Commit ⋅ rsquaredacademy/rfm


  ulm <-
    mapdata %>%
    magrittr::extract2("monetary") %>%
    extract2("monetary") %>%
    max() %>%
    ceiling(.)

  llm <-
    mapdata %>%
    magrittr::extract2("monetary") %>%
    extract2("monetary") %>%
    min() %>%
    floor(.)

  bins <-
    mapdata %>%
    magrittr::use_series(frequency_score) %>%
    use_series(frequency_score) %>%
    max()

  guide_breaks <-

@@ -69,13 +69,13 @@

    round()

  p <-
    ggplot2::ggplot(data = mapdata) +
    ggplot2::geom_tile(ggplot2::aes(x = frequency_score, y = recency_score, fill = monetary)) +
    ggplot2::scale_fill_gradientn(limits = c(llm, ulm),
    ggplot(data = mapdata) +
    geom_tile(aes(x = frequency_score, y = recency_score, fill = monetary)) +
    scale_fill_gradientn(limits = c(llm, ulm),
                         colours = RColorBrewer::brewer.pal(n = brewer_n, name = brewer_name),
                         name = legend_title) +
    ggplot2::ggtitle(plot_title) + ggplot2::xlab(xaxis_title) + ggplot2::ylab(yaxis_title) +
    ggplot2::theme(plot.title = ggplot2::element_text(hjust = plot_title_justify))
    ggtitle(plot_title) + xlab(xaxis_title) + ylab(yaxis_title) +
    theme(plot.title = element_text(hjust = plot_title_justify))

  if (print_plot) {
    print(p)

@@ -132,14 +132,14 @@


  p <-
    rfm_hist_data(rfm_table) %>%
    ggplot2::ggplot(ggplot2::aes(score)) +
    ggplot2::geom_histogram(bins = hist_bins, fill = hist_color) +
    ggplot2::ylab(yaxis_title) + ggplot2::ggtitle(plot_title) + ggplot2::xlab(xaxis_title) +
    ggplot2::facet_grid(. ~ rfm, scales = "free_x",
      labeller = ggplot2::labeller(
    ggplot(aes(score)) +
    geom_histogram(bins = hist_bins, fill = hist_color) +
    ylab(yaxis_title) + ggtitle(plot_title) + xlab(xaxis_title) +
    facet_grid(. ~ rfm, scales = "free_x",
      labeller = labeller(
        rfm = c(amount = hist_m_label, recency_days = hist_r_label,
                transaction_count = hist_f_label))) +
    ggplot2::theme(plot.title = ggplot2::element_text(hjust = plot_title_justify))
    theme(plot.title = element_text(hjust = plot_title_justify))

  if (print_plot) {
    print(p)

@@ -185,17 +185,17 @@


  p <-
    rfm_barchart_data(rfm_table) %>%
    ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = monetary_score), fill = bar_color) +
    ggplot2::facet_grid(recency_score ~ frequency_score) +
    ggplot2::scale_y_continuous(sec.axis = ggplot2::sec_axis(~ ., name = sec_yaxis_title)) +
    ggplot2::xlab(xaxis_title) + ggplot2::ylab(" ") + ggplot2::ggtitle(sec_xaxis_title) +
    ggplot2::theme(
      plot.title = ggplot2::element_text(
    ggplot() +
    geom_bar(aes(x = monetary_score), fill = bar_color) +
    facet_grid(recency_score ~ frequency_score) +
    scale_y_continuous(sec.axis = sec_axis(~ ., name = sec_yaxis_title)) +
    xlab(xaxis_title) + ylab(" ") + ggtitle(sec_xaxis_title) +
    theme(
      plot.title = element_text(
        face = "plain", size = 11, hjust = 0.5
      ),
      axis.text.y = ggplot2::element_blank(),
      axis.ticks.y = ggplot2::element_blank()
      axis.text.y = element_blank(),
      axis.ticks.y = element_blank()
    )

  if (print_plot) {

@@ -248,26 +248,26 @@


  data <-
    rfm_table %>%
    magrittr::use_series(rfm) %>%
    use_series(rfm) %>%
    dplyr::count(transaction_count)

  ylim_max <-
    data %>%
    dplyr::pull(n) %>%
    max() %>%
    magrittr::multiply_by(1.1) %>%
    multiply_by(1.1) %>%
    ceiling(.)

