search for: coord_cartesian

...;#CC79A7") ## this is the colour-blind palette set.seed(020823) df<-as.data.frame(cbind(rep(1980:1991,2),c(10*runif(12),10*runif(12)),c(rep(1,12),rep(2,12)))) colnames(df)<-c("Year","Flow","Stat") df ggplot(df,aes(Year,Flow,group=Stat,colour=Stat))+ coord_cartesian(ylim = c(0, 10)) + geom_line()+ geom_point() ## this works ## BUT: ## code 2 col.2<-cb8[4:5] ggplot(df,aes(Year,Flow,group=Stat,colour=Stat))+ coord_cartesian(ylim = c(0, 10)) + geom_line()+ geom_point()+ scale_color_manual(values =cb8[4:5])+ theme_bw() ## this gives error...

Hi, When I zoom into a graph created in ggplot2 with the coord_cartesian(ylim=c(0,5)) option, I have no values labelled on my y-axis. For this graph ggplot2 only puts labels the y-axis at intervals of 10 (i.e. 0, 10, 20, ...). However, the major portion of the graph I am interested in is located between the values of 0 and 5 on the y-axis (thus why I am zoooming). How c...

...ng the same way as the qplot above: ggplot(data = somdf, mapping = aes(x = pixX, y = pixY)) + layer(data = somdf, geom = "tile", fill=rgb) + scale_y_continuous(name=" ",breaks=" ") + scale_x_continuous(name=" ",breaks=" ") + scale_fill_identity() + coord_cartesian() + opts(aspect.ratio = .75) + facet_grid(unitX ~ unitY,margins=FALSE) The result is a plot where all tiles are filled with grey50, and not the data values. I've also tried this variation with the same results: ggplot(data = somdf, mapping = aes(x = pixX, y = pixY)) + geom_tile(data = somdf,...

...me,y=data,colour=group1))+facet_wrap(~id,ncol=1)+theme_bw() p1 <- p1 + xlab("Julian Day (2008-2009)")+ylab(expression(Temperature~(degree*C)))+ element_blank()+ theme( legend.position="right", legend.direction="vertical", legend.title = element_blank()) +coord_cartesian(xlim=c(250,550))+coord_cartesian(ylim=c(0,40))+scale_x_continuous(breaks=c(250,300,350,400,450,500,550),labels=c("250","300","350","34","84","134","184")) p1 ### This is how it should look like (though shows annotations for all...

Hello, i use ggplot to plot some measures including CIs as horizontal errorbars. I get an error when the scale limits are narrower than the boundaries of the error bar and hence the CIs are not plotted. library(ggplot2) df <- data.frame(resp=c(1,2), k=c(1,2), se=c(1,2)) ggplot(df, aes(resp,y=k)) + geom_point() + geom_errorbarh(aes(xmax = resp + se, xmin = resp - se)) +

...fg0 <- ggplot(aes(x=Grade,y=Math,colour=RiskStatic45678),data=math.f) mfg1 <- mfg0 + geom_smooth(method="lm", formula=y ~ ns(x,2),size=1) + geom_smooth(aes(y=nalt.math,color="NALT"),size=1,data=nalt) + scale_colour_brewer("Risk Status", pal="Set1") + coord_cartesian(ylim = c(175, 245)) mfg1 And when I specify that, the only value that shows up on the Y-axis is a '200'. How can I manually specify that I want 180, 200, 220, and 240 to show up? Also please cc me on the email as I am a digest subscriber. Chris

Dear Colleagues, In the following simple ggplot2 code: -------------------------------- m <- ggplot(d.fig, aes(time, prob)) m + stat_summary(fun.data = "median_hilow", conf.int = .95, geom = "smooth") + facet_wrap(~ Cohort, nrow=1) + coord_cartesian(ylim = c(0, .03)) -------------------------------- Is there a way to replace the y-axis label from "prob" to "Predicted Probability" and replace the x-axis label from "time" to "Time Elapsed"? Many thanks. Best, Shige

Dear ggplot2 users, is there an easy/elegant way to suppress zero count bars in histograms with logarithmic y axis ? One (made up) example would be qplot(exp(rnorm(1000))) + geom_histogram(colour = "cornsilk", fill = "darkblue") + scale_x_sqrt() + scale_y_log10() Thanks! Markus [[alternative HTML version deleted]]

...plot( (subsetxx ) )+ geom_point(aes(x,y,colour=cut(Powermap,c(0,-1,-10,-20,-30,-40,-50,-60,-70,-80,-90,-100,-110))))+ geom_text(aes(x,y,color=cut(Powermap, c(0,-1,-10,-20,-30,-40,-50,-60,-70,-80,-90,-100,-110)), label=round(Powermap,3)),vjust=1,legend=FALSE)+labs(colour="Powermap")+ coord_cartesian(xlim = c(1, dimx),ylim = c(1, dimy))

Dear All, I am plotting a graph in ggplot, I would like to magnify the values between 0-1 without losing data in the higher range. How can I do that? neither scale_y_continous nor coord_cartesian works. Thank you ?zg?l Universit? Libre de Bruxelles

