Convert a list of lists into a Pandas Dataframe












10












$begingroup$


I am trying to convert a list of lists which looks like the following into a Pandas Dataframe



[['New York Yankees ', '"Acevedo Juan"  ', 900000, ' Pitchern'], 

['New York Yankees ', '"Anderson Jason"', 300000, ' Pitchern'], 

['New York Yankees ', '"Clemens Roger" ', 10100000, ' Pitchern'], 

['New York Yankees ', '"Contreras Jose"', 5500000, ' Pitchern']]


I am basically trying to convert each item in the array into a pandas data frame which has four columns. What would be the best approach to this as pd.Dataframe does not quite give me what I am looking for.






pandas







share|improve this question











$endgroup$












  • $begingroup$
    see this question in stack overflow: stackoverflow.com/questions/.../…
    $endgroup$
    – keramat
    Jan 5 '18 at 18:46
















10












$begingroup$


I am trying to convert a list of lists which looks like the following into a Pandas Dataframe



[['New York Yankees ', '"Acevedo Juan"  ', 900000, ' Pitchern'], 

['New York Yankees ', '"Anderson Jason"', 300000, ' Pitchern'], 

['New York Yankees ', '"Clemens Roger" ', 10100000, ' Pitchern'], 

['New York Yankees ', '"Contreras Jose"', 5500000, ' Pitchern']]


I am basically trying to convert each item in the array into a pandas data frame which has four columns. What would be the best approach to this as pd.Dataframe does not quite give me what I am looking for.






pandas







share|improve this question











$endgroup$












  • $begingroup$
    see this question in stack overflow: stackoverflow.com/questions/.../…
    $endgroup$
    – keramat
    Jan 5 '18 at 18:46














10












10








10


3



$begingroup$


I am trying to convert a list of lists which looks like the following into a Pandas Dataframe



[['New York Yankees ', '"Acevedo Juan"  ', 900000, ' Pitchern'], 

['New York Yankees ', '"Anderson Jason"', 300000, ' Pitchern'], 

['New York Yankees ', '"Clemens Roger" ', 10100000, ' Pitchern'], 

['New York Yankees ', '"Contreras Jose"', 5500000, ' Pitchern']]


I am basically trying to convert each item in the array into a pandas data frame which has four columns. What would be the best approach to this as pd.Dataframe does not quite give me what I am looking for.






pandas







share|improve this question











$endgroup$




I am trying to convert a list of lists which looks like the following into a Pandas Dataframe



[['New York Yankees ', '"Acevedo Juan"  ', 900000, ' Pitchern'], 

['New York Yankees ', '"Anderson Jason"', 300000, ' Pitchern'], 

['New York Yankees ', '"Clemens Roger" ', 10100000, ' Pitchern'], 

['New York Yankees ', '"Contreras Jose"', 5500000, ' Pitchern']]


I am basically trying to convert each item in the array into a pandas data frame which has four columns. What would be the best approach to this as pd.Dataframe does not quite give me what I am looking for.






pandas




pandas






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Jun 5 '18 at 18:51









Emre

8,54011935




8,54011935










asked Jan 5 '18 at 18:40









Aravind VeluchamyAravind Veluchamy

51113




51113












  • $begingroup$
    see this question in stack overflow: stackoverflow.com/questions/.../…
    $endgroup$
    – keramat
    Jan 5 '18 at 18:46


















  • $begingroup$
    see this question in stack overflow: stackoverflow.com/questions/.../…
    $endgroup$
    – keramat
    Jan 5 '18 at 18:46
















$begingroup$
see this question in stack overflow: stackoverflow.com/questions/.../…
$endgroup$
– keramat
Jan 5 '18 at 18:46




$begingroup$
see this question in stack overflow: stackoverflow.com/questions/.../…
$endgroup$
– keramat
Jan 5 '18 at 18:46










