Update train_test.py

train_test.py

@@ -9,10 +9,10 @@ from sklearn.linear_model import LinearRegression
 from sklearn.model_selection import train_test_split
 import matplotlib.pyplot as plt
 
-df = pd.read_csv("forestfires.csv")
+data = pd.read_csv("forestfires.csv")
 
-x = df.drop(columns=['rain'])
-y = df[['rain']]
+x = data.drop(columns=['rain'])
+y = data[['rain']]
 
 x_train, x_test, y_train, y_test,  = train_test_split(x, y, test_size=0.5, random_state=0)
 
@@ -30,8 +30,8 @@ plt.xlabel("rain")
 plt.ylabel("Freq")
 plt.show()
 
-x = df.drop(columns=['DC'])
-y = df[['DC']]
+x = data.drop(columns=['DC'])
+y = data[['DC']]
 
 x_train, x_test, y_train, y_test,  = train_test_split(x, y, test_size=0.5, random_state=0)
 
@@ -49,8 +49,8 @@ plt.xlabel("DC")
 plt.ylabel("Freq")
 plt.show()
 
-x = df.drop(columns=['month'])
-y = df[['month']]
+x = data.drop(columns=['month'])
+y = data[['month']]
 
 x_train, x_test, y_train, y_test,  = train_test_split(x, y, test_size=0.5, random_state=0)
 
@@ -67,18 +67,3 @@ plt.title("Month Test")
 plt.xlabel("Month")
 plt.ylabel("Freq")
 plt.show()
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