cm101.Rmd

---
title: "cm101"
author: "Cody"
date: "October 24, 2017"
output: pdf_document
---

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

# R for strings

```{r}
my_string <- "That's cool"
my_string
my_string2 <- 'This is another string with "double quotes". That\'s cool'
my_string2
my_string3 <- "A slash \\ "
my_string3
```

### Homework

How do I "string" a single slash?
```{r}
my_string4 <- `my_string`
my_string5 <- 'my_string'
my_string4==my_string5
my_string
```
Back quotes `` will allow for white space. This is useful for using datasets with strings.

```{r}
library(singer)
places <- unique(singer_locations$city)

str(places)
nchar(c("City","double", "a very long string"))
nchar(c("",NA," ","      ","\t","  "))
```
Note: Tab is represented by \t or just a tab, and they have different values under nchar. Quite strange.

## The tools of the trade

```{r}
devtools::install_github("tidyverse/stringer")
devtools::install_github("tidyverse/glue")
library(tidyverse)
library(stringer)
library(glue)
```

glueing 'glue{}'

```{r}
my_name <- "Cody"
my_age <- 013
my_color <- "Orange"
glue("My name is {my_name},", " My age yesterday was {my_age-1/365}")
paste0("My name is ",my_name,", My age yesterday was ",my_age-1/365)
```

Indentation
```{r}
glue("
My name is
          {my_name}, 
My age yesterday was 
          {my_age-1/365}")
```
Phrase : Today is Wedneday, October 29, 1986 and the sun shrines
Sys.date()
glue them togther

```{r}
phrase <- "Today is {Today_date} and the sun shrines"
glue(phrase,
     Today_date=Sys.Date())
glue(phrase,
     Today_date=(format(Sys.Date(), "%A, %B %d, %Y")))
```
Glue data
```{r}
singer_locations %>% 
  glue_data("{artist_name} is from {city}.") %>% 
  head()
```

# Stringr

Here are all the functions from this package
```{r}
library(stringr)
install.packages("htmlwidgets")
library(htmlwidgets)
getNamespaceExports("stringr")
```

Now lets say we want only the functions that have str
```{r}
getNamespaceExports("stringr") %>%
  str_view("str_")

getNamespaceExports("stringr") %>% 
  str_subset("str_")
```

Lets find all the places containing th estring "york"
```{r}
places <- unique(singer_locations$city)

places %>% 
  str_to_lower() %>% 
  str_subset("york")
```

 # Regular Expressions
 
 
```{r}
places %>%
str_subset("[Yy]ork")

places %>% 
  str_subset(coll("york",ignore_case=TRUE))

places %>% 
  str_subset("York$")

places %>% 
  str_subset("^York")
```

Find all places that contain a digit in their name

```{r}
places %>% 
  str_subset("[:digit:]")
```

B.a means must begin with B and have one a after B.
B.a? means either 0 or 1 a must happen after B.
B.a+ means multiple a can come after B.
```{r}
places %>% 
  str_subset("B.a+")
```