Get my FREE cheat sheets for R programming and statistics (including transcripts of these lessons) here: www.learnmore365.com/courses/rprogramming-resource-library
00:01 Cleaning your data involves systematic exploration, cleaning, manipulation, visualization, and analysis. 01:44 Installing packages in R expands functionality. 05:31 Converting character variable to factor variable in R 07:31 Using the factor function to swap levels in R 11:11 Understanding the difference between 'or' and 'and' in filtering data. 13:03 Handling missing data is crucial for accurate analysis. 17:02 Understanding how to handle missing values in data sets is crucial for data cleaning in R. 18:49 Handle missing data with nuanced approach, not just sweeping deletion 22:16 Identify and handle duplicates in data frames 24:04 Selecting and filtering data using base R method
We really appreciate your best RUclips channel for learning R we looking forward to see more especially for survival analysis, parametric and non parametric tests
Your tutorials are unarguably the most explicit and practical for the use of R. Beyond using R as a tool, you explain a lot of statistical concepts. Thanks for all you do, I've learned a lot from your channel
Thank you so much for creating so much accessible and engaging content. For a beginner the way you teach is very clear and easy to understand and your passion for R has made me love it even more! (I also appreciate being hyped up for learning by some drum and bass in the intro)
Incredible channel, the material is better than any course I have paid for. The delivery and the breakdown of topics into separate videos are perfect for learning. Thank you for sharing your expertise and time.
Very useful thank you - especially the section on NAs and recoding. Also appreciate the editing, effects, sound quality and close ups of the code. I’ve recently been using the star wars database for my English teaching lessons to help students with the interrogative. How tall is R2D2? How much does Darth Vader weigh? Etc. One request if possible - Times, Dates and TimeDates. Thank you again, your videos have been very helpful.
Thank you so much Dr Martin. As a beginner , the way you explain the R programming makes me loving that language more and easy to deal with coding. Keep up with more great videos.
Doc Martin! As usual an excellent video! I have one question regarding the recoding. In case of binary cases is it not typical to do 0 and 1 in order to be able to some stats on the data? Thanks and Happy Holidays!
Such good videos for learning R programming and such a nice series. When is the next episode about manipulating your data comming out? Can't wait for it!
Thank you very much Sir. This was quite easy to understand as a beginner. Would you kindly maybe make a series of these videos for us beginners because you have many videos and we wouldn't know which video to watch after this one. I hope that makes sense. Anyway thank you a lot for these videos
Love your videos, man - they're clear and concise, easy to follow! Would you be open to creating content based on the Google Data Analytics Cert? One of the case studies they have is about a fictional bike study called Cyclistic. And there is only one person on YT who does it in an R (Caribou Data Science) but it's not as seamless or clear as you make your videos out to be! :)
When you start to explain how to find complete and incomplete cases at 16:09, what do you do if you want to find incomplete cases for the entire dataset? Would you just omit the "select" portion of the code?
I'm having a problem where I want to mutate two variables with values 0, 1 and NA into a new variable with the sum of 0 and 1, however, R in my case counts NA as 0. Are there an easy fix to this, to exclude the NA?
Can anybody help me with how to disaggregate data that exists in the same column? i.e. in this example lets say you wanted to have a second column(or new variable) for secondary hair color for those values which contain a primary then a secondary hair color i.e "brown, grey", "auburn, white" etc. I am actually working on a file which contains addresses and in many cases the apartment number is not actually separated into another column. However, it should be for the import into the database I am working on and therefore I want to try to create logic to clean and disaggregate these pieces into separate columns. Any help would be greatly appreciated.
Warning in install.packages("tidyverse") : 'lib = "C:/Program Files/R/R-4.2.3/library"' is not writable Error in install.packages("tidyverse") : unable to install packages do you have any insight why I get this message? I'm starting with R for a statistics class and I see you recommend this package? my laptop is archaic...
