Overview

Dataset statistics

Number of variables6
Number of observations1005
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows3
Duplicate rows (%)0.3%
Total size in memory50.2 KiB
Average record size in memory51.1 B

Variable types

Categorical1
Text1
Numeric3
DateTime1

Dataset

Description충청남도 청양군에 소재하는 한우, 젖소, 육우 사육 농장의 사육 농장구분, 소재지, 사육 두수 현황에 관한 데이터 입니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=397&beforeMenuCd=DOM_000000201001001000&publicdatapk=15042777

Alerts

데이터기준일 has constant value ""Constant
Dataset has 3 (0.3%) duplicate rowsDuplicates
젖소 is highly overall correlated with 육우High correlation
육우 is highly overall correlated with 젖소High correlation
농장구분 is highly imbalanced (89.4%)Imbalance
한우 has 18 (1.8%) zerosZeros
젖소 has 987 (98.2%) zerosZeros
육우 has 969 (96.4%) zerosZeros

Reproduction

Analysis started2024-01-09 22:21:39.744330
Analysis finished2024-01-09 22:21:40.754104
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

농장구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
개인
991 
법인
 
14

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개인
2nd row개인
3rd row개인
4th row개인
5th row개인

Common Values

ValueCountFrequency (%)
개인 991
98.6%
법인 14
 
1.4%

Length

2024-01-10T07:21:40.800149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:21:40.870205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 991
98.6%
법인 14
 
1.4%

소재지
Text

Distinct944
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2024-01-10T07:21:41.131966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length32
Mean length22.119403
Min length17

Characters and Unicode

Total characters22230
Distinct characters237
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

Unique888 ?
Unique (%)88.4%

Sample

1st row충청남도 청양군 남양면 구용길 506
2nd row충청남도 청양군 남양면 구룡리 267-1
3rd row충청남도 청양군 남양면 구용길 330-19
4th row충청남도 청양군 남양면 구용길 510-19
5th row충청남도 청양군 남양면 구룡리 53-3
ValueCountFrequency (%)
충청남도 1006
20.0%
청양군 1006
20.0%
장평면 150
 
3.0%
정산면 138
 
2.7%
비봉면 123
 
2.4%
청양읍 101
 
2.0%
운곡면 100
 
2.0%
남양면 94
 
1.9%
목면 90
 
1.8%
청남면 81
 
1.6%
Other values (1154) 2144
42.6%
2024-01-10T07:21:41.560552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4500
20.2%
청 2242
 
10.1%
양 1247
 
5.6%
남 1190
 
5.4%
충 1051
 
4.7%
도 1013
 
4.6%
군 1011
 
4.5%
면 910
 
4.1%
1 728
 
3.3%
- 649
 
2.9%
Other values (227) 7689
34.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13405
60.3%
Space Separator 4500
 
20.2%
Decimal Number 3670
 
16.5%
Dash Punctuation 649
 
2.9%
Close Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 2242
16.7%
양 1247
 
9.3%
남 1190
 
8.9%
충 1051
 
7.8%
도 1013
 
7.6%
군 1011
 
7.5%
면 910
 
6.8%
리 446
 
3.3%
길 422
 
3.1%
산 221
 
1.6%
Other values (213) 3652
27.2%
Decimal Number
ValueCountFrequency (%)
1 728
19.8%
2 501
13.7%
3 377
10.3%
4 368
10.0%
5 350
9.5%
6 307
8.4%
0 279
 
7.6%
7 275
 
7.5%
8 245
 
6.7%
9 240
 
6.5%
Space Separator
ValueCountFrequency (%)
4500
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 649
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13405
60.3%
Common 8825
39.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 2242
16.7%
양 1247
 
9.3%
남 1190
 
8.9%
충 1051
 
7.8%
도 1013
 
7.6%
군 1011
 
7.5%
면 910
 
6.8%
리 446
 
3.3%
길 422
 
3.1%
산 221
 
1.6%
Other values (213) 3652
27.2%
Common
ValueCountFrequency (%)
4500
51.0%
1 728
 
