Skip to content
Projects
Groups
Snippets
Help
Loading...
Help
Support
Keyboard shortcuts
?
Submit feedback
Contribute to GitLab
Sign in / Register
Toggle navigation
P
pomegranate-farming-monitoring-system
Project overview
Project overview
Details
Activity
Releases
Repository
Repository
Files
Commits
Branches
Tags
Contributors
Graph
Compare
Issues
0
Issues
0
List
Boards
Labels
Milestones
Merge Requests
0
Merge Requests
0
CI / CD
CI / CD
Pipelines
Jobs
Schedules
Analytics
Analytics
CI / CD
Repository
Value Stream
Wiki
Wiki
Snippets
Snippets
Members
Members
Collapse sidebar
Close sidebar
Activity
Graph
Create a new issue
Jobs
Commits
Issue Boards
Open sidebar
TMP2023-229
pomegranate-farming-monitoring-system
Commits
88d13d5f
Commit
88d13d5f
authored
Oct 29, 2023
by
Gimhan A.H.L.D.K
Browse files
Options
Browse Files
Download
Email Patches
Plain Diff
add training and dataset
parent
31d7115d
Changes
2
Hide whitespace changes
Inline
Side-by-side
Showing
2 changed files
with
3631 additions
and
0 deletions
+3631
-0
Training/pest and disease prediction/pest and disease dataset.csv
...pest and disease prediction/pest and disease dataset.csv
+2153
-0
Training/pest and disease prediction/pest prediction train.ipynb
.../pest and disease prediction/pest prediction train.ipynb
+1478
-0
No files found.
Training/pest and disease prediction/pest and disease dataset.csv
0 → 100644
View file @
88d13d5f
Temperature,Humidity,Rain,Wind_speed,Disease,Status
23.56,99.97,yes,22,Bacterialblight,high
23.17,93.2,yes,21,Bacterialblight,high
17.52,96.62,yes,19,Bacterialblight,high
24.76,96.71,yes,18,Bacterialblight,high
34.53,17.07,yes,27,Bacterialblight,high
22.5,88.49,yes,15,Bacterialblight,high
23.05,87.87,no,26,Bacterialblight,high
20.31,88.53,yes,24,Bacterialblight,high
12.32,70,yes,13,Bacterialblight,high
22.34,96.2,no,23,Bacterialblight,high
13.11,85.6,yes,20,Bacterialblight,high
24.12,86.86,yes,14,Bacterialblight,high
20.95,93.48,yes,27,Bacterialblight,high
31.77,46.28,yes,14,Bacterialblight,high
16.09,90.18,yes,26,Bacterialblight,high
22.45,85.27,yes,17,Bacterialblight,high
13.88,99.15,yes,23,Bacterialblight,high
18.84,96.83,yes,24,Bacterialblight,high
23.93,94.82,yes,17,Bacterialblight,high
31.32,17.9,yes,21,Bacterialblight,high
21.16,98.8,yes,18,Bacterialblight,high
19.71,98.21,yes,21,Bacterialblight,high
14.56,97.46,yes,25,Bacterialblight,high
13.52,93.03,yes,18,Bacterialblight,high
15.77,85.79,no,26,Bacterialblight,high
14.39,93.34,yes,15,Bacterialblight,high
34.89,29.01,yes,22,Bacterialblight,high
15.13,91.11,yes,20,Bacterialblight,high
13.08,91.96,yes,16,Bacterialblight,high
12.8,94.93,yes,25,Bacterialblight,high
10.13,86.46,yes,28,Bacterialblight,high
16.48,92.66,yes,28,Bacterialblight,high
24.2,85.92,yes,24,Bacterialblight,high
31.94,19.06,yes,12,Bacterialblight,high
16.5,95.79,yes,15,Bacterialblight,high
22.2,90.32,yes,23,Bacterialblight,high
12.54,85.61,yes,23,Bacterialblight,high
21.15,96.37,yes,25,Bacterialblight,high
17.09,99.63,yes,21,Bacterialblight,high
20.64,88.43,yes,21,Bacterialblight,high
17.86,88.75,yes,17,Bacterialblight,high
19.44,90.72,yes,22,Bacterialblight,high
23.77,92.85,yes,25,Bacterialblight,high
22.45,95.3,yes,21,Bacterialblight,high
19.52,97.02,yes,28,Bacterialblight,high
18.07,98.12,yes,25,Bacterialblight,high
18.65,99.77,yes,13,Bacterialblight,high
12.44,93.91,yes,22,Bacterialblight,high
11.75,85.92,yes,21,Bacterialblight,high
20.71,89.5,yes,25,Bacterialblight,high
23.2,96.1,yes,23,Bacterialblight,high
18.71,86.45,yes,26,Bacterialblight,high
15.47,99.09,yes,15,Bacterialblight,high
12,97.96,yes,15,Bacterialblight,high
20.56,89.86,yes,26,Bacterialblight,high
23.95,96.95,yes,26,Bacterialblight,high
20.86,92.08,yes,27,Bacterialblight,high
10.76,94.33,yes,12,Bacterialblight,high
20.04,91.75,yes,28,Bacterialblight,high
13.05,85.37,yes,18,Bacterialblight,high
20.6,86.53,yes,16,Bacterialblight,high
12.29,91.76,yes,26,Bacterialblight,high
12.75,85.64,no,17,Bacterialblight,high
23.71,86.44,no,27,Bacterialblight,high
20.28,89.01,no,19,Bacterialblight,high
17.95,87.11,no,15,Bacterialblight,high
23.59,92.54,no,26,Bacterialblight,high
21.92,92.89,no,19,Bacterialblight,high
15.36,97.47,no,19,Bacterialblight,high
19.55,89.6,yes,26,Bacterialblight,high
24.68,94.78,yes,13,Bacterialblight,high
17.24,97.55,yes,16,Bacterialblight,high
11.52,88.84,yes,17,Bacterialblight,high
15.96,91.73,yes,16,Bacterialblight,high
17.96,87.65,yes,12,Bacterialblight,high
23.48,98.23,yes,14,Bacterialblight,high
17.27,92.26,yes,28,Bacterialblight,high
15.39,95.19,yes,16,Bacterialblight,high
18.48,91.32,yes,26,Bacterialblight,high
28.17,66.78,yes,18,Bacterialblight,high
11.08,94.46,yes,15,Bacterialblight,high
21.58,94.47,yes,25,Bacterialblight,high
14.85,90.87,yes,17,Bacterialblight,high
14.81,91.45,yes,13,Bacterialblight,high
23.48,99.16,yes,22,Bacterialblight,high
27.63,61.5,yes,15,Bacterialblight,high
13.25,98.99,yes,28,Bacterialblight,high
15.76,89.19,yes,12,Bacterialblight,high
11.2,92.14,yes,16,Bacterialblight,high
13.89,97.02,yes,13,Bacterialblight,high
28.86,76.97,no,23,Bacterialblight,high
19.3,96.82,no,26,Bacterialblight,high
15.09,92.42,no,23,Bacterialblight,high
24.59,85.34,no,24,Bacterialblight,high
11.91,93.46,no,21,Bacterialblight,high
11.5,88.15,yes,28,Bacterialblight,high
24.06,92.94,yes,15,Bacterialblight,high
23.95,93.33,yes,26,Bacterialblight,high
26.01,78.26,yes,24,Bacterialblight,high
23.49,98.57,yes,17,Bacterialblight,high
24.62,87.84,yes,25,Bacterialblight,high
13.46,91.67,yes,12,Bacterialblight,high
21.13,95.34,yes,17,Bacterialblight,high
22,95.12,yes,25,Bacterialblight,high
11.75,85.52,yes,15,Bacterialblight,high
11.96,93.57,yes,26,Bacterialblight,high
16.39,86.64,yes,17,Bacterialblight,high
21.77,94.42,yes,27,Bacterialblight,high
15.01,94.22,yes,19,Bacterialblight,high
14.07,89.13,yes,25,Bacterialblight,high
28.89,63.42,yes,15,Bacterialblight,high
17.54,93.83,yes,27,Bacterialblight,high
28.82,74.64,yes,17,Bacterialblight,high
12.42,97.88,yes,17,Bacterialblight,high
12.34,88.56,yes,16,Bacterialblight,high
14.83,98.69,yes,14,Bacterialblight,high
21.12,93.29,yes,23,Bacterialblight,high
15.83,91.67,yes,22,Bacterialblight,high
15.99,89.28,yes,13,Bacterialblight,high
22.62,96.3,yes,22,Bacterialblight,high
10.71,94.84,yes,18,Bacterialblight,high
12.79,97.32,yes,26,Bacterialblight,high
13.53,86.81,yes,25,Bacterialblight,high
20.85,92.99,yes,24,Bacterialblight,high
20.08,93.05,yes,26,Bacterialblight,high
19.19,91.81,yes,13,Bacterialblight,high
20.49,86.79,yes,28,Bacterialblight,high
11.35,90.78,yes,17,Bacterialblight,high
11.44,89.61,yes,17,Bacterialblight,high
13.95,96.15,yes,21,Bacterialblight,high
24.34,92.41,yes,27,Bacterialblight,high
12.44,88.14,yes,28,Bacterialblight,high
21.05,93.9,yes,18,Bacterialblight,high
23.42,90.96,yes,13,Bacterialblight,high
19.66,88.16,yes,12,Bacterialblight,high
15.47,93.55,yes,16,Bacterialblight,high
23.66,86.54,yes,22,Bacterialblight,high
21.71,85.51,yes,28,Bacterialblight,high
18.74,99.46,yes,15,Bacterialblight,high
13.4,95.22,yes,16,Bacterialblight,high
18.78,96.67,yes,27,Bacterialblight,high
11.98,85.08,yes,20,Bacterialblight,high
12.36,91.23,yes,27,Bacterialblight,high
20.31,88.48,yes,26,Bacterialblight,high
19.71,86.95,yes,21,Bacterialblight,high
23.84,96.85,yes,28,Bacterialblight,high
17.1,96.31,yes,15,Bacterialblight,high
13.91,93.68,yes,24,Bacterialblight,high
24.92,89.99,yes,27,Bacterialblight,high
17.25,93.96,yes,16,Bacterialblight,high
11.95,97.52,yes,22,Bacterialblight,high
10.71,98.59,yes,28,Bacterialblight,high
15.53,92.7,yes,27,Bacterialblight,high
11.24,95.99,yes,14,Bacterialblight,high
22.43,92.18,yes,22,Bacterialblight,high
17.89,96.92,yes,22,Bacterialblight,high
24.85,95.15,yes,22,Bacterialblight,high
24.28,91.83,yes,23,Bacterialblight,high
26.86,63.71,yes,13,Bacterialblight,high
23.8,86.92,yes,27,Bacterialblight,high
27.87,75.23,yes,24,Bacterialblight,high
13.31,93.43,yes,20,Bacterialblight,high
27.8,61.29,yes,23,Bacterialblight,high
10.39,88.71,yes,24,Bacterialblight,high
24.42,99.26,yes,16,Bacterialblight,high
13.15,98,yes,22,Bacterialblight,high
28,70.68,yes,19,Bacterialblight,high
24.86,86.01,yes,24,Bacterialblight,high
17.5,94.57,yes,15,Bacterialblight,high
13.5,89.82,yes,12,Bacterialblight,high
11.73,92.9,yes,18,Bacterialblight,high
28.26,65.51,yes,23,Bacterialblight,high
20.24,96.98,yes,22,Bacterialblight,high
29.88,67.77,yes,19,Bacterialblight,high
24.18,90.31,yes,27,Bacterialblight,high
20.7,89.88,yes,18,Bacterialblight,high
15.94,96.25,yes,25,Bacterialblight,high
27.52,69.58,yes,17,Bacterialblight,high
15.52,91.38,yes,19,Bacterialblight,high
21.74,90.85,yes,24,Bacterialblight,high
14.1,86.5,yes,15,Bacterialblight,high
29.77,66.24,yes,16,Bacterialblight,high
10.09,95.42,yes,27,Bacterialblight,high
29.6,75.53,yes,20,Bacterialblight,high
22.93,88.87,yes,27,Bacterialblight,high
16.43,99.14,yes,26,Bacterialblight,high
29.22,69.92,yes,21,Bacterialblight,high
18.53,88.04,yes,28,Bacterialblight,high
15.57,95.96,yes,15,Bacterialblight,high
20.12,94.17,yes,24,Bacterialblight,high
18.88,88.12,yes,27,Bacterialblight,high
17.21,85.45,yes,15,Bacterialblight,high
27.52,63.27,yes,16,Bacterialblight,high
13.87,87.22,yes,27,Bacterialblight,high
16.17,91.19,yes,20,Bacterialblight,high
22.29,94.25,no,27,Bacterialblight,high
19.42,97.27,no,26,Bacterialblight,high
18.42,97.36,no,21,Bacterialblight,high
27.36,70.22,no,28,Bacterialblight,high
14.67,89.28,no,15,Bacterialblight,high
29.47,68.75,no,24,Bacterialblight,high
36.4,23.42,no,27,Bacterialblight,high
23.67,85.27,no,15,Bacterialblight,high
30.21,44.28,no,16,Bacterialblight,low
26.29,64.67,yes,27,Bacterialblight,low
32.05,36.9,yes,20,Bacterialblight,low
29.29,72.4,yes,27,Bacterialblight,low
30.03,58.89,yes,26,Bacterialblight,low
33.18,46.56,yes,21,Bacterialblight,low
35.9,33.77,yes,28,Bacterialblight,low
36.43,51.16,yes,15,Bacterialblight,low
33.31,57.17,no,24,Bacterialblight,low
30.58,53.54,no,27,Bacterialblight,low
30.67,10.28,no,7,Bacterialblight,low
35.38,58.14,no,8,Bacterialblight,low
33.16,54.53,no,1,Bacterialblight,low
30.07,17.55,no,9,Bacterialblight,low
32.72,48.24,no,6,Bacterialblight,low
37,16.44,no,9,Bacterialblight,low
36.48,57.78,no,1,Bacterialblight,low
35.06,20.16,no,8,Bacterialblight,low
36.52,38.52,no,2,Bacterialblight,low
33.24,24.59,no,8,Bacterialblight,low
31.82,47.55,no,5,Bacterialblight,low
35.83,55.68,no,4,Bacterialblight,low
36.84,53.64,no,5,Bacterialblight,low
36,49.11,no,6,Bacterialblight,low
36.2,40.12,no,4,Bacterialblight,low
33.2,14.8,no,3,Bacterialblight,low
36.91,38.18,no,2,Bacterialblight,low
33.07,29.56,no,6,Bacterialblight,low
35.67,46.97,no,9,Bacterialblight,low
33.47,42.64,no,5,Bacterialblight,low
31.26,36.2,no,2,Bacterialblight,low
36.47,37.29,no,1,Bacterialblight,low
36.55,24.52,no,5,Bacterialblight,low
36.71,28.06,no,5,Bacterialblight,low
30.02,37.55,no,7,Bacterialblight,low
34.75,30.74,no,3,Bacterialblight,low
34.7,50,no,2,Bacterialblight,low
30.33,30.92,no,8,Bacterialblight,low
36.93,16.91,no,6,Bacterialblight,low
34.5,28.91,no,2,Bacterialblight,low
30.61,12.17,no,5,Bacterialblight,low
33.23,59.58,no,9,Bacterialblight,low
32.49,57.44,no,6,Bacterialblight,low
31.62,49.04,no,1,Bacterialblight,low
32.86,49.69,yes,2,Bacterialblight,low
32.79,22.9,yes,6,Bacterialblight,low
31.46,36.42,yes,2,Bacterialblight,low
30.7,56.14,yes,2,Bacterialblight,low
31.25,47.95,yes,7,Bacterialblight,low
33.63,12.98,yes,8,Bacterialblight,low
27.03,68.01,no,4,Bacterialblight,low
32.63,25.62,no,7,Bacterialblight,low
30.12,54.61,no,5,Bacterialblight,low
32.31,36.55,no,2,Bacterialblight,low
31.94,49.09,no,9,Bacterialblight,low
35.68,22.76,no,6,Bacterialblight,low
36.57,10.1,no,1,Bacterialblight,low
32.31,19.59,no,9,Bacterialblight,low
27.41,74.21,no,8,Bacterialblight,low
33.91,38.73,no,9,Bacterialblight,low
34.99,16.82,no,6,Bacterialblight,low
32.64,41.86,no,6,Bacterialblight,low
35.53,26.41,no,2,Bacterialblight,low
30.83,34.74,no,2,Bacterialblight,low
36.51,52.16,no,1,Bacterialblight,low
31.21,11.21,no,2,Bacterialblight,low
30.16,40.41,yes,6,Bacterialblight,low
31.98,38.59,no,6,Bacterialblight,low
31.09,28.52,no,4,Bacterialblight,low
