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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# Data Team Workshops
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Welcome to the Data Team workshops page! If you want to learn R or use the tools in our data pipeline, you've come to the right place. Over time we'll add more and more tutorials to cover a breadth of topics so that you can explore the R ecosystem and see how it could benefit your workflow.
## Tutorial References
Much of our R tutorials are based on the exceptionally handy [*R for Data Science*](https://r4ds.had.co.nz/) by Grolemund and Wickham. Rather than following a standard "computer science"-like approach of teaching the language fundamentals without application, Grolemund and Wickham take an application-first approach by going through the basics of data import, munging, and analysis while teaching the language on the side. For extra reading and exercises, we highly encourage perusing this text.
Once you feel comfortable working with R, the [RStudio cheatsheets](https://rstudio.com/resources/cheatsheets/) are an invaluable resource when you need some form of quick reference. The sheets are designed so that you can *visually* understand what the functions are doing, which builds a stronger intuition than just reading the function documentation.
For working with regular expressions, I highly recommend [regex101](https://regex101.com). Do note that you *don't* need to escape your backslashes on this platform, but you *do* need to do so with R!
# Workshop Recordings
Access to all recordings requires an NYU login (choose the "Sign in with SSO" button)
1. [Session 1: Getting to Know Your Data](https://nyu.zoom.us/rec/share/VLku7fo5upo3bVs8xdS8K92Q2UPwzrfzCHUxVGPCJh6XZtQqLGlElp2H4aUvEQr3.NghErP0lw2NxupVV)
2. [Session 2: Finding Relationships in Your Data](https://nyu.zoom.us/rec/share/zSF42XLuzubrBt9fwP2sMPriZvSAp9uq4hU5Qdc1CZI6TjZ6Vu7Cle-Id1Pny54r.cO3UymskhDJVXyWr)
3. [Session 3: Making R Work for You](https://nyu.zoom.us/rec/share/55nw_SkaeuhaCXAtZSNbCemnwi9trTvgKLiSKNjaoEew8Qb7mb3UTwKE6eT7rRyg.sg0ApiMqrMhP7B_D)
4. [Session 4: Workflows in R -- Recommended practices](https://nyu.zoom.us/rec/share/w1QiqFhfCjfSkPvrUjobg4_1xERFT3_v6FO9RjvggmfNzdjbG-TTpWYZtKfJvRD4.NHpuJlT-HIR-qihP)
# Setup
There are a couple steps to take to get ready:
## 1 - Get Materials
All materials for the workshops are contained in this repository. You'll need to download this repo to get started. There are a couple methods you can use.
### ZIP Download
Github provides downloadable ZIP archives of entire repositories for ease of use. Use the "Download ZIP" menu item via the "Code" button shown below:
Extract the ZIP in a folder you remember, and you'll be all set.
### Git-based
We'll have a git & Github tutorial soon, but for now we'll cover the basics just to get you started:
1. Install [Github Desktop](https://desktop.github.com/). This application takes care of most git workflow tasks.
2. Once installed, open Github Desktop, navigate to the menu, and select `File > Clone Repository...`.
3. In the dialog box that pops up, select the "URL" tab, and put "Global-TIES-for-Children/workshops" into the "Repository URL or GitHub username and repository" field. Choose whichever local path that you want.
## 2 - Get Set Up
At this point, you should have downloaded this repository. Now we need to set up this repository:
1. Download and install [R](https://cran.r-project.org/) *and* [RStudio](https://rstudio.com/). Note: R and RStudio are *not* the same thing. R is the language and execution environment, and RStudio is an integrated development environment (IDE) *for* R. In other words, you write code using RStudio, and then you run your code in R.
2. Navigate to where you downloaded this repository, and open `workshops.Rproj` with RStudio (double-clicking the file should do).
3. In the "Console" tab that should appear in the left pane, run these two commands in order:
```{r, eval=FALSE}
install.packages("devtools")
devtools::install_deps(dependencies = TRUE)
```
All of the packages that all materials depend upon should now be installed.