Convert column to a float from str dropping non-numeric strings

Let us say we have the following dataframe

df[‘Amount $’]

And we want to convert all numbers to float and drop the non-numeric rows. isnumeric() will not work since this data is all str dtype. The only option is to write a small function which tries to convert a string to a float. If it fails it returns FALSE. If this function is mapped to the entire column using a lambda function then it will return a boolean list(series) where TRUE means float and FALSE means non-float. When this is used as a boolean mask on the dataframe, it will filter out the non-numeric rows.

def tryfloat(self, f):
       try:
           float(f)
           return True

       except ValueError:
           return False

df[ df['Amount $'].apply(lambda x: tryfloat(x)) ]

Result is this table