  p <-
    data %>%
    ggplot2::ggplot(ggplot2::aes(x = transaction_count, y = n)) +
    ggplot2::geom_bar(stat = "identity", fill = bar_color) +
    ggplot2::xlab(xaxis_title) + ggplot2::ylab(yaxis_title) + ggplot2::ylim(0, ylim_max) +
    ggplot2::ggtitle(plot_title) +
    ggplot2::geom_text(
      ggplot2::aes(label = n, y = n + 3), position = ggplot2::position_dodge(0.9), vjust = 0
    ggplot(aes(x = transaction_count, y = n)) +
    geom_bar(stat = "identity", fill = bar_color) +
    xlab(xaxis_title) + ylab(yaxis_title) + ylim(0, ylim_max) +
    ggtitle(plot_title) +
    geom_text(
      aes(label = n, y = n + 3), position = position_dodge(0.9), vjust = 0
    ) +
    ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5))
    theme(plot.title = element_text(hjust = 0.5))

  if (print_plot) {
    print(p)

@@ -316,10 +316,10 @@


  p <-
    rfm_table %>%
    magrittr::use_series(rfm) %>%
    ggplot2::ggplot() +
    ggplot2::geom_point(ggplot2::aes(x = amount, y = recency_days), color = point_color) +
    ggplot2::xlab(xaxis_title) + ggplot2::ylab(yaxis_title) + ggplot2::ggtitle(plot_title)
    use_series(rfm) %>%
    ggplot() +
    geom_point(aes(x = amount, y = recency_days), color = point_color) +
    xlab(xaxis_title) + ylab(yaxis_title) + ggtitle(plot_title)

  if (print_plot) {
    print(p)

@@ -339,10 +339,10 @@


  p <-
    rfm_table %>%
    magrittr::use_series(rfm) %>%
    ggplot2::ggplot() +
    ggplot2::geom_point(ggplot2::aes(x = amount, y = transaction_count), color = point_color) +
    ggplot2::xlab(xaxis_title) + ggplot2::ylab(yaxis_title) + ggplot2::ggtitle(plot_title)
    use_series(rfm) %>%
    ggplot() +
    geom_point(aes(x = amount, y = transaction_count), color = point_color) +
    xlab(xaxis_title) + ylab(yaxis_title) + ggtitle(plot_title)

  if (print_plot) {
    print(p)

@@ -362,10 +362,10 @@


  p <-
    rfm_table %>%
    magrittr::use_series(rfm) %>%
    ggplot2::ggplot() +
    ggplot2::geom_point(ggplot2::aes(x = transaction_count, y = recency_days), color = point_color) +
    ggplot2::xlab(xaxis_title) + ggplot2::ylab(yaxis_title) + ggplot2::ggtitle(plot_title)
    use_series(rfm) %>%
    ggplot() +
    geom_point(aes(x = transaction_count, y = recency_days), color = point_color) +
    xlab(xaxis_title) + ylab(yaxis_title) + ggtitle(plot_title)

  if (print_plot) {
    print(p)

@@ -60,7 +60,7 @@

      recency_days = (analysis_date - !! recent_visit) / lubridate::ddays()
    ) %>%
    dplyr::select(!! cust_id, recency_days, !! order_count, !! revenues) %>%
    magrittr::set_names(c("customer_id", "recency_days", "transaction_count", "amount"))
    set_names(c("customer_id", "recency_days", "transaction_count", "amount"))

  result$recency_score   <- NA
  result$frequency_score <- NA

@@ -8,7 +8,7 @@

#'
rfm_launch_app <- function() {

	rlang::inform("`rfm_launch_app()` has been soft-deprecated and will be removed in the next release. In future, to launch the app, run the below code:\n 
	message("`rfm_launch_app()` has been soft-deprecated and will be removed in the next release. In future, to launch the app, run the below code:\n 
	- install.packages('xplorerr')\n - xplorerr::app_rfm_analysis()\n")

	check_suggests('haven')

