pandas - How to convert numbers represented as characters for short into numeric in Python

Question

I have a column in my data frame which has values like '3.456B' which actually stands for 3.456 Billion (and similar notation for Million). How to convert this string form to correct numeric representation?

This shows the data frame:

import pandas as pd
data_csv = pd.read_csv('https://biz.yahoo.com/p/csv/422conameu.csv')
data_csv

This is a sample value:

data_csv['Market Cap'][0]
type(data_csv['Market Cap'][0])

I tried this:

data_csv.loc[data_csv['Market Cap'].str.contains('B'), 'Market Cap'] = data_csv['Market Cap'].str.replace('B', '').astype(float).fillna(0.0)
data_csv

But unfortunately there are also values with 'M' at the end which denotes Millions. It returns error as follows:

ValueError: invalid literal for float(): 6.46M

How can I replace both B and M with appropriate values in this column? Is there a better way to do it?

Answer 1

I'd use a dictionary to replace the strings then evaluate as float.

mapping = dict(K='E3', M='E6', B='E9')

df['Market Cap'] = pd.to_numeric(df['Market Cap'].replace(mapping, regex=True))