title: Converting to Excel "Date" format (within Excel file) using python and pandas from another date format from html table
body: <p>I am new to python and exploring to get data from excel using it and found pandas library to get data</p>
  <p>I need to get the rates from a HTML table on a website. <a href="https://i.stack.imgur.com/p3M8z.png" rel="nofollow noreferrer">Table from which the data has to be read</a>
  Then dump it in an excel file.
  I am using Python
  I have used the following code</p>
  <pre><code>import pandas as pd
  from datetime import datetime
  import lxml as lx
  import openpyxl as oxl
  url = &quot;https://www.example.com&quot;
  
  tables = pd.read_html(url)
  table = tables[0]
  table.to_excel('output.xlsx')
  </code></pre>
  <p>The dates are in dd mmm yyyy format in the 'Effective Date' column</p>
  <p>I would like to convert them to the dd/mm/yyyy format</p>
  <p>I used the following code to convert the table</p>
  <pre><code>['Effective Date'] = pd.to_datetime(table['Effective Date'],
                                          infer_datetime_format=False, format='%d/%m/%Y', errors='ignore')
  </code></pre>
  <p>but it fails to convert the dates in the column. Could someone head me in some proper direction please.</p>
  <p>Here is the complete code</p>
  <pre><code>import pandas as pd
  import html5lib
  import datetime
  import locale
  import pytz
  import lxml as lx
  import openpyxl as oxl
  
  url = &quot;https://www.rba.gov.au/statistics/cash-rate/&quot;
  
  tables = pd.read_html(url)
  
  table = tables[0]
  
  table['Effective Date'] = pd.to_datetime(table['Effective Date'],
                                          infer_datetime_format=False, format='%d/%m/%Y', errors='ignore')
  
  table.to_excel('rates.xlsx')
  </code></pre>