Introduction to R for Environmental Data Analysis

Introduction to R for Environmental Data Analysis, available at Free, has an average rating of 4.4, with 9 lectures, based on 34 reviews, and has 2100 subscribers.

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You will learn about Program with R Learn to use ggplot2 Visualize climate data Raise awareness about rising temperatures Use linear interpolation This course is ideal for individuals who are Programmers curious about the intersection of environmental science, coding, and data science/visualization. It is particularly useful for Programmers curious about the intersection of environmental science, coding, and data science/visualization.

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Summary

Title: Introduction to R for Environmental Data Analysis

Price: Free

Average Rating: 4.4

Number of Lectures: 9

Number of Published Lectures: 9

Number of Curriculum Items: 9

Number of Published Curriculum Objects: 9

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

Program with R

Learn to use ggplot2

Visualize climate data

Raise awareness about rising temperatures

Use linear interpolation

Who Should Attend

Programmers curious about the intersection of environmental science, coding, and data science/visualization.

Target Audiences

Programmers curious about the intersection of environmental science, coding, and data science/visualization.

Interested in climate change, programming, or data visualization? Then, this course is for you!

In this course, you will learn how to graph climate data using the R programming language in Google Colab! Specifically, we’ll be looking at how the average annual air temperature changes as the years go by (the x-axis will be the year, and the y-axis will be the average annual temperature). We’ll use San Diego climate data from the National Centers for the Environmental Information (NCEI) Global Summary of the Year weather database, but you’re welcome to use data from any city. To approximate missing values in the dataset, we’ll use linear interpolation and install the necessary packages such as tidyverse, ggplot2, readr, and imputeTS. We’ll make basic graphs with ggplot2, including features such as the axes, data points, and lines. Then, we’ll make more aesthetic and visual graphs by adding layers, or geoms, with different features such as a title, axes labels, gradient color scale, locally estimated scatterplot smoother, and more! Next, we’ll make the graphs with the Fahrenheit system instead of Celsius using a math equation to convert the temperature values. Finally, you’ll be provided with some additional resources regarding climate change. No programming experience is needed.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Set Up Google Colab R Notebook

Lecture 1: Create an R Notebook in Google Colab.

Chapter 3: Download, Install, and Load the Climate Data and Packages

Lecture 1: Downloading, Installing, and Loading the Climate Data and Packages

Chapter 4: Use Linear Interpolation to Approximate Missing Values

Lecture 1: Linear Interpolation to Approximate Missing Values

Chapter 5: Make a Basic Graph Using ggplot2

Lecture 1: Making a Basic Graph Using ggplot2

Chapter 6: Add Additional Visual/Aesthetic Aspects to the Graph

Lecture 1: Adding More Layers and Aesthetic Aspects to the Graph

Chapter 7: Create the Graphs Using the Fahrenheit System

Lecture 1: Creating the Graphs with the Fahrenheit Temperature System

Chapter 8: Climate Change Resources + Wrap Up

Lecture 1: Climate Change Resources + Wrap Up

Chapter 9: Notebook Guide with Code

Lecture 1: Notebook Guide with Code

Instructors

Sarah Gao
Instructor at Udemy

Rating Distribution

1 stars: 0 votes

2 stars: 2 votes

3 stars: 2 votes

4 stars: 11 votes

5 stars: 19 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!