Statistical Analysis with R

The digital world we live in has given companies and people access to staggering amounts of data, and anyone who can make use of that to drive valuable insights stands to benefit. The ability to work with large amounts of data is becoming a standard requirement for countless jobs across multiple industries.

R, probably the most well-known language for data analysis, has been used for years due to its robust statistical functionality, outstanding graphing ability, and extensibility through packages.

This interactive module will get us up to speed with R and assumes no prior knowledge of it. We'll start with the very basics and work our way up to advanced concepts like exception handling. By the time we're done, we'll be able to write detailed, useful code in R.

Learn R from Scratch

## Function to Handle Exceptions

Other methods can be used to handle exceptions in R.

Here is a minimal list of functions that can help programmers in handling errors and warnings in code:
* `warning(...)` — to generate warnings
* `stop(...)` — to generate errors
* `suppressWarnings(expression)` — to evaluate the given expression and ignore any warnings
* `tryCatch(...)` — we have already studied this in detail [here](https://www.educative.io/collection/page/6151088528949248/5357220915052544/4845381156339712)

Let's have a look at each one of them in detail.

### Warning

The function `warning()` generates a warning message specified by the programmer. Suppose we are writing a program that divides two numbers however, we know that if a number is divided by $0$, it returns ```INF```. In such a case it is better to give a warning as this might be an unintentional mistake by the programmer:




# Function to Handle Exceptions

Other methods can be used to handle exceptions in R.

Here is a minimal list of functions that can help programmers in handling errors and warnings in code:
* `warning(...)` — to generate warnings
* `stop(...)` — to generate errors
* `suppressWarnings(expression)` — to evaluate the given expression and ignore any warnings
* `tryCatch(...)` — we have already studied this in detail [here](https://www.educative.io/collection/page/6151088528949248/5357220915052544/4845381156339712)

Let's have a look at each one of them in detail.

## Warning

The function `warning()` generates a warning message specified by the programmer. Suppose we are writing a program that divides two numbers however, we know that if a number is divided by $0$, it returns ```INF```. In such a case it is better to give a warning as this might be an unintentional mistake by the programmer:




In this lesson, we mention some other functions that can be useful while handling exceptions.

Getting Started

Variables

Exploring R Objects

R Operators and Notation

Conditional Statements

Loops

Functions

Input/Output

Exception Handling

Classes

Fun Challenges

Conclusion

Other Methods for Exception Handling

Function to Handle Exceptions