ggplot2

There is nothing wrong that I can see. Your code works. Some times such errors arise due to not flowing the ggplot expression properly. Try it like this: ggplot(train, aes(x= Item_Visibility, y = Item_Outlet_Sales)) + geom_point(size = 2.5, color=”navy”) + xlab(“Item Visibility”) + ylab(“Item Outlet Sales”) + ggtitle(“Item Visibility vs Item Outlet Sales”) Assuming you … Read more

Next time please include the head this can be done using head(Store_sales) ProductID category sales product 1 101 Bakery 9468 White bread 2 102 Personal Care 9390 Everday Female deodorant 3 103 Cereal 9372 Weetabix 4 104 Produce 9276 Apple 5 105 Meat 9268 Chicken Breasts 6 106 Bakery 9252 Pankcakes I reproduced relevant fields … Read more

ggplot2 is my favourite R package, so here is how I would solve this: df = data.frame(difficulty = 2 + (runif(200) * 6), ID = rep(c(“point”, “bubble”), each = 100)) df$movement = rep(c(1.2, 1.4), each = 100) * df$difficulty + (runif(200) / 5) library(ggplot2) theme_set(theme_bw()) ggplot(df, aes(x = difficulty, y = movement, color = ID, … Read more

The example that you give is for plotting maps, usually starting from a shapefile. In that case the data contains a column named group which is used by geom_polygon to ensure that boundaries and shapes are connected correctly. If the column were named something else, e.g. xxx, then you’d use group = xxx. This question … Read more

Have a look at scale_color_manual, the examples should be sufficient. The general structure of tweaking any scale in ggplot2 is to use the appropriate scale function: scale_{aes_name}_{scale_type}, where aes_name can be color, x, or any other aeshetic, and where scale_type can be continuous, discrete, manual, etc. Googling for ggplot2 legend position led me to this … Read more

you should not use all variables as id.vars try this code dfm <- melt(df, id.vars=c(“iteration”)) What do you really need to plot?? What is your x and y axis? line plot or point? As far as i understood this should work. ggplot(dfm,aes(iterartion,value,colour=variable))+geom_point() solved how to plot with ggplot?

I really recommend taking a look at the documentation for geom_bar() (as well as the basic ggplot2 documentation), but this might help get you started. You can add an outline to your bars by using colour = “black”, and you can change the axis labels by using labs(). We use the arguments within theme() to … Read more

Please have a look at how to ask questions on SO and how to provide data/examples. It makes it a lot easier for people to help you if we have all the information ready to go. The data I’ve produced a table using some of your data: library(tidyverse) df <- tribble(~absent, ~present, ~total, ~session, 15,8,3,’s1′, … Read more

d <- read.table(text=readClipboard(), header=TRUE, stringsAsFactors = T, na.strings=”U”) df <- melt(d, id.var=”date”) ggplot(aes(x=date, y=value), data = df) + geom_bar(aes(fill = variable), stat=”identity”, position = ‘dodge’) or ggplot(aes(x=factor(date), y=value), data = df) + geom_bar(stat=”identity”, position = ‘dodge’) + facet_grid(variable~., scales=”free_y”, drop = F) + theme(axis.text.x = element_text(angle = 45, vjust = 1.1, hjust = 1.05)) 4 … Read more