Introduction to Pandas
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Introduction to Pandas

Clara Bennett & Tyler Jorgensen, Picwell

Class materials for PyLadies DC -- October 11, 2015

Viewing the materials

The class materials combine code and notes in IPython notebooks. You can view the tutorial notebook and the case study notebook right in GitHub. (They render IPython notebooks now! How cool is that??)

However, we chose to use IPython notebooks so that you can easily play with the code yourself and build your understanding of the Pandas library by seeing what happens when you change things. Therefore, we highly recommend that download this git repository and run the notebooks yourself locally.

Running the materials locally

Download the git repository

If you are familiar with git, go ahead and clone this repository. If not, you can click the "Download Zip" button to get a zipped folder with all of the files downloaded to your local machine. Unzip the folder and put it somewhere that you can easily access via the command line.


The required libraries to run the pandas_tutorial.ipynb notebook are found in requirements.txt. The additional libraries required to run pandas_case_study.ipynb are found in optionals.txt. To install the requirements with pip, simply change to the intro_pandas directory and run

pip install -r requirements.txt

You may need to use sudo if you're going to install the requirements to your system, rather than in a virtualenv.

Alternatively, you can install all of the requirements and basically anything else that you would need to work with data in Python by installing the Anaconda distribution. It comes bundled with all the pydata things.

Run the IPython Notebook server

Once you have everything installed, navigate to the intro_pandas directory from the command line and run

ipython notebook

This will start the IPython Notebook server and open a new tab in your browser that shows the contents of the intro_pandas directory. Do not close the command line window that is running the server.

Run the course notebooks

In your IPython Notebook browser tab, click on pandas_tutorial.ipynb. This will open yet another tab with the tutorial notebook in it.

Note that while every cell already has an input number and an output number, none of the cells have actually been run yet in this session. We recommend going to cell > run all as a first step, so that the whole notebook is loaded into memory and you can re-run whichever cells you like.

To run a cell and advance to the next one, press shift + enter. The results of the last line in the cell will be output below it. As you go through the notebook, feel free to modify the data and the code to see how the output changes. You can add new cells via the insert menu at the top.

Happy learning!