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Beiträge, die mit rStats getaggt sind


📊 Curious about how to handle empty lists in R? My latest blog post covers essential techniques and tips for efficient data management.

Check it out at https://www.spsanderson.com/steveondata/posts/2025-01-13/ and share your insights in the comments!

#R #RStats #Programming #Data #Tech #Blog
A code snippet in R programming language displayed on a dark-themed editor. The code demonstrates creating a mixed-type list using the list() function. The list contains three elements: the number 1, the string "text", and the logical value TRUE. The output shows the list elements indexed as [[1]], [[2]], and [[3]], with their respective values displayed below each index.


📝 In today's article, I explored how to create empty lists in R! Discover the basics and best practices to enhance your data manipulation skills.

Check it out at https://www.spsanderson.com/steveondata/posts/2025-01-13/! Your thoughts matter, so feel free to comment!

#R #RStats #Programming #Data #Code #Blog
A code snippet in R programming language displayed on a dark-themed editor. The code demonstrates creating a mixed-type list using the list() function. The list contains three elements: the number 1, the string "text", and the logical value TRUE. The output shows the list elements indexed as [[1]], [[2]], and [[3]], with their respective values displayed below each index.


📊 Struggling with matrix creation in R? You're not alone! In my latest post, I break down the steps to create empty matrices and avoid common pitfalls.

Dive in at https://www.spsanderson.com/steveondata/posts/2025-01-09/ and let me know your experiences!

#R #RStats #Programming #Learn #Code #RProgramming #Blog #Matrix #Matricies #Array
Code snippet showing how to create empty matrices in R. The first example creates a 3x4 matrix using matrix(NA, nrow = 3, ncol = 4). The second example creates a 2x2 matrix using matrix(NA, 2, 2). Both matrices are printed afterward.
A surreal, green-tinted cityscape inspired by "The Matrix." A large glowing green "R" dominates the background, surrounded by falling binary code. In the foreground, a figure in a black trench coat and sunglasses, resembling Neo, stands on a high ledge overlooking the city. The scene is atmospheric, blending digital and physical elements seamlessly.


🚀 In today's article, I explore how to create empty matrices in R! 🖥️ If you're looking to streamline your data analysis, this guide is for you.

Check it out at https://www.spsanderson.com/steveondata/posts/2025-01-09/ and share your thoughts!

Let's tackle those matrix challenges together!

#R #RStats #Programming #Data #Stats #RProgramming #Blog #Matrix #Matrices #Array
Code snippet showing how to create empty matrices in R. The first example creates a 3x4 matrix using matrix(NA, nrow = 3, ncol = 4). The second example creates a 2x2 matrix using matrix(NA, 2, 2). Both matrices are printed afterward.
A surreal, green-tinted cityscape inspired by "The Matrix." A large glowing green "R" dominates the background, surrounded by falling binary code. In the foreground, a figure in a black trench coat and sunglasses, resembling Neo, stands on a high ledge overlooking the city. The scene is atmospheric, blending digital and physical elements seamlessly.


🔢 Tired of messy decimals in your data? Learn how to master R's rounding functions like round(), signif(), ceiling(), and more! This guide is packed with examples to clean up your data and improve precision.

Check it out here: https://www.spsanderson.com/steveondata/posts/2024-12-31/ 💡

#R #RStats #Programming #Data #Tips #Blog
A code snippet in a dark-themed editor demonstrates various R functions for rounding numbers. The functions listed include `round()`, `signif()`, `ceiling()`, `floor()`, and `trunc()`, each with a comment explaining its purpose. Below the list, an example shows the creation of a vector `prices` with values 19.99, 24.49, and 5.75, and the use of the `round()` function to round the vector to 2 decimal places.


🧹 Struggling with messy datasets?

Learn how to clean them up with R's complete.cases()! This guide shows you how to handle missing data effectively with clear examples and tips. 🖥️💡

👉 https://www.spsanderson.com/steveondata/posts/2024-12-19/

#R #RStats #Programming #Data #Tips #RProgramming #blog
A code snippet in R creating a vector `x` with missing values (`NA`) and using `complete.cases(x)` to check which elements are non-missing, outputting `TRUE TRUE FALSE TRUE TRUE FALSE`.


