similar to: ggplot2 plot with symbols and then add line

I am trying to figure out how to use ggplot2. I would like to do the below with ggplot, but I can not figure out how. The data provided is a subset of a much larger data set, but these data are the data necessary to make the plot. I think I would rather have the colors become symbols, and I do know how to do that in lattice, but here is a quick and dirty version. thanks r

Hadley, I don't know if I am doing something wrong or if it is ggplot please see the two graphs at the bottom of the page (code). melt.nut <- (structure(list(RiverMile = c(119L, 119L, 119L, 119L, 119L, 119L, 119L, 119L, 119L, 148L, 148L, 148L, 148L, 148L, 148L, 148L, 179L, 179L, 179L, 179L, 179L, 179L, 179L, 185L, 185L, 185L, 185L, 185L, 185L, 185L, 190L, 190L, 190L, 190L, 190L, 190L,

I would like to use the data below where the plots are close to what I want. Instead of color I would like to use different symbols, and have the symbols in the legend match the graphs. I am also going to add a regression line to these I know about the type="r" (which is fine for these particular graphs) argument, but it fits the subsets instead of the entire data set-- should I use a

merge can only merge two objects at a time- I would like to merge more than two objects at a time. s.d <- structure(list(RiverMile = c(202L, 198L, 190L, 185L, 179L, 148L, 119L, 61L)), .Names = "RiverMile", row.names = c(NA, -8L), class = "data.frame") #s.d is all of the river miles that can occur in all of the data frames that I want to put together feb06 <-

taxa <- (structure(list(Date = structure(c(4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), .Label = c("2006/04", "2006/05", "2006/07", "2006/10", "2006/12", "2007/02", "2007/04", "2007/06", "2007/08", "2007/10", "2007/12", "2008/01"), class =

This is an example of two months of data from a twenty four month data set that I would like to apply this too. These data are subsets of the same stations throught time, but differing ones were included on different sampling dates. I would like to subset these data and then put them together as a big matrix with the by column being RiverMile. What is the easiest way to proceed as this is a

Hi, Try this: #mat1 is the data res<-do.call(cbind,lapply(seq_len(nrow(mat1)),function(i) {new1<-do.call(rbind,lapply(seq_len(nrow(mat1[-i,])),function(j) {x1<-rbind(mat1[i,],mat1[j,]); x2<-(abs(x1[1,1]-x1[2,1])*abs(x1[1,5]-x1[2,5]))+(abs(x1[1,2]-x1[2,2])*abs(x1[1,6]-x1[2,6]))+(abs(x1[1,3]-x1[2,3])*abs(x1[1,7]-x1[2,7]))+(abs(x1[1,4]-x1[2,4])*abs(x1[1,8]-x1[2,8]))}));new1}))

Hi R-Help, data at bottom I've been struggling with a problem where I need to order based on 1) the Frequency "Freq" and 2) keeping each group of 3 of the same type together "Var2" but I want across all groups it to go "high to low" based on the earn factor. Thank you! structure(list(Var1 = structure(c(1L, 3L, 2L, 1L, 2L, 3L, 1L, 3L, 2L, 3L, 1L, 2L, 3L, 1L,

I would like to reformat this data frame into something that I can produce some descriptive statistics. I have been playing around with the reshape package and maybe this is not the best way to proceed. I would like to use RiverMile and constituent as the grouping variables to get the summary statistics: 198a 198b mean mean sd sd ... ... etc. for all of these. I have tried

I am trying to investigate the interaction term in the below. The paradigm in aquatic systems is that algal production is either nitrogen (TIN) or Phosphorus limited, and I am trying to investigate this- what is the best way to go about investigating the interaction term. I have some thoughts on the above, but I will withhold them to see what others think. Thanks for your help. d <-

I can't get my simultaneous equations to work using system fit. Please help. #Reproducible script Empdata<- read.csv("/Users/ngwinuiazenui/Documents/UPLOADemp.csv") View(Empdata) str(Empdata) Empdata$gnipc<-as.numeric(Empdata$gnipc) install.packages("systemfit") library("systemfit") pdata <- plm.data(Empdata,

The aggregate function for some reason will now work for me. The error I'm getting is: "Error in sort.list(y) : 'x' must be atomic for 'sort.list' Have you called 'sort' on a list?" agPriceList=aggregate(PriceList$Size, list(PriceList$bandNum),sum) *Price list dataframe:* dput(PriceList) structure(list(Price = c(0, 8.18, 8.27, 10.42, 10.5, 10.6, 11.13,

Dear friends, I have a weekly time series which starts on Jan 4th, 2003 and ends on december 31st, 2016. I set up my ts object as follows: MyTseries <- ts(mydataset, start=2003, end=2016, frequency=52) MyModel <- auto.arima(MyTseries, d=1, D=1) MyModelForecast <- forecast (MyModel, h=12) Since my last observation was on december 31st, 2016 I expected my forecast date to start on

Hadley et al., I was using the cast function to reshape some data (aggregate a melted data frame) and I did not put in the fill and for the most part the values that came out were fine, but there were value great than an order of magnitude from the actual value. When I put in the fill argument everything is okay. I don't provide a reproducible example because the data set is to large to post

> On Dec 6, 2017, at 5:07 AM, Paul Bernal <paulbernal07 at gmail.com> wrote: > > Dear friends, > > I have a weekly time series which starts on Jan 4th, 2003 and ends on > december 31st, 2016. > > I set up my ts object as follows: > > MyTseries <- ts(mydataset, start=2003, end=2016, frequency=52) > > MyModel <- auto.arima(MyTseries, d=1, D=1)

Thank you very much David. As a matter of fact, I solved it by doing the following: MyTimeSeriesObj <- ts(MyData, freq=365.25/7, start=decimal_date(mdy("01-04-2003"))) After doing that adjustment, my forecasts dates started from 2017 on. Cheers, Paul 2017-12-06 12:03 GMT-05:00 David Winsemius <dwinsemius at comcast.net>: > > > On Dec 6, 2017, at 5:07 AM, Paul

f <- (structure(list(X = structure(96:97, .Label = c("119DAmm", "119DN", "119DNN", "119DO", "119DOC", "119Flow", "119Nit", "119ON", "119OPhos", "119OrgP", "119Phos", "119TKN", "119TOC", "148DAmm", "148DN", "148DNN", "148DO",

Hi there, I am having a little problem with combining three scale_manual commands in a facet plot. I am not able to combine the three different characteristics, instead ending up with three different descriptions next to the graph for the same geom. I would like to see two separate labels (not three); one describing lines 1-7 and the other 8-14. For each of the treatments (A-B) I want a

Sadly you failed to set your email program to send plain text and the data is corrupted at my end. I also think you need to reduce the size of the data set... the intent here is to increase your understanding, not debug your particular analysis. I will say that I am having a very challenging time understanding what you are trying to accomplish though. What are the equations that you think need

OK, Let's try this again! Here is the reproducible script; it is long because I had to copy the panel dataset here. My question is related to systemfit; I don't know how to get the result for the entire panel. #Reproducible script Empdata<- read.csv("/Users/ngwinuiazenui/Documents/UPLOADemp.csv") View(Empdata) install.packages("systemfit")