01_template.Rmd

---
title: "my first notebook"
author: "‽"
date: "today's date"
output:
  html_notebook:
    toc: yes
    toc_float: yes
---

This is an [R Notebook](https://rmarkdown.rstudio.com/r_notebooks.html) illustrating [literate programming](https://en.wikipedia.org/wiki/Literate_programming) techniques with R code **inside** *code chunks* and incorporating explanations (enhanced via [R Markdown](http://rmarkdown.rstudio.com/)) **outside** the *code chunks*. You can execute code within the R Notebook. Results appear beneath the code will also be integrated into the output documents identified in the [YAML](https://en.wikipedia.org/wiki/YAML) header .

Try executing the code chunk, below, by clicking the green-arrow *Run* button (within the chunk), or by placing your cursor inside the chunk and pressing *Ctrl+Shift+Enter.*


```{r}
plot(cars)
```

Add a new chunk by clicking the *Insert Chunk* button on the toolbar or by pressing *Ctrl+Alt+I*.

When you save the notebook, an HTML file containing the code and output will be saved alongside it (click the *Preview* button or press *Ctrl+Shift+K* to preview the HTML file).

The preview shows you a rendered HTML copy of the contents of the editor. Consequently, unlike *Knit*, *Preview* does not run any R code chunks. Instead, the output of the chunk when it was last run in the editor is displayed.

*Ctrl+Shift+M*:  Generates a pipe -- ` %>% ` -- between functions (When you use the `tidyerse` package.)

###### https://rmarkdown.rstudio.com/r_notebooks.html

# Packages and the Tidyverse

###### https://tidyverse.org

```{r message=FALSE, warning=FALSE}
library(tidyverse)
```



# Hello World

This is my very first R Notebook.  

My^[Your Name Here ;-j] *favorite **search** engines* are 

1. [Google](http://google.com)
3. [Yahoo](http://yahoo.com)
2. [Bing](http://bing.com)

###### https://rmarkdown.rstudio.com/

# Load Data

###### https://support.rstudio.com/hc/en-us/articles/218611977-Importing-Data-with-RStudio
###### https://www.rstudio.com/resources/webinars/importing-data-into-r/

### Hurricane data from github

(Do you want to copy/paste the code?  https://is.gd/rcode)

```{r message=FALSE, warning=FALSE, include=FALSE}
canes <- read_csv("https://is.gd/bigstorms")
```

```{r echo=FALSE}
canes
```

have a look at the data structures and data types

###### http://r4ds.had.co.nz/tibbles.html

```{r}
class(canes)
```

###### http://r4ds.had.co.nz/vectors.html

```{r}
glimpse(canes)
```


# dplyr

- filter  (rows)
- arrange (sort rows by variables)
- select (columns)
- mutate (change cell values)
- Count
- Summarize

###### http://r4ds.had.co.nz/transform.html#introduction-2
###### http://dplyr.tidyverse.org/

```{r}
starwars
```

## Filter

```{r}
starwars_small <- starwars %>% 
  filter(!is.na(mass), !is.na(height))
```

## Arrange

```{r}
starwars_small %>% 
  arrange(desc(height), desc(name))
```

## Select

```{r}
starwars_small %>% 
  arrange(species, height) %>% 
  select(name, species, height, mass, birth_year)
```


```{r}
starwars_small %>% 
  select(name, species, height, mass, birth_year) %>% 
  arrange(species, desc(height), mass, name) %>% 
  filter(species == "Human") 
  
```



## Mutate

```{r}
starwars_small %>% 
  select(name, species, height, mass, birth_year) %>% 
  arrange(species, desc(height), mass, name) %>% 
  filter(species == "Human") %>% 
  mutate(BMI = round(height / mass, 2))
```


## Count

```{r}
starwars %>% 
  count(mass) %>% 
  arrange(desc(n))
```


## Summarize

```{r}
starwars %>% 
  filter(!is.na(height)) %>% 
  group_by(species) %>% 
  summarise(Count = n(), mean_ht = mean(height), min_ht = min(height),
            max_ht = max(height)) %>% 
  arrange(desc(Count))
```


# More information

https://rfun.library.duke.edu/intro2r