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

Unique4 ?
Unique (%)1.2%

Sample

1st row생강
2nd row생강
3rd row생강
4th row생강
5th row생강
ValueCountFrequency (%)
돼지고기 23
 
6.9%
인삼 21
 
6.3%
쇠고기 19
 
5.7%
닭고기 19
 
5.7%
보리 17
 
5.1%
유장 16
 
4.8%
쌀 16
 
4.8%
오리 13
 
3.9%
치즈 12
 
3.6%
감자 9
 
2.7%
Other values (47) 167
50.3%
2023-12-12T17:09:44.342817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
고 73
 
9.2%
기 67
 
8.5%
리 34
 
4.3%
유 30
 
3.8%
지 29
 
3.7%
돼 23
 
2.9%
인 21
 
2.7%
삼 21
 
2.7%
쇠 19
 
2.4%
닭 19
 
2.4%
Other values (76) 454
57.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 790
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 73
 
9.2%
기 67
 
8.5%
리 34
 
4.3%
유 30
 
3.8%
지 29
 
3.7%
돼 23
 
2.9%
인 21
 
2.7%
삼 21
 
2.7%
쇠 19
 
2.4%
닭 19
 
2.4%
Other values (76) 454
57.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 790
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 73
 
9.2%
기 67
 
8.5%
리 34
 
4.3%
유 30
 
3.8%
지 29
 
3.7%
돼 23
 
2.9%
인 21
 
2.7%
삼 21
 
2.7%
쇠 19
 
2.4%
닭 19
 
2.4%
Other values (76) 454
57.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 790
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
고 73
 
9.2%
기 67
 
8.5%
리 34
 
4.3%
유 30
 
3.8%
지 29
 
3.7%
돼 23
 
2.9%
인 21
 
2.7%
삼 21
 
2.7%
쇠 19
 
2.4%
닭 19
 
2.4%
Other values (76) 454
57.5%

품목코드
Real number (ℝ)

HIGH CORRELATION 

Distinct329
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.0527215 × 108
Minimum1.05131 × 108
Maximum2.2072 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-12T17:09:44.511594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.05131 × 108
5-th percentile2.032155 × 108
Q14.0410186 × 108
median8.0405601 × 108
Q31.2112012 × 109
95-th percentile2.00875 × 109
Maximum2.2072 × 109
Range2.102069 × 109
Interquartile range (IQR)8.0709936 × 108

Descriptive statistics

Standard deviation6.0364939 × 108
Coefficient of variation (CV)0.66681537
Kurtosis-0.67538309
Mean9.0527215 × 108
Median Absolute Deviation (MAD)4.0106101 × 108
Skewness0.65401758
Sum3.0055035 × 1011
Variance3.6439258 × 1017
MonotonicityNot monotonic
2023-12-12T17:09:44.672040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
404902000 2
 
0.6%
810709000 2
 
0.6%
404901000 2
 
0.6%
1003902000 1
 
0.3%
1201101000 1
 
0.3%
2207200000 1
 
0.3%
2207109090 1
 
0.3%
2207109010 1
 
0.3%
2207101000 1
 
0.3%
2101301000 1
 
0.3%
Other values (319) 319
96.1%
ValueCountFrequency (%)
105131000 1
0.3%
105139000 1
0.3%
105991010 1
0.3%
105991090 1
0.3%
201100000 1
0.3%
201201000 1
0.3%
201209000 1
0.3%
201300000 1
0.3%
202100000 1
0.3%
202201000 1
0.3%
ValueCountFrequency (%)
2207200000 1
0.3%
2207109090 1
0.3%
2207109010 1
0.3%
2207101000 1
0.3%
2106903029 1
0.3%
2106903021 1
0.3%
2103202000 1
0.3%
2103201000 1
0.3%
2101301000 1
0.3%
2009790000 1
0.3%

설명
Text

Distinct331
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-12T17:09:44.898595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length26
Mean length11.783133
Min length1

Characters and Unicode

Total characters3912
Distinct characters275
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique330 ?
Unique (%)99.4%

Sample

1st row생강(미파쇄분쇄/기타)
2nd row생강(파쇄는쇄/신선는장)
3rd row생강(파쇄는쇄/건조)
4th row생강(파쇄는쇄/기타)
5th row생강(설탕조제)
ValueCountFrequency (%)
토마토스 2
 
0.6%
맥주보리(기타 1
 
0.3%
변성정 1
 
0.3%
기타 1
 
0.3%
주류제조용효주정 1
 
0.3%
조주정 1
 
0.3%
보리의(추출물,센스,축물 1
 
0.3%
맥아(기타/볶음 1
 
0.3%
맥아(훈연한 1
 
0.3%
가공곡물(보리의것 1
 
0.3%
Other values (321) 321
96.7%
2023-12-12T17:09:45.366405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 312
 
8.0%
( 298
 
7.6%
/ 192
 
4.9%
기 187
 
4.8%
타 145
 
3.7%
장 91
 
2.3%
조 67
 
1.7%
분 66
 
1.7%
, 65
 
1.7%
리 62
 
1.6%
Other values (265) 2427
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2915
74.5%
Close Punctuation 312
 