Dear All, I am trying to graph a simple scatter plot where the x axis is year and the y axis is a percentage (percentage of infant death). Instead of plotting the raw data, I want to plot summary statistics such as mean and median. Here is the problem: the value range of y is between 0 and 1, but since infant death is a rare event, the mean and median is very low (something like 5%), which shows

...er Desjardins" <cddesjardins at gmail.com>, > <r-help at r-project.org> > Message-ID: > <2E9C414912813E4EB981326983E0A10406653ACE at inboexch.inbo.be> > Content-Type: text/plain; charset="us-ascii" > > Dear Chris, > > Changing > > coord_cartesian(ylim = c(0, 5)) > > into > > coord_cartesian() + scale_y_continuous(limits = c(0, 5)) > > That should solve your problem. > > HTH, > > Thierry > > ------------------------------------------------------------------------ > ---- > ir. Thierry Onkelinx >...

...hacer mi trabajo, algo similar a esto, pero adaptado a mi región. Si te fijas en las lineas 141-161, esta esto: ## Convert the base map into a ggplot object ## All added Cartesian coordinates to enable more geom options later on map.ggmap <- ggmap(map.base, extend = "panel") + coord_cartesian() ## Display a message cat("Creating a ggplot object ...\n") ## Various display settings for the ggplot object main.plot <- map.ggmap + ## Create a density plot ## based on the ggmap's crime data example stat_density2d(aes(x = longitude,...

...;); require("scales")} small.sample.dat <- schnabel.comp small.sample <- ggplot(data = small.sample.dat, mapping = aes(x = sample, y = pop.estimate)) + geom_point(size = 2) + geom_line() + geom_hline(yintercept = N, col = "red", lwd = 1) + coord_cartesian(xlim = c(0:100), ylim = c(300:500)) + scale_x_continuous(breaks = pretty_breaks(11)) + scale_y_continuous(breaks = pretty_breaks(11)) + labs(x = "\nSample", y = "Population estimate\n", title = "Sample sizes are between 5% and 15%\nof the population") +...

Hi all-- I am in the process of helping colleagues write up a ms in which we fit zero-inflated Poisson models. I would prefer plotting the rate ratios and 95% CI (as I've found Gelman and others convincing about plotting tables...), but our journals usually like the numbers themselves. Thus, I'm looking at a recent JAMA article in which both numbers and dotplot of RR and 95% CI are

Hi, This is probably an easy one, but I am new to ggplot2 and cannot find an answer online. I am bar plotting values of 10 groups. These values are all within a 90-100 range, so I would like leave out the area of the bars below 90. If I say "graph + scale_y_continuous(limit=c(90, 100))", it does limit the axis but the bars disappear completely. Any solution here? Thanks a lot!

...-------------------------------------------------------------------- # Example adapted from the help page of "geom_segment" library(ggplot2) library(grid) d <- data.frame(x1=-135.3, x2=-158.3, y1=37.2, y2=45.2) p <- ggplot(seals, aes(x = long, y = lat)) p1 <- ggplot() + coord_cartesian() + geom_rect(data=d, mapping=aes(xmin=x1, xmax=x2, ymin=y1, ymax=y2), fill="red", color="red", alpha=0.5) + geom_segment(data=seals, aes(x = long, y = lat, xend = long + delta_long, yend = lat + delta_lat), arrow = arrow(length = unit(0.2,"cm"))) p2 <-...

Hi, I am using ggplot2 to with the following code: gmathk2 <- qplot(time,math,colour=Kids,data=kids.ach.lm.k5,geom="smooth",method="lm",formula=y~ns(x,1)) + opts(title="Smoother Plot: Math K-5") + xlab("Time") + ylab("Math") + scale_colour_brewer(pal="Set1"); gmathk2 This plots all the smoother for all the x values. What I'd like

...> small.sample.dat <- schnabel.comp > > small.sample <- ggplot(data = small.sample.dat, > mapping = aes(x = sample, y = pop.estimate)) + > geom_point(size = 2) + > geom_line() + > geom_hline(yintercept = N, col = "red", lwd = 1) + > coord_cartesian(xlim = c(0:100), ylim = c(300:500)) + > scale_x_continuous(breaks = pretty_breaks(11)) + > scale_y_continuous(breaks = pretty_breaks(11)) + > labs(x = "\nSample", y = "Population estimate\n", > title = "Sample sizes are between 5% and 15%\nof the popula...

...help at r-project.org>, Ben Bolker <bbolker at gmail.com> Subject: Re: [R] ggplot2: Get the regression line with 95% confidence bands Message-ID: <352cddfd-6db4-4715-bad1-2f5690d8dc29 at atsu.edu> Content-Type: text/plain; charset="utf-8"; Format="flowed" coord_cartesian also seems to work for y, and including the breaks = . How about: df=data.frame(year= c(2012,2015,2018,2022), score=c(495,493, 495, 474)) ggplot(df, aes(x = year, y = score)) + geom_point() + geom_smooth(method = "lm", formula = y ~ x) + labs(title = "Standa...