Overview

Dataset statistics

Number of variables7
Number of observations108
Missing cells22
Missing cells (%)2.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 KiB
Average record size in memory61.2 B

Variable types

Numeric4
Text2
Categorical1

Dataset

Description경기도 화성시의 양동농가 현황입니다. 사업장명, 축종, 소재지, 사육두수, 동수, 면적으로 구성되어있습니다.
Author경기도 화성시
URLhttps://www.data.go.kr/data/15127291/fileData.do

Alerts

축종 has constant value ""Constant
사육두수(두) is highly overall correlated with 면적(제곱미터)High correlation
동수(동) is highly overall correlated with 면적(제곱미터)High correlation
면적(제곱미터) is highly overall correlated with 사육두수(두) and 1 other fieldsHigh correlation
사육두수(두) has 22 (20.4%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-23 05:38:09.205764
Analysis finished2024-03-23 05:38:13.008354
Duration3.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.5
Minimum1
Maximum108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-23T14:38:13.140664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.35
Q127.75
median54.5
Q381.25
95-th percentile102.65
Maximum108
Range107
Interquartile range (IQR)53.5

Descriptive statistics

Standard deviation31.32092
Coefficient of variation (CV)0.57469577
Kurtosis-1.2
Mean54.5
Median Absolute Deviation (MAD)27
Skewness0
Sum5886
Variance981
MonotonicityStrictly increasing
2024-03-23T14:38:13.424314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
70 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
Other values (98) 98
90.7%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%
99 1
0.9%

사업장명
Text

Distinct107
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size996.0 B
2024-03-23T14:38:13.970747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length4
Mean length5.5
Min length3

Characters and Unicode

Total characters594
Distinct characters140
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)98.1%

Sample

1st row경기종축개량사업소
2nd row대건농장
3rd row대지농장
4th row은우농장
5th row논곡축산
ValueCountFrequency (%)
농업회사법인 9
 
7.0%
주식회사 6
 
4.7%
유한회사 3
 
2.3%
태돈영농조합법인 2
 
1.6%
우정축산 2
 
1.6%
윈더미어농장 1
 
0.8%
개미농장 1
 
0.8%
대림농장 1
 
0.8%
서영농장 1
 
0.8%
예성1농장 1
 
0.8%
Other values (101) 101
78.9%
2024-03-23T14:38:14.781988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 92
 
15.5%
장 81
 
13.6%
사 24
 
4.0%
회 22
 
3.7%
20
 
3.4%
산 20
 
3.4%
인 15
 
2.5%
법 13
 
2.2%
업 12
 
2.0%
축 11
 
1.9%
Other values (130) 284
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 552
92.9%
Space Separator 20
 
3.4%
Decimal Number 8
 
1.3%
Lowercase Letter 6
 
1.0%
Uppercase Letter 5
 
0.8%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 92
 
16.7%
장 81
 
14.7%
사 24
 
4.3%
회 22
 
4.0%
산 20
 
3.6%
인 15
 
2.7%
법 13
 
2.4%
업 12
 
2.2%
축 11
 
2.0%
성 10
 
1.8%
Other values (116) 252
45.7%
Lowercase Letter
ValueCountFrequency (%)
m 2
33.3%
r 1
16.7%
a 1
16.7%
s 1
16.7%
i 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
F 2
40.0%
G 2
40.0%
K 1
20.0%
Decimal Number
ValueCountFrequency (%)
2 5
62.5%
1 3
37.5%
Space Separator
ValueCountFrequency (%)
20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 552
92.9%
Common 31
 
5.2%
Latin 11
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 92
 
16.7%
장 81
 
14.7%
사 24
 
4.3%
회 22
 
4.0%
산 20
 
3.6%
인 15
 
2.7%
법 13
 
2.4%
업 12
 
2.2%
축 11
 
2.0%
성 10
 
1.8%
Other values (116) 252
45.7%
Latin
ValueCountFrequency (%)
m 2
18.2%
F 2
18.2%
G 2
18.2%
r 1
9.1%
a 1
9.1%
s 1
9.1%
i 1
9.1%
K 1
9.1%
Common
ValueCountFrequency (%)
20
64.5%
2 5
 
