Python Vs. R By Lavanya Vijayan

Python Vs. R By Lavanya Vijayan

Python and R are common programming languages used when working with data. In this course, taught by expert data scientist and coding instructor Lavanya Vijayan, you'll learn the important considerations for using each language in various circumstances. You'll discover how to analyze data using both languages, and examine the use-cases that play to each language's strengths. By the end of this course, you should feel confident in your ability to discern the best programming language to use between Python and R.
Data Strategy
Growth Mindset
Personal Development
Content Rating: U

Episodes

00:15 min
01:11 min
Python and R are two very popular programming languages used in the data science world. After this course, you'll be able to identify the best situations for utilizing each programming language.
00:39 min
Before diving into the topics discussed in this course, there are a few things you should be aware of. After this lesson, you'll be able to feel prepared when navigating the rest of the course.
00:15 min
02:10 min
There are specific programming languages that play nicely in the context of the data science world. After this lesson, you'll be able to recognize the reasoning behind this logic.
03:22 min
Using Python when working on data science projects can be a valuable tool. After this lesson, you'll be able to identify the reasoning for using Python in data science situations.
02:41 min
R is a helpful analytics language for working in the data science world. After this lesson, you'll be able to identify the benefits of using R for data science.
02:12 min
Python and R are both valuable languages to use when tackling a data science initiative. After this lesson, you'll be able to conduct high-level comparisons between the two languages.
00:15 min
02:28 min
When loading your data, the method you will use depends on the type of data file you have and the programming language you're working in. After this lesson, you'll be familiar with the methods of loading data for the major file formats in both Python and R.
04:07 min
There are different approaches to data exploration depending on which programming language you are using. After this lesson, you'll be able to recognize the key differences and similarities in exploring your data with Python and R.
05:35 min
Python and R can both be extremely valuable to use when cleaning and manipulating your data. After this lesson, you'll be able to recognize these values and differences to make better decisions throughout your process.
03:15 min
Visualizing your data is a crucial aspect of discovering and communicating trends captured by your data, so it's necessary to carry out the right steps to create visualizations. After this lesson, you'll be able to translate visualization goals into visualization methods and pinpoint how the process differs between languages.
00:15 min
02:46 min
There are many strategies for conducting data analysis in R. After this lesson, you'll be able to conceptualize a major data analysis strategy in R and the types of insights this can help you achieve in a data science project.
01:47 min
Python can be a very useful language to perform data analysis. After this lesson, you'll be able to conceptualize a powerful strategy for data analysis in Python and how insights can be drawn from this.
00:15 min
04:29 min
There are several common applications of Python in which it's the better tool to use. After this lesson, you'll be able to identify what these applications are, and why Python is the right choice in these circumstances.
02:07 min
There are applications of R in which it's the better language to use for data science projects. After this lesson, you'll be able to articulate what these projects and goals are, and why R is the better option in these circumstances.
00:15 min
01:07 min
Now that you've finished this course, you should feel armed to determine which programming language to use and when to use them in different scenarios. Thanks for watching!