.. _dataframes:

Dataframes
==========
Dataframes provide a table-like environment in order to keep our data (which could have lots of different types). It thus provides a spreadsheet-like interface for working with data, which can be very helpful. A dataframe can help us organize our data into a common (table/spreadsheet) format without having to go to the effort of defining our own objects, custom data types and so on. They are very commonly used in *data science* and *data visualization* type applications. 

A picture of a typical dataframe (here made using the `Polars <https://pola.rs/>`_ interface) in Python is shown below. 

.. figure:: dataframe_example.png
  :width: 800
  :align: center
  :alt: An example dataframe shown in interactive Python

  Screenshot of VSCode, software from `Microsoft <https://code.visualstudio.com/>`_. See `course copyright statement <https://uom-eee-eeen11202.github.io/chapters/about/copyright>`_.

We won't consider the details of dataframes in more detail here, we will explore them in the labs instead.

Note that you might also see *data series*. These are similar to dataframes, but represent a single column of data rather than multiple columns.

Not every programming languages has the concept of dataframes, and you can always use a 2D list or array or similar in a table-like structure. Nevertheless, when dataframes are available they provide lots of built in functions to help processing data.