Filtering Pandas Dataframe using OR statement

Question

I have a pandas dataframe and I want to filter the whole df based on the value of two columns in the data frame. I want to get back all rows and columns where IBRD or IMF != 0.

alldata_balance = alldata[(alldata[IBRD] !=0) or (alldata[IMF] !=0)] 

but this gives me a ValueError

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

So I know I am not using the or statement correctly, is there a way to do this?

Answer 1

From the docs:

Another common operation is the use of boolean vectors to filter the data. The operators are: | for or, & for and, and ~ for not. These must be grouped by using parentheses.

http://pandas.pydata.org/pandas-docs/version/0.15.2/indexing.html#boolean-indexing

Try:

alldata_balance = alldata[(alldata[IBRD] !=0) | (alldata[IMF] !=0)]