3 Answers
3






active

oldest

votes


















13












$begingroup$

from pandas import DataFrame

data = [['New York Yankees', 'Acevedo Juan', 900000, 'Pitcher'], 

['New York Yankees', 'Anderson Jason', 300000, 'Pitcher'], 

['New York Yankees', 'Clemens Roger', 10100000, 'Pitcher'], 

['New York Yankees', 'Contreras Jose', 5500000, 'Pitcher']]

DataFrame.from_records(data)





share|improve this answer











$endgroup$









  • 1




    $begingroup$
    You could refine it a bit more with: DataFrame.from_records(data, columns=['Team', 'Player', 'whatever-stat-is-that', 'position'])
    $endgroup$
    – Juan Ignacio Gil
    Jan 11 '18 at 10:14










  • $begingroup$
    Is there a way to specify the imports more specifically? E.g. I want to specify that DataFrame["Team"] must refer to the first item of each sublist (i.e. data[i][0]) and DataFrame["Position"] to refer to the last item of each sublist (i.e. data[i][-1])?
    $endgroup$
    – Ivo
    Jan 17 at 15:20










  • $begingroup$
    @Ivo: Use the columns parameter of DataFrame.from_records.
    $endgroup$
    – Emre
    Jan 17 at 21:27





















3












$begingroup$

You can just directly define it as a data frame as follows:



import pandas as pd



data = [['New York Yankees', 'Acevedo Juan', 900000, 'Pitcher'], 

        ['New York Yankees', 'Anderson Jason', 300000, 'Pitcher'], 

        ['New York Yankees', 'Clemens Roger', 10100000, 'Pitcher'], 

        ['New York Yankees', 'Contreras Jose', 5500000, 'Pitcher']]



data = pd.DataFrame(data)





share|improve this answer









$endgroup$





















    3












    $begingroup$

    Once you have the data:



    import pandas as pd
    

    
data = [['New York Yankees ', '"Acevedo Juan"  ', 900000, ' Pitchern'], 
    
        ['New York Yankees ', '"Anderson Jason"', 300000, ' Pitchern'], 
    
        ['New York Yankees ', '"Clemens Roger" ', 10100000, ' Pitchern'], 
    
        ['New York Yankees ', '"Contreras Jose"', 5500000, ' Pitchern']]


    You can create dataframe from the transposing the data:



    data_transposed = zip(data)
    
df = pd.DataFrame(data_transposed, columns=["Team", "Player", "Salary", "Role"])


    Another way:



    df = pd.DataFrame(data)
    
df = df.transpose()
    
df.columns = ["Team", "Player", "Salary", "Role"]





    share|improve this answer











    $endgroup$













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      3 Answers
      3






      active

      oldest

      votes








      3 Answers
      3






      active

      oldest

      votes









      active

      oldest

      votes






      active

      oldest

      votes









      13












      $begingroup$

      from pandas import DataFrame
      
data = [['New York Yankees', 'Acevedo Juan', 900000, 'Pitcher'], 
      
['New York Yankees', 'Anderson Jason', 300000, 'Pitcher'], 
      
['New York Yankees', 'Clemens Roger', 10100000, 'Pitcher'], 
      
['New York Yankees', 'Contreras Jose', 5500000, 'Pitcher']]
      
DataFrame.from_records(data)





      share|improve this answer











      $endgroup$









      • 1




        $begingroup$
        You could refine it a bit more with: DataFrame.from_records(data, columns=['Team', 'Player', 'whatever-stat-is-that', 'position'])
        $endgroup$
        – Juan Ignacio Gil
        Jan 11 '18 at 10:14










      • $begingroup$
        Is there a way to specify the imports more specifically? E.g. I want to specify that DataFrame["Team"] must refer to the first item of each sublist (i.e. data[i][0]) and DataFrame["Position"] to refer to the last item of each sublist (i.e. data[i][-1])?
        $endgroup$
        – Ivo
        Jan 17 at 15:20










