Create a Total row in Pandas Dataframe

Question

So I am trying to create a new row in my dataframe that adds up the sums for only column A B and C and have the means for column D and E. I have tried doing something like:

df.loc['totals'] = df['daily budget', 'weekly budget', 'monthly budget'].sum() + df['average spent monthly','average spent yearly'].mean()

It didnt work. Should I try to define each value by doing something like

sum1 = df['daily budget'].sum()
sum2 = df['weekly budget'].sum()
sum3 = ....
mean1 =df['average monthly'].mean()
mean2 = ....

And fill in the cell?

You should give a minimal-reproducible-example. Without data, it is hard to understand what do you want. — ndclt
– ndclt, Commented Sep 23, 2020 at 19:55

Mike · Accepted Answer · 2020-09-23 19:54:47Z

1

If you want to go with your approach then this should work.

sum1 = df['daily budget'] + df['weekly budget'] + df['monthly budget']

mean1 = (df['average spent monthly'] + df['average spent yearly'])/2

df['total'] = sum1 + mean1

answered Sep 23, 2020 at 19:54

Mike

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4 Comments

DayLy Over a year ago

I get a nan result for all columns using this method.

Mike Over a year ago

check your data types with df.dtypes to verify that those columns are numeric data types

DayLy Over a year ago

They are all float64 except for one which is an object because its a bunch of names. On the bottom of the list it says dtype:Object though. I though i resolved this problem when I used pd.to_numeric on columns containing numbers.

Mike Over a year ago

Is it possible to add a snippet of the dataframe so we can see?

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