@@ -1,4 +1,3 @@

1		-	#' @importFrom utils packageVersion
2	1		.onAttach <- function(...) {
3	2
4	3		if (!interactive() \|\| stats::runif(1) > 0.1) return()

@@ -65,7 +65,7 @@

      !! cust_id, date_most_recent, recency_days, transaction_count,
      amount
    ) %>%
    magrittr::set_names(c("customer_id", "date_most_recent", "recency_days", "transaction_count", "amount"))
    set_names(c("customer_id", "date_most_recent", "recency_days", "transaction_count", "amount"))

  result$recency_score   <- NA
  result$frequency_score <- NA

@@ -1,24 +1,27 @@

#' @importFrom magrittr %>% %<>%
#' @import magrittr 
#' @import ggplot2
#' @import dplyr
#' @import stats
bins <- function(data, value, n_bins) {

  my_value   <- rlang::enquo(value)
  my_value   <- enquo(value)
  length_out <- n_bins + 1

  data %>%
    dplyr::pull(!! my_value) %>%
    stats::quantile(probs = seq(0, 1, length.out = length_out)) %>%
    pull(!! my_value) %>%
    quantile(probs = seq(0, 1, length.out = length_out)) %>%
    unname() %>%
    magrittr::extract(c(-1, -length_out)) %>%
    magrittr::add(1)
    extract(c(-1, -length_out)) %>%
    add(1)

}

bins_lower <- function(data, value, bins) {

  my_value <- rlang::enquo(value)
  my_value <- enquo(value)

  data %>%
    dplyr::pull(!! my_value) %>%
    pull(!! my_value) %>%
    min() %>%
    append(bins)


@@ -26,13 +29,13 @@


bins_upper <- function(data, value, bins) {

  my_value <- rlang::enquo(value)
  my_value <- enquo(value)

  data_max <-
    data %>%
    dplyr::pull(!! my_value) %>%
    pull(!! my_value) %>%
    max() %>%
    magrittr::add(1)
    add(1)

  c(bins, data_max)
}

@@ -40,10 +43,10 @@


check_levels <- function(rfm_heatmap_data, column) {

  my_column <- rlang::enquo(column)
  my_column <- enquo(column)

  rfm_heatmap_data %>%
    dplyr::pull(!! my_column) %>%
    pull(!! my_column) %>%
    as.factor() %>%
    levels() %>%
    as.vector() %>%

@@ -58,14 +61,14 @@

  extra_data        <- expand.grid(missing2, seq_len(n_bins), 0)
  names(extra_data) <- names(rfm_heatmap_data)

  dplyr::bind_rows(rfm_heatmap_data, extra_data)
  bind_rows(rfm_heatmap_data, extra_data)

}

#' @importFrom utils packageVersion menu install.packages
#' @import utils
check_suggests <- function(pkg) {

  pkg_flag <- tryCatch(utils::packageVersion(pkg), error = function(e) NA)
  pkg_flag <- tryCatch(packageVersion(pkg), error = function(e) NA)

  if (is.na(pkg_flag)) {


@@ -73,8 +76,8 @@


    if (interactive()) {
      message(msg, "\nWould you like to install it?")
      if (utils::menu(c("Yes", "No")) == 1) {
        utils::install.packages(pkg)
      if (menu(c("Yes", "No")) == 1) {
        install.packages(pkg)
      } else {
        stop(msg, call. = FALSE)
      }

