Update app.py

app.py

@@ -61,29 +61,10 @@ def asubmit(aparam):
 	adf3 = pd.read_csv(StringIO(csvString), sep=",")
 	aparam["acontainer"].dataframe(adf3)
 
-	if ("0" == "mycustom"):
-		import matplotlib.pyplot as plt
-		xpoints = np.array(adf3['Date'])
-		ypoints = np.array(adf3['Celsius'])
-		plt.plot(xpoints, ypoints, 1)
-		plt.xlabel('Date')
-		plt.ylabel('Celsius')
-		plt.show()
-
 	from sklearn.linear_model import LinearRegression
 # Creating a Linear Regression model on our data
 	lin = LinearRegression()
 	lin.fit(adf3[['Date']].astype('float').astype('int32'), adf3['Celsius'])
-#	lin.fit(pd.to_numeric(adf3[['Date']]), adf3['Celsius'])
-
-# Creating a plot
-	ax = adf3.plot.scatter(x='Date', y='Celsius', alpha=.1)
-	ax.plot(adf3['Date'], lin.predict(adf3[['Date']]), c='r')
-
-#	lin.score(adf3[['Date']], adf3['Celsius'])
-#	st.write(lin.predict(np.array([[20230223]])))
-#	st.write(lin.predict(np.array([['Date']], dtype='int32')))
-#	st.write(lin.predict(adf3[['Date']]))
 
 	atrendproject = [20230223,]
 	st.write(type(lin.predict(np.array([atrendproject]))))