Overview

Dataset statistics

Number of variables8
Number of observations40
Missing cells15
Missing cells (%)4.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory70.3 B

Variable types

Text3
Categorical2
Numeric3

Dataset

Description강원도 강릉시 소재 가금류 농장현황으로 사업자명칭, 등록축종, 사업장소재지, 사육두수, 동수, 면적, 데이터기준일 등을 제공합니다.
Author강원도 강릉시
URLhttps://www.data.go.kr/data/15092263/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
사육두수 is highly overall correlated with 동수(계) and 1 other fieldsHigh correlation
동수(계) is highly overall correlated with 사육두수 and 1 other fieldsHigh correlation
면적(계) is highly overall correlated with 사육두수 and 1 other fieldsHigh correlation
사업장소재지(도로명) has 14 (35.0%) missing valuesMissing
사육두수 has 1 (2.5%) missing valuesMissing
사업장명칭 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:34:44.464674
Analysis finished2023-12-12 20:34:46.742928
Duration2.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명칭
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-13T05:34:46.958580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length4.75
Min length3

Characters and Unicode

Total characters190
Distinct characters92
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

Unique40 ?
Unique (%)100.0%

Sample

1st row모솔양계
2nd row싱싱축산
3rd row박병수
4th row김병기
5th row행복농장
ValueCountFrequency (%)
모솔양계 1
 
2.1%
싱싱축산 1
 
2.1%
옥계혜운농장 1
 
2.1%
옥계쌍둥이동물농장 1
 
2.1%
박영선 1
 
2.1%
정재규 1
 
2.1%
함창식 1
 
2.1%
황현기 1
 
2.1%
솔봉농장 1
 
2.1%
오솔길 1
 
2.1%
Other values (38) 38
79.2%
2023-12-13T05:34:47.396834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 23
 
12.1%
장 18
 
9.5%
8
 
4.2%
계 7
 
3.7%
김 6
 
3.2%
이 5
 
2.6%
옥 4
 
2.1%
솔 3
 
1.6%
성 3
 
1.6%
봉 3
 
1.6%
Other values (82) 110
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 180
94.7%
Space Separator 8
 
4.2%
Open Punctuation 1
 
0.5%
Close Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 23
 
12.8%
장 18
 
10.0%
계 7
 
3.9%
김 6
 
3.3%
이 5
 
2.8%
옥 4
 
2.2%
솔 3
 
1.7%
성 3
 
1.7%
봉 3
 
1.7%
태 3
 
1.7%
Other values (79) 105
58.3%
Space Separator
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 180
94.7%
Common 10
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 23
 
12.8%
장 18
 
10.0%
계 7
 
3.9%
김 6
 
3.3%
이 5
 
2.8%
옥 4
 
2.2%
솔 3
 
1.7%
성 3
 
1.7%
봉 3
 
1.7%
태 3
 
1.7%
Other values (79) 105
58.3%
Common
ValueCountFrequency (%)
8
80.0%
( 1
 
10.0%
) 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 180
94.7%
ASCII 10
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 23
 
12.8%
장 18
 
10.0%
계 7
 
3.9%
김 6
 
3.3%
이 5
 
2.8%
옥 4
 
2.2%
솔 3
 
1.7%
성 3
 
1.7%
봉 3
 
1.7%
태 3
 
1.7%
Other values (79) 105
58.3%
ASCII
ValueCountFrequency (%)
8
80.0%
( 1
 
10.0%
) 1
 
10.0%

등록축종
Categorical

Distinct10
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
육계
19 
종계/산란계
12 
오리
2 
돼지, 육계
 
1
육계, 사슴, 칠면조, 꿩
 
1
Other values (5)
5 

Length

Max length19
Median length2
Mean length4.5
Min length2

Unique

Unique7 ?
Unique (%)17.5%

Sample

1st row종계/산란계
2nd row종계/산란계
3rd row종계/산란계
4th row종계/산란계
5th row종계/산란계

Common Values

ValueCountFrequency (%)
육계 19
47.5%
종계/산란계 12
30.0%
오리 2
 
5.0%
돼지, 육계 1
 
2.5%
육계, 사슴, 칠면조, 꿩 1
 
2.5%
<NA> 1
 
2.5%
육계, 오리, 기러기 1
 
2.5%
육계, 사슴 1
 
2.5%
종계/산란계, 육계, 칠면조, 거위 1
 
2.5%
육계, 오리 1
 
2.5%

Length

2023-12-13T05:34:47.609872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:34:47.778194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
육계 25
49.0%
종계/산란계 13
25.5%
오리 4
 
