data analysis

Top five(ish) sources of ecological data

In this post, I show you how to navigate some common ecological data portals and discuss when you might want to use one or another for accessing data that you can use for practice or your next research project.

The basics of prototyping and exporting your plots in R

In this tutorial, I go over the basics of how to prototype, save, and export your plots from R.

How to create your own functions in R

In this tutorial, I'm going to explain how to create your own functions and provide a few examples.

Search through your ecological data with the 'grep()' function

Here I describe the functions called `grep()`, `grepl()`, and `sub()`, which allow you to find strings in your data that match particular patterns.

Learning about data structures in R

In this tutorial, we're introduce the structures that R provides to help you organize your data.

R Data types 101, or What kind of data do I have?

In this tutorial, I introduce you to several different types of data, explain how to use and manipulate each of them, and show you how to check what type of data you have.

Complete tutorial on using 'apply' functions in R

Here I show you a useful family of functions that allows you to repetitively perform a specified function (e.g., sum, mean) across a vector, matrix, or data frame.

How to use pipes to clean up your R code

In this tutorial, I'm going to give an explanation of what pipes are and when they can be used, and then I'm going to demonstrate how useful they can be for writing neat and clear R code.

How to use R Markdown (part two): for learning R!

In part two of my series on R Markdown, I'll go over how to use R Markdown for learning R by documenting your journey into your own guide to R.

How to use R Markdown (part one)

R Markdown is a powerful method for creating reports that combine formatted text with R code. This can help you with accountability, data analysis reproducibility, for making tutorials (like this one), and also for learning R! In part one of this two-part series, you'll learn how to create basic R Markdown documents with all the essential content.