Overview

Dataset statistics

Number of variables7
Number of observations317
Missing cells85
Missing cells (%)3.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.1 KiB
Average record size in memory58.4 B

Variable types

Numeric2
Text4
DateTime1

Dataset

Description경상남도 사료제조업체 현황에 대한 데이터로, 제조업체명, 사료구분(배합, 단미, 보조 등), 생산사료명, 생산능력(톤), 영업상태에 대한 정보를 제공합니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15016374

Alerts

전화번호 has 83 (26.2%) missing valuesMissing
번호 has unique valuesUnique
생산능력(톤) has 140 (44.2%) zerosZeros

Reproduction

Analysis started2023-12-10 23:54:03.842536
Analysis finished2023-12-10 23:54:04.966360
Duration1.12 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct317
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean159
Minimum1
Maximum317
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T08:54:05.068400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16.8
Q180
median159
Q3238
95-th percentile301.2
Maximum317
Range316
Interquartile range (IQR)158

Descriptive statistics

Standard deviation91.654242
Coefficient of variation (CV)0.57644177
Kurtosis-1.2
Mean159
Median Absolute Deviation (MAD)79
Skewness0
Sum50403
Variance8400.5
MonotonicityStrictly increasing
2023-12-11T08:54:05.212266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
210 1
 
0.3%
217 1
 
0.3%
216 1
 
0.3%
215 1
 
0.3%
214 1
 
0.3%
213 1
 
0.3%
212 1
 
0.3%
211 1
 
0.3%
209 1
 
0.3%
Other values (307) 307
96.8%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
317 1
0.3%
316 1
0.3%
315 1
0.3%
314 1
0.3%
313 1
0.3%
312 1
0.3%
311 1
0.3%
310 1
0.3%
309 1
0.3%
308 1
0.3%

사업장명
Text

Distinct238
Distinct (%)75.1%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T08:54:05.472176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length8.0252366
Min length2

Characters and Unicode

Total characters2544
Distinct characters281
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

Unique182 ?
Unique (%)57.4%

Sample

1st row아이엠팜주식회사
2nd row대성물산
3rd row(주)한국바이오케미칼
4th row바이오허브
5th row참살이영농조합법인
ValueCountFrequency (%)
주식회사 17
 
4.5%
주)동우티엠씨 5
 
1.3%
주)씨티씨바이오 5
 
1.3%
주)코리아에프앤에프 5
 
1.3%
주)에이치에스아쿠아피드 4
 
1.0%
에스제이바이오 4
 
1.0%
아쿠아엘씨생명과학 4
 
1.0%
주)세농 4
 
1.0%
이랑사(2with4 3
 
0.8%
농업회사법인 3
 
0.8%
Other values (262) 327
85.8%
2023-12-11T08:54:05.896741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 173
 
6.8%
( 162
 
6.4%
) 162
 
6.4%
이 78
 
3.1%
사 70
 
2.8%
64
 
2.5%
아 55
 
2.2%
산 50
 
2.0%
에 49
 
1.9%
농 42
 
1.7%
Other values (271) 1639
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2087
82.0%
Open Punctuation 162
 
6.4%
Close Punctuation 162
 
6.4%
Space Separator 64
 
2.5%
Uppercase Letter 43
 
1.7%
Lowercase Letter 17
 
0.7%
Decimal Number 6
 
0.2%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 173
 
8.3%
이 78
 
3.7%
사 70
 
3.4%
아 55
 
2.6%
산 50
 
2.4%
에 49
 
2.3%
농 42
 
2.0%
오 40
 
1.9%
업 37
 
1.8%
한 32
 
1.5%
Other values (241) 1461
70.0%
Uppercase Letter
ValueCountFrequency (%)
M 7
16.3%
P 5
11.6%
T 5
11.6%
A 3
7.0%
O 3
7.0%
L 3
7.0%
S 3
7.0%
R 3
7.0%
J 2
 
4.7%
B 2
 
4.7%
Other values (7) 7
16.3%
Lowercase Letter
ValueCountFrequency (%)
h 4
23.5%
i 4
23.5%
t 3
17.6%
w 3
17.6%
c 1
 
