Merge 7c9b6bfc9e into fe4d4b0690

.Rbuildignore

@@ -0,0 +1,3 @@
+^LICENSE\.md$
+^.*\.Rproj$
+^\.Rproj\.user$

DESCRIPTION

@@ -0,0 +1,41 @@
+Type: Package
+Package: tidyexplain
+Title: Animated Explanations of Tidyverse Verbs
+Version: 0.0.1.9000
+Date: 2018-08-27
+Authors@R: 
+    c(person(given = "Garrick",
+             family = "Aden-Buie",
+             role = c("aut", "cre"),
+             email = "g.adenbuie@gmail.com"),
+      person(given = "David",
+             family = "Zimmermann",
+             role = "aut",
+             email = "david_j_zimmermann@hotmail.com"),
+      person(given = "Tyler Grant",
+             family = "Smith",
+             role = "ctb"))
+Description: Animated explanations of the verbs in the tidyverse
+    using gganimate and ggplot2.
+License: MIT + file LICENSE
+Depends: 
+    gganimate (>= 0.9.9.9999),
+    ggplot2 (>= 3.0.0)
+Imports: 
+    dplyr,
+    magrittr,
+    purrr,
+    rlang (>= 0.1.2),
+    scales,
+    tidyr,
+    tidyselect
+Suggests: 
+    knitr,
+    roxygen2,
+    testthat,
+    viridis
+VignetteBuilder: 
+    knitr
+Encoding: UTF-8
+Roxygen: list(markdown = TRUE)
+RoxygenNote: 6.1.1

LICENSE

@@ -1,116 +1,2 @@
-CC0 1.0 Universal
-
-Statement of Purpose
-
-The laws of most jurisdictions throughout the world automatically confer
-exclusive Copyright and Related Rights (defined below) upon the creator and
-subsequent owner(s) (each and all, an "owner") of an original work of
-authorship and/or a database (each, a "Work").
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-works ("Commons") that the public can reliably and without fear of later
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-and redistribute as freely as possible in any form whatsoever and for any
-purposes, including without limitation commercial purposes. These owners may
-contribute to the Commons to promote the ideal of a free culture and the
-further production of creative, cultural and scientific works, or to gain
-reputation or greater distribution for their Work in part through the use and
-efforts of others.
-
-For these and/or other purposes and motivations, and without any expectation
-of additional consideration or compensation, the person associating CC0 with a
-Work (the "Affirmer"), to the extent that he or she is an owner of Copyright
-and Related Rights in the Work, voluntarily elects to apply CC0 to the Work
-and publicly distribute the Work under its terms, with knowledge of his or her
-Copyright and Related Rights in the Work and the meaning and intended legal
-effect of CC0 on those rights.
-
-1. Copyright and Related Rights. A Work made available under CC0 may be
-protected by copyright and related or neighboring rights ("Copyright and
-Related Rights"). Copyright and Related Rights include, but are not limited
-to, the following:
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-  i. the right to reproduce, adapt, distribute, perform, display, communicate,
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-  ii. moral rights retained by the original author(s) and/or performer(s);
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-  iii. publicity and privacy rights pertaining to a person's image or likeness
-  depicted in a Work;
-
-  iv. rights protecting against unfair competition in regards to a Work,
-  subject to the limitations in paragraph 4(a), below;
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-  v. rights protecting the extraction, dissemination, use and reuse of data in
-  a Work;
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-  vi. database rights (such as those arising under Directive 96/9/EC of the
-  European Parliament and of the Council of 11 March 1996 on the legal
-  protection of databases, and under any national implementation thereof,
-  including any amended or successor version of such directive); and
-
-  vii. other similar, equivalent or corresponding rights throughout the world
-  based on applicable law or treaty, and any national implementations thereof.
-
-2. Waiver. To the greatest extent permitted by, but not in contravention of,
-applicable law, Affirmer hereby overtly, fully, permanently, irrevocably and
-unconditionally waives, abandons, and surrenders all of Affirmer's Copyright
-and Related Rights and associated claims and causes of action, whether now
-known or unknown (including existing as well as future claims and causes of
-action), in the Work (i) in all territories worldwide, (ii) for the maximum
-duration provided by applicable law or treaty (including future time
-extensions), (iii) in any current or future medium and for any number of
-copies, and (iv) for any purpose whatsoever, including without limitation
-commercial, advertising or promotional purposes (the "Waiver"). Affirmer makes
-the Waiver for the benefit of each member of the public at large and to the
-detriment of Affirmer's heirs and successors, fully intending that such Waiver
-shall not be subject to revocation, rescission, cancellation, termination, or
-any other legal or equitable action to disrupt the quiet enjoyment of the Work
-by the public as contemplated by Affirmer's express Statement of Purpose.
-
-3. Public License Fallback. Should any part of the Waiver for any reason be
-judged legally invalid or ineffective under applicable law, then the Waiver
-shall be preserved to the maximum extent permitted taking into account
-Affirmer's express Statement of Purpose. In addition, to the extent the Waiver
-is so judged Affirmer hereby grants to each affected person a royalty-free,
-non transferable, non sublicensable, non exclusive, irrevocable and
-unconditional license to exercise Affirmer's Copyright and Related Rights in
-the Work (i) in all territories worldwide, (ii) for the maximum duration
-provided by applicable law or treaty (including future time extensions), (iii)
-in any current or future medium and for any number of copies, and (iv) for any
-purpose whatsoever, including without limitation commercial, advertising or
-promotional purposes (the "License"). The License shall be deemed effective as
-of the date CC0 was applied by Affirmer to the Work. Should any part of the
-License for any reason be judged legally invalid or ineffective under
-applicable law, such partial invalidity or ineffectiveness shall not
-invalidate the remainder of the License, and in such case Affirmer hereby
-affirms that he or she will not (i) exercise any of his or her remaining
-Copyright and Related Rights in the Work or (ii) assert any associated claims
-and causes of action with respect to the Work, in either case contrary to
-Affirmer's express Statement of Purpose.
-
-4. Limitations and Disclaimers.
-
-  a. No trademark or patent rights held by Affirmer are waived, abandoned,
-  surrendered, licensed or otherwise affected by this document.
-
-  b. Affirmer offers the Work as-is and makes no representations or warranties
-  of any kind concerning the Work, express, implied, statutory or otherwise,
-  including without limitation warranties of title, merchantability, fitness
-  for a particular purpose, non infringement, or the absence of latent or
-  other defects, accuracy, or the present or absence of errors, whether or not
-  discoverable, all to the greatest extent permissible under applicable law.
-
-  c. Affirmer disclaims responsibility for clearing rights of other persons
-  that may apply to the Work or any use thereof, including without limitation
-  any person's Copyright and Related Rights in the Work. Further, Affirmer
-  disclaims responsibility for obtaining any necessary consents, permissions
-  or other rights required for any use of the Work.
-
-  d. Affirmer understands and acknowledges that Creative Commons is not a
-  party to this document and has no duty or obligation with respect to this
-  CC0 or use of the Work.
-
-For more information, please see
-<http://creativecommons.org/publicdomain/zero/1.0/>
+YEAR: 2018
+COPYRIGHT HOLDER: Garrick Aden-Buie

LICENSE.md

@@ -0,0 +1,21 @@
+# MIT License
+
+Copyright (c) 2018 Garrick Aden-Buie
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

NAMESPACE

@@ -0,0 +1,41 @@
+# Generated by roxygen2: do not edit by hand
+
+S3method(print,anim_opts)
+export("%>%")
+export(anim_options)
+export(animate_anti_join)
+export(animate_full_join)
+export(animate_gather)
+export(animate_inner_join)
+export(animate_intersect)
+export(animate_left_join)
+export(animate_right_join)
+export(animate_semi_join)
+export(animate_setdiff)
+export(animate_spread)
+export(animate_union)
+export(animate_union_all)
+export(get_font_size)
+export(is.anim_opts)
+export(set_anim_options)
+export(set_font_size)
+importFrom(dplyr,anti_join)
+importFrom(dplyr,arrange)
+importFrom(dplyr,bind_cols)
+importFrom(dplyr,bind_rows)
+importFrom(dplyr,data_frame)
+importFrom(dplyr,filter)
+importFrom(dplyr,full_join)
+importFrom(dplyr,group_by)
+importFrom(dplyr,inner_join)
+importFrom(dplyr,left_join)
+importFrom(dplyr,mutate)
+importFrom(dplyr,pull)
+importFrom(dplyr,right_join)
+importFrom(dplyr,row_number)
+importFrom(dplyr,select)
+importFrom(dplyr,semi_join)
+importFrom(dplyr,slice)
+importFrom(magrittr,"%>%")
+importFrom(tidyr,gather)
+importFrom(tidyr,spread)

R/00_base_join.R

@@ -1,37 +0,0 @@
-# Animated dplyr joins with gganimate
-# * Garrick Aden-Buie
-# * garrickadenbuie.com
-# * MIT License: https://opensource.org/licenses/MIT
-
-library(tidyverse)
-library(gganimate)
-
-if (!getOption("tidy_verb_anim.font_registered", FALSE)) {
-  source(here::here("R", "01_register-fonts.R"))
-}
-
-if (!getOption("tidy_verb_anim.functions_loaded", FALSE)) {
-  source(here::here("R", "02_functions.R"))
-}
-
-source(here::here("R", "03_check-folders.R"))
-
-plot_data_join <- function(x, title = "", xlims = xlim(0.5, 5.5), ylims = ylim(-3.5, -0.5)) {
-  plot_data(x, title) +
-    xlims + ylims
-}
-
-# Data ----
-x <- data_frame(
-  id = 1:3,
-  x = paste0("x", 1:3)
-)
-
-y <- data_frame(
-  id = (1:4)[-3],
-  y = paste0("y", (1:4)[-3])
-)
-
-initial_join_dfs <- proc_data(x, "x") %>%
-  bind_rows(mutate(proc_data(y, "y"), .x = .x + 3)) %>%
-  mutate(frame = 1)

R/00_base_set.R

@@ -1,50 +0,0 @@
-# Animated dplyr set opertaions with gganimate
-# * Contributed by Tyler Grant Smith <https://github.com/TylerGrantSmith>
-# * and Garrick Aden-Buie <https://www.garrickadenbuie.com>
-# * MIT License: https://opensource.org/licenses/MIT
-
-library(tidyverse)
-library(gganimate)
-
-if (!getOption("tidy_verb_anim.font_registered", FALSE)) {
-  source(here::here("R", "01_register-fonts.R"))
-}
-
-if (!getOption("tidy_verb_anim.functions_loaded", FALSE)) {
-  source(here::here("R", "02_functions.R"))
-}
-
-source(here::here("R", "03_check-folders.R"))
-
-# Initialize data processing function ----
-
-proc_data_set <- function(x, .id = "x") {
-  proc_data(x, .id, colorize_row_id, "before")
-}
-
-plot_data_set <- function(x, title = "", xlims = xlim(1.5, 6.5), ylims = ylim(-3.5, -0.5)) {
-  filter(x, label != "id") %>%
-  plot_data(title) +
-  xlims + ylims
-}
-
-# Data ----
-
-x <- tibble::tribble(
-  ~id,   ~x,    ~y,
-  1,  "1",  "a",
-  2,  "1",  "b",
-  3,  "2",  "a"
-)
-
-y <- tibble::tribble(
-  ~id, ~x, ~y,
-  1,  "1",  "a",
-  4,  "2",  "b"
-)
-
-initial_set_dfs <- bind_rows(
-  proc_data_set(x, "x"),
-  proc_data_set(y, "y") %>% mutate(.x = .x + 3)
-) %>%
-  mutate(frame = 1)

R/00_base_tidyr.R

@@ -1,28 +0,0 @@
-# Animated dplyr joins with gganimate
-# * Garrick Aden-Buie
-# * garrickadenbuie.com
-# * MIT License: https://opensource.org/licenses/MIT
-
-library(tidyverse)
-library(gganimate)
-
-if (!getOption("tidy_verb_anim.font_registered", FALSE)) {
-  source(here::here("R", "01_register-fonts.R"))
-}
-
-if (!getOption("tidy_verb_anim.functions_loaded", FALSE)) {
-  source(here::here("R", "02_functions.R"))
-}
-
-source(here::here("R", "03_check-folders.R"))
-
-# Data ----
-set.seed(42)
-wide <- data_frame(
-  id = rep(1:2),
-  x = letters[1:2],
-  y = letters[3:4],
-  z = letters[5:6]
-)
-
-long <- tidyr::gather(wide, key, val, x:z)

R/01_register-fonts.R

@@ -1,7 +0,0 @@
-# Note: I used Fira Sans and Mono (downloaded here from Google Fonts).
-#       Feel free to change font names below for desired fonts.
-
-sysfonts::font_add_google("Fira Sans")
-sysfonts::font_add_google("Fira Mono")
-showtext::showtext_auto()
-options(tidy_verb_anim.font_registered = TRUE)

R/02_functions.R

@@ -1,112 +0,0 @@
-proc_data <- function(x, .id = "x", color_fun = colorize_keys, color_when = c("after", "before"), ...) {
-  color_when <- match.arg(color_when)
-  n_colors <- max(x$id)
-
-  if (color_when == "before") x <- color_fun(x, n_colors, ...)
-
-  x <- x %>%
-    mutate(.y = -row_number()) %>%
-    tidyr::gather("label", "value", setdiff(colnames(x), c(".y", "color"))) %>%
-    mutate(value = as.character(value)) %>%
-    group_by(.y) %>%
-    mutate(
-      .x = 1:n(),
-      .id = .id,
-      .width = 1
-    ) %>%
-    ungroup(.y)
-
-  if (color_when == "after") x <- color_fun(x, n_colors, ...)
-  x
-}
-
-colorize_keys <- function(df, n_colors, key_col = "id", color_other = "#d0d0d0", color_missing = "#ffffff") {
-  # Assumes that key_col is integer
-  colors <- scales::brewer_pal(type = "qual", "Set1")(n_colors)
-  mutate(
-    df,
-    color = ifelse(label == key_col, value, n_colors + 1),
-    color = colors[as.integer(color)],
-    color = ifelse(is.na(color), "#d0d0d0", color),
-    color = ifelse(is.na(value), "#ffffff", color)
-  )
-}
-
-colorize_row_id <- function(df, n_colors, key_col = "id") {
-  # Assumes that key_col is integer
-  colors <- scales::brewer_pal(type = "qual", "Set1")(n_colors)
-  df$color <- colors[df[[key_col]]]
-  df
-}
-
-colorize_wide_tidyr <- function(df, n_colors, key_col = "id") {
-  n_colors <- n_colors + length(setdiff(unique(df$label), key_col))
-  colors <- scales::brewer_pal(type = "qual", "Set1")(n_colors)
-
-  df$value_int <- as.integer(gsub("[a-zA-Z]", "0", df$value))
-  max_id_color <- max(df$value_int)
-
-  df %>%
-    bind_rows(
-      filter(df, .y == "-1") %>% mutate(.y = 0)
-    ) %>%
-    mutate(
-      idcp = max_id_color - 1L,
-      idc = case_when(
-        label == "id" ~ value_int,
-        TRUE ~ map_int(label, ~which(. == unique(label))) + idcp
-      )
-    ) %>%
-    select(-idcp, -value_int) %>%
-    mutate(
-      idc   = ifelse(.y == 0 & label == "id", 100, idc),
-      value = ifelse(.y == 0, label, value),
-      .id   = ifelse(.y == 0, "n", .id),
-      color = colors[idc],
-    ) %>%
-    filter(!is.na(color)) %>%
-    mutate(alpha = ifelse(label != "id" & .y < 0, 0.6, 1.0)) %>%
-    select(-idc)
-}
-
-plot_data <- function(x, title = "") {
-  if (!"alpha" %in% colnames(x)) x$alpha <- 1
-  if (!".text_color" %in% colnames(x)) x$`.text_color` <- "white"
-  if (!".text_size" %in% colnames(x)) x$`.text_size` <- 12
-  ggplot(x) +
-    aes(.x, .y, fill = color, label = value) +
-    geom_tile(aes(alpha = alpha), width = 0.9, height = 0.9) +
-    geom_text(aes(x = .x, color = .text_color, size = .text_size), hjust = 0.5, family = "Fira Sans") +
-    scale_fill_identity() +
-    scale_alpha_identity() +
-    scale_color_identity() +
-    scale_size_identity() +
-    coord_equal() +
-    ggtitle(title) +
-    theme_void() +
-    theme(plot.title = element_text(family = "Fira Mono", hjust = 0.5, size = 24)) +
-    guides(fill = FALSE)
-}
-
-animate_plot <- function(x, transition_length = 2, state_length = 1) {
-  x +
-    transition_states(frame, transition_length, state_length) +
-    enter_fade() +
-    exit_fade() +
-    ease_aes("sine-in-out")
-}
-
-save_static_plot <- function(g, filename, formats = c("png", "svg")) {
-  filenames <- formats %>%
-    purrr::set_names() %>%
-    purrr::map_chr(static_plot_filename, x = filename) %>%
-    purrr::iwalk(
-      ~ ggsave(filename = .x, plot = g, dev = .y)
-    )
-}
-
-static_plot_filename <- function(x, ext) {
-  here::here("images", "static", ext, paste0(x, ".", ext))
-}
-
-options(tidy_verb_anim.functions_loaded = TRUE)

