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 reshape2 package.
For example,
library(reshape2)
plotDF <- melt(SPYdf,
??? ??? ??? ??? ??? ??? id.vars="Date", # variables to replicate
??? ??? ??? ??? ??? ??? measure.vars=c("close", "volume"),
# variables
to create index from
??? ??? ??? ??? ??? ??? variable.name="parameter", # name of new
variable for index
??? ??? ??? ??? ??? ??? value.name="resp") # name of what will be
your
response variable
Now the ggplot2 code:
library(ggplot2)
ggplot(plotDF, aes(x=Date, y=resp)) +
??? facet_wrap(~parameter, ncol=1, scales="free") +
??? geom_line()
Hope that does the trick!
Charlie
On 01/18/2018 02:11 PM, Eric Berger wrote:> 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.numeric(SPYxts$SPY.Close),
> ?volume=as.numeric(SPYxts$SPY.Volume))
> rownames(SPYdf) <- NULL
>
> head(SPYxts)
> head(SPYdf)
>
> #? ? ? ? ? ?SPY.Close SPY.Volume
> #2007-01-03? ? 141.37? ?94807600
> #2007-01-04? ? 141.67? ?69620600
> #2007-01-05? ? 140.54? ?76645300
> #2007-01-08? ? 141.19? ?71655000
> #2007-01-09? ? 141.07? ?75680100
> #2007-01-10? ? 141.54? ?72428000
>
> #? ? ? ? Date? close? ?volume
> #1 2007-01-03 141.37 94807600
> #2 2007-01-04 141.67 69620600
> #3 2007-01-05 140.54 76645300
> #4 2007-01-08 141.19 71655000
> #5 2007-01-09 141.07 75680100
> #6 2007-01-10 141.54 72428000
>
> Thanks,
> Eric
>
>
>
> On Thu, Jan 18, 2018 at 8:00 PM, Charlie Redmon <redmonc at gmail.com
> <mailto:redmonc at gmail.com>> wrote:
>
> 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
>
> --
> Charles Redmon
> GRA, Center for Research Methods and Data Analysis
> PhD Student, Department of Linguistics
> University of Kansas
> Lawrence, KS, USA
>
>
--
Charles Redmon
GRA, Center for Research Methods and Data Analysis
PhD Student, Department of Linguistics
University of Kansas
Lawrence, KS, USA
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 cowplot::plot_grid( plotlist=pLst, nrow=2, ncol=2 ) That worked fine. The one issue I have is that in the ggplot you suggest, the price and volume facets are the same size. I would like them to be different sizes (e.g. the volume facet at the bottom is generally shown smaller than the facet above it in these types of charts.) I tried to find out how to do it but didn't succeed. I found a couple of relevant discussions (including Hadley writing that he did not think it was a useful feature. :-() https://github.com/tidyverse/ggplot2/issues/566 and an ancient one where someone seems to have been able to get a heights parameter working in a call to facet_grid but it did not work for me. https://kohske.wordpress.com/2010/12/25/adjusting-the-relative-space-of-a-facet-grid/ Thanks again, Eric p.s. Joshua thanks for your suggestions, but I was hoping for a ggplot solution. On Fri, Jan 19, 2018 at 6:33 PM, Charlie Redmon <redmonc at gmail.com> wrote:> 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 reshape2 package. > For example, > > library(reshape2) > plotDF <- melt(SPYdf, > id.vars="Date", # variables to replicate > measure.vars=c("close", "volume"), # variables to > create index from > variable.name="parameter", # name of new variable > for index > value.name="resp") # name of what will be your > response variable > > Now the ggplot2 code: > > library(ggplot2) > ggplot(plotDF, aes(x=Date, y=resp)) + > facet_wrap(~parameter, ncol=1, scales="free") + > geom_line() > > > Hope that does the trick! > > Charlie > > > > On 01/18/2018 02:11 PM, Eric Berger wrote: > >> 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.numeric(SPYxts$SPY.Cl >> ose), >> volume=as.numeric(SPYxts$SPY.Volume)) >> rownames(SPYdf) <- NULL >> >> head(SPYxts) >> head(SPYdf) >> >> # SPY.Close SPY.Volume >> #2007-01-03 141.37 94807600 >> #2007-01-04 141.67 69620600 >> #2007-01-05 140.54 76645300 >> #2007-01-08 141.19 71655000 >> #2007-01-09 141.07 75680100 >> #2007-01-10 141.54 72428000 >> >> # Date close volume >> #1 2007-01-03 141.37 94807600 >> #2 2007-01-04 141.67 69620600 >> #3 2007-01-05 140.54 76645300 >> #4 2007-01-08 141.19 71655000 >> #5 2007-01-09 