7.8%
사슴 2
 
3.9%
칠면조 2
 
3.9%
돼지 1
 
2.0%
꿩 1
 
2.0%
na 1
 
2.0%
기러기 1
 
2.0%
거위 1
 
2.0%

사업장소재지(지번)
Text

Distinct35
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-13T05:34:48.076967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length27
Mean length21.825
Min length4

Characters and Unicode

Total characters873
Distinct characters72
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

Unique34 ?
Unique (%)85.0%

Sample

1st row강원도 강릉시 지변동 372번지 1호
2nd row강원도 강릉시 강동면 산성우리 322번지 3호 외 3필지(산성우리 322외 1필지, 산성우리 325)
3rd row강원도 강릉시 강동면 임곡리 21번지
4th row강원도 강릉시 주문진읍 교항리 698번지 1호
5th row강원도 강릉시 성산면 송암리 386번지
ValueCountFrequency (%)
강원도 34
18.3%
강릉시 34
18.3%
강동면 8
 
4.3%
산성우리 5
 
2.7%
주문진읍 5
 
2.7%
구정면 4
 
2.2%
1호 4
 
2.2%
3호 3
 
1.6%
교항리 3
 
1.6%
성산면 3
 
1.6%
Other values (74) 83
44.6%
2023-12-13T05:34:48.576850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
243
27.8%
강 76
 
8.7%
지 37
 
4.2%
시 35
 
4.0%
번 34
 
3.9%
원 34
 
3.9%
도 34
 
3.9%
릉 34
 
3.9%
리 30
 
3.4%
1 23
 
2.6%
Other values (62) 293
33.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 500
57.3%
Space Separator 243
27.8%
Decimal Number 127
 
14.5%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
강 76
15.2%
지 37
 
7.4%
시 35
 
7.0%
번 34
 
6.8%
원 34
 
6.8%
도 34
 
6.8%
릉 34
 
6.8%
리 30
 
6.0%
면 23
 
4.6%
동 18
 
3.6%
Other values (48) 145
29.0%
Decimal Number
ValueCountFrequency (%)
1 23
18.1%
2 19
15.0%
3 18
14.2%
6 12
9.4%
8 11
8.7%
4 10
7.9%
7 10
7.9%
9 9
 
7.1%
5 8
 
6.3%
0 7
 
5.5%
Space Separator
ValueCountFrequency (%)
243
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 500
57.3%
Common 373
42.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
강 76
15.2%
지 37
 
7.4%
시 35
 
7.0%
번 34
 
6.8%
원 34
 
6.8%
도 34
 
6.8%
릉 34
 
6.8%
리 30
 
6.0%
면 23
 
4.6%
동 18
 
3.6%
Other values (48) 145
29.0%
Common
ValueCountFrequency (%)
243
65.1%
1 23
 
6.2%
2 19
 
5.1%
3 18
 
4.8%
6 12
 
3.2%
8 11
 
2.9%
4 10
 
2.7%
7 10
 
2.7%
9 9
 
2.4%
5 8
 
2.1%
Other values (4) 10
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 500
57.3%
ASCII 373
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
243
65.1%
1 23
 
6.2%
2 19
 
5.1%
3 18
 
4.8%
6 12
 
3.2%
8 11
 
2.9%
4 10
 
2.7%
7 10
 
2.7%
9 9
 
2.4%
5 8
 
2.1%
Other values (4) 10
 
2.7%
Hangul
ValueCountFrequency (%)
강 76
15.2%
지 37
 
7.4%
시 35
 
7.0%
번 34
 
6.8%
원 34
 
6.8%
도 34
 
6.8%
릉 34
 
6.8%
리 30
 
6.0%
면 23
 
4.6%
동 18
 
3.6%
Other values (48) 145
29.0%

사업장소재지(도로명)
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing14
Missing (%)35.0%
Memory size452.0 B
2023-12-13T05:34:48.870164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length21.384615
Min length17

