stevensanderson, to programming
@stevensanderson@mstdn.social avatar
stevensanderson, to random
@stevensanderson@mstdn.social avatar

Exciting news! 🚀 TidyDensity version 1.4.0 is here.

  • Quantile normalization to handle skewed data distributions
  • Duplicate row detection for improved data quality
  • Chi-square distribution parameter estimation made easy
  • Markov Chain Monte Carlo (MCMC) sampling for advanced analysis
  • AIC calculations for model selection

#DataAnalysis #RStats #TidyDensity R #RProgramming #Probability #tidy #tidyverse

I will do tutorials of new functionality during the week.

Post: https://www.spsanderson.com/steveondata/posts/2024-04-29/

stevensanderson, to datascience
@stevensanderson@mstdn.social avatar

Discover efficient string splitting in R using strsplit()!

Learn practical examples and unleash the power of regular expressions.

Enhance your data cleaning skills and level up your R programming.

Experiment with strsplit() today!

Post: https://www.spsanderson.com/steveondata/posts/2024-04-26/

#R

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stevensanderson, to programming
@stevensanderson@mstdn.social avatar

My #R has been submitted to CRAN for version 1.4.0

Lots of good stuff in this one!

#R

https://github.com/spsanderson/TidyDensity/blob/master/NEWS.md

jumpingrivers, to datascience
@jumpingrivers@fosstodon.org avatar

📣 Exciting news, everyone! 🌟 Make sure to head over to this weeks blog "What's new in R 4.4.0?" by Russ Hyde, and dive into the world of the latest R release📊🔬💻

Discover some of the amazing new features that this version has to offer! 🔍 🔭 🚀


https://www.jumpingrivers.com/blog/whats-new-r44/

stevensanderson, to random
@stevensanderson@mstdn.social avatar

Master data manipulation in R by dropping unnecessary columns from data frames using simple methods like the $ operator, subset() function, and dplyr package's select() function.

Try these techniques on your own datasets for efficient data cleaning and analysis!

Post: https://www.spsanderson.com/steveondata/posts/2024-04-25/

#R

stevensanderson, to programming
@stevensanderson@mstdn.social avatar
stevensanderson, to random
@stevensanderson@mstdn.social avatar

Today's topic is: Identifying Common Rows Between Data Frames in R

In data analysis, comparing datasets is crucial. A common task is checking if rows from one data frame exist in another. I have had to do this myself many times.

Today I discuss the following:

1️⃣ The merge() Function

2️⃣ The %in% Operator

For a step-by-step guide and examples, check out the full blog post.

Link: https://lnkd.in/eDRvYr6C

#R

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stevensanderson, to programming
@stevensanderson@mstdn.social avatar

🔍 How to Extract Last Row in Data Frame in R

Base R
Use nrow(my_df) to get the total rows.
Extract the last row with indexing: my_df[nrow(my_df), ].

dplyr
Use tail(my_df, 1) to get the last row.

data.table
Convert to data.table: my_dt <- as.data.table(my_df).
Get last row using .N: my_dt[.N].

Now you know three ways to extract the last row. Try it yourself! 📊

#RProgramming #DataFrames #CodingTips #R #RStats #Programming #Coding #Data #datatable #dplyr #baseR

Post: https://www.spsanderson.com/steveondata/posts/2024-04-18/

stevensanderson, to programming
@stevensanderson@mstdn.social avatar

I had previously discussed how to drop those pesky NA records from your data.frame but now, what if you actually want to inspect them? That is what I cover in today's post.

Post: https://www.spsanderson.com/steveondata/posts/2024-04-17/

#R

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stevensanderson, to programming
@stevensanderson@mstdn.social avatar

Need to Find Rows with a Specific Value (Anywhere!) in R?

Ever have a large R data table where you need rows containing a specific value, but you're not sure which column it's in? We've all been there! Here's a quick guide to tackle this using both dplyr and base R functionalities.

