This is part of why I am creating these videos. I wish I had college professors that had a knack and love for data science, instead of ones that were just there to become tenured. Some were good researchers, but they couldn't teach the ideas or get students to think creatively and outside the box. I also create these videos to give back to the data science community because it has been so good to me over the years. Plus, I just love to help others. I am glad you like my videos and are benefiting from them. Please feel free to share them with others so that they can learn also. Thanks again. :)
Thank you. Helping people to learn data science and real everyday use for data science is what this RUclips channel is all about. The data science community has been very good to me, so this is my way of giving back. These are all processes that I and my team actually use for a Fortune 200 international company every day to provide really interesting insights that executives can act on and make great decisions based off of. Thank you.
Thank you. I am glad you found this helpful. You will find that roughly 80% of a data scientist's and data analyst's work day is spent dealing with data issues (new, unclean data, data in hard to get to places, etc...) the better and more effective one gets at cleansing data, the easier your day will be and the more time you can spend on the other 20% (creating new novel processes, deep learning, etc.) Look at the other videos on my channel which cover all sorts of stuff that you will find helpful to your career. Thanks again and best of luck with your career!
Thank you. 80% of data science is obtaining and cleaning the data. This video shows how we do this with real campaign data for a real company. Real applications! What would you like to see next in my videos?
As I have time, a lot of the datasets are uploaded to Kaggle and the code on Researchgate.net. Just look up David Maillie on either. Thanks again. Question - I like to hear from my audience, what would you like to see in an upcoming tutorial video?
@@techknowhow4802 Hello! This is a great tutorial! However the dataset is not up on the Kaggle or Researchgate. Could you please send us a link or give us an email to send a request. thanks!
Is the subset function being used an alternative to filter? If yes why prefer this over filter and what’s the syntax? If No what’s the difference between subset and filter and again why prefer the former over the later?
SOme of these data files are on Kaggle.com. Others are sometimes proprietary information and so I cannot always release them to the public. Thanks again. :)
Hi, Thank you for wonderful video. I have one question. I have dd-mm-yyyy HH:MM format in excel file. When I import it, it is imported as 43922.03 and so on. How shall I convert this to date and time format in R? Thanks in advance.
Look at the data type of your columnsin Excel. If you leave them as text that can happen. Also, general date with minutes and hours will have same issues. Change format for affected columns in Excel to be the very first choice in Date type. *3/14/2012. That will then come across correctly. Easier to fix in Excel by column. ☺
If you need time - place that portion in a Seperate column. I have never had to use the time portion for any analysis. It is possible depend8ng on your niche and your data. If you need that, place it in a Seperate column for later analysis.
Thank you for creating a video to help people learn data science. I wish I would have known about you 3 months ago. I would have gladly pay you to teach me Data Science in such great detail:) (I am trying to install package (openxlsx) and I keep getting this error message- Error in library(openxlsx) : there is no package called ‘openxlsx’). I have done "installed.packages ("openxlsx", dependencies = TRUE), and the error message continues to appear. And, I even tried - 'help(openxlsx)' it says, No documentation for ‘openxlsx’ in specified packages and libraries: you could try ‘??openxlsx’. Any suggestions of what is the issue and why I continue to get this error message.
Your welcome. If you don't mind my asking - What is the current BI tool that you are using? Or do you use numerous tools and/or apps? Do you see any specific problems you need solutions to? I like to see what my audience is using and problems they might be facing and then I can create tutorial videos that are better catered to them. Thanks again. :)
Unfortunately no. Data doesn't work like that. There are some applications like Alteryx that help here, but R is great once you have built a reusable process.
A lot of the data I use is proprietary. That means I cannot share it and in most cases it is scrubbed. If you are looking for a similar practice dataset for data cleaning in r or pretty much anything in r for that matter, try the University of California at Irvine Data Science Data Repository. They have thousands of freely available datasets all labelled correctly for you to choose from and use for learning, building reusable processes and templates and much more. Thanks again for watching this and the other videos on my data science channel. :)
Clear delivery of Subject materials. Appreciated.
Glad you liked it
You are an amazing teacher and data scientist. I wish if had a teacher like you in my collage. Thanks for helping beginners like me.
This is part of why I am creating these videos. I wish I had college professors that had a knack and love for data science, instead of ones that were just there to become tenured. Some were good researchers, but they couldn't teach the ideas or get students to think creatively and outside the box. I also create these videos to give back to the data science community because it has been so good to me over the years. Plus, I just love to help others. I am glad you like my videos and are benefiting from them. Please feel free to share them with others so that they can learn also. Thanks again. :)
@William Maphosa Did you receive the dataset and could you kindly share? Thanks
Being new to R, I really appreciate this. So well explained.
Thank you. Helping people to learn data science and real everyday use for data science is what this RUclips channel is all about. The data science community has been very good to me, so this is my way of giving back. These are all processes that I and my team actually use for a Fortune 200 international company every day to provide really interesting insights that executives can act on and make great decisions based off of. Thank you.