@@ -57,7 +57,7 @@

  result <-
    data %>%
    dplyr::select(!! cust_id, !! n_recency, !! order_count, !! revenues) %>%
    magrittr::set_names(c("customer_id", "recency_days", "transaction_count", "amount"))
    set_names(c("customer_id", "recency_days", "transaction_count", "amount"))

  result$recency_score   <- NA
  result$frequency_score <- NA

@@ -42,7 +42,7 @@


  rfm_score_table <-
    data %>%
    magrittr::use_series(rfm) %>%
    use_series(rfm) %>%
    dplyr::mutate(segment = 1)

  n_segments <- length(segment_names)

@@ -109,19 +109,18 @@

    dplyr::group_by(segment) %>%
    dplyr::select(segment, recency_days) %>%
    dplyr::summarise(avg_recency = stats::median(recency_days)) %>%
    # dplyr::rename(segment = segment, avg_recency = `median(recency_days)`) %>%
    dplyr::arrange(avg_recency)

  n_fill <- nrow(data)

  p <-
    ggplot2::ggplot(data, ggplot2::aes(segment, avg_recency)) +
    ggplot2::geom_bar(stat = "identity", fill = ggthemes::calc_pal()(n_fill)) +
    ggplot2::xlab("Segment") + ggplot2::ylab("Median Recency") +
    ggplot2::ggtitle("Median Recency by Segment") +
    ggplot2::coord_flip() +
    ggplot2::theme(
      plot.title = ggplot2::element_text(hjust = 0.5)
    ggplot(data, aes(segment, avg_recency)) +
    geom_bar(stat = "identity", fill = ggthemes::calc_pal()(n_fill)) +
    xlab("Segment") + ylab("Median Recency") +
    ggtitle("Median Recency by Segment") +
    coord_flip() +
    theme(
      plot.title = element_text(hjust = 0.5)
    )

  if (print_plot) {

@@ -151,13 +150,13 @@

  n_fill <- nrow(data)

  p <-
    ggplot2::ggplot(data, ggplot2::aes(segment, avg_frequency)) +
    ggplot2::geom_bar(stat = "identity", fill = ggthemes::calc_pal()(n_fill)) +
    ggplot2::xlab("Segment") + ggplot2::ylab("Median Frequency") +
    ggplot2::ggtitle("Median Frequency by Segment") +
    ggplot2::coord_flip() +
    ggplot2::theme(
      plot.title = ggplot2::element_text(hjust = 0.5)
    ggplot(data, aes(segment, avg_frequency)) +
    geom_bar(stat = "identity", fill = ggthemes::calc_pal()(n_fill)) +
    xlab("Segment") + ylab("Median Frequency") +
    ggtitle("Median Frequency by Segment") +
    coord_flip() +
    theme(
      plot.title = element_text(hjust = 0.5)
    )

  if (print_plot) {

@@ -188,13 +187,13 @@

  n_fill <- nrow(data)

  p <-
    ggplot2::ggplot(data, ggplot2::aes(segment, avg_monetary)) +
    ggplot2::geom_bar(stat = "identity", fill = ggthemes::calc_pal()(n_fill)) +
    ggplot2::xlab("Segment") + ggplot2::ylab("Median Monetary Value") +
    ggplot2::ggtitle("Median Monetary Value by Segment") +
    ggplot2::coord_flip() +
    ggplot2::theme(
      plot.title = ggplot2::element_text(hjust = 0.5)
    ggplot(data, aes(segment, avg_monetary)) +
    geom_bar(stat = "identity", fill = ggthemes::calc_pal()(n_fill)) +
    xlab("Segment") + ylab("Median Monetary Value") +
    ggtitle("Median Monetary Value by Segment") +
    coord_flip() +
    theme(
      plot.title = element_text(hjust = 0.5)
    )

  if (print_plot) {

Files		•	•	•	Coverage
R	513	455	0	58	88.69%
Project Totals (9 files)	513	455	0	58	88.69%

