Overview

Dataset statistics

Number of variables15
Number of observations27
Missing cells51
Missing cells (%)12.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory125.9 B

Variable types

Unsupported3
Text3
Categorical9

Dataset

Description현재 제주 지역에서 발견되어 감귤산업에 경제적 피해를 주고 있는 감귤황룡병 방제 등록 약제정보를 국민에게 제공하여 농가에서 손쉽게 사전에 방제할수 있도록 하는 등 농민의 자산 및 자연환경 보호에 활용하고자 함
Author농림축산검역본부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220214000000001863

Alerts

Unnamed: 7 is highly overall correlated with Unnamed: 8 and 4 other fieldsHigh correlation
Unnamed: 8 is highly overall correlated with Unnamed: 7 and 3 other fieldsHigh correlation
Unnamed: 9 is highly overall correlated with Unnamed: 7 and 4 other fieldsHigh correlation
Unnamed: 10 is highly overall correlated with Unnamed: 7 and 5 other fieldsHigh correlation
Unnamed: 11 is highly overall correlated with Unnamed: 7 and 4 other fieldsHigh correlation
Unnamed: 12 is highly overall correlated with Unnamed: 7 and 5 other fieldsHigh correlation
Unnamed: 13 is highly overall correlated with Unnamed: 10 and 2 other fieldsHigh correlation
Unnamed: 0 has 27 (100.0%) missing valuesMissing
살충제 약물 has 2 (7.4%) missing valuesMissing
제품이름 has 5 (18.5%) missing valuesMissing
한국제품이름 has 8 (29.6%) missing valuesMissing
수확전 농약처리 간격(PHI) has 5 (18.5%) missing valuesMissing
해충이름 has 4 (14.8%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수확전 농약처리 간격(PHI) is an unsupported type, check if it needs cleaning or further analysisUnsupported
해충이름 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 03:22:35.982037
Analysis finished2023-12-11 03:22:37.749014
Duration1.77 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing27
Missing (%)100.0%
Memory size375.0 B

살충제 약물
Text

MISSING 

Distinct24
Distinct (%)96.0%
Missing2
Missing (%)7.4%
Memory size348.0 B
2023-12-11T12:22:37.932253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length94
Median length60
Mean length15.28
Min length1

Characters and Unicode

Total characters382
Distinct characters142
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)92.0%

Sample

1st row아바멕틴 유제
2nd row카바릴
3rd row클로르피리포스
4th row클로티아니딘 (토양)
5th row디플루벤주론
ValueCountFrequency (%)
12
 
15.4%
해충 3
 
3.8%
이미다클로프리드 2
 
2.6%
토양 2
 
2.6%
티아메톡삼 2
 
2.6%
r 1
 
1.3%
없음 1
 
1.3%
조절에 1
 
1.3%
제품 1
 
1.3%
florida 1
 
1.3%
Other values (52) 52
66.7%
2023-12-11T12:22:38.359149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
61
 
16.0%
e 10
 
2.6%
로 10
 
2.6%
) 9
 
2.4%
( 9
 
2.4%
t 8
 
2.1%
i 8
 
2.1%
스 7
 
1.8%
= 7
 
1.8%
피 6
 
1.6%
Other values (132) 247
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 213
55.8%
Space Separator 61
 
16.0%
Lowercase Letter 59
 
15.4%
Math Symbol 13
 
3.4%
Uppercase Letter 12
 
3.1%
Close Punctuation 9
 
2.4%
Open Punctuation 9
 
2.4%
Control 3
 
0.8%
Other Punctuation 1
 
0.3%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 10
 
4.7%
스 7
 
3.3%
피 6
 
2.8%
해 6
 
2.8%
충 6
 
2.8%
메 6
 
2.8%
이 5
 
2.3%
리 4
 
1.9%
트 4
 
1.9%
드 4
 
1.9%
Other values (100) 155
72.8%
Lowercase Letter
ValueCountFrequency (%)
e 10
16.9%
t 8
13.6%
i 8
13.6%
s 5
8.5%
n 5
8.5%
a 4
 