16.1%
1 3
 
9.7%
( 1
 
3.2%
) 1
 
3.2%
' 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 552
92.9%
ASCII 42
 
7.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 92
 
16.7%
장 81
 
14.7%
사 24
 
4.3%
회 22
 
4.0%
산 20
 
3.6%
인 15
 
2.7%
법 13
 
2.4%
업 12
 
2.2%
축 11
 
2.0%
성 10
 
1.8%
Other values (116) 252
45.7%
ASCII
ValueCountFrequency (%)
20
47.6%
2 5
 
11.9%
1 3
 
7.1%
m 2
 
4.8%
F 2
 
4.8%
G 2
 
4.8%
( 1
 
2.4%
) 1
 
2.4%
r 1
 
2.4%
a 1
 
2.4%
Other values (4) 4
 
9.5%

축종
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size996.0 B
돼지
108 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
돼지 108
100.0%

Length

2024-03-23T14:38:15.537206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T14:38:15.713727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
돼지 108
100.0%

소재지(지번)
Text

Distinct106
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size996.0 B
2024-03-23T14:38:16.181474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length16.064815
Min length13

Characters and Unicode

Total characters1735
Distinct characters85
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

Unique104 ?
Unique (%)96.3%

Sample

1st row화성시 팔탄면 창곡리 965
2nd row화성시 장안면 수촌리 1421
3rd row화성시 장안면 수촌리 985
4th row화성시 매송면 송라리 13-2
5th row화성시 매송면 송라리 783
ValueCountFrequency (%)
화성시 108
25.0%
장안면 39
 
9.0%
장안리 26
 
6.0%
양감면 12
 
2.8%
향남읍 9
 
2.1%
우정읍 9
 
2.1%
매송면 8
 
1.9%
마도면 8
 
1.9%
사창리 8
 
1.9%
정남면 8
 
1.9%
Other values (151) 197
45.6%
2024-03-23T14:38:17.143694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
326
18.8%
화 111
 
6.4%
시 108
 
6.2%
성 108
 
6.2%
리 108
 
6.2%
면 85
 
4.9%
1 83
 
4.8%
장 65
 
3.7%
안 65
 
3.7%
- 47
 
2.7%
Other values (75) 629
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 970
55.9%
Decimal Number 392
22.6%
Space Separator 326
 
18.8%
Dash Punctuation 47
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 111
11.4%
시 108
11.1%
성 108
11.1%
리 108
11.1%
면 85
 
8.8%
장 65
 
6.7%
안 65
 
6.7%
정 24
 
2.5%
읍 24
 
2.5%
남 24
 
2.5%
Other values (63) 248
25.6%
Decimal Number
ValueCountFrequency (%)
1 83
21.2%
7 45
11.5%
2 44
11.2%
6 37
9.4%
3 36
9.2%
9 35
8.9%
8 31
 
7.9%
5 28
 
7.1%
0 27
 
6.9%
4 26
 
6.6%
Space Separator
ValueCountFrequency (%)
326
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 970
55.9%
Common 765
44.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
화 111
11.4%
시 108
11.1%
성 108
11.1%
리 108
11.1%
면 85
 
8.8%
장 65
 
6.7%
안 65
 
6.7%
정 24
 
2.5%
읍 24
 
2.5%
남 24
 
2.5%
Other values (63) 248
25.6%
Common
ValueCountFrequency (%)
326
42.6%
1 83
 
10.8%
- 47
 
6.1%
7 45
 
5.9%
2 44
 
5.8%
6 37
 
4.8%
3 36
 
4.7%
9 35
 
4.6%
8 31
 
4.1%
5 28
 
3.7%
Other values (2) 53
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 970
55.9%
ASCII 765
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
326
42.6%
1 83
 
10.8%
- 47
 
6.1%
7 45
 
5.9%
2 44
 
5.8%
6 37
 
4.8%
3 36
 
4.7%
9 35
 
4.6%
8 31
 
4.1%
5 28
 
3.7%
Other values (2) 53
 
6.9%
Hangul
ValueCountFrequency (%)
화 111
11.4%
시 108
11.1%
성 108
11.1%
리 108
11.1%
면 85
 
8.8%
장 65
 
6.7%
안 65
 
6.7%
정 24
 
2.5%
읍 24
 
2.5%
남 24
 
2.5%
Other values (63) 248
25.6%

사육두수(두)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct76
Distinct (%)88.4%
Missing22
Missing (%)20.4%
Infinite0
Infinite (%)0.0%
Mean1384.9651
Minimum1
Maximum7719
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-23T14:38:17.541457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q1121.25
median882
Q31981.5
95-th percentile4212
Maximum7719
Range7718
Interquartile range (IQR)1860.25

Descriptive statistics

Standard deviation1581.678
Coefficient of variation (CV)1.1420346
Kurtosis2.9760349
Mean1384.9651
Median Absolute Deviation (MAD)833
Skewness1.6410169
Sum119107
Variance2501705.4
MonotonicityNot monotonic
2024-03-23T14:38:17.825432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1593 2
 
1.9%
14 2
 
1.9%
15 2
 
1.9%
5615 2
 
1.9%
1 2
 
1.9%
2 2
 
1.9%
832 2
 
1.9%
4 2
 
1.9%
4197 2
 
1.9%
1349 2
 
1.9%
Other values (66) 66
61.1%
(Missing) 22
 
20.4%
ValueCountFrequency (%)
1 2
1.9%
2 2
1.9%
4 2
1.9%
5 1
0.9%
13 1
0.9%
14 2
1.9%
15 2
1.9%
18 1
0.9%
21 1
0.9%
22 1
0.9%
ValueCountFrequency (%)
7719 1
0.9%
5731 1
0.9%
5615 2
1.9%
4217 1
0.9%
4197 2
1.9%
4151 1
0.9%
3643 1
0.9%
3245 1
0.9%
2928 1
0.9%
2891 1
0.9%

동수(동)
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5833333
Minimum1
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-23T14:38:18.047111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q38
95-th percentile10.65
Maximum15
Range14
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.0143737
Coefficient of variation (CV)0.53988782
Kurtosis-0.24509836
Mean5.5833333
Median Absolute Deviation (MAD)2
Skewness0.48675415
Sum603
Variance9.0864486
MonotonicityNot monotonic
2024-03-23T14:38:18.245883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
3 15
13.9%
6 13
12.0%
7 12
11.1%
9 12
11.1%
4 12
11.1%
2 11
10.2%
5 10
9.3%
1 7
6.5%
8 6
 
5.6%
10 4
 
3.7%
Other values (3) 6
 
5.6%
ValueCountFrequency (%)
1 7
6.5%
2 11
10.2%
3 15
13.9%
4 12
11.1%
5 10
9.3%
6 13
12.0%
7 12
11.1%
8 6
 
5.6%
9 12
11.1%
10 4
 
3.7%
ValueCountFrequency (%)
15 1
 
0.9%
12 3
 
2.8%
11 2
 
1.9%
10 4
 
3.7%
9 12
11.1%
8 6
5.6%
7 12
11.1%
6 13
12.0%
5 10
9.3%
4 12
11.1%

면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2455.8629
Minimum221.24
Maximum12337.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-23T14:38:18.506690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum221.24
5-th percentile454.01
Q11118.3
median2050.055
Q33035.885
95-th percentile6331.938
Maximum12337.5
Range12116.26
Interquartile range (IQR)1917.585

Descriptive statistics

Standard deviation2064.8767
Coefficient of variation (CV)0.84079479
Kurtosis7.3472633
Mean2455.8629
Median Absolute Deviation (MAD)968.445
Skewness2.3589532
Sum265233.19
Variance4263715.8
MonotonicityNot monotonic
2024-03-23T14:38:18.746425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2217.6 4
 