8.2%
- 649
 
7.4%
2 501
 
5.7%
3 377
 
4.3%
4 368
 
4.2%
5 350
 
4.0%
6 307
 
3.5%
0 279
 
3.2%
7 275
 
3.1%
Other values (4) 491
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13405
60.3%
ASCII 8825
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4500
51.0%
1 728
 
8.2%
- 649
 
7.4%
2 501
 
5.7%
3 377
 
4.3%
4 368
 
4.2%
5 350
 
4.0%
6 307
 
3.5%
0 279
 
3.2%
7 275
 
3.1%
Other values (4) 491
 
5.6%
Hangul
ValueCountFrequency (%)
청 2242
16.7%
양 1247
 
9.3%
남 1190
 
8.9%
충 1051
 
7.8%
도 1013
 
7.6%
군 1011
 
7.5%
면 910
 
6.8%
리 446
 
3.3%
길 422
 
3.1%
산 221
 
1.6%
Other values (213) 3652
27.2%

한우
Real number (ℝ)

ZEROS 

Distinct131
Distinct (%)13.0%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean26.297809
Minimum0
Maximum514
Zeros18
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size9.0 KiB
2024-01-10T07:21:41.676969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median10
Q330
95-th percentile103.85
Maximum514
Range514
Interquartile range (IQR)26

Descriptive statistics

Standard deviation43.788237
Coefficient of variation (CV)1.6650907
Kurtosis24.843893
Mean26.297809
Median Absolute Deviation (MAD)8
Skewness4.0637825
Sum26403
Variance1917.4097
MonotonicityNot monotonic
2024-01-10T07:21:41.782544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 80
 
8.0%
4 69
 
6.9%
3 68
 
6.8%
5 56
 
5.6%
1 43
 
4.3%
7 41
 
4.1%
6 39
 
3.9%
10 32
 
3.2%
8 30
 
3.0%
9 30
 
3.0%
Other values (121) 516
51.3%
ValueCountFrequency (%)
0 18
 
1.8%
1 43
4.3%
2 80
8.0%
3 68
6.8%
4 69
6.9%
5 56
5.6%
6 39
3.9%
7 41
4.1%
8 30
 
3.0%
9 30
 
3.0%
ValueCountFrequency (%)
514 1
0.1%
317 1
0.1%
300 1
0.1%
281 1
0.1%
278 1
0.1%
246 1
0.1%
241 1
0.1%
235 1
0.1%
231 1
0.1%
226 1
0.1%

젖소
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.57014925
Minimum0
Maximum169
Zeros987
Zeros (%)98.2%
Negative0
Negative (%)0.0%
Memory size9.0 KiB
2024-01-10T07:21:41.870386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum169
Range169
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.3172492
Coefficient of variation (CV)12.833919
Kurtosis339.79276
Mean0.57014925
Median Absolute Deviation (MAD)0
Skewness17.27496
Sum573
Variance53.542136
MonotonicityNot monotonic
2024-01-10T07:21:41.951638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 987
98.2%
1 3
 
0.3%
2 3
 
0.3%
6 2
 
0.2%
81 1
 
0.1%
40 1
 
0.1%
41 1
 
0.1%
62 1
 
0.1%
25 1
 
0.1%
169 1
 
0.1%
Other values (4) 4
 
0.4%
ValueCountFrequency (%)
0 987
98.2%
1 3
 
0.3%
2 3
 
0.3%
6 2
 
0.2%
8 1
 
0.1%
10 1
 
0.1%
12 1
 
0.1%
25 1
 
0.1%
40 1
 
0.1%
41 1
 
0.1%
ValueCountFrequency (%)
169 1
0.1%
104 1
0.1%
81 1
0.1%
62 1
0.1%
41 1
0.1%
40 1
0.1%
25 1
0.1%
12 1
0.1%
10 1
0.1%
8 1
0.1%

육우
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.78606965
Minimum0
Maximum117
Zeros969
Zeros (%)96.4%
Negative0
Negative (%)0.0%
Memory size9.0 KiB
2024-01-10T07:21:42.042727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum117
Range117
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.5843444
Coefficient of variation (CV)8.3762862
Kurtosis166.7439
Mean0.78606965
Median Absolute Deviation (MAD)0
Skewness12.03723
Sum790
Variance43.353591
MonotonicityNot monotonic
2024-01-10T07:21:42.135750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 969
96.4%
6 4
 
0.4%
2 2
 
0.2%
4 2
 
0.2%
8 2
 
0.2%
3 2
 
0.2%
1 2
 
0.2%
5 2
 
0.2%
12 1
 
0.1%
32 1
 
0.1%
Other values (18) 18
 
1.8%
ValueCountFrequency (%)
0 969
96.4%
1 2
 
0.2%
2 2
 
0.2%
3 2
 
0.2%
4 2
 
0.2%
5 2
 
0.2%
6 4
 
0.4%
7 1
 
0.1%
8 2
 
0.2%
9 1
 
0.1%
ValueCountFrequency (%)
117 1
0.1%
90 1
0.1%
75 1
0.1%
73 1
0.1%
48 1
0.1%
47 1
0.1%
43 1
0.1%
32 1
0.1%
29 1
0.1%
24 1
0.1%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
Minimum2020-05-31 00:00:00
Maximum2020-05-31 00:00:00
2024-01-10T07:21:42.222226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:21:42.289242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-10T07:21:40.402754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:21:39.971241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:21:40.178971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:21:40.477138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:21:40.037496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:21:40.251055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:21:40.554808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:21:40.110106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:21:40.325046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:21:42.342548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
농장구분한우젖소육우
농장구분1.0000.1490.2380.337
한우0.1491.0000.0000.000
젖소0.2380.0001.0000.306
육우0.3370.0000.3061.000
2024-01-10T07:21:42.429074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
한우젖소육우농장구분
한우1.000-0.126-0.1430.112
젖소-0.1261.0000.5420.254
육우-0.1430.5421.0000.253
농장구분0.1120.2540.2531.000

Missing values

2024-01-10T07:21:40.644688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:21:40.722187image/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

농장구분소재지한우젖소육우데이터기준일
0개인충청남도 청양군 남양면 구용길 5065002020-05-31
1개인충청남도 청양군 남양면 구룡리 267-17002020-05-31
2개인충청남도 청양군 남양면 구용길 330-193002020-05-31
3개인충청남도 청양군 남양면 구용길 510-192002020-05-31
4개인충청남도 청양군 남양면 구룡리 53-341002020-05-31
5개인충청남도 청양군 남양면 금천길 126-528002020-05-31
6개인충청남도 청양군 남양면 충절로 7457002020-05-31
7개인충청남도 청양군 남양면 대봉리 111-10042020-05-31
8개인충청남도 청양군 남양면 구용길 233-296002020-05-31
9개인충청남도 청양군 남양면 대봉리 212-94002020-05-31
농장구분소재지한우젖소육우데이터기준일
995개인충청남도 청양군 정산면 덕성리 686번지 7호49002020-05-31
996개인충청남도 청양군 정산면 해남리 639번지 1호11002020-05-31
997개인충청남도 청양군 청남면 동강리 676번지 5호60002020-05-31
998개인충청남도 청양군 청남면 상장리 667번지 4호60002020-05-31
999개인충청남도 청양군 청남면 상장리 8번지 상장리한우단지한우육50002020-05-31
1000개인충청남도 청양군 청남면 인양리 819번지 1호45002020-05-31
1001개인충청남도 청양군 청남면 지곡리 288번지 5호120002020-05-31
1002개인충청남도 청양군 청남면 지곡리 689번지 7호80002020-05-31
1003개인충청남도 청양군 청남면 청소리 658번지 3호100002020-05-31
1004개인충청남도 청양군 화성면 구재리 227번지 5호3002020-05-31

Duplicate rows

Most frequently occurring

농장구분소재지한우젖소육우데이터기준일# duplicates
0개인충청남도 청양군 운곡면 승주동길 8-54002020-05-312
1개인충청남도 청양군 장평면 분향이길 15-53002020-05-312
2개인충청남도 청양군 정산면 충신길 202002020-05-312