Introduction to Programming with Python – Part 1
Wednesday, February 17
1:00 PM to 3:00 PM
This workshop introduces fundamental concepts of programming through the Python programming language. By the end of the hands-on workshop, you’ll have a core understanding of variables, data types, control flow, functions, and basic data structures. You will know enough to write basic scripts and explore other features of the language. This workshop is appropriate for those with little or no programming experience.
Introduction to Programming with Python – Part 2
Wednesday, February 24
1:00 PM to 3:00 PM
This workshop introduces fundamental concepts of programming through the Python programming language. By the end of the hands-on workshop, you’ll have a core understanding of variables, data types, control flow, functions, and basic data structures. You will know enough to write basic scripts and explore other features of the language. This workshop is appropriate for those with little or no programming experience.
Wednesday, March 3
1:00 PM to 3:00 PM
Reading, exploring, and writing data with Pandas. This series provides an introduction to core concepts for working with data in Python using the Pandas data analysis library and an opportunity to apply these concepts in an open, supported environment. In this lab we will cover an introduction to the Pandas library, including methods for reading, exploring, and writing various data formats such as tab-delimited files, Excel files, and JSON files with Pandas. The format of each open lab consists of a guided activity covering specific concepts followed by extended open time for self-guided practice using datasets and activities provided by the instructors. During this open time participants will have access to instructors and peers for questions and support.
Wednesday, March 10
1:00 PM to 3:00 PM
Data wrangling with Pandas. This series provides an introduction to core concepts for working with data in Python using the Pandas data analysis library and an opportunity to apply these concepts in an open, supported environment. In this lab we will cover common methods for cleaning and preparing datasets for analyses with Pandas such as filtering, aggregation, and joins. The format of each open lab consists of a guided activity covering specific concepts followed by extended open time for self-guided practice using datasets and activities provided by the instructors. During this open time participants will have access to instructors and peers for questions and support.
Wednesday, March 17
1:00 PM to 3:00 PM
Exploratory analysis and visualization with Pandas. This series provides an introduction to core concepts for working with data in Python using the Pandas data analysis library and an opportunity to apply these concepts in an open, supported environment. In this lab we will cover common exploratory analysis methods using Pandas and a collection of Python visualization libraries. The format of each open lab consists of a guided activity covering specific concepts followed by extended open time for self-guided practice using datasets and activities provided by the instructors. During this open time participants will have access to instructors and peers for questions and support.