title: Implementation of multiple feature linear regression
body: <p>I have a train_data which holds information about Stores and their sales. Which looks like this
  <a href="https://i.stack.imgur.com/oXoad.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/oXoad.png" alt="enter image description here"></a></p>
  
  <p>I want to build a multiple feature linear regression to predict the 'Sales' on a test_data, by using 'DayofWeek', 'Customers', 'Promo'.</p>
  
  <p>How do I build a Multiple Linear Regression Model for this, preferably by using SKlearn.</p>
  
  <p>edit: here's the link to the dataset I am using, if anyone is interested : <a href="https://www.kaggle.com/c/rossmann-store-sales" rel="nofollow noreferrer">https://www.kaggle.com/c/rossmann-store-sales</a></p>
  
  <p>This is what i've tried so far.</p>
  
  <pre><code>import pandas as pd
  
  from sklearn import linear_model
  
  x=train_data[['Promo','Customers','DayOfWeek']]
  
  y=train_data['Sales']
  
  lm=LinearRegression()
  
  
  lm.fit(x,y)
  </code></pre>
  
  <p>For which i am getting an error saying 'LinearRegression not defined'.</p>