I can't get the line to work: filter(hair_color %in% c(“blond”, “brown”) & height < 180) Error: unexpected symbol in " filter(hair_color c" > height < 180)
Thank you for this amazing resource. Very helpful for someone like myself who is learning R without any meaningful stats experience aside from a semester at uni. Is anyone learning along able to share their experience of using the mutate and recode functions. I haven't had any success using this whilst following along with this video and a previous one when trying to recode the gender to M and F, or 1 and 2. I've had to work around using : starwars %>% select(name,gender) %>% mutate(gender=if_else(gender=="masculine", "1", "2")) But I'd really like to know what I'm doing wrong using recode as I think my code looks the same as Greg's! starwars %>% select(name,gender) %>% mutate(gender=recode(gender, "masculine"=1, "feminine"=2))
Thanks so much for the engaging yet very useful video! Can i ask why the following chunk of code is not able to recode missing value to the assigned value? starwars %>% select(name, gender) %>% mutate(gender2= if_else(gender=="masculine",1,if_else(is.na(gender),3,2))). Thanks a lot in advancE!
Get my FREE cheat sheets for R programming and statistics (including transcripts of these lessons) here: www.learnmore365.com/courses/rprogramming-resource-library
Great lesson, thanks
00:01 Cleaning your data involves systematic exploration, cleaning, manipulation, visualization, and analysis.
01:44 Installing packages in R expands functionality.
05:31 Converting character variable to factor variable in R
07:31 Using the factor function to swap levels in R
11:11 Understanding the difference between 'or' and 'and' in filtering data.
13:03 Handling missing data is crucial for accurate analysis.
17:02 Understanding how to handle missing values in data sets is crucial for data cleaning in R.
18:49 Handle missing data with nuanced approach, not just sweeping deletion
22:16 Identify and handle duplicates in data frames
24:04 Selecting and filtering data using base R method
Life saver using this vidoe in a last min dash to finish some coursework
Thanks for the feedback Harrison. Glad I could help.
Honestly love all your videos. Detailed explanation and yet simple and straightforward. Keep up the great work.
We really appreciate your best RUclips channel for learning R we looking forward to see more especially for survival analysis, parametric and non parametric tests
Wow, thank you!
Your tutorials are unarguably the most explicit and practical for the use of R. Beyond using R as a tool, you explain a lot of statistical concepts. Thanks for all you do, I've learned a lot from your channel
Thank you so much for creating so much accessible and engaging content. For a beginner the way you teach is very clear and easy to understand and your passion for R has made me love it even more! (I also appreciate being hyped up for learning by some drum and bass in the intro)
Incredible channel, the material is better than any course I have paid for. The delivery and the breakdown of topics into separate videos are perfect for learning. Thank you for sharing your expertise and time.
Excellent! Thanks for putting out such great content that's not only useful, but easy to follow!
Wow - what a nice thing to say (thanks!!)
Thanks for the lessons so far. Love it
Thank you so much, you're such a huge help! I dont think i would pass my 'digital data analysis' course without your channel
Happy to help!
Very useful Greg, such a big help for at R-n00b
You channel is a life saver man. Thank you
Very helpful. the perfect mixture between the background ideas ( what data to dismiss) and the R way to do so.
Hope to see more videos.
Enjoy X-mas
Thanks a lot sir. I can't be grateful enough for your videos
I do love your enthusiasm Greg, it really keeps me interested in watching through to the end!
Thanks John - much appreciated!
You're a hell of a teacher! congrats!!
YOU ARE SUCH A GOOD TEACHER... THANK YOU
Very useful thank you - especially the section on NAs and recoding. Also appreciate the editing, effects, sound quality and close ups of the code. I’ve recently been using the star wars database for my English teaching lessons to help students with the interrogative. How tall is R2D2? How much does Darth Vader weigh? Etc. One request if possible - Times, Dates and TimeDates. Thank you again, your videos have been very helpful.
I am here for the "super duper easy"... Keep up the great work Dr, thnaks.
Thumbs up for you Greg!
