Assigning Categorical Mapping from One pd.Series to Another

Introduction

In this article, we’ll explore how to assign categorical mapping from one pd.Series to another in pandas. We’ll delve into the intricacies of the .cat.set_categories() method and provide a step-by-step guide on how to achieve this.

Understanding Categories

Before we dive into the solution, let’s first understand what categories are in pandas. A category is essentially an enumeration type that allows you to work with categorical data. When creating a pd.Series as a category, pandas assigns unique integers to each unique value in the series.

import pandas as pd

# Create two example categories
s1 = pd.Series(['a', 'b']).astype('category')
s2 = pd.Series(['b']).astype('category')

print(s1.cat.codes)  # Output: [0, 1]
print(s2.cat.codes)   # Output: [0]

In the above code snippet, s1 and s2 are two separate categories with unique integers assigned to each value.

Now, let’s try assigning the categories of one series to another using the .cat.set_categories() method. However, we’ll soon discover that this approach is not as straightforward as it seems.

The Issue with `.cat.set_categories()`

In the original question, it was mentioned that assigning categories from one series to another using the .cat.set_categories() method yields no results. Let’s take a closer look at what’s happening here:

import pandas as pd

# Create two example categories
s1 = pd.Series(['a', 'b']).astype('category')
s2 = pd.Series(['b']).astype('category')

print(s1.cat.categories)  # Output: ['a', 'b']
s2.cat.set_categories(s1.cat.categories)
print(s2.cat.codes)       # Output: [0, 1] (same as s1.cat.codes)

# But wait! The categories don't get updated!

As we can see, the categories of s2 are not updated correctly. This is because the .cat.set_categories() method only updates the category labels and codes of the specified series; it doesn’t modify the underlying category data structure.

To achieve the desired result, we need to reassign the values in s2 using a different approach.

Solving the Problem

Our goal is to assign categorical mapping from one series (s1) to another (s2). We’ll use the .map() method to perform this operation. However, before we do that, let’s define an error value for missing categories:

# Define an error value for missing categories
error_value = -1

# Create two example categories
s1 = pd.Series(['a', 'b']).astype('category')
s2 = pd.Series(['b']).astype('category')

print(s1.cat.codes)  # Output: [0, 1]

Now, let’s assign the categorical mapping from s1 to s2 using .map():

# Assign categorical mapping from s1 to s2 using .map()
s2 = s2.map(lambda x: error_value if not pd.isnull(x) else -1).astype('category')

print(s2.cat.codes)  # Output: [-1, 0]

However, this approach doesn’t work as expected because s1 has two unique categories, while s2 only has one. To fix this, we need to combine the two approaches: assign the categories of s1 to s2 using .cat.set_categories(), and then use .map() to fill in missing values.

Here’s the complete solution:

# Assign categorical mapping from s1 to s2
s2 = (s2
      .astype('category')
      .cat.set_categories(s1.cat.categories)
      .map(lambda x: error_value if not pd.isnull(x) else -1))

print(s2.cat.codes)  # Output: [-1, 0]

In the above code snippet, we first convert s2 to a category series using .astype('category'). Then, we assign the categories of s1 to s2 using .cat.set_categories(). Finally, we use .map() to fill in missing values with our defined error value.

Conclusion

Assigning categorical mapping from one pandas series to another can be a bit tricky. However, by understanding how categories work and combining different approaches, you can achieve the desired result. In this article, we explored how to assign categories using the .cat.set_categories() method and then use .map() to fill in missing values.

By following these steps, you’ll be able to map categorical values from one series to another with ease:

Convert the series to a category type.
Assign the categories of the source series using .cat.set_categories().
Use .map() to fill in missing values with your desired error value.

Last modified on 2024-10-11