R/03_check-folders.R

@@ -1,5 +0,0 @@
-if (!dir.exists(here::here("images"))) dir.create(here::here("images"))
-png_path <- here::here("images", "static", "png")
-svg_path <- here::here("images", "static", "svg")
-if (!dir.exists(png_path)) dir.create(png_path, recursive = TRUE)
-if (!dir.exists(svg_path)) dir.create(svg_path, recursive = TRUE)

R/animate_joins.R

@@ -0,0 +1,150 @@
+#' Animates a join operation
+#'
+#' Functions to visualise the join operations either static as a ggplot, or
+#' dynamic as a gif.
+#'
+#' @param x the x dataset
+#' @param y the y dataset
+#' @param by the by arguments for the join
+#' @param export the export type, either gif, first or last. The latter two
+#'              export ggplots of the first/last state of the join
+#' @param ... further arguments passed to anim_options()
+#'
+#' @return either a gif or a ggplot
+#'
+#' @seealso \code{\link[dplyr]{join}}
+#'
+#' @name animate_join
+#' @examples
+#' x <- data_frame(id = 1:3, x = paste0("x", 1:3))
+#' y <- data_frame(id = (1:4)[-3], y = paste0("y", (1:4)[-3]))
+#'
+#' # Animate the first or last state of the join
+#' animate_full_join(x, y, by = "id", export = "first")
+#' animate_full_join(x, y, by = "id", export = "last")
+#'
+#' # animate the transition as a gif (default)
+#' \donttest{
+#' animate_full_join(x, y, by = "id", export = "gif")
+#' }
+#'
+#' # different options include
+#' \donttest{
+#' animate_full_join(x, y, by = "id")
+#' animate_inner_join(x, y, by = "id")
+#' animate_left_join(x, y, by = "id")
+#' animate_right_join(x, y, by = "id")
+#' animate_semi_join(x, y, by = "id")
+#' animate_anti_join(x, y, by = "id")
+#'
+#' # further arguments can be passed to all animate_* functions, see also ?anim_options
+#' animate_full_join(
+#'   x, y, by = "id", export = "last",
+#'   text_size = 5, title_size = 25,
+#'   color_header = "black",
+#'   color_other = "lightblue",
+#'   color_fun = viridis::viridis
+#' )
+#' }
+#'
+#' # Save the results
+#' \donttest{
+#' # to save the ggplot, use
+#' fj <- animate_full_join(x, y, by = "id", export = "last")
+#' ggsave("full-join.pdf", fj)
+#'
+#' # to save the gif, use
+#' fj <- animate_full_join(x, y, by = "id", export = "gif")
+#' anim_save(fj, "full-join.gif")
+#' }
+animate_join <- function(
+  x,
+  y,
+  by,
+  type = c("full_join", "inner_join", "left_join", "right_join",
+           "semi_join", "anti_join"),
+  export = c("gif", "first", "last"),
+  ...
+) {
+  type   <- match.arg(type)
+  export <- match.arg(export)
+  x_name <- get_input_text(x)
+  y_name <- get_input_text(y)
+  data   <- make_named_data(x, y)
+
+  by_args <- if (length(by) == 1) sprintf("\"%s\"", by) else
+    sprintf("c(\"%s\")", paste(by, collapse = "\", \""))
+
+  title <- sprintf(paste0(type, "(%s, %s, by = %s)"), x_name, y_name, by_args)
+
+  if (type %in% c("semi_join", "anti_join")) {
+    # for semi and anti_joins, there is no adding of multiple rows
+    data$y <- dplyr::distinct(data$y)
+  }
+
+  ll <- process_join(data$x, data$y, by, ...)
+
+  step0 <- bind_rows(ll$x, ll$y) %>% mutate(.frame = 0, .alpha = 1)
+
+  step1 <- move_together(ll$x, ll$y, type) %>% mutate(.frame = 1)
+
+  all <- bind_rows(step0, step1)
+
+  if (export == "gif") {
+    animate_plot(all, title, ...)
+  } else if (export == "first") {
+    title <- ""
+    static_plot(step0, title, ...)
+  } else if (export == "last") {
+    static_plot(step1, title, ...)
+  }
+}
+
+
+#' @rdname animate_join
+#' @export
+animate_full_join <- function(x, y, by, export = "gif", ...) {
+  x <- rlang::enquo(x)
+  y <- rlang::enquo(y)
+  animate_join(x, y, by, type = "full_join", export = export, ...)
+}
+
+#' @rdname animate_join
+#' @export
+animate_inner_join <- function(x, y, by, export = "gif", ...) {
+  x <- rlang::enquo(x)
+  y <- rlang::enquo(y)
+  animate_join(x, y, by, type = "inner_join", export = export, ...)
+}
+
+#' @rdname animate_join
+#' @export
+animate_left_join <- function(x, y, by, export = "gif", ...) {
+  x <- rlang::enquo(x)
+  y <- rlang::enquo(y)
+  animate_join(x, y, by, type = "left_join", export = export, ...)
+}
+
+#' @rdname animate_join
+#' @export
+animate_right_join <- function(x, y, by, export = "gif", ...) {
+  x <- rlang::enquo(x)
+  y <- rlang::enquo(y)
+  animate_join(x, y, by, type = "right_join", export = export, ...)
+}
+
+#' @rdname animate_join
+#' @export
+animate_semi_join <- function(x, y, by, export = "gif", ...) {
+  x <- rlang::enquo(x)
+  y <- rlang::enquo(y)
+  animate_join(x, y, by, type = "semi_join", export = export, ...)
+}
+
+#' @rdname animate_join
+#' @export
+animate_anti_join <- function(x, y, by, export = "gif", ...) {
+  x <- rlang::enquo(x)
+  y <- rlang::enquo(y)
+  animate_join(x, y, by, type = "anti_join", export = export, ...)
+}

R/animate_options.R

@@ -0,0 +1,244 @@
+#' Animation Options
+#'
+#' Helper function to set animation and plotting options to be passed to
+#' [animate_plot()] and [static_plot()].
+#'
+#' @param color_header Color of the header row.
+#' @param color_other Color of the cells that are not highlighted otherwise.
+#' @param color_missing Color of the missing cells.
+#' @param color_fun A function that generates the colors for the highlighted
+#'   cells, default is [scales::brewer_pal()] Set1.
+#' @param text_color Color of the text of the cells, default is a black or
+#'   white, based on the background color of the cell.
+#' @param text_family Font family for the plot text, default is "Fira Mono". Use
+#'   [set_font_size()] to set global default font sizes.
+#' @param title_family Font family for the plot title, default is "Fira Mono".
+#'   Use [set_font_size()] to set global default font sizes.
+#' @param text_size Font size of the plot text, default is 5.
+#' @param title_size Font size of the plot title, default is 17.
+#' @param cell_width Width of a cell, default is 1.
+#' @param cell_height Height of a cell, default is 1.
+#' @param ease_default Default aes easing function. See [tweenr::display_ease()]
+#'   for more options. The tidyexplain default value is `sine-in-out`.
+#' @param ease_other Additional aes easing options, specified as a named list.
+#'   List entries are named with the aesthetic to which the easeing should be
+#'   applied, consistent with [gganimate::ease_aes()]. E.g. `list(color =
+#'   "sine")`.
+#' @param enter Enter fading function applied to objects in the animation. See
+#'   [gganimate::enter_exit] for a complete list of options. The tidyexplain
+#'   default is [gganimate::enter_fade()].
+#' @param exit Exit fading function applied to objects in the animation. See
+#'   [gganimate::enter_exit] for a complete list of options. The tidyexplain
+#'   default is [gganimate::exit_fade()].
+#' @inheritParams gganimate::transition_states
+#' @export
+anim_options <- function(
+  transition_length = NULL,
+  state_length = NULL,
+  ease_default = NULL,
+  ease_other   = NULL,
+  enter        = NULL,
+  exit         = NULL,
+  text_family  = NULL,
+  title_family = NULL,
+  text_size    = NULL,
+  title_size   = NULL,
+  color_header = NULL,
+  color_other  = NULL,
+  color_missing = NULL,
+  color_fun    = NULL,
+  text_color   = NULL,
+  cell_width   = NULL,
+  cell_height  = NULL,
+  ...
+){
+  enter_name <- if (!missing(enter)) rlang::quo_name(rlang::enquo(enter))
+  exit_name <- if (!missing(exit))   rlang::quo_name(rlang::enquo(exit))
+  ao <- list(
+    transition_length = transition_length,
+    state_length = state_length,
+    ease_default = ease_default,
+    ease_other   = ease_other,
+    enter        = if (!is.null(enter)) setNames(list(enter), enter_name),
+    exit         = if (!is.null(exit))  setNames(list(exit), exit_name),
+    text_family  = text_family,
+    text_size    = text_size,
+    title_family = title_family,
+    title_size   = title_size,
+    color_header = color_header,
+    color_other  = color_other,
+    color_missing = color_missing,
+    color_fun    = color_fun,
+    text_color   = text_color,
+    cell_width   = cell_width,
+    cell_height  = cell_height,
+    ...
+  )
+  ao <- purrr::compact(ao)
+  structure(ao, class = "anim_opts")
+}
+
+
+# Global Animation Options Setters and Getters ----------------------------
+
+#' @describeIn anim_options Set default animation options for the current session.
+#' @param anim_opts An [anim_options()] options list.
+#' @export
+set_anim_options <- function(anim_opts = anim_options()) {
+  stopifnot(is.anim_opts(anim_opts))
+  ao_old <- plot_settings$anim_opts
+  plot_settings$anim_opts <- merge(anim_opts, plot_settings$anim_opts)
+  invisible(ao_old)
+}
+
+get_anim_opt <- function(anim_opt = NULL) {
+  if (is.null(anim_opt)) return(plot_settings$anim_opts)
+  if (anim_opt %in% c("text_size", "title_size")) rlang::abort(
+    "Use get_text_size() or get_title_size()"
+  )
+  plot_settings$anim_opts[[anim_opt]] %||% plot_settings$default[[anim_opt]]
+}
+
+
+# Animation Options Methods -----------------------------------------------
+
+#' @export
+print.anim_opts <- function(x) {
+  # Replace ggproto (enter/exit functions) with their names
+  if ("enter" %in% names(x)) x$enter <- paste("ggproto:", names(x$enter))
+  if ("exit"  %in% names(x)) x$exit  <- paste("ggproto:", names(x$exit))
+  anim_opts <- capture.output(str(x, no.list = TRUE))
+  cat(
+    paste0("<anim_options: ", length(x), " options>"),
+    anim_opts, sep = "\n"
+  )
+}
+
+#' @export
+is.anim_opts <- function(ao) inherits(ao, "anim_opts")
+
+
+# Fill, Validate, Merge Animation Options ---------------------------------
+
+# Fills in default animation options
+fill_anim_opts <- function(ao) {
+  ao$transition_length <- ao$transition_length %||% get_anim_opt("transition_length")
+  ao$state_length <- ao$state_length %||% get_anim_opt("state_length")
+  ao$ease_default <- ao$ease_default %||% get_anim_opt("ease_default")
+  ao$ease_other   <- ao$ease_other   %||% get_anim_opt("ease_other")
+  ao$enter        <- ao$enter        %||% get_anim_opt("enter")
+  ao$exit         <- ao$exit         %||% get_anim_opt("exit")
+  ao$text_family  <- ao$text_family  %||% get_anim_opt("text_family")
+  ao$title_family <- ao$title_family %||% get_anim_opt("title_family")
+  ao$color_header <- ao$color_header %||% get_anim_opt("color_header")
+  ao$color_other  <- ao$color_other  %||% get_anim_opt("color_other")
+  ao$color_missing <- ao$color_missing %||% get_anim_opt("color_missing")
+  ao$color_fun    <- ao$color_fun    %||% get_anim_opt("color_fun")
+  ao$text_color   <- ao$text_color   %||% get_anim_opt("text_color")
+  ao$cell_width   <- ao$cell_width   %||% get_anim_opt("cell_width")
+  ao$cell_height  <- ao$cell_height  %||% get_anim_opt("cell_height")
+
+  ao
+}
+
+validate_anim_opts <- function(ao, quiet = FALSE, strict = getOption("tidyexplain.strict_dots", FALSE)) {
+  if (!inherits(ao, "anim_opts")) {
+    rlang::warn("Use `anim_options()` to set `anim_opts`")
+  }
+  ao <- fill_anim_opts(ao)
+  stopifnot(is.ggproto(ao$enter[[1]]), is.ggproto(ao$exit[[1]]))
+  extra_names <- setdiff(names(ao), names(formals(anim_options)))
+  if (!quiet && length(extra_names)) {
+    extra_names <- paste0(sprintf("`%s`", extra_names), collapse = ", ")
+    msg <- paste("Unknown animation options will be ignored:", extra_names)
+    if (isTRUE(strict)) rlang::abort(msg) else rlang::warn(msg)
+  }
+  invisible(ao)
+}
+
+merge.anim_opts <- function(ao_new, ao_base = anim_options()) {
+  ao_new  <- purrr::discard(ao_new, is.null)
+  ao_base <- purrr::discard(ao_base, is.null)
+  unique_base <- setdiff(names(ao_base), names(ao_new))
+  ao <- append(ao_new, ao_base[unique_base])
+  ao <- ao[names(formals(anim_options))]
+  ao <- purrr::discard(ao, is.null)
+  class(ao) <- "anim_opts"
+  ao
+}
+
+
+# Default Animation Options for Verb Families -----------------------------
+
+default_anim_opts <- function(family, ao_custom = NULL) {
+  family_options <- c("join", "set", "gather", "spread")
+  family <- match.arg(family, family_options, several.ok = FALSE)
+  ao_default <- switch(
+    family,
+    "gather" = anim_options(enter = enter_fade(), exit = exit_fade(),
+                            ease_default = "sine-in-out",
+                            ease_other = list(y = "cubic-out", x = "cubic-in")),
+    "spread" = anim_options(enter = enter_fade(), exit = exit_fade(),
+                            ease_default = "sine-in-out",
+                            ease_other = list(y = "cubic-out", x = "cubic-in")),
+    anim_options()
+  )
+  if (is.null(ao_custom)) {
+    # User set globals override defaults
+    ao_custom <- get_anim_opt()
+  } else {
+    # Opts from function call override user-set globals
+    ao_custom <- merge(ao_custom, get_anim_opt())
+  }
+  # function > user-set global > default (> global default)
+  if (!is.null(ao_custom)) merge(ao_custom, ao_default) else ao_default
+}
+
+# Font Size Setters and Getters -------------------------------------------
+
+#' Set Default Text Sizes for Animation Plots
+#'
+#' Sets the default text sizes for the animated and static plots produced by
+#' this package during the current session.
+#'
+#' @param text_size Font size of value labels inside the data frame squares
+#' @param title_size Font size of the function call or plot title
+#' @export
+set_font_size <- function(text_size = NULL, title_size = NULL) {
+  old <- list()
+  if (!is.null(text_size)) old$text_size <- set_text_size(text_size)
+  if (!is.null(title_size)) old$title_size <- set_title_size(title_size)
+  invisible(old)
+}
+
+#' @describeIn set_font_size Get current global font sizes
+#' @export
+get_font_size <- function() {
+  list("text_size"  = get_text_size(), "title_size" = get_title_size())
+}
+
+set_text_size <- function(size) {
+  old <- plot_settings$text_size
+  set_anim_options(anim_options(text_size = size))
+  invisible(old)
+}
+
+set_title_size <- function(size) {
+  old <- plot_settings$title_size
+  set_anim_options(anim_options(title_size = size))
+  invisible(old)
+}
+
+get_text_size <- function(x = NULL) {
+  if (!is.null(x)) return(x)
+  plot_settings$anim_opts$text_size %||%
+    getFromNamespace("theme_void", "ggplot2")()$text$size %||%
+    plot_settings$default$text_size
+}
+
+get_title_size <- function(x = NULL) {
+  if (!is.null(x)) return(x)
+  plot_settings$anim_opts$title_size %||%
+    getFromNamespace("theme_void", "ggplot2")()$plot.title$size %||%
+    plot_settings$default$title_size
+}

