Elevator Pitch
Visualizations are cool and so is Python. Lets learn how Python graphing library plotly and cufflinks can be used to create the next level of data visualization in Python. I will show you how to make great-looking, fully-interactive plots with a SINGLE line of python.
Description
Data visualization is a critical component of data analysis and even among dozens of libraries in Python’s visualization landscape, It is hard to find the one that supports for a wide range of plot types covering statistical, 3D, and geographic use cases; efficient GPU acceleration to handle large data sets; offline export of high-quality static images; two-way interactivity in the Jupyter Notebook; and stand-alone dashboarding support.
In this talk, I will introduce you to Plotly & cufflinks, a data analysis and graphing tool that works well with other Python’s open source libraries including Pandas & Numpy libraries. Then we’ll go through a fun graphing examples together through introductory plots along with some advanced charts including 3d plots. Attendees will go with: 1. Understanding of Plotly 2. Plotting Interactive Maps 3. Quick introduction to Plot Controls & Ipython widgets
No need for expensive mapping software, we’ll have everything we need in a Jupyter Notebook. You’ll leave this talk with a new-found love for visualization and the power to make your own. Happy exploring!
Notes
Technical Requirements. Users will need pandas, plotly, cufflinks, dash (optional) installed in their python stack.
Himanshu Chaturvedi is a data scientist at Toyota Financial Services in Dallas in customer anlaytics division. My interests are in Machine Learning and Natural Language Processing along with exploring new open source technologies and explaining the difficult concepts in the easy-to-understand way. I have been using various various visualization tools in open source python domain from last 4 year including matlplotlib, bokeh and now plotly and want to spread the new level of visualization using plotly.