Key error when selecting columns in pandas dataframe after read_csv











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I'm trying to read in a CSV file into a pandas dataframe and select a column, but keep getting a key error.



The file reads in successfully and I can view the dataframe in an iPython notebook, but when I want to select a column any other than the first one, it throws a key error.



I am using this code:



import pandas as pd

transactions = pd.read_csv('transactions.csv',low_memory=False, delimiter=',', header=0, encoding='ascii')
transactions['quarter']


This is the file I'm working on:
https://www.dropbox.com/s/imd7hq2iq23hf8o/transactions.csv?dl=0



Thank you!










share|improve this question




























    up vote
    4
    down vote

    favorite
    1












    I'm trying to read in a CSV file into a pandas dataframe and select a column, but keep getting a key error.



    The file reads in successfully and I can view the dataframe in an iPython notebook, but when I want to select a column any other than the first one, it throws a key error.



    I am using this code:



    import pandas as pd

    transactions = pd.read_csv('transactions.csv',low_memory=False, delimiter=',', header=0, encoding='ascii')
    transactions['quarter']


    This is the file I'm working on:
    https://www.dropbox.com/s/imd7hq2iq23hf8o/transactions.csv?dl=0



    Thank you!










    share|improve this question


























      up vote
      4
      down vote

      favorite
      1









      up vote
      4
      down vote

      favorite
      1






      1





      I'm trying to read in a CSV file into a pandas dataframe and select a column, but keep getting a key error.



      The file reads in successfully and I can view the dataframe in an iPython notebook, but when I want to select a column any other than the first one, it throws a key error.



      I am using this code:



      import pandas as pd

      transactions = pd.read_csv('transactions.csv',low_memory=False, delimiter=',', header=0, encoding='ascii')
      transactions['quarter']


      This is the file I'm working on:
      https://www.dropbox.com/s/imd7hq2iq23hf8o/transactions.csv?dl=0



      Thank you!










      share|improve this question















      I'm trying to read in a CSV file into a pandas dataframe and select a column, but keep getting a key error.



      The file reads in successfully and I can view the dataframe in an iPython notebook, but when I want to select a column any other than the first one, it throws a key error.



      I am using this code:



      import pandas as pd

      transactions = pd.read_csv('transactions.csv',low_memory=False, delimiter=',', header=0, encoding='ascii')
      transactions['quarter']


      This is the file I'm working on:
      https://www.dropbox.com/s/imd7hq2iq23hf8o/transactions.csv?dl=0



      Thank you!







      python csv pandas






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Mar 6 '16 at 19:32









      MaxU

      118k11106163




      118k11106163










      asked Mar 6 '16 at 19:30









      Harry M

      1292414




      1292414
























          3 Answers
          3






          active

          oldest

          votes

















          up vote
          22
          down vote



          accepted










          use sep='s*,s*' so that you will take care of spaces in column-names:



          transactions = pd.read_csv('transactions.csv', sep='s*,s*',
          header=0, encoding='ascii', engine='python')


          alternatively you can make sure that you don't have unquoted spaces in your CSV file and use your command (unchanged)



          prove:



          print(transactions.columns.tolist())


          Output:



          ['product_id', 'customer_id', 'store_id', 'promotion_id', 'month_of_year', 'quarter', 'the_year', 'store_sales', 'store_cost', 'unit_sales', 'fact_count']





          share|improve this answer























          • You are amazing! Thanks so much!!
            – Harry M
            Mar 6 '16 at 19:45






          • 1




            the list showed me i had an extra space in the name. thanks so much, i have been bashing my head against the wall for a few hrz now
            – Mickey Perlstein
            Sep 2 at 11:03


















          up vote
          0
          down vote













          I finally got the answer how to read a specific column:



          import pandas as pd  

          df=pd.read_csv('titanic.csv',sep='t')

          df['Sex']


          Because pandas separator uses t. I hope that works for you.






          share|improve this answer






























            up vote
            0
            down vote













            The key error generally comes if the key doesn't match any of the dataframe column name 'exactly':



