LA-01

Author

VAISHNAVI

Problem Statement

Animate a circular packing plot showing district-wise population trends.

STEP 1: Load the Dataset

data <- read.csv("C:/Users/Vaishnavi/Downloads/archive/Global_Superstore2.csv")
head(data)

  Row.ID        Order.ID Order.Date  Ship.Date    Ship.Mode Customer.ID
1  32298  CA-2012-124891 31-07-2012 31-07-2012     Same Day    RH-19495
2  26341   IN-2013-77878 05-02-2013 07-02-2013 Second Class    JR-16210
3  25330   IN-2013-71249 17-10-2013 18-10-2013  First Class    CR-12730
4  13524 ES-2013-1579342 28-01-2013 30-01-2013  First Class    KM-16375
5  47221    SG-2013-4320 05-11-2013 06-11-2013     Same Day     RH-9495
6  22732   IN-2013-42360 28-06-2013 01-07-2013 Second Class    JM-15655
     Customer.Name     Segment          City           State       Country
1      Rick Hansen    Consumer New York City        New York United States
2    Justin Ritter   Corporate    Wollongong New South Wales     Australia
3     Craig Reiter    Consumer      Brisbane      Queensland     Australia
4 Katherine Murray Home Office        Berlin          Berlin       Germany
5      Rick Hansen    Consumer         Dakar           Dakar       Senegal
6      Jim Mitchum   Corporate        Sydney New South Wales     Australia
  Postal.Code Market  Region       Product.ID   Category Sub.Category
1       10024     US    East  TEC-AC-10003033 Technology  Accessories
2          NA   APAC Oceania  FUR-CH-10003950  Furniture       Chairs
3          NA   APAC Oceania  TEC-PH-10004664 Technology       Phones
4          NA     EU Central  TEC-PH-10004583 Technology       Phones
5          NA Africa  Africa TEC-SHA-10000501 Technology      Copiers
6          NA   APAC Oceania  TEC-PH-10000030 Technology       Phones
                                                        Product.Name    Sales
1 Plantronics CS510 - Over-the-Head monaural Wireless Headset System 2309.650
2                          Novimex Executive Leather Armchair, Black 3709.395
3                                  Nokia Smart Phone, with Caller ID 5175.171
4                                     Motorola Smart Phone, Cordless 2892.510
5                                     Sharp Wireless Fax, High-Speed 2832.960
6                                Samsung Smart Phone, with Caller ID 2862.675
  Quantity Discount    Profit Shipping.Cost Order.Priority
1        7      0.0  762.1845        933.57       Critical
2        9      0.1 -288.7650        923.63       Critical
3        9      0.1  919.9710        915.49         Medium
4        5      0.1  -96.5400        910.16         Medium
5        8      0.0  311.5200        903.04       Critical
6        5      0.1  763.2750        897.35       Critical

Explanation: Loads the dataset and displays first rows.

STEP 2: Load Libraries

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.2.0     ✔ readr     2.1.6
✔ forcats   1.0.1     ✔ stringr   1.6.0
✔ ggplot2   4.0.2     ✔ tibble    3.3.1
✔ lubridate 1.9.5     ✔ tidyr     1.3.2
✔ purrr     1.2.1     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(packcircles)

Warning: package 'packcircles' was built under R version 4.5.3

library(ggplot2)
library(gganimate)

Warning: package 'gganimate' was built under R version 4.5.3

library(gifski)

Warning: package 'gifski' was built under R version 4.5.3

Explanation: Used for data manipulation, circular packing, plotting, and animation.

STEP 3: Prepare Data

set.seed(1)

# Use Region as District
data$District <- data$Region

# Simulate Year and Population
data$Year <- sample(2018:2020, nrow(data), replace = TRUE)
data$Population <- sample(10000:100000, nrow(data), replace = TRUE)

df <- data %>%
  group_by(District, Year) %>%
  summarise(Population = sum(Population), .groups = "drop")

Explanation: Since the dataset does not contain population data, values are simulated for demonstration.

STEP 4: Circular Packing Function

create_fun <- function(x){
  layout <- circleProgressiveLayout(x$Population, sizetype = "area")
  x <- cbind(x, layout)
  vertices <- circleLayoutVertices(layout)
  list(data = x, vertices = vertices)
}

Explanation: Creates circle positions and shapes.

STEP 5: Prepare Animation Data

split_data <- df %>% arrange(Year) %>% group_split(Year)

years <- sort(unique(df$Year))

frames <- lapply(split_data, create_fun)

plot_data <- purrr::map2_df(frames, years,
                           ~mutate(.x$vertices, Year = .y))

Explanation: Prepares data for animation.

STEP 6: Static Plot (Single Year)

single_year <- df %>% filter(Year == min(Year))
circle_data <- create_fun(single_year)

ggplot(circle_data$vertices, aes(x, y, group = id, fill = as.factor(id))) +
  geom_polygon(color = "black") +
  coord_equal() +
  theme_void() +
  scale_fill_viridis_d() +
  labs(title = "Circular Packing (Single Year)")

Explanation: Shows circular packing for one year.

STEP 7: Animation Plot

p <- ggplot(plot_data, aes(x, y, group = id, fill = as.factor(id))) +
  geom_polygon(color = "black", alpha = 0.8) +
  coord_equal() +
  theme_void() +
  scale_fill_viridis_d() +   
  labs(title = "Year: {frame_time}") +
  transition_time(Year)

anim <- animate(p, duration = 6, fps = 5, renderer = gifski_renderer())
anim

Explanation: Creates animated circular packing plot over years.

Interpretation

Larger circles represent higher (simulated) population
Static plot shows one snapshot
Animation shows changes over time