vignettes/billboarder-intro.Rmd
billboarder-intro.Rmd
If you want to create a grouped bar chart, first option is to put +
If you want to create a grouped bar chart, first option is to put your data in a “wide” format. Here we use stats::reshape, but I recommend to use tidyr::spread or data.table::dcast.
stats::reshape
tidyr::spread
data.table::dcast
Second option is to define a mapping of your variable with function +
Second option is to define a mapping of your variable with function bbaes (for more example of mapping, see vignette billboarder-mapping).
bbaes
@@ -167,10 +167,10 @@ Bar chart= bbaes(x = Var1, y = Freq, group = Var2) )
You can change the type of line with argument type, for +
type
You can change the type of line with argument type, for example an area-step :
area-step
billboarder() %>% bb_linechart(data = sin(seq(-pi, pi, length.out = 10)), type = "area-step")
If want to specify a variable to map to the x-axis, you had to pass a +
If want to specify a variable to map to the x-axis, you had to pass a data.frame to the function :
data.frame
df <- data.frame( @@ -216,10 +216,10 @@ Line chartbillboarder() %>% bb_linechart(data = df, x = "var_x")
If the first variable of the data.frame is a +
If the first variable of the data.frame is a Date or a POSIX, it will be automatically mapped to the x-axis :
Date
POSIX
@@ -229,24 +229,24 @@ Line chart) df #> date var -#> 1 2017-06-12 1.4030754 -#> 2 2017-06-13 1.9541651 -#> 3 2017-06-14 0.4305189 -#> 4 2017-06-15 1.0905004 -#> 5 2017-06-16 0.8014968 -#> 6 2017-06-17 0.3394191 -#> 7 2017-06-18 0.4033910 -#> 8 2017-06-19 -0.6760134 -#> 9 2017-06-20 0.4238027 -#> 10 2017-06-21 -0.4096546 +#> 1 2017-06-12 -0.2481872 +#> 2 2017-06-13 -0.7996173 +#> 3 2017-06-14 0.8885554 +#> 4 2017-06-15 -1.2819058 +#> 5 2017-06-16 0.8157619 +#> 6 2017-06-17 -0.2695514 +#> 7 2017-06-18 -0.7984315 +#> 8 2017-06-19 -0.3420709 +#> 9 2017-06-20 0.9777540 +#> 10 2017-06-21 0.9158735 billboarder() %>% bb_linechart(data = df)
+ billboarder() %>% bb_scatterplot(data = iris, x = "Petal.Length", y = "Petal.Width", group = "Species") - - + + - +
billboarder() %>% bb_scatterplot(data = iris, x = "Petal.Length", y = "Petal.Width", group = "Species")
Note : pie and donut are automatically sorted, you can change that +
Note : pie and donut are automatically sorted, you can change that with bb_data(order = NULL).
bb_data(order = NULL)
vignettes/billboarder-mapping.Rmd
billboarder-mapping.Rmd
data.framebillboarder() %>% bb_barchart(data = prod_par_filiere[, c("annee", "prod_bioenergies")])
Variable annee is used on the x-axis, and +
annee
Variable annee is used on the x-axis, and prod_bioenergies as y values.
prod_bioenergies
This is similar for line chart :
billboarder() %>% bb_linechart(data = prod_par_filiere[, c("annee", "prod_bioenergies")])
You don’t have to pass arguments to bb_barchart.
bb_barchart
This is the same for line chart :
billboarder(data = prod_par_filiere) %>% bb_aes(x = annee, y = prod_bioenergies) %>% bb_linechart()
billboarder(data = prod_par_filiere) %>% bb_barchart(mapping = bbaes(x = annee, y = prod_bioenergies))
The function to map variables is bbaes without +
The function to map variables is bbaes without underscore.
For line chart :
billboarder(data = prod_par_filiere) %>% bb_linechart(mapping = bbaes(x = annee, y = prod_bioenergies))
with ‘long’ data :
# prepare data data("prod_filiere_long") @@ -237,10 +237,10 @@ Grouping variablebillboarder(data = prod_filiere_long) %>% bb_barchart(mapping = bbaes(x = annee, y = prod, group = branche))