141.07 75680100 >> #6 2007-01-10 141.54 72428000 >> >> Thanks, >> Eric >> >> >> >> On Thu, Jan 18, 2018 at 8:00 PM, Charlie Redmon <redmonc at gmail.com >> <mailto:redmonc at gmail.com>> wrote: >> >> 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 >> >> -- Charles Redmon >> GRA, Center for Research Methods and Data Analysis >> PhD Student, Department of Linguistics >> University of Kansas >> Lawrence, KS, USA >> >> >> > -- > Charles Redmon > GRA, Center for Research Methods and Data Analysis > PhD Student, Department of Linguistics > University of Kansas > Lawrence, KS, USA > >[[alternative HTML version deleted]]
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. On 01/19/2018 01:39 PM, Eric Berger wrote:> 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 cowplot::plot_grid( > plotlist=pLst, nrow=2, ncol=2 )? That worked fine. > > The one issue? I have is that in the ggplot you suggest, the price and > volume facets are the same size. I would like them to be different sizes > (e.g. the volume facet at the bottom is generally shown smaller than > the facet above it in these types of charts.) > > I tried to find out how to do it but didn't succeed. I found a couple > of relevant discussions (including Hadley writing that he did not > think it was a useful feature. :-() > > https://github.com/tidyverse/ggplot2/issues/566 > > and an ancient one where someone seems to have been able to get a > heights parameter working in a call to facet_grid but it did not work > for me. > https://kohske.wordpress.com/2010/12/25/adjusting-the-relative-space-of-a-facet-grid/ > > Thanks again, > Eric > > p.s. Joshua thanks for your suggestions, but I was hoping for a ggplot > solution. > > > On Fri, Jan 19, 2018 at 6:33 PM, Charlie Redmon <redmonc at gmail.com > <mailto:redmonc at gmail.com>> wrote: > > 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 reshape2 package. > For example, > > library(reshape2) > plotDF <- melt(SPYdf, > ??? ??? ??? ??? ??? ??? id.vars="Date", # variables to replicate > ??? ??? ??? ??? ??? ??? measure.vars=c("close", "volume"), # > variables to create index from > variable.name <http://variable.name>="parameter", # name of new > variable for index > value.name <http://value.name>="resp") # name of what will be your > response variable > > Now the ggplot2 code: > > library(ggplot2) > ggplot(plotDF, aes(x=Date, y=resp)) + > ??? facet_wrap(~parameter, ncol=1, scales="free") + > ??? geom_line() > > > Hope that does the trick! > > Charlie > > > > On 01/18/2018 02:11 PM, Eric Berger wrote: > > 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.numeric(SPYxts$SPY.Close), > ?volume=as.numeric(SPYxts$SPY.Volume)) > rownames(SPYdf) <- NULL > > head(SPYxts) > head(SPYdf) > > #? ? ? ? ? ?SPY.Close SPY.Volume > #2007-01-03? ? 141.37? ?94807600 > #2007-01-04? ? 141.67? ?69620600 > #2007-01-05? ? 140.54? ?76645300 > #2007-01-08? ? 141.19? ?71655000 > #2007-01-09? ? 141.07? ?75680100 <tel:07%C2%A0%20%C2%A075680100> > #2007-01-10? ? 141.54? ?72428000 > > #? ? ? ? Date? close? ?volume > #1 2007-01-03 141.37 94807600 > #2 2007-01-04 141.67 69620600 > #3 2007-01-05 140.54 76645300 > #4 2007-01-08 141.19 71655000 > #5 2007-01-09 141.07 75680100 <tel:07%2075680100> > #6 2007-01-10 141.54 72428000 > > Thanks, > Eric > > > > On Thu, Jan 18, 2018 at 8:00 PM, Charlie Redmon > <redmonc at gmail.com <mailto:redmonc at gmail.com> > <mailto:redmonc at gmail.com <mailto:redmonc at gmail.com>>> wrote: > > ? ? 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 > > ? ? --? ? ?Charles Redmon > ? ? GRA, Center for Research Methods and Data Analysis > ? ? PhD Student, Department of Linguistics > ? ? University of Kansas > ? ? Lawrence, KS, USA > > > > -- > Charles Redmon > GRA, Center for Research Methods and Data Analysis > PhD Student, Department of Linguistics > University of Kansas > Lawrence, KS, USA > >-- Charles Redmon GRA, Center for Research Methods and Data Analysis PhD Student, Department of Linguistics University of Kansas Lawrence, KS, USA [[alternative HTML version deleted]]