Shift down one row then rename the column











up vote
2
down vote

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My data is looking like this:



pd.read_csv('/Users/admin/desktop/007538839.csv').head()

105586.18
0 105582.910
1 105585.230
2 105576.445
3 105580.016
4 105580.266


I want to move that 105568.18 to the 0 index because now it is the column name. And after that I want to name this column 'flux'. I've tried



pd.read_csv('/Users/admin/desktop/007538839.csv', sep='t', names = ["flux"])


but it did not work, probably because the dataframe is not in the right format.
How can I achieve that?










share|improve this question






















  • because the dataframe is not in the right format. - Can you explain more?
    – jezrael
    Nov 12 at 6:10















up vote
2
down vote

favorite












My data is looking like this:



pd.read_csv('/Users/admin/desktop/007538839.csv').head()

105586.18
0 105582.910
1 105585.230
2 105576.445
3 105580.016
4 105580.266


I want to move that 105568.18 to the 0 index because now it is the column name. And after that I want to name this column 'flux'. I've tried



pd.read_csv('/Users/admin/desktop/007538839.csv', sep='t', names = ["flux"])


but it did not work, probably because the dataframe is not in the right format.
How can I achieve that?










share|improve this question






















  • because the dataframe is not in the right format. - Can you explain more?
    – jezrael
    Nov 12 at 6:10













up vote
2
down vote

favorite









up vote
2
down vote

favorite











My data is looking like this:



pd.read_csv('/Users/admin/desktop/007538839.csv').head()

105586.18
0 105582.910
1 105585.230
2 105576.445
3 105580.016
4 105580.266


I want to move that 105568.18 to the 0 index because now it is the column name. And after that I want to name this column 'flux'. I've tried



pd.read_csv('/Users/admin/desktop/007538839.csv', sep='t', names = ["flux"])


but it did not work, probably because the dataframe is not in the right format.
How can I achieve that?










share|improve this question













My data is looking like this:



pd.read_csv('/Users/admin/desktop/007538839.csv').head()

105586.18
0 105582.910
1 105585.230
2 105576.445
3 105580.016
4 105580.266


I want to move that 105568.18 to the 0 index because now it is the column name. And after that I want to name this column 'flux'. I've tried



pd.read_csv('/Users/admin/desktop/007538839.csv', sep='t', names = ["flux"])


but it did not work, probably because the dataframe is not in the right format.
How can I achieve that?







python pandas






share|improve this question













share|improve this question











share|improve this question




share|improve this question










asked Nov 12 at 5:54









Phil Nguyen

323




323












  • because the dataframe is not in the right format. - Can you explain more?
    – jezrael
    Nov 12 at 6:10


















  • because the dataframe is not in the right format. - Can you explain more?
    – jezrael
    Nov 12 at 6:10
















because the dataframe is not in the right format. - Can you explain more?
– jezrael
Nov 12 at 6:10




because the dataframe is not in the right format. - Can you explain more?
– jezrael
Nov 12 at 6:10












2 Answers
2






active

oldest

votes

















up vote
1
down vote



accepted










For me your code working very nice:



import pandas as pd

temp=u"""105586.18
105582.910
105585.230
105576.445
105580.016
105580.266"""
#after testing replace 'pd.compat.StringIO(temp)' to '/Users/admin/desktop/007538839.csv'
df = pd.read_csv(pd.compat.StringIO(temp), sep='t', names = ["flux"])

print (df)
flux
0 105586.180
1 105582.910
2 105585.230
3 105576.445
4 105580.016
5 105580.266


For overwrite original file with same data with new header flux:



df.to_csv('/Users/admin/desktop/007538839.csv', index=False)





share|improve this answer























  • Thanks a lot! I thought it didn't work because I am actually trying to write this df back to the original csv file. So when I used read_csv() to read the file again I found nothing changed. My bad! Can you show me how to overwrite the original file with this new df?
    – Phil Nguyen
    Nov 12 at 6:24










  • @PhilNguyen - edited answer. Please check it.
    – jezrael
    Nov 12 at 6:32






  • 1




    It worked! Thanks a lot!
    – Phil Nguyen
    Nov 12 at 6:46


















up vote
0
down vote













Try this:



df=pd.read_csv('/Users/admin/desktop/007538839.csv',header=None)
df.columns=['flux']


header=None is the friend of yours.






share|improve this answer





















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    2 Answers
    2






    active

    oldest

    votes








    2 Answers
    2






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes








    up vote
    1
    down vote



    accepted










    For me your code working very nice:



    import pandas as pd

    temp=u"""105586.18
    105582.910
    105585.230
    105576.445
    105580.016
    105580.266"""
    #after testing replace 'pd.compat.StringIO(temp)' to '/Users/admin/desktop/007538839.csv'
    df = pd.read_csv(pd.compat.StringIO(temp), sep='t', names = ["flux"])

    print (df)
    flux
    0 105586.180
    1 105582.910
    2 105585.230
    3 105576.445
    4 105580.016
    5 105580.266


    For overwrite original file with same data with new header flux:



    df.to_csv('/Users/admin/desktop/007538839.csv', index=False)





    share|improve this answer























    • Thanks a lot! I thought it didn't work because I am actually trying to write this df back to the original csv file. So when I used read_csv() to read the file again I found nothing changed. My bad! Can you show me how to overwrite the original file with this new df?
      – Phil Nguyen
      Nov 12 at 6:24










    • @PhilNguyen - edited answer. Please check it.
      – jezrael
      Nov 12 at 6:32






