search for: geom_point

...; qplot(factor(month), balance, data = closed, geom = "boxplot", xlim = > range(closed$month)) There were 13 warnings (use warnings() to see them) > warnings() Warning messages: 1: Removed 1 rows containing missing values (stat_boxplot). 2: Removed 7 rows containing missing values (geom_point). 3: Removed 5 rows containing missing values (geom_point). 4: Removed 8 rows containing missing values (geom_point). 5: Removed 3 rows containing missing values (geom_point). 6: Removed 5 rows containing missing values (geom_point). 7: Removed 2 rows containing missing values (geom_point). 8: Remo...

Dear I use dataset , as called "mpg" This is code ggplot(data=mpg)+ geom_point(mapping = aes(x=displ, y=hwy, colour=year)) But I would like to see only "year of 1999" in this relationship between x and y variables How could I change the code in this direction? I found the following code library(dplyr)year_1999 <- filter(mpg, year=="1999")ggplot(year...

Whats going on here? df<-data.frame(x=1:10,y=1:10) ggplot()+geom_point(data=df,aes(x=x,y=y)) ## this is the normal usage right? ggplot()+geom_point(data=df,aes(x=df[,1],y=df[,2])) ## but I can also feed it column indices ggplot()+geom_point(aes(x=df[,'x'],y=df[,'y'])) ## or column names. ## but if i wrap it in a function... plot.func.one<-func...

I want to draw boxplot where the geom_points are displayed based on "ERBB2.MUT" subset and they should be displayed in the right box (based both on the "ERBB2.2064" field and "ERBB2_Status"). However, given my command I currently only see "red" points corresponding to "MUT" subset in one str...

...c(myDiamonds[["clarity"]]) # Calculate medians medians <- ddply( myDiamonds, .(cut), summarize, med=median(clarity, na.rm=TRUE) ) # Works myPlot <- qplot( factor(clarity), data=myDiamonds, fill=cut, geom="bar", position="dodge" ) myPlot + geom_point( data=medians, aes(x=med,shape=cut), y=0, size=2.5, ) # Doesn't work - I want density rather than count myPlot <-qplot( factor(clarity), y=..count../sum(..count..), data=myDiamonds, fill=cut, geom="bar", position="dodge" ) myPlot + geom_point( da...

Hi I am plotting line chart using ggplot and want to use geom_line and geom_point simultaneously. I get the plot but now I have two legends. None of the legend is representing the true values. I need the legend with shape and color both. Thanks > con = textConnection("inputs var1 var2 var3+ 100 10 5 2+ 1000 20 10 4+ 5000 30 15 8+ 10000 40 20 16+ 30000 50 25 32"...

...c values of the log10_P to the point size in the graph. Your help highly appreciated, Regards, Greg p <- ggplot(mydata, aes(x = X, y = log10_P)) + theme_bw() +theme(panel.border=element_blank()) + theme(legend.position="top", axis.text=element_text(size = 8)) (p1 <- p + geom_point(aes(color = Traits) [[alternative HTML version deleted]]

...be as close as 1, v2 to be as close as 0. Thanks very much. DF ID v1 v2 v3 1 0.8 0.1 0.7 2 0.85 0.3 0.6 3 0.9 0.21 0.7 4 0.95 0.22 0.8 5 0.9 0.3 0.7 6 0.8 0.4 0.76 7 0.9 0.3 0.77 ... fig1 = ggplot(data=DF, aes(x=v1,y=v2))+ geom_point()+ theme_bw()+ xlab('Variable 1')+ ylab('Variable 2') print(fig1) fig2 = ggplot(data=DF, aes(x=v1,y=v3)+ geom_point()+ theme_bw()+ xlab('Variable 1')+ ylab('Variable 3') print(fig2) [[alternative HTML version deleted]]

You could add size = log10_P to the aes() inside geom_point(). Untested code below. See also http://ggplot2.tidyverse.org/reference/geom_point.html ggplot(mydata, aes(x = X, y = log10_P)) + theme_bw() + theme(panel.border=element_blank(), legend.position="top", axis.text=element_text(size = 8)) + geom_point(aes(color = Traits, size = log...

...ints you can set the colour aesthetic. The ID is numeric so ggplot applies a colour scale. If we cast ID to a factor we get the appropriate colouring. test_df <- data.frame(ID = 1:20, v1 = rnorm(20), v2 = rnorm(20), v3 = rnorm(20)) ggplot(data=test_df, aes(x=v1,y=v2, colour = as.factor(ID))) + geom_point()+ theme_bw()+ xlab('Variable 1')+ ylab('Variable 2') How to choose a number of samples from the dataset you can use the subset function to select by some variable: sub_test_df1 <- subset(test_df, ID < 5) ggplot(data=sub_test_df1, aes(x=v1,y=v2, colour = as.factor(ID))) +...

...points   # Plot the shapefile and overlayed the points over it p <- ggplot(manuel_merged, aes(long,lat,group=group)) +   geom_polygon(aes(data=manuel_merged,fill=Area_Influ)) +   geom_path(color="white") + theme_bw() # remove this if you don't want black and white background   p + geom_point(data=manuel_points,aes(size=ACE,colour=ACE,group=NULL)) +   scale_size(name = "Número\nde\nespecies", breaks = c(2, 4, 6, 8, 10, 12, 14, 16, 18, 20)) +  scale_colour_gradientn(name = 'Número\nde\nespecies',  colours = rainbow(6), breaks = c(2, 4, 6, 8, 10, 12, 14, 16, 18, 20))+...

For example, prepare like this > df.0 <- data.frame(x = 0, y = 0, note = "1") > df.1 <- subset(df.0, note == "1") > df.2 <- subset(df.0, note == "2") Then a call to > ggplot() + aes(x = x, y = y) + > geom_point(data = df.1) + geom_point(data = df.2) produces the error > Error in eval(expr, envir, enclos) : object 'x' not found And a call to > ggplot(df.1, aes(x = x, y = y, shape = 4)) + > geom_point() + geom_point(aes(shape = 1), df.2) plots both a cross (shape = 4) and circle (shape =...

Dear All, I have this script: dat <- data.frame(Month = hstat$Date,C_avg = hstat$C.avg,C_stdev = hstat$C.stdev) ggplot(data = dat, aes(x = Month, y = C_avg, ymin = C_avg - C_stdev, ymax = C_avg + C_stdev)) + geom_point() + geom_line() + geom_errorbar() dat <- data.frame(Month = hstat$Date,K_avg = hstat$K.avg,K_stdev = hstat$K.stdev) ggplot(data = dat, aes(x = Month, y = K_avg, ymin = K_avg - K_stdev, ymax = K_avg + K_stdev)) + geom_point() + geom_line() + geom_errorbar() dat <- data.frame(Mo...

...115 FALSE FALSE 5 2023-10-13 08:44 136 FALSE TRUE 6 2023-10-12 08:55 122 FALSE TRUE 7 2023-10-11 07:55 150 TRUE TRUE > This gets me most of the way to what I want: ggplot(data = b2, aes(x = Date, y = bg)) + geom_line() + geom_point(data = filter(b2, missed_meds), shape = 20, size = 3) + geom_point(data = filter(b2, no_exercise), shape = 4, size = 3) + geom_point(aes(x = Date, y = bg, shape = missed_meds), alpha = 0) + #Invisible point layer for...

...1L, 373872L, 71450L, 53338L, 5660L)), .Names = c("Name", "Pcode", "Area"), class = "data.frame", row.names = c(NA, -13L)) library(ggplot2) p <- ggplot(provs, aes(x = 0, xend = Area, y = Pcode, yend = Pcode)) # commmand below is on one line pa <- p + geom_point(aes(Area, Pcode)) + geom_segment() + xlab("Area") pa pa1 <- p + geom_point(aes(Area, Pcode)) + geom_segment() + xlab("Area") # Error in +xlab("Area") : invalid argument to unary operator # commmand below is on one line pb <- p + geom_point(aes(Area...

...1 4.443696 1 1 4.588243 2 1 4.650505 0 2 4.296608 1 2 4.826036 2 2 4.765386"),header=TRUE); closeAllConnections(); I can form two plots, scatter and lines, as follows: p <- ggplot(mydata, aes(x=Est, y=Tri)) p + geom_point(aes(colour=factor(Group),shape=factor(Group))) and p+ geom_smooth(aes(group=factor(Group),color=factor(Group)),method=lm,se=F). However, I am unable to have the plots together. I obtain the following error: > p + geom_point(aes(colour=factor(Group),shape=factor(Group)))+geom_smooth(aes(grou...

...by two factors) and I want to overlay the original observations and the following code does almost what I want: library(ggplot) ddf <- data.frame(x=factor(rep(LETTERS[1:4], each=30)), y = runif(120,0,10), grp = factor(rep(rep(1:3, 10), 4))) ggplot(ddf, aes(x, y, colour=grp)) + geom_boxplot() + geom_point() Yet the position of the points and the position of the boxes on the x-axis is not the same. I would like that the points are shifted accordingly, such that they line up with the boxplots. I tried position_dodge: ggplot(ddf, aes(x, y, colour=grp)) + geom_boxplot() + geom_point(aes(ymax=max(y)),...

...le to find the MatLab equivalent of "MarkerEdgeColor" so I've been working on trying to overlay two plots of the same points, one plotted with fills and the other plotted with edge outlines (here is my conceptual code): pfill <- ggplot(data=DF, aes(x=X, y=Y)) + geom_point(aes(colour=TRT),size=4) + scale_colour_grey(end=0.8) + theme_bw pedge <- ggplot(data=DF, aes(x=X, y=Y)) + geom_point(aes(colour=TRT),size=4) + scale_colour_grey(end=0.8) + scale_shape(solid=FALSE) + theme_bw However,...

...re's my attempts. You can see some of the things I've tried in the commented out sections: weights %>% group_by(year(Date)) %>% summarize( m_K = mean(K, na.rm = TRUE), m_J = mean(J, na.rm = TRUE), ) %>% ggplot(aes(x = `year(Date)`)) + geom_point(aes(y = m_K, color = "red")) + geom_smooth(aes(y = m_K, color = "red")) + geom_point(aes(y = m_J, color = "blue")) + geom_smooth(aes(y = m_J, color = "blue")) + guides(size = "legend", shape = "legend")...

...;, "A", "B", "B" ) ) bar <- data.frame ( x = 1:4 + 1 , y = 4:1 + 1, membership = rep ( "C", 4 ) ) # This works, and produces a sensible (unified!) legend: foo.gg <- ggplot ( mapping = aes ( x = x, y = y , colour = membership ) ) foo.gg <- foo.gg + geom_point(data = foo) foobar.gg <- foo.gg + geom_point ( data = bar ) # works fine, creates a unified scale showing "membership" foobar.gg # This does not work: booboo.gg <- foo.gg + geom_point ( data = bar, colour = "black" ) # so far, so good, but... booboo.gg # it will not l...