5.9%
e 1
 
5.9%
o 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
4 3
50.0%
Open Punctuation
ValueCountFrequency (%)
( 162
100.0%
Close Punctuation
ValueCountFrequency (%)
) 162
100.0%
Space Separator
ValueCountFrequency (%)
64
100.0%
Other Punctuation
ValueCountFrequency (%)
& 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2087
82.0%
Common 397
 
15.6%
Latin 60
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 173
 
8.3%
이 78
 
3.7%
사 70
 
3.4%
아 55
 
2.6%
산 50
 
2.4%
에 49
 
2.3%
농 42
 
2.0%
오 40
 
1.9%
업 37
 
1.8%
한 32
 
1.5%
Other values (241) 1461
70.0%
Latin
ValueCountFrequency (%)
M 7
 
11.7%
P 5
 
8.3%
T 5
 
8.3%
h 4
 
6.7%
i 4
 
6.7%
t 3
 
5.0%
A 3
 
5.0%
w 3
 
5.0%
O 3
 
5.0%
L 3
 
5.0%
Other values (14) 20
33.3%
Common
ValueCountFrequency (%)
( 162
40.8%
) 162
40.8%
64
 
16.1%
2 3
 
0.8%
4 3
 
0.8%
& 3
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2087
82.0%
ASCII 457
 
18.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 173
 
8.3%
이 78
 
3.7%
사 70
 
3.4%
아 55
 
2.6%
산 50
 
2.4%
에 49
 
2.3%
농 42
 
2.0%
오 40
 
1.9%
업 37
 
1.8%
한 32
 
1.5%
Other values (241) 1461
70.0%
ASCII
ValueCountFrequency (%)
( 162
35.4%
) 162
35.4%
64
 
14.0%
M 7
 
1.5%
P 5
 
1.1%
T 5
 
1.1%
h 4
 
0.9%
i 4
 
0.9%
2 3
 
0.7%
4 3
 
0.7%
Other values (20) 38
 
8.3%

소재지
Text

Distinct241
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T08:54:06.214595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length39
Mean length24.51735
Min length16

Characters and Unicode

Total characters7772
Distinct characters217
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique190 ?
Unique (%)59.9%

Sample

1st row경상남도 진주시 문산읍 삼곡리 1033번지 바이오21센터 벤304호
2nd row경상남도 진주시 문산읍 동부로 853
3rd row경상남도 진주시 문산읍 월아산로950번길 14-20
4th row경상남도 진주시 정촌면 무선산로 285
5th row경상남도 진주시 대곡면 유곡로 275-53
ValueCountFrequency (%)
경상남도 317
 
19.1%
김해시 73
 
4.4%
양산시 36
 
2.2%
창원시 34
 
2.1%
진주시 27
 
1.6%
사천시 24
 
1.4%
밀양시 21
 
1.3%
통영시 19
 
1.1%
함안군 17
 
1.0%
한림면 15
 
0.9%
Other values (596) 1074
64.8%
2023-12-11T08:54:06.786764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1357
 
17.5%
남 356
 
4.6%
상 353
 
4.5%
경 328
 
4.2%
도 323
 
4.2%
1 314
 
4.0%
시 240
 
3.1%
로 207
 
2.7%
2 196
 
2.5%
길 171
 
2.2%
Other values (207) 3927
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4694
60.4%
Decimal Number 1369
 
17.6%
Space Separator 1357
 
17.5%
Dash Punctuation 120
 
1.5%
Close Punctuation 96
 
1.2%
Open Punctuation 96
 
1.2%
Other Punctuation 38
 
0.5%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 356
 
7.6%
상 353
 
7.5%
경 328
 
7.0%
도 323
 
6.9%
시 240
 
5.1%
로 207
 
4.4%
길 171
 
3.6%
동 170
 
3.6%
면 159
 
3.4%
산 143
 
3.0%
Other values (190) 2244
47.8%
Decimal Number
ValueCountFrequency (%)
1 314
22.9%
2 196
14.3%
5 136
9.9%
3 131
9.6%
4 124
 
9.1%
0 109
 
8.0%
8 99
 
7.2%
9 99
 
7.2%
7 84
 
6.1%
6 77
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 37
97.4%
· 1
 
2.6%
Space Separator
ValueCountFrequency (%)
1357
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%
Close Punctuation
ValueCountFrequency (%)
) 96
100.0%
Open Punctuation
ValueCountFrequency (%)
( 96
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4694
60.4%
Common 3076
39.6%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 356
 
