commodity.py

import numpy as np
import pandas as pd
import seaborn as sns
from datetime import datetime
from sklearn.tree import DecisionTreeRegressor
import random


class Commodity:

    def __init__(self, csv_name):
        self.name = csv_name
        dataset = pd.read_csv(csv_name)
        self.X = dataset.iloc[:, :-1].values
        self.Y = dataset.iloc[:, 3].values

        from sklearn.tree import DecisionTreeRegressor
        depth = random.randrange(7,18)
        self.regressor = DecisionTreeRegressor(max_depth=depth)
        self.regressor.fit(self.X, self.Y)


    def getPredictedValue(self, value):
        if value[1]>=2019:
            fsa = np.array(value).reshape(1, 3)
         
            return self.regressor.predict(fsa)[0]
        else:
            c=self.X[:,0:2]
            x=[]
            for i in c:
                x.append(i.tolist())
            fsa = [value[0], value[1]]
            ind = 0
            for i in range(0,len(x)):
                if x[i]==fsa:
                    ind=i
                    break

            return self.Y[i]

    def getCropName(self):
        a = self.name.split('.')
        return a[0]