Understanding missing data and missing values. 5 ways to deal with missing data using R programming
In this video I talk about how to understand missing data and missing values. I also provide 5 strategies to deal with missing data using R programming. If you're doing quantitative analysis or statistical analysis, your dataset will almost certainly contain missing values. Dealing with missing data using R programming is easy and I provide a step by step approach. This is an R programming for beginners video.
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In this video I talk about how to understand missing data and missing values. I also provide 5 strategies to deal with missing data using R programming. If you’re doing quantitative analysis or statistical analysis, your dataset will almost certainly contain missing values. Dealing with missing data using R programming is easy and I provide a step by step approach. This is an R programming for beginners video.
SUBSCRIBE:
——————–
Click here: https://www.youtube.com/subscription_center?add_user=YourChannelNameHere
LETS CONNECT:
—————————
Twitter: @drgregmartin
Linkedin: https://www.linkedin.com/in/drgregmartin/
Facebook: https://www.facebook.com/thisweekinglobalhealth/
SUPPORT THIS CHANNEL
—————————————–
Patreon: https://www.patreon.com/drgregmartin
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You have saved hundreds if not thousands of hours of beginning analysts time. Thanks!
This helped!!!!!
supper video
clear,
thank you soo much
Greg,
I am having trouble seeing the difference between changing missing data to value vs imputation. Are they not the same? Can you explain the difference.
Thanks!
Great lessions by the way.
Great video. Looking forward to your videos about imputation and the MICE package. Keep’em coming!
Best r tutorial , visuals, pace, delivery….so good!
Great introductory video! Thanks! 😀
I have a question for everyone: I'm imputing missing values for Gender in a dataframe. Out of the complete rows (no NAs) Male=61.89% and Female=the rest obviously. Is there a way I can impute the values randomly but in these proportions? It feels like there must be but I am new to R… Thanks!!
This video has useful information. However, it didn't help me understand missing data. It helped me understand how to filter out or replace missing values with a constant. Not the same.
Great vid but instead of using the "%>%" function, how could we have done it? Since we are not able to save these changes made to the original dataset using "%>%" function.
Why my latest R version shows that no tidyverse package 😫
Great video, helped me a lot cleaning some datasets in an easy way.
Come clean and tell us why you use youtube to push your political agendas whilst hiding behind other doors!
https://www.youtube.com/watch?v=HkPjTHyJ0no&fbclid=IwAR077sXI8CpzxhuRlSVg-ZtyUIv3t7MjzBePyILZT_5_9slPtMkSEkmCQek
It's time you come clean and talk about this.
Dear Greg, I've been watching all you R video in your other channel " R Programming 101". Why didn't you put this R video in that channel?