Plots two variables of a dataframe on an alluvial plot. A third variable can be added either to the left or the right of the alluvial plot to provide coloring of the flows. All numerical variables are scaled, centered and YeoJohnson transformed before binning.
alluvial_long(
data,
key,
value,
id,
fill = NULL,
fill_right = T,
bins = 5,
bin_labels = c("LL", "ML", "M", "MH", "HH"),
NA_label = "NA",
order_levels_value = NULL,
order_levels_key = NULL,
order_levels_fill = NULL,
complete = TRUE,
fill_by = "first_variable",
col_vector_flow = palette_qualitative() %>% palette_filter(greys = F),
col_vector_value = RColorBrewer::brewer.pal(9, "Greys")[c(3, 6, 4, 7, 5)],
verbose = F,
stratum_labels = T,
stratum_label_type = "label",
stratum_label_size = 4.5,
stratum_width = 1/4,
auto_rotate_xlabs = T,
...
)a dataframe
unquoted column name or string of x axis variable
unquoted column name or string of y axis variable
unquoted column name or string of id column
unquoted column name or string of fill variable which will be used to color flows, Default: NULL
logical, TRUE fill variable is added to the right FALSE to the left, Default: T
number of bins for automatic binning of numerical variables, Default: 5
labels for bins, Default: c("LL", "ML", "M", "MH", "HH")
character vector define label for missing data
character vector denoting order of y levels from low to high, does not have to be complete can also just be used to bring levels to the front, Default: NULL
character vector denoting order of x levels from low to high, does not have to be complete can also just be used to bring levels to the front, Default: NULL
character vector denoting order of color fill variable levels from low to high, does not have to be complete can also just be used to bring levels to the front, Default: NULL
logical, insert implicitly missing observations, Default: TRUE
one_of(c('first_variable', 'last_variable', 'all_flows', 'values')), Default: 'first_variable'
HEX color values for flows, Default: palette_filter( greys = F)
HEX color values for y levels/values, Default:RColorBrewer::brewer.pal(9, 'Greys')[c(3,6,4,7,5)]
logical, print plot summary, Default: F
logical, Default: TRUE
character, Default: "label"
numeric, Default: 4.5
double, Default: 1/4
logical, Default: TRUE
additional parameter passed to manip_bin_numerics
ggplot2 object
if (FALSE) {
data = quarterly_flights
alluvial_long( data, key = qu, value = mean_arr_delay, id = tailnum, fill_by = 'last_variable' )
# more flow coloring variants ------------------------------------
alluvial_long( data, key = qu, value = mean_arr_delay, id = tailnum, fill_by = 'first_variable' )
alluvial_long( data, key = qu, value = mean_arr_delay, id = tailnum, fill_by = 'all_flows' )
alluvial_long( data, key = qu, value = mean_arr_delay, id = tailnum, fill_by = 'value' )
# color by additional variable carrier ---------------------------
alluvial_long( data, key = qu, value = mean_arr_delay, fill = carrier, id = tailnum )
# use same color coding for flows and y levels -------------------
palette = c('green3', 'tomato')
alluvial_long( data, qu, mean_arr_delay, tailnum, fill_by = 'value'
, col_vector_flow = palette
, col_vector_value = palette )
# reorder levels ------------------------------------------------
alluvial_long( data, qu, mean_arr_delay, tailnum, fill_by = 'first_variable'
, order_levels_value = c('on_time', 'late') )
alluvial_long( data, qu, mean_arr_delay, tailnum, fill_by = 'first_variable'
, order_levels_key = c('Q4', 'Q3', 'Q2', 'Q1') )
require(dplyr)
require(magrittr)
order_by_carrier_size = data %>%
group_by(carrier) %>%
count() %>%
arrange( desc(n) ) %>%
.[['carrier']]
alluvial_long( data, qu, mean_arr_delay, tailnum, carrier
, order_levels_fill = order_by_carrier_size )
}