Overview

Dataset statistics

Number of variables9
Number of observations1924
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory141.0 KiB
Average record size in memory75.1 B

Variable types

Text1
Categorical4
DateTime1
Numeric3

Dataset

Description상주시 가축사육업 현황에 대한 데이터로 주사육업종, 소재지, 등록일자, 영업상태구분, 사육두수, 동수, 면적에 대한 자료를 제공합니다.
Author경상북도 상주시
URLhttps://www.data.go.kr/data/15075569/fileData.do

Alerts

영업상태구분 has constant value ""Constant
데이터기준일 has constant value ""Constant
Dataset has 1 (0.1%) duplicate rowsDuplicates
사육두수 is highly overall correlated with 면적(제곱미터)High correlation
동수 is highly overall correlated with 면적(제곱미터)High correlation
면적(제곱미터) is highly overall correlated with 사육두수 and 1 other fieldsHigh correlation
주사육업종 is highly imbalanced (72.7%)Imbalance
사육두수 has 50 (2.6%) zerosZeros

Reproduction

Analysis started2023-12-12 16:33:58.593936
Analysis finished2023-12-12 16:34:00.423018
Duration1.83 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명칭
Text

Distinct270
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
2023-12-13T01:34:00.561763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length4
Mean length4.3622661
Min length2

Characters and Unicode

Total characters8393
Distinct characters182
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique197 ?
Unique (%)10.2%

Sample

1st row○○개목장
2nd row○○대마목장
3rd row○○농장
4th row○○농장
5th row○○농장
ValueCountFrequency (%)
○○농장 1216
60.7%
○○목장 146
 
7.3%
○○축산 91
 
4.5%
농장 39
 
1.9%
○○농원 29
 
1.4%
○○골농장 18
 
0.9%
○○산농장 14
 
0.7%
○○ 13
 
0.6%
○○한우농장 11
 
0.5%
○○장 10
 
0.5%
Other values (262) 416
 
20.8%
2023-12-13T01:34:01.011530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
○ 3847
45.8%
장 1745
20.8%
농 1601
19.1%
목 184
 
2.2%
산 126
 
1.5%
축 112
 
1.3%
79
 
0.9%
원 43
 
0.5%
2 34
 
0.4%
우 30
 
0.4%
Other values (172) 592
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4398
52.4%
Other Symbol 3847
45.8%
Space Separator 79
 
0.9%
Decimal Number 47
 
0.6%
Close Punctuation 8
 
0.1%
Open Punctuation 8
 
0.1%
Uppercase Letter 4
 
< 0.1%
Lowercase Letter 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 1745
39.7%
농 1601
36.4%
목 184
 
4.2%
산 126
 
2.9%
축 112
 
2.5%
원 43
 
1.0%
우 30
 
0.7%
한 28
 
0.6%
사 28
 
0.6%
골 27
 
0.6%
Other values (161) 474
 
10.8%
Decimal Number
ValueCountFrequency (%)
2 34
72.3%
1 10
 
21.3%
3 3
 
6.4%
Uppercase Letter
ValueCountFrequency (%)
B 3
75.0%
Y 1
 
25.0%
Other Symbol
ValueCountFrequency (%)
○ 3847
100.0%
Space Separator
ValueCountFrequency (%)
79
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4398
52.4%
Common 3990
47.5%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 1745
39.7%
농 1601
36.4%
목 184
 
4.2%
산 126
 
2.9%
축 112
 
2.5%
원 43
 
1.0%
우 30
 
0.7%
한 28
 
0.6%
사 28
 
0.6%
골 27
 
0.6%
Other values (161) 474
 
10.8%
Common
ValueCountFrequency (%)
○ 3847
96.4%
79
 
2.0%
2 34
 
0.9%
1 10
 
0.3%
) 8
 
0.2%
( 8
 
0.2%
3 3
 
0.1%
- 1
 
< 0.1%
Latin
ValueCountFrequency (%)
B 3
60.0%
n 1
 
20.0%
Y 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4398
52.4%
Geometric Shapes 3847
45.8%
ASCII 148
 
1.8%

Most frequent character per block

Geometric Shapes
ValueCountFrequency (%)
○ 3847
100.0%
Hangul
ValueCountFrequency (%)
장 1745
39.7%
농 1601
36.4%
목 184
 
4.2%
산 126
 
2.9%
축 112
 
2.5%
원 43
 
1.0%
우 30
 
0.7%
한 28
 
0.6%
사 28
 
0.6%
골 27
 
0.6%
Other values (161) 474
 
10.8%
ASCII
ValueCountFrequency (%)
79
53.4%
2 34
23.0%
1 10
 
6.8%
) 8
 
5.4%
( 8
 
5.4%
B 3
 
2.0%
3 3
 
2.0%
n 1
 
0.7%
- 1
 
0.7%
Y 1
 
0.7%

주사육업종
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
한우
1641 
육계
 
89
돼지
 
57
젖소
 
54
육우
 
43
Other values (7)
 
40

Length

Max length6
Median length2
Mean length2.0389813
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
한우 1641
85.3%
육계 89
 
4.6%
돼지 57
 
3.0%
젖소 54
 
2.8%
육우 43
 
2.2%
종계/산란계 18
 
0.9%
산양 8
 
0.4%
염소 8
 
0.4%
메추리 2
 
0.1%
사슴 2
 
0.1%
Other values (2) 2
 
0.1%

Length

2023-12-13T01:34:01.163538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한우 1641
85.3%
육계 89
 
4.6%
돼지 57
 
3.0%
젖소 54
 
2.8%
육우 43
 
2.2%
종계/산란계 18
 
0.9%
산양 8
 
0.4%
염소 8
 
0.4%
메추리 2
 
0.1%
사슴 2
 
0.1%
Other values (2) 2
 
0.1%

소재지
Categorical

Distinct24
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
공성면
324 
낙동면
298 
사벌국면
161 
청리면
120 
함창읍
110 
Other values (19)
911 

Length

Max length4
Median length3
Mean length3.0836798
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row화남면
2nd row화남면
3rd row외서면
4th row낙동면
5th row동문동

Common Values

ValueCountFrequency (%)
공성면 324
16.8%
낙동면 298
15.5%
사벌국면 161
 
8.4%
청리면 120
 
6.2%
함창읍 110
 
5.7%
중동면 108
 
5.6%
신흥동 80
 
4.2%
외서면 79
 
4.1%
공검면 74
 
3.8%
내서면 69
 
3.6%
Other values (14) 501
26.0%

Length

2023-12-13T01:34:01.298309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공성면 324
16.8%
낙동면 298
15.5%
사벌국면 161
 
8.4%
청리면 120
 
6.2%
함창읍 110
 
5.7%
중동면 108
 
5.6%
신흥동 80
 
4.2%
외서면 79
 
4.1%
공검면 74
 
3.8%
내서면 69
 
3.6%
Other values (14) 501
26.0%

등록일자
Date

Distinct701
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
Minimum2004-08-09 00:00:00
Maximum2020-12-21 00:00:00
2023-12-13T01:34:01.494149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:01.686247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
정상
1924 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상 1924
100.0%

Length

2023-12-13T01:34:01.832515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:34:01.937503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 1924
100.0%

사육두수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct244
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2780.2204
Minimum0
Maximum280000
Zeros50
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size17.0 KiB
2023-12-13T01:34:02.061949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q114
median30
Q370
95-th percentile7550
Maximum280000
Range280000
Interquartile range (IQR)56

Descriptive statistics

Standard deviation14663.572
Coefficient of variation (CV)5.274248
Kurtosis119.89184
Mean2780.2204
Median Absolute Deviation (MAD)20
Skewness9.0306241
Sum5349144
Variance2.1502034 × 108
MonotonicityNot monotonic
2023-12-13T01:34:02.221691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 106
 
5.5%
20 92
 
4.8%
50 82
 
4.3%
30 72
 
3.7%
40 68
 
3.5%
15 66
 
3.4%
0 50
 
2.6%
100 40
 
2.1%
25 39
 
2.0%
16 38
 
2.0%
Other values (234) 1271
66.1%
ValueCountFrequency (%)
0 50
2.6%
1 3
 
0.2%
2 19
 
1.0%
3 28
1.5%
4 37
1.9%
5 30
1.6%
6 29
1.5%
7 33
1.7%
8 24
1.2%
9 34
1.8%
ValueCountFrequency (%)
280000 1
0.1%
240000 1
0.1%
150000 1
0.1%
130000 1
0.1%
120000 1
0.1%
110000 1
0.1%
96000 1
0.1%
85000 1
0.1%
84000 1
0.1%
83600 1
0.1%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2286902
Minimum0
Maximum22
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size17.0 KiB
2023-12-13T01:34:02.362545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile5
Maximum22
Range22
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.719754
Coefficient of variation (CV)0.77164337
Kurtosis19.800058
Mean2.2286902
Median Absolute Deviation (MAD)1
Skewness3.3118381
Sum4288
Variance2.957554
MonotonicityNot monotonic
2023-12-13T01:34:02.492248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1 772
40.1%
2 624
32.4%
3 228
 
11.9%
4 161
 
8.4%
5 53
 
2.8%
6 34
 
1.8%
7 17
 
0.9%
8 11
 
0.6%
9 9
 
0.5%
12 3
 
0.2%
Other values (8) 12
 
0.6%
ValueCountFrequency (%)
0 1
 
0.1%
1 772
40.1%
2 624
32.4%
3 228
 
11.9%
4 161
 
8.4%
5 53
 
2.8%
6 34
 
1.8%
7 17
 
0.9%
8 11
 
0.6%
9 9
 
0.5%
ValueCountFrequency (%)
22 1
 
0.1%
17 1
 
0.1%
15 1
 
0.1%
14 2
 
0.1%
13 1
 
0.1%
12 3
 
0.2%
11 2
 
0.1%
10 3
 
0.2%
9 9
0.5%
8 11
0.6%

면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct993
Distinct (%)51.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean786.39764
Minimum0
Maximum8390
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size17.0 KiB
2023-12-13T01:34:02.618473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile84.6395
Q1307.875
median500
Q3891.5
95-th percentile2469.55
Maximum8390
Range8390
Interquartile range (IQR)583.625

