In R, the ls() function can be used to list all the variables in the global environment. It returns the names of all the objects or variables defined in the global environment, allowing you to inspect and access the global variables present in your program.

When performing 'AND' and 'OR' operations in R, if either operand is 'NA', the result will be 'NA' for both 'AND' and 'OR' operations. This is because the presence of 'NA' indicates that the value is missing or unknown, resulting in an unknown outcome for the logical operation.

To customize the appearance of an R scatter plot, including changing colors, markers, and sizes, you can use the col parameter to change colors, the pch parameter to change markers, and the cex parameter to change the size of the points. These graphical parameters can be specified within the plot() function.

One way to handle this is by using the is.finite() function which checks whether the value is finite or not. This function returns FALSE if the value is Inf or NaN and TRUE otherwise. Depending on the use case, you can then decide how to handle these non-finite values.

To calculate the median of each column in a data frame in R, you would use the apply() function. By specifying the appropriate margin argument (2 for columns), you can apply the median() function across each column of the data frame.

R allows lists to contain elements of different data types without coercing them. Unlike vectors, where elements are coerced to a common type, lists retain the individual data types of their elements. This means you can have a list with elements that are numeric, character, logical, etc., all coexisting without being coerced.

The ifelse() function in R allows vectorized conditional operations, which means it can process entire vectors of conditions and return corresponding values based on those conditions. In contrast, the if-else statement in R works with scalar conditions and can only evaluate one condition at a time.

The plot() function is commonly used to create a basic plot in R. It can be used to create a wide range of plots such as scatter plots, line plots, bar plots, and more.

To create a scatter plot in R that shows the relationship between two numeric variables, you would use the plot() function and pass the two numeric variables as the x and y arguments. The points() function can be used to add individual data points to the scatter plot. Alternatively, the ggplot2 package provides a more advanced and customizable approach to creating scatter plots.

The purrr package in R provides functions that can help avoid explicit use of nested loops. It offers a variety of functions for functional programming and iteration, such as map(), walk(), and reduce(), which can simplify and streamline operations without the need for nested loops.