6.8%
c 4
 
6.8%
d 3
 
5.1%
o 3
 
5.1%
m 3
 
5.1%
Other values (4) 6
10.2%
Uppercase Letter
ValueCountFrequency (%)
R 3
25.0%
C 2
16.7%
F 1
 
8.3%
P 1
 
8.3%
M 1
 
8.3%
G 1
 
8.3%
I 1
 
8.3%
N 1
 
8.3%
A 1
 
8.3%
Math Symbol
ValueCountFrequency (%)
= 7
53.8%
+ 6
46.2%
Space Separator
ValueCountFrequency (%)
61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Control
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Number
ValueCountFrequency (%)
¹ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 213
55.8%
Common 98
25.7%
Latin 71
 
18.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 10
 
4.7%
스 7
 
3.3%
피 6
 
2.8%
해 6
 
2.8%
충 6
 
2.8%
메 6
 
2.8%
이 5
 
2.3%
리 4
 
1.9%
트 4
 
1.9%
드 4
 
1.9%
Other values (100) 155
72.8%
Latin
ValueCountFrequency (%)
e 10
14.1%
t 8
11.3%
i 8
11.3%
s 5
 
7.0%
n 5
 
7.0%
a 4
 
5.6%
c 4
 
5.6%
d 3
 
4.2%
R 3
 
4.2%
o 3
 
4.2%
Other values (13) 18
25.4%
Common
ValueCountFrequency (%)
61
62.2%
) 9
 
9.2%
( 9
 
9.2%
= 7
 
7.1%
+ 6
 
6.1%
3
 
3.1%
? 1
 
1.0%
- 1
 
1.0%
¹ 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 213
55.8%
ASCII 168
44.0%
None 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
61
36.3%
e 10
 
6.0%
) 9
 
5.4%
( 9
 
5.4%
t 8
 
4.8%
i 8
 
4.8%
= 7
 
4.2%
+ 6
 
3.6%
s 5
 
3.0%
n 5
 
3.0%
Other values (21) 40
23.8%
Hangul
ValueCountFrequency (%)
로 10
 
4.7%
스 7
 
3.3%
피 6
 
2.8%
해 6
 
2.8%
충 6
 
2.8%
메 6
 
2.8%
이 5
 
2.3%
리 4
 
1.9%
트 4
 
1.9%
드 4
 
1.9%
Other values (100) 155
72.8%
None
ValueCountFrequency (%)
¹ 1
100.0%

제품이름
Text

MISSING 

Distinct21
Distinct (%)95.5%
Missing5
Missing (%)18.5%
Memory size348.0 B
2023-12-11T12:22:38.597940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14.5
Mean length13.181818
Min length9

Characters and Unicode

Total characters290
Distinct characters49
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)90.9%

Sample

1st rowAgri-mek 0.15EC
2nd rowSevin XLR Plus
3rd rowLorsban 4E
4th rowBelay 50 WDG
5th rowMicromite 80WGS
ValueCountFrequency (%)
numerous 2
 
4.3%
4e 2
 
4.3%
2sc 2
 
4.3%
wg 2
 
4.3%
240sc 1
 
2.2%
nexter 1
 
2.2%
miticide 1
 
2.2%
spintor 1
 
2.2%
delegate 1
 
2.2%
envidor 1
 
2.2%
Other values (32) 32
69.6%
2023-12-11T12:22:39.057602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
 
15.9%
e 21
 
7.2%
i 17
 
5.9%
n 14
 
4.8%
t 14
 
4.8%
r 13
 
4.5%
o 13
 
4.5%
a 11
 
3.8%
m 8
 
2.8%
d 8
 
2.8%
Other values (39) 125
43.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 157
54.1%
Uppercase Letter 56
 
