title: Exclude last two rows when import a csv file using read_csv in Pandas
body: <p>Afternoon All,</p>
  
  <p>I am extracting data from SQL server to a csv format then reading the file in. </p>
  
  <pre><code>df = pd.read_csv(
                              'TKY_RFQs.csv', 
                              sep='~', 
                              usecols=[
                                       0,1,2,3,4,5,6,7,8,9,
                                       10,11,12,13,14,15,16,17,18,19,
                                       20,21,22,23,24,25,26,27,28,29,
                                       30,31,32,33,34,35,36,37
                                      ]
                  )
  </code></pre>
  
  <p>There is a blank row then the record count at the end of the file which I would like to remove.</p>
  
  <p><a href="https://i.stack.imgur.com/frYjZ.png" rel="nofollow noreferrer">End of file screenshot</a></p>
  
  <p>I have been getting around the issue via this code but would like to resolve the root problem:</p>
  
  <pre><code># Count_Row=df.shape[0] # gives number of row count
  # df_Sample = df[['trading_book','state', 'rfq_num_of_dealers']].head(Count_Row-1)
  </code></pre>
  
  <p>Is there a way to exclude the last two rows in the file or alternativcely remove any row which has null values for all columns?</p>
  
  <p>Pete</p>