      • $begingroup$
        @Ivo: Use the columns parameter of DataFrame.from_records.
        $endgroup$
        – Emre
        Jan 17 at 21:27


















      13












      $begingroup$

      from pandas import DataFrame
      
data = [['New York Yankees', 'Acevedo Juan', 900000, 'Pitcher'], 
      
['New York Yankees', 'Anderson Jason', 300000, 'Pitcher'], 
      
['New York Yankees', 'Clemens Roger', 10100000, 'Pitcher'], 
      
['New York Yankees', 'Contreras Jose', 5500000, 'Pitcher']]
      
DataFrame.from_records(data)





      share|improve this answer











      $endgroup$









      • 1




        $begingroup$
        You could refine it a bit more with: DataFrame.from_records(data, columns=['Team', 'Player', 'whatever-stat-is-that', 'position'])
        $endgroup$
        – Juan Ignacio Gil
        Jan 11 '18 at 10:14










      • $begingroup$
        Is there a way to specify the imports more specifically? E.g. I want to specify that DataFrame["Team"] must refer to the first item of each sublist (i.e. data[i][0]) and DataFrame["Position"] to refer to the last item of each sublist (i.e. data[i][-1])?
        $endgroup$
        – Ivo
        Jan 17 at 15:20










      • $begingroup$
        @Ivo: Use the columns parameter of DataFrame.from_records.
        $endgroup$
        – Emre
        Jan 17 at 21:27
















      13












      13








      13





      $begingroup$

      from pandas import DataFrame
      
data = [['New York Yankees', 'Acevedo Juan', 900000, 'Pitcher'], 
      
['New York Yankees', 'Anderson Jason', 300000, 'Pitcher'], 
      
['New York Yankees', 'Clemens Roger', 10100000, 'Pitcher'], 
      
['New York Yankees', 'Contreras Jose', 5500000, 'Pitcher']]
      
DataFrame.from_records(data)





      share|improve this answer











      $endgroup$



      from pandas import DataFrame
      
data = [['New York Yankees', 'Acevedo Juan', 900000, 'Pitcher'], 
      
['New York Yankees', 'Anderson Jason', 300000, 'Pitcher'], 
      
['New York Yankees', 'Clemens Roger', 10100000, 'Pitcher'], 
      
['New York Yankees', 'Contreras Jose', 5500000, 'Pitcher']]
      
DataFrame.from_records(data)






      share|improve this answer














      share|improve this answer



      share|improve this answer








      edited Jan 6 '18 at 0:58

























      answered Jan 5 '18 at 18:46









      EmreEmre

      8,54011935




      8,54011935








      • 1




        $begingroup$
        You could refine it a bit more with: DataFrame.from_records(data, columns=['Team', 'Player', 'whatever-stat-is-that', 'position'])
        $endgroup$
        – Juan Ignacio Gil
        Jan 11 '18 at 10:14










      • $begingroup$
        Is there a way to specify the imports more specifically? E.g. I want to specify that DataFrame["Team"] must refer to the first item of each sublist (i.e. data[i][0]) and DataFrame["Position"] to refer to the last item of each sublist (i.e. data[i][-1])?
        $endgroup$
        – Ivo
        Jan 17 at 15:20










      • $begingroup$
        @Ivo: Use the columns parameter of DataFrame.from_records.
        $endgroup$
        – Emre
        Jan 17 at 21:27
















      • 1




        $begingroup$
        You could refine it a bit more with: DataFrame.from_records(data, columns=['Team', 'Player', 'whatever-stat-is-that', 'position'])
        $endgroup$
        – Juan Ignacio Gil
        Jan 11 '18 at 10:14










      • $begingroup$
        Is there a way to specify the imports more specifically? E.g. I want to specify that DataFrame["Team"] must refer to the first item of each sublist (i.e. data[i][0]) and DataFrame["Position"] to refer to the last item of each sublist (i.e. data[i][-1])?
        $endgroup$
        – Ivo
        Jan 17 at 15:20