34.64,31.08,yes,1,Bacterialblight,low
36.88,36.3,no,1,Bacterialblight,low
35.19,24.54,no,3,Bacterialblight,low
36.3,43.27,yes,5,Bacterialblight,low
36.63,10.57,no,7,Bacterialblight,low
30.04,17.53,no,1,Bacterialblight,low
30.45,11.17,no,3,Bacterialblight,low
31.02,19.08,no,5,Bacterialblight,low
35.37,39.38,no,3,Bacterialblight,low
30.04,10.49,no,9,Bacterialblight,low
33.34,39.95,no,6,Bacterialblight,low
35.94,28.95,no,3,Bacterialblight,low
31.72,34.32,no,5,Bacterialblight,low
30.31,42.4,no,6,Bacterialblight,low
35.96,47.22,no,8,Bacterialblight,low
36.95,47.72,no,7,Bacterialblight,low
35.85,42.44,no,9,Bacterialblight,low
35.61,49.47,no,4,Bacterialblight,low
32.46,33.23,no,1,Bacterialblight,low
33.67,57.87,no,7,Bacterialblight,low
33.34,59.73,no,3,Bacterialblight,low
33.61,31.59,no,5,Bacterialblight,low
36.51,56.02,no,4,Bacterialblight,low
31.92,23.27,no,9,Bacterialblight,low
34.5,44.78,no,3,Bacterialblight,low
31.04,34.99,no,5,Bacterialblight,low
30.49,19.5,no,3,Bacterialblight,low
32.9,18.66,yes,4,Bacterialblight,low
35.23,36.92,no,3,Bacterialblight,low
33.67,50.34,no,2,Bacterialblight,low
36.31,27.18,no,3,Bacterialblight,low
30.98,51.58,no,7,Bacterialblight,low
34.43,45.67,no,7,Bacterialblight,low
34.72,11.39,no,4,Bacterialblight,low
32.21,36.4,no,2,Bacterialblight,low
35.87,46.69,no,1,Bacterialblight,low
36.11,43.61,no,5,Bacterialblight,low
31.17,47.42,no,7,Bacterialblight,low
36.48,54.33,no,9,Bacterialblight,low
33.64,23.57,no,5,Bacterialblight,low
33.57,44.86,no,7,Bacterialblight,low
30.96,23.48,no,6,Bacterialblight,low
30.86,41,no,5,Bacterialblight,low
33.08,47.75,no,8,Bacterialblight,low
30.95,53.3,no,7,Bacterialblight,low
30.23,51.49,no,3,Bacterialblight,low
36.21,18.82,no,2,Bacterialblight,low
32.29,26.68,no,8,Bacterialblight,low
31.88,31.42,no,8,Bacterialblight,low
36.03,50.08,no,8,Bacterialblight,low
34.92,55.15,no,4,Bacterialblight,low
31.3,53.82,no,3,Bacterialblight,low
34.75,20.89,no,4,Bacterialblight,low
36.46,14.9,no,2,Bacterialblight,low
33.68,16.01,yes,5,Bacterialblight,low
35.78,12.51,no,3,Bacterialblight,low
32.29,13.27,no,2,Bacterialblight,low
33.17,25.52,no,5,Bacterialblight,low
34.56,13.64,no,5,Bacterialblight,low
34.79,50.78,no,6,Bacterialblight,low
30.4,42.25,no,3,Bacterialblight,low
34.67,29.48,no,5,Bacterialblight,low
31.26,23.95,no,4,Bacterialblight,low
34.29,32.33,no,5,Bacterialblight,low
30.92,46.8,no,1,Bacterialblight,low
35.82,59.93,no,9,Bacterialblight,low
33.42,52.13,no,3,Bacterialblight,low
34.44,21.82,no,5,Bacterialblight,low
29.55,67.03,no,2,Bacterialblight,low
33.28,25.06,yes,7,Bacterialblight,low
34.44,60,no,2,Bacterialblight,low
27.3,71.68,no,9,Bacterialblight,low
31.68,57.49,no,8,Bacterialblight,low
33.02,41.1,no,3,Bacterialblight,low
27.27,69.81,no,9,Bacterialblight,low
33.45,27.54,no,7,Bacterialblight,low
35.86,48.1,no,1,Bacterialblight,low
30.78,12.7,no,7,Bacterialblight,low
35.49,28.99,no,6,Bacterialblight,low
35.65,26.88,no,4,Bacterialblight,low
32.18,20.32,no,1,Bacterialblight,low
33.07,51.81,no,5,Bacterialblight,low
30.47,24.44,no,2,Bacterialblight,low
34.42,24.89,no,8,Bacterialblight,low
35.88,21.86,no,1,Bacterialblight,low
36.81,37.63,no,7,Bacterialblight,low
36.69,40.55,no,4,Bacterialblight,low
31.49,25.41,no,6,Bacterialblight,low
31.3,22.47,no,3,Bacterialblight,low
33.33,28.03,no,6,Bacterialblight,low
36.21,30.79,no,7,Bacterialblight,low
35.42,42.61,no,9,Bacterialblight,low
33.31,46.02,no,4,Bacterialblight,low
35.51,49.75,no,4,Bacterialblight,low
32.75,53.58,no,8,Bacterialblight,low
34.02,30.39,no,1,Bacterialblight,low
35.38,57.16,no,6,Bacterialblight,low
30.07,15.33,no,9,Bacterialblight,low
31.92,18.63,no,3,Bacterialblight,low
31.25,27.64,no,8,Bacterialblight,low
34.86,26.89,no,7,Bacterialblight,low
36.27,30.92,no,5,Bacterialblight,low
30.21,53.23,yes,8,Bacterialblight,low
36.64,38.16,no,1,Bacterialblight,low
34.32,20.04,no,4,Bacterialblight,low
36.11,54.42,no,2,Bacterialblight,low
32.76,34.04,no,3,Bacterialblight,low
36.17,54.35,no,3,Bacterialblight,low
34.16,31.3,no,1,Bacterialblight,low
30.34,22.1,no,9,Bacterialblight,low
28.78,72.24,no,3,Bacterialblight,medium
18.64,90.86,no,5,Bacterialblight,medium
23.2,89.44,no,9,Bacterialblight,medium
34.21,13.99,no,1,Bacterialblight,medium
26.02,79.56,no,2,Bacterialblight,medium
10.21,89.14,no,3,Bacterialblight,medium
29.37,79.22,no,7,Bacterialblight,medium
27.69,64.61,no,5,Bacterialblight,medium
28.08,75.04,no,6,Bacterialblight,medium
32.34,47.92,no,8,Bacterialblight,medium
22.9,95.81,no,8,Bacterialblight,medium
27.79,65.56,no,13,Bacterialblight,medium
26.53,64.35,no,10,Bacterialblight,medium
29.88,66.3,no,13,Bacterialblight,medium
26.62,63.26,no,11,Bacterialblight,medium
29.92,70.95,no,12,Bacterialblight,medium
26.66,60.59,yes,15,Bacterialblight,medium
28.56,77.98,yes,9,Bacterialblight,medium
27.23,62.08,yes,15,Bacterialblight,medium
28.44,70.28,yes,13,Bacterialblight,medium
29.88,62.89,yes,12,Bacterialblight,medium
26.38,78.27,yes,10,Bacterialblight,medium
27.2,65.85,yes,9,Bacterialblight,medium
26.19,66.79,yes,10,Bacterialblight,medium
27.72,62.39,yes,8,Bacterialblight,medium
28.82,76.66,yes,15,Bacterialblight,medium
28.14,68.96,yes,15,Bacterialblight,medium
28.64,76.58,yes,11,Bacterialblight,medium
29.14,70.38,yes,14,Bacterialblight,medium
29.45,65.93,yes,10,Bacterialblight,medium
28.9,72.44,yes,14,Bacterialblight,medium
28.82,67.18,yes,9,Bacterialblight,medium
26.66,63.89,yes,12,Bacterialblight,medium
27.96,62.21,yes,15,Bacterialblight,medium
28.37,69.59,yes,11,Bacterialblight,medium
27,67.21,yes,11,Bacterialblight,medium
26.73,78.21,no,12,Bacterialblight,medium
29.72,66.71,no,13,Bacterialblight,medium
29.67,70.72,no,9,Bacterialblight,medium
27.68,67.74,no,14,Bacterialblight,medium
26.28,73.96,no,13,Bacterialblight,medium
33.67,52.85,no,12,Bacterialblight,medium
29.73,71.65,yes,10,Bacterialblight,medium
28.19,72.62,yes,14,Bacterialblight,medium
26.6,79.61,yes,11,Bacterialblight,medium
27.37,71.67,no,15,Bacterialblight,medium
26.21,62.82,no,9,Bacterialblight,medium
28.96,76.58,no,13,Bacterialblight,medium
28.13,77.1,no,12,Bacterialblight,medium
34.31,18.58,yes,15,Bacterialblight,medium
10.17,96.93,no,8,Bacterialblight,medium
28.89,76.88,yes,13,Bacterialblight,medium
28.5,73.08,yes,12,Bacterialblight,medium
28.52,64.48,yes,13,Bacterialblight,medium
29.51,65.82,yes,9,Bacterialblight,medium
28.58,62.42,yes,12,Bacterialblight,medium
29.95,74.87,yes,13,Bacterialblight,medium
27.31,70.53,yes,9,Bacterialblight,medium
34.58,35.48,yes,12,Bacterialblight,medium
29.66,61.77,yes,10,Bacterialblight,medium
27.17,77.79,no,9,Bacterialblight,medium
27.4,70.95,no,10,Bacterialblight,medium
28.16,76.2,no,10,Bacterialblight,medium
29.15,67.52,yes,8,Bacterialblight,medium
28.15,60.02,yes,8,Bacterialblight,medium
28.32,61.77,yes,15,Bacterialblight,medium
27.77,78.73,yes,10,Bacterialblight,medium
27.53,67.01,yes,12,Bacterialblight,medium
27.38,60.41,yes,14,Bacterialblight,medium
27.65,74.05,yes,13,Bacterialblight,medium
28.45,63.94,no,10,Bacterialblight,medium
26.14,65.11,no,10,Bacterialblight,medium
29.18,76.74,no,15,Bacterialblight,medium
29.35,76.62,no,9,Bacterialblight,medium
26.74,61.01,yes,15,Bacterialblight,medium
28.23,60.66,yes,12,Bacterialblight,medium
29,74.33,yes,10,Bacterialblight,medium
26.22,60.69,yes,14,Bacterialblight,medium
26.41,74.18,yes,10,Bacterialblight,medium
26.75,70.83,yes,8,Bacterialblight,medium
28.59,72.11,yes,11,Bacterialblight,medium
26.07,73.23,yes,9,Bacterialblight,medium
27.04,65.55,yes,10,Bacterialblight,medium
26.71,75.98,no,8,Bacterialblight,medium
29.72,74.59,no,12,Bacterialblight,medium
28.35,72.61,no,14,Bacterialblight,medium
26.59,77.56,no,11,Bacterialblight,medium
27.37,70.52,yes,11,Bacterialblight,medium
29.19,78.72,no,15,Bacterialblight,medium
28.5,69.45,yes,9,Bacterialblight,medium
29.66,60.95,yes,12,Bacterialblight,medium
26.99,79.73,no,8,Bacterialblight,medium
28.95,72.06,yes,8,Bacterialblight,medium
28.58,69.7,yes,9,Bacterialblight,medium
28.07,61.61,no,15,Bacterialblight,medium
28.9,72.43,yes,13,Bacterialblight,medium
28.7,63.47,yes,9,Bacterialblight,medium
29.21,65.69,yes,12,Bacterialblight,medium
26,60.94,yes,12,Bacterialblight,medium
28.82,67.14,yes,12,Bacterialblight,medium
26.23,74.43,yes,8,Bacterialblight,medium
29.86,62.93,yes,10,Bacterialblight,medium
28.22,68.99,no,15,Bacterialblight,medium
26.14,67.72,no,13,Bacterialblight,medium
29.53,66.16,no,14,Bacterialblight,medium
28.05,67.13,no,11,Bacterialblight,medium
26.14,65.51,yes,15,Bacterialblight,medium
29.62,64.74,yes,9,Bacterialblight,medium
29.67,71.28,yes,11,Bacterialblight,medium
27.09,70.06,yes,10,Bacterialblight,medium
28.5,61.15,yes,10,Bacterialblight,medium
28.94,75.53,yes,14,Bacterialblight,medium
28.26,71.47,yes,15,Bacterialblight,medium
29.85,77.79,no,13,Bacterialblight,medium
29.17,73.88,no,14,Bacterialblight,medium
28.5,62.94,yes,9,Bacterialblight,medium
28.65,65.34,yes,15,Bacterialblight,medium
26.59,68.79,yes,12,Bacterialblight,medium
28.83,60.58,yes,8,Bacterialblight,medium
29.4,60.9,no,15,Bacterialblight,medium
28.02,66.62,yes,15,Bacterialblight,medium
29.52,69.93,yes,12,Bacterialblight,medium
28.76,70.33,yes,11,Bacterialblight,medium
29.11,79.28,yes,9,Bacterialblight,medium
28.47,72.02,yes,12,Bacterialblight,medium
27.86,72.32,yes,11,Bacterialblight,medium
28.28,63.21,no,13,Bacterialblight,medium
29.69,78.01,no,14,Bacterialblight,medium
29.06,69.69,yes,9,Bacterialblight,medium
29.13,65.89,no,8,Bacterialblight,medium
28.57,67.2,yes,15,Bacterialblight,medium
26.64,65.71,yes,11,Bacterialblight,medium
28.55,76.53,yes,9,Bacterialblight,medium
26.03,69.05,yes,9,Bacterialblight,medium
26.11,77.98,yes,15,Bacterialblight,medium
27.15,73.97,yes,8,Bacterialblight,medium
27.13,77.3,no,12,Bacterialblight,medium
28.5,60.63,no,15,Bacterialblight,medium
26.92,61.05,no,8,Bacterialblight,medium
29.15,66.54,no,13,Bacterialblight,medium
28.95,66.2,yes,8,Bacterialblight,medium
26.9,68.11,yes,10,Bacterialblight,medium
26.87,74.05,yes,10,Bacterialblight,medium
27.32,67.8,yes,12,Bacterialblight,medium
26,61.35,yes,15,Bacterialblight,medium
29.67,77.51,yes,9,Bacterialblight,medium
29.7,79.9,yes,8,Bacterialblight,medium
26.36,72.51,no,12,Bacterialblight,medium
27.69,67.62,no,15,Bacterialblight,medium
29.48,70.04,no,9,Bacterialblight,medium
26.47,74,no,14,Bacterialblight,medium
28.67,70.59,no,11,Bacterialblight,medium
26.2,70.35,no,13,Bacterialblight,medium
29.14,60.96,no,14,Bacterialblight,medium
27.83,77.37,no,10,Bacterialblight,medium
26.2,62.1,yes,11,Bacterialblight,medium
28.6,71.56,yes,11,Bacterialblight,medium
28.7,76.96,no,13,Bacterialblight,medium
29.83,74.79,no,10,Bacterialblight,medium
26.57,67.2,yes,15,Bacterialblight,medium
26.28,64.89,yes,10,Bacterialblight,medium
27.42,68.18,yes,8,Bacterialblight,medium
28.24,65.94,yes,14,Bacterialblight,medium
26.09,61.9,yes,15,Bacterialblight,medium
27.97,78.26,no,8,Bacterialblight,medium
27.97,78.09,no,14,Bacterialblight,medium
26.98,64.86,yes,12,Bacterialblight,medium
24.84,90.62,yes,13,anthracnose,high
18.4,92.14,yes,15,anthracnose,high
12.35,99.27,yes,15,anthracnose,high
36.55,49.16,yes,15,anthracnose,high
19.85,67.71,yes,14,anthracnose,high
33.62,15.45,no,20,anthracnose,high
25.79,67.71,yes,13,anthracnose,high
18.42,85.6,yes,16,anthracnose,high
23.93,73.27,yes,15,anthracnose,high
14.22,88.63,yes,19,anthracnose,high
24.49,73.33,yes,15,anthracnose,high
14.03,90.12,yes,16,anthracnose,high
20.64,71.15,yes,20,anthracnose,high
21.04,74.77,yes,19,anthracnose,high
18.69,97.89,yes,14,anthracnose,high
15.45,94.21,yes,12,anthracnose,high
23.61,88.6,yes,18,anthracnose,high
20.92,97.61,yes,12,anthracnose,high
21.15,96.28,yes,13,anthracnose,high
22.34,92.89,yes,16,anthracnose,high
20.93,83.59,yes,17,anthracnose,high
10.95,75.24,yes,19,anthracnose,high
14.72,75.79,yes,17,anthracnose,high
11,81.87,yes,13,anthracnose,high
13.3,66.89,yes,18,anthracnose,high
22.49,93.76,yes,13,anthracnose,high
12.97,80.94,yes,13,anthracnose,high
19.66,84.24,yes,17,anthracnose,high
13.54,79.14,yes,15,anthracnose,high
18.74,67.92,yes,18,anthracnose,high
17.14,81.18,yes,16,anthracnose,high
