Karthiga final

NAMESPACE

@@ -17,6 +17,8 @@ export(get_video_and_rank)
 export(get_video_ids)
 export(preprare_data)
 export(print_videos)
+export(tabulate_overallsummary)
+export(tabulate_summary)
 export(visualize)
 export(visualize_channel)
 export(visualize_proportion)
@@ -27,6 +29,7 @@ import(ggtext)
 import(gridExtra)
 import(httr)
 import(jsonlite)
+import(kableExtra)
 import(lubridate)
 import(stringr)
 import(tidyr)

R/preference_analysis.R

@@ -1,5 +1,6 @@
 library(dplyr)
 library(ggplot2)
+library(kableExtra)
 
 #' Helps to prepare data for preference breakdown
 #'
@@ -102,6 +103,76 @@ calculate_and_display_summary<-function(merged_info)
                                c("Category", "Count", "Duration in mins", "Percecntage")))
 }
 
+#' Tabulates summary on least and most favorite category
+#'
+#' @param merged_info
+#'
+#' @return: gives table
+#'
+#' @import kableExtra
+#' @export
+#'
+#' @example
+#' merged_data <- data.frame(categoryid = c("22", "27"),
+#'       channelId = c("UCAuUUnT6oDeKwE6v1NGQxug", "UCtYLUTtgS3k1Fg4y5tAhLbw"),
+#'       categoryTitle = c("Entertainment","Education"),
+#'       count = c(1, 19),
+#'       duration_sum = c(21.05, 399.95),
+#'       percentage_duration = c(5, 95))
+#' visualize(merged_data)
+#' tabulate_summary(merged_data)
+tabulate_summary<-function(merged_info)
+{
+  min_category <- min(merged_info$count)
+  max_category <- max(merged_info$count)
+  min_categorylist <- merged_info$categoryTitle[merged_info$count == min_category]
+  max_categorylist <- merged_info$categoryTitle[merged_info$count == max_category]
+  min_category_duration <- sum(merged_info$duration_sum[merged_info$count == min_category])
+  max_category_duration <- sum(merged_info$duration_sum[merged_info$count == max_category])
+  min_category_percentage <- sum(merged_info$percentage_duration[merged_info$count == min_category])
+  max_category_percentage <- sum(merged_info$percentage_duration[merged_info$count == max_category])
+
+
+  summary_data <- data.frame(
+    Likeness = c("Least Favorite", "Most Favorite"),
+    categories = c(paste(paste(min_categorylist, collapse = ", ")), paste(paste(max_categorylist, collapse = ", "))),
+    Time_Spend_Minutes = c(paste(round(min_category_duration), "min"),paste(round(max_category_duration), "min")),
+    Percentage_Time_Spent = c(paste(round(min_category_percentage), "%"), paste(round(max_category_percentage), "%"))
+  )
+
+  top_10_videos_print <-  kbl(summary_data, caption = "Summary on Least and Most favourite category") %>%
+    kable_classic(full_width = F, html_font = "Cambria")
+
+  print(top_10_videos_print)
+}
+
+#' Tabulates the overall summary on category
+#'
+#' @param merged_info
+#'
+#' @return
+#' @import kableExtra
+#'
+#' @export
+#' @example
+#' merged_data <- data.frame(categoryid = c("22", "27"),
+#'       channelId = c("UCAuUUnT6oDeKwE6v1NGQxug", "UCtYLUTtgS3k1Fg4y5tAhLbw"),
+#'       categoryTitle = c("Entertainment","Education"),
+#'       count = c(1, 19),
+#'       duration_sum = c(21.05, 399.95),
+#'       percentage_duration = c(5, 95))
+#'
+#' tabulate_overallsummary(merged_data)
+tabulate_overallsummary<-function(merged_info)
+{
+  splitted_data <- merged_info[, c("categoryTitle", "count", "duration_sum", "percentage_duration")]
+  colnames(splitted_data) <- c("Category", "Count", "Duration in mins", "Percecntage of watch time")
+  table_channel_stats <-  kbl(splitted_data, caption = "Overall Summary on breakdown") %>%
+    kable_classic(full_width = F, html_font = "Cambria")
+
+    print(table_channel_stats)
+}
+
 #' Helps to display category in pi chart
 #'@description
 #'This method helps to create pi chart
@@ -123,9 +194,9 @@ visualize<-function(merged_info)
   category_plot <- ggplot(merged_info, aes(x = " ", y = count, fill = categoryTitle)) +
     geom_bar(stat = "identity") +
     coord_polar("y", start = 0) +
-    labs(title = "Breakdown on your watch category", fill = "categoryTitle") +
+    labs(title = "Categorical breakdown in your watch history", fill = "categoryTitle") +
     theme_minimal()+
-    labs(x="")
+    labs(x="",  fill = "Categories")
   print(category_plot)
 }
 
