To load the data for today’s lecture, make sure you’ve got the ‘data.rdata’ file downloaded into the same working directory you defined in the setup section, then run these lines of code: We’ll just be working with a small portion: part of hurricane season (August 15-October 15) data for birds sighted across North Carolina from 2017 to 2019. Luckily, Lane has already done the hard part for you.
Visit this link for more information about how scientists use eBird data in their research projects, or check out this video of Lane Scher, where she talks us through how to use eBird and how it is used by scientists today.ĮBird is an extremely popular platform with a LOT of data (we’re talking gigabytes here) this would take you a very long time to download and use. Every time someone goes out on a walk or sits on their back porch, they’ll create a ‘checklist’ for that activity, recording the species and number of birds they see. eBird is a community-based platform launched in 2002 where anyone can create an account and log the birds they see.
The data we’re going to be working with today is from eBird. I hope this tutorial will help you appreciate EDA and begin to be comfortable with the basic tools of the trade. In my experience, I’ve discovered missing and duplicate data points, flipped latitude-longitude locations, and data that was just wrong, all from performing EDA. It can save you a lot of headaches in the future, too, by finding incorrect data points, or bizarre data trends due to incorrect data types. You have to know what’s going on with your data before you can begin to analyze it. We cover the basics here.ĮDA is really important for data analysis. This can be as simple as looking at a data table, or as complicated as plotting data points on a map. For this tutorial, we assume a basic understanding of the layout of RStudio.Įxploratory Data Analysis, or EDA, is a catch-all term that means “looking at the data you’ve got before starting on your analysis.” Just like you might read the back cover, flip through the pages, and admire the cover of a book before diving into the story, we do the same thing with data. If you are new to R or RStudio, check out my introductory R modules to get started. To access data files and scripts for this tutorial, visit this tutorial’s GitHub page. Welcome to Part 1 of our eBird dataset tutorial! Part 2 applies the basic exploratory data analysis lessons learned in this tutorial to some real-world analysis of hurricanes’ effects on birds in North Carolina.