Overview

Dataset statistics

Number of variables6
Number of observations535
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.2 KiB
Average record size in memory50.2 B

Variable types

Numeric2
Text2
Categorical2

Dataset

Description전북특별자치도 진안군 축사 현황에 대한 데이터입니다. 사업장 명칭, 주사육 업종, 사업장 소재지, 사육두수에 대한 정보를 제공합니다.
Author전북특별자치도 진안군
URLhttps://www.data.go.kr/data/15039284/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
주사육업종 is highly imbalanced (50.1%)Imbalance
순번 has unique valuesUnique
사육두수 has 42 (7.9%) zerosZeros

Reproduction

Analysis started2024-03-14 21:01:47.505858
Analysis finished2024-03-14 21:01:50.033851
Duration2.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct535
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean268
Minimum1
Maximum535
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-03-15T06:01:50.170377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile27.7
Q1134.5
median268
Q3401.5
95-th percentile508.3
Maximum535
Range534
Interquartile range (IQR)267

Descriptive statistics

Standard deviation154.58547
Coefficient of variation (CV)0.57681144
Kurtosis-1.2
Mean268
Median Absolute Deviation (MAD)134
Skewness0
Sum143380
Variance23896.667
MonotonicityStrictly increasing
2024-03-15T06:01:50.493459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
353 1
 
0.2%
367 1
 
0.2%
366 1
 
0.2%
365 1
 
0.2%
364 1
 
0.2%
363 1
 
0.2%
362 1
 
0.2%
361 1
 
0.2%
360 1
 
0.2%
Other values (525) 525
98.1%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
535 1
0.2%
534 1
0.2%
533 1
0.2%
532 1
0.2%
531 1
0.2%
530 1
0.2%
529 1
0.2%
528 1
0.2%
527 1
0.2%
526 1
0.2%

사업장명칭
Text

Distinct475
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-03-15T06:01:51.495259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length4
Mean length4.6635514
Min length2

Characters and Unicode

Total characters2495
Distinct characters277
Distinct categories6 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique430 ?
Unique (%)80.4%

Sample

1st row우식농장
2nd row진현농장
3rd row군식농장
4th row가림농장
5th row슬기농장
ValueCountFrequency (%)
농장 21
 
3.6%
2 6
 
1.0%
초원농장 4
 
0.7%
희망농장 4
 
0.7%
강정한우마을 4
 
0.7%
대곡농장 3
 
0.5%
한우리농장 3
 
0.5%
가림농장 3
 
0.5%
양지농장 3
 
0.5%
호준농장 3
 
0.5%
Other values (483) 536
90.8%
2024-03-15T06:01:52.787168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 505
20.2%
농 463
 
18.6%
55
 
2.2%
우 39
 
1.6%
산 38
 
1.5%
원 35
 
1.4%
목 31
 
1.2%
한 29
 
1.2%
마 29
 
1.2%
2 28
 
1.1%
Other values (267) 1243
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2385
95.6%
Space Separator 55
 
2.2%
Decimal Number 37
 
1.5%
Open Punctuation 8
 
0.3%
Close Punctuation 8
 
0.3%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 505
21.2%
농 463
 
19.4%
우 39
 
1.6%
산 38
 
1.6%
원 35
 
1.5%
목 31
 
1.3%
한 29
 
1.2%
마 29
 
1.2%
대 26
 
1.1%
진 26
 
1.1%
Other values (257) 1164
48.8%
Decimal Number
ValueCountFrequency (%)
2 28
75.7%
1 5
 
13.5%
8 2
 
5.4%
0 1
 
2.7%
5 1
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
H 1
50.0%
L 1
50.0%
Space Separator
ValueCountFrequency (%)
55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2384
95.6%
Common 108
 
4.3%
Latin 2
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 505
21.2%
농 463
 
19.4%
우 39
 
1.6%
산 38
 
1.6%
원 35
 
1.5%
목 31
 
1.3%
한 29
 
1.2%
마 29
 
1.2%
대 26
 
1.1%
진 26
 
1.1%
Other values (256) 1163
48.8%
Common
ValueCountFrequency (%)
55
50.9%
2 28
25.9%
( 8
 
7.4%
) 8
 
7.4%
1 5
 
4.6%
8 2
 
1.9%
0 1
 
0.9%
5 1
 
0.9%
Latin
ValueCountFrequency (%)
H 1
50.0%
L 1
50.0%
Han
ValueCountFrequency (%)
珍 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2384
95.6%
ASCII 110
 
4.4%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 505
21.2%
농 463
 
19.4%
우 39
 
1.6%
산 38
 
1.6%
원 35
 
1.5%
목 31
 
1.3%
한 29
 
1.2%
마 29
 
1.2%
대 26
 
1.1%
진 26
 
1.1%
Other values (256) 1163
48.8%
ASCII
ValueCountFrequency (%)
55
50.0%
2 28
25.5%
( 8
 
7.3%
) 8
 
7.3%
1 5
 
4.5%
8 2
 
1.8%
H 1
 
0.9%
L 1
 
0.9%
0 1
 
0.9%
5 1
 
0.9%
CJK
ValueCountFrequency (%)
珍 1
100.0%

주사육업종
Categorical

IMBALANCE 

Distinct12
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
한우
354 
육계
70 
돼지
36 
염소
 
27
젖소
 
15
Other values (7)
 
33

Length

Max length5
Median length2
Mean length2.0149533
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
한우 354
66.2%
육계 70
 
13.1%
돼지 36
 
6.7%
염소 27
 
5.0%
젖소 15
 
2.8%
산양 15
 
2.8%
육우 6
 
1.1%
오리 5
 
0.9%
산란육성계 2
 
0.4%
메추리 2
 
0.4%
Other values (2) 3
 
0.6%

Length

2024-03-15T06:01:53.225760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한우 354
66.2%
육계 70
 
13.1%
돼지 36
 
6.7%
염소 27
 
5.0%
젖소 15
 
2.8%
산양 15
 
2.8%
육우 6
 
1.1%
오리 5
 
0.9%
산란육성계 2
 
0.4%
메추리 2
 
0.4%
Other values (2) 3
 
0.6%

사업장소재지
Text

Distinct64
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-03-15T06:01:54.109307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters10165
Distinct characters90
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

Unique9 ?
Unique (%)1.7%

Sample

1st row전북특별자치도 진안군 동향면 능금리
2nd row전북특별자치도 진안군 성수면 좌포리
3rd row전북특별자치도 진안군 진안읍 가림리
4th row전북특별자치도 진안군 진안읍 가림리
5th row전북특별자치도 진안군 진안읍 연장리
ValueCountFrequency (%)
전북특별자치도 535
25.0%
진안군 535
25.0%
진안읍 155
 
7.2%
부귀면 89
 
4.2%
성수면 83
 
3.9%
동향면 58
 
2.7%
마령면 56
 
2.6%
백운면 51
 
2.4%
물곡리 33
 
1.5%
연장리 26
 
1.2%
Other values (67) 519
24.3%
2024-03-15T06:01:55.205541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1605
15.8%
안 706
 
6.9%
진 690
 
6.8%
군 544
 
5.4%
자 543
 
5.3%
전 541
 
5.3%
도 540
 
5.3%
치 535
 
5.3%
별 535
 
5.3%
특 535
 
5.3%
Other values (80) 3391
33.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8560
84.2%
Space Separator 1605
 
15.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 706
 
8.2%
진 690
 
8.1%
군 544
 
6.4%
자 543
 
6.3%
전 541
 
6.3%
도 540
 
6.3%
치 535
 
6.2%
별 535
 
6.2%
특 535
 
6.2%
북 535
 
6.2%
Other values (79) 2856
33.4%
Space Separator
ValueCountFrequency (%)
1605
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8560
84.2%
Common 1605
 
15.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 706
 
8.2%
진 690
 
8.1%
군 544
 
6.4%
자 543
 
6.3%
전 541
 
6.3%
도 540
 
6.3%
치 535
 
6.2%
별 535
 
6.2%
특 535
 
6.2%
북 535
 
6.2%
Other values (79) 2856
33.4%
Common
ValueCountFrequency (%)
1605
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8560
84.2%
ASCII 1605
 
15.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1605
100.0%
Hangul
ValueCountFrequency (%)
안 706
 
8.2%
진 690
 
8.1%
군 544
 
6.4%
자 543
 
6.3%
전 541
 
6.3%
도 540
 
6.3%
치 535
 
6.2%
별 535
 
6.2%
특 535
 
6.2%
북 535
 
6.2%
Other values (79) 2856
33.4%

사육두수
Real number (ℝ)