            You could also try:



            import csv
            import pandas as pd
            import re
            with open (filename, "r") as file:
            df = pd.read_csv(file, delimiter = ",")
            df.columns = ((df.columns.str).replace("^ ","")).str.replace(" $","")
            print(df.columns)





            share|improve this answer





















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              3 Answers
              3






              active

              oldest

              votes








              3 Answers
              3






              active

              oldest

              votes









              active

              oldest

              votes






              active

              oldest

              votes








              up vote
              22
              down vote



              accepted










              use sep='s*,s*' so that you will take care of spaces in column-names:



              transactions = pd.read_csv('transactions.csv', sep='s*,s*',
              header=0, encoding='ascii', engine='python')


              alternatively you can make sure that you don't have unquoted spaces in your CSV file and use your command (unchanged)



              prove:



              print(transactions.columns.tolist())


              Output:



              ['product_id', 'customer_id', 'store_id', 'promotion_id', 'month_of_year', 'quarter', 'the_year', 'store_sales', 'store_cost', 'unit_sales', 'fact_count']





              share|improve this answer























              • You are amazing! Thanks so much!!
                – Harry M
                Mar 6 '16 at 19:45






              • 1




                the list showed me i had an extra space in the name. thanks so much, i have been bashing my head against the wall for a few hrz now
                – Mickey Perlstein
                Sep 2 at 11:03















              up vote
              22
              down vote



              accepted










              use sep='s*,s*' so that you will take care of spaces in column-names:



              transactions = pd.read_csv('transactions.csv', sep='s*,s*',
              header=0, encoding='ascii', engine='python')


              alternatively you can make sure that you don't have unquoted spaces in your CSV file and use your command (unchanged)



              prove:



              print(transactions.columns.tolist())


              Output:



              ['product_id', 'customer_id', 'store_id', 'promotion_id', 'month_of_year', 'quarter', 'the_year', 'store_sales', 'store_cost', 'unit_sales', 'fact_count']





              share|improve this answer























              • You are amazing! Thanks so much!!
                – Harry M
                Mar 6 '16 at 19:45






              • 1




                the list showed me i had an extra space in the name. thanks so much, i have been bashing my head against the wall for a few hrz now
                – Mickey Perlstein
                Sep 2 at 11:03













              up vote
              22
              down vote



              accepted







              up vote
              22
              down vote



              accepted






              use sep='s*,s*' so that you will take care of spaces in column-names:



              transactions = pd.read_csv('transactions.csv', sep='s*,s*',
              header=0, encoding='ascii', engine='python')


              alternatively you can make sure that you don't have unquoted spaces in your CSV file and use your command (unchanged)



              prove:



              print(transactions.columns.tolist())


              Output:



              ['product_id', 'customer_id', 'store_id', 'promotion_id', 'month_of_year', 'quarter', 'the_year', 'store_sales', 'store_cost', 'unit_sales', 'fact_count']





              share|improve this answer














              use sep='s*,s*' so that you will take care of spaces in column-names:



              transactions = pd.read_csv('transactions.csv', sep='s*,s*',
              header=0, encoding='ascii', engine='python')


              alternatively you can make sure that you don't have unquoted spaces in your CSV file and use your command (unchanged)



              prove:



              print(transactions.columns.tolist())


              Output:



              ['product_id', 'customer_id', 'store_id', 'promotion_id', 'month_of_year', 'quarter', 'the_year', 'store_sales', 'store_cost', 'unit_sales', 'fact_count']






              share|improve this answer














              share|improve this answer



              share|improve this answer








              edited Feb 7 '17 at 9:00

























              answered Mar 6 '16 at 19:34









              MaxU

              118k11106163




              118k11106163












              • You are amazing! Thanks so much!!
                – Harry M
                Mar 6 '16 at 19:45






              • 1




                the list showed me i had an extra space in the name. thanks so much, i have been bashing my head against the wall for a few hrz now
                – Mickey Perlstein
                Sep 2 at 11:03


















