title: Normalization Of single Column Of Dataframe
body: <p>I have a Dataframe as shown:</p>
  <p><a href="https://i.stack.imgur.com/pFIwk.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/pFIwk.png" alt="Dataframe" /></a></p>
  <p>I have to normalise the Close column of dataframe as follows:</p>
  <ol>
  <li><p>For Each symbol we have to divide the close price on succeeding days by the First close price. This means the normalised closed for APLAPOLLO on 24/11/2020 will be calculated as:</p>
  <p><strong><strong>Normalised_Close_price=(Close on 24/11/2020)/(Close on 23/11/2020)=0.9915</strong>( Valid Only For Aplapollo)</strong></p>
  </li>
  <li><p>Now if the symbol changes the method remains same only the values in the above formulae changes. Hence For AUBANK the normalised closed on 24/11/2020 will be calculated as:</p>
  <p><strong><strong>Normalised_Close_price=(Close on 24/11/2020)/(Close on 23/11/2020)=0.9915</strong>( Valid Only for AUBANK)</strong></p>
  </li>
  <li><p>The normalised close for other symbol should be calculated in the same way.</p>
  </li>
  </ol>
  <p>Hence after the calculation the dataframe should look as shown:</p>
  <p><a href="https://i.stack.imgur.com/CsyvX.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/CsyvX.png" alt="Expected Dataframe" /></a></p>
  <p>eg: For Aplapollo from above explanation:</p>
  <ol>
  <li>normalise value for 24/11/2020=(3219.95/3247.45)=0.991532</li>
  <li>normalise value for 25/11/2020=(Close on 25/11/2020)/(Close on 23/11/2020)=0.991686</li>
  <li>normalise value for 26/11/2020=(Close on 26/11/2020)/(Close on 23/11/2020)=0.978907</li>
  </ol>
  <p>Similarly for other symbols</p>
  <p>I have referred to the following answer on normalising dataframe columns:</p>
  <p><a href="https://stackoverflow.com/questions/26414913/normalize-columns-of-pandas-data-frame#:%7E:text=You%20can%20apply%20a%20custom%20function%20to%20operate%20the%20DataFrame%20.&amp;text=it%20takes%20mean%20for%20each,is%20the%20normalized%20data%20set.&amp;text=Pandas%20does%20column%20wise%20normalization%20by%20default.">Normalize columns of pandas data frame</a></p>
  <p>This does not help as the values are changing as per the condition in my case</p>