Pandas : Precision error when converting string to float












0















Using pandas to deal with timestamps, I am concatening two columns and then convert the result in floating. It appears that when I display the two columns I observe two different results. How can the conversion from string to float can affect the value? Thanks for your help.



Here is the content of the data.csv file



epoch_day,epoch_ns
1533081601,224423000


Here is my test program:



import pandas as pd
pd.options.display.float_format = '{:.10f}'.format
df_mid = pd.read_csv("data.csv")

df_mid['result_1']=df_mid['epoch_day'].astype(str).str.cat(df_mid['epoch_ns'].astype(str), sep =".")
df_mid['result_2'] = df_mid['epoch_day'].astype(str).str.cat(df_mid['epoch_ns'].astype(str), sep =".").astype(float)
print(df_mid)


The result is :



   epoch_day   epoch_ns              result_1              result_2
0 1533081601 224423000 1533081601.224423000 1533081601.2244229317


Thanks for your help



FX










share|improve this question



























    0















    Using pandas to deal with timestamps, I am concatening two columns and then convert the result in floating. It appears that when I display the two columns I observe two different results. How can the conversion from string to float can affect the value? Thanks for your help.



    Here is the content of the data.csv file



    epoch_day,epoch_ns
    1533081601,224423000


    Here is my test program:



    import pandas as pd
    pd.options.display.float_format = '{:.10f}'.format
    df_mid = pd.read_csv("data.csv")

    df_mid['result_1']=df_mid['epoch_day'].astype(str).str.cat(df_mid['epoch_ns'].astype(str), sep =".")
    df_mid['result_2'] = df_mid['epoch_day'].astype(str).str.cat(df_mid['epoch_ns'].astype(str), sep =".").astype(float)
    print(df_mid)


    The result is :



       epoch_day   epoch_ns              result_1              result_2
    0 1533081601 224423000 1533081601.224423000 1533081601.2244229317


    Thanks for your help



    FX










    share|improve this question

























      0












      0








      0








      Using pandas to deal with timestamps, I am concatening two columns and then convert the result in floating. It appears that when I display the two columns I observe two different results. How can the conversion from string to float can affect the value? Thanks for your help.



      Here is the content of the data.csv file



      epoch_day,epoch_ns
      1533081601,224423000


      Here is my test program:



      import pandas as pd
      pd.options.display.float_format = '{:.10f}'.format
      df_mid = pd.read_csv("data.csv")

      df_mid['result_1']=df_mid['epoch_day'].astype(str).str.cat(df_mid['epoch_ns'].astype(str), sep =".")
      df_mid['result_2'] = df_mid['epoch_day'].astype(str).str.cat(df_mid['epoch_ns'].astype(str), sep =".").astype(float)
      print(df_mid)


      The result is :



         epoch_day   epoch_ns              result_1              result_2
      0 1533081601 224423000 1533081601.224423000 1533081601.2244229317


      Thanks for your help



      FX










      share|improve this question














      Using pandas to deal with timestamps, I am concatening two columns and then convert the result in floating. It appears that when I display the two columns I observe two different results. How can the conversion from string to float can affect the value? Thanks for your help.



      Here is the content of the data.csv file



      epoch_day,epoch_ns
      1533081601,224423000


      Here is my test program:



      import pandas as pd
      pd.options.display.float_format = '{:.10f}'.format
      df_mid = pd.read_csv("data.csv")

      df_mid['result_1']=df_mid['epoch_day'].astype(str).str.cat(df_mid['epoch_ns'].astype(str), sep =".")
      df_mid['result_2'] = df_mid['epoch_day'].astype(str).str.cat(df_mid['epoch_ns'].astype(str), sep =".").astype(float)
      print(df_mid)


      The result is :



         epoch_day   epoch_ns              result_1              result_2
      0 1533081601 224423000 1533081601.224423000 1533081601.2244229317


      Thanks for your help



      FX







      string pandas precision floating-accuracy






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      asked Nov 13 '18 at 5:16









      fxtokyofxtokyo

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          Floating-point numbers are represented in computer hardware as base 2 (binary) fractions. Most decimal fractions cannot be represented exactly as binary fractions.



          When you convert your string, python creates a float which is the closest binary fraction for your input.



