This dataset was built by augmenting datasets of rainfall, climate and fertilizer data available for India.

To load the training data in your jupyter notebook, use the below command:

import pandas as pd

train_data = pd.read_csv("https://raw.githubusercontent.com/dphi-official/Datasets/master/crop_recommendation/train_set_label.csv")

You can find more details on how to save a prediction file here: https://discuss.dphi.tech/t/how-to-submit-predictions/548

Sample submission: You should submit a CSV file with a header row and the sample submission can be found below:

prediction

rice

papaya

coffee

mungbean

banana

jute

.

.

.

.

Etc.

Note that the header name should be ‘prediction’ else it will throw an evaluation error. A sample submission file can be found here

Load the test data (name it as test_data). You can load the data using the below command.

test_data = pd.read_csv('https://raw.githubusercontent.com/dphi-official/Datasets/master/crop_recommendation/test_set_label.csv')

Here the target column is deliberately not there as you need to predict it

Thanks to Atharva Ingle for providing the dataset.

Data Sprint #26: Crop Recommendation