How to convert object to float in Pandas?

I read a csv file into a pandas dataframe and got all column types as objects. I need to convert the second and third columns to float.

I tried using

df["Quantidade"] = pd.to_numeric(df.Quantidade, errors='coerce')

but got NaN.

Here’s my dataframe. Should I need to use some regex in the third column to get rid of the “R$ “?

Answer

Try this:

# sample dataframe
d = {'Quantidade':['0,20939', '0,0082525', '0,009852', '0,012920', '0,0252'],
     'price':['R$ 165.000,00', 'R$ 100.000,00', 'R$ 61.500,00', 'R$ 65.900,00', 'R$ 49.375,12']}
df = pd.DataFrame(data=d)

# Second column
df["Quantidade"] = df["Quantidade"].str.replace(',', '.').astype(float)

#Third column
df['price'] = df.price.str.replace(r'w+$s+', '').str.replace('.', '')
                   .str.replace(',', '.').astype(float)

Output:

Quantidade  price
0   0.209390    165000.00
1   0.008252    100000.00
2   0.009852    61500.00
3   0.012920    65900.00
4   0.025200    49375.12