Overview

Dataset statistics

Number of variables5
Number of observations176
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.5 KiB
Average record size in memory43.8 B

Variable types

Numeric3
Categorical1
Text1

Dataset

Description국가가축방역통합시스템(KAHIS)에서 추출한 `21.10.13.기준 태백시 전체 축산농가 현황으로 농장 리스트, 사육 두수, 농장 위경도를 제공합니다.
Author강원도 태백시
URLhttps://www.data.go.kr/data/15092090/fileData.do

Alerts

순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:50:05.136720
Analysis finished2023-12-12 06:50:06.796884
Duration1.66 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct176
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88.5
Minimum1
Maximum176
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T15:50:06.861881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.75
Q144.75
median88.5
Q3132.25
95-th percentile167.25
Maximum176
Range175
Interquartile range (IQR)87.5

Descriptive statistics

Standard deviation50.950957
Coefficient of variation (CV)0.57571703
Kurtosis-1.2
Mean88.5
Median Absolute Deviation (MAD)44
Skewness0
Sum15576
Variance2596
MonotonicityStrictly increasing
2023-12-12T15:50:06.993392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
90 1
 
0.6%
114 1
 
0.6%
115 1
 
0.6%
116 1
 
0.6%
117 1
 
0.6%
118 1
 
0.6%
119 1
 
0.6%
120 1
 
0.6%
121 1
 
0.6%
Other values (166) 166
94.3%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
176 1
0.6%
175 1
0.6%
174 1
0.6%
173 1
0.6%
172 1
0.6%
171 1
0.6%
170 1
0.6%
169 1
0.6%
168 1
0.6%
167 1
0.6%

축종-품종
Categorical

Distinct12
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
닭-토종닭
82 
소-한우
61 
염소
12 
벌-개량종
 
4
사슴-엘크
 
3
Other values (7)
14 

Length

Max length6
Median length5
Mean length4.4488636
Min length2

Unique

Unique2 ?
Unique (%)1.1%

Sample

1st row소-한우
2nd row소-한우
3rd row소-한우
4th row소-한우
5th row소-한우

Common Values

ValueCountFrequency (%)
닭-토종닭 82
46.6%
소-한우 61
34.7%
염소 12
 
6.8%
벌-개량종 4
 
2.3%
사슴-엘크 3
 
1.7%
사슴-꽃사슴 3
 
1.7%
벌-재래종 3
 
1.7%
돼지-일반 2
 
1.1%
산양 2
 
1.1%
벌-이탈리안 2
 
1.1%
Other values (2) 2
 
1.1%

Length

2023-12-12T15:50:07.134686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
닭-토종닭 82
46.6%
소-한우 61
34.7%
염소 12
 
6.8%
벌-개량종 4
 
2.3%
사슴-엘크 3
 
1.7%
사슴-꽃사슴 3
 
1.7%
벌-재래종 3
 
1.7%
돼지-일반 2
 
1.1%
산양 2
 
1.1%
벌-이탈리안 2
 
1.1%
Other values (2) 2
 
1.1%

사육두수
Text

Distinct63
Distinct (%)35.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T15:50:07.326400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length1.7329545
Min length1

Characters and Unicode

Total characters305
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

Unique35 ?
Unique (%)19.9%

Sample

1st row20
2nd row16
3rd row43
4th row2
5th row14
ValueCountFrequency (%)
3 16
 
9.1%
5 12
 
6.8%
10 9
 
5.1%
12 8
 
4.5%
6 8
 
4.5%
7 7
 
4.0%
2 7
 
4.0%
15 7
 
4.0%
30 7
 
4.0%
4 6
 
3.4%
Other values (53) 89
50.6%
2023-12-12T15:50:07.638468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 53
17.4%
0 49
16.1%
3 44
14.4%
5 38
12.5%
2 32
10.5%
4 23
7.5%
6 19
 
6.2%
7 16
 
5.2%
8 16
 
5.2%
9 14
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 304
99.7%
Other Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 53
17.4%
0 49
16.1%
3 44
14.5%
5 38
12.5%
2 32
10.5%
4 23
7.6%
6 19
 
6.2%
7 16
 
5.3%
8 16
 
5.3%
9 14
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 305
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 53
17.4%
0 49
16.1%
3 44
14.4%
5 38
12.5%
2 32
10.5%
4 23
7.5%
6 19
 
6.2%
7 16
 
5.2%
8 16
 
5.2%
9 14
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 305
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 53
17.4%
0 49
16.1%
3 44
14.4%
5 38
12.5%
2 32
10.5%
4 23
7.5%
6 19
 
6.2%
7 16
 
5.2%
8 16
 
5.2%
9 14
 
4.6%

위도
Real number (ℝ)

Distinct134
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.190892
Minimum37.08715
Maximum37.335516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T15:50:07.769250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.08715
5-th percentile37.098817
Q137.123914
median37.176975
Q337.260521
95-th percentile37.316033
Maximum37.335516
Range0.248366
Interquartile range (IQR)0.1366065

Descriptive statistics

Standard deviation0.074234941
Coefficient of variation (CV)0.0019960516
Kurtosis-1.2640485
Mean37.190892
Median Absolute Deviation (MAD)0.0652455
Skewness0.30822474
Sum6545.597
Variance0.0055108265
MonotonicityNot monotonic
2023-12-12T15:50:07.906628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.326594 3
 
1.7%
37.166463 3
 
1.7%
37.12865 3
 
1.7%
37.313572 2
 
1.1%
37.11903 2
 
1.1%
37.227219 2
 
1.1%
37.253775 2
 
1.1%
37.272461 2
 
1.1%
37.201986 2
 
1.1%
37.119886 2
 
1.1%
Other values (124) 153
86.9%
ValueCountFrequency (%)
37.08715 2
1.1%
37.087511 1
0.6%
37.090091 1
0.6%
37.090933 1
0.6%
37.092905 1
0.6%
37.094305 1
0.6%
37.098263 2
1.1%
37.099002 1
0.6%
37.099363 2
1.1%
37.099466 1
0.6%
ValueCountFrequency (%)
37.335516 1
 
0.6%
37.326594 3
1.7%
37.325127 2
1.1%
37.324994 1
 
0.6%
37.323525 1
 
0.6%
37.3209 1
 
0.6%
37.314411 1
 
0.6%
37.313572 2
1.1%
37.303594 1
 
0.6%
37.302869 1
 
0.6%

경도
Real number (ℝ)

Distinct134
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.99462
Minimum128.90678
Maximum129.06131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T15:50:08.039829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.90678
5-th percentile128.92305
Q1128.97588
median128.99409
Q3129.01552
95-th percentile129.05265
Maximum129.06131
Range0.154533
Interquartile range (IQR)0.0396365

Descriptive statistics

Standard deviation0.033167553
Coefficient of variation (CV)0.00025712353
Kurtosis0.063445275
Mean128.99462
Median Absolute Deviation (MAD)0.0201405
Skewness-0.14451763
Sum22703.053
Variance0.0011000865
MonotonicityNot monotonic
2023-12-12T15:50:08.191165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.968811 3
 
1.7%
128.977675 3
 
1.7%
129.035219 3
 
1.7%
128.977833 2
 
1.1%
128.920463 2
 
1.1%
128.994094 2
 
1.1%
128.995938 2
 
1.1%
128.990305 2
 
1.1%
128.964841 2
 
1.1%
129.060961 2
 
1.1%
Other values (124) 153
86.9%
ValueCountFrequency (%)
128.906775 1
0.6%
128.918597 2
1.1%
128.918791 1
0.6%
128.920463 2
1.1%
128.921155 2
1.1%
128.921197 1
0.6%
128.923672 1
0.6%
128.946147 1
0.6%
128.946597 1
0.6%
128.947288 1
0.6%
ValueCountFrequency (%)
129.061308 2
1.1%
129.060961 2
1.1%
129.056972 1
0.6%
129.056833 1
0.6%
129.053177 2
1.1%
129.052652 2
1.1%
129.049566 1
0.6%
129.048475 1
0.6%
129.048005 1
0.6%
129.047894 1
0.6%

Interactions

2023-12-12T15:50:06.316781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:50:05.388784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:50:06.024626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:50:06.432059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:50:05.493450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:50:06.141099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:50:06.519339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:50:05.599266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:50:06.218137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:50:08.286261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번축종-품종사육두수위도경도
순번1.0000.7790.4930.6040.585
축종-품종0.7791.0000.9350.4070.330
사육두수0.4930.9351.0000.4220.000
위도0.6040.4070.4221.0000.752
경도0.5850.3300.0000.7521.000
2023-12-12T15:50:08.376762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번위도경도축종-품종
순번1.000-0.2740.0390.467
위도-0.2741.000-0.4740.181
경도0.039-0.4741.0000.143
축종-품종0.4670.1810.1431.000

Missing values

2023-12-12T15:50:06.661617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:50:06.763793image/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

순번축종-품종사육두수위도경도
01소-한우2037.287769128.991436
12소-한우1637.290488128.994075
23소-한우4337.289225128.992827
34소-한우237.265677128.994172
45소-한우1437.099363129.015769
56소-한우1537.300577128.950775
67소-한우2737.176002129.015016
78소-한우537.13173128.999305
89소-한우4337.128727128.98938
910소-한우1437.270613128.991827
순번축종-품종사육두수위도경도
166167사슴-꽃사슴237.201986128.964841
167168벌-재래종937.325127128.967933
168169벌-개량종10537.313572128.977833
169170벌-재래종1537.100413129.053177
170171벌-개량종1237.166463128.977675
171172벌-이탈리안3337.300677128.967788
172173벌-개량종3537.166494128.974313
173174벌-이탈리안12037.213069128.986238
174175벌-재래종2037.303594128.976175
175176벌-개량종5037.202513128.979541