Overview

Dataset statistics

Number of variables5
Number of observations96
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory42.4 B

Variable types

Text3
Categorical1
Numeric1

Dataset

Description대전광역시 유성구 가축사육업 현황에 대한 데이터로 사업장명칭, 주사육업종, 사육두수, 사업장소재지 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15034868/fileData.do

Alerts

사육두수 has 1 (1.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 16:47:23.867253
Analysis finished2023-12-12 16:47:25.152170
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명칭
Text

Distinct91
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size900.0 B
2023-12-13T01:47:25.388046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length4
Mean length4.8541667
Min length4

Characters and Unicode

Total characters466
Distinct characters136
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)91.7%

Sample

1st row구암농장
2nd row진미농장
3rd row진흥농장
4th row의석농장
5th row성수농장
ValueCountFrequency (%)
농장 19
 
15.8%
성북농장 4
 
3.3%
무지개 2
 
1.7%
가마동농장 2
 
1.7%
세동농장 2
 
1.7%
소민농장 1
 
0.8%
강현양 1
 
0.8%
도깨비농장 1
 
0.8%
신창수 1
 
0.8%
새일농장 1
 
0.8%
Other values (86) 86
71.7%
2023-12-13T01:47:25.892890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 93
20.0%
농 92
19.7%
24
 
5.2%
성 16
 
3.4%
동 10
 
2.1%
마 6
 
1.3%
북 5
 
1.1%
이 5
 
1.1%
새 5
 
1.1%
금 4
 
0.9%
Other values (126) 206
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 440
94.4%
Space Separator 24
 
5.2%
Decimal Number 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 93
21.1%
농 92
20.9%
성 16
 
3.6%
동 10
 
2.3%
마 6
 
1.4%
북 5
 
1.1%
이 5
 
1.1%
새 5
 
1.1%
금 4
 
0.9%
원 4
 
0.9%
Other values (123) 200
45.5%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 440
94.4%
Common 26
 
5.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 93
21.1%
농 92
20.9%
성 16
 
3.6%
동 10
 
2.3%
마 6
 
1.4%
북 5
 
1.1%
이 5
 
1.1%
새 5
 
1.1%
금 4
 
0.9%
원 4
 
0.9%
Other values (123) 200
45.5%
Common
ValueCountFrequency (%)
24
92.3%
1 1
 
3.8%
2 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 440
94.4%
ASCII 26
 
5.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 93
21.1%
농 92
20.9%
성 16
 
3.6%
동 10
 
2.3%
마 6
 
1.4%
북 5
 
1.1%
이 5
 
1.1%
새 5
 
1.1%
금 4
 
0.9%
원 4
 
0.9%
Other values (123) 200
45.5%
ASCII
ValueCountFrequency (%)
24
92.3%
1 1
 
3.8%
2 1
 
3.8%

주사육업종
Categorical

Distinct7
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size900.0 B
한우
64 
육계
18 
산양
 
5
종계/산란계
 
4
사슴
 
3
Other values (2)
 
2

Length

Max length6
Median length2
Mean length2.2083333
Min length2

Unique

Unique2 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
한우 64
66.7%
육계 18
 
18.8%
산양 5
 
5.2%
종계/산란계 4
 
4.2%
사슴 3
 
3.1%
부화용알생산 1
 
1.0%
육우 1
 
1.0%

Length

2023-12-13T01:47:26.103653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:47:26.229964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한우 64
66.7%
육계 18
 
18.8%
산양 5
 
5.2%
종계/산란계 4
 
4.2%
사슴 3
 
3.1%
부화용알생산 1
 
1.0%
육우 1
 
1.0%

권리주체명
Text

Distinct93
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size900.0 B
2023-12-13T01:47:26.563330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length3
Mean length3.1770833
Min length2

Characters and Unicode

Total characters305
Distinct characters115
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

Unique90 ?
Unique (%)93.8%

Sample

1st row노원용
2nd row강권식
3rd row김봉애
4th row강의석
5th row김성수
ValueCountFrequency (%)
심현용 2
 
2.0%
남기원 2
 
2.0%
성영현 2
 
2.0%
강신태 1
 
1.0%
엄영희 1
 
1.0%
노원용 1
 
1.0%
이호병 1
 
1.0%
강현양 1
 
1.0%
임세묵 1
 
1.0%
김은미 1
 
1.0%
Other values (85) 85
86.7%
2023-12-13T01:47:27.110588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 17
 