19.3%
Space Separator 46
 
15.9%
Decimal Number 27
 
9.3%
Other Punctuation 3
 
1.0%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 21
13.4%
i 17
10.8%
n 14
8.9%
t 14
8.9%
r 13
8.3%
o 13
8.3%
a 11
 
7.0%
m 8
 
5.1%
d 8
 
5.1%
u 7
 
4.5%
Other values (11) 31
19.7%
Uppercase Letter
ValueCountFrequency (%)
S 7
12.5%
W 6
10.7%
P 5
8.9%
C 5
8.9%
E 5
8.9%
G 5
8.9%
D 4
7.1%
M 4
7.1%
I 3
 
5.4%
A 3
 
5.4%
Other values (7) 9
16.1%
Decimal Number
ValueCountFrequency (%)
2 6
22.2%
0 6
22.2%
5 5
18.5%
4 4
14.8%
7 2
 
7.4%
1 2
 
7.4%
6 1
 
3.7%
8 1
 
3.7%
Space Separator
ValueCountFrequency (%)
46
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 213
73.4%
Common 77
 
26.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 21
 
9.9%
i 17
 
8.0%
n 14
 
6.6%
t 14
 
6.6%
r 13
 
6.1%
o 13
 
6.1%
a 11
 
5.2%
m 8
 
3.8%
d 8
 
3.8%
S 7
 
3.3%
Other values (28) 87
40.8%
Common
ValueCountFrequency (%)
46
59.7%
2 6
 
7.8%
0 6
 
7.8%
5 5
 
6.5%
4 4
 
5.2%
. 3
 
3.9%
7 2
 
2.6%
1 2
 
2.6%
6 1
 
1.3%
- 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46
 
15.9%
e 21
 
7.2%
i 17
 
5.9%
n 14
 
4.8%
t 14
 
4.8%
r 13
 
4.5%
o 13
 
4.5%
a 11
 
3.8%
m 8
 
2.8%
d 8
 
2.8%
Other values (39) 125
43.1%

한국제품이름
Text

MISSING 

Distinct18
Distinct (%)94.7%
Missing8
Missing (%)29.6%
Memory size348.0 B
2023-12-11T12:22:39.267220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length5.4210526
Min length2

Characters and Unicode

Total characters103
Distinct characters65
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)89.5%

Sample

1st row올스타, 버티맥, 아라틴 등
2nd row세빈, 세단 등
3rd row탑베이트 파워 등
4th row똑소리, 빅카드 등
5th row디밀린
ValueCountFrequency (%)
등 6
 
18.8%
아타라 2
 
6.2%
토큐 1
 
3.1%
나방전문 1
 
3.1%
런너 1
 
3.1%
모벤토 1
 
3.1%
시나위 1
 
3.1%
델리게이트 1
 
3.1%
부메랑 1
 
3.1%
완승 1
 
3.1%
Other values (16) 16
50.0%
2023-12-11T12:22:39.666002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
 
14.6%
, 6
 
5.8%
등 6
 
5.8%
아 3
 
2.9%
라 3
 
2.9%
타 3
 
2.9%
이 3
 
2.9%
세 2
 
1.9%
토 2
 
1.9%
드 2
 
1.9%
Other values (55) 58
56.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 82
79.6%
Space Separator 15
 
14.6%
Other Punctuation 6
 
5.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
등 6
 
7.3%
아 3
 
3.7%
라 3
 
3.7%
타 3
 
3.7%
이 3
 
3.7%
세 2
 
2.4%
토 2
 
2.4%
드 2
 
2.4%
리 2
 
2.4%
트 2
 
2.4%
Other values (53) 54
65.9%
Space Separator
ValueCountFrequency (%)
15
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 82
79.6%
Common 21
 
