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R provides powerful ways to visualize data.

In my use case, I needed to represent mean salaries vs titles or mean salaries vs companies.

I used the “barplot” initially to represent a bargraph. As I explored the R language further, I realized that the ggplot is used a lot for data visualization. I wondered why there was a need for two functions essentially to perform the same operation.

The data is of the format:

Title Mean_Salary
Accountants 83000.00
Actuaries 117000.00
Art Directors 108000.00
Biomedical Engineers 98000.00
Chief Executives 145000.00
Computer Programmers 120000.00
…. ….
…. ….
…. ….

I wanted to sort the above data based on the descending value of the Salary and plot a bargraph of the top 10 Salaries.

I sorted the data frame to be the decreasing order of the Mean_Salary, this way I would get the top 10 salaries as the top 10 rows of the data frame.


The bar plot was constructed using the following command.

colors<- c("red", "yellow", "green", "violet", 
		"orange", "blue", "pink", "cyan", "darkblue", "purple")

		main="Top Salary by Title",

In the barplot, the first value “height” determines the y-value and the names.arg determines the x-value. For purpose of similar looking graphs between barplot and ggplot, I have added the colors vector, which will give a colorful bar graph with 10 colored bars.

By doing this I got the following graph:


There was one additional step I did for the ggplot. In ggplot the order of the bars is determined by the order of the factors, so I further ordered the dataframe using the following command.


I used the following command to construct a ggplot:

ggplot(sort.aggr_datset_ord[1:10,], aes(Title, Mean_Salary, fill=Title))
		+geom_bar(position="dodge", stat="identity", width=0.75)

The first argument is the data frame for the plot is done. The “aes” determines the x value and the y value, in this case, Title and Mean_Salary being the x and y respectively. The Title was used for “fill”, which made sure that each of the bars got a different color.

Since we are constructing a bar chart, used the geom_bar with stat=”identity”. This is used when we want the height of the bar to represent the value of the data(and not the count). I did not want the legend in this case(as each color is representative of the title), so hid it using the “theme”.

By doing this I got the following graph:


Both the above commands solve the same purpose, creating a barchart for the title vs Salary. However, while constructing, ggplot felt like a more flexible option, as it gave a lot of flexibility around the aesthetics of the plot, the colors, the labels, the positioning etc.

For a rudimentary and quick graph during exploratory phase of analysis, barplot command seems to be a good option, however if the purpose of the graph is a better visualization, then ggplot provides more flexibility and options.

Fork the code at Github