BatchGetSymbols 2.2

One of the main requests I get for package BatchGetSymbols is to add the choice of frequency of the financial dataset. Today I finally got some time to work on it. I just posted a new version of BatchGetSymbols in CRAN. The major change is that users can now set the time frequency of the financial data: dailly, weekly, monthly or yearly. Let’s check it out:

library(BatchGetSymbols)

## Loading required package: rvest

## Loading required package: xml2

## Loading required package: dplyr

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

## 

library(purrr)

## 
## Attaching package: 'purrr'

## The following object is masked from 'package:rvest':
## 
##     pluck

library(ggplot2)

my.fct <- function(my.freq) {
  
  df <- BatchGetSymbols(tickers = c('GE'), 
                      first.date = '2010-01-01',
                      last.date = Sys.Date(), do.cache = FALSE,
                      freq.data = my.freq)$df.tickers
  
  df$freq <- my.freq

  return(df)
}

my.possible.freq <-  c('daily', 'weekly', 'monthly', 'yearly')

df.allfreq <- bind_rows(map(.x = my.possible.freq, .f = my.fct))

## 
## Running BatchGetSymbols for:

## 
##    tickers =GE
##    Downloading data for benchmark ticker
## ^GSPC | yahoo (1|1)
## GE | yahoo (1|1) - Got 100% of valid prices | Good job!
## Running BatchGetSymbols for:
##    tickers =GE
##    Downloading data for benchmark ticker
## ^GSPC | yahoo (1|1)
## GE | yahoo (1|1) - Got 100% of valid prices | You got it!
## Running BatchGetSymbols for:
##    tickers =GE
##    Downloading data for benchmark ticker
## ^GSPC | yahoo (1|1)
## GE | yahoo (1|1) - Got 100% of valid prices | Feels good!
## Running BatchGetSymbols for:
##    tickers =GE
##    Downloading data for benchmark ticker
## ^GSPC | yahoo (1|1)
## GE | yahoo (1|1) - Got 100% of valid prices | You got it!

p <- ggplot(df.allfreq, aes(x=ref.date, y = price.adjusted)) + 
  geom_point() + geom_line() + facet_grid(freq ~ ticker)

print(p)