Perform basic arithmetic, logical, and vectorized operations in R

Use functions and control structures (loops, if-else statements)

Import data from CSV, Excel, and text files using read.csv and readxl

Export data to CSV and Excel formats for further use.

Introduction to the tidyverse package (dplyr, ggplot2, tidyr)

Create basic plots using plot(), hist(), and boxplot()

Use ggplot2 for advanced data visualizations (scatter plots, bar charts, histograms)

Customize visualizations to present data effectively.

Handle missing data using functions like is.na(), na.omit(), and na.rm()

Apply data imputation techniques to fill missing values

Manipulate data using dplyr functions (select(), filter(), mutate(), arrange(), summarize())

Join datasets with left_join(), right_join(), inner_join(), and full_join()

Reshape data with tidyr using unite() and separate()

Work with nested and hierarchical data structures

Perform exploratory data analysis with descriptive statistics (mean, median, mode, standard deviation)

Identify and visualize relationships in data using correlation analysis and ggplot2.