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#package — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #package, aggregated by home.social.

  1. I just uploaded version 0.4.1-5 (amd64) of #Debian #package pkcs11-proxy (proxy for the PKCS11-library; bugfix) to #unstable

  2. I just uploaded version 0.4.1-5 (amd64) of #Debian #package pkcs11-proxy (proxy for the PKCS11-library; bugfix) to #unstable

  3. Ceuta residents call for calm as Spain rallies over enclave’s migrant crisis byteseu.com/2330061/ #AFR #CIV #CWP #DEST:AFA #DEST:CSA #DEST:G #DEST:GNS #DEST:LBY #DEST:OUKTPM #DEST:OUSWDM #DEST:PGE #DEST:PSC #DEST:RAST #DEST:RBN #DEST:REULB #DEST:RNP #DEST:RWS #DEST:RWSA #DEST:UCDPTEST #DLI #EMEA #EMRG #ES #eu #EUROP #EZC #GEN #GreatBritain #HRGT #IMM #INTAG #m&a #MPOP #MTPIX #NAFR #NEWS1 #PACKAGE:WORLDNEWS #POL #RACR #RSBI:HUMANRIGHTS #RULES:IMMIGRATION #SOCI #UnitedKingdom #VIO #WEU

  4. seeing people think you cant install software on an immutable distro still :eyeroll:

  5. At first glance, bar charts might seem like a simple visualization type. But with a little creativity, they can be enhanced in countless ways to reveal deeper insights and make your data shine.

    The attached visual highlights a variety of bar chart styles to inspire your work.

    Take a look here for more details: statisticsglobe.com/online-cou

    #datastructure #data #tidyverse #rstats #package #datasciencetraining

  6. ‘It’s been a long time’: Senate Republicans through Ram Trump’s Clawback package, NPR star-news.press/wp

    ,'It's been a long time': Senate Republicans through Ram Trump's Clawback package, NPR star-news.press/wp, 2025-07-17 06:31:00 #long #time #Senate #Republicans #Ram #Trumps #Clawback #package #NPR

    star-news.press/long-overdue-s

  7. ‘It’s been a long time’: Senate Republicans through Ram Trump’s Clawback package, NPR star-news.press/wp

    ,'It's been a long time': Senate Republicans through Ram Trump's Clawback package, NPR star-news.press/wp, 2025-07-17 06:31:00 #long #time #Senate #Republicans #Ram #Trumps #Clawback #package #NPR

    star-news.press/long-overdue-s

  8. ‘It’s been a long time’: Senate Republicans through Ram Trump’s Clawback package, NPR star-news.press/wp

    ,'It's been a long time': Senate Republicans through Ram Trump's Clawback package, NPR star-news.press/wp, 2025-07-17 06:31:00 #long #time #Senate #Republicans #Ram #Trumps #Clawback #package #NPR

    star-news.press/long-overdue-s

  9. ‘It’s been a long time’: Senate Republicans through Ram Trump’s Clawback package, NPR star-news.press/wp

    ,'It's been a long time': Senate Republicans through Ram Trump's Clawback package, NPR star-news.press/wp, 2025-07-17 06:31:00 #long #time #Senate #Republicans #Ram #Trumps #Clawback #package #NPR

    star-news.press/long-overdue-s

  10. Using dplyr and ggplot2 in R can significantly streamline your data analysis process, making it easier to work with complex data sets.

    I have created a video tutorial in collaboration with Albert Rapp, where I demonstrate how to do this in practice: youtube.com/watch?v=EKISB0gnue4

    #coding #datavisualization #rprogramming #dataviz #statisticalanalysis #package #datastructure #ggplot2 #bigdata #tidyverse

  11. I recently discovered the tidyplots package in R, and it’s impressive how effortlessly it enables you to create beautiful, publication-ready plots.