      • $begingroup$
        @Ivo: Use the columns parameter of DataFrame.from_records.
        $endgroup$
        – Emre
        Jan 17 at 21:27










      1




      1




      $begingroup$
      You could refine it a bit more with: DataFrame.from_records(data, columns=['Team', 'Player', 'whatever-stat-is-that', 'position'])
      $endgroup$
      – Juan Ignacio Gil
      Jan 11 '18 at 10:14




      $begingroup$
      You could refine it a bit more with: DataFrame.from_records(data, columns=['Team', 'Player', 'whatever-stat-is-that', 'position'])
      $endgroup$
      – Juan Ignacio Gil
      Jan 11 '18 at 10:14












      $begingroup$
      Is there a way to specify the imports more specifically? E.g. I want to specify that DataFrame["Team"] must refer to the first item of each sublist (i.e. data[i][0]) and DataFrame["Position"] to refer to the last item of each sublist (i.e. data[i][-1])?
      $endgroup$
      – Ivo
      Jan 17 at 15:20




      $begingroup$
      Is there a way to specify the imports more specifically? E.g. I want to specify that DataFrame["Team"] must refer to the first item of each sublist (i.e. data[i][0]) and DataFrame["Position"] to refer to the last item of each sublist (i.e. data[i][-1])?
      $endgroup$
      – Ivo
      Jan 17 at 15:20












      $begingroup$
      @Ivo: Use the columns parameter of DataFrame.from_records.
      $endgroup$
      – Emre
      Jan 17 at 21:27






      $begingroup$
      @Ivo: Use the columns parameter of DataFrame.from_records.
      $endgroup$
      – Emre
      Jan 17 at 21:27













      3












      $begingroup$

      You can just directly define it as a data frame as follows:



      import pandas as pd
      

      
data = [['New York Yankees', 'Acevedo Juan', 900000, 'Pitcher'], 
      
        ['New York Yankees', 'Anderson Jason', 300000, 'Pitcher'], 
      
        ['New York Yankees', 'Clemens Roger', 10100000, 'Pitcher'], 
      
        ['New York Yankees', 'Contreras Jose', 5500000, 'Pitcher']]
      

      
data = pd.DataFrame(data)





      share|improve this answer









      $endgroup$


















        3












        $begingroup$

        You can just directly define it as a data frame as follows:



        import pandas as pd
        

        
data = [['New York Yankees', 'Acevedo Juan', 900000, 'Pitcher'], 
        
        ['New York Yankees', 'Anderson Jason', 300000, 'Pitcher'], 
        
        ['New York Yankees', 'Clemens Roger', 10100000, 'Pitcher'], 
        
        ['New York Yankees', 'Contreras Jose', 5500000, 'Pitcher']]
        

        
data = pd.DataFrame(data)





        share|improve this answer









        $endgroup$
















          3












          3








          3





          $begingroup$

          You can just directly define it as a data frame as follows:



          import pandas as pd
          

          
data = [['New York Yankees', 'Acevedo Juan', 900000, 'Pitcher'], 
          
        ['New York Yankees', 'Anderson Jason', 300000, 'Pitcher'], 
          
        ['New York Yankees', 'Clemens Roger', 10100000, 'Pitcher'], 
          
        ['New York Yankees', 'Contreras Jose', 5500000, 'Pitcher']]
          

          
data = pd.DataFrame(data)





          share|improve this answer









          $endgroup$



          You can just directly define it as a data frame as follows:



          import pandas as pd
          

          
data = [['New York Yankees', 'Acevedo Juan', 900000, 'Pitcher'], 
          
        ['New York Yankees', 'Anderson Jason', 300000, 'Pitcher'], 
          
        ['New York Yankees', 'Clemens Roger', 10100000, 'Pitcher'], 
          
        ['New York Yankees', 'Contreras Jose', 5500000, 'Pitcher']]
          

          
data = pd.DataFrame(data)






