# Loading necessary libraries
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(ggplot2)

# Defining the data
product_category <- c("Electronics", "Clothing", "Home & Kitchen", "Books", "Electronics", "Clothing", "Home & Kitchen", "Books")
date <- as.Date(c("2023-01-01", "2023-01-02", "2023-01-03", "2023-01-04", "2023-01-05", "2023-01-06", "2023-01-07", "2023-01-08"))
sales <- c(5000, 3000, 7000, 2000, 6000, 4000, 8000, 2500)
price <- c(100, 50, 80, 30, 120, 60, 90, 25)

# Creating the data frame
Sales <- data.frame(
  Product_Category = product_category,
  Date = date,
  Sales = sales,
  Price = price
)

# Displaying the data frame
View(Sales)

# Grouping sales by Product_Category and calculate total sales
sales_by_category <- Sales %>%
  group_by(Product_Category) %>%
  summarise(Total_Sales = sum(Sales))

# Creating a bar chart using ggplot2
library(ggplot2)

ggplot(sales_by_category, aes(x = Product_Category, y = Total_Sales)) +
  geom_bar(stat = "identity", fill = "skyblue") +
  labs(title = "Total Sales by Product Category",
       x = "Product Category",
       y = "Total Sales") +
  theme_minimal()

# Creating a line chart using ggplot2
ggplot(Sales, aes(x = Date, y = Sales)) +
  geom_line(color = "blue", size = 1) +
  geom_point(color = "red", size = 3) +
  labs(title = "Sales Trends Over Time",
       x = "Date",
       y = "Sales") +
  theme_minimal()
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

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