title: Remove Column with Duplicate Values in Pandas
body: <p>I have a database with sample as below:
  <a href="https://i.stack.imgur.com/mdNXj.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/mdNXj.png" alt="enter image description here"></a></p>
  
  <p>Data frame is generated when I load data in Python as per below code</p>
  
  <pre><code>import os
  import pandas as pd
  data_dir="D:\\userdata\\adbharga\\Desktop\\AVA\\PythonCoding\\VF-Aus\\4G Cell Graphs"
  os.chdir(data_dir)
  df = pd.read_csv('CA Throughput(Kbit_s) .csv',index_col=None, header=0)
  </code></pre>
  
  <p>Output:</p>
  
  <p><a href="https://i.stack.imgur.com/xfHvi.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/xfHvi.png" alt="enter image description here"></a></p>
  
  <p>Is there any way by which we can avoid reading duplicate columns in Pandas, or remove the duplicate columns post reading.
  Pl Note: Column Name is different once data is read in Pandas, so command like df=df.loc[:,~df.columns.duplicated()] won't work.
  Actual database is very big and has many duplicate column with Dates only.</p>