          You can actually see to which decimal number this corresponds by running the following:



          from decimal import Decimal
          Decimal(1533081601.224423000)
          OUTPUT: Decimal('1533081601.224422931671142578125')


          You can see the Python documentation for more info https://docs.python.org/2/tutorial/floatingpoint.html






          share|improve this answer
























          • Thanks a lot for your explanation @guilherm-costa.

            – fxtokyo
            Nov 28 '18 at 2:02











          • Thanks for the feedback. Could you please accept the answer?

            – Guilherme Costa
            Nov 28 '18 at 12:31











          Your Answer






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          Floating-point numbers are represented in computer hardware as base 2 (binary) fractions. Most decimal fractions cannot be represented exactly as binary fractions.



          When you convert your string, python creates a float which is the closest binary fraction for your input.



          You can actually see to which decimal number this corresponds by running the following:



          from decimal import Decimal
          Decimal(1533081601.224423000)
          OUTPUT: Decimal('1533081601.224422931671142578125')


          You can see the Python documentation for more info https://docs.python.org/2/tutorial/floatingpoint.html






          share|improve this answer
























          • Thanks a lot for your explanation @guilherm-costa.

            – fxtokyo
            Nov 28 '18 at 2:02











          • Thanks for the feedback. Could you please accept the answer?

            – Guilherme Costa
            Nov 28 '18 at 12:31
















          0














          Floating-point numbers are represented in computer hardware as base 2 (binary) fractions. Most decimal fractions cannot be represented exactly as binary fractions.



          When you convert your string, python creates a float which is the closest binary fraction for your input.



          You can actually see to which decimal number this corresponds by running the following:



          from decimal import Decimal
          Decimal(1533081601.224423000)
          OUTPUT: Decimal('1533081601.224422931671142578125')


          You can see the Python documentation for more info https://docs.python.org/2/tutorial/floatingpoint.html






          share|improve this answer
























          • Thanks a lot for your explanation @guilherm-costa.

            – fxtokyo
            Nov 28 '18 at 2:02











          • Thanks for the feedback. Could you please accept the answer?

            – Guilherme Costa
            Nov 28 '18 at 12:31














          0












          0








          0







          Floating-point numbers are represented in computer hardware as base 2 (binary) fractions. Most decimal fractions cannot be represented exactly as binary fractions.



          When you convert your string, python creates a float which is the closest binary fraction for your input.



          You can actually see to which decimal number this corresponds by running the following:



          from decimal import Decimal
          Decimal(1533081601.224423000)
          OUTPUT: Decimal('1533081601.224422931671142578125')


          You can see the Python documentation for more info https://docs.python.org/2/tutorial/floatingpoint.html






          share|improve this answer













          Floating-point numbers are represented in computer hardware as base 2 (binary) fractions. Most decimal fractions cannot be represented exactly as binary fractions.



          When you convert your string, python creates a float which is the closest binary fraction for your input.



          You can actually see to which decimal number this corresponds by running the following:



          from decimal import Decimal
          Decimal(1533081601.224423000)
          OUTPUT: Decimal('1533081601.224422931671142578125')


          You can see the Python documentation for more info https://docs.python.org/2/tutorial/floatingpoint.html







          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered Nov 20 '18 at 17:40









          Guilherme CostaGuilherme Costa

          515




          515













          • Thanks a lot for your explanation @guilherm-costa.

            – fxtokyo
            Nov 28 '18 at 2:02











          • Thanks for the feedback. Could you please accept the answer?

            – Guilherme Costa
            Nov 28 '18 at 12:31



















          • Thanks a lot for your explanation @guilherm-costa.

            – fxtokyo
            Nov 28 '18 at 2:02











          • Thanks for the feedback. Could you please accept the answer?

            – Guilherme Costa
            Nov 28 '18 at 12:31

















          Thanks a lot for your explanation @guilherm-costa.

          – fxtokyo
          Nov 28 '18 at 2:02





          Thanks a lot for your explanation @guilherm-costa.

          – fxtokyo
          Nov 28 '18 at 2:02













          Thanks for the feedback. Could you please accept the answer?

          – Guilherme Costa
          Nov 28 '18 at 12:31





          Thanks for the feedback. Could you please accept the answer?

          – Guilherme Costa
          Nov 28 '18 at 12:31


















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