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#' Visually compare two dataframes and see where they are different.
#'
#' `vis_compare`, like the other `vis_*` families, gives an at-a-glance ggplot
#' of a dataset, but in this case, hones in on visualising **two** different
#' dataframes of the same dimension, so it takes two dataframes as arguments.
#'
#' @param df1 The first dataframe to compare
#'
#' @param df2 The second dataframe to compare to the first.
#'
#' @return `ggplot2` object displaying which values in each data frame are
#' present in each other, and which are not.
#'
#' @seealso [vis_miss()] [vis_dat()] [vis_guess()] [vis_expect()] [vis_cor()]
#'
#' @examples
#'
#' # make a new dataset of iris that contains some NA values
#' aq_diff <- airquality
#' aq_diff[1:10, 1:2] <- NA
#' vis_compare(airquality, aq_diff)
#' @export
vis_compare <- function(df1,
df2){
# could add a parameter, sort_match, to help with
# sort_match logical TRUE/FALSE.
# TRUE arranges the columns in order of most matches.
# make a TRUE/FALSE matrix of the data.
# Tells us whether it is the same (true) as the other dataset, or not (false)
# throw error if df1 not data.frame
test_if_dataframe(df1)
# throw error if df2 not data.frame
test_if_dataframe(df2)
if (!identical(dim(df1), dim(df2))) {
stop("vis_compare requires identical dimensions of df1 and df2")
}
v_identical <- Vectorize(identical)
df_diff <- purrr::map2_df(df1, df2, v_identical)
d <- df_diff %>%
as.data.frame() %>%
purrr::map_df(compare_print) %>%
vis_gather_() %>%
dplyr::mutate(value_df1 = vis_extract_value_(df1),
value_df2 = vis_extract_value_(df2))
# then we plot it
ggplot2::ggplot(data = d,
ggplot2::aes_string(
x = "variable",
y = "rows")) +
# text assists with plotly mouseover
# text = c("value_df1", "value_df2"))) +
# this test code has been removed as ggplot2 version 3.0.0
# breaks.
# Logged in issue https://github.com/ropensci/visdat/issues/89
ggplot2::geom_raster(ggplot2::aes_string(fill = "valueType")) +
ggplot2::theme_minimal() +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 45,
vjust = 1,
hjust = 1)) +
ggplot2::labs(x = "",
y = "Observations",
# this prevents it from being used in the boilerplate
fill = "Cell Type") +
ggplot2::scale_fill_manual(limits = c("same",
"different"),
breaks = c("same", # red
"different"), # dark blue
values = c("#fc8d59", # Orange
"#91bfdb"), # blue
na.value = "grey") +
# flip the axes
ggplot2::scale_y_reverse() +
ggplot2::theme(axis.text.x = ggplot2::element_text(hjust = 0.25)) +
ggplot2::scale_x_discrete(position = "top",
limits = names(df_diff))
}
#' (Internal) A utility function for `vis_compare`
#'
#' `compare_print` is an internal function that takes creates a dataframe with
#' information about where there are differences in the dataframe. This
#' function is used in `vis_compare`. It evaluates on the data `(df1 == df2)`
#' and (currently) replaces the "true" (the same) with "Same"
#' and FALSE with "Different", unless it is missing (coded as NA), in which
#' case it leaves it as NA.
#'
#' @param x a vector
#'
#'
compare_print <- function(x){
dplyr::if_else(x == "TRUE",
true = "same",
false = "different",
missing = "missing")
} # end function
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