Create main.py

main.py

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+import pandas as pd
+from sklearn.model_selection import train_test_split
+from sklearn.linear_model import LinearRegression
+import numpy as np
+import subprocess
+subprocess.call(["pip", "install", "scikit-learn"])
+
+df=pd.read_csv('GOOG.csv')
+p=df.drop('Close',axis=1)
+q=p.drop('Date',axis=1)
+gw=q.drop('High',axis=1)
+g=q.drop('Adj Close',axis=1)
+x=g
+
+x_train,x_test,y_train,y_test = train_test_split(x,y,test_size=0.2,random_state=100)
+
+lr=LinearRegression()
+lr.fit(x_train,y_train)
+y_lr_train_pred=lr.predict(x_train)
+y_lr_test_pred=lr.predict(x_test)
+a = np.array(list(map(float,input().split(","))))
+
+
+a_reshaped = a.reshape(1, -1)
+
+prediction = lr.predict(a_reshaped)
+
+print(prediction)