ggplot(df, aes(x=team, y=points)) + geom_boxplot() + geom_text(aes(label=outlier), na.rm=TRUE, hjust=-.5) Please take note that we may alternatively classify these outliers using a different variable. To label the outliers based on the player name instead, we could, for instance,...
pie = ggplot(df, aes(x="", y=share, fill=brand)) + geom_bar(stat="identity", width=1) # Convert to pie (polar coordinates) and add labels pie = pie + coord_polar("y", start=0) + geom_text(aes(label = paste0(round(value*100), "%")), position = position_stack(vjust = ...
Do you want to make stunning data visualizations? Now you can — Here’s a complete guide to an amazing ggplot boxplot in R.
the ggplot2 functionscale_y_continuous(expand = expansion(mult = c(0, 0.1)))can be used toadd more spaces between labels and the plot top border. The optionmult = c(0, 0.1)indicates that 0% and 10% spaces are respectively added at the bottom and the top...
> boxplot.with.outlier.label(y~x2*x1, lab_y) Error in text.default(temp_x + 0.19, temp_y_new, current_label, col = label.col) : zero length ‘labels’ Thanks Jon, I found the bug and fixed it (the bug was introduced after the major extension introduced to deal with cases of ...
Histograms mitigate this issue by grouping several data points into logical ranges (known as bins) and allowing them to be visualized. In this tutorial, we will cover how to implement histograms in Python using the Plotly data visualization library. We will also touch on different ways to ...
for other functions to use, and should not be changed. If you prefer the full name of a company to be displayed instead of the short name, you can do so by changing the value of the keylabeltoMicrosoft. For the sake of simplicity, we will use the same value for the key...
There doesn’t seem to be a simple function in R for creating bihistograms, butStrictlyStatsuggests overlaying two histograms on top of each other, for the same effect. For the code using either ggplot or base graphics, seethis article the R-Bloggers site. You can also find an online calc...
can explore more powerful packages that make it easier to build more interesting and useful visualizations. A very popular and easy-to-use library for plotting in R is calledggplot2. Below we create an interesting view of the distributions of prices based on the number of bedrooms in the ...
GGPlot2 Essentials for Great Data Visualization in R by A. Kassambara (Datanovia) Network Analysis and Visualization in R by A. Kassambara (Datanovia) Practical Statistics in R for Comparing Groups: Numerical Variables by A. Kassambara (Datanovia) Inter-Rater Reliability Essen...