14.45,66.11,yes,18,anthracnose,high
10.05,99.77,yes,17,anthracnose,high
20.74,86.61,yes,16,anthracnose,high
11.72,91.26,yes,17,anthracnose,high
14.24,86.36,yes,15,anthracnose,high
10.24,93.18,yes,16,anthracnose,high
16.98,76.83,yes,13,anthracnose,high
16.68,90.99,yes,19,anthracnose,high
21.44,71.72,yes,13,anthracnose,high
24.43,68.07,yes,17,anthracnose,high
24.47,81.08,yes,17,anthracnose,high
16.99,66.51,yes,20,anthracnose,high
20.64,71.91,yes,17,anthracnose,high
20.12,88.2,yes,12,anthracnose,high
19.94,89.59,yes,16,anthracnose,high
21.53,73.82,yes,20,anthracnose,high
13.96,82.53,yes,14,anthracnose,high
12.13,80.63,yes,20,anthracnose,high
10.27,86.6,yes,18,anthracnose,high
16.58,95.25,yes,16,anthracnose,high
15.35,99.36,yes,20,anthracnose,high
19.17,70.93,yes,14,anthracnose,high
24.08,78.99,yes,18,anthracnose,high
16.02,75.32,yes,15,anthracnose,high
10.99,66.82,yes,18,anthracnose,high
16.09,94.05,yes,13,anthracnose,high
15.02,97.69,yes,13,anthracnose,high
15.25,86.11,yes,12,anthracnose,high
24.32,67.51,yes,14,anthracnose,high
17.99,87.8,yes,19,anthracnose,high
10.86,93.34,yes,20,anthracnose,high
23.02,97.2,yes,15,anthracnose,high
21.22,78.46,yes,14,anthracnose,high
22.02,84.34,yes,17,anthracnose,high
14.62,96.79,yes,18,anthracnose,high
18.7,81.94,yes,16,anthracnose,high
19.12,82.23,yes,13,anthracnose,high
25.12,82.21,yes,17,anthracnose,high
20.15,88.3,yes,15,anthracnose,high
16.93,66.69,yes,12,anthracnose,high
10.88,85.91,yes,17,anthracnose,high
14.44,78.57,yes,12,anthracnose,high
23.8,86.32,yes,16,anthracnose,high
23.45,79.41,yes,14,anthracnose,high
25.79,93.12,yes,14,anthracnose,high
17.62,67.13,yes,12,anthracnose,high
18.84,84.79,yes,20,anthracnose,high
20.23,90.49,yes,17,anthracnose,high
14.45,90.07,yes,19,anthracnose,high
17.15,76.1,yes,16,anthracnose,high
13.07,72.81,no,20,anthracnose,high
21.02,98.03,no,12,anthracnose,high
22.07,83.55,no,13,anthracnose,high
18.9,80.24,no,20,anthracnose,high
22.03,92.62,no,19,anthracnose,high
16.93,66.21,no,20,anthracnose,high
18.78,72.12,yes,16,anthracnose,high
12.66,96.99,yes,13,anthracnose,high
22.02,91.4,no,12,anthracnose,high
15.29,83.22,yes,14,anthracnose,high
20.39,71.22,yes,18,anthracnose,high
16.89,87.01,yes,17,anthracnose,high
20.41,94.6,yes,12,anthracnose,high
21.09,90.39,yes,19,anthracnose,high
25.76,89.69,no,16,anthracnose,high
11.72,70.26,yes,18,anthracnose,high
15.6,91.48,yes,17,anthracnose,high
25.24,71.2,yes,17,anthracnose,high
20.7,97.98,yes,20,anthracnose,high
16.98,80.2,yes,13,anthracnose,high
13.57,89.57,yes,16,anthracnose,high
13.87,96.12,yes,19,anthracnose,high
28.29,54.71,yes,13,anthracnose,high
25.66,89.49,no,15,anthracnose,high
17.07,95.13,no,15,anthracnose,high
27.35,53.98,no,20,anthracnose,high
14.26,91.78,yes,18,anthracnose,high
24.82,72.86,yes,20,anthracnose,high
25.93,69.32,yes,17,anthracnose,high
24.78,72.5,no,14,anthracnose,high
27.22,58.57,no,15,anthracnose,high
22.56,93.88,no,20,anthracnose,high
19.44,67.05,no,12,anthracnose,high
16.62,85.78,no,14,anthracnose,high
28.37,57.7,no,17,anthracnose,high
24.22,76.24,yes,15,anthracnose,high
20.66,73.57,yes,20,anthracnose,high
19.74,77.9,yes,18,anthracnose,high
26.73,63.6,yes,13,anthracnose,high
12.8,84.89,yes,16,anthracnose,high
17.84,68.79,yes,19,anthracnose,high
17.28,80.01,yes,15,anthracnose,high
15.24,99.87,yes,18,anthracnose,high
16.15,81.77,yes,17,anthracnose,high
16.6,91.29,yes,17,anthracnose,high
20.14,83.45,yes,16,anthracnose,high
20.09,92.34,yes,14,anthracnose,high
13.97,81.38,yes,15,anthracnose,high
17.99,77.57,yes,13,anthracnose,high
24.69,69.88,yes,15,anthracnose,high
20.56,98.38,yes,14,anthracnose,high
24.02,74.28,yes,14,anthracnose,high
20.88,84.79,yes,17,anthracnose,high
17.93,93.61,yes,15,anthracnose,high
18.31,68.49,yes,17,anthracnose,high
12.54,76.07,yes,20,anthracnose,high
20.77,82.99,yes,16,anthracnose,high
25.91,84.5,yes,13,anthracnose,high
11.55,91.82,yes,20,anthracnose,high
21.76,84.59,yes,13,anthracnose,high
15.56,83.7,yes,17,anthracnose,high
18.65,77.76,yes,18,anthracnose,high
20.38,65.82,yes,15,anthracnose,high
21.09,72.16,yes,15,anthracnose,high
18.59,77.41,yes,18,anthracnose,high
23.16,83.3,yes,19,anthracnose,high
13.54,77.25,yes,16,anthracnose,high
10.76,87.8,yes,14,anthracnose,high
17.62,74.13,yes,18,anthracnose,high
25.82,87.13,yes,19,anthracnose,high
16.68,90.86,yes,17,anthracnose,high
15.29,72.04,yes,19,anthracnose,high
16.02,93.41,yes,19,anthracnose,high
10.74,75.58,yes,16,anthracnose,high
13.36,86.21,yes,20,anthracnose,high
14.85,73.74,yes,14,anthracnose,high
22.06,91.71,yes,14,anthracnose,high
30.71,30.17,yes,19,anthracnose,high
20.56,65.94,yes,15,anthracnose,high
13.68,86.4,yes,19,anthracnose,high
31.92,47.45,yes,17,anthracnose,high
20.07,86.65,yes,14,anthracnose,high
33.79,48.93,yes,18,anthracnose,high
15.21,84.33,yes,13,anthracnose,high
18.57,87.48,yes,15,anthracnose,high
18.75,87.44,yes,17,anthracnose,high
20.74,72.67,yes,19,anthracnose,high
19.84,80.24,yes,18,anthracnose,high
13.86,73.6,yes,15,anthracnose,high
17.63,68.73,yes,17,anthracnose,high
14.63,65.68,yes,19,anthracnose,high
14.84,88.44,yes,18,anthracnose,high
22.79,89.28,yes,16,anthracnose,high
14.07,73.08,yes,16,anthracnose,high
12.48,98.8,yes,19,anthracnose,high
26.04,62.25,yes,20,anthracnose,high
11.94,95.68,yes,12,anthracnose,high
23.7,72.71,yes,19,anthracnose,high
21.43,80.56,yes,18,anthracnose,high
27.96,51.37,yes,14,anthracnose,high
35.71,47.86,no,17,anthracnose,high
19.59,69,yes,20,anthracnose,high
32.04,35.14,yes,20,anthracnose,high
13.38,73.5,yes,12,anthracnose,high
29.73,52.94,yes,16,anthracnose,high
25.06,98.58,yes,18,anthracnose,high
14.53,70.18,yes,19,anthracnose,high
35.59,25.06,yes,15,anthracnose,high
14.07,94.47,yes,15,anthracnose,high
30.49,41.4,yes,20,anthracnose,high
13.61,78.7,yes,19,anthracnose,high
19.04,94.22,yes,20,anthracnose,high
10.42,97.79,yes,13,anthracnose,high
28.94,60.03,yes,17,anthracnose,high
25.43,66.13,yes,15,anthracnose,high
29.85,56.42,yes,20,anthracnose,high
13.42,69.38,yes,14,anthracnose,high
14.05,70.13,yes,12,anthracnose,high
10.44,90.02,no,20,anthracnose,high
26.69,56.07,no,12,anthracnose,high
20.27,76.59,no,11,anthracnose,high
20.84,97.5,no,14,anthracnose,high
25.89,86.34,no,15,anthracnose,high
27.32,51.34,no,27,anthracnose,high
20.36,80.42,no,28,anthracnose,high
27.76,58.03,no,30,anthracnose,high
16.44,87.68,no,29,anthracnose,high
11.1,85.13,no,30,anthracnose,high
19.25,88.03,no,10,anthracnose,high
11.23,89.25,no,9,anthracnose,high
14.21,94.76,no,7,anthracnose,high
14.6,99.61,yes,12,anthracnose,high
26.26,62.95,yes,17,anthracnose,high
14.64,85.68,yes,19,anthracnose,high
29.22,60.48,yes,35,anthracnose,high
35.72,29.15,yes,6,anthracnose,low
36.28,32.89,no,4,anthracnose,low
28.77,52.12,no,2,anthracnose,low
36.97,33.36,no,4,anthracnose,low
29.17,54.8,no,5,anthracnose,low
34.92,45.41,no,2,anthracnose,low
30,59.92,no,5,anthracnose,low
30.94,38.71,no,4,anthracnose,low
30.49,28.17,no,3,anthracnose,low
36.5,16.95,no,4,anthracnose,low
31.57,22.22,no,6,anthracnose,low
36.65,11.43,no,7,anthracnose,low
31.38,22.69,no,5,anthracnose,low
30.19,38.51,yes,1,anthracnose,low
35.66,24.88,yes,4,anthracnose,low
34.67,27.93,yes,5,anthracnose,low
34.39,22.05,yes,2,anthracnose,low
31.67,29.68,yes,3,anthracnose,low
36.71,24.28,yes,1,anthracnose,low
35.67,20.45,yes,7,anthracnose,low
31.15,39.73,yes,3,anthracnose,low
35.82,29.19,yes,3,anthracnose,low
35.03,24.75,yes,4,anthracnose,low
36.73,48.15,no,4,anthracnose,low
34.65,23.17,no,3,anthracnose,low
35.74,37.1,yes,1,anthracnose,low
32.74,43.04,no,1,anthracnose,low
32.98,32.8,no,2,anthracnose,low
34.32,31.53,no,3,anthracnose,low
33.58,11.56,no,7,anthracnose,low
33.83,41.41,no,5,anthracnose,low
36.93,49.55,no,6,anthracnose,low
36.73,10.32,no,6,anthracnose,low
36.52,29.02,yes,6,anthracnose,low
35.69,41.78,no,3,anthracnose,low
30.62,37.06,no,2,anthracnose,low
33.33,11.81,no,2,anthracnose,low
30.27,23.59,no,7,anthracnose,low
30.25,48.77,no,3,anthracnose,low
32.53,10.89,no,4,anthracnose,low
31.92,47.53,no,4,anthracnose,low
32.95,21.53,yes,2,anthracnose,low
34.04,18.47,no,4,anthracnose,low
33.68,25.46,no,2,anthracnose,low
30.65,49.76,no,6,anthracnose,low
32.3,27.52,no,6,anthracnose,low
33.62,33.57,no,4,anthracnose,low
31.37,13.63,no,3,anthracnose,low
31.41,36.99,no,2,anthracnose,low
30.33,37.02,no,5,anthracnose,low
33.13,38.98,no,5,anthracnose,low
35.17,14.29,no,7,anthracnose,low
31.49,10.94,no,6,anthracnose,low
33.12,38.18,no,6,anthracnose,low
30.5,34.05,no,4,anthracnose,low
31.72,19.85,no,2,anthracnose,low
35.93,18,no,7,anthracnose,low
33.15,28.76,no,2,anthracnose,low
30.49,46.79,no,2,anthracnose,low
34.52,25.8,no,6,anthracnose,low
36.4,45.9,no,5,anthracnose,low
31.78,45.98,no,4,anthracnose,low
31.47,27.78,no,1,anthracnose,low
32.78,27.23,no,1,anthracnose,low
36.2,31.72,no,6,anthracnose,low
30.59,38.21,no,4,anthracnose,low
30.16,15.67,no,2,anthracnose,low
31.75,47.9,no,2,anthracnose,low
30.81,29.4,no,3,anthracnose,low
30.55,20.07,no,2,anthracnose,low
34.26,33.28,no,3,anthracnose,low
35.25,10.73,no,4,anthracnose,low
35.61,21.56,no,1,anthracnose,low
33.39,25.4,no,6,anthracnose,low
33.78,20.14,no,4,anthracnose,low
33.2,30,no,1,anthracnose,low
34.58,33.71,no,6,anthracnose,low
31.12,38.98,no,7,anthracnose,low
30.76,33.88,no,7,anthracnose,low
30.09,27.95,no,6,anthracnose,low
34.64,43.39,no,2,anthracnose,low
34.43,19.35,no,3,anthracnose,low
31.51,35.63,no,6,anthracnose,low
34.37,41.33,no,7,anthracnose,low
36.65,47.45,no,7,anthracnose,low
35.76,17,no,4,anthracnose,low
28.63,64.48,no,1,anthracnose,low
35.89,32.37,no,7,anthracnose,low
30.05,10.39,no,2,anthracnose,low
30.58,24.43,no,5,anthracnose,low
31.72,16.81,no,3,anthracnose,low
27.4,61.42,no,1,anthracnose,low
30.92,19.76,no,3,anthracnose,low
34.51,11.23,no,4,anthracnose,low
27.24,59.74,no,3,anthracnose,low
32.36,27.78,no,3,anthracnose,low
34.74,21.62,no,2,anthracnose,low
36.03,34.14,no,2,anthracnose,low
34.29,32.57,no,3,anthracnose,low
26.19,53.6,no,6,anthracnose,low
31.56,27.61,no,2,anthracnose,low
33.71,35.28,no,3,anthracnose,low
33.69,10.66,no,3,anthracnose,low
33.64,33.06,no,5,anthracnose,low
36.85,11.6,no,6,anthracnose,low
31.69,47.57,no,6,anthracnose,low
33.3,44.32,no,7,anthracnose,low
34.92,20.78,no,6,anthracnose,low
34.46,32.85,no,7,anthracnose,low
34.44,47.44,no,5,anthracnose,low
33.16,24.05,no,3,anthracnose,low
36.22,22.72,no,1,anthracnose,low
36.33,42.3,no,2,anthracnose,low
35.9,18.35,no,5,anthracnose,low
32.2,36.68,no,6,anthracnose,low
31.17,33.76,no,3,anthracnose,low
33.45,26.97,no,6,anthracnose,low
32.75,34.52,no,4,anthracnose,low
28.57,53.53,no,2,anthracnose,low
33.4,31.24,no,2,anthracnose,low
33.14,39.07,no,4,anthracnose,low
36.48,32.68,no,4,anthracnose,low
36.1,10.14,no,7,anthracnose,low
35.89,15.06,no,7,anthracnose,low
31.97,31.52,no,4,anthracnose,low
26.2,58.15,no,4,anthracnose,low
32.05,38.75,no,7,anthracnose,low
32.61,25.57,no,3,anthracnose,low
31.61,41.15,no,3,anthracnose,low
26.84,61.06,no,7,anthracnose,low
30.55,24.36,no,2,anthracnose,low
30.3,13.6,no,1,anthracnose,low
33.51,25.97,no,2,anthracnose,low
27.34,63.22,no,5,anthracnose,low
32.57,29.39,no,5,anthracnose,low
36.15,12.48,no,5,anthracnose,low
34.65,12.82,no,6,anthracnose,low
26.73,61.89,no,4,anthracnose,low
36.71,37.98,no,6,anthracnose,low
33.46,20.66,no,4,anthracnose,low
32.77,31.55,no,3,anthracnose,low
36.12,38.2,no,1,anthracnose,low
30.01,38.6,no,5,anthracnose,low
28.9,52.65,no,5,anthracnose,low
31.49,35.24,no,4,anthracnose,low
12.39,86.98,no,1,anthracnose,low
33.05,14.72,no,1,anthracnose,low
31.1,23.83,no,1,anthracnose,low
30.74,48.58,no,7,anthracnose,low
30.82,24.54,no,2,anthracnose,low
31.95,32.21,no,4,anthracnose,low
33.68,41.65,no,3,anthracnose,low
35.91,32.43,no,1,anthracnose,low
33.47,34.64,no,4,anthracnose,low
35.41,35.93,no,1,anthracnose,low
33.57,17.09,no,7,anthracnose,low
34.81,42.64,no,2,anthracnose,low
30.17,26.54,no,1,anthracnose,low
32.47,11.06,no,4,anthracnose,low
34.95,21.78,no,4,anthracnose,low
36.73,14.44,no,4,anthracnose,low
35.98,43.39,no,1,anthracnose,low
36.47,27.7,no,2,anthracnose,low
26.89,57.89,no,2,anthracnose,low
34.89,26.29,no,2,anthracnose,low
30.3,19.79,no,5,anthracnose,low
35,11.62,no,4,anthracnose,low
