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Python is a general-purpose programming language that is becoming ever more popular for data science. This workshop is designed for beginners who had zero experience with Python, as it will offer you an introduction to the basic concepts of Python. Anaconda and Jupyter notebook will be introduced. Basic data types in Python, Python lists, functions, and packages will be covered. You will learn a fundamental Python package, NumPy, and powerful ways to store and manipulate data, and helpful data science tools to begin conducting your own analyses. The workshop will be offered twice in the Spring semester, so please pick the date which works better for you.
Following our Introduction to R workshop, this hands-on workshop Intermediate R will be the next stop on your journey in advancing your overall knowledge and capabilities wile programming in R. We will cover conditional statements, loops, and functions in R, as well as introducing on how to plot data with default graphics system in R. R plotting examples will be provided, from simple graphs such as boxplot and histogram to correlation matrices. You will be able to power your R scripts and generate R graphs with customizations after this workshop.
This hands-on workshop is designed for true beginners of R. This is the second (last) intro-level one offered in the Spring semester. We will be using R Studio in this workshop, so please make sure you have R (the environment) and R Studio (the program) both downloaded and installed prior to the workshop. Starting with a mini-lecture about R and programming, the workshop will teach you how to start programming with R (asking the right questions on Google) and provide you with hands-on experience in using R to perform basic analysis with an existing dataset. Hopefully, with the knowledge gained in the 90 minutes, you will become a more confident self-learner in programming and apply relevant data analysis skills to your own work.
The very basic data types in R were introduced in the Introduction to R workshop, even you missed it and you have no previous experience in R, this SSDA training workshop Instruction to Tidyverse might still be a good fit for you if you are interested in performing data analysis. You will learn to work with R tables through a powerful set of tools known as the Tidyverse, and learn the intertwined processes of data manipulation and visualization using the tools dplyr and ggplot2. You’ll get a taste of the value of exploratory data analysis and the power of Tidyverse tools.
Social scientists engaged in domestic research will typically utilize at least some of the U.S. Census data, an assemblage of over 100 different censuses, surveys, and data collection programs. While many download the data "by hand" from a web-based repository and import it into R, there is a quicker and often cleaner approach that uses the census API and the R package tidycensus. In this intermediate-level workshop you will learn more about census data (collection, geographies, types, errors) and how to use the tidycensus in R to directly access census data. After this workshop you should be able to start to automate your census data collection and easily streamline these data into your research.