Descriptive statistics

Standard deviation862.69254
Coefficient of variation (CV)1.0970182
Kurtosis14.7005
Mean786.39764
Median Absolute Deviation (MAD)295
Skewness3.1171474
Sum1513029.1
Variance744238.42
MonotonicityNot monotonic
2023-12-13T01:34:02.751066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
350.0 89
 
4.6%
400.0 77
 
4.0%
800.0 66
 
3.4%
700.0 47
 
2.4%
300.0 32
 
1.7%
200.0 31
 
1.6%
500.0 27
 
1.4%
150.0 26
 
1.4%
600.0 21
 
1.1%
250.0 20
 
1.0%
Other values (983) 1488
77.3%
ValueCountFrequency (%)
0.0 1
0.1%
12.9 1
0.1%
14.4 1
0.1%
15.0 1
0.1%
16.33 1
0.1%
16.64 1
0.1%
19.14 1
0.1%
19.36 1
0.1%
20.3 1
0.1%
21.08 1
0.1%
ValueCountFrequency (%)
8390.0 1
0.1%
7942.06 1
0.1%
7600.0 1
0.1%
6704.44 1
0.1%
6675.0 1
0.1%
6350.0 1
0.1%
6157.9 1
0.1%
6042.85 1
0.1%
5661.6 1
0.1%
5083.5 1
0.1%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
2020-12-29
1924 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-29
2nd row2020-12-29
3rd row2020-12-29
4th row2020-12-29
5th row2020-12-29

Common Values

ValueCountFrequency (%)
2020-12-29 1924
100.0%

Length

2023-12-13T01:34:02.916305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:34:03.040459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-29 1924
100.0%

Interactions

2023-12-13T01:33:59.850358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:33:59.314118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:33:59.573403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:33:59.952732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:33:59.401399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:33:59.679808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:00.060318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:33:59.485864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:33:59.758287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:34:03.143902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주사육업종소재지사육두수동수면적(제곱미터)
주사육업종1.0000.3720.7630.1630.454
소재지0.3721.0000.0620.0000.088
사육두수0.7630.0621.0000.1310.608
동수0.1630.0000.1311.0000.841
면적(제곱미터)0.4540.0880.6080.8411.000
2023-12-13T01:34:03.258111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주사육업종소재지
주사육업종1.0000.116
소재지0.1161.000
2023-12-13T01:34:03.360994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사육두수동수면적(제곱미터)주사육업종소재지
사육두수1.0000.4990.6870.4490.022
동수0.4991.0000.6880.0650.003
면적(제곱미터)0.6870.6881.0000.2120.033
주사육업종0.4490.0650.2121.0000.116
소재지0.0220.0030.0330.1161.000

Missing values

2023-12-13T01:34:00.200126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:34:00.366154image/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

사업장명칭주사육업종소재지등록일자영업상태구분사육두수동수면적(제곱미터)데이터기준일
0○○개목장젖소화남면2004-08-09정상855873.462020-12-29
1○○대마목장한우화남면2004-08-09정상222567.02020-12-29
2○○농장육계외서면2004-08-09정상7000043508.22020-12-29
3○○농장육계낙동면2004-08-16정상4500022470.02020-12-29
4○○농장육계동문동2004-08-20정상7140033285.02020-12-29
5○○축산육계낙동면2004-08-20정상7000043584.02020-12-29
6○○농장종계/산란계북문동2004-09-06정상2000081198.82020-12-29
7○○농장육계신흥동2004-09-13정상3000021680.02020-12-29
8○○농장육계신흥동2004-09-13정상3000021836.02020-12-29
9○○농장육계신흥동2004-09-13정상30000141704.12020-12-29
사업장명칭주사육업종소재지등록일자영업상태구분사육두수동수면적(제곱미터)데이터기준일
1914○○골농장한우공성면2020-11-19정상03750.02020-12-29
1915○○골농장한우공성면2020-11-20정상02550.02020-12-29
1916○○농장한우외서면2020-11-26정상01243.02020-12-29
1917○○농장한우낙동면2020-11-26정상381600.02020-12-29
1918○농장한우공성면2020-11-26정상42575.02020-12-29
1919○○농장한우낙동면2020-11-30정상011600.02020-12-29
1920○○농장한우공성면2020-12-15정상1433000.02020-12-29
1921○○농장한우공성면2020-12-15정상641800.02020-12-29
1922○○농장한우계림동2020-12-15정상511300.02020-12-29
1923○○농장한우이안면2020-12-21정상2141.62020-12-29

Duplicate rows

Most frequently occurring

사업장명칭주사육업종소재지등록일자영업상태구분사육두수동수면적(제곱미터)데이터기준일# duplicates
0○○농장한우공검면2014-03-03정상4541053.02020-12-292