8.0%
Open Punctuation 298
 
7.6%
Other Punctuation 278
 
7.1%
Decimal Number 95
 
2.4%
Lowercase Letter 12
 
0.3%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 187
 
6.4%
타 145
 
5.0%
장 91
 
3.1%
조 67
 
2.3%
분 66
 
2.3%
리 62
 
2.1%
냉 61
 
2.1%
고 60
 
2.1%
제 56
 
1.9%
삼 54
 
1.9%
Other values (242) 2066
70.9%
Lowercase Letter
ValueCountFrequency (%)
g 5
41.7%
k 1
 
8.3%
i 1
 
8.3%
n 1
 
8.3%
h 1
 
8.3%
o 1
 
8.3%
l 1
 
8.3%
e 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
0 51
53.7%
5 18
 
18.9%
1 12
 
12.6%
4 6
 
6.3%
8 4
 
4.2%
3 3
 
3.2%
6 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
/ 192
69.1%
, 65
 
23.4%
. 14
 
5.0%
· 6
 
2.2%
% 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 312
100.0%
Open Punctuation
ValueCountFrequency (%)
( 298
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2915
74.5%
Common 985
 
25.2%
Latin 12
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 187
 
6.4%
타 145
 
5.0%
장 91
 
3.1%
조 67
 
2.3%
분 66
 
2.3%
리 62
 
2.1%
냉 61
 
2.1%
고 60
 
2.1%
제 56
 
1.9%
삼 54
 
1.9%
Other values (242) 2066
70.9%
Common
ValueCountFrequency (%)
) 312
31.7%
( 298
30.3%
/ 192
19.5%
, 65
 
6.6%
0 51
 
5.2%
5 18
 
1.8%
. 14
 
1.4%
1 12
 
1.2%
· 6
 
0.6%
4 6
 
0.6%
Other values (5) 11
 
1.1%
Latin
ValueCountFrequency (%)
g 5
41.7%
k 1
 
8.3%
i 1
 
8.3%
n 1
 
8.3%
h 1
 
8.3%
o 1
 
8.3%
l 1
 
8.3%
e 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2915
74.5%
ASCII 991
 
25.3%
None 6
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 312
31.5%
( 298
30.1%
/ 192
19.4%
, 65
 
6.6%
0 51
 
5.1%
5 18
 
1.8%
. 14
 
1.4%
1 12
 
1.2%
4 6
 
0.6%
g 5
 
0.5%
Other values (12) 18
 
1.8%
Hangul
ValueCountFrequency (%)
기 187
 
6.4%
타 145
 
5.0%
장 91
 
3.1%
조 67
 
2.3%
분 66
 
2.3%
리 62
 
2.1%
냉 61
 
2.1%
고 60
 
2.1%
제 56
 
1.9%
삼 54
 
1.9%
Other values (242) 2066
70.9%
None
ValueCountFrequency (%)
· 6
100.0%

대분류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
농산물
186 
축산물
130 
임산물
 
16

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row농산물
2nd row농산물
3rd row농산물
4th row농산물
5th row농산물

Common Values

ValueCountFrequency (%)
농산물 186
56.0%
축산물 130
39.2%
임산물 16
 
4.8%

Length

2023-12-12T17:09:45.515328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:09:45.633851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농산물 186
56.0%
축산물 130
39.2%
임산물 16
 
4.8%

Interactions

2023-12-12T17:09:42.999431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:42.798162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:43.106484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:09:42.907753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:09:45.714248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목구분품목명품목코드대분류
품목구분1.0001.0000.9110.826
품목명1.0001.0000.9721.000
품목코드0.9110.9721.0000.826
대분류0.8261.0000.8261.000
2023-12-12T17:09:45.821927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목구분품목코드대분류
품목구분1.000-0.5590.723
품목코드-0.5591.0000.722
대분류0.7230.7221.000

Missing values

2023-12-12T17:09:43.225620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:09:43.326407image/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

품목구분품목명품목코드설명대분류
026생강910119000생강(미파쇄분쇄/기타)농산물
126생강910121000생강(파쇄는쇄/신선는장)농산물
226생강910122000생강(파쇄는쇄/건조)농산물
326생강910129000생강(파쇄는쇄/기타)농산물
426생강2006003000생강(설탕조제)농산물
527설탕1701910000사탕수수,당(기타/향미는색제첨가)농산물
627설탕1701990000사탕수수,당(기타)농산물
728땅콩1202301000낙화생(탈각하지니한)(종자)농산물
828땅콩1202302000낙화생(탈각한)(종자)농산물
928땅콩1202410000낙화생(탈각하지니한)(기타)농산물
품목구분품목명품목코드설명대분류
32222떫은감813401000감(건조)농산물
32323단감810701000단감(신선)농산물
32423단감810709000단감(기타)농산물
32524배808300000배(신선)농산물
32624배2008400000배(조제저장처리)농산물
32725복숭아809300000복숭아(넥타린포함)(신선)농산물
32825복숭아2008701000복숭아(설탕첨가/밀폐용기의/넥터린함)농산물
32925복숭아2008709000복숭아(기타/조제저장처리/넥터린함)농산물
33026생강910111000생강(미파쇄분쇄/신선는장)농산물
33126생강910112000생강(미파쇄분쇄/건조)농산물