R programming in one hour - a crash course for beginners

R programming is easy. In this video, I'll walk you though how to clean your data; how to manipulate (or wrangle) your data; how to summarize your data; how to create tables and describe your data; how to visualize your data using ggplot (a powerful data visualization package that I use to create bar charts, boxplots, scatterplots, histograms, line graphs and more) . And of course how to analyze your data. The data analysis includes using hypothesis testing and p-values to make inference about a population using sample data. To do this, I'll teach you how to do a t-test, ANOVA, chi-squared test and linear regression models. So if you're a data scientists or researcher doing statistical analysis or some kind of quantitative analysis of data, this video is for you. I cover all of this in one hour.

[emmanuelhoustonkwashie]

This is a complete semester course described in detail in an hour. My Professor, who is paid to teach this course, will be unable to cover even half of what is shown in this video until the semester is through. When I raise inquiries about specific codes in class, the Professor becomes enraged. Greg, I can't thank you enough for this video and so many others. R programming is quickly becoming second nature to me. How can I get access to the linear model and other graphs you used to demonstrate some aspects of the programming? Thank you very much. You are simply the best!

[khawlabintal-azwar]

For those who cannot see the starwars data set:

if (!require(dplyr)) install.packages("dplyr")
library(dplyr)

starwarsDF <-




Type this first and run it:
if (!require(dplyr)) install.packages("dplyr")
library(dplyr)

And then type this and run it:
starwarsDF <-



It is the same dataset.

[sevif_]

(I am adding shortcuts for myself, so if some of them are incorrect don't complain)
00:00 - intro
04:00 - basics
06:52 - Built in data sets to practice with
07:30 - installing and using packages
11:44 - Data structure and types of variables
[ ]
16:04 - Changing variable order
16:31 - changing variable name
17:00 - changing a variable type (factor)
18:12 - changing factor levels
19:36 - filter rows
20:31 - recode data
21:14 - dealing with missing data
22:00 - dealing with duplicates
23:31 - manipulate (create or change a variable[mutate])
23:21 - conditional change (if_else)

c.d.n

[muhammedhadedy]

No words can express my deep gratitude. Thank you so much, Mr. Greg. Please, keep up the great work.

[sullivanfam]

I cannot tell you how excited I am that I finally understand what I am doing in R! Granted, I've spent about 8 hours working through this 1 hour video, but it has finally "clicked." Thank you!

[vikramamin]

I was searching for videos on R programming and stumbled upon your channel. The way you explain the concepts is so wonderful. Simple and precise. I like the fact that in many of your videos, you do touch upon topics that were taught in a previous video.
This video is like a refresher just before one is about to give his / her exam.
Thank u so much for putting in the hard yards and making life for us wannabe data analysts slightly better. Wish u the best in life!!!

[fisfia]

Thanks a mill for this, Greg! I've watched the video 4 times and worked through all of it in RStudio. Not only did I learn a lot of R, I also did grasp some concepts in statistics that I've struggled with before. There's a big difference in the level of understanding when trying it out on your own. Awesome! I highly recommend putting in the time, it was so worth it. I've now downloaded the visualization cheat sheet as well, but that I think I'll have to save until the next weekend ;) Hope your weekend was just as great.

[nl]

I've watched four tutorials on R programming and yours is the best one! Not only concise, quick and relevant, but the way you talk about these topics is truly entertaining and captivating :) Thank you

[sebas]

This video is definitely a life saver! I watched it twice before my midterm exam, and went from barely knowing how to import a csv file and do basic work with it to getting a 90 in my midterm! This even video even helped me get the statistics base knowledge needed to properly understand and analyze the data that is provided by the codes in the video. Again, this is a lifesaver for everyone trying to understand statistics and basic RStudio coding! Forever grateful for all your help!

[fms]

Greg, I absolutely love your teaching style. I was flip-flopping between R and Python and you have convinced me that for data exploration, graphing and statistical analysis, R is the best bet. No doubt I will still learn Python but your style of teaching is what has got me convinced and serious about learning R. I can't thank you enough.

[haraldurkarlsson]

I agree with your approach of using in-house data for these demonstrations 100%. I can't count the number times I have started a lesson (and even paid for it) and quit in frustration because I could not access or find the data they used. Some instructors use some "obscure" data from a R package but don't bother telling you it came from. Others use "external" data that is either no longer accessible (or needs a signup or API) or in has been "wrangled" from the original form into some other shape. Many times I have had to reverse engineer or simulate the data on my own. If you are trying to teach some specific task or topic then this misses the point of the lesson (reminds of my high school when our math books were in Swedish - not my native language - I and I was busy trying to figure out what the words meant rather than doing the math) .
So thanks for be so good about using built-in data rather than some obscure data!

[kumaryashneel]

Thank you Greg. This video is a life saver. My last masters unit (From Fiji) required to use R Programming Language for the major assessment. I had never used R and coming from a non programming background i struggled in keeping up labs, this crash course truly helped. So many vital topics put in so amazingly, well knitted. I learnt more in this video then i had in my whole semester. Thank you and best wishes

[vmzdzqe]

I really appreciate the animation. Kept the lecture a lot more engaging and clear when you were reviewing the code

[TaherehV]

Thank you so much! I looked through a lot of tutorial videos but found them slow, boring and confusing. But you are awesome teacher! 👌

[dr.ranaismail]

Wonderful video!!! I can't recommend it enough! I'm an SPSS user, but I'm learning R programming to be able to run analysis anywhere I go for free (and on the run lol), and then to be able to help others with their own data analysis when they don't have SPSS. R is becoming a more universal package in my opinion. Thank you so much Greg Martin for all your efforts and dedication to teaching global minds :) keep it up!

[philippeberube]

Merci beaucoup pour la vidéo. I'm experienced in SAS and Power BI, but did not know where to start on how to program in R. Your video touched upon all the important themes we need to know to get started.

[revathivamshi]

This category of videos boost up our interest on learning the programming languages .

[wesselgilbers]

Amazing video! Thanks for this. The only explanation I found missing in the video is that you need to code library(package_name) for the packages each time you open up Rstudio in order to use the package again.

[linafakih]

the word I love you doesn't currently express how grateful I am. This is super helpful!!! Thank youuu!!

[bradk]

I’ve been learning python for the last few months and haven’t used R in a long time… this is the perfect refresher I needed for an upcoming interview I have! Excellent stuff :-)