7.6%
상 353
 
7.5%
경 328
 
7.0%
도 323
 
6.9%
시 240
 
5.1%
로 207
 
4.4%
길 171
 
3.6%
동 170
 
3.6%
면 159
 
3.4%
산 143
 
3.0%
Other values (190) 2244
47.8%
Common
ValueCountFrequency (%)
1357
44.1%
1 314
 
10.2%
2 196
 
6.4%
5 136
 
4.4%
3 131
 
4.3%
4 124
 
4.0%
- 120
 
3.9%
0 109
 
3.5%
8 99
 
3.2%
9 99
 
3.2%
Other values (6) 391
 
12.7%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4694
60.4%
ASCII 3077
39.6%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1357
44.1%
1 314
 
10.2%
2 196
 
6.4%
5 136
 
4.4%
3 131
 
4.3%
4 124
 
4.0%
- 120
 
3.9%
0 109
 
3.5%
8 99
 
3.2%
9 99
 
3.2%
Other values (6) 392
 
12.7%
Hangul
ValueCountFrequency (%)
남 356
 
7.6%
상 353
 
7.5%
경 328
 
7.0%
도 323
 
6.9%
시 240
 
5.1%
로 207
 
4.4%
길 171
 
3.6%
동 170
 
3.6%
면 159
 
3.4%
산 143
 
3.0%
Other values (190) 2244
47.8%
None
ValueCountFrequency (%)
· 1
100.0%

생산사료명
Text

Distinct174
Distinct (%)55.2%
Missing2
Missing (%)0.6%
Memory size2.6 KiB
2023-12-11T08:54:07.010327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length13.168254
Min length2

Characters and Unicode

Total characters4148
Distinct characters184
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique134 ?
Unique (%)42.5%

Sample

1st row보조사료 / 생균제
2nd row양어용배합사료
3rd row보조사료/생균제
4th row보조사료/규산염제
5th row보조사료/미생물제(생균제)
ValueCountFrequency (%)
배합사료 28
 
6.4%
보조사료/생균제 24
 
5.5%
수입사료 17
 
3.9%
반추동물용 14
 
3.2%
섬유질 13
 
3.0%
양축용 12
 
2.7%
10
 
2.3%
단미사료/혼합성-혼합제 7
 
1.6%
단미사료/동물성/무기물류(패분 7
 
1.6%
보조사료/규산염제 6
 
1.4%
Other values (193) 301
68.6%
2023-12-11T08:54:07.409502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 334
 
8.1%
사 325
 
7.8%
료 324
 
7.8%
물 218
 
5.3%
단 190
 
4.6%
미 165
 
4.0%
류 147
 
3.5%
성 146
 
3.5%
124
 
3.0%
합 115
 
2.8%
Other values (174) 2060
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3416
82.4%
Other Punctuation 369
 
8.9%
Space Separator 124
 
3.0%
Close Punctuation 90
 
2.2%
Open Punctuation 90
 
2.2%
Dash Punctuation 48
 
1.2%
Connector Punctuation 4
 
0.1%
Uppercase Letter 4
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 325
 
9.5%
료 324
 
9.5%
물 218
 
6.4%
단 190
 
5.6%
미 165
 
4.8%
류 147
 
4.3%
성 146
 
4.3%
합 115
 
3.4%
제 99
 
2.9%
질 99
 
2.9%
Other values (159) 1588
46.5%
Other Punctuation
ValueCountFrequency (%)
/ 334
90.5%
, 23
 
6.2%
· 10
 
2.7%
. 2
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
R 1
25.0%
M 1
25.0%
T 1
25.0%
Space Separator
ValueCountFrequency (%)
124
100.0%
Close Punctuation
ValueCountFrequency (%)
) 90
100.0%
Open Punctuation
ValueCountFrequency (%)
( 90
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
p 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3416
82.4%
Common 727
 
17.5%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 325
 
9.5%
료 324
 
9.5%
물 218
 
6.4%
단 190
 
5.6%
미 165
 
4.8%
류 147
 
4.3%
성 146
 
4.3%
합 115
 
3.4%
제 99
 
2.9%
질 99
 
2.9%
Other values (159) 1588
46.5%
Common
ValueCountFrequency (%)
/ 334
45.9%
124
 
