Converting Float to Int on certain columns in a data frame

Question

I am trying to convert columns 0 to 4 and 6 to ints from there current float types.

I tried:

df[0:4,6].astype(int)

but of course this does not work...

Answer 1

I was getting an error as some of my column values were NaN which obviously can not be converted to int. So a better approach would be to handle NaN before converting the datatype and avoid ValueError: Cannot convert non-finite values (NA or inf) to integer.

df['col_name'] = df['col_name'].fillna(0).astype(int)

This fills NaN with 0 and then converts to the desired datatype which is int in this case.

Answer 2

consider df

df = pd.DataFrame(np.random.rand(10, 10) * 10)

use np.r_ to get slc

slc = np.r_[0:4, 6]
df[slc] = df[slc].astype(int)
df

or pass a dictionary of types with keys as column names

df.astype({c: int for c in slc})