Overview

Dataset statistics

Number of variables4
Number of observations677
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.3 KiB
Average record size in memory32.2 B

Variable types

Text2
Categorical2

Dataset

Description충청북도 옥천군 축산 및 가금류 농가 현황(사업장명, 축종구분,행정동명, 사육두수, 소재지) 등의 데이터를 제공 합니다.
Author충청북도 옥천군
URLhttps://www.data.go.kr/data/15034243/fileData.do

Alerts

축종구분 is highly imbalanced (82.7%)Imbalance

Reproduction

Analysis started2023-12-12 13:55:06.882696
Analysis finished2023-12-12 13:55:07.280219
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

Distinct608
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2023-12-12T22:55:07.557994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length8
Mean length8.3692762
Min length6

Characters and Unicode

Total characters5666
Distinct characters290
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique556 ?
Unique (%)82.1%

Sample

1st row 의경농장
2nd row 강*훈
3rd row 가풍목장
4th row 원각목장
5th row 군남목장2
ValueCountFrequency (%)
농장 11
 
1.6%
친환경우리소영농조합법인 6
 
0.9%
청정목장 5
 
0.7%
형제목장 4
 
0.6%
구일목장 3
 
0.4%
금산목장 3
 
0.4%
금암목장 3
 
0.4%
태형농장 3
 
0.4%
동백농장 3
 
0.4%
그린농장 3
 
0.4%
Other values (607) 657
93.7%
2023-12-12T22:55:08.051697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2754
48.6%
장 539
 
9.5%
농 289
 
5.1%
목 268
 
4.7%
* 72
 
1.3%
산 62
 
1.1%
성 44
 
0.8%
축 43
 
0.8%
우 40
 
0.7%
영 38
 
0.7%
Other values (280) 1517
26.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2778
49.0%
Space Separator 2754
48.6%
Other Punctuation 74
 
1.3%
Decimal Number 40
 
0.7%
Open Punctuation 10
 
0.2%
Close Punctuation 10
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 539
 
19.4%
농 289
 
10.4%
목 268
 
9.6%
산 62
 
2.2%
성 44
 
1.6%
축 43
 
1.5%
우 40
 
1.4%
영 38
 
1.4%
수 34
 
1.2%
이 33
 
1.2%
Other values (268) 1388
50.0%
Decimal Number
ValueCountFrequency (%)
2 23
57.5%
1 6
 
15.0%
3 4
 
10.0%
4 3
 
7.5%
0 2
 
5.0%
6 1
 
2.5%
5 1
 
2.5%
Other Punctuation
ValueCountFrequency (%)
* 72
97.3%
' 2
 
2.7%
Space Separator
ValueCountFrequency (%)
2754
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2888
51.0%
Hangul 2778
49.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 539
 
19.4%
농 289
 
10.4%
목 268
 
9.6%
산 62
 
2.2%
성 44
 
1.6%
축 43
 
1.5%
우 40
 
1.4%
영 38
 
1.4%
수 34
 
1.2%
이 33
 
1.2%
Other values (268) 1388
50.0%
Common
ValueCountFrequency (%)
2754
95.4%
* 72
 
2.5%
2 23
 
0.8%
( 10
 
0.3%
) 10
 
0.3%
1 6
 
0.2%
3 4
 
0.1%
4 3
 
0.1%
0 2
 
0.1%
' 2
 
0.1%
Other values (2) 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2888
51.0%
Hangul 2778
49.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2754
95.4%
* 72
 
2.5%
2 23
 
0.8%
( 10
 
0.3%
) 10
 
0.3%
1 6
 
0.2%
3 4
 
0.1%
4 3
 
0.1%
0 2
 
0.1%
' 2
 
0.1%
Other values (2) 2
 
0.1%
Hangul
ValueCountFrequency (%)
장 539
 
19.4%
농 289
 
10.4%
목 268
 
9.6%
산 62
 
2.2%
성 44
 
1.6%
축 43
 
1.5%
우 40
 
1.4%
영 38
 
1.4%
수 34
 
1.2%
이 33
 
1.2%
Other values (268) 1388
50.0%

축종구분
Categorical

IMBALANCE 

Distinct7
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
한우
633 
염소
 
20
산란계
 
10
젖소
 
5
돼지
 
5
Other values (2)
 
4

Length

Max length8
Median length6
Mean length6.0502216
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row 한우
2nd row 한우
3rd row 한우
4th row 한우
5th row 한우

