Apply function to pandas DataFrame that can return multiple rows

Question

I am trying to transform DataFrame, such that some of the rows will be replicated a given number of times. For example:

df = pd.DataFrame({\'class\': [\'A\',         


        

Answer 1

repeated_items = [list(row[1]*row[2]) for row in df.itertuples()]

will create a nested list:

[['A'], [], ['C', 'C']]

which you can then iterate over with list comprehensions to create a new data frame:

new_df = pd.DataFrame({"class":[j for i in repeated_items for j in i]})

Of course, you can do it in a single line as well if you want:

new_df = pd.DataFrame({"class":[j for i in [list(row[1]*row[2]) for row in df.itertuples()] for j in i]})