On 21Sep2019 20:42, Markos <mar...@c2o.pro.br> wrote:
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)
[...]
And the data_array variable gets the fields in string format:
[['0,456' '0,120' '0,168']
[...]
Please see the documentation for the read_csv function here:
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html?highlight=read_csv#pandas.read_csv
In particular, because you have values formatted in the European style
with "," for the decimal marker (and possibly "." for the thousands
marker), you want to set the "decimal=" parameter of read-csv to ",".
This is better than trying to mangle the data yourself, better to just
correctly specify the dialect (i.e. set decimal= in your call).
Cheers,
Cameron Simpson <c...@cskk.id.au>
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