Line graphs show change over an ordered axis, usually time; slope is the message.
Unsorted or gappy x values draw zigzag lines; sort by x and handle missing periods explicitly.
In this chapter, we will learn to:
We will use a data set related to GDP growth rate. You can download it from here. It contains GDP (Gross Domestic Product) growth data for the BRICS (Brazil, Russia, India, China, South Africa) for the years 2000 to 2005.
gdp <- readr::read_csv('https://raw.githubusercontent.com/rsquaredacademy/datasets/master/gdp.csv')
gdp# A tibble: 6 × 6
...1 X year growth india china
<dbl> <dbl> <date> <dbl> <dbl> <dbl>
1 1 1 2000-01-01 6 5 8
2 2 2 2001-01-01 9 9 5
3 3 3 2002-01-01 8 8 6
4 4 4 2003-01-01 9 8 8
5 5 5 2004-01-01 9 5 9
6 6 6 2005-01-01 8 7 8To create a line chart, use geom_line(). In the below example, we examine the GDP growth rate trend of India for the years 2000 to 2005.
ggplot(gdp, aes(year, india)) +
geom_line()
To modify the color of the line, use the color argument and supply it a valid color name. In the below example, we modify the color of the line to 'blue'. Remember that the color argument should be outside aes().
ggplot(gdp, aes(year, india)) +
geom_line(color = 'blue')
The line type can be modified using the linetype argument. It can take 7 different values. You can specify the line type either using numbers or words as shown below:
Let us modify the line type to dashed style by supplying the value 2 to the linetype argument.
ggplot(gdp, aes(year, india)) +
geom_line(linetype = 2)
The above example can be recreated by supplying the value 'dashed' instead of 2.
ggplot(gdp, aes(year, india)) +
geom_line(linetype = 'dashed')
The width of the line can be modified using the linewidth argument. It can take any value above 0 as input.
ggplot(gdp, aes(year, india)) +
geom_line(linewidth = 2)
Now let us map the aesthetics to the variables. The data used in the above example cannot be used as we need a variable with country names. We will use pivot_longer() function from the tidyr package to reshape the data.
gdp2 <- gdp |>
select(year, growth, india, china) |>
tidyr::pivot_longer(cols = -year, names_to = "country", values_to = "gdp")
gdp2# A tibble: 18 × 3
year country gdp
<date> <chr> <dbl>
1 2000-01-01 growth 6
2 2000-01-01 india 5
3 2000-01-01 china 8
4 2001-01-01 growth 9
5 2001-01-01 india 9
6 2001-01-01 china 5
7 2002-01-01 growth 8
8 2002-01-01 india 8
9 2002-01-01 china 6
10 2003-01-01 growth 9
11 2003-01-01 india 8
12 2003-01-01 china 8
13 2004-01-01 growth 9
14 2004-01-01 india 5
15 2004-01-01 china 9
16 2005-01-01 growth 8
17 2005-01-01 india 7
18 2005-01-01 china 8In the original data, to plot GDP trend of multiple countries we will have to use geom_line() multiple times. But in the reshaped data, we have the country names as one of the variables and this can be used along with the group argument to plot data of multiple countries with a single line of code as shown below. By mapping country to the group argument, we have plotted data of all countries.
ggplot(gdp2, aes(year, gdp, group = country)) +
geom_line()
In the above plot, we cannot distinguish between the lines and there is no way to identify which line represents which country. To make it easier to identify the trend of different countries, let us map the color argument to the variable country as shown below. Now, each country will be represented by line of different color.
ggplot(gdp2, aes(year, gdp, group = country)) +
geom_line(aes(color = country))
We can map linetype argument to country as well. In this case, each country will be represented by a different line type.
ggplot(gdp2, aes(year, gdp, group = country)) +
geom_line(aes(linetype = country))
We can map the width of the line to the variable country as well. But in this case, the plot does not look either elegant or intuitive.
ggplot(gdp2, aes(year, gdp, group = country)) +
geom_line(aes(linewidth = country))
Remember that in all the above cases, we mapped the arguments to a variable inside aes().
unemploy series from economics over date with linewidth = 1.unemploy + uempmed to long format and draw both series distinguished by color.Worked solutions in solutions/line.md (attempt first).