Describe and Summarise your data
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- čas přidán 19. 05. 2024
- If you want to learn about to summarise your data by making tables in R or provide descriptive statistics of your dataset, then this video is for you. R programming provides more than one way to summarise and describe your data. You can use base R using, for example, the table() function, for example (and that is covered in this video). I prefer to use the Tidyverse packages that make it much easier (especially if you are a beginner) to create a summary or table. So if you are into data science or just needing to analyse some data, your starting point is descriptive statistics and summary tables before you move on to inferential statistics and modelling your data. This is an R programming for beginners video and I only use datasets that you have each access to.
A huge thanks to Nested Knowledge for supporting the creation of this video. I you are doing research of any kind, you'll need to do a literature review. Nested Knowledge allows you to create and share your systematic literature reviews online. Go to: nested-knowledge.com
Get my FREE cheat sheets for R programming and statistics (including transcripts of these lessons) here: www.learnmore365.com/courses/rprogramming-resource-library
To parrot others, you always have premium R content. Probably the only resource where I look forward to seeing it in my CZcams feed.
You really make the best R-videos. Always feel motivated to work with R after watching this. Thank you very much!
Thanks 👍🏻👍🏻👍🏻👍🏻 glad to hear it.
Imagine have you as a professor at the university, everyone would pass. Big thanks to you!
Wow Thank you for your kind words, I really appreciate it!
I hated R till I found your channel , I know there are a million comments telling you same thing but you are one of the best R teachers. I hope you are having a good day wherever you are in the world ❤
Thank you so much, Farida. I really appreciate your feedback 😀
so far you have taught R in the best way. Please do the complete R tutorials with the aim of cracking a data analyst job. We really do not know what we need to cover as in for performing good at data analyst jobs. You can also make a video depicting an overall picture or syllabus for R, for different kind of analysis which will help us to know what all we have to learn to get a job as a DA first, and then take it from there. Please be consistent. You are amazing.
Your videos are always illuminating and a great reference when working in R. Please do a tutorial on difference in differences using R. Thanks
Really love the tutorials. Is there any chance there could be a playlist/video on user-defined functions and loops in the future? I'm finding it hard to find a good tutorial that goes through it all slowly. Cheers.
The best educational R videos I have found on CZcams, thank you for the helpful information.
I love your style of teaching. Your approach makes coding easy. Thanks for the great work you’re doing.
You're very welcome! Glad you enjoyed it!
Your videos are excellent and you explain everything in a very simple way, I can say that I have filled in a lot of gaps, especially in visualisation. I was wondering if you will create more videos or specifically videos regarding loops. Thank you!
Extremely well thought-out and practical!
Great video - thanks very much! Thanks for explaining that last part slowly too.
One minor comment -> @10.02 I couldn't see your full console, so missed that there needed to be a close brackets, pipe operator before the 'arrange' function starts.
You are an absolute rockstar, thank you very much. R is amazing, and you are an equally amazing teacher.
Very well explained tutorial, as always. Please, keep posting new videos.
😀 will do 👍🏻
Thanks Greg, R Programming 101 is the best R programming tutorial I have ever found !
Thank you for the feedback!
Great videos! Keep the good stuff coming!
Great video, thank you! Is there any package that can be used to created the coloured table with the percentage indicator you showed at the beginning of the table? Thank you!
Great R tutorial! I’m looking forward to learn. from you more =)
Anyway, do you have any recommended book about R for statistics and data science for further reading?
Great as usual. Thank you so much for your great videos.
I should have gone through this set of videos months ago! Would have saved me many sleepless nights and project delay!
Glad you find them useful!
Love your videos, please keep uploading them :)
Amazing way as Usual Thanks 🙏 keep up the great work looking forward for the next episode
Thanks 👍🏻👍🏻👍🏻
Thank you for these beautiful videos. I'd be really happy if you made one on packages that deal with spatial data like cartography. Thanks for your efforts 👍
Great suggestion! Thanks for your feedback 😀
wonderful video. Greg, I have learned so much from your videos. Thank you.
Thanks for the feedback. Much appreciated. I'm glad that you found it helpful.
Very well explained 👍
The best place to learn R, I really enjoy. Thanks
Happy to hear that! Thank you for the feedback.
Thanks so much. These are great. Keep it up.
Many thanks once again for your fantastic course!
Happy to hear that! You are most welcome!
Thank you for this lesson.
Step by step I am begining to be a big fun of your CZcams channel 😀)
P.S. Thank you for these valuable knowledge what you share for us.
