Is there a way to cast a column to float that handle no numeric values?

[argenisleon]

Hi, is there a way to convert a column with string values to float? Something like this in pandas:

import pandas as pd
s = pd.Series(['apple', '1.0', '2', -3, None]) 
pd.to_numeric(s, errors='coerce')

0    NaN
1    1.0
2    2.0
3   -3.0
4    NaN
dtype: float64

I am trying this approach using the fastnumbers library:

from fastnumbers import fast_float
df=dt.Frame({"col1":['apple', '1.0', '2-1', -3]})
df["cast"]=np.vectorize(fast_float)(df["col1"],default=0).flatten()
print(df)

   | col1      cast
   | str32  float64
-- + -----  -------
 0 | apple       NA
 1 | 1.0          1
 2 | 2-1         NA
 3 | -3          -3
[4 rows x 2 columns]

Is there a function in datatable that can handle this?

[oleksiyskononenko]

What about just using casting?

>>> from datatable import dt
>>> DT = dt.Frame(['apple', '1.0', '2', -3, None]/dt.str32)
>>> DT
   | C0   
   | str32
-- + -----
 0 | apple
 1 | 1.0  
 2 | 2    
 3 | -3   
 4 | NA   
[5 rows x 1 column]
>>> DT[0] = dt.float32
>>> DT
   |      C0
   | float32
-- + -------
 0 |      NA
 1 |       1
 2 |       2
 3 |      -3
 4 |      NA
[5 rows x 1 column]

In the general case, one can use .as_type().