How to add a 'total' dataframe to a dictionary of dataframes in python?

Question

I am a beginner, so feedback is welcome.

I have a dictionary of data frames, with each value of the dictionary a data frame containing data from a specific country. I'd like to create a total data frame, that shows the sum of each of the data frames in the dictionary.

d['total'] = d['Germany'].add(d['Belgium'], fill_value=0)
d['total'] = d['total'].add(d['France'], fill_value=0)

This works perfectly fine for two dataframes, but I have n number of dataframes in my dictionary, so I thought it was stupid to repeat this for each country. Is there a better way to do this?

mozway · Answer 1 · 2022-12-24T09:03:34.993

2

To sum all existing DataFrames in the dictionary, you can use:

d['total'] = sum(d.values())

Or to limit to a list of keys:

l = ['Germany', 'Belgium', 'France']

d['total'] = sum(d[c] for c in l)

using only numeric columns:

d['total'] = sum(d[c].select_dtypes('number') for c in l)

edited Dec 24 '22 at 09:03

answered Dec 24 '22 at 07:18

mozway

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Yes this is correct. Thank you!! As a note for others, this method doesn't work if there are strings in your dateframe. I did, and this broke until I removed the columns with strings. – stevearama111 Dec 24 '22 at 07:52
1

@stevearama111 in this case use `select_dtypes('number')` to filter the numeric columns, see update – mozway Dec 24 '22 at 09:00
you're a champion. thanks! – stevearama111 Dec 25 '22 at 11:03

How to add a 'total' dataframe to a dictionary of dataframes in python?

1 Answers1

using only numeric columns: