Li Wang 6/9/2022

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1. My thoughts on R vs Python:

Key Similarities:

R and Python are programming languages and both these languages are similar in few ways. They are free to download and use; They are used majorly in data science.

Key Differences:

R mainly focuses on the statistical part of a project while Python is flexible in its usage and data analysis tasks.

R is a powerful tool for visualizing data in the form of graphs. It is difficult to use R in a production environment due to its yet-to-develop production tools, whereas Python is easily integrated with a complex work environment.

Python is a better option as it runs faster in all the environments than R.

2. What functionality do I like about R?

Open Source:

R is an open-source language and is free to download and use.

Platform independent:

R is platform-independent and can work on all the operating systems like UNIX, Windows, and Mac.

Data Wrangling:

Through its packages like readr and dplyr, R has the capability of converting a messy code into a structured one.

Package Availability:

R has numerous packages dedicated to the development of machine learning, data analysis, and statistical projects.

Plots and Graphs:

Through ggplot and plotly, R creates attractive graphs with notations and formulas.

R Markdown output

plot(iris)

3. What parts do I miss about your other language?

Slow Runtime: R is a slow processing language. In comparison to other languages such as Python, it takes more time to give an output.

Difficult to learn: Unlike Python, R is a complicated language and is difficult for a beginner to learn.

It is difficult to use R in a production environment due to its yet-to-develop production tools, whereas Python is easily integrated with a complex work environment.

4. Do I consider R a difficult language to learn?

I think R is difficult for a beginner to learn because it’s so different to many programming languages. The syntax of R, unlike languages like Python, is very difficult to read. What’s more, basic operations like selecting, naming and renaming variables in R are more confusing than they are in other languages.