Remove rows with empty lists from pandas data frame

Question

I have a data frame with some columns with empty lists and others with lists of strings:

       donation_orgs                              donation_context
0            []                                           []
1   [the research of Dr. ...]   [In lieu of flowers , memorial donations ...]

I'm trying to return a data set without any of the rows where there are empty lists.

I've tried just checking for null values:

dfnotnull = df[df.donation_orgs != []]
dfnotnull

and

dfnotnull = df[df.notnull().any(axis=1)]
pd.options.display.max_rows=500
dfnotnull

And I've tried looping through and checking for values that exist, but I think the lists aren't returning Null or None like I thought they would:

dfnotnull = pd.DataFrame(columns=('donation_orgs', 'donation_context'))
for i in range(0,len(df)):
    if df['donation_orgs'].iloc(i):
        dfnotnull.loc[i] = df.iloc[i]

All three of the above methods simply return every row in the original data frame.=

Answer 1

To avoid converting to str and actually use the lists, you can do this:

df[df['donation_orgs'].map(lambda d: len(d)) > 0]

It maps the donation_orgs column to the length of the lists of each row and keeps only the ones that have at least one element, filtering out empty lists.

It returns

Out[1]: 
                            donation_context          donation_orgs
1  [In lieu of flowers , memorial donations]  [the research of Dr.]

as expected.