17.1%
) 90
 
12.4%
( 90
 
12.4%
- 48
 
6.6%
, 23
 
3.2%
· 10
 
1.4%
_ 4
 
0.6%
. 2
 
0.3%
+ 2
 
0.3%
Latin
ValueCountFrequency (%)
C 1
20.0%
p 1
20.0%
R 1
20.0%
M 1
20.0%
T 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3416
82.4%
ASCII 722
 
17.4%
None 10
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 334
46.3%
124
 
17.2%
) 90
 
12.5%
( 90
 
12.5%
- 48
 
6.6%
, 23
 
3.2%
_ 4
 
0.6%
. 2
 
0.3%
+ 2
 
0.3%
C 1
 
0.1%
Other values (4) 4
 
0.6%
Hangul
ValueCountFrequency (%)
사 325
 
9.5%
료 324
 
9.5%
물 218
 
6.4%
단 190
 
5.6%
미 165
 
4.8%
류 147
 
4.3%
성 146
 
4.3%
합 115
 
3.4%
제 99
 
2.9%
질 99
 
2.9%
Other values (159) 1588
46.5%
None
ValueCountFrequency (%)
· 10
100.0%

생산능력(톤)
Real number (ℝ)

ZEROS 

Distinct42
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.223975
Minimum0
Maximum668
Zeros140
Zeros (%)44.2%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T08:54:07.586732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q310
95-th percentile100
Maximum668
Range668
Interquartile range (IQR)10

Descriptive statistics

Standard deviation63.633471
Coefficient of variation (CV)3.1464374
Kurtosis41.217132
Mean20.223975
Median Absolute Deviation (MAD)1
Skewness5.6466782
Sum6411
Variance4049.2187
MonotonicityNot monotonic
2023-12-11T08:54:07.769217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 140
44.2%
2 28
 
8.8%
1 22
 
6.9%
10 21
 
6.6%
5 14
 
4.4%
20 10
 
3.2%
3 10
 
3.2%
8 9
 
2.8%
50 8
 
2.5%
4 5
 
1.6%
Other values (32) 50
 
15.8%
ValueCountFrequency (%)
0 140
44.2%
1 22
 
6.9%
2 28
 
8.8%
3 10
 
3.2%
4 5
 
1.6%
5 14
 
4.4%
6 4
 
1.3%
7 1
 
0.3%
8 9
 
2.8%
9 3
 
0.9%
ValueCountFrequency (%)
668 1
 
0.3%
330 1
 
0.3%
300 4
1.3%
290 1
 
0.3%
256 1
 
0.3%
250 1
 
0.3%
230 1
 
0.3%
200 1
 
0.3%
160 1
 
0.3%
125 1
 
0.3%

전화번호
Text

MISSING 

Distinct189
Distinct (%)80.8%
Missing83
Missing (%)26.2%
Memory size2.6 KiB
2023-12-11T08:54:08.109789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.008547
Min length12

Characters and Unicode

Total characters2810
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

Unique161 ?
Unique (%)68.8%

Sample

1st row055-763-1357
2nd row055-577-4976
3rd row055-755-3234
4th row055-744-4100
5th row055-759-1680
ValueCountFrequency (%)
055-323-3663 5
 
2.1%
055-835-0351 5
 
2.1%
055-346-2141 5
 
2.1%
055-298-1048 4
 
1.7%
055-362-1015 4
 
1.7%
055-391-7270 4
 
1.7%
055-326-0403 3
 
1.3%
055-646-3250 3
 
1.3%
055-251-4343 2
 
0.9%
055-322-2835 2
 
0.9%
Other values (179) 197
84.2%
2023-12-11T08:54:08.550344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 631
22.5%
- 468
16.7%
0 382
13.6%
3 267
9.5%
2 174
 
6.2%
8 164
 
5.8%
7 161
 
5.7%
6 158
 
5.6%
1 150
 
5.3%
4 147
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2342
83.3%
Dash Punctuation 468
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 631
26.9%
0 382
16.3%
3 267
11.4%
2 174
 
