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## What Is R programming?

R is an open-source programming language and free software environment developed by Ross Ihaka in 1993. It forms a statistical environment to perform statistical graphics and computing. It consists of machine learning algorithms, time series, linear regression, statistical inference, etc.

Most R libraries are written in R itself, but C, C++, and Fortran are preferred for heavy computational tasks. The statisticians and data miners utilize this programming language to interpret data and generate statistical software.

## R Program To Create A Matrix

### # R program to create a matrix

M = matrix(
# Taking sequence of elements
c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16),
# Number of rows
nrow = 4,
# Number of columns
ncol = 4,
# So this parameter decides how to arrange the matrix
byrow = TRUE
)
# Naming rows
rownames(M) = c("a", "b", "c", "d")
# Naming columns
colnames(M) = c("d", "e", "f", "g")
cat("The 4x4 matrix:\n")
print(M)

### Output

The 4x4 matrix:

```   d  e  f  g
a  1  2  3  4
b  5  6  7  8
c  9 10 11 12
d 13 14 15 16
```

[Program exited with exit code 0]

## Applications Of R Programming Language

R is very popular in data-driven industries. It is a free and open-source programming language with an active community that contributes to its advancement and helps it reach new heights. R is suitable for all businesses that deal with huge volumes of data. Here is the list of most prominent industries that use R to drive meaning from massive volumes of structured and unstructured data:

Finance: R is used by finance industries to determine risk analytics, risk modeling, develop financial reports, and so on.

Social Media: It is another industry that necessitates the use of computer languages such as R for marketing and metric measurement, among other things.

Healthcare: R is used in healthcare for drug discovery, study genetics, epidemiology, and other scientific studies that require a large amount of data to be analyzed and insights to be generated.

E-commerce: It is another data-driven industry. R is critical for extracting vital insights from massive volumes of data from numerous sources.

Customer Satisfaction: Various industrial industries, like electronic and automotive companies, make use of R to assess clients’ sentiments. Many firms all over the globe utilize R, including Google, Microsoft, Facebook, Wipro, Twitter, etc.

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