New to R. . This has been so helpful. Thanks
Glad it was helpful!
thank you so much for the video! so helpful to beginners in R and very clearly explained in simple language i can't thank you enough :)
Glad you found it helpful! Thanks again. :)
Thank you 😊 I just got some ideas about data cleaning.
Thanks for the video. This help me much to cleaning Data efficiently.
Thank you. I am glad you found this helpful. You will find that roughly 80% of a data scientist's and data analyst's work day is spent dealing with data issues (new, unclean data, data in hard to get to places, etc...) the better and more effective one gets at cleansing data, the easier your day will be and the more time you can spend on the other 20% (creating new novel processes, deep learning, etc.) Look at the other videos on my channel which cover all sorts of stuff that you will find helpful to your career. Thanks again and best of luck with your career!
Superb video sir!
Thank you. 80% of data science is obtaining and cleaning the data. This video shows how we do this with real campaign data for a real company. Real applications! What would you like to see next in my videos?
Thanks for this amazing video. Could you by any chance give us the R script you're working from?
thank you
This video is amazing! Thank you, David, for posting it. Could you please share the R Codes and the data you are using in this video?
As I have time, a lot of the datasets are uploaded to Kaggle and the code on Researchgate.net. Just look up David Maillie on either. Thanks again. Question - I like to hear from my audience, what would you like to see in an upcoming tutorial video?
@@techknowhow4802 Hello! This is a great tutorial! However the dataset is not up on the Kaggle or Researchgate. Could you please send us a link or give us an email to send a request. thanks!
@@techknowhow4802 Please upload Machine learning videos on R like how to develop a regression models using R.
Thank you so much for this video. I am new to R and this really helped me gain a better understand of the coding.
Glad it was helpful!
Is the subset function being used an alternative to filter?
If yes why prefer this over filter and what’s the syntax?
If No what’s the difference between subset and filter and again why prefer the former over the later?
Thanks for posting this video it´s very helpful, do you have any recommendation on how to standardize Tech-Stack inventories?
I couldn't find the dataset when I searched with your name (David Maillie) on Kaggle. I found your Kaggle but did not find any Oil Change data
I don't publish every dataset. Some contain proprietary data that I cannot release like that. Thank you for understanding.
Example is really nice. Can you share the data file?
SOme of these data files are on Kaggle.com. Others are sometimes proprietary information and so I cannot always release them to the public. Thanks again. :)
if you can help with, how to remove a bivariate outlier. thanks
Hi, Thank you for wonderful video. I have one question. I have dd-mm-yyyy HH:MM format in excel file. When I import it, it is imported as 43922.03 and so on. How shall I convert this to date and time format in R?
Thanks in advance.
Look at the data type of your columnsin Excel. If you leave them as text that can happen. Also, general date with minutes and hours will have same issues. Change format for affected columns in Excel to be the very first choice in Date type. *3/14/2012. That will then come across correctly. Easier to fix in Excel by column. ☺
If you need time - place that portion in a Seperate column. I have never had to use the time portion for any analysis. It is possible depend8ng on your niche and your data. If you need that, place it in a Seperate column for later analysis.
Thank you for creating a video to help people learn data science. I wish I would have known about you 3 months ago. I would have gladly pay you to teach me Data Science in such great detail:)
(I am trying to install package (openxlsx) and I keep getting this error message- Error in library(openxlsx) : there is no package called ‘openxlsx’). I have done "installed.packages ("openxlsx", dependencies = TRUE), and the error message continues to appear. And, I even tried - 'help(openxlsx)' it says,
No documentation for ‘openxlsx’ in specified packages and libraries:
you could try ‘??openxlsx’.
Any suggestions of what is the issue and why I continue to get this error message.
Your welcome. If you don't mind my asking - What is the current BI tool that you are using? Or do you use numerous tools and/or apps? Do you see any specific problems you need solutions to? I like to see what my audience is using and problems they might be facing and then I can create tutorial videos that are better catered to them. Thanks again. :)
using as.Date gives me NA in the column... any idea why??
Look at your data. Might be a problem with the original formatting or maybe you have a missing value hiding in there?
Do you provide the link for the data you are using
Could you please share the R file you used?
Where to get the data from
SOme of the datasets are at Kaggle. Look me up there. :)
@@techknowhow4802 thank you very much
Couldn't you just put the data in the dishwasher and clean it automatically ? hehehe :0
Unfortunately no. Data doesn't work like that. There are some applications like Alteryx that help here, but R is great once you have built a reusable process.
This video was really helpful. Would you consider sharing the script as a link to the file in the description box?
A lot of the data I use is proprietary. That means I cannot share it and in most cases it is scrubbed. If you are looking for a similar practice dataset for data cleaning in r or pretty much anything in r for that matter, try the University of California at Irvine Data Science Data Repository. They have thousands of freely available datasets all labelled correctly for you to choose from and use for learning, building reusable processes and templates and much more. Thanks again for watching this and the other videos on my data science channel. :)