Totally just a mashup of “tibbletime: What’s It Used For?” by Matt Dancho at Business Science, and Daniel P. Hadley’s “How to Add a Logo to ggplot by Magick”. I don’t know who bert is. I wish I did. Wherever you are, Bert, your MC Hammer gif is awesome!

library(tibbletime)
library(tidyquant)

# Stock Prices from Yahoo! Finance
stocks <- c("INTC", "AMD", "NVDA", "MSFT")

stock_tbl <- stocks %>%
    tq_get(get = "stock.prices", from = "2017-01-01", to = "2018-01-04") 

stock_tbl <- stock_tbl %>%
    group_by(symbol)

stock_tbl

## # A tibble: 1,012 x 8
## # Groups: symbol [4]
##    symbol date        open  high   low close   volume adjusted
##    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
##  1 INTC   2017-01-03  36.6  36.9  36.3  36.6 20196500     35.6
##  2 INTC   2017-01-04  36.7  36.8  36.3  36.4 15915700     35.4
##  3 INTC   2017-01-05  36.5  36.7  36.3  36.3 13986000     35.3
##  4 INTC   2017-01-06  36.6  36.7  36.2  36.5 15114000     35.5
##  5 INTC   2017-01-09  36.5  36.9  36.5  36.6 19449400     35.6
##  6 INTC   2017-01-10  36.5  36.9  36.5  36.5 15918800     35.5
##  7 INTC   2017-01-11  36.5  37.0  36.5  37.0 22398400     35.9
##  8 INTC   2017-01-12  36.8  36.8  36.3  36.7 20391900     35.7
##  9 INTC   2017-01-13  36.7  36.9  36.6  36.8 15072200     35.8
## 10 INTC   2017-01-17  36.7  36.8  36.6  36.8 20163000     35.8
## # ... with 1,002 more rows

# Setup plotting function that can be reused later
ggplot_facet_by_symbol <- function(data, x, y, group = NULL) {
    
    # Setup expressions
    x_expr     <- rlang::enquo(x)
    y_expr     <- rlang::enquo(y)
    group_expr <- rlang::enquo(group)
    
    if (group_expr == ~NULL) { 
        # No groups
        g <- data %>%
            ggplot(aes(x = rlang::eval_tidy(rlang::`!!`(x_expr)), 
                       y = rlang::eval_tidy(rlang::`!!`(y_expr)), 
                       color = symbol)) +
            labs(x = quo_name(x_expr),
                 y = quo_name(y_expr))
    } else {
        # Deal with groups
        g <- data %>%
            ggplot(aes(x = rlang::eval_tidy(rlang::`!!`(x_expr)), 
                       y = rlang::eval_tidy(rlang::`!!`(y_expr)), 
                       color = symbol,
                       group = rlang::eval_tidy(rlang::`!!`(group_expr)) 
                       )
                   )  +
            labs(x = quo_name(x_expr),
                 y = quo_name(y_expr),
                 group = quo_name(group_expr))
    }
    
    # Add faceting and theme
    g <- g +
        geom_line() +
        facet_wrap(~ symbol, ncol = 2, scales = "free_y") +
        scale_color_tq() +
        theme_tq()
    
    return(g)
}

# Plot adjusted vs date
stock_tbl %>%
    ggplot_facet_by_symbol(date, adjusted) +
    labs(title = "Adjusted Prices 2017 through 2018")

library(here)
library(magick)

background <- image_read("https://i.imgur.com/cFRL127.png")

logo_raw <- image_read("https://i.imgur.com/oJDChqu.gif")

frames <- lapply(logo_raw, function(frame) {
  image_composite(background, frame, offset = "+100+400")
})


animation <- image_animate(image_join(frames))


image_write(animation, here::here("hammertibbletime.gif"))

Hammertime x tibbletime