title: Merging two pandas dataframes results in "duplicate" columns
body: <p>I'm trying to merge two dataframes which contain the same key column. Some of the other columns also have identical headers, although not an equal number of rows, and after merging these columns are "duplicated" with the original headers given a postscript _x, _y, etc.</p>
  
  <p>Does anyone know how to get pandas to drop the duplicate columns in the example below?</p>
  
  <p>This is my python code:</p>
  
  <pre><code>import pandas as pd
  
  holding_df = pd.read_csv('holding.csv')
  invest_df = pd.read_csv('invest.csv')
  
  merge_df = pd.merge(holding_df, invest_df, on='key', how='left').fillna(0)
  merge_df.to_csv('merged.csv', index=False)
  </code></pre>
  
  <p>And the CSV files contain this:</p>
  
  <p>First rows of left-dataframe (holding_df)</p>
  
  <pre><code>key, dept_name, res_name, year, need, holding
  DeptA_ResA_2015, DeptA, ResA, 2015, 1, 1
  DeptA_ResA_2016, DeptA, ResA, 2016, 1, 1
  DeptA_ResA_2017, DeptA, ResA, 2017, 1, 1
  ...
  </code></pre>
  
  <p>Right-dataframe (invest_df)</p>
  
  <pre><code>key, dept_name, res_name, year, no_of_inv, inv_cost_wo_ice
  DeptA_ResA_2015, DeptA, ResA, 2015, 1, 1000000
  DeptA_ResB_2015, DeptA, ResB, 2015, 2, 6000000
  DeptB_ResB_2015, DeptB, ResB, 2015, 1, 6000000
  ...
  </code></pre>
  
  <p>Merged result</p>
  
  <pre><code>key, dept_name_x, res_name_x, year_x, need, holding, dept_name_y, res_name_y, year_y, no_of_inv, inv_cost_wo_ice
  DeptA_ResA_2015, DeptA, ResA, 2015, 1, 1, DeptA, ResA, 2015.0, 1.0, 1000000.0
  DeptA_ResA_2016, DeptA, ResA, 2016, 1, 1, 0, 0, 0.0, 0.0, 0.0
  DeptA_ResA_2017, DeptA, ResA, 2017, 1, 1, 0, 0, 0.0, 0.0, 0.0
  DeptA_ResA_2018, DeptA, ResA, 2018, 1, 1, 0, 0, 0.0, 0.0, 0.0
  DeptA_ResA_2019, DeptA, ResA, 2019, 1, 1, 0, 0, 0.0, 0.0, 0.0
  ...
  </code></pre>