R/animate_sets.R

@@ -0,0 +1,133 @@
+#' Animates a set operation
+#'
+#' Functions to visualise the set operations either static as a ggplot, or
+#' dynamic as a gif.
+#'
+#' @param x the x dataset
+#' @param y the y dataset
+#' @param export the export type, either gif, first or last. The latter two
+#'              export ggplots of the first/last state of the join
+#' @param type type of the set, i.e., intersect, setdiff, etc.
+#' @param ... further argument passed to anim_options()
+#'
+#' @return either a gif or a ggplot
+#'
+#' @seealso \code{\link[dplyr]{setops}}
+#'
+#' @examples
+#' x <- data_frame(x = c(1, 1, 2), y = c("a", "b", "a"))
+#' y <- data_frame(x = c(1, 2), y = c("a", "b"))
+#'
+#' # Animate the first or last state of the set
+#' animate_union(x, y, export = "first")
+#' animate_union(x, y, export = "last")
+#'
+#' # animate the transition as a gif (default)
+#' \donttest{
+#' animate_union(x, y, export = "gif")
+#' }
+#'
+#' # different options include
+#' \donttest{
+#' animate_union(x, y)
+#' animate_union_all(x, y)
+#' animate_intersect(x, y)
+#' animate_setdiff(x, y)
+#'
+#' # further arguments can be passed to all animate_* functions
+#' animate_union(
+#'   x, y,
+#'   text_size = 5, title_size = 25,
+#'   color_header = "black",
+#'   color_fun = viridis::viridis
+#' )
+#' }
+#'
+#' # Save the results
+#' \dontrun{
+#' # to save the ggplot, use
+#' un <- animate_union(x, y, by = "id", export = "last")
+#' ggsave("union.pdf", un)
+#'
+#' animate_union(x, y, by = "id", export = "gif")
+#' # to save the gif, use
+#' un <- animate_union(x, y, by = "id", export = "gif")
+#' anim_save(un, "union.gif")
+#' }
+animate_set <- function(
+  x, y,
+  type = c("union", "union_all", "intersect", "setdiff"),
+  export = c("gif", "first", "last"),
+  ...
+) {
+  type   <- match.arg(type)
+  export <- match.arg(export)
+  x_name <- get_input_text(x)
+  y_name <- get_input_text(y)
+  data   <- make_named_data(x, y)
+
+  col_names <- purrr::map(data, names)
+
+  if (!all(names(data$x) %in% names(data$y)) && ncol(data$x) == ncol(data$y))
+    stop("x and y must have the same variables/column-names")
+
+  title <- sprintf(paste0(type, "(%s, %s)"), x_name, y_name)
+
+  if (type %in% c("union", "intersect", "setdiff")) {
+    data <- purrr::map(data, dplyr::distinct)
+  }
+
+  if (type == "union_all") {
+    ll <- process_join(data$x, data$y, by = names(data$x), fill = FALSE, ...)
+    ll <- purrr::map(ll, ~ mutate(., .id_long = paste(.id_long, .side, sep = "-")))
+  } else {
+    ll <- process_join(data$x, data$y, by = names(data$x), ...)
+  }
+
+  step0 <- bind_rows(ll$x, ll$y) %>% mutate(.frame = 0, .alpha = 1)
+
+  step1 <- move_together(ll$x, ll$y, type) %>% mutate(.frame = 1)
+
+  all <- bind_rows(step0, step1)
+
+  if (export == "gif") {
+    animate_plot(all, title, ...)
+  } else if (export == "first") {
+    title <- ""
+    static_plot(step0, title, ...)
+  } else if (export == "last") {
+    static_plot(step1, title, ...)
+  }
+}
+
+#' @rdname animate_set
+#' @export
+animate_union <- function(x, y, export = "gif", ...) {
+  x <- rlang::enquo(x)
+  y <- rlang::enquo(y)
+  animate_set(x, y, type = "union", export = export, ...)
+}
+
+#' @rdname animate_set
+#' @export
+animate_union_all <- function(x, y, export = "gif", ...) {
+  x <- rlang::enquo(x)
+  y <- rlang::enquo(y)
+  animate_set(x, y, type = "union_all", export = export, ...)
+}
+
+#' @rdname animate_set
+#' @export
+animate_intersect <- function(x, y, export = "gif", ...) {
+  x <- rlang::enquo(x)
+  y <- rlang::enquo(y)
+  animate_set(x, y, type = "intersect", export = export, ...)
+}
+
+#' @rdname animate_set
+#' @export
+animate_setdiff <- function(x, y, export = "gif", ...) {
+  x <- rlang::enquo(x)
+  y <- rlang::enquo(y)
+  animate_set(x, y, type = "setdiff", export = export, ...)
+}

R/animate_tidyr.R

@@ -0,0 +1,123 @@
+#' Animates the gather function
+#'
+#' @param w a data_frame in the wide format
+#' @param key the key
+#' @param value the value
+#' @param ... further arguments passed to [tidyr::gather()], [process_wide()],
+#'   or [process_long()]
+#' @param detailed boolean value if the animation should show one step for each
+#'   key value
+#' @inheritParams animate_join
+#' @inheritParams anim_options
+#'
+#' @return a gif or a ggplot
+#' @export
+#'
+#' @examples
+#' wide <- data_frame(
+#'   year = 2010:2011,
+#'   Alice = c(105, 110),
+#'   Bob = c(100, 97),
+#'   Charlie = c(90, 95)
+#' )
+#' animate_gather(wide, "person", "sales", -year, export = "first")
+#' animate_gather(wide, "person", "sales", -year, export = "last")
+#'
+#' \donttest{
+#'   animate_gather(wide, "person", "sales", -year, export = "gif")
+#'   # if you want to have a less detailed animation, you can also use
+#'   animate_gather(wide, "person", "sales", -year, export = "gif", detailed = FALSE)
+#' }
+animate_gather <- function(w, key, value, ..., export = "gif", detailed = TRUE, anim_opts = anim_options()) {
+  anim_opts <- default_anim_opts("gather", anim_opts)
+  lhs <- w
+  rhs <- tidyr::gather(w, !!key, !!value, ...)
+
+  # construct the title sequence
+  wname <- deparse(substitute(w))
+  tidyr_selection <- get_quos_names(...)
+  ids <- setdiff(colnames(w), tidyselect::vars_select(colnames(w), ...))
+
+  id_string <- paste0(", ", paste(sprintf("%s", tidyr_selection), collapse = ", "))
+
+  sequence <- c(
+    current_state = "wide",
+    final_state = "long",
+    operation = sprintf("gather(%s, %s, %s%s)",
+                        wname,
+                        dput_parser(key),
+                        dput_parser(value),
+                        id_string),
+    reverse_operation = sprintf("spread(%s, %s, %s)",
+                                "long",
+                                dput_parser(key),
+                                dput_parser(value))
+  )
+
+  key_values <- rhs %>% pull(key) %>% unique()
+  lhs_proc <- process_wide(lhs, ids, key, key_values, value, ...)
+  rhs_proc <- process_long(rhs, ids, key, value, ...)
+
+  gather_spread(lhs_proc, rhs_proc, sequence = sequence, key_values = key_values,
+                export = export, detailed = detailed, ..., anim_opts = anim_opts)
+}
+
+
+#' Animates the spread function
+#'
+#' @param l a data_frame in the long/tidy format
+#' @param ... further arguments passed to [process_long] or [process_wide]
+#' @inheritParams animate_gather
+#' @inheritParams animate_join
+#' @inheritParams anim_options
+#'
+#' @return a ggplot or a gif
+#' @export
+#'
+#' @examples
+#' long <- data_frame(
+#'   year = c(2010L, 2011L, 2010L, 2011L, 2010L, 2011L),
+#'   person = c("Alice", "Alice", "Bob", "Bob", "Charlie", "Charlie"),
+#'   sales = c(105, 110, 100, 97, 90, 95)
+#' )
+#' animate_spread(long, key = "person", value = "sales", export = "first")
+#' animate_spread(long, key = "person", value = "sales", export = "last")
+#'
+#' \donttest{
+#'   animate_spread(long, key = "person", value = "sales", export = "gif")
+#'   # if you want to have a less detailed animation, you can also use
+#'   animate_spread(long, key = "person", value = "sales", export = "gif", detailed = FALSE)
+#' }
+animate_spread <- function(l, key, value, export = "gif", detailed = TRUE, ..., anim_opts = anim_options()) {
+  anim_opts <- default_anim_opts("spread", anim_opts)
+
+  lhs <- l
+  rhs <- tidyr::spread(l, key = key, value = value)
+
+  # construct the title sequence
+  lname <- deparse(substitute(l))
+  ids <- names(lhs)
+  ids <- ids[!ids %in% c(key, value)]
+
+  id_string <- paste0(", ", paste(sprintf("-%s", ids), collapse = ", "))
+
+  sequence <- c(
+    current_state = "long",
+    final_state = "wide",
+    operation = sprintf("spread(%s, %s, %s)",
+                        lname,
+                        dput_parser(key),
+                        dput_parser(value)),
+    reverse_operation = sprintf("gather(%s, %s, %s%s)",
+                                "wide",
+                                dput_parser(key),
+                                dput_parser(value),
+                                id_string)
+  )
+
+  lhs_proc <- process_long(lhs, ids, key, value, ...)
+  rhs_proc <- process_wide(rhs, ids, key, value, ...)
+
+  key_values <- lhs %>% pull(key) %>% unique()
+  gather_spread(lhs_proc, rhs_proc, sequence, key_values, export, detailed, ..., anim_opts = anim_opts)
+}

R/anti_join.R

@@ -1,48 +0,0 @@
-source(here::here("R/00_base_join.R"))
-
-initial_join_dfs <- initial_join_dfs %>%
-  arrange(.x, .y) %>%
-  mutate(.obj = row_number(), .obj = .obj + 90 * as.integer(.id == "y"))
-
-aj_step2 <- initial_join_dfs %>%
-  filter(.id == "x" | value %in% paste(1:2)) %>%
-  mutate(frame = 2,
-         .x = ifelse(.id == "y", 2.5, .x + 1.5),
-         alpha = case_when(
-           .x > 3 && .id == "x" ~ 0.5,
-           .y > -2.5 ~ 0.25,
-           TRUE ~ 1
-         ))
-
-aj_step3 <- aj_step2 %>%
-  filter(alpha == 1) %>%
-  mutate(frame = 3)
-
-aj_step4 <- aj_step2 %>%
-  filter(alpha == 1) %>%
-  mutate(frame = 4, .y = -1)
-
-aj <- bind_rows(
-  initial_join_dfs,
-  aj_step2,
-  aj_step3,
-  aj_step4
-) %>%
-  mutate(
-    alpha = ifelse(is.na(alpha), 1, alpha),
-    .obj = ifelse(value == 4, 0, .obj)
-  ) %>%
-  arrange(.obj, frame) %>%
-  plot_data("anti_join(x, y)") %>%
-  animate_plot(transition_length = c(2, 1, 2),
-               state_length = c(1, 0, 0, 1))
-
-aj <- animate(aj)
-anim_save(here::here("images", "anti-join.gif"), aj)
-
-aj_g <- anti_join(x, y, by = "id") %>%
-  proc_data() %>%
-  mutate(.x = .x + 1.5) %>%
-  plot_data_join("anti_join(x, y)")
-
-save_static_plot(aj_g, "anti-join")

R/full_join.R

@@ -1,29 +0,0 @@
-source(here::here("R/00_base_join.R"))
-
-fj_joined_df <- full_join(x, y, "id") %>%
-  proc_data("x") %>%
-  mutate(.id = ifelse(value %in% c("4", "y4"), "y", .id)) %>%
-  mutate(frame = 2, .x = .x + 1)
-
-fj_extra_blocks <- inner_join(x, y, "id") %>%
-  select(id) %>%
-  proc_data("y") %>%
-  mutate(frame = 2, .x = .x + 1)
-
-fj <- initial_join_dfs %>%
-  bind_rows(fj_joined_df, fj_extra_blocks) %>%
-  plot_data("full_join(x, y)") +
-  transition_states(frame, transition_length = 2, state_length = 1) +
-  enter_appear() +
-  exit_disappear(early = TRUE) +
-  ease_aes("sine-in-out")
-
-fj <- animate(fj)
-anim_save(here::here("images", "full-join.gif"), fj)
-
-fj_g <- full_join(x, y, "id") %>%
-  proc_data() %>%
-  mutate(.x = .x + 1) %>%
-  plot_data_join("full_join(x, y)", ylims = ylim(-4.5, -0.5))
-
-save_static_plot(fj_g, "full-join")

R/inner_join.R

@@ -1,29 +0,0 @@
-source(here::here("R/00_base_join.R"))
-
-ij_joined_df <- inner_join(x, y, "id")
-ij_joined_df <- bind_rows(
-  proc_data(ij_joined_df, "x"),
-  proc_data(ij_joined_df, "y")
-) %>%
-  filter(!(label == "x" & .id == "y") & !(label == "y" & .id == "x")) %>%
-  mutate(frame = 2, .x = .x + 1)
-
-ij <- bind_rows(
-  initial_join_dfs,
-  ij_joined_df
-) %>%
-  mutate(removed = value %in% c("3", "4", "x3", "y4"),
-         removed = as.integer(removed)) %>%
-  arrange(desc(frame), removed, desc(.id)) %>%
-  plot_data("inner_join(x, y)") %>%
-  animate_plot()
-
-ij <- animate(ij)
-anim_save(here::here("images", "inner-join.gif"), ij)
-
-ij_g <- inner_join(x, y, by = "id") %>%
-  proc_data() %>%
-  mutate(.x = .x + 1) %>%
-  plot_data_join("inner_join(x, y)")
-
-save_static_plot(ij_g, "inner-join")

R/intersect.R

@@ -1,28 +0,0 @@
-source(here::here("R/00_base_set.R"))
-
-ins_df <- intersect(x,y)
-ins_step2 <-
-  bind_rows(
-    proc_data_set(ins_df, "x"),
-    proc_data_set(ins_df, "y")
-  ) %>%
-  filter(.y == -1) %>%
-  mutate(frame = 2, .x = .x + 1.5)
-
-ins <-
-  initial_set_dfs %>%
-  bind_rows(ins_step2) %>%
-  arrange(desc(frame)) %>%
-  plot_data_set("intersect(x, y)") %>%
-  animate_plot()
-
-ins <- animate(ins)
-
-anim_save(here::here("images", "intersect.gif"), ins)
-
-ins_g <- intersect(x, y) %>%
-  proc_data_set() %>%
-  mutate(.x = .x + 1.5) %>%
-  plot_data_set("intersect(x, y)")
-
-save_static_plot(ins_g, "intersect")

R/left_join.R

@@ -1,27 +0,0 @@
-source(here::here("R/00_base_join.R"))
-
-lj_joined_dfs <- left_join(x, y, "id") %>%
-  proc_data("x") %>%
-  mutate(frame = 2, .x = .x + 1)
-
-lj_extra_blocks <- inner_join(x, y, "id") %>%
-  select(id) %>%
-  proc_data("y") %>%
-  mutate(frame = 2, .x = .x + 1)
-
-lj <- bind_rows(
-  initial_join_dfs,
-  lj_joined_dfs,
-  lj_extra_blocks
-) %>%
-  mutate(color = ifelse(is.na(value), "#ffffff", color)) %>%
-  arrange(value) %>%
-  plot_data("left_join(x, y)") %>%
-  animate_plot()
-
-lj <- animate(lj)
-anim_save(here::here("images", "left-join.gif"), lj)
-
-lj_g <- plot_data_join(lj_joined_dfs, "left_join(x, y)")
-
-save_static_plot(lj_g, "left-join")

R/left_join_extra.R

@@ -1,71 +0,0 @@
-source(here::here("R/00_base_join.R"))
-
-y_extra <- bind_rows(y, data_frame(id = 2, y = "y5"))
-
-# I manually linked objects together, it was late and this was easier...
-anim_df <- tibble::tribble(
-  ~.y, ~label, ~value, ~.x, ~.id,    ~color, ~frame, ~obj,
-  -1L,   "id",    "1",   1,  "x", "#E41A1C",      1,    1,
-  -2L,   "id",    "2",   1,  "x", "#377EB8",      1,    2,
-  -2L,   "id",    "2",   1,  "x", "#377EB8",      1,    3,
-  -3L,   "id",    "3",   1,  "x", "#4DAF4A",      1,    4,
-  -1L,    "x",   "x1",   2,  "x", "#d0d0d0",      1,    5,
-  -2L,    "x",   "x2",   2,  "x", "#d0d0d0",      1,    6,
-  -3L,    "x",   "x3",   2,  "x", "#d0d0d0",      1,    8,
-  -2L,    "x",   "x2",   2,  "x", "#d0d0d0",      1,    7,
-  -1L,   "id",    "1",   4,  "y", "#E41A1C",      1,    9,
-  -2L,   "id",    "2",   4,  "y", "#377EB8",      1,    10,
-  -3L,   "id",    "4",   4,  "y", "#984EA3",      1,    99,
-  -4L,   "id",    "2",   4,  "y", "#377EB8",      1,    11,
-  -1L,    "y",   "y1",   5,  "y", "#d0d0d0",      1,    12,
-  -2L,    "y",   "y2",   5,  "y", "#d0d0d0",      1,    13,
-  -3L,    "y",   "y4",   5,  "y", "#d0d0d0",      1,    98,
-  -4L,    "y",   "y5",   5,  "y", "#d0d0d0",      1,    14,
-  -1L,   "id",    "1",   2,  "x", "#E41A1C",      2,    1,
-  -2L,   "id",    "2",   2,  "x", "#377EB8",      2,    2,
-  -3L,   "id",    "2",   2,  "x", "#377EB8",      2,    3,
-  -4L,   "id",    "3",   2,  "x", "#4DAF4A",      2,    4,
-  -1L,    "x",   "x1",   3,  "x", "#d0d0d0",      2,    5,
-  -2L,    "x",   "x2",   3,  "x", "#d0d0d0",      2,    6,
-  -3L,    "x",   "x2",   3,  "x", "#d0d0d0",      2,    7,
-  -4L,    "x",   "x3",   3,  "x", "#d0d0d0",      2,    8,
-  -1L,    "y",   "y1",   4,  "x", "#d0d0d0",      2,    12,
-  -2L,    "y",   "y2",   4,  "x", "#d0d0d0",      2,    13,
-  -3L,    "y",   "y5",   4,  "x", "#d0d0d0",      2,    14,
-  -1L,   "id",    "1",   2,  "y", "#E41A1C",      2,    9,
-  -2L,   "id",    "2",   2,  "y", "#377EB8",      2,    10,
-  -3L,   "id",    "2",   2,  "y", "#377EB8",      2,    11
-)
-
-lj_extra <- anim_df %>%
-  arrange(obj, frame) %>%
-  plot_data("left_join(x, y)") %>%
-  animate_plot()
-
-lj_extra <- animate(lj_extra)
-anim_save(here::here("images", "left-join-extra.gif"), lj_extra)
-
-## Save static images
-df_names <- data_frame(
-  .x = c(1.5, 4.5), .y = 0.25,
-  value = c("x", "y"),
-  size = 12,
-  color = "black"
-)
-
-g_input <- proc_data(y_extra) %>%
-  mutate(.x = .x + 3) %>%
-  bind_rows(proc_data(x)) %>%
-  plot_data() +
-  geom_text(data = df_names, family = "Fira Mono", size = 24) +
-  annotate("text", label = "↑ duplicate keys in y", x = 4.5, y = -4.75,
-           family = "Fira Sans", color = "grey45")
-
-save_static_plot(g_input, "left-join-extra-input")
-
-lj_g <- left_join(x, y_extra, by = "id") %>%
-  proc_data() %>%
-  mutate(.x = .x + 1) %>%
-  plot_data_join("left_join(x, y)", ylims = ylim(-4.5, -0.5))
-
-save_static_plot(lj_g, "left-join-extra")