20.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
등 6
 
7.3%
아 3
 
3.7%
라 3
 
3.7%
타 3
 
3.7%
이 3
 
3.7%
세 2
 
2.4%
토 2
 
2.4%
드 2
 
2.4%
리 2
 
2.4%
트 2
 
2.4%
Other values (53) 54
65.9%
Common
ValueCountFrequency (%)
15
71.4%
, 6
 
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 82
79.6%
ASCII 21
 
20.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15
71.4%
, 6
 
28.6%
Hangul
ValueCountFrequency (%)
등 6
 
7.3%
아 3
 
3.7%
라 3
 
3.7%
타 3
 
3.7%
이 3
 
3.7%
세 2
 
2.4%
토 2
 
2.4%
드 2
 
2.4%
리 2
 
2.4%
트 2
 
2.4%
Other values (53) 54
65.9%

농약처리제한 간격 (REI)
Categorical

Distinct7
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Memory size348.0 B
12 시간
13 
<NA>
5 
24 시간
3 
4 시간
3 
5 일
 
1
Other values (2)
2 

Length

Max length6
Median length6
Mean length5.4074074
Min length4

Unique

Unique3 ?
Unique (%)11.1%

Sample

1st row<NA>
2nd row<NA>
3rd row12 시간
4th row12 시간
5th row5 일

Common Values

ValueCountFrequency (%)
12 시간 13
48.1%
<NA> 5
 
18.5%
24 시간 3
 
11.1%
4 시간 3
 
11.1%
5 일 1
 
3.7%
10 일 1
 
3.7%
48 시간 1
 
3.7%

Length

2023-12-11T12:22:39.871837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:22:40.047486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시간 20
40.8%
12 13
26.5%
na 5
 
10.2%
24 3
 
6.1%
4 3
 
6.1%
일 2
 
4.1%
5 1
 
2.0%
10 1
 
2.0%
48 1
 
2.0%

수확전 농약처리 간격(PHI)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5
Missing (%)18.5%
Memory size348.0 B

해충이름
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4
Missing (%)14.8%
Memory size348.0 B

Unnamed: 7
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Memory size348.0 B
+++,R
10 
-
6 
<NA>
4 
++
3 
귤나무이
 
1
Other values (3)
3 

Length

Max length7
Median length6
Mean length4.2222222
Min length2

Unique

Unique4 ?
Unique (%)14.8%

Sample

1st row귤나무이
2nd row<NA>
3rd row++
4th row++
5th row+++,R

Common Values

ValueCountFrequency (%)
+++,R 10
37.0%
- 6
22.2%
<NA> 4
 
14.8%
++ 3
 
11.1%
귤나무이 1
 
3.7%
+++ 1
 
3.7%
+ 1
 
3.7%
+++, R 1
 
3.7%

Length

2023-12-11T12:22:40.192693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:22:40.313402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
12
42.9%
r 11
39.3%
na 4
 
14.3%
귤나무이 1
 
3.6%

Unnamed: 8
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Memory size348.0 B
+++,R
8 
-
8 
<NA>
4 
+
3 
?
2 
Other values (2)
2 

Length

Max length6
Median length5
Mean length3.6666667
Min length2

Unique

Unique2 ?
Unique (%)7.4%

Sample

1st row잎굴파리
2nd row<NA>
3rd row+++,R
4th row-
5th row+

Common Values

ValueCountFrequency (%)
+++,R 8
29.6%
- 8
29.6%
<NA> 4
14.8%
+ 3
 
11.1%
? 2
 
7.4%
잎굴파리 1
 
3.7%
++,R 1
 
3.7%

Length

2023-12-11T12:22:40.551819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:22:40.743320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13
48.1%
r 9
33.3%
na 4
 
14.8%
잎굴파리 1
 
3.7%

Unnamed: 9
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size348.0 B
-
10 
+++,R
7 
<NA>
4 
+
4 
녹응매
 
1

Length

Max length6
Median length2
Mean length3.4814815
Min length2

Unique

Unique2 ?
Unique (%)7.4%

Sample

1st row녹응매
2nd row<NA>
3rd row+++,R
4th row+
5th row+

Common Values

ValueCountFrequency (%)
- 10
37.0%
+++,R 7
25.9%
<NA> 4
 
14.8%
+ 4
 
14.8%
녹응매 1
 
3.7%
++,R 1
 
3.7%

Length

2023-12-11T12:22:40.936296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:22:41.116899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
14
51.9%
r 8
29.6%
na 4
 
