R package reviews | dlookr | diagnose, explore and repair your data quick!

In this video, we'll learn how to quickly diagnose, explore and fix problem in your data.

We'll have a deep look at missing values and ourliers and will be able to impute them with fancy machine learning techniques. And of course, we'll make much more.

If you only want the code (or want to support me), consider join the channel (join button below any of the videos), because I provide the code upon members requests.

Music by Vincent Rubinetti
Download the music on Bandcamp:
Stream the music on Spotify:

Enjoy! 🥳

[wayarberry]

Outstanding. Tremendous functionality accessible with relatively few, simple commands. Top notch graphics as well. Keep up the good work!

[muhammedhadedy]

Wow, what an amazing tutorial. I've been using R for 5 years, and I've never used the dlookr package before. Your explanation was simple, focused and directed to the point, just as usual.
Thank you so much for your great videos. I really appreciate your work.
😊😊😊😊😊😊.

[mkklindhardt]

I love your videos and screencasts! They are very educational and still very high-level.

Could you please make a video on performing meta-analysis in R using for example the metafor or other packages? Especially covering the choices one has to make concerning types of meta-analysis: e.g. fixed-effects, random-effects or bayesian meta-analysis of different types of response variables, modulators and outcomes. It could also be cool if you covered the considerations of multivariate and multilevel meta-analysis as well as composite outcome meta-analysis, such as the concept of "borrowing of strength" (BoS) in meta-analysis when dealing with multiple outcomes or studies with small sample sizes.

[sandiprijal]

Why didn't I came across you channel till now? This is phenomenal

[imanol]

This (specially this!) is marvelous, but also the rest of the series of explanatory videos. Congrats!

[angezoclanclounon]

Thanks a lot Dr. Yury. Nice and helpful video.

[syhusada]

I've been using data explorer and dlookr more in my learning journey thanks to you sir.

[buraktiras]

An overall thanks for all the videos uploaded into this channel!

[hendrikpehlke]

Wow! Thank you! So many important informations. I have to watch this video several times. But one question: In which order would you use the packages "janitor" and "dlookr". Would be interesting to teach people how to load and handle "dirty" excel table, fix some excel problems (e.g. date as numbers or entries like "no data" in numerical columns etc) and if those problems are fixed to use "dlookr" to diagnose, explore and repair the data.

[dasrotrad]

What a great presentation. I love this package. Thank you for introducing it and descdribing it in such an easy to follow presentation.

[landoska]

Great! I love your videos. Please cover mixed models 🙏🤓

[bj]

I really hope your channel will grow in the future. Your videos are very helpful to me.

[haraldurkarlsson]

Yury,
I noticed that your code for imputing outliers in the diamonds data repeats and is thus prime for a for loop, apply or map function (this is roughly 14 minutes into the video). I did not try to get too fancy so I wrote a short for loop to iterate over the methods. The function generates the plots one after the other. I thought I might share this with you and your viewers. Here is my rather crude code:

imp_na_method <- c("mean", "median", "mode", "capping")
for (i in imp_na_method){
result = plot(imputate_outlier(diamonds, carat, method = i))
print(result)
}

I am sure that an apply function or one of purrr's map functions might even be more compact. Would love to see what folks come up with.

Thanks for all these excellent videos.

[angvl]

Great video and great analysis ! Thank you very much!
I also like package("recipes") and package("vtreat").

[SadatQuayiumApu]

Thank you very much for the videos!
These are life changing indeed.

[SergioUribe]

great package, kudos and keep the work!

[haraldurkarlsson]

Yury,
I have duplicated your code and it basically reproduces with a few exceptions. For instance the correlation plot is not a matrix with ellipses but rather a colored chart with the r values. I guess as the package gets updated we will see some variations. Still good stuff - thanks.
P. S. I ran my code in normal r-session with script rather than in RMarkdown.

[GreenManXY]

How do you get the results in the same window as your code? And the ability to preview graphs?

[RUJedi]

Amazing video. This will be a great package for my EDA work. Many thanks.
Is everything ok with your website in the video description? I keep getting a 404 Site Not Found error page. Same result when I try similar links in a few of your other videos.... ?

[M.Nagah]

I have a question plz, Why did we put “temp” as a predictor to imputate missing values in Ozone variable ?