7.4%
8 164
 
7.0%
7 161
 
6.9%
6 158
 
6.7%
1 150
 
6.4%
4 147
 
6.3%
9 108
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 468
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2810
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 631
22.5%
- 468
16.7%
0 382
13.6%
3 267
9.5%
2 174
 
6.2%
8 164
 
5.8%
7 161
 
5.7%
6 158
 
5.6%
1 150
 
5.3%
4 147
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2810
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 631
22.5%
- 468
16.7%
0 382
13.6%
3 267
9.5%
2 174
 
6.2%
8 164
 
5.8%
7 161
 
5.7%
6 158
 
5.6%
1 150
 
5.3%
4 147
 
5.2%

등록일자
Date

Distinct267
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum1975-08-05 00:00:00
Maximum2017-05-04 00:00:00
2023-12-11T08:54:08.715866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:54:08.876726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-11T08:54:04.489599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:54:04.274925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:54:04.579961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:54:04.377609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:54:09.005726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호생산능력(톤)
번호1.0000.144
생산능력(톤)0.1441.000
2023-12-11T08:54:09.086665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호생산능력(톤)
번호1.000-0.032
생산능력(톤)-0.0321.000

Missing values

2023-12-11T08:54:04.701034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:54:04.804095image/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.
2023-12-11T08:54:04.904112image/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

번호사업장명소재지생산사료명생산능력(톤)전화번호등록일자
01아이엠팜주식회사경상남도 진주시 문산읍 삼곡리 1033번지 바이오21센터 벤304호보조사료 / 생균제0055-763-13572009-11-17
12대성물산경상남도 진주시 문산읍 동부로 853양어용배합사료0<NA>2010-04-14
23(주)한국바이오케미칼경상남도 진주시 문산읍 월아산로950번길 14-20보조사료/생균제5055-577-49762011-09-28
34바이오허브경상남도 진주시 정촌면 무선산로 285보조사료/규산염제0055-755-32342005-04-13
45참살이영농조합법인경상남도 진주시 대곡면 유곡로 275-53보조사료/미생물제(생균제)2055-744-41002011-04-22
56해성산업경상남도 진주시 솔밭로14번길 7 (상평동)단미사료/식물성/곡물류 및 곡류부산물류5055-759-16802006-02-03
67그린낙농경상남도 진주시 판문로 419 (판문동)보조사료/아미노산제0<NA>2009-07-24
78주식회사 에스제이바이오경상남도 통영시 산양읍 산양일주로 1488보조사료/생균제0055-646-32502007-03-22
89해미수산경상남도 통영시 산양읍 삼덕리 1 지선어류용배합사료0<NA>2007-08-22
910주식회사 에스제이바이오경상남도 통영시 산양읍 산양일주로 1488어류용배합사료1<NA>2011-11-28
번호사업장명소재지생산사료명생산능력(톤)전화번호등록일자
307308우림상사경상남도 양산시 상북면 수서로 114단미사료/식물성/섬유질류/섬유질가공사료20055-375-80272003-12-22
308309라우피드경상남도 김해시 상동면 상동로543번안길 7-3보조사료/아미노산제5055-321-43442006-06-23
309310신화산업경상남도 밀양시 하남읍 명례로 406단미사료/식물성/곡물부산물류(미강)10055-391-15402006-06-14
310311고성낙농영농조합법인경상남도 고성군 고성읍 남해안대로 2829-21, 2층단미사료/식물성/섬유질류/섬유질가공사료25055-673-82452004-10-01
311312(주)코리아에프앤에프경상남도 사천시 환경길 116 (사등동)양축용배합사료40055-835-03511997-01-27
312313(주)카길애그리퓨리나 김해공장경상남도 김해시 진영읍 본산로 257양축용 배합사료300055-340-33311998-08-25
313314부경양돈협동조합사료공장경상남도 김해시 진영읍 본산2로79번길 27양축용 배합사료200055-346-03311994-04-09
314315(주)농협사료 경남지사경상남도 함안군 법수면 윤외공단길 118양축용 배합사료668055-583-89811975-08-05
315316에이티씨경상남도 통영시 장골산길 8-10 (북신동)단미사료/동물성/단백질류(어분)0055-643-23342000-03-06
316317(주)아쿠아테크경상남도 김해시 생림면 나전로 231어류용 배합사료4055-323-91882006-03-06