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

## Input Data from a File
R is one of the most popular languages for data manipulation and analysis. We can perform various statistical analysis with this language. However, the size of the data that we are talking about here is in Gigabytes or Terabytes. Such a large quantity of data cannot be entered by the user interactively from the keyboard. Therefore, data is fed into the system/program using external files. 

Here, we will be learning how to take input from `.txt` files. Now, suppose we have this data stored in a file.

The format of the `.txt` file is:
```
Alex, California, 2025550167, F
Brian, NewYork, 2025354137, M
Charles, Boston, 2025339164, M
```

### Steps to Take Input from File
1. We need to specify the **file name** and its **path** in the local filesystem. If the text file is in the same directory as the R program, just the file name is enough. Open that file using this syntax:
```r
fileData <- file(path, open = "r")

# path is the location of the file plus its name
# open = "r" specifies that we want to open the file in read-mode
```

2. In the next step, we fetch all the data from the file. In this case, we fetch data from `fileData`. For this purpose, we use the function `readLines()`. The syntax is:
```
lines <- readLines(fileData)
```
3. Now that all the lines of the files are stored in the variable `lines`, we can do any calculation or task on this data. 


Let's look at the complete code for inputting data from a `.txt` file and displaying its contents on the screen.

# Input Data from a File
R is one of the most popular languages for data manipulation and analysis. We can perform various statistical analysis with this language. However, the size of the data that we are talking about here is in Gigabytes or Terabytes. Such a large quantity of data cannot be entered by the user interactively from the keyboard. Therefore, data is fed into the system/program using external files. 

Here, we will be learning how to take input from `.txt` files. Now, suppose we have this data stored in a file.

The format of the `.txt` file is:
```
Alex, California, 2025550167, F
Brian, NewYork, 2025354137, M
Charles, Boston, 2025339164, M
```

## Steps to Take Input from File
1. We need to specify the **file name** and its **path** in the local filesystem. If the text file is in the same directory as the R program, just the file name is enough. Open that file using this syntax:
```r
fileData <- file(path, open = "r")

# path is the location of the file plus its name
# open = "r" specifies that we want to open the file in read-mode
```

2. In the next step, we fetch all the data from the file. In this case, we fetch data from `fileData`. For this purpose, we use the function `readLines()`. The syntax is:
```
lines <- readLines(fileData)
```
3. Now that all the lines of the files are stored in the variable `lines`, we can do any calculation or task on this data. 


Let's look at the complete code for inputting data from a `.txt` file and displaying its contents on the screen.

Let's get our hands dirty by taking input from .txt files

Getting Started

Variables

Exploring R Objects

R Operators and Notation

Conditional Statements

Loops

Functions

Input/Output

Exception Handling

Classes

Fun Challenges

Conclusion

Handling TXT files

Input Data from a File

Steps to Take Input from File