ZEROS 

Distinct146
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9309.7514
Minimum0
Maximum300000
Zeros42
Zeros (%)7.9%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-03-15T06:01:55.612062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median25
Q390
95-th percentile70000
Maximum300000
Range300000
Interquartile range (IQR)81

Descriptive statistics

Standard deviation28711.457
Coefficient of variation (CV)3.0840198
Kurtosis27.789883
Mean9309.7514
Median Absolute Deviation (MAD)21
Skewness4.4747417
Sum4980717
Variance8.2434779 × 108
MonotonicityNot monotonic
2024-03-15T06:01:56.049734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 42
 
7.9%
10 27
 
5.0%
30 20
 
3.7%
5 20
 
3.7%
4 17
 
3.2%
20 15
 
2.8%
12 15
 
2.8%
21 13
 
2.4%
50 12
 
2.2%
11 12
 
2.2%
Other values (136) 342
63.9%
ValueCountFrequency (%)
0 42
7.9%
2 9
 
1.7%
3 12
 
2.2%
4 17
3.2%
5 20
3.7%
6 10
 
1.9%
7 7
 
1.3%
8 7
 
1.3%
9 11
 
2.1%
10 27
5.0%
ValueCountFrequency (%)
300000 1
0.2%
200000 1
0.2%
160000 1
0.2%
140000 1
0.2%
135000 1
0.2%
130000 2
0.4%
125000 1
0.2%
110000 1
0.2%
105000 1
0.2%
100000 2
0.4%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-11-30
535 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-30
2nd row2023-11-30
3rd row2023-11-30
4th row2023-11-30
5th row2023-11-30

Common Values

ValueCountFrequency (%)
2023-11-30 535
100.0%

Length

2024-03-15T06:01:56.459216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:01:56.755112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-30 535
100.0%

Interactions

2024-03-15T06:01:48.715930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:01:48.105620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:01:49.053735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:01:48.397280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T06:01:56.937732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번주사육업종사업장소재지사육두수
순번1.0000.4630.4790.241
주사육업종0.4631.0000.6820.800
사업장소재지0.4790.6821.0000.000
사육두수0.2410.8000.0001.000
2024-03-15T06:01:57.127225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번사육두수주사육업종
순번1.000-0.2620.214
사육두수-0.2621.0000.492
주사육업종0.2140.4921.000

Missing values

2024-03-15T06:01:49.448781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T06:01:49.916321image/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

순번사업장명칭주사육업종사업장소재지사육두수데이터기준일자
01우식농장한우전북특별자치도 진안군 동향면 능금리1202023-11-30
12진현농장육계전북특별자치도 진안군 성수면 좌포리1000002023-11-30
23군식농장육계전북특별자치도 진안군 진안읍 가림리350002023-11-30
34가림농장돼지전북특별자치도 진안군 진안읍 가림리5002023-11-30
45슬기농장한우전북특별자치도 진안군 진안읍 연장리602023-11-30
56평지농장돼지전북특별자치도 진안군 마령면 평지리1502023-11-30
67경오농장한우전북특별자치도 진안군 진안읍 가림리652023-11-30
78세희농장돼지전북특별자치도 진안군 진안읍 구룡리8002023-11-30
89명수농장한우전북특별자치도 진안군 안천면 백화리402023-11-30
910현대축산돼지전북특별자치도 진안군 진안읍 구룡리10002023-11-30
순번사업장명칭주사육업종사업장소재지사육두수데이터기준일자
525526태홍농장한우전북특별자치도 진안군 진안읍 구룡리02023-11-30
526527운마한우전북특별자치도 진안군 부귀면 수항리02023-11-30
527528주원농장한우전북특별자치도 진안군 동향면 자산리02023-11-30
528529현정이네 농장염소전북특별자치도 진안군 진안읍 오천리02023-11-30
529530중리농장한우전북특별자치도 진안군 안천면 백화리02023-11-30
530531은구농장염소전북특별자치도 진안군 진안읍 운산리02023-11-30
531532제2 이화농장육우전북특별자치도 진안군 백운면 남계리02023-11-30
532533주용농장한우전북특별자치도 진안군 안천면 신괴리02023-11-30
533534안방농장2한우전북특별자치도 진안군 마령면 동촌리02023-11-30
534535상영농장한우전북특별자치도 진안군 진안읍 물곡리02023-11-30