`echarts4r`

comes with a highly customisable grid and
axis, but admittedly they take some getting used to.

## Axis helper

You can customise the axis with `e_axis`

,
`e_x_axis`

or `e_y_axis`

, you can see the official
documentation for more details. There is also a helper function,
`e_format_axis`

and its sisters `e_format_x_axis`

and `e_format_y_axis`

. The latter lets you easily add suffix
or prefix to your axis labels.

Say you want to plot against ceslius.

```
df <- data.frame(
x = 1:20, # celsius
y = runif(20, 1, 100) # percentages
)
df |>
e_charts(x) |>
e_line(y) |>
e_format_x_axis(suffix = "°C") |>
e_legend(FALSE)
```

Since version `0.2.1`

you can also easily format the axis
to decimal, percentages or currencies thanks to contribution from Artem Klevtsov.

```
df |>
dplyr::mutate(y = y / 100) |>
e_charts(x) |>
e_line(y, legend = FALSE) |>
e_x_axis(
formatter = e_axis_formatter("currency", currency = "GBP")
) |>
e_y_axis(
formatter = e_axis_formatter("decimal", digits = 3)
)
```

## Grid

You can also customise the grid to have, for instance, multiple plots on one canvas.

Let’s initialise a basic plot.

```
df <- data.frame(
x = 1:20,
w = runif(20, 1, 100),
z = runif(20, 25, 75)
)
df |>
e_charts(x) |>
e_line(w) |>
e_line(z)
```

Now say we don’t want `w`

and `z`

on the same
plot. We could of course make two entirely different plots (2 plots
initialised with `e_charts()`

), but it would be cleaner to
have them on the same canvas, a bit like ggplot2
facets.

First two plots on the same canvas means multiple axis, so we’ll plot each serie on its own axis.

`echarts4r`

is an R API to a JavaScript library, so arrays
start at one; `x`

and `y`

indices default to 0 so
we only need to change one of the series’ indices to 1. Therefore one
serie is plotted on index 0 and the other on index 1 for two
`x`

and `y`

axis.

Notice how `echarts4r`

puts the additional axis on the top
and right of the plot. This is a useful feature but not what we want;
we’re missing a split grid.

We use `e_grid`

twice for two grids, we define the height
of each; `35%`

is ideal for stacked grids, you need some
margin for the legend, the axis, etc. hence not using
`50%`

.

```
df |>
e_charts(x) |>
e_line(w) |>
e_line(z, x_index = 1, y_index = 1) |>
e_grid(height = "35%") |> # two grids of 35% height
e_grid(height = "35%", top = "50%") # this grid is 50% from the top
```

However, we still have both line plots on the same grid. Here is how
to think about grids and axis in `echarts4r`

.

- Your series (i.e.:
`e_line`

) are plotted against axis (`e_axis`

) - These axis are plotted in grids
`e_grid`

So we have two grids and two axis but the axis are both plotted on the same grid(point #2 above). So we need to move our two additional axis to another grid. Note that grid indices also start at 0 here.

```
df |>
e_charts(x) |>
e_line(w) |>
e_line(z, x_index = 1, y_index = 1) |>
e_grid(height = "35%") |>
e_grid(height = "35%", top = "50%") |>
e_y_axis(gridIndex = 1) |> # put x and y on grid index 1
e_x_axis(gridIndex = 1)
```

There you go!

You can also have a different grid to put the plots side by side.

## Axis

You can also mess with the axis to completely change your chart. For instance, from a regular bar chart:

```
df <- data.frame(
x = LETTERS[1:10],
y = seq(1, 20, by = 2),
z = runif(10, 5, 20)
)
df |>
e_charts(x) |>
e_bar(y)
```

to a polar chart.

```
df |>
e_charts(x) |>
e_polar() |>
e_angle_axis(x) |> # angle = x
e_radius_axis() |>
e_bar(y, coord_system = "polar")
```

or a radial chart one.

```
df |>
e_charts(x) |>
e_polar() |>
e_angle_axis() |>
e_radius_axis(x) |> # radius = x
e_bar(y, coord_system = "polar")
```

This will also work with other chart types.

```
df |>
e_charts(x) |>
e_polar() |>
e_angle_axis() |>
e_radius_axis(x) |>
e_line(y, coord_system = "polar") |>
e_scatter(z, coord_system = "polar")
```