How can I use advanced Pandas features in Jupyter Notebook?

How can I use advanced Pandas features in Jupyter Notebook?

You can leverage advanced Pandas features like multi-indexing, pivot tables, and groupby operations in Jupyter Notebook. Would you like examples of any specific feature?

Yes, can you show me how to create a pivot table?

Sure! You can create a pivot table using the pivot_table() function. For example:

import pandas as pd

data = {'A': ['foo', 'foo', 'bar', 'bar'], 'B': ['one', 'two', 'one', 'two'], 'C': [1, 2, 3, 4]}

df = pd.DataFrame(data)
pivot = df.pivot_table(values='C', index='A', columns='B', aggfunc='sum')
print(pivot)

This will give you a pivot table summarizing the values in column 'C'.

What if I want to apply multiple aggregation functions?

You can use the aggfunc parameter to apply multiple aggregation functions. For example:

pivot = df.pivot_table(values='C', index='A', columns='B', aggfunc=[np.sum, np.mean])

This will create a pivot table with both sum and mean for the values.

Thanks! Can you explain how to use multi-indexing?

Absolutely! Multi-indexing allows you to have multiple levels of indexing in your DataFrame. You can set it using the set_index() method. Would you like a code example?