Group by multi index without losing an index with pandas in python

Sure, I'd be happy to help with that! Grouping by multiple indices in pandas can be done using the groupby function along with specifying multiple columns as the grouping keys. Here's a step-by-step tutorial with code examples:
Let's start by creating a sample DataFrame to work with.
Now, let's group the DataFrame by both 'City' and 'Year' columns.
You can perform various operations on the grouped data, such as calculating the mean, sum, or applying custom functions.
For example, let's calculate the mean temperature and humidity for each city-year combination:
Here's the complete code:
The output will show the original DataFrame and the grouped DataFrame with the mean values for each city-year combination.
This tutorial covers the basics of grouping by multiple indices in pandas without losing the original index. You can further customize the aggregation functions based on your specific needs.
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