3.7%
3364.2 3
 
2.8%
2281.19 2
 
1.9%
2772.0 2
 
1.9%
3326.4 2
 
1.9%
2317.98 2
 
1.9%
960.0 2
 
1.9%
2287.84 2
 
1.9%
2159.94 1
 
0.9%
872.9 1
 
0.9%
Other values (87) 87
80.6%
ValueCountFrequency (%)
221.24 1
0.9%
281.4 1
0.9%
342.0 1
0.9%
353.85 1
0.9%
387.0 1
0.9%
446.8 1
0.9%
467.4 1
0.9%
539.25 1
0.9%
628.15 1
0.9%
649.8 1
0.9%
ValueCountFrequency (%)
12337.5 1
0.9%
11213.589 1
0.9%
9044.95 1
0.9%
6985.1 1
0.9%
6688.0 1
0.9%
6455.04 1
0.9%
6103.32 1
0.9%
5719.1 1
0.9%
5551.8 1
0.9%
5382.0 1
0.9%

Interactions

2024-03-23T14:38:11.837014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:38:09.631073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:38:10.411759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:38:11.255134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:38:11.983509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:38:09.801344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:38:10.693385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:38:11.399514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:38:12.232806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:38:10.021500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:38:10.952650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:38:11.555072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:38:12.430069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:38:10.223952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:38:11.110466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:38:11.702806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T14:38:18.928733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사육두수(두)동수(동)면적(제곱미터)
연번1.0000.0000.3240.362
사육두수(두)0.0001.0000.2930.803
동수(동)0.3240.2931.0000.659
면적(제곱미터)0.3620.8030.6591.000
2024-03-23T14:38:19.071753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사육두수(두)동수(동)면적(제곱미터)
연번1.0000.072-0.1000.259
사육두수(두)0.0721.0000.2890.534
동수(동)-0.1000.2891.0000.669
면적(제곱미터)0.2590.5340.6691.000

Missing values

2024-03-23T14:38:12.712130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T14:38:12.935510image/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

연번사업장명축종소재지(지번)사육두수(두)동수(동)면적(제곱미터)
01경기종축개량사업소돼지화성시 팔탄면 창곡리 9656871406.68
12대건농장돼지화성시 장안면 수촌리 1421159311455.0
23대지농장돼지화성시 장안면 수촌리 985<NA>3716.0
34은우농장돼지화성시 매송면 송라리 13-2<NA>91602.0
45논곡축산돼지화성시 매송면 송라리 783<NA>1660.0
56대화농장돼지화성시 마도면 고모리 149-11891525.97
67경희축산돼지화성시 마도면 백곡리 740-1554921.04
78광명농장돼지화성시 남양읍 무송리 58014102443.0
89남산농장돼지화성시 송산면 마산리 399-2<NA>93465.0
910개성농장돼지화성시 팔탄면 고주리 3132261760.78
연번사업장명축종소재지(지번)사육두수(두)동수(동)면적(제곱미터)
9899씨와이농장돼지화성시 장안면 장안리 2706561535293.44
99100킴스팜(Kim's Farm)돼지화성시 장안면 장안리 1990<NA>72287.84
100101초록농장돼지화성시 양감면 사창리 777-18156272868.0
101102케이비제네틱스유한회사농업회사법인돼지화성시 장안면 장안리 1738-1832411213.589
102103농업회사법인 구성 주식회사돼지화성시 장안면 장안리 2019768712337.5
103104태산농장 농업회사법인 유한회사돼지화성시 장안면 덕다리 718241953.08
104105농업회사법인 주식회사 오투돼지화성시 장안면 장안리 1954484419.36
105106농업회사법인 주식회사 리앤팜돼지화성시 장안면 장안리 2344<NA>46455.04
106107농업회사법인천연농장 주식회사돼지화성시 장안면 장안리 2697561526688.0
107108산골농장2돼지화성시 비봉면 쌍학리 812461221.24