Trying to remove commas and dollars signs with Pandas in Python

You have to access the str attribute per http://pandas.pydata.org/pandas-docs/stable/text.html

df1['Avg_Annual'] = df1['Avg_Annual'].str.replace(',', '')
df1['Avg_Annual'] = df1['Avg_Annual'].str.replace('$', '')
df1['Avg_Annual'] = df1['Avg_Annual'].astype(int)

alternately;

df1['Avg_Annual'] = df1['Avg_Annual'].str.replace(',', '').str.replace('$', '').astype(int)

if you want to prioritize time spent typing over readability.

Shamelessly stolen from this answer... but, that answer is only about changing one character and doesn't complete the coolness: since it takes a dictionary, you can replace any number of characters at once, as well as in any number of columns.

# if you want to operate on multiple columns, put them in a list like so:
cols = ['col1', 'col2', ..., 'colN']

# pass them to df.replace(), specifying each char and it's replacement:
df[cols] = df[cols].replace({'\$': '', ',': ''}, regex=True)

@shivsn caught that you need to use regex=True; you already knew about replace (but also didn't show trying to use it on multiple columns or both the dollar sign and comma simultaneously).

This answer is simply spelling out the details I found from others in one place for those like me (e.g. noobs to python an pandas). Hope it's helpful.