my_report.Rmd

---
title: "Writing Reports with R Markdown"
author: "Helena Nitschky"
date: '2023-03-29'
output: html_document
---

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

```{r packages, include=FALSE}
library(tidyverse)
```

This report was prepared to the attention of the United Nations. It analyzes the relationship between a country's GDP, its life expectancy and CO2 emissions. Our goal is to determine to what degree a country's economic strength or weakness may be related to its publichealth status and impact on climate pollution. We hypothesize that both life expectacy and CO2 emissions increase with a country's GDP. 

```{r loading data, include=FALSE}
gapminder_1997 <- read_csv("data/gapminder_1997.csv")
```

```{r gdp_lifeexp_1997, echo =FALSE}
ggplot(data = gapminder_1997) + #plus sign instead of pipe because ggplot
  aes(x = gdpPercap, y = lifeExp, color = continent, size = pop/1000000) + 
  geom_point() + 
  labs(x = "GDP (per capita)",
       y = "Life Expectancy", 
       title = "Do people in wealthy countries live longer?", 
       size = "Population (in millions")
```

```{r}
nCountries <- gapminder_1997 %>% 
  select(country) %>% 
  n_distinct()

minGDP <- gapminder_1997 %>% 
  summarize(round(min(gdpPercap))) %>% 
  pull()

maxGDP <- gapminder_1997 %>% 
  summarize(round(max(gdpPercap))) %>% 
  pull()

```

The above plot shows the relationship between GDP per capita and life expectancy for a total `r nCountries`. For this set of countries, economic wealth ranged from a minimum of USD `r minGDP` to a maximum of USD `r maxGDP`.

|HEADER 1|HEADER 2| 
|--------|--------|
|row 1, column 1|row 1, column 2|
|row 2, column 1|row 2, column 1|

|Summary of Data| 
|--------|--------|
|Number of Countries|`r nCountries`|
|Minimum GDP per capita|`r minGDP`|
|Maximum GDP per capita|`r maxGDP`|

```{r kabletabl}
library(knitr)

gapminder_1997 %>% 
  filter(continent == "Oceania") %>% 
  kable()
```

# Header1
## Header2 
### Header3

#Exercise R Markdown Syntax
* Create a bullet point list with three items
* As the first item, write the name of your currently favorite programing language in bold
* As the second item, write the name of a function you have found most useful in italics 
* Turn your bullet point list into numbered list 
* Create a fourth list item and find an online and or cheat sheet for basic Markdown syntax, write its name down here and hyperlink its url 

## Bullet List Exercise 

- **Snakemake** is my favorite programming language 
- *filter()* is the most useful function. 
- Differential Expression/Multivariate Analysis 

1) **Snakemake** is my favorite programming language 
2) *filter()* is the most useful function. 
3) Differential Expression/Multivariate Analysis 
4) <chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.rstudio.com/wp-content/uploads/2015/02/rmarkdown-cheatsheet.pdf>