    The example visualizations shown here were created by the package author, Jan Broder Engler, and are featured on the tidyplots website: jbengler.github.io/tidyplots/

    Click this link for detailed information: statisticsglobe.com/online-cou

    #statisticsclass #datavisualization #advancedanalytics #rprogramminglanguage #visualanalytics #package #tidyverse

  12. If you're a Stata user, you should switch to R now!

    Thinking about switching to R? Check out my online course for absolute beginners in R programming.

    Click this link for detailed information: statisticsglobe.com/online-cou

    #advancedanalytics #data #package #datasciencecourse #statisticsclass #rprogramminglanguage

  13. Basic boxplots are often not the best way to visualize your data! They can hide important information, such as the distribution of individual data points or group-specific differences.

    The attached visual showcases several ways to enhance boxplots.

    All of these examples were created using ggplot2 and extensions in R.

    Click this link for detailed information: statisticsglobe.com/online-cou

    #statisticsclass #datavisualization #advancedanalytics #rprogramminglanguage #visualanalytics #package

  14. ggplot2 is the gold standard when it comes to data visualization.

    The image in this post showcases examples of ggplot2 visualizations, demonstrating its versatility to create a wide range of plots with nearly limitless customization options.

    Check out my online course, "Data Visualization in R Using ggplot2 & Friends," for a deeper dive into creating stunning plots with ggplot2.

    More info: statisticsglobe.com/online-cou

    #package #dataviz #statistical #tidyverse #pythondeveloperjobs

  15. When performing multiple imputation of missing data, it is essential to evaluate how the imputed values compare to the observed data.

    The attached image, created with the bwplot() function, showcases how the distributions of observed and imputed values vary across different imputations for multiple variables.

    I’ll be hosting an 8-week online workshop on Missing Data Imputation in R: statisticsglobe.com/online-wor

    #dataanalytics #dataviz #statistical #database #datavisualization #package

  16. To people/projects/organizations/companies promoting their software/frameworks/tools to software developers...

    If your website shows virtually nothing about how your package works, but has a "Learn more" button, and clicking that "Learn more" button triggers a popup video rather than a page describing what your thing actually does, you've already lost about 93% of the initiative.

    So don't do that.

    Thank you for attending my TED talk.

    #software #package #promotion #tutorial #demo #website #DontDoThat #video #text #TextNotVideo #developer

  17. Dimensionality reduction simplifies high-dimensional data while retaining its essential features. It’s a powerful tool for improving data analysis, visualization, and machine learning performance.

    Image credit to Wikipedia: en.wikipedia.org/wiki/Dimensio

    I've developed an in-depth course on PCA theory and its application in R programming. Check out this link for more details: statisticsglobe.com/online-cou

    #rstudio #datastructure #programming #package #statistical #bigdata

  18. Creating publication-ready plots in R is easier than ever with ggpubr. This extension for ggplot2 simplifies the process of generating clean and professional graphics, especially for exploratory data analysis and reporting.

    Course link: statisticsglobe.com/online-cou

    #dataanalytics #rstats #dataanalytic #datavisualization #package #datasciencetraining #visualanalytics #datastructure #tidyverse #ggplot2

  19. On October 7, 20204, exactly the same day Python 3.13 was released, the package for Ubuntu 24.10 (which will be released today) was already available ⚡

    packages.ubuntu.com/oracular/p

    Kudos to the maintainers for the great job of packaging Python for Debian and Ubuntu 👏

  20. Hey, I've created a video tutorial on how to add a normal density curve on top of a histogram using the ggplot2 package in the R programming language: m.youtube.com/watch?v=drkqpbER

    #Package #statisticians

  21. Hey, I've created a tutorial on how to calculate multiple summary statistics using the R programming language. The tutorial shows examples for Base R & the dplyr package: statisticsglobe.com/calculate-

    #datasciencetraining #statisticians #Package #tidyverse

  22. Hey, I've published an extensive video introduction on data visualization using the ggplot2 package in the R programming language. The tutorial explains the basics & demonstrates advanced examples: m.youtube.com/watch?v=Cl9yE_PF

    #Package #RStudio #tidyverse #statisticians #ggplot2 #DataAnalytics