Is it better to learn R-Programing or Python?

In this tutorial, we will draw some differences between R-Programing and Python which could be better to use because both languages are very popular programming languages that are used for data mining or data analysis to handle big data, And the choice depends totally upon the requirements and performance we need.

Here we will see the difference between them along with some examples to see the same example in both programming languages.


R-Programing Vs Python

Both R and Python are popular programming languages used extensively in data science and analysis. The choice between them depends on your specific needs and preferences.

R is a programming language designed for statistical computing and graphics. It has a large community of users and a vast collection of libraries for statistical analysis, machine learning, and data visualization. If your primary focus is on statistical analysis or data visualization, then R may be the better choice.

Python, on the other hand, is a general-purpose programming language that can be used for a wide range of tasks, including data analysis and ML. It has a larger user base than R and is highly versatile, with libraries available for many different applications, including web development, scientific computing, and artificial intelligence. If you need to work with a diverse set of tools and applications, it may be the better choice.

Ultimately, the choice between R and Python depends on your specific needs and the tools and libraries you plan to use. If you’re unsure, it’s a good idea to learn both and decide which one suits your needs best.

Here we have arranged the same example written in both languages where we can draw the conclusion as per our choice where we can get to know which language is better and when to use which language depending upon the requirement of the situation

Code In Both the languages

Here a program is given to get the mean and standard deviation of a list given in both languages.

# create a list of numbers
numbers <- c(5, 10, 15, 20, 25)

# calculate the mean and standard deviation
mean( numbers)
sd( numbers)


[1] 15
[1] 7.905694
# import the numpy library for numerical computations
import numpy as np

# create a list of numbers
numbers = [5, 10, 15, 20, 25]

# calculate the mean and standard deviation using numpy
np.mean( numbers)
np.std( numbers)

As we can see we will get the same output in case of both programming languages which is producing output the same in terms of syntax also.


To learn more about Is it better to learn You may visit: R programming language vs Python by coursera.

To learn more about programming, and solutions to the problems related to it along with concepts visit: How to send commands to multiple devices with python.

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