    • 1




      It worked! Thanks a lot!
      – Phil Nguyen
      Nov 12 at 6:46















    up vote
    1
    down vote



    accepted










    For me your code working very nice:



    import pandas as pd

    temp=u"""105586.18
    105582.910
    105585.230
    105576.445
    105580.016
    105580.266"""
    #after testing replace 'pd.compat.StringIO(temp)' to '/Users/admin/desktop/007538839.csv'
    df = pd.read_csv(pd.compat.StringIO(temp), sep='t', names = ["flux"])

    print (df)
    flux
    0 105586.180
    1 105582.910
    2 105585.230
    3 105576.445
    4 105580.016
    5 105580.266


    For overwrite original file with same data with new header flux:



    df.to_csv('/Users/admin/desktop/007538839.csv', index=False)





    share|improve this answer























    • Thanks a lot! I thought it didn't work because I am actually trying to write this df back to the original csv file. So when I used read_csv() to read the file again I found nothing changed. My bad! Can you show me how to overwrite the original file with this new df?
      – Phil Nguyen
      Nov 12 at 6:24










    • @PhilNguyen - edited answer. Please check it.
      – jezrael
      Nov 12 at 6:32






    • 1




      It worked! Thanks a lot!
      – Phil Nguyen
      Nov 12 at 6:46













    up vote
    1
    down vote



    accepted







    up vote
    1
    down vote



    accepted






    For me your code working very nice:



    import pandas as pd

    temp=u"""105586.18
    105582.910
    105585.230
    105576.445
    105580.016
    105580.266"""
    #after testing replace 'pd.compat.StringIO(temp)' to '/Users/admin/desktop/007538839.csv'
    df = pd.read_csv(pd.compat.StringIO(temp), sep='t', names = ["flux"])

    print (df)
    flux
    0 105586.180
    1 105582.910
    2 105585.230
    3 105576.445
    4 105580.016
    5 105580.266


    For overwrite original file with same data with new header flux:



    df.to_csv('/Users/admin/desktop/007538839.csv', index=False)





    share|improve this answer














    For me your code working very nice:



    import pandas as pd

    temp=u"""105586.18
    105582.910
    105585.230
    105576.445
    105580.016
    105580.266"""
    #after testing replace 'pd.compat.StringIO(temp)' to '/Users/admin/desktop/007538839.csv'
    df = pd.read_csv(pd.compat.StringIO(temp), sep='t', names = ["flux"])

    print (df)
    flux
    0 105586.180
    1 105582.910
    2 105585.230
    3 105576.445
    4 105580.016
    5 105580.266


    For overwrite original file with same data with new header flux:



    df.to_csv('/Users/admin/desktop/007538839.csv', index=False)






    share|improve this answer














    share|improve this answer



    share|improve this answer








    edited Nov 12 at 6:30

























    answered Nov 12 at 6:09









    jezrael

    316k22256333




    316k22256333












    • Thanks a lot! I thought it didn't work because I am actually trying to write this df back to the original csv file. So when I used read_csv() to read the file again I found nothing changed. My bad! Can you show me how to overwrite the original file with this new df?
      – Phil Nguyen
      Nov 12 at 6:24










    • @PhilNguyen - edited answer. Please check it.
      – jezrael
      Nov 12 at 6:32






    • 1




      It worked! Thanks a lot!
      – Phil Nguyen
      Nov 12 at 6:46


















    • Thanks a lot! I thought it didn't work because I am actually trying to write this df back to the original csv file. So when I used read_csv() to read the file again I found nothing changed. My bad! Can you show me how to overwrite the original file with this new df?
      – Phil Nguyen
      Nov 12 at 6:24










    • @PhilNguyen - edited answer. Please check it.
      – jezrael
      Nov 12 at 6:32






    • 1




      It worked! Thanks a lot!
      – Phil Nguyen
      Nov 12 at 6:46
















    Thanks a lot! I thought it didn't work because I am actually trying to write this df back to the original csv file. So when I used read_csv() to read the file again I found nothing changed. My bad! Can you show me how to overwrite the original file with this new df?
    – Phil Nguyen
    Nov 12 at 6:24




    Thanks a lot! I thought it didn't work because I am actually trying to write this df back to the original csv file. So when I used read_csv() to read the file again I found nothing changed. My bad! Can you show me how to overwrite the original file with this new df?
    – Phil Nguyen
    Nov 12 at 6:24












    @PhilNguyen - edited answer. Please check it.
    – jezrael
    Nov 12 at 6:32




    @PhilNguyen - edited answer. Please check it.
    – jezrael
    Nov 12 at 6:32




    1




    1




    It worked! Thanks a lot!
    – Phil Nguyen
    Nov 12 at 6:46




    It worked! Thanks a lot!
    – Phil Nguyen
    Nov 12 at 6:46












    up vote
    0
    down vote













    Try this:



    df=pd.read_csv('/Users/admin/desktop/007538839.csv',header=None)
    df.columns=['flux']


    header=None is the friend of yours.






    share|improve this answer

























      up vote
      0
      down vote













      Try this:



      df=pd.read_csv('/Users/admin/desktop/007538839.csv',header=None)
      df.columns=['flux']


      header=None is the friend of yours.






      share|improve this answer























        up vote
        0
        down vote










        up vote
        0
        down vote









        Try this:



        df=pd.read_csv('/Users/admin/desktop/007538839.csv',header=None)
        df.columns=['flux']


        header=None is the friend of yours.






        share|improve this answer












        Try this:



        df=pd.read_csv('/Users/admin/desktop/007538839.csv',header=None)
        df.columns=['flux']


        header=None is the friend of yours.







        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Nov 12 at 5:57









        U9-Forward

        11.5k2834




        11.5k2834






























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