Very clear, useful and interesting. I'm just getting into R and this helped me understand how it can be used for sensible data cleaning.
Great to hear! Thanks for watching!
Thank you, Dr Martin
Much appreciated. Amazing skills in such a simplified way thank you.
Glad it was helpful! Thanks!
Truly helpful! Amazing video for tidyverse
Glad it was helpful!
Thank you so much Dr Martin. As a beginner , the way you explain the R programming makes me loving that language more and easy to deal with coding. Keep up with more great videos.
Thank you for the feedback. Glad you enjoyed it! You got this!
This is brilliant, I am on my third video and I am amazed at how easy this is made to seem👏
Easy, Peasy, Lemon Squeezy!
Best R Programming Channel
Keep it going!
this tutorial is Excellent! thank you!
You are an awesome teacher. I want to give you a hug right now! 😊Thank you for making it so easy to foloow through.
Hi there, Greg! Thanks a lot for these videos, love your style. I've learned A LOT!
Great to hear, Yamila! Thank you for the feedback!
Thank you so much for the great and useful videos
Thank you so much! love all your videos! simple and straightforward! with detailed explanation.
I'm so glad to have you as a subscriber! Thank you for being a part of this community.
Solid tut. Thank you.
I don't usually comment, but this man here is the best I've come across on youtube,. Damn, too good
Out of all the online classes and videos I have done, I WISH I STARTED WITH THIS ONE!! Thank you!
Glad it was helpful! Thanks for your amazing feedback
You're amazing at teaching this. Thank you!
you are most welcome melina.
Excellent lectures and a good lecturer also
You really make programming seem "easy-peasy lemon squeezy", keep it up!
Thanks for watching!!! I appreciate your feedback!
Thank you so much. Your videos are very helpful.
Glad you like them!
Thank you for this. Very helpful.
You're very welcome! Glad it was helpful.
Perfect lecture ! benefited a lot.
Glad it was helpful! Thank you :)
You Sir, are a legend!
You sir have an incredible voice for teaching. Glad I found your channel
Glad to hear it! Thank you!
Thank you very very very much!! Really appreciate your wonderful video. 👍👍👍
You are very welcome. Glad you enjoyed it!
Thank you so much!
Very helpful! Thank you, sir!:D
Glad it was helpful!
Appreciate your helpful videos
Happy to help! Thank you.
Bravo, this content was very good
thanks . I've really appreciate your video
You are welcome! Thank you!
Thank you!! 👑
Thank you very much! Very helpful
Glad it helped! Thanks for watching!
GREAT VIDEO
best practice lecture for R
oh my god man you are a godsent!!!!
I've been learning R in the google data course from Coursera and they don't teach much.
Thanks a lot!
You're welcome!
Excellente~! Thanks -
great! thank you very much
Thanks for the great feedback- Much appreciated !!
Doc Martin!
As usual an excellent video! I have one question regarding the recoding. In case of binary cases is it not typical to do 0 and 1 in order to be able to some stats on the data?
Thanks and Happy Holidays!
Thank you!
You're welcome!
Love this. I didn't know there was an in-house R dataset for star wars.
Yeah - I love it!
You explained it thoroughly ❤❤
Glad it was helpful!
Thanks a lot.
Most welcome!
love it
Thank you for the video sir
Most welcome! Thanks for watching.
Great content.
Recode is superseded… we need a new video on this topic 🙂
Such good videos for learning R programming and such a nice series. When is the next episode about manipulating your data comming out? Can't wait for it!
haha - any day now... (perhaps tonight)
Thank you so much, you're such a great help! please show us how to create Dashboards via Shiny. Thanks a lot.
super thanks
Pretty handy tips
Glad you think so!
Thank you very much Sir. This was quite easy to understand as a beginner. Would you kindly maybe make a series of these videos for us beginners because you have many videos and we wouldn't know which video to watch after this one. I hope that makes sense. Anyway thank you a lot for these videos
I will try my best
Just curious is there any reason why you haven't enabled coloured brackets as per the last update it would make the code easier to read
Thanks
Love your videos, man - they're clear and concise, easy to follow! Would you be open to creating content based on the Google Data Analytics Cert?