@@ -146,15 +217,17 @@ visualize<-function(merged_info)
 #'       duration_sum = c(21.05, 399.95),
 #'       percentage_duration = c(5, 95))
 #' visualize_channel(merged_data)
-visualize_channel<-function(merged_info)
+visualize_channel <- function(merged_info)
 {
-  ggplot(merged_info, aes(x = channelName, y = 1, size = count, color = channelName)) +
-    geom_point(alpha = 0.7,show.legend = FALSE) +
-    geom_text(aes(label = round(duration_sum)), vjust = -0.5, size=5, color= 'white')+
-    scale_size_continuous(range = c(20, 70)) +
-    labs(x = "Channel Name", y = NULL, size = "Duration", title=" Watch time (in minutes) per channel")+
-    theme(axis.text.y=element_blank())+
-    labs(y="")
+       ggplot(merged_info, aes(x = channelName, y = 1, size = count, color = channelName)) +
+             geom_point(alpha = 0.7, show.legend = FALSE) +
+             geom_text(aes(label = channelName), vjust = -8, size = 5, color = 'black') +  # corrected
+             geom_text(aes(label = paste("count: ", round(count))), vjust = 8, size = 5, color = 'black') +  # corrected
+             geom_text(aes(label = paste(round(duration_sum), " min")), vjust = 10, size = 5, color = 'black') +  # corrected
+             scale_size_continuous(range = c(20, 70)) +
+             labs(x = "Channel Name", y = NULL, size = "Duration", title = "Channel View Summary: Watch Time and Video Duration") +
+             theme(axis.text.y = element_blank(), axis.text.x = element_blank()) +
+            labs(y = "", x = "")  # corrected
 }
 
 #' Main function that helps to co-ordinate all the functions
@@ -181,6 +254,8 @@ get_Preference_Breakdown<-function(video_ids)
     }
     video_ids <- gsub(" ", "", video_ids)
     merged_info <- preprare_data(video_ids)
+    tabulate_summary(merged_info)
+    tabulate_overallsummary(merged_info)
     calculate_and_display_summary(merged_info)
     visualize(merged_info)
     visualize_channel(merged_info)

R/rank_and_analyse_top_videos.R

@@ -1,5 +1,5 @@
 library(ggplot2)
-
+library(kableExtra)
 
 #' @param channelId
 #'
@@ -27,6 +27,7 @@ get_video_ids <-function(channelId,year)
 #' @param channelID
 #' @param year
 #'
+#' @import kableExtra
 #' @return videos a dataframe
 #' @export
 #'
@@ -60,6 +61,7 @@ get_video_and_rank<-function(channelID, year)
 #' @param reverse
 #'
 #' @export
+#' @import kableExtra
 #'
 #' @examples
 #' dummy_data <- data.frame(
@@ -78,7 +80,9 @@ print_videos<-function(filtered_video_details, reverse = TRUE)
   if(reverse){
     top_videos<-top_videos[nrow(top_videos):1, ]
   }
-  print(top_videos)
+  top_10_videos <-  kbl(top_videos, caption = "TOP 10 Videos") %>%
+    kable_classic(full_width = F, html_font = "Cambria")
+  print(top_10_videos)
 }
 
 #' Helps to calculate proportion of views, count,comments, duration
@@ -141,7 +145,7 @@ visualize_proportion<-function(proportion_data)
 {
   ggplot(proportion_data, aes(x = Category, y = Proportion,fill = Category)) +
     geom_bar(stat = 'identity',  width = 0.5) +
-    labs(x = "", y = "Proportion (%)", title = "Proportions of Top 10 Videos") +
+    labs(x = "", y = "Proportion (%)", title = "Proportions of Top 10 Videos",fill="Metrics") +
     theme_minimal()
 
 }