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comment: false

coverage:
  status:
    project:
      default:
        target: auto
        threshold: 1%
        informational: true
    patch:
      default:
        target: auto
        threshold: 1%
        informational: true

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132	132
133	133		p <-
134	134		rfm_hist_data(rfm_table) %>%
135		-	ggplot2::ggplot(ggplot2::aes(score)) +
136		-	ggplot2::geom_histogram(bins = hist_bins, fill = hist_color) +
137		-	ggplot2::ylab(yaxis_title) + ggplot2::ggtitle(plot_title) + ggplot2::xlab(xaxis_title) +
138		-	ggplot2::facet_grid(. ~ rfm, scales = "free_x",
139		-	labeller = ggplot2::labeller(
	135	+	ggplot(aes(score)) +
	136	+	geom_histogram(bins = hist_bins, fill = hist_color) +
	137	+	ylab(yaxis_title) + ggtitle(plot_title) + xlab(xaxis_title) +
	138	+	facet_grid(. ~ rfm, scales = "free_x",
	139	+	labeller = labeller(
140	140		rfm = c(amount = hist_m_label, recency_days = hist_r_label,
141	141		transaction_count = hist_f_label))) +
142		-	ggplot2::theme(plot.title = ggplot2::element_text(hjust = plot_title_justify))
	142	+	theme(plot.title = element_text(hjust = plot_title_justify))
143	143
144	144		if (print_plot) {
145	145		print(p)

248	248
249	249		data <-
250	250		rfm_table %>%
251		-	magrittr::use_series(rfm) %>%
	251	+	use_series(rfm) %>%
252	252		dplyr::count(transaction_count)
253	253
254	254		ylim_max <-
255	255		data %>%
256	256		dplyr::pull(n) %>%
257	257		max() %>%
258		-	magrittr::multiply_by(1.1) %>%
	258	+	multiply_by(1.1) %>%
259	259		ceiling(.)
260	260
261	261		p <-
262	262		data %>%
263		-	ggplot2::ggplot(ggplot2::aes(x = transaction_count, y = n)) +
264		-	ggplot2::geom_bar(stat = "identity", fill = bar_color) +
265		-	ggplot2::xlab(xaxis_title) + ggplot2::ylab(yaxis_title) + ggplot2::ylim(0, ylim_max) +
266		-	ggplot2::ggtitle(plot_title) +
267		-	ggplot2::geom_text(
268		-	ggplot2::aes(label = n, y = n + 3), position = ggplot2::position_dodge(0.9), vjust = 0
	263	+	ggplot(aes(x = transaction_count, y = n)) +
	264	+	geom_bar(stat = "identity", fill = bar_color) +
	265	+	xlab(xaxis_title) + ylab(yaxis_title) + ylim(0, ylim_max) +
	266	+	ggtitle(plot_title) +
	267	+	geom_text(
	268	+	aes(label = n, y = n + 3), position = position_dodge(0.9), vjust = 0
269	269		) +
270		-	ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5))
	270	+	theme(plot.title = element_text(hjust = 0.5))
271	271
272	272		if (print_plot) {
273	273		print(p)

316	316
317	317		p <-
318	318		rfm_table %>%
319		-	magrittr::use_series(rfm) %>%
320		-	ggplot2::ggplot() +
321		-	ggplot2::geom_point(ggplot2::aes(x = amount, y = recency_days), color = point_color) +
322		-	ggplot2::xlab(xaxis_title) + ggplot2::ylab(yaxis_title) + ggplot2::ggtitle(plot_title)
	319	+	use_series(rfm) %>%
	320	+	ggplot() +
	321	+	geom_point(aes(x = amount, y = recency_days), color = point_color) +
	322	+	xlab(xaxis_title) + ylab(yaxis_title) + ggtitle(plot_title)
323	323
324	324		if (print_plot) {
325	325		print(p)