One of the case studies they have is about a fictional bike study called Cyclistic.
And there is only one person on YT who does it in an R (Caribou Data Science) but it's not as seamless or clear as you make your videos out to be! :)
Yo you arer the best programing youtube chanel bro
Wow I appreciate the kind words. Your support encourages me to create more content that you'll enjoy! Thank you
For the replace NA, it just filter the dataset but it doesn't change anything from the dataset. So the dataset remained not cleaned.
When you start to explain how to find complete and incomplete cases at 16:09, what do you do if you want to find incomplete cases for the entire dataset? Would you just omit the "select" portion of the code?
Hi,
Love your videos they are so helpful. Could you do a video on loops in r ?? Thanks!
Thanks for the suggestion. Will do.
Got it!
Thank you so much for watching and leaving a comment! I appreciate your support.
What if the integer was a chr data type and you want to change it to an integer or double
Tx sir
Welcome!!
I'm having a problem where I want to mutate two variables with values 0, 1 and NA into a new variable with the sum of 0 and 1, however, R in my case counts NA as 0. Are there an easy fix to this, to exclude the NA?
How can you convert data type using mutate in dplyr?
what is the difference between a data frame and a tibble
Can anybody help me with how to disaggregate data that exists in the same column? i.e. in this example lets say you wanted to have a second column(or new variable) for secondary hair color for those values which contain a primary then a secondary hair color i.e "brown, grey", "auburn, white" etc. I am actually working on a file which contains addresses and in many cases the apartment number is not actually separated into another column. However, it should be for the import into the database I am working on and therefore I want to try to create logic to clean and disaggregate these pieces into separate columns. Any help would be greatly appreciated.
And how do you undo a command that you had already executed?
Hello can you make playlist about OOP in R ?
Could you do a video on data management using R please
Warning in install.packages("tidyverse") :
'lib = "C:/Program Files/R/R-4.2.3/library"' is not writable
Error in install.packages("tidyverse") : unable to install packages
do you have any insight why I get this message? I'm starting with R for a statistics class and I see you recommend this package? my laptop is archaic...
I can't get the line to work: filter(hair_color %in% c(“blond”, “brown”) & height < 180)
Error: unexpected symbol in " filter(hair_color c"
> height < 180)
same here, showing ERROR in 'filter()'
variable types
select and filter
find and deal with missing data
find and deal with duplicates
recode values
Thank you for this amazing resource. Very helpful for someone like myself who is learning R without any meaningful stats experience aside from a semester at uni.
Is anyone learning along able to share their experience of using the mutate and recode functions. I haven't had any success using this whilst following along with this video and a previous one when trying to recode the gender to M and F, or 1 and 2. I've had to work around using :
starwars %>%
select(name,gender) %>%
mutate(gender=if_else(gender=="masculine", "1", "2"))
But I'd really like to know what I'm doing wrong using recode as I think my code looks the same as Greg's!
starwars %>%
select(name,gender) %>%
mutate(gender=recode(gender, "masculine"=1, "feminine"=2))
Really excellent PT.
Then how R is associated with Python algorithm?
Thanks so much for the engaging yet very useful video! Can i ask why the following chunk of code is not able to recode missing value to the assigned value? starwars %>%
select(name, gender) %>% mutate(gender2= if_else(gender=="masculine",1,if_else(is.na(gender),3,2))). Thanks a lot in advancE!
Hello Sir, can you please make a video about pachage shiny on medical data ?
Thanks a lot, great videos !!
How come I am just discovering this channel?
I'm a newbie to r, is there a open community where people can help you with your work
If you are here from Tom's Bayesian stats class, give this video a thumbs up!
nobody seemed to be. But here's a thumbs up (I'm here cause of stats class too lol)
Never thought Jason Statham is an "R" Expert
Super duper easier in SPSS.