Details
Come join PYPTUG at out next monthly meeting (October 30th 2018) to learn more about the Python programming language, modules and tools. Python is the language to learn if you've never programmed before, and at the other end, it is also a tool that no expert would do without.
Main talk: Altair
presented by Martin DeWitt
bio:
Originally from Winston-Salem, Martin DeWitt is a former assistant professor of physics, who frequently used Python and IPython notebooks to teach both introductory and upper-level physics courses and labs. He is currently transitioning to a career in data science.
Abstract:
Altair is a statistical visualization Python library designed to facilitate the exploration of data by making it easy to generate interactive web-based visualizations. Using Pandas dataframes as data sources, Altair's API provides functionality to transform data (bin, sort, filter, and aggregate) and produce common graphs including histograms, line charts, scatter plots, and heatmaps. Graphs can be made interactive with features like panning, zooming, and filtering by mouse pointer selections. Most of the aspects of generating the visualizations -- axes, scales, legends, and interactive features -- are handled automatically, only requiring the user to employ Altair's concise declarative syntax to specify the connections between data columns in the dataframe and the various properties of the graph (axes, color, size, etc). With very few lines of code, you can generate rich, interactive, and portable web-based graphs.
In this presentation, I will first briefly introduce importing and viewing data using Pandas. I will then demonstrate some of the features of Altair for transforming data and creating both static and interactive graphs. We will work through a number of examples, step-by-step, from importing the data to a finalized graph. I intend for you to code along with me, so please be sure to bring your laptop.
For those who are interested in how the magic happens, Altair is based on Vega/Vega-Lite, which is a high-level grammar for producing interactive visualizations. "With Vega, visualizations are described in JSON, and generate interactive views using either HTML5 Canvas or SVG."(http://vega.github.io/) Altair works by taking specifications from the user through Python objects, generating the proper JSON code, and then using Vega to add a Canvas or SVG-based visualization to a web page. There are also renderers that allow Vega visualizations to be displayed in IPython and Jupyter notebooks.
Main talk: Altair
presented by Martin DeWitt
bio:
Originally from Winston-Salem, Martin DeWitt is a former assistant professor of physics, who frequently used Python and IPython notebooks to teach both introductory and upper-level physics courses and labs. He is currently transitioning to a career in data science.
Abstract:
Altair is a statistical visualization Python library designed to facilitate the exploration of data by making it easy to generate interactive web-based visualizations. Using Pandas dataframes as data sources, Altair's API provides functionality to transform data (bin, sort, filter, and aggregate) and produce common graphs including histograms, line charts, scatter plots, and heatmaps. Graphs can be made interactive with features like panning, zooming, and filtering by mouse pointer selections. Most of the aspects of generating the visualizations -- axes, scales, legends, and interactive features -- are handled automatically, only requiring the user to employ Altair's concise declarative syntax to specify the connections between data columns in the dataframe and the various properties of the graph (axes, color, size, etc). With very few lines of code, you can generate rich, interactive, and portable web-based graphs.
In this presentation, I will first briefly introduce importing and viewing data using Pandas. I will then demonstrate some of the features of Altair for transforming data and creating both static and interactive graphs. We will work through a number of examples, step-by-step, from importing the data to a finalized graph. I intend for you to code along with me, so please be sure to bring your laptop.
For those who are interested in how the magic happens, Altair is based on Vega/Vega-Lite, which is a high-level grammar for producing interactive visualizations. "With Vega, visualizations are described in JSON, and generate interactive views using either HTML5 Canvas or SVG."(http://vega.github.io/) Altair works by taking specifications from the user through Python objects, generating the proper JSON code, and then using Vega to add a Canvas or SVG-based visualization to a web page. There are also renderers that allow Vega visualizations to be displayed in IPython and Jupyter notebooks.
Lightning talks!
We will have some time for extemporaneous "lightning talks" of 5-10 minute duration. If you'd like to do one, some suggestions of talks were provided here, if you are looking for inspiration. Or talk about a project you are working on.
When:
Tuesday, October 30th 2018
Meeting starts at 6:00PM
Meeting starts at 6:00PM
Where:
Wake Forest University, close to Polo Rd and University Parkway:
Manchester Hall
room: Manchester 241
Wake Forest University, Winston-Salem, NC 27109
Manchester Hall
room: Manchester 241
Wake Forest University, Winston-Salem, NC 27109
See also this campus map (PDF) and also the Parking Map (PDF) (Manchester hall is #20A on the parking map)
And speaking of parking: Parking after 5pm is on a first-come, first-serve basis. The official parking policy is:
"Visitors can park in any general parking lot on campus. Visitors should avoid reserved spaces, faculty/staff lots, fire lanes or other restricted area on campus. Frequent visitors should contact Parking and Transportation to register for a parking permit."
Mailing List:
Don't forget to sign up to our user group mailing list:
It is the only step required to become a PYPTUG member.
