Converting strings to floats in a DataFrame

Question

How to covert a DataFrame column containing strings and NaN values to floats. And there is another column whose values are strings and floats; how to convert th

Answer 1

NOTE: pd.convert_objects has now been deprecated. You should use pd.Series.astype(float) or pd.to_numeric as described in other answers.

This is available in 0.11. Forces conversion (or set's to nan) This will work even when astype will fail; its also series by series so it won't convert say a complete string column

In [10]: df = DataFrame(dict(A = Series(['1.0','1']), B = Series(['1.0','foo'])))

In [11]: df
Out[11]: 
     A    B
0  1.0  1.0
1    1  foo

In [12]: df.dtypes
Out[12]: 
A    object
B    object
dtype: object

In [13]: df.convert_objects(convert_numeric=True)
Out[13]: 
   A   B
0  1   1
1  1 NaN

In [14]: df.convert_objects(convert_numeric=True).dtypes
Out[14]: 
A    float64
B    float64
dtype: object