Drawing Scatter Plots with Two Nominal Variables Using Plotly Package in R

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In this article, we will explore how to draw scatter plots using the Plotly package in R. We will use a real-world example and provide detailed explanations of each step.

Introduction

The Plotly package is a popular data visualization library in R that allows us to create interactive, web-based visualizations. It supports various types of charts, including scatter plots, line plots, bar charts, and more. In this article, we will focus on drawing scatter plots with two nominal variables using the Plotly package.

Preparing the Data

To draw a scatter plot, we need a dataset with at least two variables: one for the x-axis and one for the y-axis. The x-axis variable should be categorical or nominal, while the y-axis variable can be either numerical or categorical.

In this example, we have a dataframe data_f with 166 columns. We want to draw scatter plots using Plotly Package in R.

Code: Basic Scatter Plot

Let’s start by creating a basic scatter plot using the Plotly package.

# Install and load necessary libraries
install.packages("plotly")
library(plotly)

# Create a dataframe with two nominal variables (X1, X2) and one numerical variable (Y1)
X1 <- rep(c("A","B"), each = 4)
X2 <- rep(letters[1:4], len = length(X1))
Y1 <- c(1, 1.5, 1.3, 1.4, 1.8, 1.7, 1.5, 1.6)

# Create a dataframe
data_f <- data.frame(X1 = X1, X2 = X2, Y1 = Y1)

# Create a scatter plot
plt <- plot_ly(data = data_f,
               x = ~ list(X1, X2),
               hovermode = "x unified")

# Display the plot
plot(plt)

This code creates a basic scatter plot with two nominal variables (X1, X2) and one numerical variable (Y1).

Code: Using a Loop to Draw Scatter Plots for All Columns

However, this code only draws a single scatter plot. We want to draw scatter plots using Plotly Package in R for all columns of the dataframe data_f.

Let’s use a loop to draw scatter plots for each column.

# Create a dataframe with two nominal variables (X1, X2) and multiple numerical variables (Y1, Y2, ..., Y166)
# ...

for (i in 3:dim(data_f)[2]) {
  # Extract the current column name
  colname <- colnames(data_f)[i]

  # Create a scatter plot
  plt <- plot_ly(data = data_f,
                 x = ~ list(X1, X2),
                 y = data_f[, i],
                 mode = "lines+markers",
                 type = "scatter")

  # Add text to the plot
  text1 <- paste0("X1 : ", data_f$X1, "\n",
                 "X2 : ", data_f$X2, "\n",
                 "Y1 : ", data_f$Y1, "\n",
                 "Y2 : ", data_f$Y2, "\n",
                 "Y" colname ": ", data_f[, i])

  # Update the plot
  plt <- plt %>% add_trace(x = paste(data_f$X1, data_f$X2),
                           y = data_f[, i],
                           mode = "lines+markers",
                           type = "scatter",
                           line = list(width = 4),
                           marker = list(size = 15),
                           text = text1,
                           hoverinfo = "text")

  # Display the plot
  plot(plt)
}

This code uses a loop to draw scatter plots for each column of the dataframe data_f. It extracts the current column name, creates a scatter plot, adds text to the plot, and updates the plot.

Tips and Tricks

Use the x = ~ list(X1, X2) argument to specify multiple x-axis variables.
Use the hovermode argument to achieve a combined hovertemplate.

Last modified on 2025-02-10