R/move_together.R

@@ -0,0 +1,105 @@
+
+#' Combines two processed datasets and combines them for a given method
+#'
+#' @param lhs the left-hand side dataset
+#' @param rhs the righ-hand side dataset
+#' @param type a string of the desired combination method, allowed are all dplyr
+#'             joins or sets
+#'
+#' @return  processed dataset of the combined values
+#'
+#' @examples
+#' NULL
+move_together <- function(lhs, rhs, type) {
+
+  all <- bind_rows(lhs, rhs)
+
+  # separate column and row-filter (ids)
+  x_cols <- dplyr::distinct(lhs, .col)
+  y_cols <- dplyr::distinct(rhs, .col)
+
+  # separate header columns from ids and treat them as columns
+  x_ids <- dplyr::distinct(lhs, .id, .id_long)
+  y_ids <- dplyr::distinct(rhs, .id, .id_long)
+
+  x_headers <- filter(x_ids, grepl("^\\.header", .id_long))
+  y_headers <- filter(y_ids, grepl("^\\.header", .id_long))
+
+  x_ids <- x_ids %>% filter(!grepl("^\\.header", .id_long))
+  y_ids <- y_ids %>% filter(!grepl("^\\.header", .id_long))
+
+  # assign two combiner functions depending on the type
+  # one for combining the columns (col_combiner)
+  # one for combining the rows (row_combiner)
+  if (type == "full_join") {
+    col_combiner <- dplyr::full_join
+    row_combiner <- dplyr::full_join
+  } else if (type == "inner_join") {
+    col_combiner <- dplyr::full_join
+    row_combiner <- dplyr::inner_join
+  } else if (type == "left_join") {
+    col_combiner <- dplyr::full_join
+    row_combiner <- dplyr::left_join
+  } else if (type == "right_join") {
+    col_combiner <- dplyr::full_join
+    row_combiner <- dplyr::right_join
+  } else if (type == "semi_join") {
+    col_combiner <- dplyr::left_join
+    row_combiner <- dplyr::semi_join
+  } else if (type == "anti_join") {
+    col_combiner <- dplyr::left_join
+    row_combiner <- dplyr::anti_join
+  } else if (type == "union") {
+    col_combiner <- dplyr::full_join
+    row_combiner <- dplyr::union
+  } else if (type == "union_all") {
+    col_combiner <- dplyr::full_join
+    row_combiner <- dplyr::union_all
+  } else if (type == "intersect") {
+    col_combiner <- dplyr::full_join
+    row_combiner <- dplyr::intersect
+  } else if (type == "setdiff") {
+    col_combiner <- dplyr::full_join
+    row_combiner <- dplyr::anti_join
+  } else if (type == "bind_rows") {
+    col_combiner <- dplyr::full_join
+    row_combiner <- dplyr::bind_rows
+  } else if (type == "bind_cols") {
+    col_combiner <- dplyr::full_join
+    row_combiner <- dplyr::left_join
+  } else {
+    stop("Unknown func")
+  }
+
+  take_cols <- col_combiner(x_cols, y_cols, by = ".col")
+  take_ids  <- row_combiner(x_ids, y_ids, by = c(".id", ".id_long"))
+  take_headers <- col_combiner(x_headers, y_headers, by = c(".id", ".id_long"))
+
+  take_ids <- bind_rows(take_headers, take_ids)
+
+  take <- tidyr::crossing(take_ids, take_cols)
+
+  mid <- (2 + length(unique(lhs$.col)) + length(unique(rhs$.col))) / 2
+  xvals <- 1:nrow(take_cols)
+  xvals <- xvals - mean(xvals) + mid
+  names(xvals) <- pull(take_cols, .col)
+
+  yvals <- cumsum(ifelse(grepl("^\\.header", take_ids$.id_long), 0, -1))
+  names(yvals) <- pull(take_ids, .id_long)
+
+  take_vals <- semi_join(all, take %>% select(".id", ".col"),
+                         by = c(".id", ".col")) %>%
+    mutate(.alpha = 1,
+           .x = xvals[.col],
+           .y = yvals[.id_long])
+
+  bind_rows(
+    # take,
+    take_vals,
+    # fade in place:
+    all %>% filter(!.id_long %in% take_ids$.id_long) %>% mutate(.alpha = 0),
+    # moving fade or fade in place as well:
+    all %>% filter(.id_long %in% take_ids$.id_long & !.col %in% take_cols$.col) %>%
+      mutate(.alpha = 0)
+  )
+}

R/plot_helpers.R

@@ -0,0 +1,76 @@
+#' Animate a Plot
+#'
+#' @param d a processed dataset
+#' @param title the title of the plot
+#' @param anim_opts Animation options generated with [anim_options()]. Overrides
+#'   any options set in `...`.
+#' @return a `gganim` object
+#' @examples
+#' NULL
+animate_plot <- function(
+  d,
+  title = "",
+  ...,
+  anim_opts = anim_options(...)
+) {
+  ao <- validate_anim_opts(anim_opts)
+  ease_opts <- if (!is.null(ao$ease_other)) {
+    ao$ease_other$default <- ao$ease_default
+    ao$ease_other
+    } else list(default = ao$ease_default)
+  ao_ease_aes <- do.call(ease_aes, ease_opts)
+
+  static_plot(d, title, anim_opts = ao) +
+    transition_states(.frame, ao$transition_length, ao$state_length) +
+    ao$enter[[1]] +
+    ao$exit[[1]] +
+    ao_ease_aes
+}
+
+
+#' Prints the tiles for a processed dataset statically
+#'
+#' @inheritParams animate_plot
+#' @inheritDotParams anim_options
+#'
+#' @return a ggplot
+#'
+#' @examples
+#' NULL
+static_plot <- function(
+  d,
+  title = "",
+  ...,
+  anim_opts = anim_options(...)
+) {
+  ao <- validate_anim_opts(anim_opts)
+  text_size <- get_text_size(ao$text_size)
+  title_size <- get_title_size(ao$title_size)
+
+  if (!".alpha" %in% names(d)) d <- d %>% mutate(.alpha = 1)
+  if (!".textcolor" %in% names(d))
+    d <- d %>% mutate(.textcolor = choose_text_color(.color))
+
+  if (".id_long" %in% names(d)) {
+    d <- d %>% mutate(.item_id = paste(.id_long, .col, sep = "-"))
+  } else {
+    # tidyr
+    d <- d %>% mutate(.item_id = .id)
+  }
+
+  width <- ao$cell_width %||% 1
+  height <- ao$cell_height %||% 1
+
+  ggplot(d, aes(x = .x * width, y = .y * height, fill = .color, alpha = .alpha,
+                group = .item_id)) +
+    geom_tile(width = 0.9 * width, height = 0.9 * height) +
+    coord_equal() +
+    geom_text(data = d %>% filter(!is.na(.val)), aes(label = .val, color = .textcolor),
+              family = ao$text_family, size = text_size) +
+    scale_fill_identity() +
+    scale_color_identity() +
+    scale_alpha_identity() +
+    labs(title = title) +
+    theme_void() +
+    theme(plot.title = element_text(family = ao$title_family, hjust = 0.5, size = title_size))
+}

R/process_data_helpers.R

@@ -0,0 +1,155 @@
+
+#' Preprocess data
+#'
+#' @param x a left dataset
+#' @param y a right dataset
+#' @param by a by argument for joins / set operations
+#' @param fill if missing ids should be filled
+#' @param ... further arguments passed to add_color
+#' @param ao anim_options()
+#'
+#' @return a preprocessed dataset
+#'
+#' @examples
+#' NULL
+process_join <- function(x, y, by, fill = TRUE, ...,
+                         ao = anim_options(...)) {
+
+  #' test for
+  #' a <- c("unique", "mult", "mult", "also unique")
+  #' add_duplicate_number(a)
+  add_duplicate_number <- function(a) {
+    data_frame(v = a) %>%
+      group_by(v) %>%
+      mutate(id = paste(v, 1:n(), sep = "-")) %>%
+      pull(id)
+  }
+
+  x <- x %>%
+    tidyr::unite(dplyr::one_of(by), col = ".id", remove = FALSE) %>%
+    mutate(.id_long = add_duplicate_number(.id))
+
+  y <- y %>%
+    tidyr::unite(dplyr::one_of(by), col = ".id", remove = FALSE)  %>%
+    mutate(.id_long = add_duplicate_number(.id))
+
+  ids <- dplyr::union(x %>% dplyr::select(.id, .id_long),
+                      y %>% dplyr::select(.id, .id_long))
+
+  x_ <- process_data_join(x, ids, by, fill = fill, ao = ao)
+  y_ <- process_data_join(y, ids, by, fill = fill, ao = ao) %>%
+    mutate(.x = .x + ncol(x) - 1)
+
+  list(x = x_, y = y_)
+}
+
+
+#' Processes the data
+#'
+#' @param x a preprocessed dataset
+#' @param ids a data_frame of ids (.id and .id_long)
+#' @param by a vector of by-arguments
+#' @param width the width of the tiles
+#' @param side the side (x or y, lhs or rhs, etc)
+#' @param fill if missing ids should be filled
+#' @param ... further arguments passed to add_color
+#' @param ao anim_options
+#'
+#' @return a data_frame including all necessary information
+#'
+#' @examples
+#' NULL
+process_data_join <- function(x, ids, by, width = 1, side = NA, fill = TRUE,
+                              ...,
+                              ao = anim_options(...)) {
+  if (is.na(side)) side <- deparse(substitute(x))
+
+  x_names <- names(x)[grepl("^[^\\.]", names(x))]
+  x_keys <- 1:length(x_names)
+  names(x_keys) <- x_names
+
+  special_vars <- names(x)[grepl("^\\.", names(x))]
+
+  x <- x %>%
+    mutate(.r = row_number()) %>%
+    tidyr::gather_(key = ".col", value = ".val", names(x)[grepl("^[^.]", names(x))]) %>%
+    mutate(.x = x_keys[.col],
+           .y = -.r) %>%
+    bind_rows(data_frame(.id = ".header",
+                         .id_long = paste(".header", x_names, sep = "_"),
+                         .r = 0,
+                         .col = x_names,
+                         .val = x_names,
+                         .x = x_keys, .y = 0), .) %>%
+    mutate(.width = width,
+           .side = side)
+
+  # if there are multiple values in the ids (-2, -3 etc) but they are not present
+  # in x, because it is in the second/other dataset, add these values here
+  id_long <- ids$.id_long
+  mis_ids <- id_long[!id_long %in% x$.id_long]
+  # if the missing value is a -1, that means the missing value comes not from
+  # missing dublicate ids
+  mis_ids <- mis_ids[grepl("[^-1]$", mis_ids)]
+  if (length(mis_ids) > 0 && fill) {
+    mis_ids_short <- gsub("-[0-9]+$", "", mis_ids)
+
+    # insert the missing ids at the right place
+    for (i in mis_ids_short) {
+      irow <- (1:nrow(x))[x$.id == i]
+      irow <- irow[1]
+      x <- bind_rows(
+        x %>% slice(1:irow),
+        x %>% filter(.id %in% mis_ids_short) %>% mutate(.id_long = mis_ids),
+        x %>% slice((irow + 1):nrow(x))
+      )
+    }
+  }
+
+  add_color_join(x, rev(ids$.id), by, ao)
+}
+
+#' Adds Color to a processed data_frame
+#'
+#' @param x a processed data_frame
+#' @param ids a vector of ids for the color-matching
+#' @param by a vector of column names that constitute the by-argument of joins/sets
+#' @param color_header color for the header
+#' @param color_other color for "inactive" values
+#' @param color_missing color for missing values
+#' @param color_fun the function to generate the colors
+#' @param text_color the color for the text inside the tiles,
+#'         defaults to white/black depending on tile color
+#' @param ...
+#'
+#' @return the processed data_frame with a new column .color
+#'
+#' @examples
+#' NULL
+add_color_join <- function(x, ids, by, ao, ...) {
+
+  color_header <- ao$color_header %||% get_anim_opt("color_header")
+  color_other  <- ao$color_other  %||% get_anim_opt("color_other")
+  color_missing <- ao$color_missing %||% get_anim_opt("color_missing")
+  color_fun    <- ao$color_fun    %||% get_anim_opt("color_fun")
+  text_color   <- ao$text_color   %||% get_anim_opt("text_color")
+
+  colors <- c(color_header, color_fun(length(ids)))
+  names(colors) <- c(".header", ids)
+
+  res <- x %>%
+    mutate(
+      .color = ifelse(is.na(.val),
+                      color_missing,
+                      ifelse(.col %in% by,
+                             colors[.id],
+                             color_other)),
+      .color = ifelse(.id == ".header", color_header, .color),
+      .textcolor = text_color)
+
+  if (is.na(text_color))
+    res <- res %>% mutate(.textcolor = choose_text_color(.color))
+
+  return(res)
+}
+

R/right_join.R

@@ -1,30 +0,0 @@
-source(here::here("R/00_base_join.R"))
-
-rj_joined_dfs <- right_join(x, y, "id") %>%
-  proc_data("y") %>%
-  mutate(frame = 2, .x = .x + 1)
-
-rj_extra_blocks <- inner_join(x, y, "id") %>%
-  select(id) %>%
-  proc_data("x") %>%
-  mutate(frame = 2, .x = .x + 1)
-
-rj <- bind_rows(
-  initial_join_dfs,
-  rj_joined_dfs,
-  rj_extra_blocks
-) %>%
-  filter(!is.na(value)) %>%
-  mutate(
-    .id = ifelse(label == "x", label, .id),
-    removed = as.integer(grepl("3", value))
-  ) %>%
-  arrange(removed, value, .id, frame) %>%
-  plot_data("right_join(x, y)") %>%
-  animate_plot()
-
-rj <- animate(rj)
-anim_save(here::here("images", "right-join.gif"), rj)
-
-rj_g <- plot_data(rj_joined_dfs, "right_join(x, y)")
-save_static_plot(rj_g, "right-join")

R/semi_join.R

@@ -1,30 +0,0 @@
-source(here::here("R/00_base_join.R"))
-
-sj_joined_df <- semi_join(x, y, "id") %>%
-  proc_data("x") %>%
-  mutate(frame = 2, .x = .x + 1.5)
-
-sj_extra_blocks <- inner_join(x, y, "id") %>%
-  select(id) %>%
-  proc_data("y") %>%
-  mutate(frame = 2, .x = .x + 1.5)
-
-sj <- bind_rows(
-  initial_join_dfs,
-  sj_joined_df,
-  sj_extra_blocks
-) %>%
-  arrange(value) %>%
-  plot_data("semi_join(x, y)") %>%
-  animate_plot()
-
-sj <- animate(sj)
-anim_save(here::here("images", "semi-join.gif"), sj)
-
-# Static Images
-sj_g <- semi_join(x, y, "id") %>%
-  proc_data() %>%
-  mutate(.x = .x + 1.5) %>%
-  plot_data_join("semi_join(x, y)")
-
-save_static_plot(sj_g, "semi-join")