30.97,41.64,no,4,anthracnose,low
27.08,53.86,no,5,anthracnose,low
32.27,26.08,no,6,anthracnose,low
35.78,40.53,no,5,anthracnose,low
30.7,12.7,no,6,anthracnose,low
36.38,45.35,no,6,anthracnose,low
35.74,24.27,no,4,anthracnose,low
28.07,56.65,no,2,anthracnose,low
32.93,41.66,no,7,anthracnose,low
30.38,36.93,no,4,anthracnose,low
30.12,35.67,no,7,anthracnose,low
33.71,38.01,no,2,anthracnose,low
33.5,45.73,no,4,anthracnose,low
32.44,26.24,no,6,anthracnose,low
32.27,46.22,no,3,anthracnose,low
36.85,19.51,no,7,anthracnose,low
31.7,19.88,no,5,anthracnose,low
30.26,46.69,no,4,anthracnose,low
34.16,12.28,no,5,anthracnose,low
35.77,29.71,no,5,anthracnose,low
30.1,39.41,no,6,anthracnose,low
32.11,17.51,no,1,anthracnose,low
34.25,47.55,no,5,anthracnose,low
33.28,22.14,no,5,anthracnose,low
34.5,43.78,no,1,anthracnose,low
13.79,93.27,no,6,anthracnose,low
34.4,16.45,no,6,anthracnose,low
34.48,18.67,no,5,anthracnose,low
32.94,20.55,yes,5,anthracnose,low
31.49,10.46,yes,1,anthracnose,low
35.64,32.72,yes,3.8,anthracnose,low
35.49,13.09,yes,5,anthracnose,low
11.44,93.33,yes,5,anthracnose,low
33.73,33.35,yes,12,anthracnose,low
35.56,16.02,yes,15,anthracnose,low
26.21,59.02,yes,7,anthracnose,low
34.76,30.76,yes,5,anthracnose,low
31.38,19.81,yes,20.5,anthracnose,low
30.61,22.56,yes,20.7,anthracnose,low
29.54,51.45,no,13,anthracnose,medium
26.28,58.75,no,13,anthracnose,medium
36.29,17.13,yes,20,anthracnose,medium
27.52,57.6,no,8,anthracnose,medium
28.33,62.69,no,10,anthracnose,medium
27.58,64.96,no,8,anthracnose,medium
33.23,23.05,yes,11,anthracnose,medium
27.97,62.08,no,19,anthracnose,medium
15.63,84.99,no,8,anthracnose,medium
27.67,57.95,yes,4,anthracnose,medium
35.46,33.22,no,4,anthracnose,medium
25.19,94.29,no,8,anthracnose,medium
28.78,57.1,yes,16,anthracnose,medium
31.76,36.06,no,10,anthracnose,medium
28.59,57.83,yes,12,anthracnose,medium
27.06,58.5,yes,10,anthracnose,medium
28.26,57.71,yes,8,anthracnose,medium
27.8,57.32,no,20,anthracnose,medium
27.82,58.17,yes,19,anthracnose,medium
28.28,59.2,yes,5,anthracnose,medium
29.59,60.73,no,18,anthracnose,medium
27.4,56.2,yes,2,anthracnose,medium
27.28,51.99,no,14,anthracnose,medium
28.92,64.65,yes,20,anthracnose,medium
28.99,54.32,yes,7,anthracnose,medium
29.33,61.66,yes,4,anthracnose,medium
27.12,52.33,yes,10,anthracnose,medium
29.74,60.86,yes,7,anthracnose,medium
27.92,51.01,no,1,anthracnose,medium
29.37,64.49,no,4,anthracnose,medium
27.53,57.45,no,16,anthracnose,medium
29.82,57.34,no,1,anthracnose,medium
28.98,59.5,yes,20,anthracnose,medium
27.81,54.66,yes,6,anthracnose,medium
28.58,58.9,yes,8,anthracnose,medium
27.93,58.87,yes,13,anthracnose,medium
28.7,54.19,yes,4,anthracnose,medium
27.73,58.42,yes,16,anthracnose,medium
26.32,63.03,yes,19,anthracnose,medium
26.55,63.56,yes,6,anthracnose,medium
26.16,50.47,yes,3,anthracnose,medium
27,54.26,yes,13,anthracnose,medium
28.63,50.32,no,7,anthracnose,medium
29.79,63.65,yes,1,anthracnose,medium
27.28,55.93,yes,10,anthracnose,medium
28.89,61.02,yes,19,anthracnose,medium
27.12,54.39,yes,8,anthracnose,medium
28.64,60.4,yes,11,anthracnose,medium
28.63,52.49,yes,4,anthracnose,medium
27.7,51.14,yes,19,anthracnose,medium
26.24,63.27,yes,2,anthracnose,medium
28.28,62.42,no,1,anthracnose,medium
26.78,52.74,no,15,anthracnose,medium
28.84,62.46,no,3,anthracnose,medium
29.05,58.2,no,17,anthracnose,medium
27.9,62.4,no,13,anthracnose,medium
28.45,64.18,yes,6,anthracnose,medium
29.55,57.55,yes,5,anthracnose,medium
26.26,55.9,yes,5,anthracnose,medium
29.77,56.37,yes,14,anthracnose,medium
27.56,56.87,yes,1,anthracnose,medium
28.82,55.25,yes,13,anthracnose,medium
29.23,60.37,yes,16,anthracnose,medium
29.94,54.14,yes,19,anthracnose,medium
28.03,58.33,no,12,anthracnose,medium
27.4,63,yes,17,anthracnose,medium
27.17,56.41,no,12,anthracnose,medium
29.63,62.36,no,11,anthracnose,medium
26.49,54.13,yes,9,anthracnose,medium
27.62,58.05,no,10,anthracnose,medium
26.14,58.72,yes,8,anthracnose,medium
29.47,61.26,yes,4,anthracnose,medium
27.3,61.79,yes,16,anthracnose,medium
28.52,53.68,no,19,anthracnose,medium
27,50.18,no,10,anthracnose,medium
28.72,53.32,no,9,anthracnose,medium
28.1,62.6,no,6,anthracnose,medium
29.09,52.83,no,10,anthracnose,medium
28.51,63.49,yes,17,anthracnose,medium
27.25,59.35,yes,3,anthracnose,medium
28.83,52.56,yes,2,anthracnose,medium
27.28,62.2,yes,16,anthracnose,medium
28.01,55.22,no,6,anthracnose,medium
26.78,51.22,no,15,anthracnose,medium
26.48,64.48,no,3,anthracnose,medium
26.26,60.64,yes,19,anthracnose,medium
29.61,54.15,yes,9,anthracnose,medium
29.26,64.59,yes,8,anthracnose,medium
27.32,59.26,yes,8,anthracnose,medium
27.38,54.79,yes,1,anthracnose,medium
28.47,59.81,yes,17,anthracnose,medium
28.38,50.99,yes,14,anthracnose,medium
28.72,51.19,yes,3,anthracnose,medium
29.97,54.81,yes,1,anthracnose,medium
27.75,62.24,yes,19,anthracnose,medium
28.31,51.28,yes,18,anthracnose,medium
26.67,54.96,yes,7,anthracnose,medium
27.46,50.45,no,11,anthracnose,medium
29.5,55.83,no,11,anthracnose,medium
28.58,53.87,no,6,anthracnose,medium
29.88,58.92,yes,6,anthracnose,medium
28.48,57.21,no,3,anthracnose,medium
29.36,57.53,no,19,anthracnose,medium
26.37,63.97,no,10,anthracnose,medium
27.71,64.95,no,7,anthracnose,medium
29.6,57.47,yes,10,anthracnose,medium
26.85,51.34,yes,11,anthracnose,medium
28.13,59.79,yes,6,anthracnose,medium
28.65,61.4,yes,6,anthracnose,medium
26.74,62.66,yes,3,anthracnose,medium
28.45,52.76,no,14,anthracnose,medium
26.92,59.12,no,3,anthracnose,medium
29.57,59.22,yes,16,anthracnose,medium
27.52,63.76,no,18,anthracnose,medium
26.33,57.67,no,11,anthracnose,medium
28.99,61.43,no,4,anthracnose,medium
29.23,54.16,yes,7,anthracnose,medium
26.51,60.59,no,11,anthracnose,medium
26.17,57.56,no,6,anthracnose,medium
29.3,64.91,no,3,anthracnose,medium
26.3,61.01,no,1,anthracnose,medium
28.43,59.24,no,20,anthracnose,medium
29.36,50.17,yes,5,anthracnose,medium
27.22,59.59,yes,2,anthracnose,medium
26.56,54.13,yes,4,anthracnose,medium
27.51,57.59,yes,1,anthracnose,medium
29.94,55.84,yes,18,anthracnose,medium
28.21,52.7,yes,1,anthracnose,medium
28.38,53.07,yes,7,anthracnose,medium
29,56.31,yes,12,anthracnose,medium
28.9,61.95,yes,1,anthracnose,medium
28.8,51.53,yes,16,anthracnose,medium
27.38,60.56,yes,6,anthracnose,medium
27.79,57.02,yes,18,anthracnose,medium
26.06,57.27,yes,2,anthracnose,medium
26.49,51.1,yes,19,anthracnose,medium
29.85,55.25,yes,12,anthracnose,medium
26.01,57.16,yes,7,anthracnose,medium
28.33,59.14,yes,17,anthracnose,medium
19.52,81.92,yes,9,anthracnose,medium
26.9,61.5,no,13,anthracnose,medium
26.55,56.08,no,5,anthracnose,medium
26.93,51.49,no,1,anthracnose,medium
27.93,60.66,no,19,anthracnose,medium
29.53,56.92,no,19,anthracnose,medium
28.93,51.71,no,1,anthracnose,medium
29.31,53.39,no,2,anthracnose,medium
29.97,58.36,no,15,anthracnose,medium
29.6,54.56,no,4,anthracnose,medium
28.02,60.26,no,11,anthracnose,medium
26.81,64.22,no,5,anthracnose,medium
28.79,64.27,no,18,anthracnose,medium
26.38,64.56,no,14,anthracnose,medium
26.46,50.77,no,1,anthracnose,medium
26.17,59.31,no,17,anthracnose,medium
27.93,53.86,no,6,anthracnose,medium
27.08,61.6,no,2,anthracnose,medium
27.76,58.39,no,20,anthracnose,medium
27.45,55.32,no,8,anthracnose,medium
26.58,58.49,no,18,anthracnose,medium
29.88,59.4,no,16,anthracnose,medium
29.83,63.92,no,18,anthracnose,medium
29.29,63,no,15,anthracnose,medium
29.18,50.04,no,2,anthracnose,medium
28.24,62.66,no,1,anthracnose,medium
29.33,56.01,no,4,anthracnose,medium
26.99,53.18,yes,8,anthracnose,medium
29.23,55.98,yes,7,anthracnose,medium
29.09,61.87,yes,17,anthracnose,medium
29.4,56.09,yes,10,anthracnose,medium
26.56,57.82,yes,8,anthracnose,medium
27.7,62.79,yes,1,anthracnose,medium
29.01,64.55,yes,12,anthracnose,medium
15.49,84.07,yes,1,anthracnose,medium
26.67,63.98,yes,8,anthracnose,medium
27.84,55.27,yes,14,anthracnose,medium
33.64,35.1,yes,7,anthracnose,medium
13.03,73.01,yes,4,anthracnose,medium
24.92,64.69,no,11,aphid,high
14.93,85.88,no,3,aphid,high
25.82,63.75,no,2,aphid,high
20.42,64.45,no,8,aphid,high
31.98,64.27,no,5,aphid,high
20.61,57.11,no,1,aphid,high
21.69,63.39,no,14.5,aphid,high
18.56,56.63,no,4,aphid,high
30.3,64.35,no,5,aphid,high
26.6,68.87,no,13,aphid,high
31.28,69.06,no,7,aphid,high
23.04,66.54,no,17,aphid,high
29.9,64.95,no,16,aphid,high
28.35,67.34,no,15,aphid,high
25.17,60.43,no,13,aphid,high
18.06,67.7,no,18,aphid,high
25.92,69.68,no,1,aphid,high
19.62,54.27,no,9,aphid,high
27.5,62.85,no,11,aphid,high
26.97,69.76,no,19,aphid,high
21.51,67.13,no,18,aphid,high
27.17,60.78,no,10,aphid,high
24.56,66.98,no,19,aphid,high
29.32,68.56,no,4,aphid,high
30.87,68.91,no,19,aphid,high
22.9,64.86,no,13,aphid,high
27.14,62.44,no,13,aphid,high
24.49,64.2,no,18,aphid,high
30.17,69.97,no,7,aphid,high
27.04,69.36,no,3,aphid,high
26.08,64.69,no,2,aphid,high
26.53,63.08,no,7,aphid,high
25.82,63.61,no,17,aphid,high
27.22,64,no,14,aphid,high
28.4,68.64,no,12,aphid,high
23.75,66.53,no,10,aphid,high
21.02,67.19,no,11,aphid,high
24.85,60.33,no,15,aphid,high
21.75,66.44,no,1,aphid,high
27.04,61.15,no,3,aphid,high
22.27,61.65,no,14,aphid,high
28.58,62,no,13,aphid,high
23.18,65.56,no,5,aphid,high
24.1,68.84,no,13,aphid,high
24.45,61.76,no,13,aphid,high
21.92,67.99,no,14,aphid,high
27.08,69.91,no,4,aphid,high
22.19,66.54,no,15,aphid,high
27.19,67.31,no,6,aphid,high
27.19,69.04,no,18,aphid,high
30.43,63.93,no,2,aphid,high
22.6,66.02,no,15,aphid,high
23.5,63.34,no,20,aphid,high
30.42,62.37,no,15,aphid,high
27.38,65.53,no,4,aphid,high
24.45,69.77,no,12,aphid,high
22.53,66.74,no,16,aphid,high
24.08,65.46,no,8,aphid,high
23.97,62.72,no,19,aphid,high
31.26,68.31,no,20,aphid,high
25.13,66.73,no,7,aphid,high
24.68,62.51,no,12,aphid,high
21.72,69.83,no,1,aphid,high
28.73,65.11,no,17,aphid,high
23.62,65.34,no,10,aphid,high
30.02,66.71,no,18,aphid,high
29.98,61.06,no,2,aphid,high
22.2,62.96,no,12,aphid,high
27.32,65.12,no,10,aphid,high
27.98,65.76,no,5,aphid,high
23.94,69.91,no,15,aphid,high
31.58,63.14,no,9,aphid,high
25.66,67.25,no,6,aphid,high
21.84,65.67,no,1,aphid,high
27.07,64.78,no,13,aphid,high
24.15,67.29,no,13,aphid,high
22.25,61.24,no,6,aphid,high
26.07,67.82,no,4,aphid,high
25.41,69.49,no,6,aphid,high
22.19,60.05,no,19,aphid,high
22.54,64.66,no,3,aphid,high
29.35,66.37,no,1,aphid,high
22.17,67.68,no,18,aphid,high
30.16,67.53,no,15,aphid,high
28.94,64.19,no,5,aphid,high
29.39,61.14,no,16,aphid,high
26.84,60.1,no,17,aphid,high
30.7,68.52,no,6,aphid,high
27.07,68.08,no,14,aphid,high
30.75,63.47,no,20,aphid,high
30.66,66.25,no,19,aphid,high
25.9,69.5,no,13,aphid,high
26.95,60.74,no,19,aphid,high
27.64,66.65,no,15,aphid,high
24.43,61.35,no,2,aphid,high
23.7,60.98,no,10,aphid,high
22.93,68.92,no,2,aphid,high
25.71,63.63,no,17,aphid,high
22.78,63.03,no,18,aphid,high
23.62,67.34,no,13,aphid,high
22.48,68.38,no,2,aphid,high
40.48,4.07,no,6,aphid,high
23.29,60.76,no,3,aphid,high
15.43,18.81,no,12,aphid,high
23.27,63.15,no,2,aphid,high
24.31,68.78,no,12,aphid,high
25.41,67.76,no,7,aphid,high
29.91,66.85,no,18,aphid,high
27.04,62.62,no,11,aphid,high
30.76,63.95,no,15,aphid,high
28.68,64.75,no,18,aphid,high
27.75,65.4,no,6,aphid,high
25.55,69.19,no,11,aphid,high
4.78,26.25,no,2,aphid,high
23.65,61.92,no,18,aphid,high
18.89,50.71,no,11,aphid,high
27.15,64.11,no,18,aphid,high
30.55,64.35,no,4,aphid,high
26.87,64.5,no,18,aphid,high
25.95,62.76,no,5,aphid,high
27.41,67.34,no,1,aphid,high
31.19,63.65,no,5,aphid,high
31.68,64.6,no,7,aphid,high
29.56,66.25,no,9,aphid,high
23.24,62.63,no,12,aphid,high
27.01,62.36,no,16,aphid,high
23.2,68.9,no,16,aphid,high
24.89,62.76,no,8,aphid,high
30.09,66.59,no,8,aphid,high
23.9,69.49,no,1,aphid,high
24.18,66.76,no,11,aphid,high
24.19,61.32,no,14,aphid,high
25.85,67.18,no,3,aphid,high
21.8,65.14,no,16,aphid,high
24.06,62.08,no,16,aphid,high
30.42,64.23,no,7,aphid,high
26.52,68.43,no,17,aphid,high
22.17,66.23,no,2,aphid,high
25.12,61.63,no,8,aphid,high
23.96,69.1,no,5,aphid,high
30.66,69.77,no,18,aphid,high
25.6,69.18,no,8,aphid,high
30.21,66.45,no,7,aphid,high
21.79,60.29,no,6,aphid,high
24.8,64.4,no,5,aphid,high
28.36,69.75,no,9,aphid,high
28.73,63.99,no,7,aphid,high
27.84,62.7,no,18,aphid,high