Characters and Unicode

Total characters556
Distinct characters78
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

Unique26 ?
Unique (%)100.0%

Sample

1st row강원도 강릉시 지변길 155 (지변동)
2nd row강원도 강릉시 강동면 율곡로 707-72
3rd row강원도 강릉시 강동면 임곡로 529-21
4th row강원도 강릉시 성산면 지암길 139-7
5th row강원도 강릉시 강릉대로469번길 60-5 (포남동)
ValueCountFrequency (%)
강원도 26
20.0%
강릉시 26
20.0%
강동면 6
 
4.6%
옥계면 5
 
3.8%
성산면 4
 
3.1%
구정면 4
 
3.1%
율곡로 3
 
2.3%
헌화로 2
 
1.5%
유천동 1
 
0.8%
37 1
 
0.8%
Other values (52) 52
40.0%
2023-12-13T05:34:49.250288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
104
18.7%
강 59
 
10.6%
릉 27
 
4.9%
시 26
 
4.7%
원 26
 
4.7%
도 26
 
4.7%
면 20
 
3.6%
2 19
 
3.4%
길 19
 
3.4%
5 15
 
2.7%
Other values (68) 215
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 330
59.4%
Space Separator 104
 
18.7%
Decimal Number 98
 
17.6%
Dash Punctuation 14
 
2.5%
Close Punctuation 5
 
0.9%
Open Punctuation 5
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
강 59
17.9%
릉 27
 
8.2%
시 26
 
7.9%
원 26
 
7.9%
도 26
 
7.9%
면 20
 
6.1%
길 19
 
5.8%
동 12
 
3.6%
로 11
 
3.3%
성 6
 
1.8%
Other values (54) 98
29.7%
Decimal Number
ValueCountFrequency (%)
2 19
19.4%
5 15
15.3%
1 12
12.2%
3 11
11.2%
7 9
9.2%
9 8
8.2%
8 8
8.2%
4 7
 
7.1%
0 5
 
5.1%
6 4
 
4.1%
Space Separator
ValueCountFrequency (%)
104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 330
59.4%
Common 226
40.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
강 59
17.9%
릉 27
 
8.2%
시 26
 
7.9%
원 26
 
7.9%
도 26
 
7.9%
면 20
 
6.1%
길 19
 
5.8%
동 12
 
3.6%
로 11
 
3.3%
성 6
 
1.8%
Other values (54) 98
29.7%
Common
ValueCountFrequency (%)
104
46.0%
2 19
 
8.4%
5 15
 
6.6%
- 14
 
6.2%
1 12
 
5.3%
3 11
 
4.9%
7 9
 
4.0%
9 8
 
3.5%
8 8
 
3.5%
4 7
 
3.1%
Other values (4) 19
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 330
59.4%
ASCII 226
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
104
46.0%
2 19
 
8.4%
5 15
 
6.6%
- 14
 
6.2%
1 12
 
5.3%
3 11
 
4.9%
7 9
 
4.0%
9 8
 
3.5%
8 8
 
3.5%
4 7
 
3.1%
Other values (4) 19
 
8.4%
Hangul
ValueCountFrequency (%)
강 59
17.9%
릉 27
 
8.2%
시 26
 
7.9%
원 26
 
7.9%
도 26
 
7.9%
면 20
 
6.1%
길 19
 
5.8%
동 12
 
3.6%
로 11
 
3.3%
성 6
 
1.8%
Other values (54) 98
29.7%

사육두수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct27
Distinct (%)69.2%
Missing1
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean5572.2051
Minimum13
Maximum50000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-13T05:34:49.374772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile21.3
Q145
median258
Q31000
95-th percentile31773.2
Maximum50000
Range49987
Interquartile range (IQR)955

