Data Science

Introduction to R

4.56 (668 Ratings)
Beginner

Beginner

Skill level
offer

Free

Course cost

About this course

R is a comprehensive statistical and graphical programming language which is fast gaining popularity among data analysts. It is free and runs on a variety of platforms including Windows, Unix, and macOS. It provides an unparalleled platform for programming new statistical methods in an easy and straightforward manner.

Skills covered

  • check R commands
  • check R packages
  • check R functions
  • check Debug
  • check profile R code

Course Syllabus

Intro to R

  • play Introduction to R
  • play R Commands
  • play R Objects.
  • play Data Frames.
  • play List and R Packages
  • play Importing Data in R.
  • play Saving Work in R and scrapping

Course Certificate

Get Introduction to R course completion certificate from Great learning which you can share in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.

GL Academy Sample Certificate

Discussion on Introduction to R

37 Comments

A

Which file should i submit for Practice assessment ? (.R file or excel file)…plzz ans me

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How to add rows to dataframe in R.I want to add some observations to the dataframe.Is there any easy way to do so?

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How to Convert a list to a data frame in R

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How to remove rows with nan values in R.

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How to remove duplicate rows in R?

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where can I get data for data manipulation in R

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What is the simplest way to clear in my console in R ?

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How can I concatenate two strings in R ?

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I’m not able to start learn due to access problem already logged in but error coming about batch not started kindly help me to enroll in this course

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Hi Mayur,

We are extremely sorry for the inconvenience. To help you with this, Kindly write to us at academy@greatlearning.in with your registered email id and we will help you at the earliest.

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How do you add color to a bar graph in R?

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Let’s say, you create a bar-plot using ggplot2:
ggplot(data = diamonds,aes(x=cut)) + geom_bar() Now, there are two ways to add color to these bars. Either you can use ‘fill’ as an attribute inside geom_bar() function of ‘fill’ as an aesthetic in ass() layer.
ggplot(data = diamonds,aes(x=cut)) + geom_bar(fill=“palegreen4”)
With this command, we are using ‘fill’ as an attribute.
Now, let’s use ‘fill’ as an aesthetic:
ggplot(data = diamonds,aes(x=cut,fill=cut)) + geom_bar()

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I need to save R objects into JSON format. What package do I need to use for this?

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  1. Install rjson Package. In the R console, you can issue the following command to install the rjson package.
  2. Input Data. Create a JSON file by copying the below data into a text editor like notepad.
  3. Read the JSON File.
  4. Convert JSON to a Data Frame.
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Can you use R-squared to evaluate forecasted data correlation?

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We cannot use R-squared to determine whether the coefficient estimates and predictions are biased, which is why you must assess the residual plots. R-squared does not indicate if a regression model provides an adequate fit to your data.

A good model can have a low Rsquare Value. The coefficient of correlation is the “R” value which is given in the summary table in the Regression output. R square is also called the coefficient of determination.
Multiply R times R to get the R square value.
In other words, the Coefficient of Determination is the square of Coefficient of Correlation.

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How can I swap the rows and columns of an R object?

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The transpose (reversing rows and columns) is perhaps the simplest method of reshaping a dataset.

Use the t() function to transpose a matrix or a data frame. In the latter case, row names become variable (column) names.

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Is Python better than R for data science?

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Python is Object oriented programming language, it is easier to debug a python program.

Python is open source and simple/easy to learn.

Now rather than figuring out if R or Python is better, it is more important to understand the techniques that are involved in executing these tools. These tools are more of communication to us, where in we instruct the tools in order to execute the models we need the results for. In that case, both R and Python does good job and has unique values.

Ex: For various Machine learning models and visualization.

If the focus is only on data analysis, then i would say both R and Python are equally good. But python being a object oriented language, and if you are object oriented programmer already, then Python is better.

As the world is emerging with IT programmers, the developers community know object oriented programming and hence the adoption of data science techniques using python is much easier.

In the recent past, there has been huge adoption of python in data science.

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Is ResNet one of the R-CNN model?

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In short ResNet is a CNN model.R-CNN is a bigger concept which has/uses ResNet in it as well other classical CNN models

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Is there any free PDF to learn R for data science?

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What are R commands?

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An R script is simply a text file containing (almost) the same commands that you would enter on the command line of R. ( almost) refers to the fact that if you are using sink() to send the output to a file, you will have to enclose some commands in print() to get the same output as on the command line.

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