In this tutorial, we will look at how to concat two category type Pandas series with the help of some examples.

## How to combine category type Pandas series?

You can use the Pandas `concat()`

function to combine two category type Pandas series. The following is the syntax –

# concat pandas series pd.concat([s1, s2])

Combining series with the same categories results in a category type series. In other cases, the resulting type will depend on the underlying categories.

## Examples

Let’s look at some examples of combining two category type series in Pandas.

### Concat category type Pandas series with the same categories

First, let’s combine two categorical Pandas series having the same category values using the `pd.concat()`

function.

import pandas as pd # create category type pandas series s1 = pd.Series(['a', 'b']).astype('category') s2 = pd.Series(['a', 'b', 'b']).astype('category') # combine the series print(pd.concat([s1, s2]))

Output:

0 a 1 b 0 a 1 b 2 b dtype: category Categories (2, object): ['a', 'b']

The resulting combined series is of category type with the same categories.

### Concat category type Pandas series with different categories

Let’s now create two category type Pandas series having different categories.

# create category type pandas series s1 = pd.Series(['a', 'b']).astype('category') s2 = pd.Series(['a', 'b', 'c']).astype('category') # display the series print(s1) print(s2)

Output:

0 a 1 b dtype: category Categories (2, object): ['a', 'b'] 0 a 1 b 2 c dtype: category Categories (3, object): ['a', 'b', 'c']

You can see that the series `s1`

has the categories “a” and “b” whereas the series `s2`

has the categories “a”, “b”, and “c”.

Let’s now combine them with the `pd.concat()`

function and see the outcome.

# combine the series print(pd.concat([s1, s2]))

Output:

0 a 1 b 0 a 1 b 2 c dtype: object

You can see that the resulting series is of `object`

type.

If you want to combine Pandas series with different categories into a category type series, use the `union_categoricals()`

function.

For example, let’s combine the above two series using the `union_categoricals()`

function.

from pandas.api.types import union_categoricals # combine series with different categories print(union_categoricals([s1, s2]))

Output:

['a', 'b', 'a', 'b', 'c'] Categories (3, object): ['a', 'b', 'c']

Note that the resulting categorical has unique categories combined from both the series.

For more on the `union_categoricals()`

function in Pandas, refer to this tutorial.

You might also be interested in –

- Concat DataFrames in Pandas
- Pandas Category Column to a List
- Pandas – Set Category Order of a Categorical Column

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