Hi Charlie and Bert,
Thank you both for the suggestions and pointers. I will look into them.
FYI I repeatedly refer to tidyquant because that package refers to itself as
"tidyquant: Tidy Quantitative Financial Analysis" and I am hoping to get the
attention of someone who is involved in the tidyqua
Thanks for the reminder about lattice! I did some searching and there's
a good example of manipulating the size of subplots using the `position`
argument (see pp. 202-203 in the Trellis Users Guide:
http://ml.stat.purdue.edu/stat695t/writings/Trellis.User.pdf). This is
not within the paneling e
That (the need for base graphics) is false. It certainly **can** be done in
base graphics -- see ?layout for a perhaps more straightforward way to do
it along the lines you suggest.
However both lattice and ggplot are based on grid graphics, which has a
similar but slightly more flexible ?grid.lay
For this kind of control you will probably need to move to base graphics
and utilize the `fig` argument in par(), in which case you would want to
run the plot() command twice: once with your first outcome and once with
your second, changing the par() settings before each one to control the
size
Hi Charlie,
Thanks. This is helpful. As mentioned in my original question, I want to be
able to plot a few such charts on the same page,
say a 2 x 2 grid with such a chart for each of 4 different stocks. Using
your solution I accomplished this by making
a list pLst of your ggplots and then calling
So the general strategy for getting these into separate panels in ggplot
is to have a single variable that will be your response and a factor
variable that indexes which original variable it came from. This can be
accomplished in many ways, but the way I use is with the melt() function
in the r
If you don't want to wait for a ggplot2 solution, here are two
alternatives you can use right now:
chartSeries(SPYxts)
# or (with xts > 0.10
plot(SPYxts$SPY.Close)
addSeries(SPYxts$SPY.Volume, type = "h")
You might also try autoplot.zoo(), though I've never used it.
On Thu, Jan 18, 2018 at 2:
Hi Charlie,
I am comfortable to put the data in any way that works best. Here are two
possibilities: an xts and a data frame.
library(quantmod)
quantmod::getSymbols("SPY") # creates xts variable SPY
SPYxts <- SPY[,c("SPY.Close","SPY.Volume")]
SPYdf <- data.frame(Date=index(SPYxts),close=as.numer
Could you provide some information on your data structure (e.g., are the
two time series in separate columns in the data)? The solution is fairly
straightforward once you have the data in the right structure. And I do
not think tidyquant is necessary for what you want.
Best,
Charlie
--
Charle
A very common chart in the financial markets is a split chart with two time
series shown in two vertically stacked sub-charts.
A classic case would be the top panel showing the time series of historical
prices of some stock, and the bottom
panel showing the volume traded per day immediately below i
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