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

[Markos]

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)

and the variable "data" has the structure:

Spectrum,  Py,  Ace, Anth,
0  1         0,456  0,120  0,168
1  2         0,456 0,040 0,280
2  3         0,152 0,200 0,280

I copy the numeric fields to an array with the command:

data_array = data.values [:, 1:]

And the data_array variable gets the fields in string format:

[['0,456' '0,120' '0,168']
['0,456' '0,040' '0,280']
['0,152' '0,200' '0,280']]

The only way I found to change comma "," to dot "." was using the method 
replace():

for i, line in enumerate (data_array):
data_array [i] = ([float (element.replace (',', '.')) for element in 
data_array [i]])

But I'm wondering if there is another, more "efficient" way to make this 
change without having to "iterate" all elements of the array with a loop 
"for".

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?

Thanks you,

Markos