R/setdiff.R

@@ -1,102 +0,0 @@
-source(here::here("R/00_base_set.R"))
-
-# ---- setdiff(x, y) ----
-
-# Dim elements unique to y
-setd_step2 <- initial_set_dfs %>%
-  mutate(
-    frame = 2,
-    alpha = case_when(
-      .y == -1 ~ 0.55,
-      .id == "y" ~ 0.15,
-      TRUE ~ 1
-    )
-  )
-
-# Merge, dim overlapping elements
-setd_step3 <- initial_set_dfs %>%
-  filter(!(.id == "y" & .y == -2)) %>%
-  mutate(
-    frame = 3,
-    alpha = ifelse(.y == -1, 0.25, 1),
-    .x = ifelse(.id == "y", .x - 3, .x),
-    .x = .x + 1.5
-  )
-
-# Result of setdiff
-setd_step4 <- setdiff(x, y) %>%
-  proc_data_set("xy") %>%
-  mutate(frame = 4, .x = .x + 1.5)
-
-setd <- bind_rows(
-  initial_set_dfs,
-  setd_step2,
-  setd_step3,
-  setd_step4
-) %>%
-  mutate(alpha = ifelse(is.na(alpha), 1, alpha)) %>%
-  arrange(frame, desc(.y), desc(.id)) %>%
-  plot_data_set(., "setdiff(x, y)") %>%
-  animate_plot()
-
-setd <- animate(setd)
-
-anim_save(here::here("images", "setdiff.gif"), setd)
-
-setd_g <- setdiff(x, y) %>%
-  proc_data_set() %>%
-  mutate(.x = .x + 1.5) %>%
-  plot_data_set("setdiff(x, y)")
-
-save_static_plot(setd_g, "setdiff")
-
-
-# ---- setdiff(y, x) ----
-
-# Dim elements unique to x
-setd2_step2 <- initial_set_dfs %>%
-  mutate(
-    frame = 2,
-    alpha = case_when(
-      .y == -1 ~ 0.55,
-      .id == "x" ~ 0.15,
-      TRUE ~ 1
-    )
-  )
-
-# Merge, dim overlapping elements
-setd2_step3 <- initial_set_dfs %>%
-  filter(!(.id == "x" & .y <= -2)) %>%
-  mutate(
-    frame = 3,
-    alpha = ifelse(.y == -1, 0.25, 1),
-    .x = ifelse(.id == "y", .x - 3, .x),
-    .x = .x + 1.5
-  )
-
-# Result of setdiff
-setd2_step4 <- setdiff(y, x) %>%
-  proc_data_set("xy") %>%
-  mutate(frame = 4, .x = .x + 1.5)
-
-setd2 <- bind_rows(
-  initial_set_dfs,
-  setd2_step2,
-  setd2_step3,
-  setd2_step4
-) %>%
-  mutate(alpha = ifelse(is.na(alpha), 1, alpha)) %>%
-  arrange(frame, desc(.y), .id) %>%
-  plot_data_set(., "setdiff(y, x)") %>%
-  animate_plot()
-
-setd2 <- animate(setd2)
-
-anim_save(here::here("images", "setdiff-rev.gif"), setd2)
-
-setd2_g <- setdiff(x, y) %>%
-  proc_data_set() %>%
-  mutate(.x = .x + 1.5) %>%
-  plot_data_set("setdiff(y, x)")
-
-save_static_plot(setd2_g, "setdiff-rev")

R/tidyr_helpers.R

@@ -0,0 +1,355 @@
+#' Gets the ... names
+#'
+#' Used to get the -year
+#'
+#' @param ... arguments
+#'
+#' @return a vector of the names of ...
+#'
+#' @examples
+#' x <- 1:10
+#' y <- 1
+#' get_quos_names(-x)
+#' get_quos_names(x:y)
+get_quos_names <- function(...) {
+  q <- rlang::quos(...)
+  purrr::map_chr(q, rlang::quo_name)
+}
+
+#' Parses a simple vector so that it looks like its input
+#'
+#' @param x a vector
+#'
+#' @return a string
+#'
+#' @examples
+#' dput_parser("x")
+#' dput_parser(c("x", "y"))
+dput_parser <- function(x) UseMethod("dput_parser")
+
+dput_parser.character <- function(x) {
+  if (length(x) == 1) {
+    sprintf('"%s"', x)
+  } else {
+    x <- capture.output(dput(x))
+    paste(x, collapse = "")
+  }
+}
+
+#' Adds color to processed tidy data
+#'
+#' @param x a processed data-frame as outputted by process_long or process_wide
+#' @param key_values the unique key-values
+#' @param color_fun the color function
+#' @param color_header the color for the header
+#' @param ... not used
+#'
+#' @return a data-frame with the colors
+#'
+#' @examples
+#' NULL
+add_color_tidyr <- function(x, key_values,
+                            color_fun = scales::brewer_pal(type = "qual", "Set1"),
+                            color_header = "#737373",
+                            color_id = "#d0d0d0") {
+
+  color_dict <- color_fun(3)
+  names(color_dict) <- c("id", "key", "value")
+
+  x %>% mutate(.color = color_dict[.type])
+}
+
+#' Processes a wide dataframe and converts it into a dataset that can be plotted
+#'
+#' @param x a wide data frame
+#' @param ids a vector of id-variables that are already in the tidy-format
+#' @param key a vector of key-variables
+#' @param color_id the color for the id-body
+#' @param ...
+#'
+#' @return TODO
+#'
+#' @examples
+#' wide <- data_frame(
+#'   year = 2010:2011,
+#'   Alice = c(105, 110),
+#'   Bob = c(100, 97),
+#'   Charlie = c(90, 95)
+#' )
+#' process_wide(wide, ids = "year", key = "person")
+#' process_wide(wide, ids = "year", key = "person") %>% static_plot
+process_wide <- function(x, ids, key, color_id = "lightgray", ...) {
+
+  if (!all(ids %in% names(x)))
+    stop("all ids must be in x")
+
+  nr <- nrow(x)
+  nc <- ncol(x)
+  key_values <- names(x)
+  key_values <- key_values[!key_values %in% ids]
+
+  id_values <- x %>% select(dplyr::one_of(ids))
+  id_values <- id_values %>% tidyr::gather(key = ".key_map", value = ".id_map")
+
+  x <- x %>% mutate(.r = row_number()) %>%
+    tidyr::unite(dplyr::one_of(ids), col = ".id_map", remove = F)
+
+  x <- x %>%
+    gather(key = ".col", value = ".val", names(x)[grepl("^[^\\.]", names(x))]) %>%
+    mutate(.key_map = .col,
+           .type = ifelse(.col %in% ids, "id", "value"),
+           .val = as.character(.val),
+           .x = rep(1:nc, each = nr),
+           .y = -rep(1:nr, nc),
+           .header = F)
+
+  # make sure that we have one id value per key
+  tmp <- x %>% filter(.key_map %in% ids)
+  x <- bind_rows(
+    left_join(tmp %>% select(-.key_map),
+              tmp %>% select(.id_map) %>% tidyr::crossing(.key_map = key_values),
+              by = ".id_map"),
+    x %>% filter(!.key_map %in% ids)
+  )
+
+  # add header:
+  crosser <- tidyr::crossing(.id_map = as.character(id_values$.id_map),
+                      .key_map = key_values)
+  key_header <- data_frame(
+    .key_map = key_values,
+    .r = 0,
+    .col = key_values,
+    .val = key_values,
+    .type = "key",
+    .x = length(ids) + 1:length(key_values),
+    .y = 0,
+    .header = TRUE) %>%
+    left_join(crosser, by = ".key_map")
+
+  id_header <- left_join(
+    data_frame(.id_map = ids,
+               .r = 0,
+               .col = ids,
+               .val = ids,
+               .type = "id",
+               .x = 1:length(ids),
+               .y = 0,
+               .header = TRUE),
+    tidyr::crossing(.id_map = ids, .key_map = key_values),
+    by = ".id_map"
+  )
+
+  x <- bind_rows(id_header, key_header, x)
+
+  x <- x %>% tidyr::unite(.key_map, .id_map, .val, col = ".id", remove = F)
+
+  x %>%
+    add_color_tidyr(key_values = key_values) %>%
+    mutate(.alpha = ifelse(.header == TRUE, 1, 0.6))
+}
+
+#' Processes a long dataframe and converts it into a dataset that can be plotted
+#'
+#' @param x a long data frame
+#' @param ids a vector of id-variables that are already in the tidy-format
+#' @param key a vector of key-variables
+#' @param ...
+#'
+#' @return TODO
+#'
+#' @examples
+#' long <- data_frame(
+#'   year = c(2010L, 2011L, 2010L, 2011L, 2010L, 2011L),
+#'   person = c("Alice", "Alice", "Bob", "Bob", "Charlie", "Charlie"),
+#'   sales = c(105, 110, 100, 97, 90, 95)
+#' )
+#' process_long(long, ids = "year", key = "person", value = "sales")
+#' process_long(long, ids = "year", key = "person", value = "sales") %>% static_plot
+process_long <- function(x, ids, key, value, ...) {
+
+  if (!all(c(ids, key, value) %in% names(x)))
+    stop("all ids, key, and value must be names of x")
+
+  nr <- nrow(x)
+  nc <- ncol(x)
+  xn <- names(x)
+
+  x <- x %>% mutate(.r = row_number()) %>%
+    tidyr::unite(ids, col = ".id_map", remove = F) %>%
+    tidyr::unite(key, col = ".key_map", remove = F)
+
+  key_values <- x %>% pull(key) %>% unique()
+
+  type_dict <- c(rep("id", length(ids)), rep("key", length(key)), rep("value", length(value)))
+  names(type_dict) <-  c(ids, key, value)
+
+  x_dict <- 1:nc
+  names(x_dict) <- xn
+
+  x <- x %>%
+    tidyr::gather(key = ".col", value = ".val", names(x)[grepl("^[^\\.]", names(x))]) %>%
+    mutate(
+      .x = x_dict[.col],
+      .y = -rep(1:nr, nc),
+      .type = type_dict[.col],
+      .val = as.character(.val),
+      .header = FALSE
+    )
+
+  # add headers:
+
+  id_headers <- tidyr::crossing(.id_map = ids, # x$.id_map %>% unique()
+                                .key_map = key_values,
+  ) %>%
+    mutate(
+      .r = 0,
+      .col = "id",
+      .val = .id_map,
+      .x = x_dict[.val],
+      .y = 0,
+      .type = "id",
+      .header = TRUE
+  )
+
+  x <- x %>%
+    dplyr::add_row(
+      .before = T,
+      .id_map = c(rep("key", length(key)), rep("value", length(value))),
+      .key_map = c(rep("key", length(key)), rep("value", length(value))),
+      .r = 0,
+      .col = c(rep("key", length(key)), rep("value", length(value))),
+      .val = c(key, value),
+      .x = length(ids) + 1:length(c(key, value)),
+      .y = 0,
+      .type = c(rep("key", length(key)), rep("value", length(value))),
+      .header = TRUE
+    )
+
+  x <- bind_rows(id_headers, x)
+
+  x <- x %>%
+    tidyr::unite(.key_map, .id_map, .val, col = ".id", remove = F)
+
+  x %>% add_color_tidyr(key_values = key_values) %>%
+    mutate(.alpha = ifelse(.header == TRUE, 1, 0.6))
+}
+
+#' Animates a gather or spread function
+#'
+#' internally used by animate_spread and animate_gather
+#'
+#' @param lhs the (processed) dataset on the left-side
+#' @param rhs the (processed) dataset on the right-side
+#' @param sequence a named vector of the sequence titles
+#'          (current_state, final_state, operation, and reverse_operation)
+#' @param key_values the unique key-values
+#' @param export the export type, either gif, first or last. The latter two
+#'              export ggplots of the first/last state of the join
+#' @param detailed boolean value if the animation should show one step for each
+#'              key value
+#' @param ... further arguments passed to animate_plot
+#'
+#' @return the plot or the gif
+#'
+#' @examples
+#' NULL
+gather_spread <- function(lhs, rhs, sequence, key_values, export, detailed, ...,
+                          anim_opts = anim_options(...)) {
+  # lhs is the one state of the df
+  # rhs is the target state
+
+  # animate the four steps: inital with sequence[["current_state]],
+  # transformations by the unique key-values with sequence[["operation"]],
+  # final with sequence[["final_state"]]
+  # and back transformation with sequence[["reverse_operation]]
+
+  # have lhs and rhs in the right format: preprocessed with ids, .x, .y etc.
+  # have a color function that makes coloring easier
+  # transformations: for each key-variable: respective ids "fly in", keys fly in and ids fly in (all in one step for one key. i.e., Alice)
+
+  # how much is the rhs to the left of lhs?
+
+  if (!detailed) {
+    anim_df <- bind_rows(
+      lhs %>% mutate(.frame = 0),
+      rhs %>% mutate(.frame = 1)
+    )
+    frame_labels <- c(sequence[["operation"]], sequence[["reverse_operation"]])
+
+    title_string <- "{ifelse(transitioning, previous_state, ifelse(grepl('gather', next_state), 'Wide', 'Long'))}"
+
+    tl <- 2
+    sl <- 1
+
+  } else {
+    xshift <- 2
+
+    rhs <- rhs %>% mutate(.x = .x + max(lhs$.x) + xshift)
+    # the header rows
+    header_start <- lhs %>% filter(.header == TRUE, !.key_map %in% key_values)
+    header_end <- rhs %>% filter(.header == TRUE)
+
+    state_start <- lhs %>% mutate(.frame = 0)
+    state_end <- rhs %>% mutate(.frame = length(key_values) + 2)
+
+    step_0 <- lhs %>% mutate(.frame = 1)
+    # for each unique key-value move the respective entries
+    keys_remaining <- lhs %>% filter(.key_map %in% key_values)
+    keys_shifted <- lhs[0, ]
+    key_steps <- lhs[0, ]
+    f <- 1
+    ids_remaining <- lhs %>% filter(.type == "id" & .header == FALSE)
+
+    for (keyval in key_values) {
+      f <- f + 1
+      move_rhs <- rhs %>% filter(.key_map == keyval)
+
+      keys_remaining <- keys_remaining %>% filter(.key_map != keyval)
+
+      if (keyval == key_values[length(key_values)]) {
+        header_start <- NULL
+      }
+      hd <- header_end %>% filter(.key_map == keyval |
+                                    (.type %in% c("key", "value") &
+                                       .col %in% c("key", "value")))
+      keys_shifted <- bind_rows(keys_shifted, move_rhs)
+      round_n <- bind_rows(header_start, hd,
+                           keys_remaining, keys_shifted) %>%
+        mutate(.frame = f)
+
+      key_steps <- bind_rows(key_steps, round_n)
+    }
+
+    anim_df <- bind_rows(state_start, step_0, key_steps, state_end)
+
+    # form the .frame as proper factors
+    frame_labels <- c(
+      sequence[["current_state"]],
+      paste(sequence[["operation"]], key_values),
+      sequence[["final_state"]],
+      sequence[["reverse_operation"]]
+    )
+    title_string <- "{gsub('\\\\) [a-zA-Z]+$', ')', previous_state)}"
+
+    tl <- length(unique(anim_df$.frame)) * 2
+    sl <- 1
+  }
+
+  frame_levels <- anim_df$.frame %>% unique()
+
+  anim_df <- anim_df %>%
+    mutate(.frame = factor(.frame,
+                           levels = frame_levels,
+                           labels = frame_labels))
+
+  if (export == "gif") {
+    animate_plot(anim_df, title = title_string, anim_opts = anim_opts)
+  } else if (export == "first") {
+    static_plot(state_start, anim_opts = anim_opts) #....
+  } else if (export == "last") {
+    static_plot(state_end, anim_opts = anim_opts) #....
+  }
+
+  # open issues: ... doesnt work properly.
+  # especially if the id-arguments are passed in the gather-style, i.e., -year, or year:var
+}

R/tidyr_spread_gather.R

@@ -1,97 +0,0 @@
-source(here::here("R", "00_base_tidyr.R"))
-
-sg_wide <- wide %>%
-  proc_data("0-wide", colorize_wide_tidyr) %>%
-  mutate(frame = 1, .id = "0-wide")
-
-sg_long <- wide %>%
-  tidyr::gather("key", "val", -id) %>%
-  proc_data("3-tall", color_fun = function(x, y) x) %>%
-  split(.$label)
-
-sg_long$id <-
-  sg_wide %>%
-  filter(label == "id") %>%
-  select(value, color) %>%
-  left_join(sg_long$id, ., by = "value") %>%
-  mutate(alpha = 1)
-
-sg_long$key <-
-  sg_wide %>%
-  filter(label != "id") %>%
-  select(label, color) %>%
-  left_join(sg_long$key, ., by = c("value" = "label")) %>%
-  distinct() %>%
-  mutate(alpha = 1)
-
-sg_long$val <-
-  sg_wide %>%
-  filter(label != "id", .y < 0) %>%
-  select(value, color) %>%
-  left_join(sg_long$val, ., by = "value") %>%
-  mutate(alpha = 0.6)
-
-sg_long <- bind_rows(sg_long) %>% mutate(frame = 2)
-
-sg_long_labels <- data_frame(id = 1, a = "id", x = "key", y = "val") %>%
-  proc_data("4-label") %>%
-  filter(label != "id") %>%
-  mutate(color = "#FFFFFF", .y = 0, .x = .x -1, frame = 2, alpha = 1, label = recode(label, "a" = "id"))
-
-sg_wide_labels <- data_frame(id = 1, a = "id") %>%
-  proc_data("2-label") %>%
-  filter(label != "id") %>%
-  mutate(color = "#FFFFFF", .y = 0, .x = .x -1, frame = 1, alpha = 1, label = recode(label, "a" = "id"))
-
-sg_long_extra_keys <- map_dfr(
-  seq_len(nrow(wide) - 1),
-  ~ filter(sg_wide, .y > -1) # Extra key blocks in long column
-)
-
-n_key_cols <- length(setdiff(colnames(wide), "id"))
-
-sg_long_extra_id <- map_dfr(
-  seq_len(n_key_cols - 1),
-  ~ filter(sg_wide, .x == 1) # Extra id column blocks for long column
-)
-
-sg_data <- bind_rows(
-  sg_wide,
-  sg_wide_labels,
-  sg_long,
-  sg_long_labels,
-  sg_long_extra_keys,
-  sg_long_extra_id
-) %>%
-  mutate(
-    label = ifelse(value %in% setdiff(colnames(wide), "id"), "key", label),
-    label = ifelse(value %in% c("key", "val"), "zzz", label),
-    .text_color = ifelse(grepl("label", .id), "black", "white"),
-    .text_size = ifelse(grepl("label", .id), 8, 12)
-  ) %>%
-  arrange(label, .id, value) %>%
-  mutate(frame = factor(frame, labels = c('spread(long, key, val)', 'gather(wide, key, val, x:z)'))) %>%
-  select(.x, .y, everything())
-
-sg_static <-
-  sg_data %>%
-  split(.$frame) %>%
-  imap(~ plot_data(.x, .y) +
-         ylim(-6.5, 0.5) +
-         labs(subtitle = "returns") +
-         theme(plot.subtitle = element_text(family = "Fira Sans", size = 14, color = "grey50", hjust = 0.5, margin = margin(25)))
-  )
-
-save_static_plot(sg_static[[1]], "tidyr-spread")
-save_static_plot(sg_static[[2]], "tidyr-gather")
-
-sg_anim <-
-  sg_data %>%
-  plot_data() %>%
-  animate_plot() +
-  view_follow() +
-  labs(title = "{ifelse(transitioning, next_state, ifelse(grepl('gather', next_state), 'long', 'wide'))}") +
-  ease_aes("sine-in-out", x = "exponential-out")
-
-sg_anim <- animate(sg_anim)
-anim_save(here::here("images", "tidyr-spread-gather.gif"), sg_anim)

