🤔QUESTION OF THE DAY: How do you handle missing data? Comments down below! 😃 💗Help support this TH-cam channel by hitting the Subscribe button, Like button and Comment down below! 👇
Sir, can you make a another video on missing data of numerical type where some advanced techniques applicable when mean and median is not working. You are write thing, keep it up and make more video on R.
Hi Deep patel, you got it, next episodes of the ‘Data pre-processing series’ will have more advanced topic of handling missing data. Please subscribe and hit notification bell for update of latest video.
Marco Festugato It’s a pleasure, more videos on Data pre-processing is in the making. Please stay tune for more. P.S. I also referenced your name in the video description
@@DataProfessor thank you very much, I appreciated it a lot! I've started studying R, there should be more youtube channels like yours, I really like it. Don't stop please! And consider writing me if you come to visit Italy :)
Can you do a video regarding some of the important algorithms to master, like regression, classification etc? Trying to find information online can sometimes be overwhelming because they throw a million things at you at once. Thanks in advance.
Hi Bazi, thanks for your suggestion. I'll put this into the to-do list. In the meantime, please subscribe and hit the notification bell for updates of new videos.
Hi Bazi, following up on your suggestion, I've just released a video Data Science 101: Overview of Machine Learning Model Building Process at th-cam.com/video/BOk1hlCPW0c/w-d-xo.html I also referenced your name in the video description, check it out!
Once again..Amazing video!!. However, at the end of the video you suggested to upload other videos on how to deal with missing values for other types of data which are not numerical such as factor, categorical , ordinal..Are you still going to upload these videos? Thanks
Thanks Desmond for the comment and kind words. Yes, definitely and thanks for reminding, I will put this in the priority to-do list. If there is any other topic you would like to see, feel free to suggest.
Great question! There's a mice R package that allows imputing both missing quantitative and qualitative values, the original paper describing the package is available at www.jstatsoft.org/article/view/v045i03
Hello Professor. I have a question which is related to missing data. I have a dataset cars_missing and there has two missing data. When I run sum(is.na(cars_missing)), it's only show 1. Also, When I run view(cars_missing), I can see in column "cubicinches" there has "NA", but in column "brand" there only show blank without NA. I think that's why when I run sum(is.na) there only show 1. Can you explain why?
really nice video . but sir i am getting error while loading data Error in function (type, msg, asError = TRUE) : error:1407742E:SSL routines:SSL23_GET_SERVER_HELLO:tlsv1 alert protocol version
It is difficult to say which is better than the other. If using mean for imputation, the mean value is preserved, meaning that the new resulting mean value would not be changed while this would cause perturbation to the median value; and vice versa for using median imputation. It should also be mentioned that either mean or median imputation ignores the relationship with other variables of the dataset. A better approach would be to perform regression imputation which would consider the relationship with other variables of the dataset. Further complicating this issue is that this discussion is valid for missing values that are numeric. If they are categorical then mean/media imputation would not be valid, thus favoring the logistic regression for predicting the categorical missing values (in a similar fashion to regression imputation for predicting numerical missing values).
Brilliant video! Clear and simple explanations for those just starting out in this area :) Did you ever make videos on how to deal with ordinal/categorical missing data? I can't seem to find them on your channel?
Hi, for imputing categorical data, I would recommend to use the mice R package. Please kindly refer to this for more information www.coursera.org/lecture/missing-data/mice-r-package-N6STE
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🤔QUESTION OF THE DAY: How do you handle missing data? Comments down below! 😃
💗Help support this TH-cam channel by hitting the Subscribe button, Like button and Comment down below! 👇
Your detailed and relaxing method of teaching helps me a lot, Thanks a bunch
Thank you very much for your channel Professor Chanin. And this series will be really useful. Greetings from Poland !
Hi Szymon, It’s a pleasure! Thanks for your support and comment!
Your vids are completely amazing. Please keep posting it, it helps me a lot. Greetings from Brazil!
Glad you like them! Appreciate your kind words 😃
Very Nice... It was very good with basic knowledge covered so simply that all concepts cleared in one go.. Thanks a lot
Thanks for the kind words!
Crystal Clear Explanation!!!
Thanks for the kind words 😃
Sir, can you make a another video on missing data of numerical type where some advanced techniques applicable when mean and median is not working.
You are write thing, keep it up and make more video on R.
Hi Deep patel, you got it, next episodes of the ‘Data pre-processing series’ will have more advanced topic of handling missing data. Please subscribe and hit notification bell for update of latest video.
very nice session sir its really helpful for me completing my project
@@DataProfessor You lied.
