---
title: "Pivot_Wider and Pivot_Longer"
author: "Prof. Eric A. Suess"
date: "Today's Date"
output:
  html_document:
    toc: yes
    toc:float: yes
  pdf_document:
    toc: yes
params:
  symbol1: GM
  symbol2: F
  symbol3: TWTR
---

# Introduction: {.sidebar}

```{r message=FALSE}
library(tidyverse)
library(lubridate)
library(quantmod)
library(BatchGetSymbols)
```

### Nice Example:  {.sidebar}

Here is a nice example from the [tidyr](https://tidyr.tidyverse.org/reference/spread.html) website.

```{r}
set.seed(12345)

stocks <- data_frame(
  time = ymd('2009-01-01') + 0:9,  # ymd() is from the lubridate package
  X = rnorm(10, 0, 1),
  Y = rnorm(10, 0, 2),
  Z = rnorm(10, 0, 4)
)

stocks
```

```{r}
stocksm <- stocks %>% pivot_longer(-time,
                                   names_to = "stock", 
                                   values_to = "price"
                                   ) %>%
                      arrange(stock)
stocksm
```


```{r}
stocksm %>% pivot_wider(
                       names_from = stock,
                       values_from = price
                       )
```

```{r}
stocksm %>% pivot_wider(
                       names_from = time,
                       values_from = price
                       )
```


# Download some stock market data.  Nice and tidy? Yes or No?

Using [quantmod](http://www.quantmod.com/)

```{r}
library(quantmod)
```

This report examines the price of three stocks.

- print(params$symbol1)
- params$symbol2
- params$symbol3

```{r}
getSymbols(params$symbol1, src="yahoo") # from yahoo finance 
```

```{r}
stock01 <- getSymbols(params$symbol1, auto.assign = FALSE, src="yahoo") 
barChart(stock01)
```

```{r}
stock01 %>% head()
```



We will use the [BatchGetSymbols](https://cran.r-project.org/web/packages/BatchGetSymbols/vignettes/BatchGetSymbols-vignette.html) R package to download stock market data.

```{r}
library(BatchGetSymbols)
```


```{r}
# set dates
first.date <- Sys.Date() - 30
last.date <- Sys.Date()

# set tickers
tickers <- params

l.out <- BatchGetSymbols(tickers = tickers, 
                         first.date = first.date,
                         last.date = last.date, 
                         cache.folder = file.path(tempdir(), 
                                                  'BGS_Cache') ) # cache in tempdir()
```


```{r}
print(l.out$df.control)
```

Is the data in a tidy format?

```{r}
print(l.out$df.tickers)
```


```{r}
l.out$df.tickers %>% ggplot(aes(x = ref.date, y = price.close)) +
   geom_line() +
   facet_wrap(~ticker, scales = 'free_y') 
```