Most efficient way to replace ", " with "." in a array and/or dataframe

[Markos]

Em 22-09-2019 13:10, Piet van Oostrum escreveu:
> Markos <markos at c2o.pro.br> writes:
>
>> Hi,
>>
>> I have a table.csv file with the following structure:
>>
>> , Polyarene conc ,, mg L-1 ,,,,,,,
>> Spectrum, Py, Ace, Anth,
>> 1, "0,456", "0,120", "0,168"
>> 2, "0,456", "0,040", "0,280"
>> 3, "0,152", "0,200", "0,280"
>>
>> I open as dataframe with the command:
>>
>> data = pd.read_csv ('table.csv', sep = ',', skiprows = 1)
>>
> [snip]
>
>> Also I'm also wondering if there would be any benefit of making this
>> modification in dataframe before extracting the numeric fields to the
>> array.
>>
>> Please, any comments or tip?
> data = pd.read_csv ('table.csv', sep = ',', skiprows = 1, decimal=b',', skipinitialspace=True)
>
Thank you for the tip.

I didn't realize that I could avoid formatting problems in the dataframe 
or array simply by using the read_csv command with the correct 
parameters (sep and decimal).

I searched for information about the meaning of the letter "b" in the 
parameter decimal=b','  but didn't find.

I found that it also works without the letter b.

Best Regards,
Markos