🌟 The dplyr Way: Streamlined Selection

🌟 Base R to the Rescue: Manual Looping

#R

Post: https://www.spsanderson.com/steveondata/posts/2024-04-16/

stevensanderson, (edited ) to programming
@stevensanderson@mstdn.social avatar

Estimating the degrees of freedom 'k' and the non-centrality 'ncp' parameters of the chi-square distribution from just a vector of numbers? I think I am there. Here is a post the work I did over the last couple of days:

Post: https://www.spsanderson.com/steveondata/posts/2024-04-15/

#R

stevensanderson, to github
@stevensanderson@mstdn.social avatar
stevensanderson,
@stevensanderson@mstdn.social avatar

@ramikrispin I think this is it. The Mega Test Scrip creates 1000 different combinations of the rchisq() data and runs it all using different approachs

https://github.com/spsanderson/TidyDensity/issues/414#issuecomment-2053657200

#R

stevensanderson, to RegEx
@stevensanderson@mstdn.social avatar

I decided to make a blog post out of a problem I worked on a day or two ago and thankfully I was also pointed to another solution from @embiggenData which worked well too.

#R

Post: https://www.spsanderson.com/steveondata/posts/2024-04-12/

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stevensanderson, to datascience
@stevensanderson@mstdn.social avatar

Today's post is the complement of yesterdays, instead of filtering out rows, let's get the ones we want :)

#R

Post: https://www.spsanderson.com/steveondata/posts/2024-04-11/

jumpingrivers, to datascience
@jumpingrivers@fosstodon.org avatar

📣 We are pleased sponsors of 26th April #R Dev Day at Imperial College #LDN. 📊🔬🚀

This 🆓 satellite event to our #SatRdays conference(27th), is a platform to learn about contributing & opportunity to collaborate in base R.👨‍💻 👩‍💻

🥳🥳 Registered participants receive a 💫 40% SatRdays DISCOUNT CODE🎊🎉 on the 27th.🎡 🇬🇧

Don't miss out! Get Your Tickets 🎟️ & 40% Discount Now⬇️

#RStats #datascience #ai #machinelearning #programming #rprogramming #londonevent #python
https://www.meetup.com/r-contributors/events/299810000/

stevensanderson, to datascience
@stevensanderson@mstdn.social avatar

Looking to do some data filtering in base R? Well then of course I have a post for you! Many times people in a corporate environment are strapped from installing packages or it is cumbersome to get it done, this is why I like to focus on base R solutions.

#R #RStats #RProgramming #Coding #DataScience #Data #DataScientist #Programming

Post: https://www.spsanderson.com/steveondata/posts/2024-04-10/

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stevensanderson, to datascience
@stevensanderson@mstdn.social avatar

Got NA's in your data? Well, if you want to get rid of them then this post is for you!

#R

Post: https://www.spsanderson.com/steveondata/posts/2024-04-09/

cascadiarconf, to rstats

🚨 🚨 There's only a few hours left to purchase your Early Bird Tickets to attend . Sales end tonight at 11:59 pm PT. Don't miss out!‼

Purchase your early bird tickets today: https://lnkd.in/eJC33jks

To learn more about the conference, visit: https://cascadiarconf.com/

@rstats #R

stevensanderson, to datascience
@stevensanderson@mstdn.social avatar

Need some practice on merging data in #R well then this post is for you. It is not an exhuastive post but hopefully you learn something :)

#R

Post:https://www.spsanderson.com/steveondata/posts/2024-04-05/

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stevensanderson, to datascience
@stevensanderson@mstdn.social avatar
stevensanderson, to random
@stevensanderson@mstdn.social avatar

Need to visualize and scale multi-dimensional data? Well sometimes we do and this post is for you!

Post: https://www.spsanderson.com/steveondata/posts/2024-04-04/

#R

stevensanderson, to datascience
@stevensanderson@mstdn.social avatar
stevensanderson, to datascience
@stevensanderson@mstdn.social avatar

Ever struggle with features in your data overshadowing others due to different scales? Normalization can be your hero!

In R, there are ways to transform your data for a more even playing field. This post explores two popular methods:

  1. Z-score normalization
  2. Min-max scaling

#R

Post: https://www.spsanderson.com/steveondata/posts/2024-04-02/

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