This is a series of ipython notebooks for downloading Twitter data in Python. For tutorials on how to analyze the data you've downloaded, please refer to a separate series of notebooks here: https://github.com/gdsaxton/PANDAS
In the first notebook I will show you how to use the Twitter API keys you set up in a prior tutorial: Setting up Access to the Twitter API. More notebooks will be forthcoming shortly.
If you are new to Python, you may wish to go through a series of tutorials I have created in order. If you don't wish to do all the tutorials you should at least ensure you have your Twitter API key and you've set up Python on your computer as shown in the tutorial "Setting up Your Computer to Use My Python Code".
Also note that we are using the iPython notebook interactive computing framework for running the code in this tutorial. If you're unfamiliar with this see this tutorial "Four Ways to Run your Code".
For a more general set of PANDAS notebook tutorials, I'd recommend this cookbook by Julia Evans. I also have a growing list of "recipes" that contains frequently used PANDAS commands.
##Prerequisites As you may know from my other tutorials, I am a big fan of the free Anaconda version of Python 2.7. It contains all of the prerequisites you need and will save you a lot of headaches getting your system set up. Once it's all installed open up a terminal and run the following:
git clone https://github.com/gdsaxton/Twitter.git
cd Twitter
ipython notebook
A tab containing links to all of the available chapters will open up in your browser at http://localhost:8888
I hope you find these tutorials helpful; please acknowledge the source in your own research papers if you’ve found them useful:
Saxton, Gregory D. (2015). Analyzing Big Data with Python. Buffalo, NY: http://social-metrics.org
Also, please share and spread the word to help build a vibrant community of Python and PANDAS users.
Happy coding!