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

[Richard Damon]

On 9/22/19 7:05 PM, Markos wrote:
>
> 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

The b indicates that the string is a 'bytes' string vs a text string.
This isn't so important to differentiate for ASCII characters, but can
make a difference if you have extended characters and the file might not
be in Unicode.

-- 
Richard Damon