CSV cannot be interpreted by numeric values
A short example of data would be most useful here. Otherwise we have no idea what you're actually writing/reading. But I'll hazard a guess based on the information you've provided.
The pandas dataframe will have column names. These column names will be text. Unless you tell Excel/Sheets to use the first row as the column name, it will have to treat the column as text. If this isn't the case, could you perhaps save the head of the dataframe to a csv, check it in a text editor, and see how Excel/Sheets imports it. Then include those five rows and two columns in your follow up.
(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,