pandas: to_numeric for multiple columns

Question

I\'m working with the following df:

c.sort_values(\'2005\', ascending=False).head(3)
      GeoName ComponentName     IndustryId IndustryClassification Descri         


        

Answer 1

If you are looking for a range of columns, you can try this:

df.iloc[7:] = df.iloc[7:].astype(float)

The examples above will convert type to be float, for all the columns begin with the 7th to the end. You of course can use different type or different range.

I think this is useful when you have a big range of columns to convert and a lot of rows. It doesn't make you go over each row by yourself - I believe numpy do it more efficiently.

This is useful only if you know that all the required columns contain numbers only - it will not change "bad values" (like string) to be NaN for you.