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STACKING AND UNSTACKING MULTIINDICES

In this article we’ll be working on our example from the previous part. Our subject today is stacking and unstacking multi-indices. So, without further ado, let’s import pandas and numpy and let’s recreate our previous example:

In [1]:

import numpy as np
import pandas as pd

# the tuples used as indices
index = [('Company A', 2018), ('Company A', 2019),
        ('Company B', 2018), ('Company B', 2019),
        ('Company C', 2018), ('Company C', 2019)]

# the list of sales
sales = [125, 211,
        390, 455,
        475, 655]

# Let's create a Series object.
s = pd.Series(sales, index=index)

# Here's the multi-index.
m_index = pd.MultiIndex.from_tuples(index)

# Let's reindex the Series object.
s = s.reindex(m_index)

s

Out[1]:

Company A  2018    125
           2019    211
Company B  2018    390
           2019    455
Company C  2018    475
           2019    655
dtype: int64

As you prpbably noticed, the multi-indexed Series looks very much like a DataFrame. Actually, it can be easily converted to a DataFrame by means of the unstack method. There’s also the stack method, which does the contrary, so converts a DataFrame to a multi-indexed Series. Have a look:

In [2]:

# convert to DataFrame
s_df = s.unstack()
s_df

Out[2]:

	2018	2019
Company A	125	211
Company B	390	455
Company C	475	655

In [3]:

# convert back to multi-indexed Series
s = s_df.stack()
s

Out[3]:

Company A  2018    125
           2019    211
Company B  2018    390
           2019    455
Company C  2018    475
           2019    655
dtype: int64