24.76,65.4,no,7,aphid,high
5.84,20.12,no,2,aphid,high
27.9,64.56,no,18,aphid,high
30.02,64.39,no,16,aphid,high
3.67,36.15,no,2,aphid,high
22.37,69.63,no,18,aphid,high
23.37,65.36,no,8,aphid,high
30.43,60.34,no,5,aphid,high
32.95,32.24,no,4,aphid,high
25.33,65.16,no,17,aphid,high
23.32,66.15,no,13,aphid,high
27.48,69.93,no,18,aphid,high
31.65,60.22,no,13,aphid,high
28.25,69.3,no,9,aphid,high
27.55,60.04,no,20,aphid,high
26.14,68.31,no,6,aphid,high
10.93,13.09,no,6,aphid,high
26.49,61.29,no,19,aphid,high
20.69,63.8,no,6,aphid,high
32.91,29.86,no,17,aphid,high
28.33,66.37,no,16,aphid,high
25.83,61.87,no,13,aphid,high
27.16,67.58,no,16,aphid,high
21.87,69.06,no,17,aphid,high
26.4,60.7,no,2,aphid,high
10.35,7.87,no,16,aphid,high
22.62,66.77,no,15,aphid,high
40.19,12.09,no,14,aphid,high
27.11,67.2,no,2,aphid,low
19.89,66.18,no,8,aphid,low
7.21,81.62,no,6,aphid,low
30.31,60.03,no,15,aphid,low
7.58,17.87,no,15,aphid,low
17.52,7.94,no,17,aphid,low
13.08,0.66,yes,9,aphid,low
8.74,22.6,yes,14,aphid,low
17.65,18.15,yes,5,aphid,low
10.82,9.4,yes,8,aphid,low
6.02,23.53,yes,20,aphid,low
13.7,3.25,yes,9,aphid,low
9.47,87.03,yes,7,aphid,low
15.58,6.6,yes,16,aphid,low
19.7,52.84,yes,18,aphid,low
6.32,0.43,yes,5,aphid,low
24.08,63.62,yes,15,aphid,low
5.57,21.5,yes,13,aphid,low
0.75,37.58,yes,11,aphid,low
1.36,21.48,yes,16,aphid,low
7.27,6.97,yes,10,aphid,low
0.79,24.58,yes,17,aphid,low
0.84,20.01,yes,5,aphid,low
26.76,66.43,yes,3,aphid,low
17.86,32.77,yes,18,aphid,low
17.67,83.39,yes,9,aphid,low
0.96,34.48,yes,12,aphid,low
14.37,4.93,yes,4,aphid,low
4.6,9.79,yes,19,aphid,low
1.59,87.15,yes,8,aphid,low
4.39,6.21,yes,8,aphid,low
10.12,20.99,yes,7,aphid,low
1.98,24.97,yes,11,aphid,low
9.77,87.44,yes,14,aphid,low
3.92,2.46,yes,9,aphid,low
5.11,5.86,yes,4,aphid,low
1.1,32.84,yes,3,aphid,low
0.89,23.85,yes,6,aphid,low
4.18,14.8,yes,17,aphid,low
2.8,5.96,yes,7,aphid,low
11.32,23.21,yes,2,aphid,low
4.25,7.8,yes,9,aphid,low
8.62,9,yes,9,aphid,low
11.01,39.13,yes,10,aphid,low
15.73,8.23,yes,3,aphid,low
12.18,84.96,yes,14,aphid,low
8.13,32.85,yes,7,aphid,low
1.16,5.58,yes,9,aphid,low
0.42,1.24,yes,4,aphid,low
7.79,81.45,yes,15,aphid,low
16.64,9.62,yes,10,aphid,low
1.49,89.27,yes,8,aphid,low
1.62,36.41,yes,11,aphid,low
5.26,88.74,yes,7,aphid,low
4.01,4.36,yes,19,aphid,low
3.54,38.32,yes,13,aphid,low
2.38,15.63,yes,16,aphid,low
9.18,22.08,yes,13,aphid,low
11.35,30.98,yes,18,aphid,low
15.48,37.11,yes,2,aphid,low
9.57,0.29,yes,5,aphid,low
17.79,1.85,yes,20,aphid,low
10.86,87.52,yes,10,aphid,low
8.11,7.38,yes,9,aphid,low
0.41,19.03,yes,12,aphid,low
9.42,38.06,yes,6,aphid,low
36.94,34.91,yes,13,aphid,low
7.65,38.29,yes,6,aphid,low
15.9,38.67,yes,14,aphid,low
11.82,12.29,yes,18,aphid,low
31.19,12.66,yes,1,aphid,low
0.11,9.26,yes,2,aphid,low
11.37,38.26,yes,18,aphid,low
13.99,22.48,yes,17,aphid,low
3.74,29.42,yes,17,aphid,low
36.1,30.06,yes,19,aphid,low
16.51,11.48,yes,15,aphid,low
17.51,26.61,yes,12,aphid,low
43.37,26.46,yes,2,aphid,low
4.24,80.59,yes,7,aphid,low
10.29,6.03,yes,3,aphid,low
1.73,5.27,yes,11,aphid,low
13.81,33.93,yes,1,aphid,low
6.39,83.63,yes,7,aphid,low
4.45,80.73,yes,18,aphid,low
4.49,5.71,yes,9,aphid,low
17.68,19.64,yes,17,aphid,low
11.55,0.74,yes,5,aphid,low
15.06,22.15,yes,4,aphid,low
2,6.63,yes,5,aphid,low
7.91,10.46,yes,15,aphid,low
13.54,13.53,yes,18,aphid,low
9.41,1.2,yes,5,aphid,low
11.89,8.25,yes,4,aphid,low
2.18,82.65,yes,14,aphid,low
13.09,9.49,yes,19,aphid,low
36.95,35.22,yes,16,aphid,low
4.5,19.97,yes,14,aphid,low
13.43,16.4,yes,20,aphid,low
15.24,88.73,yes,19,aphid,low
2.61,30.76,yes,13,aphid,low
8.4,8.88,yes,8,aphid,low
10.1,87.51,yes,8,aphid,low
17.07,31.24,yes,5,aphid,low
14.45,29.59,yes,11,aphid,low
13.87,18.68,yes,18,aphid,low
12.85,3.59,yes,20,aphid,low
43.49,5.28,yes,3,aphid,low
14.84,39.97,yes,8,aphid,low
39.33,10.25,yes,4,aphid,low
12.03,36.48,yes,12,aphid,low
12.2,31.93,yes,10,aphid,low
45.71,39.94,yes,3,aphid,low
13.08,0.04,yes,14,aphid,low
12.35,2.47,yes,11,aphid,low
41.05,28.23,yes,10,aphid,low
0.99,31,yes,20,aphid,low
4.14,26.91,yes,7,aphid,low
17.54,0.07,yes,16,aphid,low
8.76,16.12,yes,17,aphid,low
12.79,88.09,yes,20,aphid,low
39.4,16.62,yes,8,aphid,low
10.26,11,yes,11,aphid,low
10.94,85.43,yes,16,aphid,low
41.99,11.77,yes,16,aphid,low
5.88,27.74,yes,3,aphid,low
13.6,81.14,yes,3,aphid,low
45.74,39.64,yes,10,aphid,low
34.25,0.78,yes,13,aphid,low
0,34.35,yes,6,aphid,low
30.76,3.76,yes,18,aphid,low
17.46,17.51,yes,8,aphid,low
16.57,28.11,yes,6,aphid,low
1.44,88.13,yes,2,aphid,low
13.1,21.86,yes,7,aphid,low
31,16.6,yes,7,aphid,low
17.48,11.95,yes,2,aphid,low
5.35,34.37,yes,15,aphid,low
14.35,3.1,yes,13,aphid,low
7.9,31.61,yes,14,aphid,low
5.89,34.24,yes,5,aphid,low
5.05,13.61,yes,2,aphid,low
35.2,2.7,yes,5,aphid,low
5.59,18.61,yes,19,aphid,low
31.94,69.39,yes,14,aphid,low
1.81,16.46,yes,15,aphid,low
37.22,7.98,yes,7,aphid,low
36.43,27.7,yes,9,aphid,low
12.24,82.41,yes,20,aphid,low
15.64,20.1,yes,9,aphid,low
35.47,20.1,yes,17,aphid,low
29.09,68.8,yes,6,aphid,low
15.43,7.93,yes,16,aphid,low
33.52,80.12,yes,2,aphid,low
39.89,15.6,yes,3,aphid,low
31.7,15.06,yes,16,aphid,low
37.5,9.96,yes,3,aphid,low
37.12,4.6,yes,16,aphid,low
34.49,37.57,yes,19,aphid,low
17.54,15.77,yes,20,aphid,low
7.68,34.68,yes,12,aphid,low
18.33,65.84,yes,20,aphid,medium
19.31,62.55,yes,15,aphid,medium
19.6,68.7,yes,8,aphid,medium
19.9,53.04,yes,10,aphid,medium
20.9,55.31,yes,6,aphid,medium
20.28,69.41,yes,17,aphid,medium
19.17,50.66,yes,20,aphid,medium
18.07,54.22,yes,4,aphid,medium
18.34,57.36,yes,16,aphid,medium
19.25,66.4,no,9,aphid,medium
18.14,68.75,no,11,aphid,medium
19.54,56.32,yes,19,aphid,medium
20.64,60.19,yes,12,aphid,medium
18.66,55.67,no,3,aphid,medium
20.48,64.39,no,9,aphid,medium
18.4,60.7,no,19,aphid,medium
20.31,57.47,no,4,aphid,medium
18.28,67.26,no,7,aphid,medium
20.18,52.04,no,10,aphid,medium
19.78,59.48,yes,9,aphid,medium
18.01,66.31,yes,6,aphid,medium
20.1,59.8,yes,5,aphid,medium
20.41,52.92,yes,6,aphid,medium
18.91,66.7,yes,5,aphid,medium
19.67,52.98,no,13,aphid,medium
19.36,52.22,no,10,aphid,medium
18.72,52.74,no,8,aphid,medium
18.85,53.22,no,5,aphid,medium
20.04,67.38,no,15,aphid,medium
20.56,56.04,no,8,aphid,medium
19.71,65.37,no,6,aphid,medium
20.38,63.83,no,1,aphid,medium
18.98,64.45,no,13,aphid,medium
18.52,52.71,yes,17,aphid,medium
19.05,58.26,yes,13,aphid,medium
20.57,51.13,yes,14,aphid,medium
19,69.91,yes,19,aphid,medium
19.17,54.66,yes,13,aphid,medium
20.78,61.65,yes,16,aphid,medium
19.67,61.57,yes,5,aphid,medium
18.11,60.05,yes,12,aphid,medium
20.92,59.37,yes,8,aphid,medium
19.94,64.53,yes,10,aphid,medium
19.07,54.92,yes,13,aphid,medium
18.24,55.45,yes,9,aphid,medium
19.79,59.8,yes,10,aphid,medium
20.51,63.99,yes,4,aphid,medium
19.47,58.87,no,13,aphid,medium
18.18,59.74,no,12,aphid,medium
20.85,64.21,no,17,aphid,medium
18.49,62.29,no,17,aphid,medium
18.19,52.19,no,9,aphid,medium
19.71,60.45,no,18,aphid,medium
18.06,56.25,no,8,aphid,medium
20.75,63.7,no,1,aphid,medium
20.89,61.06,no,6,aphid,medium
18.36,66.38,no,1,aphid,medium
19.96,61.75,no,12,aphid,medium
18.85,54.24,no,11,aphid,medium
19.5,59.24,no,19.8,aphid,medium
20.65,54.32,no,4,aphid,medium
20.99,64.71,no,12,aphid,medium
18.05,55.69,yes,14,aphid,medium
18.57,54.89,yes,3,aphid,medium
19.37,65.76,yes,13,aphid,medium
18.73,65.89,yes,4,aphid,medium
19.91,60.16,no,20,aphid,medium
18.01,67.39,no,20,aphid,medium
19.04,58.33,no,12,aphid,medium
21,59.01,no,12,aphid,medium
20.4,50.44,no,17,aphid,medium
19.61,56.09,no,19,aphid,medium
20.96,66.48,no,19,aphid,medium
19.18,56.14,no,12,aphid,medium
19.08,63.33,no,4,aphid,medium
18.12,64.6,no,18,aphid,medium
20.54,65.45,no,15,aphid,medium
20.12,64.23,yes,14,aphid,medium
18.17,52.79,yes,10,aphid,medium
20.02,59.58,yes,19,aphid,medium
18.78,60.15,yes,5,aphid,medium
20.97,57.3,yes,13,aphid,medium
20.4,50.94,yes,19,aphid,medium
19.64,51.45,yes,16,aphid,medium
20.85,53.86,yes,17,aphid,medium
23.33,69.51,no,8,aphid,medium
20.78,59.99,no,18,aphid,medium
20.21,53.38,no,3,aphid,medium
20.95,50.71,no,2,aphid,medium
19.35,61.6,no,1,aphid,medium
20.68,68.97,no,20,aphid,medium
19.76,51.92,no,14,aphid,medium
20.8,59.4,no,14,aphid,medium
18.84,69.45,no,4,aphid,medium
20.6,61.7,no,16,aphid,medium
19.86,51.42,no,16,aphid,medium
19.21,65.58,no,4,aphid,medium
19.84,51.5,no,14,aphid,medium
18.66,53.45,no,20,aphid,medium
19.41,68.97,no,20,aphid,medium
14.03,83.45,no,3,aphid,medium
23.08,67.47,no,20,aphid,medium
20.58,56.28,no,8,aphid,medium
11.11,2.91,no,14,aphid,medium
19.31,67.24,no,11,aphid,medium
18.25,64.6,no,6,aphid,medium
18.3,60.82,no,20,aphid,medium
18.43,54.7,no,16.5,aphid,medium
20.94,60.88,no,15,aphid,medium
19.77,50,yes,16,aphid,medium
18.25,59.72,yes,20,aphid,medium
19.72,56.24,yes,9,aphid,medium
19.73,54.74,yes,20,aphid,medium
18.63,51.4,yes,18,aphid,medium
18.86,55.49,yes,10,aphid,medium
20.6,62.48,yes,2,aphid,medium
20.4,69.87,yes,15,aphid,medium
18.75,65.67,yes,17,aphid,medium
20.39,54.42,yes,12,aphid,medium
19.24,54.69,yes,20,aphid,medium
20.45,64.61,yes,5,aphid,medium
20.43,50.48,no,16,aphid,medium
18.89,58.26,no,9,aphid,medium
18.53,53.21,no,12,aphid,medium
18.03,59.24,no,8,aphid,medium
19.53,66.76,yes,3,aphid,medium
18.86,55.56,yes,8,aphid,medium
20.63,59.4,yes,18,aphid,medium
19.68,51.04,yes,12,aphid,medium
20.53,65.77,yes,9,aphid,medium
20.42,67.69,yes,10,aphid,medium
20.77,58.15,yes,8,aphid,medium
20.58,62.04,no,11,aphid,medium
19.21,52.24,no,2,aphid,medium
19.93,59.29,no,2,aphid,medium
18.1,56.59,no,15,aphid,medium
19.51,60.52,no,6,aphid,medium
18.86,62.71,no,4,aphid,medium
19.52,66.42,no,19.1,aphid,medium
18.35,61.09,no,9,aphid,medium
18.32,62,yes,3,aphid,medium
18.63,67.46,yes,4,aphid,medium
19.41,66.88,yes,19,aphid,medium
18.41,59.78,yes,1,aphid,medium
19.97,65.36,yes,16,aphid,medium
18.41,59.31,yes,20,aphid,medium
18.12,50.34,yes,9,aphid,medium
18.8,69.01,yes,8,aphid,medium
19.19,66.98,yes,5,aphid,medium
20.07,60.21,yes,1,aphid,medium
18.06,66.24,yes,15,aphid,medium
18.96,55.64,yes,15,aphid,medium
20.76,59.98,yes,17,aphid,medium
18.39,63.11,yes,17.8,aphid,medium
20.52,65.36,yes,19,aphid,medium
19.16,58.91,yes,18,aphid,medium
20.86,68.64,yes,1,aphid,medium
18.25,58.87,yes,12,aphid,medium
18.63,61.15,no,19,aphid,medium
19.3,59.27,yes,8,aphid,medium
19.14,58.74,no,4.9,aphid,medium
36.05,69.81,yes,16,whiteflies,high
22.97,52.75,no,22,whiteflies,high
17.2,27.89,yes,22,whiteflies,high
33.37,64.56,yes,28,whiteflies,high
33.07,61.81,no,17,whiteflies,high
36.6,60.75,yes,16,whiteflies,high
24.19,55.76,no,29,whiteflies,high
32.77,62.86,no,15,whiteflies,high
34.08,65.97,no,19,whiteflies,high
36.54,62.11,no,16,whiteflies,high
35.39,67.99,no,18,whiteflies,high
25.29,59.47,no,16,whiteflies,high
29.57,62.63,no,27,whiteflies,high
28.33,62.36,no,20,whiteflies,high
30.71,66.61,yes,30,whiteflies,high
28.54,65.49,no,24,whiteflies,high
33.17,68.09,no,21,whiteflies,high
36.84,67.74,yes,17,whiteflies,high
32.39,69.68,no,18,whiteflies,high
36.14,63.75,yes,20,whiteflies,high
34.41,63.63,yes,15,whiteflies,high
34.01,65.55,yes,26,whiteflies,high
36.07,69.61,no,30,whiteflies,high
30.17,64.45,no,30,whiteflies,high
31.04,61.17,no,18,whiteflies,high
31.6,60.34,no,21,whiteflies,high
34.5,61.88,no,21,whiteflies,high
36.47,61.1,no,16,whiteflies,high
29.33,63.55,no,30,whiteflies,high
35.81,61.15,no,28,whiteflies,high
28.96,63.23,no,19,whiteflies,high
32.5,66.12,no,19,whiteflies,high
34.44,62.68,yes,16,whiteflies,high
34.44,63.84,no,25,whiteflies,high
35.49,66.86,no,19,whiteflies,high
30.85,61.05,no,16,whiteflies,high
32.85,63.98,no,22,whiteflies,high
33.97,68.38,yes,15,whiteflies,high
35.12,66.38,no,25,whiteflies,high
34.57,60.71,yes,17,whiteflies,high
34.18,67.63,yes,24,whiteflies,high
33.97,67.73,yes,29,whiteflies,high
32.7,62.77,yes,20,whiteflies,high
34.29,60.74,no,19,whiteflies,high
36.64,67.2,yes,24,whiteflies,high
28.05,66.41,yes,30,whiteflies,high
34.64,68.97,yes,21,whiteflies,high
32.62,67.62,yes,15,whiteflies,high
33.43,69.03,yes,20,whiteflies,high
34.92,61.66,no,28,whiteflies,high
31.23,63.63,no,25,whiteflies,high
36.18,68.39,no,15,whiteflies,high
36.79,63.53,no,30,whiteflies,high
35.86,64.26,no,21,whiteflies,high
