Online Workshops are Live/Synchronous:

• Click here to join this workshop in Webex: https://gsumeetings.webex.com/gsumeetings/j.php?MTID=m49e663335942aac3727916b1fee9a025
  • Steps for joining a Webex meeting: https://www.youtube.com/watch?v=fE5FnEUKtaE
  • You may be required to download the Webex app to attend the workshop, so please give yourself ample time to do so before the workshop begins.
  • Set these as your options when joining the Webex meeting: (1) Set your video option to No Video, and (2) Mute yourself.
• There is NO REGISTRATION and there is no maximum attendance -- the more the merrier!
• You will NOT need to install any data software to attend the workshop -- you will not be doing any hands-on work during the online workshop but instead will be watching the workshop instructor demonstrate the software/tools. There will be opportunities to ask questions.

Recorded Workshops:

We also will offer recorded versions of the workshops to enable those not able to attend the live version to instead watch the recorded version at their convenience. As the recordings become available, we will post them here:

https://research.library.gsu.edu/dataservices/rds-workshops-recordings

At the end of the recorded workshop, we will provide the check-in form link for attendance purposes. 

This workshop is the second of a two-part series in using Python for conducting data analysis. The workshop will build upon the topics covered in Python & Data 1 and introduce participants to more tools and techniques for managing and analyzing data.

Participants will have the opportunity to practice manipulating and creating new variables from a sample dataset. Participants will also practice generating statistical models using the same sample dataset.

This workshop completes all processes and analyses using code (i.e. there are no point-and-click methods). However, no previous programming or coding experience is required in order to be successful. All are welcome.

Workshop Topics:

• All topics covered in Python & Data 1
• Creating and transforming variables
• Slicing, indexing, and sub-setting data tables
• Editing, updating, and fixing data samples
• Statistical modelling using Statsmodels
• Statistical and Machine Learning modelling using Scikit-Learn

Prerequisites:

• Python & Data 1: Intro to Python for Data Analysis.
• Basic familiarity with statistical modelling (e.g. simple and multiple regression)

NOTE:

• This is the second workshop in a two-part series (Python & Data 1 is the first).
• Python is a free programming language, but there are many “distributions”. If you want to bring your own laptop to the workshop, we highly recommend you download and install the “Python 3.7 version of Anaconda” on your machine before arriving.
• This workshop will focus on using Python in a Windows environment.
• Please read our Workshops ~ Etiquette & Policies page for pertinent information to your workshop attendance.

Presenter: Jeremy Walker, Data Services Librarian and member of the Library's Research Data Services Team

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