#Remember to install packages before loading them with library()

library(tidyverse) ## A set of tools for Data manipulation and visualization
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## ✔ lubridate 1.9.4     ✔ tidyr     1.3.1
## ✔ purrr     1.1.0     
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(lubridate) ## for date time manipulation
library(scales) ## Formatting numbers and values
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#library(hrbrthemes)# For changing ggplot theme
library(extrafont) # More font options
## Registering fonts with R

#Q1 - view data

sales <- read.csv("sales.csv")

glimpse(sales)
## Rows: 1,000
## Columns: 17
## $ Invoice.ID              <chr> "750-67-8428", "226-31-3081", "631-41-3108", "…
## $ Branch                  <chr> "A", "C", "A", "A", "A", "C", "A", "C", "A", "…
## $ City                    <chr> "Yangon", "Naypyitaw", "Yangon", "Yangon", "Ya…
## $ Customer.type           <chr> "Member", "Normal", "Normal", "Member", "Norma…
## $ Gender                  <chr> "Female", "Female", "Male", "Male", "Male", "M…
## $ Product.line            <chr> "Health and beauty", "Electronic accessories",…
## $ Unit.price              <dbl> 74.69, 15.28, 46.33, 58.22, 86.31, 85.39, 68.8…
## $ Quantity                <int> 7, 5, 7, 8, 7, 7, 6, 10, 2, 3, 4, 4, 5, 10, 10…
## $ Tax.5.                  <dbl> 26.1415, 3.8200, 16.2155, 23.2880, 30.2085, 29…
## $ Total                   <dbl> 548.9715, 80.2200, 340.5255, 489.0480, 634.378…
## $ Date                    <chr> "1/5/2019", "3/8/2019", "3/3/2019", "1/27/2019…
## $ Time                    <chr> "13:08", "10:29", "13:23", "20:33", "10:37", "…
## $ Payment                 <chr> "Ewallet", "Cash", "Credit card", "Ewallet", "…
## $ cogs                    <dbl> 522.83, 76.40, 324.31, 465.76, 604.17, 597.73,…
## $ gross.margin.percentage <dbl> 4.761905, 4.761905, 4.761905, 4.761905, 4.7619…
## $ gross.income            <dbl> 26.1415, 3.8200, 16.2155, 23.2880, 30.2085, 29…
## $ Rating                  <dbl> 9.1, 9.6, 7.4, 8.4, 5.3, 4.1, 5.8, 8.0, 7.2, 5…
sales <- sales %>% 
  mutate(
    time = as.integer(substr(Time, 1, 2)), 
    date = mdy(Date),
    weekday = wday(date, label = TRUE)
  )
library(dplyr)
library(ggplot2)

# Ensure 'weekday' is a factor with proper order (Mon → Sun)
sales$weekday <- factor(sales$weekday, levels = c("Mon","Tue","Wed","Thu","Fri","Sat","Sun"))

# Define colors for each weekday
weekday_colors <- c(
  "Mon" = "#FF4D4D",   # Red
  "Tue" = "#FFA64D",   # Orange
  "Wed" = "#FFD24D",   # Yellow
  "Thu" = "#57D957",   # Green
  "Fri" = "#4D79FF",   # Blue
  "Sat" = "#B266FF",   # Purple
  "Sun" = "#FF66A3"    # Pink
)

sales_by_day <- sales %>% group_by(weekday) %>% 
  summarise(Total_Sales=sum(Total)) %>%  ungroup 
sales_by_day <- sales_by_day %>%
  mutate(weekday = factor(weekday, levels = rev(c("Mon","Tue","Wed","Thu","Fri","Sat","Sun"))))

ggplot(sales_by_day, aes(x = weekday, y = Total_Sales, fill = weekday)) +
  geom_col(width = 0.6, color = "black") +
  geom_text(aes(label = scales::comma(Total_Sales)),
            hjust = 1.1, color = "white", size = 4, fontface = "bold") +  # inside bars
  coord_flip() +
  scale_fill_manual(values = weekday_colors) +
  theme_minimal(base_size = 14) +
  theme(
    plot.title = element_text(face = "bold", size = 18, hjust = 0.5),
    axis.title.y = element_blank(),
    axis.title.x = element_text(size = 12),
    axis.text.y = element_text(size = 12, face = "bold"),
    axis.text.x = element_text(size = 11, color = "gray30"),
    panel.grid.major.y = element_blank(),
    panel.grid.minor = element_blank(),
    panel.grid.major.x = element_line(color = "gray80", linewidth = 0.4),
    legend.position = "none"
  ) +
  labs(
    title = "Weekly Sales Breakdown",
    y = "Total Sales"
  )