Launch RStudio as described here: Running RStudio and setting up your working directory
Prepare your data as described here: Best practices for preparing your data and save it in an external .txt tab or .csv files
Import your data into R as described here: Fast reading of data from txt|csv files into R: readr package.
Here, we’ll use the R built-in VADeaths data set.
Data set: VADeaths
# Data set VADeaths
## Rural Male Rural Female Urban Male Urban Female ## 50-54 11.7 8.7 15.4 8.4 ## 55-59 18.1 11.7 24.3 13.6 ## 60-64 26.9 20.3 37.0 19.3 ## 65-69 41.0 30.9 54.6 35.1 ## 70-74 66.0 54.3 71.1 50.0
# Subset x <- VADeaths[1:3, "Rural Male"] x
## 50-54 55-59 60-64 ## 11.7 18.1 26.9
Basic bar plots
# Bar plot of one variable barplot(x) # Horizontal bar plot barplot(x, horiz = TRUE)
Change group names
barplot(x, names.arg = c("A", "B", "C"))
# Change border and fill color using one single color barplot(x, col = "white", border = "steelblue") # Change the color of border. # Use different colors for each group barplot(x, col = "white", border = c("#999999", "#E69F00", "#56B4E9")) # Change fill color : single color barplot(x, col = "steelblue") # Change fill color: multiple colors barplot(x, col = c("#999999", "#E69F00", "#56B4E9"))
Change main title and axis labels
# Change axis titles # Change color (col = "gray") and remove frame barplot(x, main = "Death Rates in Virginia", xlab = "Age", ylab = "Rate")
Stacked bar plots
barplot(VADeaths, col = c("lightblue", "mistyrose", "lightcyan", "lavender", "cornsilk"), legend = rownames(VADeaths))
Grouped bar plots
barplot(VADeaths, col = c("lightblue", "mistyrose", "lightcyan", "lavender", "cornsilk"), legend = rownames(VADeaths), beside = TRUE)
It’s also possible to add legends to a plot using the function legend() as follow.
# Define a set of colors my_colors <- c("lightblue", "mistyrose", "lightcyan", "lavender", "cornsilk") # Bar plot barplot(VADeaths, col = my_colors, beside = TRUE) # Add legend legend("topleft", legend = rownames(VADeaths), fill = my_colors, box.lty = 0, cex = 0.8)
- box.lty = 0: Remove the box around the legend
- cex = 0.8: legend text size
This analysis has been performed using R statistical software (ver. 3.2.4).
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