              • You are amazing! Thanks so much!!
                – Harry M
                Mar 6 '16 at 19:45






              • 1




                the list showed me i had an extra space in the name. thanks so much, i have been bashing my head against the wall for a few hrz now
                – Mickey Perlstein
                Sep 2 at 11:03
















              You are amazing! Thanks so much!!
              – Harry M
              Mar 6 '16 at 19:45




              You are amazing! Thanks so much!!
              – Harry M
              Mar 6 '16 at 19:45




              1




              1




              the list showed me i had an extra space in the name. thanks so much, i have been bashing my head against the wall for a few hrz now
              – Mickey Perlstein
              Sep 2 at 11:03




              the list showed me i had an extra space in the name. thanks so much, i have been bashing my head against the wall for a few hrz now
              – Mickey Perlstein
              Sep 2 at 11:03












              up vote
              0
              down vote













              I finally got the answer how to read a specific column:



              import pandas as pd  

              df=pd.read_csv('titanic.csv',sep='t')

              df['Sex']


              Because pandas separator uses t. I hope that works for you.






              share|improve this answer



























                up vote
                0
                down vote













                I finally got the answer how to read a specific column:



                import pandas as pd  

                df=pd.read_csv('titanic.csv',sep='t')

                df['Sex']


                Because pandas separator uses t. I hope that works for you.






                share|improve this answer

























                  up vote
                  0
                  down vote










                  up vote
                  0
                  down vote









                  I finally got the answer how to read a specific column:



                  import pandas as pd  

                  df=pd.read_csv('titanic.csv',sep='t')

                  df['Sex']


                  Because pandas separator uses t. I hope that works for you.






                  share|improve this answer














                  I finally got the answer how to read a specific column:



                  import pandas as pd  

                  df=pd.read_csv('titanic.csv',sep='t')

                  df['Sex']


                  Because pandas separator uses t. I hope that works for you.







                  share|improve this answer














                  share|improve this answer



                  share|improve this answer








                  edited Aug 17 at 5:22

























                  answered Aug 15 at 16:46









                  Bhaskar arya

                  45




                  45






















                      up vote
                      0
                      down vote













                      The key error generally comes if the key doesn't match any of the dataframe column name 'exactly':



                      You could also try:



                      import csv
                      import pandas as pd
                      import re
                      with open (filename, "r") as file:
                      df = pd.read_csv(file, delimiter = ",")
                      df.columns = ((df.columns.str).replace("^ ","")).str.replace(" $","")
                      print(df.columns)





                      share|improve this answer

























                        up vote
                        0
                        down vote













                        The key error generally comes if the key doesn't match any of the dataframe column name 'exactly':



                        You could also try:



                        import csv
                        import pandas as pd
                        import re
                        with open (filename, "r") as file:
                        df = pd.read_csv(file, delimiter = ",")
                        df.columns = ((df.columns.str).replace("^ ","")).str.replace(" $","")
                        print(df.columns)





                        share|improve this answer























                          up vote
                          0
                          down vote










                          up vote
                          0
                          down vote









                          The key error generally comes if the key doesn't match any of the dataframe column name 'exactly':



                          You could also try:



                          import csv
                          import pandas as pd
                          import re
                          with open (filename, "r") as file:
                          df = pd.read_csv(file, delimiter = ",")
                          df.columns = ((df.columns.str).replace("^ ","")).str.replace(" $","")
                          print(df.columns)





                          share|improve this answer












                          The key error generally comes if the key doesn't match any of the dataframe column name 'exactly':



                          You could also try:



                          import csv
                          import pandas as pd
                          import re
                          with open (filename, "r") as file:
                          df = pd.read_csv(file, delimiter = ",")
                          df.columns = ((df.columns.str).replace("^ ","")).str.replace(" $","")
                          print(df.columns)






                          share|improve this answer












                          share|improve this answer



                          share|improve this answer










                          answered Oct 20 at 22:53









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