Overview

Dataset statistics

Number of variables3
Number of observations761
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.0 KiB
Average record size in memory24.2 B

Variable types

Categorical2
Text1

Dataset

Description대구광역시_농수산물도매시장 상장예외품목 현황_20220630
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15086902&dataSetDetailId=150869021e070215e204b&provdMethod=FILE

Reproduction

Analysis started2023-12-10 17:57:35.646971
Analysis finished2023-12-10 17:57:36.803718
Duration1.16 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상장예외품목중도매인상호
Categorical

Distinct38
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
(주)충북농산
68 
(주)유성청과
61 
(주)대진청과
53 
㈜선산청과
52 
(주)팔팔유통
49 
Other values (33)
478 

Length

Max length8
Median length7
Mean length6.3955322
Min length4

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st row(주)거산청과
2nd row(주)거산청과
3rd row(주)거산청과
4th row(주)거산청과
5th row(주)경도청과

Common Values

ValueCountFrequency (%)
(주)충북농산 68
 
8.9%
(주)유성청과 61
 
8.0%
(주)대진청과 53
 
7.0%
㈜선산청과 52
 
6.8%
(주)팔팔유통 49
 
6.4%
마산청과(주) 47
 
6.2%
(주)청도유통 43
 
5.7%
한양청과㈜ 42
 
5.5%
(주)백두농산 37
 
4.9%
㈜매일청과 27
 
3.5%
Other values (28) 282
37.1%

Length

2023-12-11T02:57:37.073070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주)충북농산 68
 
8.9%
주)유성청과 61
 
8.0%
주)대진청과 53
 
7.0%
㈜선산청과 52
 
6.8%
주)팔팔유통 49
 
6.4%
마산청과(주 47
 
6.2%
주)청도유통 43
 
5.7%
한양청과㈜ 42
 
5.5%
주)백두농산 37
 
4.9%
㈜매일청과 27
 
3.5%
Other values (28) 282
37.1%

품목명
Categorical

Distinct35
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
배추(일반)
176 
대파(일반)
142 
무(일반)
119 
양배추(일반)
106 
쪽파(일반)
36 
Other values (30)
182 

Length

Max length8
Median length6
Mean length5.9894875
Min length3

Unique

Unique11 ?
Unique (%)1.4%

Sample

1st row대파(일반)
2nd row양상추(일반)
3rd row얼갈이배추
4th row열무(일반)
5th row다발무

Common Values

ValueCountFrequency (%)
배추(일반) 176
23.1%
대파(일반) 142
18.7%
무(일반) 119
15.6%
양배추(일반) 106
13.9%
쪽파(일반) 36
 
4.7%
알타리무(일반) 26
 
3.4%
얼갈이배추 22
 
2.9%
미나리(일반) 20
 
2.6%
다발무 18
 
2.4%
열무(일반) 16
 
2.1%
Other values (25) 80
10.5%

Length

2023-12-11T02:57:37.383045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
배추(일반 176
23.1%
대파(일반 142
18.7%
무(일반 119
15.6%
양배추(일반 106
13.9%
쪽파(일반 36
 
4.7%
알타리무(일반 26
 
3.4%
얼갈이배추 22
 
2.9%
미나리(일반 20
 
2.6%
다발무 18
 
2.4%
열무(일반 16
 
2.1%
Other values (25) 80
10.5%

산지이름
Text

Distinct102
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
2023-12-11T02:57:37.802929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.9592641
Min length5

Characters and Unicode

Total characters4535
Distinct characters89
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

Unique26 ?
Unique (%)3.4%

Sample

1st row경북 군위군
2nd row경북 군위군
3rd row경북 군위군
4th row경북 군위군
5th row전북 고창군
ValueCountFrequency (%)
경북 220
 
14.5%
강원 128
 
8.4%
전남 118
 
7.8%
대구 69
 
4.5%
충남 52
 
3.4%
경남 45
 
3.0%
전북 40
 
2.6%
칠곡군 36
 
2.4%
달성군 36
 
2.4%
평창군 32
 
2.1%
Other values (104) 746
49.0%
2023-12-11T02:57:38.567674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
761
16.8%
군 512
 
11.3%
경 315
 
6.9%
북 298
 
6.6%
남 257
 
5.7%
시 221
 
4.9%
전 160
 
3.5%
강 144
 
3.2%
구 136
 
3.0%
원 133
 
2.9%
Other values (79) 1598
35.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3774
83.2%
Space Separator 761
 
16.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 512
 
13.6%
경 315
 
8.3%
북 298
 
7.9%
남 257
 
6.8%
시 221
 
5.9%
전 160
 
4.2%
강 144
 
3.8%
구 136
 
3.6%
원 133
 
3.5%
충 86
 
2.3%
Other values (78) 1512
40.1%
Space Separator
ValueCountFrequency (%)
761
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3774
83.2%
Common 761
 
16.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 512
 
13.6%
경 315
 
8.3%
북 298
 
7.9%
남 257
 
6.8%
시 221
 
5.9%
전 160
 
4.2%
강 144
 
3.8%
구 136
 
3.6%
원 133
 
3.5%
충 86
 
2.3%
Other values (78) 1512
40.1%
Common
ValueCountFrequency (%)
761
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3774
83.2%
ASCII 761
 
16.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
761
100.0%
Hangul
ValueCountFrequency (%)
군 512
 
13.6%
경 315
 
8.3%
북 298
 
7.9%
남 257
 
6.8%
시 221
 
5.9%
전 160
 
4.2%
강 144
 
3.8%
구 136
 
3.6%
원 133
 
3.5%
충 86
 
2.3%
Other values (78) 1512
40.1%

Correlations

2023-12-11T02:57:38.745877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상장예외품목중도매인상호품목명
상장예외품목중도매인상호1.0000.899
품목명0.8991.000
2023-12-11T02:57:38.937581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목명상장예외품목중도매인상호
품목명1.0000.390
상장예외품목중도매인상호0.3901.000
2023-12-11T02:57:39.143442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상장예외품목중도매인상호품목명
상장예외품목중도매인상호1.0000.390
품목명0.3901.000

Missing values

2023-12-11T02:57:36.486958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:57:36.702548image/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

상장예외품목중도매인상호품목명산지이름
0(주)거산청과대파(일반)경북 군위군
1(주)거산청과양상추(일반)경북 군위군
2(주)거산청과얼갈이배추경북 군위군
3(주)거산청과열무(일반)경북 군위군
4(주)경도청과다발무전북 고창군
5(주)경도청과무(일반)강원 강릉시
6(주)경도청과무(일반)강원 평창군
7(주)경도청과무(일반)강원 정선군
8(주)경도청과무(일반)강원 홍천군
9(주)경도청과무(일반)강원 양구군
상장예외품목중도매인상호품목명산지이름
751한양청과㈜열무(일반)경북 칠곡군
752한양청과㈜우엉잎대구 달성군
753한양청과㈜우엉잎경북 칠곡군
754한양청과㈜일반냉이대구 달성군
755한양청과㈜일반냉이경북 칠곡군
756한양청과㈜취나물(일반)대구 달성군
757호연청과(주)방풍나물(일반)전남 여수시
758호연청과(주)상추(일반)충북 충주시
759호연청과(주)쑥(일반)전남 여수시
760호연청과(주)아욱(일반)충북 충주시