14.8%
녹응매 1
 
3.7%

Unnamed: 10
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Memory size348.0 B
-
11 
<NA>
4 
?
4 
+++,R
3 
+
2 
Other values (3)
3 

Length

Max length6
Median length2
Mean length2.9259259
Min length2

Unique

Unique3 ?
Unique (%)11.1%

Sample

1st row거미응애
2nd row<NA>
3rd row+
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 11
40.7%
<NA> 4
 
14.8%
? 4
 
14.8%
+++,R 3
 
11.1%
+ 2
 
7.4%
거미응애 1
 
3.7%
++ 1
 
3.7%
+++ 1
 
3.7%

Length

2023-12-11T12:22:41.281486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:22:41.455438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
19
70.4%
na 4
 
14.8%
r 3
 
11.1%
거미응애 1
 
3.7%

Unnamed: 11
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size348.0 B
-
7 
?
5 
<NA>
4 
+++,R
4 
+
3 
Other values (4)
4 

Length

Max length9
Median length2
Mean length3.6666667
Min length2

Unique

Unique4 ?
Unique (%)14.8%

Sample

1st row성충 뿌리 바구미
2nd row<NA>
3rd row+ (oil)
4th row+++,R
5th row+

Common Values

ValueCountFrequency (%)
- 7
25.9%
? 5
18.5%
<NA> 4
14.8%
+++,R 4
14.8%
+ 3
11.1%
성충 뿌리 바구미 1
 
3.7%
+ (oil) 1
 
3.7%
+(eggs) 1
 
3.7%
+++ 1
 
3.7%

Length

2023-12-11T12:22:41.611591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:22:41.776593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
17
56.7%
na 4
 
13.3%
r 4
 
13.3%
성충 1
 
3.3%
뿌리 1
 
3.3%
바구미 1
 
3.3%
oil 1
 
3.3%
eggs 1
 
3.3%

Unnamed: 12
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size348.0 B
-
7 
?
5 
<NA>
4 
++
4 
+++,R
3 
Other values (4)
4 

Length

Max length7
Median length6
Mean length3.3333333
Min length2

Unique

Unique4 ?
Unique (%)14.8%

Sample

1st row깍지벌레
2nd row<NA>
3rd row+(oil)
4th row+++,R
5th row+++,R

Common Values

ValueCountFrequency (%)
- 7
25.9%
? 5
18.5%
<NA> 4
14.8%
++ 4
14.8%
+++,R 3
11.1%
깍지벌레 1
 
3.7%
+(oil) 1
 
3.7%
++,R 1
 
3.7%
+++ 1
 
3.7%

Length

2023-12-11T12:22:41.977351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:22:42.130200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
17
63.0%
na 4
 
14.8%
r 4
 
14.8%
깍지벌레 1
 
3.7%
oil 1
 
3.7%

Unnamed: 13
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Memory size348.0 B
+
8 
?
6 
-
6 
<NA>
4 
가루깍지벌레
1 
Other values (2)
2 

Length

Max length8
Median length2
Mean length2.8148148
Min length2

Unique

Unique3 ?
Unique (%)11.1%

Sample

1st row가루깍지벌레
2nd row<NA>
3rd row+ (oil)
4th row+
5th row+++,R

Common Values

ValueCountFrequency (%)
+ 8
29.6%
? 6
22.2%
- 6
22.2%
<NA> 4
14.8%
가루깍지벌레 1
 
3.7%
+ (oil) 1
 
3.7%
+++,R 1
 
3.7%

Length

2023-12-11T12:22:42.311136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:22:42.480286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
21
75.0%
na 4
 
