On CRAN

.Rbuildignore

@@ -15,3 +15,4 @@
 ^docs$
 ^debug\.log$
 ^\.github$
+^revdep$

DESCRIPTION

@@ -43,5 +43,5 @@ Suggests:
 VignetteBuilder: knitr
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.1.1
+RoxygenNote: 7.2.3
 Config/testthat/edition: 3

NAMESPACE

@@ -34,7 +34,11 @@ export(rfm_table_order)
 importFrom(RColorBrewer,brewer.pal)
 importFrom(dplyr,arrange)
 importFrom(dplyr,between)
+importFrom(dplyr,distinct)
+importFrom(dplyr,everything)
 importFrom(dplyr,group_by)
+importFrom(dplyr,join_by)
+importFrom(dplyr,left_join)
 importFrom(dplyr,mutate)
 importFrom(dplyr,n)
 importFrom(dplyr,pull)

NEWS.md

@@ -1,3 +1,18 @@
+# rfm 0.3.0
+
+## Enhancements
+
+- segment overview ([#76](https://github.com/rsquaredacademy/rfm/issues/76))
+- `rfm_create_report()` generates a segmentation analysis report
+- `rfm_table_customer()` handles customer level data with both recency date and days
+- `interactive` argument in plotting function generates interactive plots using [plotly](https://plotly.com/r/)
+- `animate` argument in plotting functions adds animation using [gganimate](https://gganimate.com)
+
+## Bug Fixes
+
+- incorrect package alias ([#88](https://github.com/rsquaredacademy/rfm/issues/88))
+- cran checks badge ([#80](https://github.com/rsquaredacademy/rfm/issues/80))
+
 # rfm 0.2.2
 
 This is a patch release for an urgent bug fix.
@@ -22,7 +37,7 @@ This is a minor release for bug fixes and enhancements.
 
 - Export plot prep data ([#20](https://github.com/rsquaredacademy/rfm/issues/20))
 - Default customer segments ([#24](https://github.com/rsquaredacademy/rfm/issues/24))
-- Median Recency ([#26](https://github.com/rsquaredacademy/rfm/issues/26))
+- Median recency ([#26](https://github.com/rsquaredacademy/rfm/issues/26))
 - Median frequency ([#27](https://github.com/rsquaredacademy/rfm/issues/27))
 - Median monetary value ([#28](https://github.com/rsquaredacademy/rfm/issues/28))
 

R/rfm-data.R

@@ -4,9 +4,12 @@
 #'
 #' @format A tibble with 49.6 rows and 3 variables:
 #' \describe{
-#'   \item{order_date}{order date}
-#'   \item{customer_id}{customer id}
-#'   \item{revenue}{transaction amount}
+#'   \item{order_date}{Order date.}
+#'   \item{customer_id}{Customer id}
+#'   \item{revenue}{Transaction amount.}
+#'   \item{first_name}{First name of the customer.}
+#'   \item{last_name}{Last name of the customer.}
+#'   \item{email}{email id of the customer.}
 #' }
 #'
 "rfm_data_orders"
@@ -22,6 +25,9 @@
 #'   \item{most_recent_visit}{Date of the most recent transaction.}
 #'   \item{number_of_purchases}{Total number of transactions/orders.}
 #'   \item{purchase_interval}{Number of days since last transaction/order.}
+#'   #'   \item{first_name}{First name of the customer.}
+#'   \item{last_name}{Last name of the customer.}
+#'   \item{email}{email id of the customer.}
 #' }
 #'
 "rfm_data_customer"

R/rfm-ggplot.R

@@ -1,7 +1,7 @@
 #' @importFrom ggplot2 ggplot geom_tile aes ggtitle xlab ylab scale_fill_gradientn
 #' @importFrom RColorBrewer brewer.pal
 rfm_gg_heatmap <- function(mapdata, plot_title, xaxis_label, yaxis_label,
-                           brewer_n, brewer_name, legend_title, print_plot) {
+                           brewer_n, brewer_name, legend_title) {
 
   ulm <- ceiling(max(mapdata[["monetary"]]))
   llm <- floor(min(mapdata[["monetary"]]))
@@ -20,11 +20,9 @@ rfm_gg_heatmap <- function(mapdata, plot_title, xaxis_label, yaxis_label,
                         colours = brewer.pal(n = brewer_n, name = brewer_name),
                         name = legend_title)
 
-  if (print_plot) {
-    print(p)
-  } else {
-    return(p)
-  }
+
+  return(p)
+
 }
 
 #' @importFrom ggplot2 geom_bar ylim coord_flip geom_text position_dodge
@@ -68,7 +66,7 @@ rfm_gg_order_dist <- function(data, flip, bar_color, plot_title, xaxis_label,
 
