Faster way to transform full names to surname and initial











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I have a large data frame that I want to merge with another dataset. In order to do so i need to get the names of individuals into a certain format. The function below converts the name in 'column' to the desired format (mostly) and stores it in 'newColumn'.



My question is, is there a better (faster and/or more puthonic) way to do this?



The main aim is to transform full names into surname and initials. ie:




  • Novak Djokovic = Djokovic N.

  • Jo-Wilfred Tsonga = Tsonga J.W.

  • Victor Estrella Burgos = Burgos V.E.


  • Juan Martin Del Potro = Del Potro J.M.



    def convertNames(df,column, newColumn):
    df[newColumn] = 'none'

    for player in df[column]:

    names = player.split(' ')

    if len(names) == 2:

    if (len(names[0].split('-')) > 1):
    newName = names[1]+' '+names[0].split('-')[0][0]+'.'+names[0].split('-')[1][0]+'.'
    else:
    newName = names[1]+' '+names[0][0]+'.'

    elif len(names) == 3:
    newName = names[1]+' '+names[2]+' '+names[0][0]+'.'

    else:
    newName = names[2]+' '+names[3]+' '+names[0][0]+'.'+names[1][0]+'.'

    df[newColumn][df[column] == player] = newName

    return df











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    up vote
    0
    down vote

    favorite












    I have a large data frame that I want to merge with another dataset. In order to do so i need to get the names of individuals into a certain format. The function below converts the name in 'column' to the desired format (mostly) and stores it in 'newColumn'.



    My question is, is there a better (faster and/or more puthonic) way to do this?



    The main aim is to transform full names into surname and initials. ie:




    • Novak Djokovic = Djokovic N.

    • Jo-Wilfred Tsonga = Tsonga J.W.

    • Victor Estrella Burgos = Burgos V.E.


    • Juan Martin Del Potro = Del Potro J.M.



      def convertNames(df,column, newColumn):
      df[newColumn] = 'none'

      for player in df[column]:

      names = player.split(' ')

      if len(names) == 2:

      if (len(names[0].split('-')) > 1):
      newName = names[1]+' '+names[0].split('-')[0][0]+'.'+names[0].split('-')[1][0]+'.'
      else:
      newName = names[1]+' '+names[0][0]+'.'

      elif len(names) == 3:
      newName = names[1]+' '+names[2]+' '+names[0][0]+'.'

      else:
      newName = names[2]+' '+names[3]+' '+names[0][0]+'.'+names[1][0]+'.'

      df[newColumn][df[column] == player] = newName

      return df











    share|improve this question
























      up vote
      0
      down vote

      favorite









      up vote
      0
      down vote

      favorite











      I have a large data frame that I want to merge with another dataset. In order to do so i need to get the names of individuals into a certain format. The function below converts the name in 'column' to the desired format (mostly) and stores it in 'newColumn'.



      My question is, is there a better (faster and/or more puthonic) way to do this?



      The main aim is to transform full names into surname and initials. ie:




      • Novak Djokovic = Djokovic N.

      • Jo-Wilfred Tsonga = Tsonga J.W.

      • Victor Estrella Burgos = Burgos V.E.


      • Juan Martin Del Potro = Del Potro J.M.



        def convertNames(df,column, newColumn):
        df[newColumn] = 'none'

        for player in df[column]:

        names = player.split(' ')

        if len(names) == 2:

        if (len(names[0].split('-')) > 1):
        newName = names[1]+' '+names[0].split('-')[0][0]+'.'+names[0].split('-')[1][0]+'.'
        else:
        newName = names[1]+' '+names[0][0]+'.'

        elif len(names) == 3:
        newName = names[1]+' '+names[2]+' '+names[0][0]+'.'

        else:
        newName = names[2]+' '+names[3]+' '+names[0][0]+'.'+names[1][0]+'.'

        df[newColumn][df[column] == player] = newName

        return df











      share|improve this question













      I have a large data frame that I want to merge with another dataset. In order to do so i need to get the names of individuals into a certain format. The function below converts the name in 'column' to the desired format (mostly) and stores it in 'newColumn'.



      My question is, is there a better (faster and/or more puthonic) way to do this?



      The main aim is to transform full names into surname and initials. ie:




      • Novak Djokovic = Djokovic N.

      • Jo-Wilfred Tsonga = Tsonga J.W.

      • Victor Estrella Burgos = Burgos V.E.


      • Juan Martin Del Potro = Del Potro J.M.



        def convertNames(df,column, newColumn):
        df[newColumn] = 'none'

        for player in df[column]:

        names = player.split(' ')

        if len(names) == 2:

        if (len(names[0].split('-')) > 1):
        newName = names[1]+' '+names[0].split('-')[0][0]+'.'+names[0].split('-')[1][0]+'.'
        else:
        newName = names[1]+' '+names[0][0]+'.'

        elif len(names) == 3:
        newName = names[1]+' '+names[2]+' '+names[0][0]+'.'

        else:
        newName = names[2]+' '+names[3]+' '+names[0][0]+'.'+names[1][0]+'.'

        df[newColumn][df[column] == player] = newName

        return df








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      asked 23 mins ago









      theotheraussie

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