32.92,63.12,no,30,whiteflies,high
30.3,63.28,yes,27,whiteflies,high
28.24,67.22,yes,29,whiteflies,high
30.61,66.22,yes,21,whiteflies,high
34.16,67.86,yes,24,whiteflies,high
35.77,64.71,yes,25,whiteflies,high
35.81,66.33,yes,20,whiteflies,high
29.18,61.22,yes,28,whiteflies,high
32.03,64.35,yes,24,whiteflies,high
31.93,61.15,no,18,whiteflies,high
35.74,65.38,no,19,whiteflies,high
32.3,63.94,no,26,whiteflies,high
31.92,61.19,no,18,whiteflies,high
33.67,64.67,yes,22,whiteflies,high
34.63,67.88,no,23,whiteflies,high
33.47,61.25,yes,16,whiteflies,high
32.11,66.04,no,22,whiteflies,high
30.45,62.48,yes,27,whiteflies,high
36.27,65.87,no,26,whiteflies,high
31.29,67.66,no,24,whiteflies,high
33.96,69.38,no,17,whiteflies,high
34.76,60.97,yes,23,whiteflies,high
34.74,64.28,no,28,whiteflies,high
33.84,61.38,yes,23,whiteflies,high
33.19,66.78,no,17,whiteflies,high
12.8,19.23,yes,20,whiteflies,high
28.82,62.27,yes,30,whiteflies,high
23.22,68.35,yes,26,whiteflies,high
34.93,67.19,yes,23,whiteflies,high
30.27,60.02,no,18,whiteflies,high
34.69,69.5,no,30,whiteflies,high
33.19,69.83,no,20,whiteflies,high
33.35,64.86,no,22,whiteflies,high
28.5,67.19,no,15,whiteflies,high
32.83,61.36,no,22,whiteflies,high
30,66.29,no,27,whiteflies,high
35.11,60.57,no,26,whiteflies,high
34.52,62.52,no,30,whiteflies,high
34.59,69.8,no,23,whiteflies,high
31.13,66.63,no,27,whiteflies,high
34.33,65.04,no,24,whiteflies,high
32.91,65.9,no,20,whiteflies,high
36,65.34,no,28,whiteflies,high
31.57,65.77,no,22,whiteflies,high
33.28,64.73,no,16,whiteflies,high
32.95,64.59,yes,17,whiteflies,high
25.47,50.86,yes,28,whiteflies,high
29.31,61.11,yes,29,whiteflies,high
34.1,65.43,yes,25,whiteflies,high
34.08,66.28,yes,30,whiteflies,high
35.65,64.17,yes,23,whiteflies,high
31.09,66.94,yes,16,whiteflies,high
6.24,20.95,no,16,whiteflies,high
28.22,67.6,no,23,whiteflies,high
30.88,65.52,no,23,whiteflies,high
35.86,62.31,yes,19,whiteflies,high
1.66,9.46,yes,16,whiteflies,high
28.1,61.22,yes,18,whiteflies,high
35.24,69.72,no,28,whiteflies,high
36.64,62.3,yes,30,whiteflies,high
30.29,68.27,yes,20,whiteflies,high
35.49,60.84,yes,22,whiteflies,high
22.6,63.06,yes,25,whiteflies,high
28.2,62.31,yes,24,whiteflies,high
17.93,12.6,no,17,whiteflies,high
31.01,61.99,no,21,whiteflies,high
32.29,64.98,no,30,whiteflies,high
28.64,63.28,no,20,whiteflies,high
30.53,66.98,yes,16,whiteflies,high
14.78,31.54,yes,20,whiteflies,high
31.12,69.65,no,15,whiteflies,high
34.16,68.1,yes,19,whiteflies,high
29.56,66.46,no,30,whiteflies,high
35.34,67.01,yes,17,whiteflies,high
2.81,13.35,yes,27,whiteflies,high
36.75,60.24,no,20,whiteflies,high
5.95,38.43,yes,28,whiteflies,high
32.16,63.47,yes,26,whiteflies,high
33.49,67.81,yes,26,whiteflies,high
28.82,69.5,yes,30,whiteflies,high
36.63,63.76,yes,27,whiteflies,high
29.26,60.48,yes,21,whiteflies,high
18.2,86.85,no,20,whiteflies,high
35.82,69.28,no,27,whiteflies,high
32.52,69.49,no,22,whiteflies,high
7.45,18.68,no,24,whiteflies,high
32.01,61.93,no,17,whiteflies,high
27.31,58.26,no,15,whiteflies,high
31.74,65.76,no,21,whiteflies,high
23.31,59.28,no,21,whiteflies,high
6.01,39.04,no,26,whiteflies,high
33.11,66.77,no,24,whiteflies,high
0.9,30.35,no,18,whiteflies,high
28.81,67.49,no,22,whiteflies,high
32.15,64.64,no,21,whiteflies,high
29,61.75,no,19,whiteflies,high
28.24,67.25,no,24,whiteflies,high
33.17,60.49,no,17,whiteflies,high
36.19,64.59,yes,20,whiteflies,high
35.12,69.84,yes,28,whiteflies,high
31.24,64.79,yes,22,whiteflies,high
28.28,61.8,yes,99,whiteflies,high
32.4,67.82,no,17,whiteflies,high
31.27,69.32,no,17,whiteflies,high
30.64,66.55,no,20,whiteflies,high
29.46,66.7,no,16,whiteflies,high
31.66,69.5,no,18,whiteflies,high
23.33,52.91,no,14,whiteflies,high
16.75,22.38,no,20,whiteflies,high
31.61,61.37,no,15,whiteflies,high
24.4,69.86,no,17,whiteflies,high
30.69,62.66,no,21,whiteflies,high
26.75,50.23,yes,20,whiteflies,high
36.56,64.22,yes,30,whiteflies,high
30.44,66.34,yes,35,whiteflies,high
30.48,66.43,yes,19,whiteflies,high
30.56,60.03,yes,14,whiteflies,high
36.08,60.11,yes,16,whiteflies,high
30.53,65.61,yes,16,whiteflies,high
35.32,67.05,no,14,whiteflies,high
35.23,65.84,no,17,whiteflies,high
29.9,63.83,yes,18,whiteflies,high
30.64,63.07,no,20,whiteflies,high
32.33,62.56,no,21,whiteflies,high
9.6,83.83,no,22,whiteflies,high
33.42,65.03,no,23,whiteflies,high
32.37,65.91,yes,25,whiteflies,high
13.46,6.66,yes,15,whiteflies,high
32.17,67.6,yes,24,whiteflies,high
6.7,2.92,yes,28,whiteflies,high
31.08,65.47,yes,10,whiteflies,high
32.51,62.06,yes,17,whiteflies,high
14.11,24.21,yes,19,whiteflies,high
23.09,62.77,no,2,whiteflies,medium
12.69,83.67,yes,10,whiteflies,medium
31.52,60.69,yes,11,whiteflies,medium
23.03,58.12,no,15,whiteflies,medium
24.2,51.99,no,12,whiteflies,medium
5.87,24.59,no,14,whiteflies,medium
22.85,66.06,yes,13,whiteflies,medium
23.58,50.48,yes,8,whiteflies,medium
23.25,64.29,no,11,whiteflies,medium
22.19,65.58,no,10,whiteflies,medium
23.52,51.67,no,15,whiteflies,medium
22.92,51.06,no,8,whiteflies,medium
2.45,27.81,no,14,whiteflies,medium
25.41,66.68,no,14,whiteflies,medium
23.27,61.96,yes,10,whiteflies,medium
2.87,80.71,yes,14,whiteflies,medium
27.69,62.59,yes,13,whiteflies,medium
24.99,52.31,no,9,whiteflies,medium
27.18,56.17,no,14,whiteflies,medium
9.56,4.27,no,15,whiteflies,medium
22.4,66.68,yes,11,whiteflies,medium
25.66,55.09,yes,13,whiteflies,medium
21.55,26.23,yes,14,whiteflies,medium
24.65,68.63,yes,11,whiteflies,medium
24,54.81,yes,9,whiteflies,medium
22.72,66.13,yes,13,whiteflies,medium
26.73,60.7,no,9,whiteflies,medium
22.31,53.78,no,15,whiteflies,medium
15.41,24.78,no,12,whiteflies,medium
26.05,56.34,no,15,whiteflies,medium
23.42,65.18,no,8,whiteflies,medium
24.32,65.7,no,15,whiteflies,medium
23.75,56.68,no,11,whiteflies,medium
23.57,62.37,no,13,whiteflies,medium
24.74,51.5,no,10,whiteflies,medium
3.02,84.99,no,14,whiteflies,medium
24.85,63.45,no,14,whiteflies,medium
22.95,61.51,no,14,whiteflies,medium
24.1,55.25,yes,11,whiteflies,medium
23.58,66.51,no,13,whiteflies,medium
17.6,28.68,yes,12,whiteflies,medium
26.38,66.69,no,11,whiteflies,medium
24.22,52.82,no,12,whiteflies,medium
23.63,68.6,no,14,whiteflies,medium
24.47,57.12,yes,12,whiteflies,medium
16.57,3.84,no,10,whiteflies,medium
29.6,67.14,yes,9,whiteflies,medium
23.7,50.39,no,15,whiteflies,medium
27.78,61.37,yes,10,whiteflies,medium
23.84,60.69,no,12,whiteflies,medium
23.49,57.44,yes,9,whiteflies,medium
24.39,52.2,yes,8,whiteflies,medium
26.29,53.99,yes,10,whiteflies,medium
27.81,67.1,no,12,whiteflies,medium
22.81,63.29,yes,13,whiteflies,medium
25.77,59.59,no,8,whiteflies,medium
25.85,68.34,yes,9,whiteflies,medium
24.4,57.84,yes,14,whiteflies,medium
23.41,54.59,yes,11,whiteflies,medium
26.92,58.56,no,13,whiteflies,medium
22.56,57.2,no,12,whiteflies,medium
22.84,68.45,no,13,whiteflies,medium
22.07,56.24,no,14,whiteflies,medium
26.29,65.1,no,10,whiteflies,medium
23.56,58.33,yes,9,whiteflies,medium
27.56,60.27,yes,15,whiteflies,medium
27.59,57.39,yes,13,whiteflies,medium
23.34,69.63,yes,12,whiteflies,medium
27.53,68.47,yes,15,whiteflies,medium
22.95,52.83,yes,14,whiteflies,medium
23.06,54.75,yes,14,whiteflies,medium
26.58,50.26,yes,11,whiteflies,medium
27.04,58.79,yes,8,whiteflies,medium
23.62,69.37,no,12,whiteflies,medium
26.02,52.46,no,12,whiteflies,medium
27.44,67.92,no,13,whiteflies,medium
25.79,66.91,yes,13,whiteflies,medium
26.77,69.5,no,8,whiteflies,medium
25.29,60.23,yes,15,whiteflies,medium
23.77,64.18,no,13,whiteflies,medium
23.07,62.43,no,10,whiteflies,medium
25.44,67.72,no,8,whiteflies,medium
24.24,65.53,yes,14,whiteflies,medium
23.65,58.5,no,11,whiteflies,medium
26.74,53.47,yes,12,whiteflies,medium
26.91,69.96,no,14,whiteflies,medium
23.1,60.96,yes,11,whiteflies,medium
26.34,64.41,yes,8,whiteflies,medium
22.07,57.61,no,15,whiteflies,medium
22.31,54.9,no,10,whiteflies,medium
27.34,67.81,no,8,whiteflies,medium
26.21,58.17,no,8,whiteflies,medium
27.13,69.53,no,13,whiteflies,medium
24.52,51.03,no,15,whiteflies,medium
24.02,52.66,no,13,whiteflies,medium
24.43,63.88,no,12,whiteflies,medium
26.14,62.95,no,8,whiteflies,medium
26.9,59.81,no,8,whiteflies,medium
23.13,54.04,no,9,whiteflies,medium
22.23,56.18,yes,10,whiteflies,medium
27.86,55.64,yes,12,whiteflies,medium
26.72,58.38,yes,10,whiteflies,medium
26.49,54.31,yes,14,whiteflies,medium
23.55,57.54,yes,11,whiteflies,medium
24.02,66.53,no,15,whiteflies,medium
22.58,58.72,no,8,whiteflies,medium
25.01,52.65,no,13,whiteflies,medium
24.65,59.97,yes,12,whiteflies,medium
22.14,55.31,yes,8,whiteflies,medium
24.92,64.07,yes,8,whiteflies,medium
26.74,53.01,no,10,whiteflies,medium
26.43,59.14,yes,15,whiteflies,medium
0.2,14.95,yes,15,whiteflies,medium
25.07,61.7,no,13,whiteflies,medium
24.27,63.5,no,9,whiteflies,medium
22.58,52.28,no,14,whiteflies,medium
23.09,54.41,no,9,whiteflies,medium
25.65,54.96,yes,11,whiteflies,medium
23.48,54.34,no,10,whiteflies,medium
23,53.14,yes,13,whiteflies,medium
22.48,55.01,no,9,whiteflies,medium
24.31,53.43,yes,8,whiteflies,medium
25.67,63.18,yes,12,whiteflies,medium
24.88,52.54,yes,10,whiteflies,medium
24.43,53.05,yes,14,whiteflies,medium
22.14,66.72,yes,9,whiteflies,medium
26.28,53.89,yes,13,whiteflies,medium
24.04,55.32,no,10,whiteflies,medium
26.04,55.26,no,10,whiteflies,medium
22.2,65.14,no,9,whiteflies,medium
24.27,50.99,no,13,whiteflies,medium
23.93,65.29,no,15,whiteflies,medium
23.1,61.97,no,15,whiteflies,medium
24.93,66.81,no,12,whiteflies,medium
26.01,61.8,no,12,whiteflies,medium
24.01,57.31,yes,13,whiteflies,medium
16.59,27.32,yes,13,whiteflies,medium
24.81,62.83,yes,15,whiteflies,medium
27.42,61.96,yes,10,whiteflies,medium
42,0.12,yes,13,whiteflies,medium
24.98,51,no,10,whiteflies,medium
24.92,69.35,no,10,whiteflies,medium
24.44,53.28,no,14,whiteflies,medium
22.27,60.37,no,10,whiteflies,medium
18.38,24.58,no,9,whiteflies,medium
27.69,61.73,yes,12,whiteflies,medium
22.72,51.26,yes,13,whiteflies,medium
23.81,60.46,yes,11,whiteflies,medium
26.34,69.54,yes,13,whiteflies,medium
22.61,62.99,yes,9,whiteflies,medium
2.7,30.53,yes,11,whiteflies,medium
22.35,64.8,yes,13,whiteflies,medium
20.84,38.66,yes,15,whiteflies,medium
22.18,58.78,no,9,whiteflies,medium
27.85,66.73,no,14,whiteflies,medium
25.79,60.53,no,13,whiteflies,medium
22.8,68.48,no,13,whiteflies,medium
23.4,57.95,no,12,whiteflies,medium
26.21,67.05,no,14,whiteflies,medium
23.54,66.68,yes,12,whiteflies,medium
23.13,55.37,yes,15,whiteflies,medium
25.59,57.43,no,11,whiteflies,medium
6.06,22.25,no,11,whiteflies,medium
25.24,54.88,no,13,whiteflies,medium
5.9,84.45,no,5,whiteflies,low
20.7,83.6,no,2,whiteflies,low
28.51,63.97,no,5,whiteflies,low
16.31,86.13,no,8,whiteflies,low
29.4,65.04,yes,6,whiteflies,low
17.09,12.71,no,2,whiteflies,low
19.17,26.3,no,4,whiteflies,low
3.43,36.71,no,2,whiteflies,low
0.05,39.17,no,3,whiteflies,low
7.16,30.9,no,2,whiteflies,low
19.36,33.39,no,8,whiteflies,low
4.4,37.11,no,8,whiteflies,low
36.52,67.93,no,1,whiteflies,low
17.42,31.52,no,5,whiteflies,low
0.7,84.41,no,1,whiteflies,low
17.97,9.23,yes,7,whiteflies,low
20.35,83.21,yes,7,whiteflies,low
9.85,7.91,yes,1,whiteflies,low
4.41,82.87,no,1,whiteflies,low
13.21,34.21,no,6,whiteflies,low
1.34,28.57,no,5,whiteflies,low
1.5,22.54,no,6,whiteflies,low
3.45,7.3,no,7,whiteflies,low
13.41,12.46,no,3,whiteflies,low
17.29,15.56,no,6,whiteflies,low
10.58,1.99,yes,7,whiteflies,low
16.07,0.06,yes,5,whiteflies,low
16.84,22.11,no,2,whiteflies,low
18.51,6.37,no,4,whiteflies,low
4.18,19.42,no,6,whiteflies,low
4.64,35.74,yes,7,whiteflies,low
21.04,32.09,no,5,whiteflies,low
20.27,14.76,yes,2,whiteflies,low
0.61,10.58,no,2,whiteflies,low
12.19,4.85,yes,6,whiteflies,low
9.61,29.66,no,6,whiteflies,low
16.31,34.67,no,6,whiteflies,low
5.62,11.61,yes,3,whiteflies,low
10.07,27.37,no,3,whiteflies,low
18.4,4.32,yes,6,whiteflies,low
5.95,83.33,yes,5,whiteflies,low
1.41,6.26,yes,8,whiteflies,low
16.78,28.59,no,5,whiteflies,low
16.42,0.36,no,7,whiteflies,low
11.85,26.22,no,6,whiteflies,low
20.83,16.58,no,7,whiteflies,low
17.48,0.13,no,2,whiteflies,low
18.97,14.55,yes,1,whiteflies,low
21.85,37.11,yes,7,whiteflies,low
6.84,28.1,yes,3,whiteflies,low
8.8,25.21,yes,3,whiteflies,low
4.18,8.53,yes,1,whiteflies,low
1.66,81.24,yes,3,whiteflies,low
17.81,6.9,yes,7,whiteflies,low
14.06,87.85,yes,3,whiteflies,low
8.84,12.71,no,4,whiteflies,low
5.98,26.48,no,3,whiteflies,low
5.11,80.35,no,2,whiteflies,low
3.01,5.78,yes,5,whiteflies,low
10.93,11.9,no,2,whiteflies,low
6.67,35.76,yes,8,whiteflies,low
8.12,87.82,no,6,whiteflies,low
12.25,1.88,yes,2,whiteflies,low
25.56,62.39,yes,4,whiteflies,low
0.9,83.11,yes,2,whiteflies,low
25.72,63.35,yes,2,whiteflies,low
12.31,34.73,yes,5,whiteflies,low
13.73,85.29,no,3,whiteflies,low
11.87,29.72,no,5,whiteflies,low
19.29,21.86,yes,6,whiteflies,low
8.57,80.81,yes,8,whiteflies,low
5.86,10.73,no,3,whiteflies,low
4.01,36.41,yes,2,whiteflies,low
18.42,83.31,yes,2,whiteflies,low
1.28,81.13,no,1,whiteflies,low
4.69,3.06,no,3,whiteflies,low
24.51,54.98,no,6,whiteflies,low
6.91,14.91,no,7,whiteflies,low
20.61,36.51,no,7,whiteflies,low
6.08,27.02,no,7,whiteflies,low
11.29,22.73,no,8,whiteflies,low
3.76,81.16,no,2,whiteflies,low
0.34,81.9,no,1,whiteflies,low
16.29,0.56,no,8,whiteflies,low
23.22,67.04,no,5,whiteflies,low
14.16,36.64,no,4,whiteflies,low
23.96,52.94,no,5,whiteflies,low
11.34,8.5,no,2,whiteflies,low
16.33,24.37,no,3,whiteflies,low
5.17,8.52,no,7,whiteflies,low
21.85,13.9,no,6,whiteflies,low
7.64,84.77,no,5,whiteflies,low
25.72,69.82,no,8,whiteflies,low
6.86,86.69,no,3,whiteflies,low
24.37,55.02,yes,5,whiteflies,low
2.42,7.58,yes,5,whiteflies,low
9.52,22.94,yes,8,whiteflies,low
1.71,7.99,yes,4,whiteflies,low
8.3,87,yes,4,whiteflies,low
21.34,5.5,yes,1,whiteflies,low
16.12,36.25,yes,1,whiteflies,low
1.92,32.53,no,5,whiteflies,low
13.01,88.37,no,6,whiteflies,low
32.18,62.14,no,7,whiteflies,low
7.53,27.81,yes,2,whiteflies,low
34.15,67.6,yes,4,whiteflies,low
15.74,11.31,yes,1,whiteflies,low
18.74,30.53,yes,8,whiteflies,low
2.69,86.75,yes,6,whiteflies,low
21.88,4.83,yes,8,whiteflies,low
27.43,54.68,yes,3,whiteflies,low
11.41,21.6,yes,2,whiteflies,low
15.84,37.95,no,6,whiteflies,low
10.83,10.22,no,6,whiteflies,low
21.17,5.58,no,8,whiteflies,low
23.87,55.12,no,7,whiteflies,low
10.47,5.12,no,3,whiteflies,low
17.47,33.39,yes,4,whiteflies,low
1.71,27.15,no,1,whiteflies,low
21.15,8.14,yes,2,whiteflies,low
3.64,87.29,yes,2,whiteflies,low
12.91,18.87,yes,8,whiteflies,low
3.57,14.97,yes,1,whiteflies,low
11.26,13.81,no,5,whiteflies,low
19.23,7.64,no,6,whiteflies,low
4.39,13.21,no,6,whiteflies,low
58,25.68,no,3,whiteflies,low
6.18,25.84,no,5,whiteflies,low
18.82,7.31,no,5,whiteflies,low
20.43,19.47,yes,7,whiteflies,low
8.9,20.85,yes,1,whiteflies,low
23.52,61.39,yes,1,whiteflies,low
16.66,86.39,yes,3,whiteflies,low
16.45,38.35,no,6,whiteflies,low
20.54,15.13,no,8,whiteflies,low
2.04,81.14,no,3,whiteflies,low
14.43,25.59,no,6,whiteflies,low
14.17,31.68,yes,1,whiteflies,low
19,29.52,yes,3,whiteflies,low
12.15,3.95,yes,8,whiteflies,low
21.09,10.38,yes,3,whiteflies,low
10.89,86.73,yes,7,whiteflies,low
20.28,25.14,no,5,whiteflies,low
3.67,11.66,no,7,whiteflies,low
19.42,31.08,no,4,whiteflies,low
21.65,37.39,no,3,whiteflies,low
17.6,18.04,yes,4,whiteflies,low
40,60,no,4,whiteflies,low
41.2,80,yes,8,whiteflies,low
36.4,92,no,2,whiteflies,low
35.9,50,yes,2,whiteflies,low
44.5,51.2,no,4,whiteflies,low
29.6,40,yes,2,whiteflies,low
33.5,75.5,yes,1,whiteflies,low
Training/pest and disease prediction/pest prediction train.ipynb
0 → 100644
View file @
88d13d5f
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "23cefb78",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "db2cb985",
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_csv('full_data.csv')"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "0d96ddd9",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Temperature</th>\n",
" <th>Humidity</th>\n",
" <th>Rain</th>\n",
" <th>Wind_speed</th>\n",
" <th>Disease</th>\n",
" <th>Status</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>23.56</td>\n",
" <td>99.97</td>\n",
" <td>yes</td>\n",
" <td>22.0</td>\n",
" <td>Bacterialblight</td>\n",
" <td>high</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>23.17</td>\n",
" <td>93.20</td>\n",
" <td>yes</td>\n",
" <td>21.0</td>\n",
" <td>Bacterialblight</td>\n",
" <td>high</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>17.52</td>\n",
" <td>96.62</td>\n",
" <td>yes</td>\n",
" <td>19.0</td>\n",
" <td>Bacterialblight</td>\n",
" <td>high</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>24.76</td>\n",
" <td>96.71</td>\n",
" <td>yes</td>\n",
" <td>18.0</td>\n",
" <td>Bacterialblight</td>\n",
" <td>high</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>34.53</td>\n",
" <td>17.07</td>\n",
" <td>yes</td>\n",
" <td>27.0</td>\n",
" <td>Bacterialblight</td>\n",
" <td>high</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Temperature Humidity Rain Wind_speed Disease Status\n",
"0 23.56 99.97 yes 22.0 Bacterialblight high\n",
"1 23.17 93.20 yes 21.0 Bacterialblight high\n",
"2 17.52 96.62 yes 19.0 Bacterialblight high\n",
"3 24.76 96.71 yes 18.0 Bacterialblight high\n",
"4 34.53 17.07 yes 27.0 Bacterialblight high"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "e93489fe",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Temperature 0\n",
"Humidity 0\n",
"Rain 0\n",
"Wind_speed 0\n",
"Disease 0\n",
"Status 0\n",
"dtype: int64"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.isnull().sum()"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "d7b9e4c7",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(2152, 6)"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.shape"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "8541bcf8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 2152 entries, 0 to 2151\n",
"Data columns (total 6 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 Temperature 2152 non-null float64\n",
" 1 Humidity 2152 non-null float64\n",
" 2 Rain 2152 non-null object \n",
" 3 Wind_speed 2152 non-null float64\n",
" 4 Disease 2152 non-null object \n",
" 5 Status 2152 non-null object \n",
"dtypes: float64(3), object(3)\n",
"memory usage: 101.0+ KB\n"
]
}
],
"source": [
"df.info()"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "7ce8151d",
"metadata": {},
"outputs": [],
"source": [
"data = df.sample(frac=1, random_state=42) "
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "0a224643",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Temperature</th>\n",
" <th>Humidity</th>\n",
" <th>Rain</th>\n",
" <th>Wind_speed</th>\n",
" <th>Disease</th>\n",
" <th>Status</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1505</th>\n",
" <td>19.78</td>\n",
" <td>59.48</td>\n",
" <td>yes</td>\n",
" <td>9.0</td>\n",
" <td>aphid</td>\n",
" <td>medium</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1660</th>\n",
" <td>28.33</td>\n",
" <td>62.36</td>\n",
" <td>no</td>\n",
" <td>20.0</td>\n",
" <td>whiteflies</td>\n",
" <td>high</td>\n",
" </tr>\n",
" <tr>\n",
" <th>889</th>\n",
" <td>31.97</td>\n",
" <td>31.52</td>\n",
" <td>no</td>\n",
" <td>4.0</td>\n",
" <td>anthracnose</td>\n",
" <td>low</td>\n",
" </tr>\n",
" <tr>\n",
" <th>306</th>\n",
" <td>32.21</td>\n",
" <td>36.40</td>\n",
" <td>no</td>\n",
" <td>2.0</td>\n",
" <td>Bacterialblight</td>\n",
" <td>low</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1771</th>\n",
" <td>31.12</td>\n",
" <td>69.65</td>\n",
" <td>no</td>\n",
" <td>15.0</td>\n",
" <td>whiteflies</td>\n",
" <td>high</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Temperature Humidity Rain Wind_speed Disease Status\n",
"1505 19.78 59.48 yes 9.0 aphid medium\n",
"1660 28.33 62.36 no 20.0 whiteflies high\n",
"889 31.97 31.52 no 4.0 anthracnose low\n",
"306 32.21 36.40 no 2.0 Bacterialblight low\n",
"1771 31.12 69.65 no 15.0 whiteflies high"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "54e47de4",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"anthracnose 600\n",
"Bacterialblight 549\n",
"whiteflies 505\n",
"aphid 498\n",
"Name: Disease, dtype: int64"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data['Disease'].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "2b774a25",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"high 782\n",
"low 700\n",
"medium 670\n",
"Name: Status, dtype: int64"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data['Status'].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "8cc15910",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"no 1087\n",
"yes 1065\n",
"Name: Rain, dtype: int64"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data['Rain'].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "a914431a",
"metadata": {},
"outputs": [],
"source": [
"crop_dict = {\n",
" 'high': 1,\n",
" 'medium': 2,\n",
" 'low': 3\n",
"}\n",
"data['status_num'] = data['Status'].map(crop_dict)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "c00686ff",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Temperature</th>\n",
" <th>Humidity</th>\n",
" <th>Rain</th>\n",
" <th>Wind_speed</th>\n",
" <th>Disease</th>\n",
" <th>Status</th>\n",
" <th>status_num</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1505</th>\n",
" <td>19.78</td>\n",
" <td>59.48</td>\n",
" <td>yes</td>\n",
" <td>9.0</td>\n",
" <td>aphid</td>\n",
" <td>medium</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1660</th>\n",
" <td>28.33</td>\n",
" <td>62.36</td>\n",
" <td>no</td>\n",
" <td>20.0</td>\n",
" <td>whiteflies</td>\n",
" <td>high</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>889</th>\n",
" <td>31.97</td>\n",
" <td>31.52</td>\n",
" <td>no</td>\n",
" <td>4.0</td>\n",
" <td>anthracnose</td>\n",
" <td>low</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>306</th>\n",
" <td>32.21</td>\n",
" <td>36.40</td>\n",
" <td>no</td>\n",
" <td>2.0</td>\n",
" <td>Bacterialblight</td>\n",
" <td>low</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1771</th>\n",
" <td>31.12</td>\n",
" <td>69.65</td>\n",
" <td>no</td>\n",
" <td>15.0</td>\n",
" <td>whiteflies</td>\n",
" <td>high</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Temperature Humidity Rain Wind_speed Disease Status \\\n",
"1505 19.78 59.48 yes 9.0 aphid medium \n",
"1660 28.33 62.36 no 20.0 whiteflies high \n",
"889 31.97 31.52 no 4.0 anthracnose low \n",
"306 32.21 36.40 no 2.0 Bacterialblight low \n",
"1771 31.12 69.65 no 15.0 whiteflies high \n",
"\n",
" status_num \n",
"1505 2 \n",
"1660 1 \n",
"889 3 \n",
"306 3 \n",
"1771 1 "
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "5c25cd19",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Int64Index: 2152 entries, 1505 to 860\n",
"Data columns (total 7 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 Temperature 2152 non-null float64\n",
" 1 Humidity 2152 non-null float64\n",
" 2 Rain 2152 non-null object \n",
" 3 Wind_speed 2152 non-null float64\n",
" 4 Disease 2152 non-null object \n",
" 5 Status 2152 non-null object \n",
" 6 status_num 2152 non-null int64 \n",
"dtypes: float64(3), int64(1), object(3)\n",
"memory usage: 134.5+ KB\n"
]
}
],
"source": [
"data.info()"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "c1c8c29e",
"metadata": {},
"outputs": [],
"source": [
"crop_dict = {\n",
" 'anthracnose': 1,\n",
" 'Bacterialblight': 2,\n",
" 'whiteflies': 3,\n",
" 'aphid': 4,\n",
"}\n",
"data['disease_num'] = data['Disease'].map(crop_dict)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "13eefaad",
"metadata": {},
"outputs": [],
"source": [
"data = data.drop('Status',axis=1,inplace=False)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "1bbd7c62",
"metadata": {},
"outputs": [],
"source": [
"data = data.drop('Disease',axis=1,inplace=False)"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "d43ae584",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Temperature</th>\n",
" <th>Humidity</th>\n",
" <th>Rain</th>\n",
" <th>Wind_speed</th>\n",
" <th>status_num</th>\n",
" <th>disease_num</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1505</th>\n",
" <td>19.78</td>\n",
" <td>59.48</td>\n",
" <td>yes</td>\n",
" <td>9.0</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1660</th>\n",
" <td>28.33</td>\n",
" <td>62.36</td>\n",
" <td>no</td>\n",
" <td>20.0</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>889</th>\n",