5.6%
성 16
 
5.2%
김 15
 
4.9%
현 11
 
3.6%
영 10
 
3.3%
순 8
 
2.6%
기 7
 
2.3%
강 7
 
2.3%
정 7
 
2.3%
용 6
 
2.0%
Other values (105) 201
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 303
99.3%
Space Separator 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 17
 
5.6%
성 16
 
5.3%
김 15
 
5.0%
현 11
 
3.6%
영 10
 
3.3%
순 8
 
2.6%
기 7
 
2.3%
강 7
 
2.3%
정 7
 
2.3%
용 6
 
2.0%
Other values (104) 199
65.7%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 303
99.3%
Common 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 17
 
5.6%
성 16
 
5.3%
김 15
 
5.0%
현 11
 
3.6%
영 10
 
3.3%
순 8
 
2.6%
기 7
 
2.3%
강 7
 
2.3%
정 7
 
2.3%
용 6
 
2.0%
Other values (104) 199
65.7%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 303
99.3%
ASCII 2
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 17
 
5.6%
성 16
 
5.3%
김 15
 
5.0%
현 11
 
3.6%
영 10
 
3.3%
순 8
 
2.6%
기 7
 
2.3%
강 7
 
2.3%
정 7
 
2.3%
용 6
 
2.0%
Other values (104) 199
65.7%
ASCII
ValueCountFrequency (%)
2
100.0%

사업장소재지(지번)
Text

Distinct92
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size900.0 B
2023-12-13T01:47:27.547098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length32
Mean length23.479167
Min length19

Characters and Unicode

Total characters2254
Distinct characters64
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)91.7%

Sample

1st row대전광역시 유성구 구암동 311번지
2nd row대전광역시 유성구 용계동 347번지 14호
3rd row대전광역시 유성구 원내동 478번지 9호
4th row대전광역시 유성구 성북동 678번지 1호 유성구 성북동 667-1외 1필지
5th row대전광역시 유성구 성북동 593번지
ValueCountFrequency (%)
유성구 97
20.6%
대전광역시 96
20.3%
성북동 26
 
5.5%
1호 14
 
3.0%
세동 11
 
2.3%
2호 10
 
2.1%
3호 9
 
1.9%
둔곡동 9
 
1.9%
4호 8
 
1.7%
대동 7
 
1.5%
Other values (126) 185
39.2%
2023-12-13T01:47:28.091065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
559
24.8%
성 123
 
5.5%
지 108
 
4.8%
대 104
 
4.6%
번 100
 
4.4%
구 99
 
4.4%
유 97
 
4.3%
동 97
 
4.3%
광 96
 
4.3%
역 96
 
4.3%
Other values (54) 775
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1328
58.9%
Space Separator 559
24.8%
Decimal Number 366
 
16.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 123
 
9.3%
지 108
 
8.1%
대 104
 
7.8%
번 100
 
7.5%
구 99
 
7.5%
유 97
 
7.3%
동 97
 
7.3%
광 96
 
7.2%
역 96
 
7.2%
시 96
 
7.2%
Other values (42) 312
23.5%
Decimal Number
ValueCountFrequency (%)
1 69
18.9%
2 58
15.8%
3 40
10.9%
4 38
10.4%
5 36
9.8%
6 34
9.3%
8 28
7.7%
9 24
 
6.6%
0 20
 
5.5%
7 19
 
5.2%
Space Separator
ValueCountFrequency (%)
559
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1328
58.9%
Common 926
41.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 123
 
9.3%
지 108
 
8.1%
대 104
 
7.8%
번 100
 
7.5%
구 99
 
7.5%
유 97
 
7.3%
동 97
 
7.3%
광 96
 
7.2%
역 96
 
7.2%
시 96
 
7.2%
Other values (42) 312
23.5%
Common
ValueCountFrequency (%)
559
60.4%
1 69
 
7.5%
2 58
 
6.3%
3 40
 
4.3%
4 38
 
4.1%
5 36
 
3.9%
6 34
 
3.7%
8 28
 
3.0%
9 24
 
2.6%
0 20
 
2.2%
Other values (2) 20
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1328
58.9%
ASCII 926
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
559
60.4%
1 69
 
