Nagesh Joshi Nagesh Joshi - 1 year ago 84
Python Question

Groupby() function of pandas working incorrectly

When I call my data frame


This is how it looks:

Pclass Fare Survived Fare Kind Counts
0 3 7.2500 0 Lowest 1
2 3 7.9250 1 Low 1
4 3 8.0500 0 Low 1
5 3 8.4583 0 Medium 1
7 3 21.0750 0 high 1

I wanted to group my data according to Survived and Fare Kind, I used the following code

third_class_grouped =third_class.groupby(["Survived","Fare Kind"], as_index=False)["Counts"].sum()

This is the output I'm getting for


Survived Fare Kind Counts
Survived Fare Kind
0 Lowest NaN NaN NaN
Low NaN NaN NaN
Medium NaN NaN NaN
high NaN NaN NaN
1 Lowest NaN NaN NaN

How do I rectify my code to get the sums in place of NaN's in Counts columns and force the Survived and Fare kind out of index

Answer Source

Try something like this.

 sums = third_class.groupby(["Survived","Fare Kind"]).sum()

I find that just summing everything and then selecting the aggregation after is easier to understand.

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