R/union.R

@@ -1,42 +0,0 @@
-source(here::here("R/00_base_set.R"))
-
-# ---- union(x, y) ----
-uxy <- bind_rows(
-  initial_set_dfs,
-  union(x, y) %>% proc_data_set("xy") %>% mutate(frame = 2, .x = .x + 1.5),
-  intersect(x, y) %>% proc_data_set("xy") %>% mutate(frame = 2, .y = -4, .x = .x + 1.5)
-) %>%
-  plot_data_set("union(x, y)", ylims = ylim(-4.5, -0.5)) %>%
-  animate_plot()
-
-uxy <- animate(uxy)
-
-anim_save(here::here("images", "union.gif"), uxy)
-
-uxy_g <- union(x, y) %>%
-  proc_data_set() %>%
-  mutate(.x = .x + 1.5) %>%
-  plot_data_set("union(x, y)", ylims = ylim(-0.5, -4.5))
-
-save_static_plot(uxy_g, "union")
-
-
-# ---- union(y, x) ----
-uyx <- bind_rows(
-  initial_set_dfs,
-  union(y, x) %>% proc_data_set("xy") %>% mutate(frame = 2, .x = .x + 1.5),
-  intersect(y, x) %>% proc_data_set("xy") %>% mutate(frame = 2, .y = -4, .x = .x + 1.5)
-) %>%
-  plot_data_set("union(y, x)", ylims = ylim(-4.5, -0.5)) %>%
-  animate_plot()
-
-uyx <- animate(uyx)
-
-anim_save(here::here("images", "union-rev.gif"), uyx)
-
-uyx_g <- union(y, x) %>%
-  proc_data_set() %>%
-  mutate(.x = .x + 1.5) %>%
-  plot_data_set("union(y, x)", ylims = ylim(-4.5, -0.5))
-
-save_static_plot(uyx_g, "union-rev")

R/union_all.R

@@ -1,23 +0,0 @@
-source(here::here("R/00_base_set.R"))
-
-ua <- bind_rows(
-  initial_set_dfs,
-  initial_set_dfs %>% mutate(frame = 2, .y = ifelse(.id == "y", .y - 3, .y)), # fly y down
-  proc_data_set(x, "ux") %>% mutate(frame = 3, .x = .x + 1.5),                # merge
-  proc_data_set(y, "uy") %>% mutate(frame = 3, .x = .x + 1.5, .y = .y - 3),   # un-merge
-  initial_set_dfs %>% mutate(frame = 4, .y = ifelse(.id == "y", .y - 3, .y))  # fly y up
-) %>%
-  arrange(desc(frame)) %>%
-  plot_data_set("union_all(x, y)", ylims = ylim(-5.5, -0.5)) +
-  transition_states(frame, 1, c(1, 0, 1, 0))
-
-ua <- animate(ua)
-
-anim_save(here::here("images", "union-all.gif"), ua)
-
-ua_g <- union_all(x, y) %>%
-  proc_data_set() %>%
-  mutate(.x = .x + 1.5) %>%
-  plot_data_set("union_all(x, y)", ylims = ylim(-5.5, -0.5))
-
-save_static_plot(ua_g, "union-all")

R/utils-pipe.R

@@ -0,0 +1,11 @@
+#' Pipe operator
+#'
+#' See \code{magrittr::\link[magrittr]{\%>\%}} for details.
+#'
+#' @name %>%
+#' @rdname pipe
+#' @keywords internal
+#' @export
+#' @importFrom magrittr %>%
+#' @usage lhs \%>\% rhs
+NULL

R/utils.R

@@ -0,0 +1,26 @@
+`%||%` <- function(x, y) if (is.null(x)) y else x
+
+choose_text_color <- function(x, black = "#000000", white = "#FFFFFF") {
+  # x = color_hex
+  color_rgb <- col2rgb(x)
+  # modified from https://stackoverflow.com/a/3943023/2022615
+  # following W3 guidelines: https://www.w3.org/TR/WCAG20/#relativeluminancedef
+  color_rgb <- color_rgb / 255
+  color_rgb[color_rgb <= 0.03928] <- color_rgb[color_rgb <= 0.03928]/12.92
+  color_rgb[color_rgb  > 0.03928] <- ((color_rgb[color_rgb > 0.03928] + 0.055)/1.055)^2.4
+  lum <- t(color_rgb) %*% c(0.2126, 0.7152, 0.0722)
+  lum <- lum[,1]
+  # threshold is supposed to be 0.179 but 1/3 seems to work better for our plots
+  ifelse(lum > 1/3, black, white)
+}
+
+get_input_text <- function(x) {
+  if (!rlang::is_quosure(x)) x <- rlang::enquo(x)
+  rlang::quo_name(x)
+}
+
+make_named_data <- function(x, y, data_names = c("x", "y")) {
+  ll <- rlang::eval_tidy(rlang::quo(list(!!x, !!y)))
+  names(ll) <- data_names
+  ll
+}

R/zzzz-package.R

@@ -0,0 +1,27 @@
+#' @importFrom dplyr left_join right_join full_join inner_join semi_join anti_join
+#' @importFrom dplyr mutate select filter arrange bind_rows bind_cols group_by pull slice data_frame row_number
+#' @importFrom tidyr gather spread
+#' @keywords internal
+"_PACKAGE"
+
+plot_settings <- new.env(parent = emptyenv())
+plot_settings$default <- list(
+  transition_length = 2,
+  state_length      = 1,
+  ease_default      = "sine-in-out",
+  ease_other        = NULL,
+  enter             = setNames(list(enter_fade()), "enter_fade()"),
+  exit              = setNames(list(exit_fade()), "exit_fade()"),
+  text_family       = "Fira Mono",
+  title_family      = "Fira Mono",
+  text_size         = 5,
+  title_size        = 17,
+  color_header      = "#737373",
+  color_other       = "#d0d0d0",
+  color_missing     = "#ffffff",
+  color_fun         = scales::brewer_pal(type = "qual", "Set1"),
+  text_color        = NA,
+  cell_width        = 1,
+  cell_height       = 1
+)
+

README.Rmd

@@ -1,5 +1,7 @@
 ---
 output: github_document
+editor_options: 
+  chunk_output_type: console
 ---
 
 <!-- README.md is generated from README.Rmd. Please edit that file -->
@@ -8,47 +10,45 @@ output: github_document
 knitr::opts_chunk$set(
   collapse = TRUE,
   comment = "#>",
-  echo = FALSE,
+  echo = TRUE,
   warning = FALSE,
   message = FALSE,
+  fig.path = "man/figures/tidyexplain-",
   cache = TRUE
 )
+library(tidyexplain)
+set_font_size(11, 26)
 ```
 
 [gganimate]: https://github.com/thomasp85/gganimate#README
 [dplyr-two-table]: https://dplyr.tidyverse.org/articles/two-table.html
-[r4ds]: http://r4ds.had.co.nz/
-[r4ds-relational]: http://r4ds.had.co.nz/relational-data.html
-[r4ds-set-ops]: http://r4ds.had.co.nz/relational-data.html#set-operations
-[r4ds-tidy-data]: http://r4ds.had.co.nz/tidy-data.html#tidy-data-1
-[tidyverse]: https://tidyverse.org
-[tidyr]: https://tidyr.tidyverse.org
+[r4ds-set-ops]: http://r4ds.had.co.nz/relation-data.html#set-operations
 
 # Tidy Animated Verbs
 
-Garrick Aden-Buie -- [&commat;grrrck](https://twitter.com/grrrck) -- [garrickadenbuie.com](https://www.garrickadenbuie.com). Set operations contributed by [Tyler Grant Smith](https://github.com/TylerGrantSmith).
+Garrick Aden-Buie -- [&commat;grrrck](https://twitter.com/grrrck) -- [garrickadenbuie.com](https://www.garrickadenbuie.com).
+
+David Zimmermann -- [&commat;dav_zim](https://twitter.com/dav_zim) -- [datashenanigan.wordpress.com](https://datashenanigan.wordpress.com/)
+
+Set operations contributed by [Tyler Grant Smith](https://github.com/TylerGrantSmith).
 
 [![Binder](http://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/gadenbuie/tidy-animated-verbs/master?urlpath=rstudio)
 [![CC0](https://img.shields.io/badge/license_(images)_-CC0-green.svg)](https://creativecommons.org/publicdomain/zero/1.0/)
 [![MIT](https://img.shields.io/badge/license_(code)_-MIT-green.svg)](https://opensource.org/licenses/MIT)
 
-- [**Mutating Joins**](#mutating-joins) — [`inner_join()`](#inner-join), [`left_join()`](#left-join),
-  [`right_join()`](#right-join), [`full_join()`](#full-join)
-  
-- [**Filtering Joins**](#filtering-joins) — [`semi_join()`](#semi-join), [`anti_join()`](#anti-join)
+- Mutating Joins: [`inner_join()`](#inner-join), [`left_join()`](#left-join),
+[`right_join()`](#right-join), [`full_join()`](#full-join)
+
+- Filtering Joins: [`semi_join()`](#semi-join), [`anti_join()`](#anti-join)
 
-- [**Set Operations**](#set-operations) — [`union()`](#union), [`union_all()`](#union-all), [`intersect()`](#intersect), [`setdiff()`](#setdiff)
+- Set Operations: [`union()`](#union), [`union_all()`](#union-all), [`intersect()`](#intersect), [`setdiff()`](#setdiff)
 
-- [**Tidy Data**](#tidy-data) — [`spread()` and `gather()`](#spread-and-gather)
+- Tidyr Operations: [`gather()`](#gather), [`spread()`](#spread)
 
 - Learn more about
-    - [Using the animations and images](#usage)
     - [Relational Data](#relational-data)
     - [gganimate](#gganimate)
-    
-## Background
 
-### Usage
 
 Please feel free to use these images for teaching or learning about action verbs from the [tidyverse](https://tidyverse.org).
 You can directly download the [original animations](images/) or static images in [svg](images/static/svg/) or [png](images/static/png/) formats, or you can use the [scripts](R/) to recreate the images locally.
@@ -56,46 +56,35 @@ You can directly download the [original animations](images/) or static images in
 Currently, the animations cover the [dplyr two-table verbs][dplyr-two-table] and I'd like to expand the animations to include more verbs from the tidyverse.
 [Suggestions are welcome!](https://github.com/gadenbuie/tidy-animated-verbs/issues)
 
-### Relational Data
-
-The [Relational Data][r4ds-relational] chapter of the
-[R for Data Science][r4ds] book by Garrett Grolemund and Hadley Wickham
-is an excellent resource for learning more about relational data.
+## Installing
 
-The [dplyr two-table verbs vignette][dplyr-two-table]
-and Jenny Bryan's [Cheatsheet for dplyr join functions](http://stat545.com/bit001_dplyr-cheatsheet.html)
-are also great resources.
+The in-development version of `tidyexplain` can be installed with `devtools`:
 
-### gganimate
+```r
+# install.package("devtools")
+devtools::install_github("gadenbuie/tidy-animated-verbs")
 
-The animations were made possible by the newly re-written [gganimate] package by 
-[Thomas Lin Pedersen](https://github.com/thomasp85)
-(original by [Dave Robinson](https://github.com/dgrtwo)).
-The [package readme][gganimate] provides an excellent (and quick) introduction to gganimte.
+library(tidyexplain)
+```
 
 ## Mutating Joins
 
-> A mutating join allows you to combine variables from two tables. It first matches observations by their keys, then copies across variables from one table to the other.  
-> [R for Data Science: Mutating joins](http://r4ds.had.co.nz/relational-data.html#mutating-joins)
-
 ```{r intial-dfs}
-source("R/00_base_join.R")
-df_names <- data_frame(
-  .x = c(1.5, 4.5), .y = 0.25,
-  value = c("x", "y"),
-  size = 12,
-  color = "black"
+x <- dplyr::data_frame(
+  id = 1:3,
+  x = paste0("x", 1:3)
 )
 
-g <- plot_data(initial_join_dfs) +
-  geom_text(data = df_names, family = "Fira Mono", size = 24)
+y <- dplyr::data_frame(
+  id = (1:4)[-3],
+  y = paste0("y", (1:4)[-3])
+)
 
-save_static_plot(g, "original-dfs")
+animate_full_join(x, y, by = c("id"), export = "first")
 ```
 
-<img src="images/static/png/original-dfs.png" width="480px" />
 
-```{r echo=TRUE}
+```{r}
 x
 y
 ```
@@ -105,13 +94,12 @@ y
 > All rows from `x` where there are matching values in `y`, and all columns from `x` and `y`.
 
 ```{r inner-join}
-source("R/inner_join.R")
+animate_inner_join(x, y, by = "id")
 ```
 
-![](images/inner-join.gif)
 
-```{r echo=TRUE}
-inner_join(x, y, by = "id")
+```{r}
+dplyr::inner_join(x, y, by = "id")
 ```
 
 ### Left Join
@@ -119,13 +107,12 @@ inner_join(x, y, by = "id")
 > All rows from `x`, and all columns from `x` and `y`. Rows in `x` with no match in `y` will have `NA` values in the new columns.
 
 ```{r left-join}
-source("R/left_join.R")
+animate_left_join(x, y, by = "id")
 ```
 
-![](images/left-join.gif)
 
-```{r echo=TRUE}
-left_join(x, y, by = "id")
+```{r}
+dplyr::left_join(x, y, by = "id")
 ```
 
 ### Left Join (Extra Rows in y)
@@ -133,14 +120,14 @@ left_join(x, y, by = "id")
 > ... If there are multiple matches between `x` and `y`, all combinations of the matches are returned.
 
 ```{r left-join-extra}
-source("R/left_join_extra.R")
-```
+y_extra <- dplyr::bind_rows(y, dplyr::data_frame(id = 2, y = "y5"))
+y_extra # has multiple rows with the key from `x`
 
-![](images/left-join-extra.gif)
+animate_left_join(x, y_extra, by = "id", title_size = 22)
+```
 
-```{r echo=TRUE}
-y_extra # has multiple rows with the key from `x`
-left_join(x, y_extra, by = "id")
+```{r}
+dplyr::left_join(x, y_extra, by = "id")
 ```
 
 ### Right Join
@@ -148,13 +135,12 @@ left_join(x, y_extra, by = "id")
 > All rows from y, and all columns from `x` and `y`. Rows in `y` with no match in `x` will have `NA` values in the new columns.
 
 ```{r right-join}
-source("R/right_join.R")
+animate_right_join(x, y, by = "id")
 ```
 
-![](images/right-join.gif)
 
-```{r echo=TRUE}
-right_join(x, y, by = "id")
+```{r}
+dplyr::right_join(x, y, by = "id")
 ```
 
 ### Full Join
@@ -162,34 +148,27 @@ right_join(x, y, by = "id")
 > All rows and all columns from both `x` and `y`. Where there are not matching values, returns `NA` for the one missing.
 
 ```{r full-join}
-source("R/full_join.R")
+animate_full_join(x, y, by = "id")
 ```
 
-![](images/full-join.gif)
 
-```{r echo=TRUE}
-full_join(x, y, by = "id")
+```{r}
+dplyr::full_join(x, y, by = "id")
 ```
 
 ## Filtering Joins
 
-> Filtering joins match observations in the same way as mutating joins, but affect the observations, not the variables.
-> ... Semi-joins are useful for matching filtered summary tables back to the original rows.
-> ... Anti-joins are useful for diagnosing join mismatches.  
-> [R for Data Science: Filtering Joins](http://r4ds.had.co.nz/relational-data.html#filtering-joins)
-
 ### Semi Join
 
 > All rows from `x` where there are matching values in `y`, keeping just columns from `x`.
 
 ```{r semi-join}
-source("R/semi_join.R")
+animate_semi_join(x, y, by = "id")
 ```
 
-![](images/semi-join.gif)
 
-```{r echo=TRUE}
-semi_join(x, y, by = "id")
+```{r}
+dplyr::semi_join(x, y, by = "id")
 ```
 
 ### Anti Join
@@ -197,45 +176,31 @@ semi_join(x, y, by = "id")
 > All rows from `x` where there are not matching values in `y`, keeping just columns from `x`.
 
