cm010.Rmd

---
title: "cm010"
author: "Cody"
date: "October 5, 2017"
output: pdf_document
---

We need the tidyverse as well as the devtools packages
```{r}
library(tidyverse)
library
library(devtools)
```
Here we explore the different ways to bring two data frames together using the dplyr package.
```{r}
left_join()
inner_join()
full_join()
anti_join()
semi_join()
```
Here we also pull packages from Joey Bernhardt's github repo.
```{r}
library(singer)
```
Now we pull the data into the current environment
```{r}
data("locations")
data("songs")
```

```{r}
glimpse(songs)
glimpse(locations)
```

```{r}
View(songs)
View(locations)
```

### Release and Year

Produce a dataframe with all the albums ('release'), the artists ('artist_name') and the year ('year') in which album was published.

```{r}
combined <- inner_join(locations,songs, by = c("title","artist_name")) %>% 
              select(release,artist_name,year)
View(inner_join(locations,songs,by="title"))
View(combined)
```

### Challenge 1

Get the number of releases per year

```{r}
inner_join(songs,locations,by="title") %>% 
  count(year)
```

## Reshaping

```{r}
data("singer_locations")
glimpse(singer_locations)
```

```{r}
hfd_y <- singer_locations %>% 
  select(year,artist_hotttnesss,artist_familiarity,duration)

hfd_y %>% 
  filter(year>1900) %>% 
  ggplot(aes(x=year,y=duration))+
  geom_point(color="orange")
hfd_y %>% 
  filter(year>1900) %>% 
  ggplot(aes(x=year,y=artist_hotttnesss))+
  geom_point(color="orange")
```

We want package 'tidyr', function 'gather()', from wide to long

```{r}
hfd_y_long <- hfd_y %>% 
                gather(key="Measure",value="Units",artist_hotttnesss:duration)
View(hfd_y)
View(hfd_y_long)
hfd_y_long %>% 
  filter(year>1900) %>% 
  ggplot(aes(x=year,y=Units))+
  geom_point()+
  facet_wrap(~ Measure)
  
```