# Importance of Combining Data

Understand the usefulness and importance of combining datasets for data analysis.

## We'll cover the following

## Recap of `pandas`

data structures

Before we see how data can be combined and manipulated, let's briefly go over `pandas`

data structures. The two primary data structures of the `pandas`

library are the `Series`

** **(one-dimensional data) and the DataFrame (two-dimensional data).

`Series`

A `Series`

is a one-dimensional labeled array that can hold any data type (integers, strings, floating point numbers, objects, etc.). The data in a `Series`

also comes with axis labels collectively known as the **index**. For example, we can create a simple `Series`

from a set of five random numbers (generated by `NumPy`

) with the following code:

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