339	339
340	340		p <-
341	341		rfm_table %>%
342		-	magrittr::use_series(rfm) %>%
343		-	ggplot2::ggplot() +
344		-	ggplot2::geom_point(ggplot2::aes(x = amount, y = transaction_count), color = point_color) +
345		-	ggplot2::xlab(xaxis_title) + ggplot2::ylab(yaxis_title) + ggplot2::ggtitle(plot_title)
	342	+	use_series(rfm) %>%
	343	+	ggplot() +
	344	+	geom_point(aes(x = amount, y = transaction_count), color = point_color) +
	345	+	xlab(xaxis_title) + ylab(yaxis_title) + ggtitle(plot_title)
346	346
347	347		if (print_plot) {
348	348		print(p)

362	362
363	363		p <-
364	364		rfm_table %>%
365		-	magrittr::use_series(rfm) %>%
366		-	ggplot2::ggplot() +
367		-	ggplot2::geom_point(ggplot2::aes(x = transaction_count, y = recency_days), color = point_color) +
368		-	ggplot2::xlab(xaxis_title) + ggplot2::ylab(yaxis_title) + ggplot2::ggtitle(plot_title)
	365	+	use_series(rfm) %>%
	366	+	ggplot() +
	367	+	geom_point(aes(x = transaction_count, y = recency_days), color = point_color) +
	368	+	xlab(xaxis_title) + ylab(yaxis_title) + ggtitle(plot_title)
369	369
370	370		if (print_plot) {
371	371		print(p)

49	49
50	50		ulm <-
51	51		mapdata %>%
52		-	magrittr::extract2("monetary") %>%
	52	+	extract2("monetary") %>%
53	53		max() %>%
54	54		ceiling(.)
55	55
56	56		llm <-
57	57		mapdata %>%
58		-	magrittr::extract2("monetary") %>%
	58	+	extract2("monetary") %>%
59	59		min() %>%
60	60		floor(.)
61	61
62	62		bins <-
63	63		mapdata %>%
64		-	magrittr::use_series(frequency_score) %>%
	64	+	use_series(frequency_score) %>%
65	65		max()
66	66
67	67		guide_breaks <-

69	69		round()
70	70
71	71		p <-
72		-	ggplot2::ggplot(data = mapdata) +
73		-	ggplot2::geom_tile(ggplot2::aes(x = frequency_score, y = recency_score, fill = monetary)) +
74		-	ggplot2::scale_fill_gradientn(limits = c(llm, ulm),
	72	+	ggplot(data = mapdata) +
	73	+	geom_tile(aes(x = frequency_score, y = recency_score, fill = monetary)) +
	74	+	scale_fill_gradientn(limits = c(llm, ulm),
75	75		colours = RColorBrewer::brewer.pal(n = brewer_n, name = brewer_name),
76	76		name = legend_title) +
77		-	ggplot2::ggtitle(plot_title) + ggplot2::xlab(xaxis_title) + ggplot2::ylab(yaxis_title) +
78		-	ggplot2::theme(plot.title = ggplot2::element_text(hjust = plot_title_justify))
	77	+	ggtitle(plot_title) + xlab(xaxis_title) + ylab(yaxis_title) +
	78	+	theme(plot.title = element_text(hjust = plot_title_justify))
79	79
80	80		if (print_plot) {
81	81		print(p)

185	185
186	186		p <-
187	187		rfm_barchart_data(rfm_table) %>%
188		-	ggplot2::ggplot() +
189		-	ggplot2::geom_bar(ggplot2::aes(x = monetary_score), fill = bar_color) +
190		-	ggplot2::facet_grid(recency_score ~ frequency_score) +
191		-	ggplot2::scale_y_continuous(sec.axis = ggplot2::sec_axis(~ ., name = sec_yaxis_title)) +
192		-	ggplot2::xlab(xaxis_title) + ggplot2::ylab(" ") + ggplot2::ggtitle(sec_xaxis_title) +
193		-	ggplot2::theme(
194		-	plot.title = ggplot2::element_text(
	188	+	ggplot() +
	189	+	geom_bar(aes(x = monetary_score), fill = bar_color) +
	190	+	facet_grid(recency_score ~ frequency_score) +
	191	+	scale_y_continuous(sec.axis = sec_axis(~ ., name = sec_yaxis_title)) +
	192	+	xlab(xaxis_title) + ylab(" ") + ggtitle(sec_xaxis_title) +
	193	+	theme(
	194	+	plot.title = element_text(
195	195		face = "plain", size = 11, hjust = 0.5
196	196		),
197		-	axis.text.y = ggplot2::element_blank(),
198		-	axis.ticks.y = ggplot2::element_blank()
	197	+	axis.text.y = element_blank(),
	198	+	axis.ticks.y = element_blank()
199	199		)
200	200
201	201		if (print_plot) {

