compilation of program9-14

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

Develop a script in R to create a violin plot displaying the distribution of a continous variable with a separate violins for each group using ggplot2.

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

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

Create a R program to calculate and visualize co relation matrix for a given data set with color coded cells the strength and direction of co relations , using ggplot2 geom_tile function

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

combination of programs 1-7

Develop a function in R to plot a function curve based on 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 displaying 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 group, 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 and R program to quickly explore a given data set, including categorical analysis using the group_by command, and visualize the findings using ggplot2 features.