14.3%
가루깍지벌레 1
 
3.6%
oil 1
 
3.6%
r 1
 
3.6%

천적에 미치는 영향
Categorical

Distinct6
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size348.0 B
저
11 
고
6 
<NA>
5 
중
3 
중/고
 
1

Length

Max length9
Median length2
Mean length2.7037037
Min length2

Unique

Unique2 ?
Unique (%)7.4%

Sample

1st row<NA>
2nd row<NA>
3rd row중
4th row고
5th row고

Common Values

ValueCountFrequency (%)
저 11
40.7%
고 6
22.2%
<NA> 5
18.5%
중 3
 
11.1%
중/고 1
 
3.7%
고 (짧은기간) 1
 
3.7%

Length

2023-12-11T12:22:42.643142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:22:42.798306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
저 11
39.3%
고 7
25.0%
na 5
17.9%
중 3
 
10.7%
중/고 1
 
3.6%
짧은기간 1
 
3.6%

Correlations

2023-12-11T12:22:42.908288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
살충제 약물제품이름한국제품이름농약처리제한 간격 (REI)Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13천적에 미치는 영향
살충제 약물1.0000.9831.0001.0001.0000.8411.0001.0000.9681.0001.0000.864
제품이름0.9831.0001.0001.0000.0000.0000.0000.0000.0000.0000.9290.000
한국제품이름1.0001.0001.0001.0001.0000.8681.0001.0000.9351.0001.0000.000
농약처리제한 \n간격 \n(REI)1.0001.0001.0001.0000.7700.0000.3690.0000.0000.0000.5710.000
Unnamed: 71.0000.0001.0000.7701.0000.7310.8400.9110.8160.8120.6940.536
Unnamed: 80.8410.0000.8680.0000.7311.0000.8260.7660.7490.8390.7750.597
Unnamed: 91.0000.0001.0000.3690.8400.8261.0000.8370.8550.8500.6510.267
Unnamed: 101.0000.0001.0000.0000.9110.7660.8371.0000.7830.8480.7800.559
Unnamed: 110.9680.0000.9350.0000.8160.7490.8550.7831.0000.9330.8030.000
Unnamed: 121.0000.0001.0000.0000.8120.8390.8500.8480.9331.0000.9340.448
Unnamed: 131.0000.9291.0000.5710.6940.7750.6510.7800.8030.9341.0000.491
천적에 \n미치는\n 영향0.8640.0000.0000.0000.5360.5970.2670.5590.0000.4480.4911.000
2023-12-11T12:22:43.071630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 13Unnamed: 12Unnamed: 8Unnamed: 9농약처리제한 간격 (REI)Unnamed: 11Unnamed: 7Unnamed: 10천적에 미치는 영향
Unnamed: 131.0000.7900.3690.4880.4060.5670.4790.5820.174
Unnamed: 120.7901.0000.6210.6670.0000.5870.5810.6360.262
Unnamed: 80.3690.6211.0000.7010.0000.4970.5210.5640.239
Unnamed: 90.4880.6670.7011.0000.2040.6750.6960.6910.191
농약처리제한 \n간격 \n(REI)0.4060.0000.0000.2041.0000.0000.3620.0000.000
Unnamed: 110.5670.5870.4970.6750.0001.0000.5860.5400.000
Unnamed: 70.4790.5810.5210.6960.3620.5861.0000.5500.373
Unnamed: 100.5820.6360.5640.6910.0000.5400.5501.0000.394
천적에 \n미치는\n 영향0.1740.2620.2390.1910.0000.0000.3730.3941.000
2023-12-11T12:22:43.239342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
농약처리제한 간격 (REI)Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13천적에 미치는 영향
농약처리제한 \n간격 \n(REI)1.0000.3620.0000.2040.0000.0000.0000.4060.000
Unnamed: 70.3621.0000.5210.6960.5500.5860.5810.4790.373
Unnamed: 80.0000.5211.0000.7010.5640.4970.6210.3690.239
Unnamed: 90.2040.6960.7011.0000.6910.6750.6670.4880.191
Unnamed: 100.0000.5500.5640.6911.0000.5400.6360.5820.394
Unnamed: 110.0000.5860.4970.6750.5401.0000.5870.5670.000
Unnamed: 120.0000.5810.6210.6670.6360.5871.0000.7900.262
Unnamed: 130.4060.4790.3690.4880.5820.5670.7901.0000.174
천적에 \n미치는\n 영향0.0000.3730.2390.1910.3940.0000.2620.1741.000