" <td>31.97</td>\n",
" <td>31.52</td>\n",
" <td>no</td>\n",
" <td>4.0</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>306</th>\n",
" <td>32.21</td>\n",
" <td>36.40</td>\n",
" <td>no</td>\n",
" <td>2.0</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1771</th>\n",
" <td>31.12</td>\n",
" <td>69.65</td>\n",
" <td>no</td>\n",
" <td>15.0</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Temperature Humidity Rain Wind_speed status_num disease_num\n",
"1505 19.78 59.48 yes 9.0 2 4\n",
"1660 28.33 62.36 no 20.0 1 3\n",
"889 31.97 31.52 no 4.0 3 1\n",
"306 32.21 36.40 no 2.0 3 2\n",
"1771 31.12 69.65 no 15.0 1 3"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "5ba412ea",
"metadata": {},
"outputs": [],
"source": [
"crop_dict = {\n",
" 'no': 0,\n",
" 'yes': 1\n",
"}\n",
"data['rain'] = data['Rain'].map(crop_dict)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "01a344e2",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Temperature</th>\n",
" <th>Humidity</th>\n",
" <th>Rain</th>\n",
" <th>Wind_speed</th>\n",
" <th>status_num</th>\n",
" <th>disease_num</th>\n",
" <th>rain</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1505</th>\n",
" <td>19.78</td>\n",
" <td>59.48</td>\n",
" <td>yes</td>\n",
" <td>9.0</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1660</th>\n",
" <td>28.33</td>\n",
" <td>62.36</td>\n",
" <td>no</td>\n",
" <td>20.0</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>889</th>\n",
" <td>31.97</td>\n",
" <td>31.52</td>\n",
" <td>no</td>\n",
" <td>4.0</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>306</th>\n",
" <td>32.21</td>\n",
" <td>36.40</td>\n",
" <td>no</td>\n",
" <td>2.0</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1771</th>\n",
" <td>31.12</td>\n",
" <td>69.65</td>\n",
" <td>no</td>\n",
" <td>15.0</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Temperature Humidity Rain Wind_speed status_num disease_num rain\n",
"1505 19.78 59.48 yes 9.0 2 4 1\n",
"1660 28.33 62.36 no 20.0 1 3 0\n",
"889 31.97 31.52 no 4.0 3 1 0\n",
"306 32.21 36.40 no 2.0 3 2 0\n",
"1771 31.12 69.65 no 15.0 1 3 0"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 41,
"id": "10780ee4",
"metadata": {},
"outputs": [],
"source": [
"data = data.drop('Rain',axis=1,inplace=False)"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "74793858",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Temperature</th>\n",
" <th>Humidity</th>\n",
" <th>Wind_speed</th>\n",
" <th>status_num</th>\n",
" <th>disease_num</th>\n",
" <th>rain</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1505</th>\n",
" <td>19.78</td>\n",
" <td>59.48</td>\n",
" <td>9.0</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1660</th>\n",
" <td>28.33</td>\n",
" <td>62.36</td>\n",
" <td>20.0</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>889</th>\n",
" <td>31.97</td>\n",
" <td>31.52</td>\n",
" <td>4.0</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>306</th>\n",
" <td>32.21</td>\n",
" <td>36.40</td>\n",
" <td>2.0</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1771</th>\n",
" <td>31.12</td>\n",
" <td>69.65</td>\n",
" <td>15.0</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Temperature Humidity Wind_speed status_num disease_num rain\n",
"1505 19.78 59.48 9.0 2 4 1\n",
"1660 28.33 62.36 20.0 1 3 0\n",
"889 31.97 31.52 4.0 3 1 0\n",
"306 32.21 36.40 2.0 3 2 0\n",
"1771 31.12 69.65 15.0 1 3 0"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "3e45bcf8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Int64Index: 2152 entries, 1505 to 860\n",
"Data columns (total 6 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 Temperature 2152 non-null float64\n",
" 1 Humidity 2152 non-null float64\n",
" 2 Wind_speed 2152 non-null float64\n",
" 3 status_num 2152 non-null int64 \n",
" 4 disease_num 2152 non-null int64 \n",
" 5 rain 2152 non-null int64 \n",
"dtypes: float64(3), int64(3)\n",
"memory usage: 117.7 KB\n"
]
}
],
"source": [
"data.info()"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "e1a041b3",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Temperature</th>\n",
" <th>Humidity</th>\n",
" <th>Wind_speed</th>\n",
" <th>status_num</th>\n",
" <th>disease_num</th>\n",
" <th>rain</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1505</th>\n",
" <td>19.78</td>\n",
" <td>59.48</td>\n",
" <td>9.0</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1660</th>\n",
" <td>28.33</td>\n",
" <td>62.36</td>\n",
" <td>20.0</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>889</th>\n",
" <td>31.97</td>\n",
" <td>31.52</td>\n",
" <td>4.0</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>306</th>\n",
" <td>32.21</td>\n",
" <td>36.40</td>\n",
" <td>2.0</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1771</th>\n",
" <td>31.12</td>\n",
" <td>69.65</td>\n",
" <td>15.0</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Temperature Humidity Wind_speed status_num disease_num rain\n",
"1505 19.78 59.48 9.0 2 4 1\n",
"1660 28.33 62.36 20.0 1 3 0\n",
"889 31.97 31.52 4.0 3 1 0\n",
"306 32.21 36.40 2.0 3 2 0\n",
"1771 31.12 69.65 15.0 1 3 0"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.rename(columns={'Temperature (C)': 'temperature', 'Humidity (%)': 'humidity'}, inplace=True)\n",
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "83db3835",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Temperature</th>\n",
" <th>Humidity</th>\n",
" <th>Wind_speed</th>\n",
" <th>status_num</th>\n",
" <th>disease_num</th>\n",
" <th>rain</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>2152.000000</td>\n",
" <td>2152.000000</td>\n",
" <td>2152.000000</td>\n",
" <td>2152.000000</td>\n",
" <td>2152.000000</td>\n",
" <td>2152.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>24.193216</td>\n",
" <td>56.737435</td>\n",
" <td>11.839498</td>\n",
" <td>1.961896</td>\n",
" <td>2.418680</td>\n",
" <td>0.494888</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>8.663167</td>\n",
" <td>24.016180</td>\n",
" <td>7.433841</td>\n",
" <td>0.829174</td>\n",
" <td>1.124465</td>\n",
" <td>0.500090</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>0.000000</td>\n",
" <td>0.040000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>18.840000</td>\n",
" <td>39.402500</td>\n",
" <td>6.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>26.140000</td>\n",
" <td>61.395000</td>\n",
" <td>12.000000</td>\n",
" <td>2.000000</td>\n",
" <td>2.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>30.442500</td>\n",
" <td>69.532500</td>\n",
" <td>17.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>58.000000</td>\n",
" <td>99.970000</td>\n",
" <td>99.000000</td>\n",
" <td>3.000000</td>\n",
" <td>4.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Temperature Humidity Wind_speed status_num disease_num \\\n",
"count 2152.000000 2152.000000 2152.000000 2152.000000 2152.000000 \n",
"mean 24.193216 56.737435 11.839498 1.961896 2.418680 \n",
"std 8.663167 24.016180 7.433841 0.829174 1.124465 \n",
"min 0.000000 0.040000 1.000000 1.000000 1.000000 \n",
"25% 18.840000 39.402500 6.000000 1.000000 1.000000 \n",
"50% 26.140000 61.395000 12.000000 2.000000 2.000000 \n",
"75% 30.442500 69.532500 17.000000 3.000000 3.000000 \n",
"max 58.000000 99.970000 99.000000 3.000000 4.000000 \n",
"\n",
" rain \n",
"count 2152.000000 \n",
"mean 0.494888 \n",
"std 0.500090 \n",
"min 0.000000 \n",
"25% 0.000000 \n",
"50% 0.000000 \n",
"75% 1.000000 \n",
"max 1.000000 "
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.describe()"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "13ebbec7",
"metadata": {},
"outputs": [],
"source": [
"X = data.drop(columns=['status_num'])\n",
"y = data['status_num']"
]
},
{
"cell_type": "code",
"execution_count": 89,
"id": "cbc8c514",
"metadata": {},
"outputs": [],
"source": [
"from sklearn.model_selection import train_test_split\n",
"X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25)"
]
},
{
"cell_type": "code",
"execution_count": 90,
"id": "7a3f0b97",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"((1614, 5), (538, 5))"
]
},
"execution_count": 90,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X_train.shape, X_test.shape"
]
},
{
"cell_type": "code",
"execution_count": 91,
"id": "a14eb98b",
"metadata": {},
"outputs": [],
"source": [
"X_train.shape, X_test.shape\n",
"\n",
"def model_acc(model):\n",
" model.fit(X_train, y_train)\n",
" acc = model.score(X_test, y_test)\n",
" print(str(model) + ' --> ' + str(acc))\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 92,
"id": "d7d66c3b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"LinearRegression() --> 0.6053670493665395\n"
]
}
],
"source": [
"from sklearn.linear_model import LinearRegression\n",
"lr = LinearRegression()\n",
"model_acc(lr)"
]
},
{
"cell_type": "code",
"execution_count": 93,
"id": "feb49098",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"DecisionTreeRegressor() --> 0.8357991226618109\n",
"RandomForestRegressor() --> 0.8895217534348617\n",
"RandomForestClassifier() --> 0.9423791821561338\n"
]
}
],
"source": [
"from sklearn.tree import DecisionTreeRegressor\n",
"dt = DecisionTreeRegressor()\n",
"model_acc(dt)\n",
"\n",
"\n",
"from sklearn.ensemble import RandomForestRegressor\n",
"rf = RandomForestRegressor()\n",
"model_acc(rf)\n",
"\n",
"from sklearn.ensemble import RandomForestClassifier\n",
"rfclassifier = RandomForestClassifier()\n",
"model_acc(rfclassifier)"
]
},
{
"cell_type": "code",
"execution_count": 88,
"id": "67f6bcf4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"DecisionTreeClassifier() --> 0.888631090487239\n"
]
}
],
"source": [
"from sklearn.tree import DecisionTreeClassifier\n",
"dtc = DecisionTreeClassifier()\n",
"model_acc(dtc)"
]
},
{
"cell_type": "code",
"execution_count": 74,
"id": "0312a458",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"RandomForestClassifier(n_estimators=80, random_state=42) --> 0.9993804213135068\n"
]
}
],
"source": [
"\n",
"rfclassifier = RandomForestClassifier(n_estimators=80,criterion = 'gini', random_state=42)\n",
"model_acc(rfclassifier)"
]
},
{
"cell_type": "code",
"execution_count": 94,
"id": "bd6cdb26",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['Temperature', 'Humidity', 'Wind_speed', 'disease_num', 'rain'], dtype='object')"
]
},
"execution_count": 94,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X_test.columns"
]
},
{
"cell_type": "code",
"execution_count": 95,
"id": "34229ac2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Int64Index: 538 entries, 14 to 2039\n",
"Data columns (total 5 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 Temperature 538 non-null float64\n",
" 1 Humidity 538 non-null float64\n",
" 2 Wind_speed 538 non-null float64\n",
" 3 disease_num 538 non-null int64 \n",
" 4 rain 538 non-null int64 \n",
"dtypes: float64(3), int64(2)\n",
"memory usage: 25.2 KB\n"
]
}
],
"source": [
"X_test.info()"
]
},
{
"cell_type": "code",
"execution_count": 96,
"id": "47511380",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"HIGH\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\Kavishka\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\sklearn\\base.py:439: UserWarning: X does not have valid feature names, but RandomForestClassifier was fitted with feature names\n",
" warnings.warn(\n"
]
}
],
"source": [
"\n",
"ans = rfclassifier.predict([['20','82','16','1','1']])\n",
"if ans[0] == 1:\n",
" print(\"HIGH\")\n",
"elif ans[0] == 2:\n",
" print(\"MEDIUM\")\n",
"else:\n",
" print(\"LOW\")"
]
},
{
"cell_type": "code",
"execution_count": 97,
"id": "5f7cb4c5",
"metadata": {},
"outputs": [],
"source": [
"import pickle\n",
"with open('pest_disease.pickle', 'wb') as file:\n",
" pickle.dump(rfclassifier, file)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5ffc16d5",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.7"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
Write
Preview
Markdown
is supported
0%
Try again
or
attach a new file
Attach a file
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Cancel
Please
register
or
sign in
to comment