@@JYvman 😂😂
Thanks for your video Chanin, I really appreciated it!! Eager to watch more of this^^
Marco Festugato It’s a pleasure, more videos on Data pre-processing is in the making. Please stay tune for more. P.S. I also referenced your name in the video description
@@DataProfessor thank you very much, I appreciated it a lot! I've started studying R, there should be more youtube channels like yours, I really like it. Don't stop please! And consider writing me if you come to visit Italy :)
Marco Festugato Thanks for your kind words of inspiration and hope your job interview is successful!
THIS IS SO HELPFUL!.
Thanks for watching 😃
Loved your way of explanation of things step by step it really helped :)
Thanks
Thank you, Glad to hear that!
Thank you for your time
Can you do a video regarding some of the important algorithms to master, like regression, classification etc? Trying to find information online can sometimes be overwhelming because they throw a million things at you at once. Thanks in advance.
Hi Bazi, thanks for your suggestion. I'll put this into the to-do list. In the meantime, please subscribe and hit the notification bell for updates of new videos.
Hi Bazi, following up on your suggestion, I've just released a video Data Science 101: Overview of Machine Learning Model Building Process at th-cam.com/video/BOk1hlCPW0c/w-d-xo.html
I also referenced your name in the video description, check it out!
Once again..Amazing video!!. However, at the end of the video you suggested to upload other videos on how to deal with missing values for other types of data which are not numerical such as factor, categorical , ordinal..Are you still going to upload these videos? Thanks
Thanks Desmond for the comment and kind words. Yes, definitely and thanks for reminding, I will put this in the priority to-do list. If there is any other topic you would like to see, feel free to suggest.
Thanks for the video. Is that possible to introduce how to impute left-censored data (with multiple limits of detection)?
It was really helpful sir. Thanks a lot ♥️
Thanks Daksha for the kind words! 😃
How can I replace missing data with characters data?
great video thank u!
Thanks for the great video! This problem just occured to me ;)
How do you deal with missing data for classification problems though?
Great question! There's a mice R package that allows imputing both missing quantitative and qualitative values, the original paper describing the package is available at www.jstatsoft.org/article/view/v045i03
@@DataProfessor Amazing, I'll have a look into that. thanks for the fast reply :)
@@jeffersonjones7863 😊
Hello Professor. I have a question which is related to missing data. I have a dataset cars_missing and there has two missing data. When I run sum(is.na(cars_missing)), it's only show 1. Also, When I run view(cars_missing), I can see in column "cubicinches" there has "NA", but in column "brand" there only show blank without NA. I think that's why when I run sum(is.na) there only show 1. Can you explain why?
really nice video . but sir i am getting error while loading data
Error in function (type, msg, asError = TRUE) :
error:1407742E:SSL routines:SSL23_GET_SERVER_HELLO:tlsv1 alert protocol version
Thank u for this. How to get previous working day date? Week starting on sunday and end on thurs day from 1 sep 2020 todate
When is it better to replace NAs with mean? When with median?
It is difficult to say which is better than the other. If using mean for imputation, the mean value is preserved, meaning that the new resulting mean value would not be changed while this would cause perturbation to the median value; and vice versa for using median imputation. It should also be mentioned that either mean or median imputation ignores the relationship with other variables of the dataset. A better approach would be to perform regression imputation which would consider the relationship with other variables of the dataset. Further complicating this issue is that this discussion is valid for missing values that are numeric. If they are categorical then mean/media imputation would not be valid, thus favoring the logistic regression for predicting the categorical missing values (in a similar fashion to regression imputation for predicting numerical missing values).
@@DataProfessor thank you for your professional answer :)
Marco Festugato You’re welcome Marco, I am already planning to make a video on regression and logistic imputation. Please stay tuned!
I didn't get the colsums part. Where did it come from? Please reply fast, I have a project assignment.
colsums perform summation of each columns
It's not working in my R. What do I do?
Brilliant video! Clear and simple explanations for those just starting out in this area :)
Did you ever make videos on how to deal with ordinal/categorical missing data? I can't seem to find them on your channel?
Good and helpful
Thanks Govindha for the kind words and motivation 😃
thank you!
You're welcome! Thank you for watching 😃
¿Which is better for data cleaning python or R?
Both are equally good and capable for data cleaning.
HOW CAN I ATTACH DATA SET
How to handle missing in categorical data?
Hello Prof, I am unable to find data pre-processing series... Please upload videos on how to clean data when it has missing values in factors.
Hi, for imputing categorical data, I would recommend to use the mice R package. Please kindly refer to this for more information www.coursera.org/lecture/missing-data/mice-r-package-N6STE
@@DataProfessor Okay thanku, I'll refer and get back to you if any problem arises.
Why to introduce missing values of the data when it is already clean??..@Data professor
Probably for validation reasons
Hi there I am your new friend
It's very helpful
Let's grow together..
very good explanation ! and a very nice youtuber !
i am Mathe Tutor on TH-cam
much Love from Germany !
Thanks! You have a great channel by the way.
Thanks a lot for your kindness !