Descriptive statistics

Standard deviation13025.361
Coefficient of variation (CV)2.3375594
Kurtosis5.4733777
Mean5572.2051
Median Absolute Deviation (MAD)242
Skewness2.5362041
Sum217316
Variance1.6966002 × 108
MonotonicityNot monotonic
2023-12-13T05:34:49.516061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
30 4
 
10.0%
1000 4
 
10.0%
30000 3
 
7.5%
800 3
 
7.5%
100 2
 
5.0%
500 2
 
5.0%
11900 1
 
2.5%
35 1
 
2.5%
258 1
 
2.5%
13 1
 
2.5%
Other values (17) 17
42.5%
ValueCountFrequency (%)
13 1
 
2.5%
15 1
 
2.5%
22 1
 
2.5%
25 1
 
2.5%
30 4
10.0%
35 1
 
2.5%
40 1
 
2.5%
50 1
 
2.5%
52 1
 
2.5%
60 1
 
2.5%
ValueCountFrequency (%)
50000 1
 
2.5%
47732 1
 
2.5%
30000 3
7.5%
11900 1
 
2.5%
5010 1
 
2.5%
2000 1
 
2.5%
1500 1
 
2.5%
1000 4
10.0%
800 3
7.5%
500 2
5.0%

동수(계)
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.075
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-13T05:34:49.653911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile5.05
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4568582
Coefficient of variation (CV)0.70210035
Kurtosis0.96726587
Mean2.075
Median Absolute Deviation (MAD)0
Skewness1.3299255
Sum83
Variance2.1224359
MonotonicityNot monotonic
2023-12-13T05:34:49.763793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 21
52.5%
2 7
 
17.5%
3 5
 
12.5%
4 4
 
10.0%
6 2
 
5.0%
5 1
 
2.5%
ValueCountFrequency (%)
1 21
52.5%
2 7
 
17.5%
3 5
 
12.5%
4 4
 
10.0%
5 1
 
2.5%
6 2
 
5.0%
ValueCountFrequency (%)
6 2
 
5.0%
5 1
 
2.5%
4 4
 
10.0%
3 5
 
12.5%
2 7
 
17.5%
1 21
52.5%

면적(계)
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean419.9
Minimum13
Maximum3171
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-13T05:34:49.901098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile14.95
Q132.25
median145
Q3383.5
95-th percentile1899.3
Maximum3171
Range3158
Interquartile range (IQR)351.25

Descriptive statistics

Standard deviation696.33165
Coefficient of variation (CV)1.6583273
Kurtosis6.3712401
Mean419.9
Median Absolute Deviation (MAD)115
Skewness2.48259
Sum16796
Variance484877.76
MonotonicityNot monotonic
2023-12-13T05:34:50.047585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
30.0 4
 
10.0%
48.0 2
 
5.0%
49.0 2
 
5.0%
18.0 1
 
2.5%
378.0 1
 
2.5%
35.0 1
 
2.5%
16.5 1
 
2.5%
120.0 1
 
2.5%
400.0 1
 
2.5%
198.0 1
 
2.5%
Other values (25) 25
62.5%
ValueCountFrequency (%)
13.0 1
 
2.5%
14.0 1
 
2.5%
15.0 1
 
2.5%
16.5 1
 
2.5%
18.0 1
 
2.5%
25.0 1
 
2.5%
30.0 4
10.0%
33.0 1
 
2.5%
35.0 1
 
2.5%
36.0 1
 
2.5%
ValueCountFrequency (%)
3171.0 1
2.5%
2228.0 1
2.5%
1882.0 1
2.5%
1652.0 1
2.5%
1029.0 1
2.5%
984.0 1
2.5%
792.0 1
2.5%
790.0 1
2.5%
765.0 1
2.5%
400.0 1
2.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2022-11-11
40 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-11-11
2nd row2022-11-11
3rd row2022-11-11
4th row2022-11-11
5th row2022-11-11

Common Values

ValueCountFrequency (%)
2022-11-11 40
100.0%

Length

2023-12-13T05:34:50.191128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:34:50.295768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-11-11 40
100.0%

