View source: R/stratify-keys.R
stratify_keys | R Documentation |
To look at as much of the raw data as possible, it can be helpful to
stratify the data into groups for plotting. You can stratify
the
keys
using the stratify_keys()
function, which adds the column,
.strata
. This allows the user to create facetted plots showing a more
of the raw data.
stratify_keys(.data, n_strata, along = NULL, fun = mean, ...)
.data |
data.frame to explore |
n_strata |
number of groups to create |
along |
variable to stratify along. This groups by each |
fun |
summary function. Default is mean. |
... |
extra arguments |
data.frame with column, .strata
containing n_strata
groups
library(ggplot2) library(brolgar) heights %>% sample_frac_keys(size = 0.1) %>% stratify_keys(10) %>% ggplot(aes(x = height_cm, y = year, group = country)) + geom_line() + facet_wrap(~.strata) # now facet along some feature library(dplyr) heights %>% key_slope(height_cm ~ year) %>% right_join(heights, ., by = "country") %>% stratify_keys(n_strata = 12, along = .slope_year, fun = median) %>% ggplot(aes(x = year, y = height_cm, group = country)) + geom_line() + facet_wrap(~.strata) heights %>% stratify_keys(n_strata = 12, along = height_cm) %>% ggplot(aes(x = year, y = height_cm, group = country)) + geom_line() + facet_wrap(~.strata)
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