Practical Business Python

Taking care of business, one python script at a time


Tue 09 June 2015

Collecting Data with Google Forms and Pandas

Posted by Chris Moffitt in articles   

Google Forms is a service that allows you to collect information via simple web forms. One of the useful features is that the forms will automatically save your data to a Google Sheet. This article will walk through how to create a form, authenticate using OAuth 2 and read all the responses into a pandas dataframe. Because the initial setup and authentication process is a little time consuming, this article will be the first in a two part series.

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Sun 17 May 2015

Notebooks Now on Github and Other Updates

Posted by Chris Moffitt in articles   

In case you missed it, github recently announced that Jupyter notebooks will be natively rendered by github. This useful new feature will make it easier for followers of pbpython to view notebooks through github as well as download them to your local system and follow along.

I have moved over 4 notebooks to github and set up the associated files so that it should be pretty straightforward for anyone to checkout the pbpython repo and work with the notebooks. This will also make it easier for others to follow along and help spot issues and make this collection of tips and tricks even more robust.

This post also contains a couple of helpful links I wanted to pass on and keep record of because I think they are really useful.

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Wed 08 April 2015

Improving Pandas’s Excel Output

Posted by Chris Moffitt in articles   

Pandas makes it very easy to output a DataFrame to Excel. However, there are limited options for customizing the output and using Excel’s features to make your output as useful as it could be. Fortunately, it is easy to use the excellent XlsxWriter module to customize and enhance the Excel workbooks created by Panda’s to_excel function. This article will describe how to use XlsxWriter and Pandas to make complex, visually appealing and useful Excel workbooks. As an added bonus, the article will briefly discuss the use of the new assign function that has been introduced in pandas 0.16.0.

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