60	60		recency_days = (analysis_date - !! recent_visit) / lubridate::ddays()
61	61		) %>%
62	62		dplyr::select(!! cust_id, recency_days, !! order_count, !! revenues) %>%
63		-	magrittr::set_names(c("customer_id", "recency_days", "transaction_count", "amount"))
	63	+	set_names(c("customer_id", "recency_days", "transaction_count", "amount"))
64	64
65	65		result$recency_score <- NA
66	66		result$frequency_score <- NA

8	8		#'
9	9		rfm_launch_app <- function() {
10	10
11		-	rlang::inform("`rfm_launch_app()` has been soft-deprecated and will be removed in the next release. In future, to launch the app, run the below code:\n
	11	+	message("`rfm_launch_app()` has been soft-deprecated and will be removed in the next release. In future, to launch the app, run the below code:\n
12	12		- install.packages('xplorerr')\n - xplorerr::app_rfm_analysis()\n")
13	13
14	14		check_suggests('haven')

65	65		!! cust_id, date_most_recent, recency_days, transaction_count,
66	66		amount
67	67		) %>%
68		-	magrittr::set_names(c("customer_id", "date_most_recent", "recency_days", "transaction_count", "amount"))
	68	+	set_names(c("customer_id", "date_most_recent", "recency_days", "transaction_count", "amount"))
69	69
70	70		result$recency_score <- NA
71	71		result$frequency_score <- NA

1		-	#' @importFrom magrittr %>% %<>%
	1	+	#' @import magrittr
	2	+	#' @import ggplot2
	3	+	#' @import dplyr
	4	+	#' @import stats
2	5		bins <- function(data, value, n_bins) {
3	6
4		-	my_value <- rlang::enquo(value)
	7	+	my_value <- enquo(value)
5	8		length_out <- n_bins + 1
6	9
7	10		data %>%
8		-	dplyr::pull(!! my_value) %>%
9		-	stats::quantile(probs = seq(0, 1, length.out = length_out)) %>%
	11	+	pull(!! my_value) %>%
	12	+	quantile(probs = seq(0, 1, length.out = length_out)) %>%
10	13		unname() %>%
11		-	magrittr::extract(c(-1, -length_out)) %>%
12		-	magrittr::add(1)
	14	+	extract(c(-1, -length_out)) %>%
	15	+	add(1)
13	16
14	17		}
15	18
16	19		bins_lower <- function(data, value, bins) {
17	20
18		-	my_value <- rlang::enquo(value)
	21	+	my_value <- enquo(value)
19	22
20	23		data %>%
21		-	dplyr::pull(!! my_value) %>%
	24	+	pull(!! my_value) %>%
22	25		min() %>%
23	26		append(bins)
24	27

26	29
27	30		bins_upper <- function(data, value, bins) {
28	31
29		-	my_value <- rlang::enquo(value)
	32	+	my_value <- enquo(value)
30	33
31	34		data_max <-
32	35		data %>%
33		-	dplyr::pull(!! my_value) %>%
	36	+	pull(!! my_value) %>%
34	37		max() %>%
35		-	magrittr::add(1)
	38	+	add(1)
36	39
37	40		c(bins, data_max)
38	41		}

