Showing posts with label data visualization. Show all posts
Showing posts with label data visualization. Show all posts

Monday, November 25, 2024

Day 10: 30-days to learn rgl, plotly, and gganimate - Create an Animated Scatter Plot with gganimate and Enhance it with Plotly Hover Details

 

Step 1: Install and Load Required Libraries

Ensure you have all the necessary libraries installed. Use the following code:

# Install required packages
install.packages(c("ggplot2", "gganimate", "plotly"))
 
# Load the libraries
library(ggplot2)
library(gganimate)
library(plotly)

Step 2: Prepare the Dataset

Use a time-series dataset or create a sample dataset for the scatter plot. For this example:

# Create a sample dataset
set.seed(123)
data <- data.frame(
  Time = rep(1:10, each = 10),
  X = runif(100, min = 1, max = 100),
  Y = runif(100, min = 1, max = 100),
  Category = rep(letters[1:10], times = 10)
)

Step 3: Create the Static ggplot

Set up the scatter plot with ggplot2:

# Create the base plot
static_plot <- ggplot(data, aes(x = X, y = Y, color = Category, frame = Time)) +
  geom_point(size = 3) +
  labs(title = "Scatter Plot Over Time", x = "X-Axis", y = "Y-Axis") +
  theme_minimal()

Step 4: Animate the Plot with gganimate

Use transition_time to animate the plot over the Time variable:

# Animate the scatter plot
animated_plot <- static_plot +
  transition_time(Time) +
  labs(subtitle = 'Time: {frame_time}')
 
# Render the animation (optional, for preview)
animate(animated_plot, nframes = 100, fps = 10)

Step 5: Export Animation Frames

Save animation frames for converting to Plotly:

# Save each frame
animation_frames <- animate(animated_plot, renderer = file_renderer(dir = "frames", overwrite = TRUE))

Step 6: Convert ggplot to Plotly for Interactivity

Add Plotly's hover functionality to the ggplot-based animation:

# Convert the static ggplot to a plotly object
plotly_plot <- ggplotly(static_plot, tooltip = c("Category", "X", "Y"))
 
# Add animation controls
plotly_plot <- plotly_plot %>%
  animation_opts(frame = 1000, redraw = TRUE) %>%
  animation_slider(currentvalue = list(prefix = "Time: "))

Step 7: Combine gganimate and Plotly

Overlay gganimate animations on the interactive Plotly scatter plot:

# Generate the final interactive plot
final_plot <- plot_ly(
  data = data,
  x = ~X,
  y = ~Y,
  color = ~Category,
  frame = ~Time,
  text = ~paste("Category:", Category, "<br>X:", round(X, 2), "<br>Y:", round(Y, 2)),
  hoverinfo = "text",
  type = 'scatter',
  mode = 'markers'
) %>%
  layout(
    title = "Interactive Scatter Plot with Animation",
    xaxis = list(title = "X-Axis"),
    yaxis = list(title = "Y-Axis")
  )

Step 8: Preview and Save

Render and view the interactive plot:

# Render the interactive animated plot
final_plot
 
# Save the plot as an HTML file

htmlwidgets::saveWidget(final_plot, "animated_scatter_plot.html")