Plotting Data - Data Science for Lawyers

R is also great for data visualization. Here are a few simple graphs.

# Let's create the following dataset of numbers of claims per year:

year <- c(2008:2017)

claims <- c(32,45,67,98,112,77,67,98,103,88)

disputes <- data.frame(year, claims)

print(disputes)

##

	Year	Claim
1	2008	32
2	2009	45
3	2010	67
4	2011	98
5	2012	112
6	2013	77
7	2014	67
8	2015	98
9	2016	103
10	2017	88

# We can visualize that data using the plot() function.

plot(disputes)

##

The plot() function, like other functions, in R has default settings.

 # Consult the R documentation to learn how the function can be further customized.

?plot()

For example, it is possible to add axis and graph labels.

plot(disputes$year,disputes$claims, type = "p", xlab="Year", ylab="Claims",
     main = "Claims per Year")

##

We can also plot data as both points and lines (“b”) and change the color of the graph.

plot(disputes$year,disputes$claims, type = "b", col="blue", xlab="Year", ylab="Claims",
     main = "Claims per Year")

##

We can even plot text labels in R using the function text() in combination with plot(). For instance, here we imagine that there were 3 different judges over our timeframe, which in turn had an impact on the data.

judges <- c("Parker","Parker","Parker","Colbert","Colbert","Colbert","Jones","Jones","Jones","Jones")

# Let's add the judge data to our dataframe and print the data again.

disputes <- cbind(disputes, judges)

print(disputes)

##

	Year	Claim	Judges
1	2008	32	Parker
2	2009	45	Parker
3	2010	67	Parker
4	2011	98	Colbert
5	2012	112	Colbert
6	2013	77	Colbert
7	2014	67	Jones
8	2015	98	Jones
9	2016	103	Jones
10	2017	88	Jones

# We can add the name of the judges to the plot with the text() function.

plot(disputes$year,disputes$claims, type = "l", col="blue", xlab="Year", ylab="Claims",
     main = "Claims per Year")

text(disputes$year,disputes$claims, label=disputes$judges)

Last update May 8, 2020.