Ggplot(aes(x = date, y = adjusted, color = symbol)) + We can also chart the time series of all the prices. # symbol date open high low close volume adjusted To see the first row of each symbol, we need to slice the data. This data is in tidy format, where symbols are stacked on top of one another. We can also download multiple stock prices. For that we will use the very popular ggplot2 package. We can see that the object aapl is a tibble. To = '') # 'AAPL' 'NFLX' 'AMZN' 'K' 'O' prices

There are several steps to this tickers = c('AAPL', 'NFLX', 'AMZN', 'K', 'O') We can download prices for several stocks. We can even zoom into a certain period of the series. We just pass the command chart_Series chart_Series(AAPL) class(AAPL) # 'xts' 'zoo'Īs we mentioned before this is an xts zoo object. head(AAPL) # AAPL.Open AAPL.High AAPL.Low AAPL.Close AAPL.Volume You can change this by passing the argument auto.assign = FALSE. By default quantmod download and stores the symbols with their own names. library(tidyquant)įirst we will download Apple price using quantmod from January 2017 to February 2018. tidyquant includes quantmod so you can install just tidyquant and get the quantmod packages as well. You can download the tidyquant package by typing install.packages('tidyquant') in you R console. For our calculations we will use tidyquant package which downloads prices in a tidy format as a tibble. The prices downloaded in by using quantmod are xts zoo objects. You can install it by typing the command install.packages('quantmod') in your R console. The most popular method is the quantmod package. There are several ways to get financial data into R.

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