Convert number strings with commas in pandas DataFrame to float

Solution 1:

If you're reading in from csv then you can use the thousands arg:

df.read_csv('foo.tsv', sep='\t', thousands=',')

This method is likely to be more efficient than performing the operation as a separate step.

You need to set the locale first:

In [ 9]: import locale

In [10]: from locale import atof

In [11]: locale.setlocale(locale.LC_NUMERIC, '')
Out[11]: 'en_GB.UTF-8'

In [12]: df.applymap(atof)
Out[12]:
      0        1
0  1200  4200.00
1  7000    -0.03
2     5     0.00

Solution 2:

You may use the pandas.Series.str.replace method:

df.iloc[:,:].str.replace(',', '').astype(float)

This method can remove or replace the comma in the string.

Solution 3:

You can convert one column at a time like this :

df['colname'] = df['colname'].str.replace(',', '').astype(float)