title: Remove/sum duplicate row with pandas
body: <p>I have this dataframe, How can i make condition that if i have a duplicate row if that they are exactly the same(Mercedes exp) I keep only one (without making the sum) Or make the sum (kia case) if there is a diffrence in rent/sale value</p>
  <p><strong>Df example</strong></p>
  <pre><code>  cars      rent  sale
    Kia       1     2
    Bmw       1     4
    Mercedes  2     1
    Ford      1     1
    Kia       4     5
    Mercedes  2     1
  </code></pre>
  <p>i write this code:</p>
  <pre><code>import pandas as pd 
  
  df=pd.DataFrame({'cars':['Kia','Bmw','Mercedes','Ford','Kia','Mercedes'],
                  'rent':[1,1,2,1,4,2],
                  'sale':[2,4,1,1,5,1]})
  
  df=df.groupby(['cars']).sum().reset_index()
  print(df)
  </code></pre>
  <p>I got <strong>this output:</strong></p>
  <pre><code>       cars  rent  sale
  0       Bmw     1     4
  1      Ford     1     1
  2       Kia     5     7
  3  Mercedes     4     2
  </code></pre>
  <p><strong>Expected output</strong>:</p>
  <pre><code>        cars  rent  sale
  0       Kia     5     7
  1       Bmw     1     4
  2  Mercedes     2     1
  3      Ford     1     1
  </code></pre>