 #' @importFrom ggplot2 geom_histogram
 rfm_gg_hist <- function(data, hist_bins, hist_color, plot_title, xaxis_label,
-                        yaxis_label, print_plot) {
+                        yaxis_label) {
 
   p <-
     data %>%
@@ -78,11 +76,7 @@ rfm_gg_hist <- function(data, hist_bins, hist_color, plot_title, xaxis_label,
     ylab(yaxis_label) +
     ggtitle(plot_title)
 
-  if (print_plot) {
-    print(p)
-  } else {
-    return(p)
-  }
+  return(p)
 
 }
 
@@ -171,8 +165,8 @@ rfm_gg_revenue_dist <- function(data, colors, legend_labels, flip,
 
   p <-
     ggplot(data, aes(fill = category, y = share, x = segment)) +
-    geom_bar(position = "dodge", stat = "identity") 
-    
+    geom_bar(position = "dodge", stat = "identity")
+
 
   p <-
     p +
@@ -185,7 +179,7 @@ rfm_gg_revenue_dist <- function(data, colors, legend_labels, flip,
     theme(legend.title = element_blank(),
           legend.position = "bottom",
           panel.background = element_rect(fill = NA),
-          axis.ticks = element_line(color = NA)) 
+          axis.ticks = element_line(color = NA))
 
 
   if (flip) {
@@ -254,7 +248,7 @@ rfm_gg_median <- function(data, bar_color, sort, ascending, flip, plot_title,
   }
 
   if (is.null(bar_color)) {
-    bar_color <- "blue"
+    bar_color <- "#0f1a34"
   }
 
   if (sort) {
@@ -341,11 +335,8 @@ rfm_gg_segment <- function(table, metric, print_plot) {
     geom_treemap_text(size = 8, place = 'centre') +
     theme(legend.position = "none")
 
-  if (print_plot) {
-    print(plot)
-  } else {
-    return(plot)
-  }
+  return(plot)
+
 }
 
 rfm_gg_segment_scatter <- function(segments, x_data, y_data, plot_title,

R/rfm-plotly.R

@@ -327,18 +327,18 @@ rfm_plotly_median <- function(data, bar_color = NULL, sort = FALSE,
 
   if (is.null(yaxis_label)) {
     yaxis_label <- ycol
-  } 
+  }
 
   if (is.null(plot_title)) {
     plot_title <- paste(yaxis_label, " by Segment")
-  } 
+  }
 
   if (is.null(xaxis_label)) {
     xaxis_label <- "Segment"
-  } 
+  }
 
   if (is.null(bar_color)) {
-    bar_color <- "blue"
+    bar_color <- "#0f1a34"
   }
 
   if (flip) {

R/rfm-plots.R

@@ -76,27 +76,33 @@ rfm_plot_heatmap <- function(data, brewer_n = 5, brewer_name = "PuBu",
   if (interactive) {
     pkg_flag <- requireNamespace("plotly", quietly = TRUE)
     if (pkg_flag) {
-      rfm_plotly_heatmap(mapdata, plot_title, xaxis_label, yaxis_label, brewer_n,
+      p <- rfm_plotly_heatmap(mapdata, plot_title, xaxis_label, yaxis_label, brewer_n,
                          brewer_name, legend_title)
     } else {
       if (interactive()) {
         message('`plotly` must be installed for this functionality. Would you like to install?')
         if (menu(c("Yes", "No")) == 1) {
           install.packages("plotly")
-          rfm_plotly_heatmap(mapdata, plot_title, xaxis_label, yaxis_label, brewer_n,
+          p <- rfm_plotly_heatmap(mapdata, plot_title, xaxis_label, yaxis_label, brewer_n,
                              brewer_name, legend_title)
         } else {
           stop('Sorry! The functionality is not available without installing the required package.', call. = FALSE)
         }
       } else {
-        warning("`plot` is not installed. Using `ggplot2` instead to generate the plot!")
+        warning("`plotly` is not installed. Using `ggplot2` instead to generate the plot!")
         p <- rfm_gg_heatmap(mapdata, plot_title, xaxis_label, yaxis_label, brewer_n,
-                            brewer_name, legend_title, print_plot)
+                            brewer_name, legend_title)
       }
     }
   } else {
-    rfm_gg_heatmap(mapdata, plot_title, xaxis_label, yaxis_label, brewer_n,
-                   brewer_name, legend_title, print_plot)
+    p <- rfm_gg_heatmap(mapdata, plot_title, xaxis_label, yaxis_label, brewer_n,
+                   brewer_name, legend_title)
+  }
+
+  if (print_plot) {
+    print(p)
+  } else {
+    return(p)
   }
 
