R programming

R programming is a language and environment for statistical computing and graphics. It is widely used among statisticians and data miners for developing statistical software and data analysis. R is highly extensible and provides a wide variety of statistical and graphical techniques, including linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, and more.

Main Functions in R Programming

1. Basic Mathematical Functions:

   • sum(x): Returns the sum of all the elements of x.
   • prod(x): Returns the product of all the elements of x.
   • min(x): Returns the minimum value of x.
   • max(x): Returns the maximum value of x.
   • mean(x): Returns the mean (average) of x.
   • median(x): Returns the median of x.
   • sd(x): Returns the standard deviation of x.
   • var(x): Returns the variance of x.

2. Data Manipulation Functions:

   • subset(x, condition): Returns subsets of x that meet the condition.
   • merge(x, y, by): Merges two data frames by common columns or row names.
   • apply(x, margin, FUN): Applies a function to the margins of an array or matrix.
   • lapply(x, FUN): Applies a function to each element of a list and returns a list.
   • sapply(x, FUN): Applies a function to each element of a list and returns a vector or matrix.

3. Data Aggregation and Reshaping:

   • aggregate(x, by, FUN): Splits the data into subsets, computes summary statistics, and returns the result in a convenient form.
   • tapply(x, INDEX, FUN): Applies a function to each cell of a ragged array, which is grouped by the given factors.
   • reshape(data, idvar, timevar, direction): Reshapes a data frame between long and wide formats.

4. Statistical Functions:

   • cor(x, y): Calculates the correlation between two vectors or matrices.
   • cov(x, y): Calculates the covariance between two vectors or matrices.
   • lm(formula, data): Fits linear models.
   • glm(formula, family, data): Fits generalized linear models.

5. Plotting and Graphics:

   • plot(x, y): Creates a scatter plot or other type of plot depending on the type of arguments.
   • hist(x): Creates a histogram of the data.
   • boxplot(x): Creates a boxplot of the data.
   • barplot(height): Creates a bar plot with vertical or horizontal bars.
   • ggplot(data, aes): Creates a complex multi-layered graph using the ggplot2 package.

6. Data Import and Export:

   • read.table(file): Reads a file in table format and creates a data frame from it.
   • read.csv(file): Reads a CSV file and creates a data frame.
   • write.table(x, file): Writes a data frame or matrix to a file.
   • write.csv(x, file): Writes a data frame to a CSV file.

7. Miscellaneous Functions:

   • str(object): Compactly displays the structure of an object.
   • summary(object): Provides a summary of an object, such as a statistical summary for a data frame or model.
   • head(x, n): Returns the first n rows of a data frame or matrix.
   • tail(x, n): Returns the last n rows of a data frame or matrix.

These functions cover a wide range of operations in R, making it a powerful tool for data analysis and statistical computing