Common Values

ValueCountFrequency (%)
한우 633
93.5%
염소 20
 
3.0%
산란계 10
 
1.5%
젖소 5
 
0.7%
돼지 5
 
0.7%
육계 2
 
0.3%
메추리 2
 
0.3%

Length

2023-12-12T22:55:08.219491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:55:08.344522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한우 633
93.5%
염소 20
 
3.0%
산란계 10
 
1.5%
젖소 5
 
0.7%
돼지 5
 
0.7%
육계 2
 
0.3%
메추리 2
 
0.3%

행정동명
Categorical

Distinct18
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
옥천읍
208 
동이면
128 
안내면
64 
이원면
49 
군서면
48 
Other values (13)
180 

Length

Max length8
Median length7
Mean length7.0324963
Min length7

Unique

Unique3 ?
Unique (%)0.4%

Sample

1st row 옥천읍
2nd row 옥천읍
3rd row 옥천읍
4th row 옥천읍
5th row 옥천읍

Common Values

ValueCountFrequency (%)
옥천읍 208
30.7%
동이면 128
18.9%
안내면 64
 
9.5%
이원면 49
 
7.2%
군서면 48
 
7.1%
안남면 45
 
6.6%
청성면 45
 
6.6%
청산면 42
 
6.2%
군북면 26
 
3.8%
청산면 6
 
0.9%
Other values (8) 16
 
2.4%

Length

2023-12-12T22:55:08.767105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
옥천읍 209
30.9%
동이면 131
19.4%
안내면 65
 
9.6%
이원면 52
 
7.7%
군서면 50
 
7.4%
청성면 48
 
7.1%
청산면 48
 
7.1%
안남면 47
 
6.9%
군북면 27
 
4.0%

사육두수
Text

Distinct143
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2023-12-12T22:55:09.120037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length1.9793205
Min length1

Characters and Unicode

Total characters1340
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

Unique59 ?
Unique (%)8.7%

Sample

1st row2
2nd row14
3rd row53
4th row11
5th row47
ValueCountFrequency (%)
21 20
 
3.0%
5 18
 
2.7%
1 18
 
2.7%
7 16
 
2.4%
2 15
 
2.2%
6 15
 
2.2%
4 15
 
2.2%
14 15
 
2.2%
23 13
 
1.9%
11 13
 
1.9%
Other values (133) 519
76.7%
2023-12-12T22:55:09.657873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 248
18.5%
2 194
14.5%
3 165
12.3%
4 142
10.6%
5 124
9.3%
0 109
8.1%
6 108
8.1%
7 100
7.5%
8 73
 
5.4%
9 60
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1323
98.7%
Other Punctuation 17
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 248
18.7%
2 194
14.7%
3 165
12.5%
4 142
10.7%
5 124
9.4%
0 109
8.2%
6 108
8.2%
7 100
7.6%
8 73
 
5.5%
9 60
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1340
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 248
18.5%
2 194
14.5%
3 165
12.3%
4 142
10.6%
5 124
9.3%
0 109
8.1%
6 108
8.1%
7 100
7.5%
8 73
 
5.4%
9 60
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1340
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 248
18.5%
2 194
14.5%
3 165
12.3%
4 142
10.6%
5 124
9.3%
0 109
8.1%
6 108
8.1%
7 100
7.5%
8 73
 
5.4%
9 60
 
4.5%

Correlations

2023-12-12T22:55:09.746402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
축종구분행정동명
축종구분1.0000.743
행정동명0.7431.000
2023-12-12T22:55:09.820290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
축종구분행정동명
축종구분1.0000.447
행정동명0.4471.000
2023-12-12T22:55:09.895149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
축종구분행정동명
축종구분1.0000.447
행정동명0.4471.000

Missing values

2023-12-12T22:55:07.152429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:55:07.236689image/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

사업장명축종구분행정동명사육두수
0의경농장한우옥천읍2
1강*훈한우옥천읍14
2가풍목장한우옥천읍53
3원각목장한우옥천읍11
4군남목장2한우옥천읍47
5훈현목장한우옥천읍46
6조*욱한우옥천읍239
7가람농장한우옥천읍34
8우진한우옥천읍7
9인준목장한우옥천읍80
사업장명축종구분행정동명사육두수
667천*귀한우군북면6
668명성목장한우군북면130
669주현농장한우군북면30
670남경목장한우군북면43
671관성농장한우군북면37
672토담목장한우군북면14
673하늘농장한우군북면82
674지오농장한우군북면29
675이*배한우군북면4
676자모흑염소농장염소군북면42