Missing values

2023-12-11T12:22:36.986393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:22:37.251743image/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.
2023-12-11T12:22:37.528013image/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

Unnamed: 0살충제 약물제품이름한국제품이름농약처리제한 간격 (REI)수확전 농약처리 간격(PHI)해충이름Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13천적에 미치는 영향
0<NA><NA><NA><NA><NA>NaN작용방식¹귤나무이잎굴파리녹응매거미응애성충 뿌리 바구미깍지벌레가루깍지벌레<NA>
1<NA><NA><NA><NA><NA>NaNNaN<NA><NA><NA><NA><NA><NA><NA><NA>
2<NA>아바멕틴 유제Agri-mek 0.15EC올스타, 버티맥, 아라틴 등12 시간7 일6+++++,R+++,R++ (oil)+(oil)+ (oil)중
3<NA>카바릴Sevin XLR Plus세빈, 세단 등12 시간5 일1A++-+-+++,R+++,R+고
4<NA>클로르피리포스Lorsban 4E탑베이트 파워 등5 일21 일1B+++,R++-++++,R+++,R고
5<NA>클로티아니딘 (토양)Belay 50 WDG똑소리, 빅카드 등12 시간04+++,R+++,R--???저
6<NA>디플루벤주론Micromite 80WGS디밀린12 시간21 일15+++++,R+++,R-+++,R--저
7<NA>디메토에이트Dimethoate 4E로고, 록숀 등10 일15-45 일1B+++---?+++,R+고
8<NA>산화펜부타주석Vendex 50WP토큐48 시간7 일12--+++,R+++,R---저
9<NA>펜프로파스린Danitol 2.4EC<NA>24 시간1 일3+++,R-+++++,R-+고
Unnamed: 0살충제 약물제품이름한국제품이름농약처리제한 간격 (REI)수확전 농약처리 간격(PHI)해충이름Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13천적에 미치는 영향
17<NA>스피네토람Delegate WG델리게이트4 시간1 일5+++,R+++,R-????저
18<NA>스피로디크로펜Envidor 2SC시나위12 시간7 일23--+++,R+++,R?--저
19<NA>스피로테트라맷Movento 240SC모벤토24 시간1 일23+++,R?+++,R??+++?저
20<NA>황numerous<NA>12 시간0NR--+++,R+++-??고 (짧은기간)
21<NA>티아메톡삼Actara 25 WG아타라12 시간04+++,R+---+++중
22<NA>티아메톡삼Platinum 75 SG아타라12 시간04+++,R+++,R--++++저
23<NA>제타싸이퍼메트린Mustang Insecticide터보사이드12 시간1 일3+++,R--?+++??고
24<NA>¹Insecticide Resistance Action Committee로부터 규정한 귤 해충의 작용방식<NA><NA><NA>NaNNaN<NA><NA><NA><NA><NA><NA><NA><NA>
25<NA>NR = 잠재적 저항성 없음 (R) = 해충 조절에 관해 Florida Citrus Pest Management Guide에서 추천한 제품<NA><NA><NA>NaNNaN<NA><NA><NA><NA><NA><NA><NA><NA>
26<NA>(+++) = 해충 조절능력 좋음 (++) = 짧은기간동안 해충조절 (+) = 해충 억제 수준 낮음 (-) = 관찰되지 않음 (?) = 자료 불충분으로 인한 분석 불가<NA><NA><NA>NaNNaN<NA><NA><NA><NA><NA><NA><NA><NA>