Overview

Dataset statistics

Number of variables4
Number of observations86
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory34.5 B

Variable types

Text2
Categorical1
Numeric1

Dataset

Description대전광역시 서구의 축산현황에 대한 데이터로 가축사육업(소, 돼지, 염소 등) 농가의 상호명, 소재지주소, 기준일 사육두수에 대한 정보
Author대전광역시 서구
URLhttps://www.data.go.kr/data/15108403/fileData.do

Alerts

주사육업종 is highly imbalanced (69.4%)Imbalance
사육두수 has 7 (8.1%) zerosZeros

Reproduction

Analysis started2023-12-12 00:46:46.585980
Analysis finished2023-12-12 00:46:47.006647
Duration0.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명칭
Text

Distinct52
Distinct (%)60.5%
Missing0
Missing (%)0.0%
Memory size820.0 B
2023-12-12T09:46:47.197804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length4.9302326
Min length2

Characters and Unicode

Total characters424
Distinct characters83
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

Unique49 ?
Unique (%)57.0%

Sample

1st row광영농장
2nd row봉곡농장
3rd row산막골농장
4th row한우리농장
5th row용촌목장
ValueCountFrequency (%)
농장명 31
25.0%
없음 31
25.0%
농장 5
 
4.0%
자백농장 3
 
2.4%
봉곡농장 3
 
2.4%
쌍둥이농장 1
 
0.8%
아도농장 1
 
0.8%
용촌농장 1
 
0.8%
허화균농장 1
 
0.8%
장태산 1
 
0.8%
Other values (46) 46
37.1%
2023-12-12T09:46:47.624231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 86
20.3%
농 80
18.9%
38
 
9.0%
명 32
 
7.5%
없 31
 
7.3%
음 31
 
7.3%
골 4
 
0.9%
진 4
 
0.9%
우 4
 
0.9%
목 4
 
0.9%
Other values (73) 110
25.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 386
91.0%
Space Separator 38
 
9.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 86
22.3%
농 80
20.7%
명 32
 
8.3%
없 31
 
8.0%
음 31
 
8.0%
골 4
 
1.0%
진 4
 
1.0%
우 4
 
1.0%
목 4
 
1.0%
자 4
 
1.0%
Other values (72) 106
27.5%
Space Separator
ValueCountFrequency (%)
38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 386
91.0%
Common 38
 
9.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 86
22.3%
농 80
20.7%
명 32
 
8.3%
없 31
 
8.0%
음 31
 
8.0%
골 4
 
1.0%
진 4
 
1.0%
우 4
 
1.0%
목 4
 
1.0%
자 4
 
1.0%
Other values (72) 106
27.5%
Common
ValueCountFrequency (%)
38
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 386
91.0%
ASCII 38
 
9.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 86
22.3%
농 80
20.7%
명 32
 
8.3%
없 31
 
8.0%
음 31
 
8.0%
골 4
 
1.0%
진 4
 
1.0%
우 4
 
1.0%
목 4
 
1.0%
자 4
 
1.0%
Other values (72) 106
27.5%
ASCII
ValueCountFrequency (%)
38
100.0%

주사육업종
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size820.0 B
한우
77 
염소
 
6
돼지
 
2
산양
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.2%

Sample

1st row한우
2nd row한우
3rd row돼지
4th row한우
5th row한우

Common Values

ValueCountFrequency (%)
한우 77
89.5%
염소 6
 
7.0%
돼지 2
 
2.3%
산양 1
 
1.2%

Length

2023-12-12T09:46:47.792706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:46:47.933884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한우 77
89.5%
염소 6
 
7.0%
돼지 2
 
2.3%
산양 1
 
1.2%

사업장소재지(도로명)
Text

Distinct84
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size820.0 B
2023-12-12T09:46:48.294705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length22.77907
Min length15

Characters and Unicode

Total characters1959
Distinct characters90
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)95.3%

Sample

1st row대전광역시 서구 내금곡길 207 (봉곡동)
2nd row대전광역시 서구 세점길 460 (봉곡동)
3rd row대전광역시 서구 장안동 396-3
4th row대전광역시 서구 조련길 80 (흑석동)
5th row대전광역시 서구 용촌동 264번지 4호
ValueCountFrequency (%)
대전광역시 86
20.5%
서구 86
20.5%
봉곡동 20
 
4.8%
용촌동 15
 
3.6%
세점길 13
 
3.1%
흑석동 11
 
2.6%
원정동 10
 
2.4%
산직동 8
 
1.9%
평촌동 6
 
1.4%
장안동 6
 
1.4%
Other values (119) 158
37.7%
2023-12-12T09:46:48.863974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
366
18.7%
시 92
 
4.7%
대 86
 
4.4%
광 86
 
4.4%
역 86
 
4.4%
서 86
 
4.4%
구 86
 
4.4%
전 86
 
4.4%
동 86
 
4.4%
) 67
 
3.4%
Other values (80) 832
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1135
57.9%
Space Separator 366
 
18.7%
Decimal Number 292
 
14.9%
Close Punctuation 67
 
3.4%
Open Punctuation 67
 
3.4%
Dash Punctuation 31
 
1.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 92
 
8.1%
대 86
 
7.6%
광 86
 
7.6%
역 86
 
7.6%
서 86
 
7.6%
구 86
 
7.6%
전 86
 
7.6%
동 86
 
7.6%
길 64
 
5.6%
곡 36
 
3.2%
Other values (65) 341
30.0%
Decimal Number
ValueCountFrequency (%)
1 66
22.6%
4 33
11.3%
2 33
11.3%
6 33
11.3%
3 30
10.3%
9 21
 
