text: import pandas
  from sklearn import linear_model
  from flask import Flask, request, render_template 
  
  
  
  app = Flask(__name__)
  df = pandas.read_csv("file.csv")
  X = df[['Evaporation', 'Sunshine', 'WindSpeed', 'Humidity', 'Pressure', 'Temperature']]
  y = df['Rainfall']
  
  regr = linear_model.LinearRegression()
  regr.fit(X.values, y.values)
  
  @app.route('/', methods =["GET", "POST"])
  def gfg():
      if request.method == "POST":
         Evaporation = request.form.get("Evaporation")
         Sunshine = request.form.get("Sunshine")
         WindSpeed = request.form.get("WindSpeed")
         Humidity = request.form.get("Humidity")
         Pressure = request.form.get("Pressure")
         Temperature = request.form.get("Temperature")
  
         predictedRain = regr.predict([[Evaporation, Sunshine, WindSpeed, Humidity, Pressure, Temperature]])
  
         
         return f"Rainfall amount is {predictedRain}"
      return render_template("form.html")
    
  if __name__=='__main__':
     app.run()
  