7.5%
2 58
 
6.3%
3 40
 
4.3%
4 38
 
4.1%
5 36
 
3.9%
6 34
 
3.7%
8 28
 
3.0%
9 24
 
2.6%
0 20
 
2.2%
Other values (2) 20
 
2.2%
Hangul
ValueCountFrequency (%)
성 123
 
9.3%
지 108
 
8.1%
대 104
 
7.8%
번 100
 
7.5%
구 99
 
7.5%
유 97
 
7.3%
동 97
 
7.3%
광 96
 
7.2%
역 96
 
7.2%
시 96
 
7.2%
Other values (42) 312
23.5%

사육두수
Real number (ℝ)

MISSING 

Distinct54
Distinct (%)56.8%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean1102.8105
Minimum1
Maximum25000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2023-12-13T01:47:28.294999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q110
median34
Q3105
95-th percentile8000
Maximum25000
Range24999
Interquartile range (IQR)95

Descriptive statistics

Standard deviation4001.2948
Coefficient of variation (CV)3.6282704
Kurtosis21.09255
Mean1102.8105
Median Absolute Deviation (MAD)26
Skewness4.5139881
Sum104767
Variance16010360
MonotonicityNot monotonic
2023-12-13T01:47:28.438963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40 6
 
6.2%
2 5
 
5.2%
6 5
 
5.2%
9 4
 
4.2%
300 4
 
4.2%
80 4
 
4.2%
5 3
 
3.1%
10 3
 
3.1%
20 3
 
3.1%
45 2
 
2.1%
Other values (44) 56
58.3%
ValueCountFrequency (%)
1 1
 
1.0%
2 5
5.2%
3 2
 
2.1%
4 2
 
2.1%
5 3
3.1%
6 5
5.2%
8 1
 
1.0%
9 4
4.2%
10 3
3.1%
11 2
 
2.1%
ValueCountFrequency (%)
25000 1
1.0%
20000 1
1.0%
18010 1
1.0%
10000 1
1.0%
8000 2
2.1%
6000 1
1.0%
2000 1
1.0%
1000 1
1.0%
800 1
1.0%
500 2
2.1%

Interactions

2023-12-13T01:47:24.805514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:47:28.549227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명칭주사육업종권리주체명사업장소재지(지번)사육두수
사업장명칭1.0000.9610.9960.9681.000
주사육업종0.9611.0000.7140.9700.515
권리주체명0.9960.7141.0000.9971.000
사업장소재지(지번)0.9680.9700.9971.0001.000
사육두수1.0000.5151.0001.0001.000
2023-12-13T01:47:28.667613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사육두수주사육업종
사육두수1.0000.358
주사육업종0.3581.000

Missing values

2023-12-13T01:47:24.945181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:47:25.097681image/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

사업장명칭주사육업종권리주체명사업장소재지(지번)사육두수
0구암농장한우노원용대전광역시 유성구 구암동 311번지34
1진미농장육계강권식대전광역시 유성구 용계동 347번지 14호25000
2진흥농장육계김봉애대전광역시 유성구 원내동 478번지 9호8000
3의석농장한우강의석대전광역시 유성구 성북동 678번지 1호 유성구 성북동 667-1외 1필지40
4성수농장한우김성수대전광역시 유성구 성북동 593번지30
5이종성목장한우이종성대전광역시 유성구 세동 235번지12
6대건농장한우오종학대전광역시 유성구 둔곡동 249번지41
7탑립농장한우정상건대전광역시 유성구 탑립동 566번지43
8석청농장한우백석환대전광역시 유성구 금고동 291번지56
9도안농장육계길석노대전광역시 유성구 학하동 31번지8000
사업장명칭주사육업종권리주체명사업장소재지(지번)사육두수
86다은농장한우최은영대전광역시 유성구 세동 266번지3
87성북농장한우신영훈대전광역시 유성구 성북동 142번지 4호24
88가마동농장한우남기원대전광역시 유성구 대동 148번지46
89학교동농장한우시오노히로꼬대전광역시 유성구 대동 91번지50
90쇠일농장한우성채경대전광역시 유성구 금탄동 154번지 6호3
91하늘연달농장한우성진아대전광역시 유성구 금탄동 158번지 1호1
92무지개 축사한우김영순대전광역시 유성구 성북동 593번지 4호80
93무지개 농장한우백상선대전광역시 유성구 성북동 593번지 2호80
94소민농장한우이정연대전광역시 유성구 성북동 332번지 1호6
95기특이네 농장종계/산란계김홍연대전광역시 유성구 용계동 179번지 1호200