 ```{r anti-join}
-source("R/anti_join.R")
+animate_anti_join(x, y, by = "id")
 ```
 
-![](images/anti-join.gif)
 
-```{r echo=TRUE}
-anti_join(x, y, by = "id")
+```{r}
+dplyr::anti_join(x, y, by = "id")
 ```
 
 ## Set Operations
 
-> Set operations are occasionally useful when you want to break a single complex filter into simpler pieces. 
-> All these operations work with a complete row, comparing the values of every variable. 
-> These expect the x and y inputs to have the same variables, and treat the observations like sets.  
-> [R for Data Science: Set operations](http://r4ds.had.co.nz/relational-data.html#set-operations)
-
 ```{r intial-dfs-so}
-source("R/00_base_set.R")
-df_names <- data_frame(
-  .x = c(2.5, 5.5), .y = 0.25,
-  value = c("x", "y"),
-  size = 12,
-  color = "black"
+x <- dplyr::data_frame(
+  x = c(1, 1, 2),
+  y = c("a", "b", "a")
+)
+y <- dplyr::data_frame(
+  x = c(1, 2),
+  y = c("a", "b")
 )
 
-g <- plot_data_set(initial_set_dfs, "", NULL, NULL) +
-  geom_text(data = df_names, family = "Fira Mono", size = 24)
-
-save_static_plot(g, "original-dfs-set-ops")
-```
-
-```{r remove-set-ops-ids}
-x <- x %>% select(-id)
-y <- y %>% select(-id)
+animate_union(x, y, export = "first")
 ```
 
-<img src="images/static/png/original-dfs-set-ops.png" width="480px" />
 
-```{r echo=TRUE}
+```{r}
 x
 y 
 ```
@@ -245,20 +210,20 @@ y
 > All unique rows from `x` and `y`.
 
 ```{r union}
-source("R/union.R")
-<<remove-set-ops-ids>>
+animate_union(x, y)
 ```
 
-![](images/union.gif)
 
-```{r echo=TRUE}
-union(x, y)
+```{r}
+dplyr::union(x, y)
 ```
 
-![](images/union-rev.gif)
 
-```{r echo=TRUE}
-union(y, x)
+
+```{r union-y-x}
+animate_union(y, x)
+
+dplyr::union(y, x)
 ```
 
 ### Union All
@@ -266,15 +231,13 @@ union(y, x)
 > All rows from `x` and `y`, keeping duplicates.
 
 ```{r union-all}
-source("R/union_all.R")
-<<remove-set-ops-ids>>
+animate_union_all(x, y)
 ```
 
-![](images/union-all.gif)
 
 
-```{r echo=TRUE}
-union_all(x, y)
+```{r}
+dplyr::union_all(x, y)
 ```
 
 
@@ -283,14 +246,12 @@ union_all(x, y)
 > Common rows in both `x` and `y`, keeping just unique rows.
 
 ```{r intersect}
-source("R/intersect.R")
-<<remove-set-ops-ids>>
+animate_intersect(x, y)
 ```
 
-![](images/intersect.gif)
 
-```{r echo=TRUE}
-intersect(x, y)
+```{r}
+dplyr::intersect(x, y)
 ```
 
 ### Set Difference
@@ -298,72 +259,91 @@ intersect(x, y)
 > All rows from `x` which are not also rows in `y`, keeping just unique rows.
 
 ```{r setdiff}
-source("R/setdiff.R")
-<<remove-set-ops-ids>>
+animate_setdiff(x, y)
 ```
 
-![](images/setdiff.gif)
 
-```{r echo=TRUE}
-setdiff(x, y)
+```{r}
+dplyr::setdiff(x, y)
 ```
 
-![](images/setdiff-rev.gif)
 
-```{r echo=TRUE}
-setdiff(y, x)
+```{r setdiff-y-x}
+animate_setdiff(y, x)
+
+dplyr::setdiff(y, x)
 ```
 
-## Tidy Data
+## Tidy Data and `gather()`, `spread()` functionality
 
-[Tidy data][r4ds-tidy-data] follows the following three rules:
+[Tidy data](http://r4ds.had.co.nz/tidy-data.html#tidy-data-1) follows
+the following three rules:
 
-1. Each variable has its own column.
-1. Each observation has its own row.
-1. Each value has its own cell.
+1.  Each variable has its own column.
+2.  Each observation has its own row.
+3.  Each value has its own cell.
 
-Many of the tools in the [tidyverse] expect data to be formatted as a tidy dataset and the [tidyr] package provides functions to help you organize your data into tidy data.
+Many of the tools in the [tidyverse](https://tidyverse.org) expect data
+to be formatted as a tidy dataset and the
+[tidyr](https://tidyr.tidyverse.org) package provides functions to help
+you organize your data into tidy data.
 
-```{r tidyr-wide-long}
-source("R/tidyr_spread_gather.R")
+```{r}
+long <- dplyr::data_frame(
+  year = c(2010, 2011, 2010, 2011, 2010, 2011),
+  person = c("Alice", "Alice", "Bob", "Bob", "Charlie", "Charlie"),
+  sales = c(105, 110, 100, 97, 90, 95)
+)
+wide <- dplyr::data_frame(
+  year = 2010:2011, 
+  Alice = c(105, 110), 
+  Bob = c(100, 97), 
+  Charlie = c(90, 95)
+)
+```
 
-tidy_plots <- list()
-tidy_plots$wide <- bind_rows(sg_wide, sg_wide_labels)
-tidy_plots$long <- bind_rows(sg_long, sg_long_labels)
+### Gather
 
-tidy_plots <- map(tidy_plots, ~ mutate(., 
-  .text_color = ifelse(grepl("id|key|val", value), "black", "white"),
-  .text_size  = ifelse(grepl("id|key|val", value), 6, 10)
-)) %>% 
-  imap(~ plot_data(.x, .y))
+> Gather takes multiple columns and collapses into key-value pairs, duplicating all other columns as needed. You use gather() when you notice that your column names are not names of variables, but values of a variable.
 
-tidy_plots$wide <- tidy_plots$wide + ylim(-6.5, 0.5)
+```{r gather}
+set_font_size(4, 15)
+set_anim_options(anim_options(cell_width = 2))
+animate_gather(wide, key = "person", value = "sales", -year)
+```
 
-save_static_plot(cowplot::plot_grid(plotlist = tidy_plots, axis = "t"), "original-dfs-tidy")
+```{r}
+tidyr::gather(wide, key = "person", value = "sales", -year)
 ```
 
-![](images/static/png/original-dfs-tidy.png)
+### Spread
+
+> Spread a key-value pair across multiple columns. Use it when an a column contains observations from multiple variables.
+
+```{r spread}
+animate_spread(long, key = "person", value = "sales")
+```
 
-```{r echo=TRUE}
-wide
-long
+```{r}
+tidyr::spread(long, key = "person", value = "sales")
 ```
 
-### Spread and Gather
 
-`spread(data, key, value)`
+## Learn More
 
-> Spread a key-value pair across multiple columns. 
-> Use it when an a column contains observations from multiple variables.
+### Relational Data
 
-`gather(data, key = "key", value = "value", ...)`
+The [Relational Data](http://r4ds.had.co.nz/relation-data.html) chapter of the
+[R for Data Science](http://r4ds.had.co.nz/) book by Garrett Grolemund and Hadley Wickham
+is an excellent resource for learning more about relational data.
 
-> Gather takes multiple columns and collapses into key-value pairs, duplicating all other columns as needed. 
-> You use `gather()` when you notice that your column names are not names of variables, but *values* of a variable.
+The [dplyr two-table verbs vignette][dplyr-two-table]
+and Jenny Bryan's [Cheatsheet for dplyr join functions](http://stat545.com/bit001_dplyr-cheatsheet.html)
+are also great resources.
 
-![](images/tidyr-spread-gather.gif)
+### gganimate
 
-```{r echo=TRUE}
-gather(wide, key, val, x:z)
-spread(long, key, val)
-```
+The animations were made possible by the newly re-written [gganimate] package by 
+[Thomas Lin Pedersen](https://github.com/thomasp85)
+(original by [Dave Robinson](https://github.com/dgrtwo)).
+The [package readme][gganimate] provides an excellent (and quick) introduction to gganimte.

README.md

@@ -4,38 +4,35 @@
 # Tidy Animated Verbs
 
 Garrick Aden-Buie – [@grrrck](https://twitter.com/grrrck) –
-[garrickadenbuie.com](https://www.garrickadenbuie.com). Set operations
-contributed by [Tyler Grant
+[garrickadenbuie.com](https://www.garrickadenbuie.com).
+
+David Zimmermann – [@dav\_zim](https://twitter.com/dav_zim) –
+[datashenanigan.wordpress.com](https://datashenanigan.wordpress.com/)
+
+Set operations contributed by [Tyler Grant
 Smith](https://github.com/TylerGrantSmith).
 
 [![Binder](http://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/gadenbuie/tidy-animated-verbs/master?urlpath=rstudio)
 [![CC0](https://img.shields.io/badge/license_\(images\)_-CC0-green.svg)](https://creativecommons.org/publicdomain/zero/1.0/)
 [![MIT](https://img.shields.io/badge/license_\(code\)_-MIT-green.svg)](https://opensource.org/licenses/MIT)
 
-  - [**Mutating Joins**](#mutating-joins) —
-    [`inner_join()`](#inner-join), [`left_join()`](#left-join),
-    [`right_join()`](#right-join), [`full_join()`](#full-join)
+  - Mutating Joins: [`inner_join()`](#inner-join),
+    [`left_join()`](#left-join), [`right_join()`](#right-join),
+    [`full_join()`](#full-join)
 
-  - [**Filtering Joins**](#filtering-joins) —
-    [`semi_join()`](#semi-join), [`anti_join()`](#anti-join)
+  - Filtering Joins: [`semi_join()`](#semi-join),
+    [`anti_join()`](#anti-join)
 
-  - [**Set Operations**](#set-operations) — [`union()`](#union),
-    [`union_all()`](#union-all), [`intersect()`](#intersect),
-    [`setdiff()`](#setdiff)
+  - Set Operations: [`union()`](#union), [`union_all()`](#union-all),
+    [`intersect()`](#intersect), [`setdiff()`](#setdiff)
 
-  - [**Tidy Data**](#tidy-data) — [`spread()` and
-    `gather()`](#spread-and-gather)
+  - Tidyr Operations: [`gather()`](#gather), [`spread()`](#spread)
 
   - Learn more about
     
-      - [Using the animations and images](#usage)
       - [Relational Data](#relational-data)
       - [gganimate](#gganimate)
 
-## Background
-
-### Usage
-
 Please feel free to use these images for teaching or learning about
 action verbs from the [tidyverse](https://tidyverse.org). You can
 directly download the [original animations](images/) or static images in
@@ -48,37 +45,35 @@ to expand the animations to include more verbs from the tidyverse.
 [Suggestions are
 welcome\!](https://github.com/gadenbuie/tidy-animated-verbs/issues)
 
-### Relational Data
+## Installing
 
-The [Relational Data](http://r4ds.had.co.nz/relational-data.html)
-chapter of the [R for Data Science](http://r4ds.had.co.nz/) book by
-Garrett Grolemund and Hadley Wickham is an excellent resource for
-learning more about relational data.
+The in-development version of `tidyexplain` can be installed with
+`devtools`:
 
-The [dplyr two-table verbs
-vignette](https://dplyr.tidyverse.org/articles/two-table.html) and Jenny
-Bryan’s [Cheatsheet for dplyr join
-functions](http://stat545.com/bit001_dplyr-cheatsheet.html) are also
-great resources.
-
-### gganimate
+``` r
+# install.package("devtools")
+devtools::install_github("gadenbuie/tidy-animated-verbs")
 
-The animations were made possible by the newly re-written
-[gganimate](https://github.com/thomasp85/gganimate#README) package by
-[Thomas Lin Pedersen](https://github.com/thomasp85) (original by [Dave
-Robinson](https://github.com/dgrtwo)). The [package
-readme](https://github.com/thomasp85/gganimate#README) provides an
-excellent (and quick) introduction to gganimte.
+library(tidyexplain)
+```
 
 ## Mutating Joins
 
-> A mutating join allows you to combine variables from two tables. It
-> first matches observations by their keys, then copies across variables
-> from one table to the other.  
-> [R for Data Science: Mutating
-> joins](http://r4ds.had.co.nz/relational-data.html#mutating-joins)
+``` r
+x <- dplyr::data_frame(
+  id = 1:3,
+  x = paste0("x", 1:3)
+)
+
+y <- dplyr::data_frame(
+  id = (1:4)[-3],
+  y = paste0("y", (1:4)[-3])
+)
 
-<img src="images/static/png/original-dfs.png" width="480px" />
+animate_full_join(x, y, by = c("id"), export = "first")
+```
+
+![](man/figures/tidyexplain-intial-dfs-1.png)<!-- -->
 
 ``` r
 x
@@ -102,10 +97,14 @@ y
 > All rows from `x` where there are matching values in `y`, and all
 > columns from `x` and `y`.
 
-![](images/inner-join.gif)
+``` r
+animate_inner_join(x, y, by = "id")
+```
+
+![](man/figures/tidyexplain-inner-join-1.gif)<!-- -->
 
 ``` r
-inner_join(x, y, by = "id")
+dplyr::inner_join(x, y, by = "id")
 #> # A tibble: 2 x 3
 #>      id x     y    
 #>   <int> <chr> <chr>
@@ -118,10 +117,14 @@ inner_join(x, y, by = "id")
 > All rows from `x`, and all columns from `x` and `y`. Rows in `x` with
 > no match in `y` will have `NA` values in the new columns.
 
-![](images/left-join.gif)
+``` r
+animate_left_join(x, y, by = "id")
+```
+
+![](man/figures/tidyexplain-left-join-1.gif)<!-- -->
 
 ``` r
-left_join(x, y, by = "id")
+dplyr::left_join(x, y, by = "id")
 #> # A tibble: 3 x 3
 #>      id x     y    
 #>   <int> <chr> <chr>
@@ -135,9 +138,8 @@ left_join(x, y, by = "id")
 > … If there are multiple matches between `x` and `y`, all combinations
 > of the matches are returned.
 
-![](images/left-join-extra.gif)
-
 ``` r
+y_extra <- dplyr::bind_rows(y, dplyr::data_frame(id = 2, y = "y5"))
 y_extra # has multiple rows with the key from `x`
 #> # A tibble: 4 x 2
 #>      id y    
@@ -146,7 +148,14 @@ y_extra # has multiple rows with the key from `x`
 #> 2     2 y2   
 #> 3     4 y4   
 #> 4     2 y5
-left_join(x, y_extra, by = "id")
+
+animate_left_join(x, y_extra, by = "id", title_size = 22)
+```
+
+![](man/figures/tidyexplain-left-join-extra-1.gif)<!-- -->
+
+``` r
+dplyr::left_join(x, y_extra, by = "id")
 #> # A tibble: 4 x 3
 #>      id x     y    
 #>   <dbl> <chr> <chr>
@@ -161,10 +170,14 @@ left_join(x, y_extra, by = "id")
 > All rows from y, and all columns from `x` and `y`. Rows in `y` with no
 > match in `x` will have `NA` values in the new columns.
 
-![](images/right-join.gif)
+``` r
+animate_right_join(x, y, by = "id")
+```
+
+![](man/figures/tidyexplain-right-join-1.gif)<!-- -->
 
 ``` r
-right_join(x, y, by = "id")
+dplyr::right_join(x, y, by = "id")
 #> # A tibble: 3 x 3
 #>      id x     y    
 #>   <int> <chr> <chr>
@@ -178,10 +191,14 @@ right_join(x, y, by = "id")
 > All rows and all columns from both `x` and `y`. Where there are not
 > matching values, returns `NA` for the one missing.
 
-![](images/full-join.gif)
+``` r
+animate_full_join(x, y, by = "id")
+```
+
+![](man/figures/tidyexplain-full-join-1.gif)<!-- -->
 
 ``` r
-full_join(x, y, by = "id")
+dplyr::full_join(x, y, by = "id")
 #> # A tibble: 4 x 3
 #>      id x     y    
 #>   <int> <chr> <chr>
@@ -193,22 +210,19 @@ full_join(x, y, by = "id")
 
 ## Filtering Joins
 
-> Filtering joins match observations in the same way as mutating joins,
-> but affect the observations, not the variables. … Semi-joins are
-> useful for matching filtered summary tables back to the original rows.
-> … Anti-joins are useful for diagnosing join mismatches.  
-> [R for Data Science: Filtering
-> Joins](http://r4ds.had.co.nz/relational-data.html#filtering-joins)
-
 ### Semi Join
 
 > All rows from `x` where there are matching values in `y`, keeping just
 > columns from `x`.
 
-![](images/semi-join.gif)
+``` r
+animate_semi_join(x, y, by = "id")
+```
+
+![](man/figures/tidyexplain-semi-join-1.gif)<!-- -->
 
 ``` r
-semi_join(x, y, by = "id")
+dplyr::semi_join(x, y, by = "id")
 #> # A tibble: 2 x 2
 #>      id x    
 #>   <int> <chr>
@@ -221,10 +235,14 @@ semi_join(x, y, by = "id")
 > All rows from `x` where there are not matching values in `y`, keeping
 > just columns from `x`.
 
