Mini-Hackathon5.Rmd

---
layout: tutorial
title: 'Mini-Hackathon 5: Times-Series (Part II)'
author: "Mariken van der Velden & Kasper Welbers"
output:
  github_document:
  toc: yes
editor_options: 
  chunk_output_type: console
---
  
```{r setup, include=FALSE}
## include this at top of your RMarkdown file for pretty output
## make sure to have the printr package installed: install.packages('printr')
knitr::opts_chunk$set(echo = TRUE)
library(printr)
library(rmarkdown)
```

Mini-Hackathons are performed and submitted in pairs of two. 
You must hand in your assignment on Canvas the next week before **Tuesday Midnight**.

Use this RMarkdown template on the canvas page for this mini-hackathon to complete your hackathon.
When you are finished, knit the file into a pdf with the knit button in the toolbar (or using Ctrl+Shift+K).
For this you need to have the `knitr` and `printr` packages installed, and all your code needs to work (see the R course companion for more instructions).
If you cannot knit the `.Rmd` file, there is probably an error in your R code, therefore add `eval=FALSE` to the code chunk: `{r, eval = FALSE}`, so you are still able to knit and upload the file.

# This Mini-Hackathon
This mini-hackathon builds upon **all** tutorials of this course.
For this hackathon, you're therefore strongly required to revisit the tutorials of the last five weeks.
If you aim to conduct additional analyses in R, we of course encourage this.
Nevertheless, it is important to not do additional analysis just for the sake of running more code chunks. 
For that reason, please provide a justification for these additional analyses.

Also, we recommend to use parameters for RMarkdown codeblocks, in particular the `cache = TRUE` parameter for codeblocks that take long to compute (e.g., downloading data from AmCAT). 
A brief explanation of some usefull parameters to make a `.Rmd` file pretty is given in the [the first tutorial](https://github.com/MarikenvdVelden/Replication-Hackathons/blob/main/Intro-to-rmd-and-data-retrieval.md).
Additionally, you can use [this cheat sheet](https://rstudio.com/wp-content/uploads/2015/02/rmarkdown-cheatsheet.pdf).

Important to take into account is that this week we will build upon codes of last weeks. 

### Hackathon Challenges

#### Challenge 1
Based on the literature in week 1 -- 6 of this course, investigate initial support for a "simple" research question that could be answered using times-series data. 
This question should have the structure of does _variable X_ lead to more/ less in _variable Y_.
To answer your question, you can choose any data set we worked with in the tutorials:

- AmCAT data
- Guardian data
- Google trends data
- Stock market data
- Polling data

If this is not sufficient to answer your question, you can search the [fivethirtyeight database](https://data.fivethirtyeight.com/) for more data [here](https://github.com/fivethirtyeight/data).

Please describe the research question and elaborate on the data, including the data structure you need (e.g. which  level of aggregation) in order to answer the question.

#### Challenge 2
Create a data set using a **tidy script** with your X, Y, and date variable.

#### Challenge 3
Develop an infographic to visualize a meaningful relationship between your X and Y variable based on your data using `ggplot2`.
Try to make the infographic as informative and appealing as possible.
For this, you can use the [_ggplot2 cheat sheet_](https://rstudio.com/wp-content/uploads/2015/03/ggplot2-cheatsheet.pdf), the [_R Graphics Cookbook_](http://www.cookbook-r.com/Graphs/), [Kieran Healy's _Data Visualization_ book](https://socviz.co/), and/ or the [_BBC Visual and Data Journalism Cookbook_](https://bbc.github.io/rcookbook/).
If you want to make more than one graph, have a look at the `facet_wrap` function: `?facet_wrap`.

#### Challenge 4
What does your infographic demonstrate? Interpret the infographic in light of your research question. 

#### Challenge 5
To answer your question, run a correlation and interpret the value.
Reflect on your research design and describe the limitations.