```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

<br>

# Remote repositories

This assignment will allow you to demonstrate your ability to set up a remote repository on **GitHub**, clone it to **RStudio**, and use **Git** for some version control.

***

# Task 1

Create a new repository on **GitHub** called `fish497`. When setting up your repo, select the following features:

* Make the repo **Private**

* Add a `README.md`
    
* Add a `.gitignore` file, selecting **R** from the .gitignore template dropdown menu that appears when you check the box (you can type "R" in the filter box to jump there quickly)

***

# Task 2

After you create your new `fish497` repo,

* Click on the Settings tab

* Click on "Manage access" from the menu on the left

* Click on the green button labeled **Invite a collaborator** (note that you may be prompted to enter your **GitHub** password)

* In the search box that appears, type `mdscheuerell` and select Mark's name/username

* Click on the green button that says **Add mdscheuerell to this repository**

**Note**: This task will trigger a message to Mark with your invitation to join your newly created repo. You will have to wait for Mark to accept your invitation before you can complete Tasks 8 & 9.

***

# Task 3

Create a new project in **RStudio** with a connection to the **GitHub** repo you just created. Recall that Mark strongly suggests you put this project folder in a location not under some other form of version control (e.g., Dropbox, Google Docs).

***

# Task 4

Add, commit, and push the `.gitgnore` and `fish497.Rproj` files to your remote repo on **GitHub**.

***

# Task 5

Begin a simple research compendium. Start by creating a folder called `analysis`. You have several options to do so:

* Use a command line function

* Add a folder inside your new project folder created in Task 3 using Finder (Mac) or Explorer (Windows)

* Click on the "New Folder" button located in the upper left of the **Files** pane of **RStudio**

Now add an **R** script named `01_read-data.R` to the `/analysis/` folder with the following contents (you can use as few/many `#` for comments as you'd like):

```
## This script will read in the raw data

## load libraries
library(here)

## set data directory
data_dir <- here("data")
```

Add, commit, and push this **R** script to your remote repo on **GitHub**.

***

# Task 6

Create a folder called `data` using any of the methods mentioned in Task 5. Download the data set on Palmer penguins located [here](palmer_penguins.csv) and place it in the `/data/` folder you just created.

Add, commit, and push this data file to your remote repo on **GitHub**.

***

# Task 7

Edit your `README.md` file to describe the current contents of your repo. This should include something about the folders and files (you don't have to describe the `.gitignore` or `.Rproj` files).

Add, commit, and push this data file to your remote repo on **GitHub**.

***

# Task 8

When you are finished, create a new issue in your repo with the title:

`Assignment 1`

Leave a comment on the issue that *briefly* describes what you've done for this assignment. After doing so, assign Mark to the issue by selecting his username from the dropdown menu under **Assignees**. Also assign the "help wanted" label from the **Labels**. Finally, click on the green **Submit new issue** button.

***

# Task 9

Navigate back to your **GitHub** repo and create a new Project based on a "basic kanban" template and name it "Assignments". Delete the 3 default cards that automatically populated the project and then add the issue you created in Task 8 to the **To do** column.