-![](images/anti-join.gif)
+``` r
+animate_anti_join(x, y, by = "id")
+```
+
+![](man/figures/tidyexplain-anti-join-1.gif)<!-- -->
 
 ``` r
-anti_join(x, y, by = "id")
+dplyr::anti_join(x, y, by = "id")
 #> # A tibble: 1 x 2
 #>      id x    
 #>   <int> <chr>
@@ -233,92 +251,114 @@ anti_join(x, y, by = "id")
 
 ## Set Operations
 
-> Set operations are occasionally useful when you want to break a single
-> complex filter into simpler pieces. All these operations work with a
-> complete row, comparing the values of every variable. These expect the
-> x and y inputs to have the same variables, and treat the observations
-> like sets.  
-> [R for Data Science: Set
-> operations](http://r4ds.had.co.nz/relational-data.html#set-operations)
+``` r
+x <- dplyr::data_frame(
+  x = c(1, 1, 2),
+  y = c("a", "b", "a")
+)
+y <- dplyr::data_frame(
+  x = c(1, 2),
+  y = c("a", "b")
+)
+
+animate_union(x, y, export = "first")
+```
 
-<img src="images/static/png/original-dfs-set-ops.png" width="480px" />
+![](man/figures/tidyexplain-intial-dfs-so-1.png)<!-- -->
 
 ``` r
 x
 #> # A tibble: 3 x 2
-#>   x     y    
-#>   <chr> <chr>
-#> 1 1     a    
-#> 2 1     b    
-#> 3 2     a
+#>       x y    
+#>   <dbl> <chr>
+#> 1     1 a    
+#> 2     1 b    
+#> 3     2 a
 y 
 #> # A tibble: 2 x 2
-#>   x     y    
-#>   <chr> <chr>
-#> 1 1     a    
-#> 2 2     b
+#>       x y    
+#>   <dbl> <chr>
+#> 1     1 a    
+#> 2     2 b
 ```
 
 ### Union
 
 > All unique rows from `x` and `y`.
 
-![](images/union.gif)
+``` r
+animate_union(x, y)
+```
+
+![](man/figures/tidyexplain-union-1.gif)<!-- -->
 
 ``` r
-union(x, y)
+dplyr::union(x, y)
 #> # A tibble: 4 x 2
-#>   x     y    
-#>   <chr> <chr>
-#> 1 2     b    
-#> 2 2     a    
-#> 3 1     b    
-#> 4 1     a
+#>       x y    
+#>   <dbl> <chr>
+#> 1     2 b    
+#> 2     2 a    
+#> 3     1 b    
+#> 4     1 a
+```
+
+``` r
+animate_union(y, x)
 ```
 
-![](images/union-rev.gif)
+![](man/figures/tidyexplain-union-y-x-1.gif)<!-- -->
 
 ``` r
-union(y, x)
+
+dplyr::union(y, x)
 #> # A tibble: 4 x 2
-#>   x     y    
-#>   <chr> <chr>
-#> 1 2     a    
-#> 2 1     b    
-#> 3 2     b    
-#> 4 1     a
+#>       x y    
+#>   <dbl> <chr>
+#> 1     2 a    
+#> 2     1 b    
+#> 3     2 b    
+#> 4     1 a
 ```
 
 ### Union All
 
 > All rows from `x` and `y`, keeping duplicates.
 
-![](images/union-all.gif)
+``` r
+animate_union_all(x, y)
+```
+
+![](man/figures/tidyexplain-union-all-1.gif)<!-- -->
 
 ``` r
-union_all(x, y)
+dplyr::union_all(x, y)
 #> # A tibble: 5 x 2
-#>   x     y    
-#>   <chr> <chr>
-#> 1 1     a    
-#> 2 1     b    
-#> 3 2     a    
-#> 4 1     a    
-#> 5 2     b
+#>       x y    
+#>   <dbl> <chr>
+#> 1     1 a    
+#> 2     1 b    
+#> 3     2 a    
+#> 4     1 a    
+#> 5     2 b
 ```
 
 ### Intersection
 
 > Common rows in both `x` and `y`, keeping just unique rows.
 
-![](images/intersect.gif)
+``` r
+animate_intersect(x, y)
+```
+
+![](man/figures/tidyexplain-intersect-1.gif)<!-- -->
 
 ``` r
-intersect(x, y)
+dplyr::intersect(x, y)
 #> # A tibble: 1 x 2
-#>   x     y    
-#>   <chr> <chr>
-#> 1 1     a
+#>       x y    
+#>   <dbl> <chr>
+#> 1     1 a
 ```
 
 ### Set Difference
@@ -326,28 +366,37 @@ intersect(x, y)
 > All rows from `x` which are not also rows in `y`, keeping just unique
 > rows.
 
-![](images/setdiff.gif)
+``` r
+animate_setdiff(x, y)
+```
+
+![](man/figures/tidyexplain-setdiff-1.gif)<!-- -->
 
 ``` r
-setdiff(x, y)
+dplyr::setdiff(x, y)
 #> # A tibble: 2 x 2
-#>   x     y    
-#>   <chr> <chr>
-#> 1 1     b    
-#> 2 2     a
+#>       x y    
+#>   <dbl> <chr>
+#> 1     1 b    
+#> 2     2 a
 ```
 
-![](images/setdiff-rev.gif)
+``` r
+animate_setdiff(y, x)
+```
+
+![](man/figures/tidyexplain-setdiff-y-x-1.gif)<!-- -->
 
 ``` r
-setdiff(y, x)
+
+dplyr::setdiff(y, x)
 #> # A tibble: 1 x 2
-#>   x     y    
-#>   <chr> <chr>
-#> 1 2     b
+#>       x y    
+#>   <dbl> <chr>
+#> 1     2 b
 ```
 
-## Tidy Data
+## Tidy Data and `gather()`, `spread()` functionality
 
 [Tidy data](http://r4ds.had.co.nz/tidy-data.html#tidy-data-1) follows
 the following three rules:
@@ -361,58 +410,88 @@ to be formatted as a tidy dataset and the
 [tidyr](https://tidyr.tidyverse.org) package provides functions to help
 you organize your data into tidy data.
 
-![](images/static/png/original-dfs-tidy.png)
+``` r
+long <- dplyr::data_frame(
+  year = c(2010, 2011, 2010, 2011, 2010, 2011),
+  person = c("Alice", "Alice", "Bob", "Bob", "Charlie", "Charlie"),
+  sales = c(105, 110, 100, 97, 90, 95)
+)
+wide <- dplyr::data_frame(
+  year = 2010:2011, 
+  Alice = c(105, 110), 
+  Bob = c(100, 97), 
+  Charlie = c(90, 95)
+)
+```
+
+### Gather
+
+> Gather takes multiple columns and collapses into key-value pairs,
+> duplicating all other columns as needed. You use gather() when you
+> notice that your column names are not names of variables, but values
+> of a variable.
 
 ``` r
-wide
-#> # A tibble: 2 x 4
-#>      id x     y     z    
-#>   <int> <chr> <chr> <chr>
-#> 1     1 a     c     e    
-#> 2     2 b     d     f
-long
-#> # A tibble: 6 x 3
-#>      id key   val  
-#>   <int> <chr> <chr>
-#> 1     1 x     a    
-#> 2     2 x     b    
-#> 3     1 y     c    
-#> 4     2 y     d    
-#> 5     1 z     e    
-#> 6     2 z     f
+set_font_size(4, 15)
+set_anim_options(anim_options(cell_width = 2))
+animate_gather(wide, key = "person", value = "sales", -year)
 ```
 
-### Spread and Gather
+![](man/figures/tidyexplain-gather-1.gif)<!-- -->
 
-`spread(data, key, value)`
+``` r
+tidyr::gather(wide, key = "person", value = "sales", -year)
+#> # A tibble: 6 x 3
+#>    year person  sales
+#>   <int> <chr>   <dbl>
+#> 1  2010 Alice     105
+#> 2  2011 Alice     110
+#> 3  2010 Bob       100
+#> 4  2011 Bob        97
+#> 5  2010 Charlie    90
+#> 6  2011 Charlie    95
+```
+
+### Spread
 
 > Spread a key-value pair across multiple columns. Use it when an a
 > column contains observations from multiple variables.
 
-`gather(data, key = "key", value = "value", ...)`
-
-> Gather takes multiple columns and collapses into key-value pairs,
-> duplicating all other columns as needed. You use `gather()` when you
-> notice that your column names are not names of variables, but *values*
-> of a variable.
+``` r
+animate_spread(long, key = "person", value = "sales")
+```
 
-![](images/tidyr-spread-gather.gif)
+![](man/figures/tidyexplain-spread-1.gif)<!-- -->
 
 ``` r
-gather(wide, key, val, x:z)
-#> # A tibble: 6 x 3
-#>      id key   val  
-#>   <int> <chr> <chr>
-#> 1     1 x     a    
-#> 2     2 x     b    
-#> 3     1 y     c    
-#> 4     2 y     d    
-#> 5     1 z     e    
-#> 6     2 z     f
-spread(long, key, val)
+tidyr::spread(long, key = "person", value = "sales")
 #> # A tibble: 2 x 4
-#>      id x     y     z    
-#>   <int> <chr> <chr> <chr>
-#> 1     1 a     c     e    
-#> 2     2 b     d     f
+#>    year Alice   Bob Charlie
+#>   <dbl> <dbl> <dbl>   <dbl>
+#> 1  2010   105   100      90
+#> 2  2011   110    97      95
 ```
+
+## Learn More
+
+### Relational Data
+
+The [Relational Data](http://r4ds.had.co.nz/relation-data.html) chapter
+of the [R for Data Science](http://r4ds.had.co.nz/) book by Garrett
+Grolemund and Hadley Wickham is an excellent resource for learning more
+about relational data.
+
+The [dplyr two-table verbs
+vignette](https://dplyr.tidyverse.org/articles/two-table.html) and Jenny
+Bryan’s [Cheatsheet for dplyr join
+functions](http://stat545.com/bit001_dplyr-cheatsheet.html) are also
+great resources.
+
+### gganimate
+
+The animations were made possible by the newly re-written
+[gganimate](https://github.com/thomasp85/gganimate#README) package by
+[Thomas Lin Pedersen](https://github.com/thomasp85) (original by [Dave
+Robinson](https://github.com/dgrtwo)). The [package
+readme](https://github.com/thomasp85/gganimate#README) provides an
+excellent (and quick) introduction to gganimte.

images/create_images.R

@@ -0,0 +1,160 @@
+library(tidyexplain)
+library(here)
+library(stringr)
+set_font_size(title_size = 20)
+
+check_and_create <- function(ff) {
+  if (!dir.exists(ff)) dir.create(ff, recursive = T)
+}
+
+check_and_create(here("images", "static", "png"))
+check_and_create(here("images", "static", "svg"))
+check_and_create(here("images", "gif"))
+
+### Animate Joins
+
+x <- dplyr::data_frame(
+  id = 1:3,
+  x = paste0("x", 1:3)
+)
+
+y <- dplyr::data_frame(
+  id = (1:4)[-3],
+  y = paste0("y", (1:4)[-3])
+)
+
+joins <- c(
+  full_join = animate_full_join,
+  inner_join = animate_inner_join,
+  left_join = animate_left_join,
+  right_join = animate_right_join,
+  semi_join = animate_semi_join
+)
+
+a <- sapply(1:length(joins), function(i) {
+  nam <- names(joins)[i]
+  nam <- str_replace(nam, "_", "-")
+  cat(nam, "\n")
+
+  width <- 7
+  height <- 7
+
+  gif_ <- joins[[i]](x, y, by = "id")
+  first_ <- joins[[i]](x, y, by = "id", export = "first")
+  last_ <- joins[[i]](x, y, by = "id", export = "last")
+
+  save_animation(animate(gif_), here("images", "gif", paste0(nam, ".gif")))
+  ggsave(here("images", "static", "png", paste0(nam, "-first.png")), first_,
+         height = height, width = width)
+  ggsave(here("images", "static", "svg", paste0(nam, "-first.svg")), first_,
+         height = height, width = width)
+  ggsave(here("images", "static", "png", paste0(nam, "-last.png")), last_,
+         height = height, width = width)
+  ggsave(here("images", "static", "svg", paste0(nam, "-last.svg")), last_,
+         height = height, width = width)
+})
+
+### Animate Sets
+
+x <- tibble::tribble(
+  ~x,    ~y,
+  "1",  "a",
+  "1",  "b",
+  "2",  "a"
+)
+
+y <- tibble::tribble(
+  ~x, ~y,
+  "1",  "a",
+  "2",  "b"
+)
+
+sets <- c(
+  union = animate_union,
+  union_all = animate_union_all,
+  intersect = animate_intersect,
+  setdiff = animate_setdiff
+)
+
+a <- sapply(1:length(sets), function(i) {
+  nam <- names(sets)[i]
+  nam <- str_replace(nam, "_", "-")
+
+  cat(nam, "\n")
+
+  width <- 7
+  height <- 7
+
+  gif_ <- sets[[i]](x, y)
+  first_ <- sets[[i]](x, y, export = "first")
+  last_ <- sets[[i]](x, y, export = "last")
+
+  save_animation(animate(gif_), here("images", "gif", paste0(nam, ".gif")))
+  ggsave(here("images", "static", "png", paste0(nam, "-first.png")), first_,
+         height = height, width = width)
+  ggsave(here("images", "static", "svg", paste0(nam, "-first.svg")), first_,
+         height = height, width = width)
+  ggsave(here("images", "static", "png", paste0(nam, "-last.png")), last_,
+         height = height, width = width)
+  ggsave(here("images", "static", "svg", paste0(nam, "-last.svg")), last_,
+         height = height, width = width)
+})
+
+
+### Animate Gather Spread
+set_font_size(text_size = 4)
+set_anim_options(anim_options(cell_width = 2))
+
+# Gather
+wide <- dplyr::data_frame(
+  year = 2010:2011,
+  Alice = c(105, 110),
+  Bob = c(100, 97),
+  Charlie = c(90, 95)
+)
+
+nam <- "gather"
+cat(nam, "\n")
+
+width <- 7
+height <- 7
+
+gif_ <- animate_gather(wide, key = "person", value = "sales", -year, cell_width = 2)
+first_ <- animate_gather(wide, key = "person", value = "sales", -year, export = "first")
+last_ <- animate_gather(wide, key = "person", value = "sales", -year, export = "last")
+
+save_animation(animate(gif_), here("images", "gif", paste0(nam, ".gif")))
+ggsave(here("images", "static", "png", paste0(nam, "-first.png")), first_,
+       height = height, width = width)
+ggsave(here("images", "static", "svg", paste0(nam, "-first.svg")), first_,
+       height = height, width = width)
+ggsave(here("images", "static", "png", paste0(nam, "-last.png")), last_,
+       height = height, width = width)
+ggsave(here("images", "static", "svg", paste0(nam, "-last.svg")), last_,
+       height = height, width = width)
+
+# Spread
+long <- dplyr::data_frame(
+  year = c(2010, 2011, 2010, 2011, 2010, 2011),
+  person = c("Alice", "Alice", "Bob", "Bob", "Charlie", "Charlie"),
+  sales = c(105, 110, 100, 97, 90, 95)
+)
+nam <- "spread"
+cat(nam, "\n")
+
+width <- 7
+height <- 7
+
+gif_ <- animate_spread(long, key = "person", value = "sales")
+first_ <- animate_spread(long, key = "person", value = "sales", export = "first")
+last_ <- animate_spread(long, key = "person", value = "sales", export = "last")
+
+save_animation(animate(gif_), here("images", "gif", paste0(nam, ".gif")))
+ggsave(here("images", "static", "png", paste0(nam, "-first.png")), first_,
+       height = height, width = width)
+ggsave(here("images", "static", "svg", paste0(nam, "-first.svg")), first_,
+       height = height, width = width)
+ggsave(here("images", "static", "png", paste0(nam, "-last.png")), last_,
+       height = height, width = width)
+ggsave(here("images", "static", "svg", paste0(nam, "-last.svg")), last_,
+       height = height, width = width)

images/static/svg/anti-join.svg

@@ -1,44 +0,0 @@
-<?xml version='1.0' encoding='UTF-8' ?>
-<svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' viewBox='0 0 504.00 360.00'>
-<defs>
-  <style type='text/css'><![CDATA[
-    line, polyline, path, rect, circle {
-      fill: none;
-      stroke: #000000;
-      stroke-linecap: round;
-      stroke-linejoin: round;
-      stroke-miterlimit: 10.00;
-    }
-  ]]></style>
-</defs>
-<rect width='100%' height='100%' style='stroke: none; fill: #FFFFFF;'/>
-<defs>
-  <clipPath id='cpMHw1MDR8MzQzLjY0OXw0MS4yNDkx'>
-    <rect x='0.00' y='41.25' width='504.00' height='302.40' />
-  </clipPath>
-</defs>
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