Notes on (Baby)Pandas
=====================


In the zoo of tools used by data scientists,
[Python](http://python.org) and
[Pandas](http://pandas.pydata.org/)
are two of the most popular animals.
*Python* is a general purpose programming language known for its simple syntax
and its vibrant ecosystem of third-party packages. *Pandas* is a Python package
for exploring and analyzing large data sets. As a working data scientist,
there's a very good chance that you'll be using each on a daily basis.

While Pandas is a very powerful tool, it isn't simple. There are often several
ways of doing the same thing. This can make it difficult to get started with
Pandas, especially for those new to programming.

Instead of tackling the full complexity of Pandas immediately, in these notes we
will learn to use a simplified version of Pandas which we've called
*BabyPandas*. As the name suggests, BabyPandas *is* Pandas, but smaller. To be
precise, BabyPandas is a subset of Pandas, meaning that we have carefully
taken some of the pieces of Pandas, but left much out. As a result, whatever
code you write in BabyPandas will also work with Pandas, so you can be happy in
the fact that you're learning one of the most powerful tools in modern data
science.

#### Authors and Contributors

These notes are authored by Parker Addison and Justin Eldridge.
Thank you to the following people who made various contributions:

- Janine Tiefenbruck
- Devanshu Desai

#### License

This work is licensed under a
[Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License][cc-by-nc-nd].

[![CC BY-NC-ND 4.0][cc-by-nc-nd-image]][cc-by-nc-nd]

[cc-by-nc-nd]: http://creativecommons.org/licenses/by-nc-nd/4.0/
[cc-by-nc-nd-image]: https://licensebuttons.net/l/by-nc-nd/4.0/88x31.png