7.2%
0 21
 
7.2%
5 19
 
6.5%
7 18
 
6.2%
8 18
 
6.2%
Space Separator
ValueCountFrequency (%)
366
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Open Punctuation
ValueCountFrequency (%)
( 67
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1135
57.9%
Common 824
42.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 92
 
8.1%
대 86
 
7.6%
광 86
 
7.6%
역 86
 
7.6%
서 86
 
7.6%
구 86
 
7.6%
전 86
 
7.6%
동 86
 
7.6%
길 64
 
5.6%
곡 36
 
3.2%
Other values (65) 341
30.0%
Common
ValueCountFrequency (%)
366
44.4%
) 67
 
8.1%
( 67
 
8.1%
1 66
 
8.0%
4 33
 
4.0%
2 33
 
4.0%
6 33
 
4.0%
- 31
 
3.8%
3 30
 
3.6%
9 21
 
2.5%
Other values (5) 77
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1135
57.9%
ASCII 824
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
366
44.4%
) 67
 
8.1%
( 67
 
8.1%
1 66
 
8.0%
4 33
 
4.0%
2 33
 
4.0%
6 33
 
4.0%
- 31
 
3.8%
3 30
 
3.6%
9 21
 
2.5%
Other values (5) 77
 
9.3%
Hangul
ValueCountFrequency (%)
시 92
 
8.1%
대 86
 
7.6%
광 86
 
7.6%
역 86
 
7.6%
서 86
 
7.6%
구 86
 
7.6%
전 86
 
7.6%
동 86
 
7.6%
길 64
 
5.6%
곡 36
 
3.2%
Other values (65) 341
30.0%

사육두수
Real number (ℝ)

ZEROS 

Distinct52
Distinct (%)60.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.034884
Minimum0
Maximum1000
Zeros7
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-12T09:46:49.068508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16.25
median20
Q350
95-th percentile112.75
Maximum1000
Range1000
Interquartile range (IQR)43.75

Descriptive statistics

Standard deviation111.53712
Coefficient of variation (CV)2.4766827
Kurtosis64.85492
Mean45.034884
Median Absolute Deviation (MAD)16.5
Skewness7.6155312
Sum3873
Variance12440.528
MonotonicityNot monotonic
2023-12-12T09:46:49.251086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7
 
8.1%
2 5
 
5.8%
22 4
 
4.7%
4 4
 
4.7%
8 4
 
4.7%
11 3
 
3.5%
20 3
 
3.5%
6 3
 
3.5%
3 2
 
2.3%
10 2
 
2.3%
Other values (42) 49
57.0%
ValueCountFrequency (%)
0 7
8.1%
2 5
5.8%
3 2
 
2.3%
4 4
4.7%
5 1
 
1.2%
6 3
3.5%
7 2
 
2.3%
8 4
4.7%
10 2
 
2.3%
11 3
3.5%
ValueCountFrequency (%)
1000 1
1.2%
230 1
1.2%
136 1
1.2%
125 1
1.2%
114 1
1.2%
109 1
1.2%
106 1
1.2%
98 1
1.2%
94 2
2.3%
92 1
1.2%

Interactions

2023-12-12T09:46:46.795781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:46:49.364878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명칭주사육업종사업장소재지(도로명)사육두수
사업장명칭1.0000.9561.0000.904
주사육업종0.9561.0000.6620.796
사업장소재지(도로명)1.0000.6621.0000.000
사육두수0.9040.7960.0001.000
2023-12-12T09:46:49.477509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사육두수주사육업종
사육두수1.0000.436
주사육업종0.4361.000

Missing values

2023-12-12T09:46:46.894813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:46:46.971661image/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

사업장명칭주사육업종사업장소재지(도로명)사육두수
0광영농장한우대전광역시 서구 내금곡길 207 (봉곡동)40
1봉곡농장한우대전광역시 서구 세점길 460 (봉곡동)109
2산막골농장돼지대전광역시 서구 장안동 396-360
3한우리농장한우대전광역시 서구 조련길 80 (흑석동)4
4용촌목장한우대전광역시 서구 용촌동 264번지 4호136
5농장명 없음한우대전광역시 서구 가마절길 99 (산직동)18
6장안농장한우대전광역시 서구 장안로 615 (장안동)21
7농장명 없음한우대전광역시 서구 외금곡길 38-22 (봉곡동)125
8농장명 없음한우대전광역시 서구 내금곡길 31 (봉곡동)106
9농장명 없음한우대전광역시 서구 무도리길 85 (원정동)29
사업장명칭주사육업종사업장소재지(도로명)사육두수
76성진농장한우대전광역시 서구 세점길 679-13 (봉곡동)36
77용촌농장한우대전광역시 서구 시누리길 49 (용촌동)16
78자백농장한우대전광역시 서구 세점길 180(흑석동)114
79아도농장염소대전광역시 서구 장안동 208번지60
80자백농장한우대전광역시 서구 흑석동 689번지 4호22
81농장명 없음한우대전광역시 서구 세점길 601(봉곡동)4
82농장명 없음염소대전광역시 서구 세점길 601(봉곡동)20
83농장명 없음염소대전광역시 서구 봉곡동 12-720
84소민농장한우대전광역시 서구 용촌동 288-119
85농장명 없음염소대전광역시 서구 용촌동 910