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Building Beautiful Plots with Matplotlib

October 12, 2015 blog-post matplotlib data-analysis

One of our favorite tools for data analysis and chart prototyping is iPython Notebooks, which we use with the Pandas and Matplotlib libraries of Python. Pandas is an easy-to-use library for manipulating data structures and performing data analysis in Python, while Matplotlib is a library used for generating two-dimensional charts and plots with code. Matplotlib easily builds the kinds of charts seen in scientific publications.

At the recent PythonPH Meetup held here at the Thinking Machines and Silicon Valley Insight office last September 24, our data science lead, Stef Sy, gave a short tutorial on how to use Matplotlib to generate beautiful charts.

Check out her presentation below or read the docs here. For questions or comments, follow and tweet Stef at @stefsy or view her work on Github.


Using AI/Big Data to Analyze Urban Mobility Patterns During the Pandemic

Can we still monitor movement under new constraints? In this second part of a blog series with ADB, we use Waze CCP mobility data to show how traffic flow has changed throughout lockdown in major Philippine cities.

Can machine learning and satellite imagery help improve humanitarian aid to Venezuelan migrants?

A hard life awaits millions of Venezuelan migrants seeking refuge in neighboring Colombia.

Dots are people too: Learnings from Information+

Our Data Designer, writes about what she learned from attending Information+, one of the few data visualization related conferences that targets both researchers and practitioners.