Week 2 Project Assignment
This lesson is called Week 2 Project Assignment, part of the R in 3 Months (Spring 2025) course. This lesson is called Week 2 Project Assignment, part of the R in 3 Months (Spring 2025) course.
Transcript
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Assignment example:
Your Turn
Before you do anything else, please check in with your coach and confirm that the data you are using is a good fit for the first few weeks of R in 3 Months. If you need some generic data, we have created a repository with several simple datasets for you to work with.
For this week, we want you to do some wrangling and analysis of your data. You can see an example in the "View code shown in video" section above. To do this assignment, you'll do the following:
1. Create a directory called “project_assignment” and create a new R project in this existing directory. Then create subfolders following our recommendation in this lesson. Alternatively, download the learner directory template which contains the project_assignment folder, and create an R project in it.
project_assignment/
├── code/
├── data-raw/
├── data/
└── project_assignment.Rproj
2. Chose a dataset (one of your own datasets or one of our suggested datasets) and store it in the data-raw folder.
3. Create an R script file, save it to the code folder, and add three sections (use ctrl + shift + R to open the section box):
# Load packages ---
# Import data ---
# Questions about the data ---
4. Under the “load packages” section you will load your packages
5. Under the “Import data” section, write the correct code to import your data as a CSV (if your data is in another format, let us know and we can help you convert it). Notice that you will need to specify the file path starting with “data-raw”.
6. Take some time to explore your dataset as we did in this lesson. No need to save your code in your script at this stage, but if you want to, add a comment or a new section for it. We recommend using pen and paper to take notes.
7. Under the “Questions about the data” section, add, as comments, exactly three questions that you want to answer with your data.
8. Under each question, create the correct code to answer it.
9. Once you've completed your work, compress your project_assignment folder and upload it to the form below.
10. If you have any specific questions, add those in the form below as well, or as comments in your R script. You can also record a video using the button below to send me a video demonstrating a bug, or explaining in more details what you were trying to do.
Have any questions? Put them below and we will help you out!
Course Content
127 Lessons
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