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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.


Effective Targeted Campaigns with Machine Intelligence

Advanced market segmentation using Machine Learning to develop targeted campaigns to improve consumer behavior around payment operations

This is what 24 hours of Metro Manila holiday traffic looks like

We're excited to be working with the MMDA to use real-time Waze data to analyze, diagnose, and address traffic congestion in Metro Manila.

Makeover Your Charts with These 5 Design Hacks

Small tweaks can make a big difference when it comes to data design. Here are five case studies from our recent data storytelling workshop.