Basic Statistics in R - Part 1
This course focuses on calculating basic statistics in R.
Data @ Rice
Wrangling Data in R with dplyr - Part 1
This course focuses on wrangling data using dplyr, a popular package in R.
Cleaning Data in R - Part 2
This course dives deeper into the process of cleaning data in R.
Cleaning Data in R - Part 1
This course focuses on the basics of cleaning data in R.
Importing and Indexing Data in R
This course focuses on importing and indexing data in R.
Basics of R and RStudio
This workshop explores the basics of R, one of the most popular programming languages for data analytics and data science in academia and beyond.
Data Analysis and Visualization with Pandas in Python
Prerequisites:
Recommended for those who have completed the Python for Absolute Beginners series or who have basic Python skills.
Overview:
This course covers basic analysis and visualization of data frames using the pandas library in Python. Topics include subsetting a data frame, calculating summary statistics, and creating bar and scatter plots.
Contact information:
Please email mrsmith@rice.edu if you have questions about the Data@Rice workshop series.
Python for Absolute Beginners - Part 2
Prerequisites:
Python for Absolute Beginners - Part 1
Overview:
This is a continuation of our two-part Python for Absolute Beginners series. This hands-on workshop introduces additional features of Python. Topics include uses of lists and dictionaries, Boolean values, for and while loops, and an introduction to libraries.
If you have experience with Python, please consider our other Python offerings.
Contact information:
Docker Part 2: Containerizing a Data Viz App
We will use a containerized Python app to show the advantages of containerization for building, iterating, and deploying an interactive application.
Docker Part 1: Introduction to Docker
Prerequisites:
While our example code will be written in Python, this class focuses on containerized deployment of lightweight, interactive apps.
Overview: