To generate a basic box plot using ggplot2, enhanced with notches and outliers, and grouped by a categorical variable using an in-built dataset in R.

Develop an R function to draw a density curve representing the probability density function of a continuous variable, with separate curves for each group, using ggplot2.

To create a violin plot using ggplot2 in R that displays the distribution of a continuous variable with separate violins for each group using an in-built dataset.

Develop a R program to calculate and visualize a correlation matrix for a given dataset, with color coded cells indicating the strength and direction of correlation , using ggplot2, geom_tile function.

Write an R program to create multiple dot plots or group data , comparing the distribution of variables across different categories, using ggplot2's position_dodge function.

Create multiple histograms using ggplot2 ::facet_wrap() to visualize how a variable(e.g., Sepal.length) is distributed across different groups (e.g.,species) in a built-in R data set.

Develop a function in R to plot a function curve based on a mathematical equation provided as input, with different curve styles for each group, using ggplot2.

Write an R script to construct a box plot showcasing the distribution of a continuous variable, grouped by a categorical variable, using ggplot2’s fill aesthetic.

Implement an R program to create a histogram illustrating the distribution of a continuous variable, with overlays of density curves for each group, using ggplot2

Develop a Script in R to produce a bar graph display in the frequency distribution of categorical data in a given dataset, grouped by a specific variable, using ggplot2

Implement an R function to generate a line graph depicting the trend of a time-series dataset , with separate lines for each graoup, utilizing ggplot2's group aesthetic.

Write an R script to create a scatter plot, incorporating categorical analysis through color-coded data points representing different groups, using ggplot2.

Develop an R program to quickly explore a given dataset, including categorical analysis using the group_by command, and visualize the findings using ggplot2 features.