 }
@@ -197,7 +203,7 @@ rfm_plot_histogram <- function(rfm_table, metric = "recency",
   }
 
   if (is.null(hist_color)) {
-    hist_color <- "blue"
+    hist_color <- "#0f1a34"
   }
 
   ycol <- switch(metric,
@@ -223,14 +229,14 @@ rfm_plot_histogram <- function(rfm_table, metric = "recency",
           stop('Sorry! The functionality is not available without installing the required package.', call. = FALSE)
         }
       } else {
-        warning("`plot` is not installed. Using `ggplot2` instead to generate the plot!")
+        warning("`plotly` is not installed. Using `ggplot2` instead to generate the plot!")
         p <- rfm_gg_hist(data, hist_bins, hist_color, plot_title, xaxis_label,
-                         yaxis_label, print_plot)
+                         yaxis_label)
       }
     }
   } else {
     p <- rfm_gg_hist(data, hist_bins, hist_color, plot_title, xaxis_label,
-                     yaxis_label, print_plot)
+                     yaxis_label)
   }
 
   if (print_plot) {
@@ -245,7 +251,7 @@ rfm_plot_histogram <- function(rfm_table, metric = "recency",
 #' @rdname rfm_plot_histogram
 #' @usage NULL
 #'
-rfm_histograms <- function(rfm_table, hist_bins = 9, hist_color = 'blue',
+rfm_histograms <- function(rfm_table, hist_bins = 9, hist_color = "#0f1a34",
                            plot_title = 'RFM Histograms', xaxis_title = ' ',
                            yaxis_title = 'Count', print_plot = TRUE) {
   .Deprecated("rfm_plot_histograms()")
@@ -299,7 +305,7 @@ rfm_plot_bar_chart <- function(rfm_table, bar_color = NULL,
                                print_plot = TRUE) {
 
   if (is.null(bar_color)) {
-    bar_color <- "blue"
+    bar_color <- "#0f1a34"
   }
 
   if (is.null(xaxis_label)) {
@@ -343,7 +349,7 @@ rfm_plot_bar_chart <- function(rfm_table, bar_color = NULL,
 #' @rdname rfm_plot_bar_chart
 #' @usage NULL
 #'
-rfm_bar_chart <- function(rfm_table, bar_color = 'blue',
+rfm_bar_chart <- function(rfm_table, bar_color = '#0f1a34',
                           xaxis_title = 'Monetary Score',
                           sec_xaxis_title = 'Frequency Score',
                           yaxis_title = ' ',
@@ -431,7 +437,7 @@ rfm_plot_order_dist <- function(rfm_table, flip = FALSE, bar_color = NULL,
   }
 
   if (is.null(bar_color)) {
-    bar_color <- "blue"
+    bar_color <- "#0f1a34"
   }
 
   if (interactive) {
@@ -461,7 +467,7 @@ rfm_plot_order_dist <- function(rfm_table, flip = FALSE, bar_color = NULL,
           stop('Sorry! The functionality is not available without installing the required package.', call. = FALSE)
         }
       } else {
-        warning("`plot` is not installed. Using `ggplot2` instead to generate the plot!")
+        warning("`plotly` is not installed. Using `ggplot2` instead to generate the plot!")
         p <- rfm_gg_order_dist(data, flip, bar_color, plot_title, xaxis_label,
                                yaxis_label, ylim_max, bar_labels, bar_label_size)
       }
@@ -512,7 +518,7 @@ rfm_plot_order_dist <- function(rfm_table, flip = FALSE, bar_color = NULL,
 #' @rdname rfm_plot_order_dist
 #' @usage NULL
 #'
-rfm_order_dist <- function(rfm_table, bar_color = 'blue',
+rfm_order_dist <- function(rfm_table, bar_color = '#0f1a34',
                            xaxis_title = 'Orders', yaxis_title = 'Customers',
                            plot_title = 'Customers by Orders',
                            print_plot = TRUE) {

R/rfm-report.R

@@ -1,6 +1,6 @@
 #' RFM report
 #'
-#' Generates a segmentation ananlysis report.
+#' Generates a segmentation analysis report.
 #'
 #' @param rfm_table An object of class \code{rfm_table}.
 #' @param segments Output from \code{rfm_segment}.
@@ -41,7 +41,7 @@
 #' rfm_create_report(rfm_result, segments, FALSE,
 #' "Customer Segmentation Report")
 #' }
-#' 
+#'
 #' @importFrom utils browseURL
 #'
 #' @export