broken link fixes

Author: madelinegillman

Extras.qmd

@@ -10,22 +10,22 @@ format:
 
 Welcome to the **Bonus lessons** page. Below are two extra chapters you can explore:
 
----
+------------------------------------------------------------------------
 
 ## Bonus: Git and GitHub
 
 Learn how to create a GitHub account, set up Git on your computer, and start version-controlling your projects. This guide will walk you through:
 
-- Registering for GitHub  
-- Installing and configuring Git  
-- Your first commit and push  
+-   Registering for GitHub\
+-   Installing and configuring Git\
+-   Your first commit and push
 
-[Go to Bonus: Git and GitHub](bonus-git-and-github.html)
+[Go to Bonus: Git and GitHub](bonus-git-and-github.qmd)
 
----
+------------------------------------------------------------------------
 
 ## Alternative Data Wrangling (Class 6 Old Version)
 
 This is an alternate take on **Data Wrangling Day 2**, covering the same concepts with a slightly different workflow and examples. It’s great if you want more practice or a different perspective.
 
-[Go to Class 6 (Old Version)](class6_old.html)
+[Go to Class 6 (Old Version)](class6_old.qmd)

README.md

@@ -2,19 +2,16 @@
 
 We are an organization that hopes to make learning to program approachable, accessible, and effective. We want to improve rigor and reproducibility in science by providing programming resources and experiences to scientists and professionals in all levels of their careers. Our classes are small-group based courses with a teacher:student ratio that allows the students to learn dynamically and independently. During classes, students are able to follow along with the teacher leading the instruction, or work with one of our floating teachers to troubleshoot or to better understand their own code.
 
-This is our curriculum for learning R programming in the context of data analysis. Our curriculum development team has worked tirelessly to develop this new curriculum for the Summer of 2024. We are constantly improving and updating our curricula, so if you're interested in contributing or have suggestions, please visit <https://howtolearntocode.web.unc.edu/> for our most up-to-date contact information. If you have gotten to our Class 7 over Github, or are proficient in Github yourself, feel free to submit an issue or pull request at <https://github.com/How-to-Learn-to-Code/Rclass-DataScience>.
+This is our curriculum for learning R programming in the context of data analysis. Our curriculum development team has worked tirelessly to develop this new curriculum for the Summer of 2024. We are constantly improving and updating our curricula, so if you're interested in contributing or have suggestions, please visit <https://howtolearntocode.web.unc.edu/> for our most up-to-date contact information. If you have gotten to our lesson Github, or are proficient in Github yourself, feel free to submit an issue or pull request at <https://github.com/How-to-Learn-to-Code/Rclass-DataScience>.
 
-| Class Day |          Topic          |                          Link                           |
+| Class Day | Topic | Link |
 |:----------------------:|:----------------------:|:----------------------:|
-|     0     | Welcome to How to Learn to Code! |       [Introduction](class0.qmd)       |
-|     1     | R Coding Basics |   [Coding Basics 1](class1.qmd)    |
-|     2     | Applying Coding Basics |   [Coding Basics 2](class2.qmd)    |
-|     3     | Let's Get Plotting! |  [Data Visualization 1](class3.qmd)  |
-|     4     | Applying Visualization Methods |  [Data Vizualization 2](class4.qmd)  |
-|     5     | Data Wrangling Basics | [Data Wrangling 1](class5.qmd) |
-|     6     | Data Wrangling with Real Experimental Data | [Data Wrangling 2](class6.qmd) |
-|     7     | Running a Reproducible Analysis |       [Project 1](class7.qmd)       |
-|     8     | Practicing on Real World Data |       [Project 2](class8.qmd)       |
-
-: Table of Contents
-
+| 0 | Welcome to How to Learn to Code! | [Introduction](class0.qmd) |
+| 1 | R Coding Basics | [Coding Basics 1](class1.qmd) |
+| 2 | Applying Coding Basics | [Coding Basics 2](class2.qmd) |
+| 3 | Let's Get Plotting! | [Data Visualization 1](class3.qmd) |
+| 4 | Applying Visualization Methods | [Data Visualization 2](class4.qmd) |
+| 5 | Data Wrangling Basics | [Data Wrangling 1](class5.qmd) |
+| 6 | Applying Data Wrangling Basics | [Data Wrangling 2](class6.qmd) |
+| 7 | Practicing on Real World Data | [Project 1](class7.qmd) |
+| 8 | Bonus Lessons | [Bonus Lessons](Extras.qmd) |

class6.qmd

@@ -1,5 +1,5 @@
 ---
-title: "Data Wrangling with Real World Data"
+title: "Applying Data Wrangling Skills"
 subtitle: "Data Wrangling, Day 2 (Tour de France edition)"
 author: "Madeline Gillman & Austin Daigle"
 format: 
@@ -71,7 +71,7 @@ Let's read in the data and dig in!
 
 rider_hx <- read_csv("https://raw.githubusercontent.com/How-to-Learn-to-Code/Rclass-DataScience/main/data/wrangling-files/TDF_Riders_History_1919-2023.csv")
 
-stage_hx <- read_csv("https://raw.githubusercontent.com/How-to-Learn-to-Code/Rclass-DataScience/main/data/wrangling-files/TDF_Stages_History_1919-2023")
+stage_hx <- read_csv("https://raw.githubusercontent.com/How-to-Learn-to-Code/Rclass-DataScience/main/data/wrangling-files/TDF_Stages_History_1919-2023.csv")
 
 ```
 
@@ -103,13 +103,15 @@ Read in the dataset.
 
 ```{r}
 
-tdf_2024_df <- read_csv("https://raw.githubusercontent.com/How-to-Learn-to-Code/Rclass-DataScience/main/data/wrangling-files/tdf_2024_stage13_data")
+tdf_2024_df <- read_csv("https://raw.githubusercontent.com/How-to-Learn-to-Code/Rclass-DataScience/main/data/wrangling-files/tdf_2024_stage13_data.csv")
 ```
 
 1.  Try using `rbind()`, `bind_rows()` , and `merge()` to join the new data with the rider history data from above. Which one(s), if any, work? Why do you think they do (or do not) work?
 2.  If you need to make any modifications to the new data to enable a join, do so and then join the datasets. Make these changes in R, NOT Excel or a text editor. Doing so in R ensures that your changes are *reproducible* and that the original data is not destroyed or modified.
 3.  Use this new dataset to add this year's average speed to the same plots you made in Part 1.
-4.  Review your code from Parts 1 and 2. See if you can use pipes to connect as many steps as possible. As you do this, make sure you add comments to your code and consider if using too many pipes sacrifices code readability.
+4.  Write this new dataset to a new comma-separated file. See if you can write the file using one of these functions: `write.csv()`, `write_csv()`, and `write.table()`. Use the help pages for each of the functions to explore the difference between each. Which one will you probably use the most in your own analyses?
+    a.  Verify you can view this file using the file explorer on OnDemand, and download to your computer. If the file does not look like you expected, review the help pages for the function you used.
+5.  Review your code from Parts 1 and 2. See if you can use pipes to connect as many steps as possible. As you do this, make sure you add comments to your code and consider if using too many pipes sacrifices code readability.
 
 ## Part 3: Stage History