Get Started

John Coene

2020-09-23

Welcome to echarts4r, let’s explore the package together.

1. All functions of the echarts4r package start with e_.
2. All its Shiny proxies end with _p.
3. All echarts4r plots are initialised with e_charts.
4. All functions are %>% friendly.
5. Most functions have escape hatches ending in _.

Your first plot

Let’s build a line chart, load the library and pipe your data to e_charts. If you are not at ease with the %>% you can use e_charts(mtcars, wt).

# prepare data
df <- state.x77 %>% 
  as.data.frame() %>% 
  tibble::rownames_to_column("State")

library(echarts4r) # load echarts4r

df %>% 
  e_charts(x = State) %>% # initialise and set x
  e_line(serie = Population) # add a line

If you are not at ease with bare column names you can use the escape hatches ending in _.

df %>% 
  e_charts_("State") %>% 
  e_line_("Population")

The easiest way is to use the %>% operator to add plots and options.

df %>% 
  e_charts(State) %>% # initialise and set x
  e_line(Population) %>%  # add a line
  e_area(Income) # add area

Options

We could also change the lines to make them smooth.

df %>% 
  e_charts(State) %>% # initialise and set x
  e_line(Population, smooth = TRUE) %>%  # add a line
  e_area(Income, smooth = TRUE) # add area

Lets label the axes with the convenience function e_axis_labels.

df %>% 
  e_charts(State) %>% # initialise and set x
  e_line(Population, smooth = TRUE) %>%  # add a line
  e_area(Income, smooth = TRUE) %>%  # add area
  e_axis_labels(x = "State") # axis labels

We can use one of the 13 built-in themes, see ?e_theme for a complete list, we’ll also add a title with e_title.

df %>% 
  e_charts(State) %>% # initialise and set x
  e_line(Population, smooth = TRUE) %>%  # add a line
  e_area(Income, smooth = TRUE) %>%  # add area
  e_axis_labels(x = "State") %>% # axis labels
  e_title("US States", "Population & Income") %>%  # Add title & subtitle
  e_theme("infographic") # theme

The legend and title are a bit close, let’s move the legend to another part the canvas.

df %>% 
  e_charts(State) %>% # initialise and set x
  e_line(Population, smooth = TRUE) %>%  # add a line
  e_area(Income, smooth = TRUE) %>%  # add area
  e_axis_labels(x = "State") %>% # axis labels
  e_title("US States", "Population & Income") %>%  # Add title & subtitle
  e_theme("infographic") %>%  # theme
  e_legend(right = 0) # move legend to the bottom

Add a tooltip, of which there are numerous options, here we use trigger = "axis" to trigger the tooltip by the axis rather than a single data point.

df %>% 
  e_charts(State) %>% # initialise and set x
  e_line(Population, smooth = TRUE) %>%  # add a line
  e_area(Income, smooth = TRUE) %>%  # add area
  e_axis_labels(x = "State") %>% # axis labels
  e_title("US States", "Population & Income") %>%  # Add title & subtitle
  e_theme("infographic") %>%  # theme
  e_legend(right = 0) %>%  # move legend to the bottom
  e_tooltip(trigger = "axis") # tooltip

Finally, we are currently plotting population and income on the same axis, let’s put them each on their respective y axis by specifying an extra axis for Income.

Dual y axes is a terrible idea, it’s only here for demonstration purposes.

df %>% 
  e_charts(State) %>% # initialise and set x
  e_line(Population, smooth = TRUE) %>%  # add a line
  e_area(Income, smooth = TRUE, y_index = 1) %>%  # add area
  e_axis_labels(x = "State") %>% # axis labels
  e_title("US States", "Population & Income") %>%  # Add title & subtitle
  e_theme("infographic") %>%  # theme
  e_legend(right = 0) %>%  # move legend to the bottom
  e_tooltip(trigger = "axis") # tooltip

Navigate options

echarts4r is highly customisable, there are too many options to have them all hard-coded in the package but rest assured; they are available, and can be passe to .... You will find all these options in the official documentation.

Official Documentation

For instance the documentation for the tooltip looks like this:

Therefore if we want to change our tooltip to an axisPointer we can do so by passing a list to axisPointer.

df %>% 
  e_charts(State) %>% # initialise and set x
  e_line(Population, smooth = TRUE) %>%  # add a line
  e_area(Income, smooth = TRUE) %>%  # add area
  e_x_axis(name = "States") %>%  # add x axis name
  e_title("US States", "Population & Income") %>%  # Add title & subtitle
  e_theme("infographic") %>%  # theme
  e_legend(right = 0) %>% # move legend to the bottom
  e_tooltip(
    axisPointer = list(
      type = "cross"
    )
  ) 

Once you come to the realisation that JSON ~= list in R, it’s pretty easy.

You’re in on the basics, go to the advanced section or navigate the site to discover how add multiple linked graphs, draw on globes, use the package in shiny, and more.