          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered Jan 6 '18 at 5:43









          LUSAQXLUSAQX

          348416




          348416























              3












              $begingroup$

              Once you have the data:



              import pandas as pd
              

              
data = [['New York Yankees ', '"Acevedo Juan"  ', 900000, ' Pitchern'], 
              
        ['New York Yankees ', '"Anderson Jason"', 300000, ' Pitchern'], 
              
        ['New York Yankees ', '"Clemens Roger" ', 10100000, ' Pitchern'], 
              
        ['New York Yankees ', '"Contreras Jose"', 5500000, ' Pitchern']]


              You can create dataframe from the transposing the data:



              data_transposed = zip(data)
              
df = pd.DataFrame(data_transposed, columns=["Team", "Player", "Salary", "Role"])


              Another way:



              df = pd.DataFrame(data)
              
df = df.transpose()
              
df.columns = ["Team", "Player", "Salary", "Role"]





              share|improve this answer











              $endgroup$


















                3












                $begingroup$

                Once you have the data:



                import pandas as pd
                

                
data = [['New York Yankees ', '"Acevedo Juan"  ', 900000, ' Pitchern'], 
                
        ['New York Yankees ', '"Anderson Jason"', 300000, ' Pitchern'], 
                
        ['New York Yankees ', '"Clemens Roger" ', 10100000, ' Pitchern'], 
                
        ['New York Yankees ', '"Contreras Jose"', 5500000, ' Pitchern']]


                You can create dataframe from the transposing the data:



                data_transposed = zip(data)
                
df = pd.DataFrame(data_transposed, columns=["Team", "Player", "Salary", "Role"])


                Another way:



                df = pd.DataFrame(data)
                
df = df.transpose()
                
df.columns = ["Team", "Player", "Salary", "Role"]





                share|improve this answer











                $endgroup$
















                  3












                  3








                  3





                  $begingroup$

                  Once you have the data:



                  import pandas as pd
                  

                  
data = [['New York Yankees ', '"Acevedo Juan"  ', 900000, ' Pitchern'], 
                  
        ['New York Yankees ', '"Anderson Jason"', 300000, ' Pitchern'], 
                  
        ['New York Yankees ', '"Clemens Roger" ', 10100000, ' Pitchern'], 
                  
        ['New York Yankees ', '"Contreras Jose"', 5500000, ' Pitchern']]


                  You can create dataframe from the transposing the data:



                  data_transposed = zip(data)
                  
df = pd.DataFrame(data_transposed, columns=["Team", "Player", "Salary", "Role"])


                  Another way:



                  df = pd.DataFrame(data)
                  
df = df.transpose()
                  
df.columns = ["Team", "Player", "Salary", "Role"]





                  share|improve this answer











                  $endgroup$



                  Once you have the data:



                  import pandas as pd
                  

                  
data = [['New York Yankees ', '"Acevedo Juan"  ', 900000, ' Pitchern'], 
                  
        ['New York Yankees ', '"Anderson Jason"', 300000, ' Pitchern'], 
                  
        ['New York Yankees ', '"Clemens Roger" ', 10100000, ' Pitchern'], 
                  
        ['New York Yankees ', '"Contreras Jose"', 5500000, ' Pitchern']]


                  You can create dataframe from the transposing the data:



                  data_transposed = zip(data)
                  
df = pd.DataFrame(data_transposed, columns=["Team", "Player", "Salary", "Role"])


                  Another way:



                  df = pd.DataFrame(data)
                  
df = df.transpose()
                  
df.columns = ["Team", "Player", "Salary", "Role"]






                  share|improve this answer














                  share|improve this answer



                  share|improve this answer








                  edited 13 hours ago









                  Coolio2654

                  1255




                  1255










                  answered Oct 3 '18 at 10:27









                  Paloma ManzanoPaloma Manzano

                  311




                  311






























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