Gain insights into R, the leading language for data analysis. Learn about its basics, advanced concepts, and practical coding to drive valuable insights from large datasets.

The digital world we live in has given companies and people access to staggering amounts of data, and anyone that 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.

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

This interactive course will get you up to speed and assumes no prior knowledge of R. You'll start with the very basics and work your way up to advanced concepts like exception handling. By the time you're done, you'll be able to write detailed, useful code in R yourself.

Learn R from Scratch

Item, Price, Quantity
Apple, $10, 20
Banana, $5, 12
Mango, $17, 18


path <- "data.csv"
csvData = read.csv(path)

items <- csvData$Item
write.csv(items, "output/outData.csv")

path <- "data.csv"
csvData = read.csv("data.csv")

items <- csvData$Item
write.csv(items, "output/outData.csv")

### Explanation
In the code snippet above, we first fetch the data of the `.csv` file in `csvData`.

> The data fetched from `read.csv()` is directly in the format of a **data frame**. Therefore, `csvData` is a data frame. Now, we can excess one of the columns `Item` using the syntax:
```
csvData$Item
```
We store this column in the variable `items` and then write on file `output/outData.csv`.

## Explanation
In the code snippet above, we first fetch the data of the `.csv` file in `csvData`.

> The data fetched from `read.csv()` is directly in the format of a **data frame**. Therefore, `csvData` is a data frame. Now, we can excess one of the columns `Item` using the syntax:
```
csvData$Item
```
We store this column in the variable `items` and then write on file `output/outData.csv`.

In this review, we provide a detailed analysis of the solution to the problem.

Getting Started

Variables

Exploring R Objects

R Operators and Notation

Conditional Statements

Loops

Functions

Input/Output

Exception Handling

Classes

Fun Challenges

Conclusion

Solution Review: Handling CSV file

Solution: Input/Output from File

Explanation