Interactions

2023-12-13T05:34:45.541843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:34:44.864751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:34:45.231863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:34:45.660272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:34:44.980890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:34:45.340492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:34:45.774281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:34:45.096437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:34:45.436519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:34:50.375227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명칭등록축종사업장소재지(지번)사업장소재지(도로명)사육두수동수(계)면적(계)
사업장명칭1.0001.0001.0001.0001.0001.0001.000
등록축종1.0001.0000.8591.0000.0000.2850.000
사업장소재지(지번)1.0000.8591.0001.0001.0001.0001.000
사업장소재지(도로명)1.0001.0001.0001.0001.0001.0001.000
사육두수1.0000.0001.0001.0001.0000.4770.873
동수(계)1.0000.2851.0001.0000.4771.0000.673
면적(계)1.0000.0001.0001.0000.8730.6731.000
2023-12-13T05:34:50.501337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사육두수동수(계)면적(계)등록축종
사육두수1.0000.5990.8840.000
동수(계)0.5991.0000.7340.115
면적(계)0.8840.7341.0000.000
등록축종0.0000.1150.0001.000

Missing values

2023-12-13T05:34:46.299102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:34:46.486375image/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.
2023-12-13T05:34:46.658470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

사업장명칭등록축종사업장소재지(지번)사업장소재지(도로명)사육두수동수(계)면적(계)데이터기준일자
0모솔양계종계/산란계강원도 강릉시 지변동 372번지 1호강원도 강릉시 지변길 155 (지변동)119001765.02022-11-11
1싱싱축산종계/산란계강원도 강릉시 강동면 산성우리 322번지 3호 외 3필지(산성우리 322외 1필지, 산성우리 325)강원도 강릉시 강동면 율곡로 707-724773233171.02022-11-11
2박병수종계/산란계강원도 강릉시 강동면 임곡리 21번지강원도 강릉시 강동면 임곡로 529-213000031029.02022-11-11
3김병기종계/산란계강원도 강릉시 주문진읍 교항리 698번지 1호<NA>1502170.02022-11-11
4행복농장종계/산란계강원도 강릉시 성산면 송암리 386번지강원도 강릉시 성산면 지암길 139-720002338.02022-11-11
5나래농원종계/산란계강원도 강릉시 사천면 노동리 164번지<NA>8001188.02022-11-11
6전인기종계/산란계강원도 강릉시 포남동 367번지강원도 강릉시 강릉대로469번길 60-5 (포남동)300448.02022-11-11
7청계농장종계/산란계강원도 강릉시 연곡면 퇴곡리 22번지 6호<NA>100136.02022-11-11
8자연같이 팜종계/산란계강원도 강릉시 강동면 산성우리 266번지 7호<NA>15003984.02022-11-11
9동녁골농장종계/산란계강원도 강릉시 연곡면 신왕리 114번지 1호<NA>50114.02022-11-11
사업장명칭등록축종사업장소재지(지번)사업장소재지(도로명)사육두수동수(계)면적(계)데이터기준일자
30용복농장육계강원도 강릉시 성산면 장안길 3325130.02022-11-11
31성산농장육계강원도 강릉시 성산면 송두길 29-10100149.02022-11-11
32손태익육계, 오리, 기러기강원도 강릉시 강동면 상시동리 382번지 2호강원도 강릉시 강동면 율곡로 2359-552146.02022-11-11
33김태집육계강원도 강릉시 옥계면 천남길 134-2240130.02022-11-11
34김학태육계, 사슴강원도 강릉시 옥계면 현내뒷길 15422130.02022-11-11
35김영식육계강원도 강릉시 옥계면 헌화로 97-2513113.02022-11-11
36부흥농장종계/산란계, 육계, 칠면조, 거위강원도 강릉시 구정면 학산리 886번지 3호강원도 강릉시 구정면 구정중앙로 158-51258148.02022-11-11
37계림농장오리강원도 강릉시 강동면 정동진리 51번지 23호강원도 강릉시 강동면 헌화로 90310005218.02022-11-11
38주경화오리강원도 강릉시 사천면 석교리 795번지<NA>35133.02022-11-11
39소담뜰 유황오리농장육계, 오리강원도 강릉시 주문진읍 교항리 1049번지<NA>5002197.42022-11-11