40	43
41	44		check_levels <- function(rfm_heatmap_data, column) {
42	45
43		-	my_column <- rlang::enquo(column)
	46	+	my_column <- enquo(column)
44	47
45	48		rfm_heatmap_data %>%
46		-	dplyr::pull(!! my_column) %>%
	49	+	pull(!! my_column) %>%
47	50		as.factor() %>%
48	51		levels() %>%
49	52		as.vector() %>%

58	61		extra_data <- expand.grid(missing2, seq_len(n_bins), 0)
59	62		names(extra_data) <- names(rfm_heatmap_data)
60	63
61		-	dplyr::bind_rows(rfm_heatmap_data, extra_data)
	64	+	bind_rows(rfm_heatmap_data, extra_data)
62	65
63	66		}
64	67
65		-	#' @importFrom utils packageVersion menu install.packages
	68	+	#' @import utils
66	69		check_suggests <- function(pkg) {
67	70
68		-	pkg_flag <- tryCatch(utils::packageVersion(pkg), error = function(e) NA)
	71	+	pkg_flag <- tryCatch(packageVersion(pkg), error = function(e) NA)
69	72
70	73		if (is.na(pkg_flag)) {
71	74

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73	76
74	77		if (interactive()) {
75	78		message(msg, "\nWould you like to install it?")
76		-	if (utils::menu(c("Yes", "No")) == 1) {
77		-	utils::install.packages(pkg)
	79	+	if (menu(c("Yes", "No")) == 1) {
	80	+	install.packages(pkg)
78	81		} else {
79	82		stop(msg, call. = FALSE)
80	83		}

57	57		result <-
58	58		data %>%
59	59		dplyr::select(!! cust_id, !! n_recency, !! order_count, !! revenues) %>%
60		-	magrittr::set_names(c("customer_id", "recency_days", "transaction_count", "amount"))
	60	+	set_names(c("customer_id", "recency_days", "transaction_count", "amount"))
61	61
62	62		result$recency_score <- NA
63	63		result$frequency_score <- NA

42	42
43	43		rfm_score_table <-
44	44		data %>%
45		-	magrittr::use_series(rfm) %>%
	45	+	use_series(rfm) %>%
46	46		dplyr::mutate(segment = 1)
47	47
48	48		n_segments <- length(segment_names)

109	109		dplyr::group_by(segment) %>%
110	110		dplyr::select(segment, recency_days) %>%
111	111		dplyr::summarise(avg_recency = stats::median(recency_days)) %>%
112		-	# dplyr::rename(segment = segment, avg_recency = `median(recency_days)`) %>%
113	112		dplyr::arrange(avg_recency)
114	113
115	114		n_fill <- nrow(data)
116	115
117	116		p <-
118		-	ggplot2::ggplot(data, ggplot2::aes(segment, avg_recency)) +
119		-	ggplot2::geom_bar(stat = "identity", fill = ggthemes::calc_pal()(n_fill)) +
120		-	ggplot2::xlab("Segment") + ggplot2::ylab("Median Recency") +
121		-	ggplot2::ggtitle("Median Recency by Segment") +
122		-	ggplot2::coord_flip() +
123		-	ggplot2::theme(
124		-	plot.title = ggplot2::element_text(hjust = 0.5)
	117	+	ggplot(data, aes(segment, avg_recency)) +
	118	+	geom_bar(stat = "identity", fill = ggthemes::calc_pal()(n_fill)) +
	119	+	xlab("Segment") + ylab("Median Recency") +
	120	+	ggtitle("Median Recency by Segment") +
	121	+	coord_flip() +
	122	+	theme(
	123	+	plot.title = element_text(hjust = 0.5)
125	124		)
126	125
127	126		if (print_plot) {

1	comment: false
2
3	coverage:
4	status:
5	project:
6	default:
7	target: auto
8	threshold: 1%
9	informational: true
10	patch:
11	default:
12	target: auto
13	threshold: 1%
14	informational: true

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