I'd like to add subtotal rows for index #1 (ie. Fruits and Animal) and subtotal columns for columns (ie. 2015 and 2016).
For the subtotal columns, I could do something like this, but it seems inefficient to run this type of code for each year (2015 & 2016). Is there a better way? I don't think 'margins' will work because there are multiple subtotals.
df[('2015','2015_Total')] = df[('2015','1st')]+df[('2015','2nd')]
For the subtotal rows (e.g., fruits total and animal total), I'm not sure where to begin.
It is very complicated, because you need create Multiindex in columns and index.
Create subtotals is easy - use groupby with sum. Then create Multiindex and last concat new columns to original DataFrame. Last you have to sort_index (I add Total_ before value for correct sorting):
print df 2015_____ 2016_______ 1st 2nd 1st 2nd Fruits Apple 10 9 11 10 Banana 20 22 21 20 Animal Lion 5 3 2 1 Tiger 2 3 5 0 df1 = df.groupby(level=0, axis=1).sum() print df1 2015_____ 2016_______ Fruits Apple 19 21 Banana 42 41 Animal Lion 8 3 Tiger 5 5 print df.columns.get_level_values(0).to_series().drop_duplicates().tolist() ['2015_____', '2016_______'] #change index to multiindex new_columns = zip(df.columns.get_level_values(0).to_series().drop_duplicates().tolist(), "Total_" + df1.columns.str[:4]) print new_columns [('2015_____', 'Total_2015'), ('2016_______', 'Total_2016')] df1.columns = pd.MultiIndex.from_tuples(new_columns) print df1 2015_____ 2016_______ Total_2015 Total_2016 Fruits Apple 19 21 Banana 42 41 Animal Lion 8 3 Tiger 5 5 df = pd.concat([df,df1], axis=1)
df2 = df.groupby(level=0, sort=False).sum() print df2 2015_____ 2016_______ 2015_____ 2016_______ 1st 2nd 1st 2nd Total_2015 Total_2016 Animal 7 6 7 1 13 8 Fruits 30 31 32 30 61 62 print df.index.levels[0][df.columns.labels[0]].to_series().drop_duplicates().tolist() ['Animal', 'Fruits'] #change index to multiindex new_idx=zip(df.index.levels[0][df.columns.labels[0]].to_series().drop_duplicates().tolist(), "Total_" + df2.index ) print new_idx [('Animal', 'Total_Animal'), ('Fruits', 'Total_Fruits')] df2.index = pd.MultiIndex.from_tuples(new_idx) print df2 2015_____ 2016_______ 2015_____ 2016_______ 1st 2nd 1st 2nd Total_2015 Total_2016 Animal Total_Animal 7 6 7 1 13 8 Fruits Total_Fruits 30 31 32 30 61 62 df = pd.concat([df,df2]) df = df.sort_index(axis=1).sort_index() print df 2015_____ 2016_______ 1st 2nd Total_2015 1st 2nd Total_2016 Animal Lion 5 3 8 2 1 3 Tiger 2 3 5 5 0 5 Total_Animal 7 6 13 7 1 8 Fruits Apple 10 9 19 11 10 21 Banana 20 22 42 21 20 41 Total_Fruits 30 31 61 32 30 62
