CSV cannot be interpreted by numeric values
By itself, the csv file should be correct. Both you and Pandas know what delimiter and floating point format are. But Excel might not agree with you, depending on your locale. A simple way to make sure is to write a tiny Excel sheet containing on first row one text value and one floating point one. You then export the file as csv and control what delimiter and floating point formats are.
AFAIK, it is much more easy to change your Python code to follow what your Excel expects that trying to explain Excel that the format of CSV files can vary...

I know that you can change the delimiter and floating point format in the current locale in a Windows system. Simply it is a global setting...
(This is a mix between code and 'user' issue, but since i suspect the issue is code, i opted to post in StackOverflow instead of SuperUser Exchange).
I generated a .csv file with pandas.DataFrame.to_csv() method. This file consists in 2 columns: one is a label (text) and another is a numeric value called accuracy (float). The delimiter used to separate columns is comma (,) and all float values are stored with dot ponctuation like this: 0.9438245862
Even saving this column as float, Excel and Google Sheets infer its type as text. And when i try to format this column as number, they ignore "0." and return a very high value instead of decimals like:
(text) 0.9438245862       =>   (number) 9438245862,00
I double-checked my .csv file reimporting it again with pandas.read_csv() and printing dataframe.dtypes and the column is imported as float succesfully.
I'd thank for some guidance on what am i missing.
Thanks,