Most welcome! Glad you liked it!
Awesome! Thank you as always....🙏 You Rock!!!!
Most welcome! Glad you liked it!
Great class.
Keep up the good work.
Thank You,
Natasha Samuel
Thank you! 😃 thanks for the great feedback!!
Great videos about R, congratulations
Thanks very much. 😃😃
Your way you of explaination is really nice...
Hi Greg - would it be possible to make a video on creating publication ready summary tables using r and r-markdown? Particularly summary statistics tables and regression tables
Interested in this too. Have you tried the stargazer package?
Very helpful.
How to compute with the data that contains greater than or lesser than (6) in R.
Thanks, one note if you use the summary() on a column that contains factors it will return the number of rows for each factors.
I am so grateful you took the time to explain 'everything.' I paid for a course and only learned a fraction of what I'm learning with your videos. I would love to know how to change the UTC timestamp into a particular zone. I am working with a crime dataset and trying to figure out #1 what day of the week most occurred and what time they occurred. I've read numerous articles, but I need help understanding the concept. ♥
Just found your Lubridate video... heading there now ☺
wonderful lecture
I love you man! Thank you so much.
Happy to help! Thanks for watching
Very helpful video! Do any videos explain how to create the prop table using the tidyverse?
Did you ever find a solution for this question?
Hi, say i have two tables in R and i want to see which rows in a column in table 1 are also there in a column in table 2, how would I go about?
HELP! That output table you made (with the period as a name)....how do I change the name of this or export the output as a CSV. None of the normal "write.csv" functions work when I try to extract the data. The sheet just comes back blank.
Very helpful sir
Great thanks!
Can you be so kind to make a dummy variabile model please!!... Thank you!
I love your videos, they are very helpful.. Thank you! :)
A note regarding code at 5:03. There is a coding difference between using the |> pipe instead of %>%. If using |> , the final "summary" requires parentheses, i.e., summary(). (R version 4.3.0)
Excellent videos
Glad you like them!
What does number=n() do inside the summarise parameter?
A tidyverse implementation of
prop.table(table(AirBags, Origin))*100
is:
Cars93 %>%
group_by(AirBags,Origin) %>%
summarise(number = n()) %>%
ungroup() %>%
mutate(propor = round (number / sum(number),3 )*100) %>%
pivot_wider(id_cols = "AirBags" , names_from = Origin,
values_from = propor)
or even a shorter one using *count()* to replace the aforementioned 2nd and 3rd rows :
Cars93 %>%
count(AirBags,Origin) %>%
mutate(propor = round (n / sum(n),3 )*100) %>%
pivot_wider(id_cols = "AirBags" , names_from = Origin,
values_from = propor)
Thank you so much, I was wondering about that part
Thanks for providing these lines of code. I added the first part to this.
Cars93 %>%
group_by(AirBags,Origin) %>%
summarise(number = n()) %>%
ungroup() %>%
pivot_wider(id_cols = "AirBags",
names_from = Origin,
values_from = number)
Wide_data is showing up as NULL in my RStudio's environment and hence pivot_longer is also throwing up errors. Please let me know what to do in this instance.
The prop table done with DPLYR didn’t give percentages.
can u help summaries data from experiment such as CV% Significant data or not sig and how to table them
You can try mine too. The channel has both Python and R playlist for fundamentals. And source files downloadable.
Thanks
pivot not the issue, but lingering around number = n(). .. Thank you -
Hello, where is the 'analyze' tutorial? I do not see just one video. I do see the playlist for regressions, I want to assume these are the videos for 'analyze'.
New video 😍
😀😀😀
16:29
Rather than that you can simply do Cars93 %>% count(Origin,AirBags)...
Thanks !!! :)
Hello Sir, sir can you please suggest a good youtube channel from where i can learn Python
Can you please help me i am trying to run this code but it shows error
dstats
msleep %>%
drop_na(vore)%>%
group_by(vore)%>%
summarise(Lower = min(sleep_total),
Average = mean(sleep_total),
Upper = max (sleep_total),
Difference =
max(sleep_total)- min(sleep_total),
arrange(Average)%>%View() arrange(Average)%>%View()
Error in View : object 'Average' not found
i get this error too
There is a close parenthese and a pip operator missing befor arrange
@@drsam7655 thank you
Why is it zoomed in too much!
You really make the best R-videos. Always feel motivated to work with R after watching this. Thank you very much!
Thank you for the feedback. Glad you enjoyed it!