Nothing
knitr::opts_chunk$set(message = FALSE)
Here you'll find a series of example of calls to yf_get()
. Most arguments
are self-explanatory, but you can find more details at the help files.
The steps of the algorithm are:
library(yfR) # set options for algorithm my_ticker <- 'GM' first_date <- Sys.Date() - 30 last_date <- Sys.Date() # fetch data df_yf <- yf_get(tickers = my_ticker, first_date = first_date, last_date = last_date) # output is a tibble with data head(df_yf)
library(yfR) library(ggplot2) my_ticker <- c('TSLA', 'GM', 'MMM') first_date <- Sys.Date() - 100 last_date <- Sys.Date() df_yf_multiple <- yf_get(tickers = my_ticker, first_date = first_date, last_date = last_date) p <- ggplot(df_yf_multiple, aes(x = ref_date, y = price_adjusted, color = ticker)) + geom_line() p
library(yfR) library(ggplot2) library(dplyr) my_ticker <- 'GE' first_date <- '2005-01-01' last_date <- Sys.Date() df_dailly <- yf_get(tickers = my_ticker, first_date, last_date, freq_data = 'daily') %>% mutate(freq = 'daily') df_weekly <- yf_get(tickers = my_ticker, first_date, last_date, freq_data = 'weekly') %>% mutate(freq = 'weekly') df_monthly <- yf_get(tickers = my_ticker, first_date, last_date, freq_data = 'monthly') %>% mutate(freq = 'monthly') df_yearly <- yf_get(tickers = my_ticker, first_date, last_date, freq_data = 'yearly') %>% mutate(freq = 'yearly') # bind it all together for plotting df_allfreq <- bind_rows( list(df_dailly, df_weekly, df_monthly, df_yearly) ) %>% mutate(freq = factor(freq, levels = c('daily', 'weekly', 'monthly', 'yearly'))) # make sure the order in plot is right p <- ggplot(df_allfreq, aes(x = ref_date, y = price_adjusted)) + geom_line() + facet_grid(freq ~ ticker) + theme_minimal() + labs(x = '', y = 'Adjusted Prices') print(p)
library(yfR) library(ggplot2) my_ticker <- c('TSLA', 'GM', 'MMM') first_date <- Sys.Date() - 100 last_date <- Sys.Date() df_yf_multiple <- yf_get(tickers = my_ticker, first_date = first_date, last_date = last_date) print(df_yf_multiple) l_wide <- yf_convert_to_wide(df_yf_multiple) names(l_wide) prices_wide <- l_wide$price_adjusted head(prices_wide)
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