Missing data slowing you down?

😱 Discover how R's complete.cases() can help you filter out incomplete rows and keep your analysis on track. Includes practical examples you can try today! 🧼✨

👉 https://www.spsanderson.com/steveondata/posts/2024-12-19/

#R #RStats #Programming #Clean #Data #Blog #BaseR #RProgramming
A code snippet in R creating a vector `x` with missing values (`NA`) and using `complete.cases(x)` to check which elements are non-missing, outputting `TRUE TRUE FALSE TRUE TRUE FALSE`.


📊 Tired of NA values messing up your calculations? Master the na.rm parameter in R to clean your data and get meaningful insights. This guide is packed with examples and tips for handling missing data. Check it out and comment with your favorite R tricks!

👉 https://www.spsanderson.com/steveondata/posts/2024-12-17/

#R #RStats #Programming #DataViz #Code #Blog
Alt text: "A code editor window showing R programming examples of na.rm usage. The code demonstrates vector operations with and without na.rm=TRUE, including sum() and mean() functions. The window has the classic macOS-style red, yellow, and green buttons at the top. The code is syntax-highlighted with comments in grey-green, functions in light blue, and values in red, making it easily readable against the dark background."


🧹 Missing values in your R data? Learn how to handle them with na.rm! This guide shows you how to clean your data and get accurate results with practical examples for vectors and data frames. Try it out and share your thoughts!

👉 https://www.spsanderson.com/steveondata/posts/2024-12-17/

#R #RStats #Programming #Data #Tips #Blog
Alt text: "A code editor window showing R programming examples of na.rm usage. The code demonstrates vector operations with and without na.rm=TRUE, including sum() and mean() functions. The window has the classic macOS-style red, yellow, and green buttons at the top. The code is syntax-highlighted with comments in grey-green, functions in light blue, and values in red, making it easily readable against the dark background."


🖥️ New to Linux? Learn how to manage your storage devices like a pro! From mounting USB drives to creating file systems, this beginner-friendly guide has you covered. Start your Linux journey today! 🚀

👉 Read here: https://www.spsanderson.com/steveondata/posts/2024-12-13/

#R #RStats #Programming #Linux #TechTips #Blog
"Terminal screenshot showing the output of the lsblk command in Linux, listing block devices and their details such as name, size, type, and mount points. Multiple devices, including loop devices, partitions, and mounted drives, are displayed."
"Stylized terminal window displaying Linux commands for managing storage devices. Commands include mounting and unmounting a USB drive (mount and umount), checking file system integrity (fsck), forcing a file system check on reboot (touch /forcefsck), and creating file systems in ext4 and FAT32 formats (mkfs)."


✨ Master the art of switch statements in C!

This guide covers:
✅ Syntax & structure
✅ Best practices
✅ Common mistakes to avoid
✅ Real-world examples Perfect for beginner C programmers! 🖥️

Take a look and share your thoughts: https://www.spsanderson.com/steveondata/posts/2024-12-11/

#R #RStats #Programming #C #CodeTips #Blog #CProgramming 🚀
Stylized code snippet illustrating the structure of a switch statement in C. The code includes cases for constant1 and constant2, each with a break statement, and a default case for handling unmatched conditions. The design mimics a modern code editor with a dark theme and colored syntax highlighting.
Screenshot of a C program in a code editor demonstrating a switch statement. The program presents a menu with options to view balance, deposit money, withdraw money, or exit. The terminal output shows the user selecting option 3 (withdraw money) and the program displaying the balance as $1000.


🚀 New to C programming? Struggling with long if-else chains? 🤔

Switch statements are here to save the day! Learn how to simplify your code, avoid common mistakes, and write cleaner programs. 🛠️

Check out my beginner-friendly guide here: https://www.spsanderson.com/steveondata/posts/2024-12-11/

#R #RStats #Programming #C #Coding 💻#Blog
Screenshot of a C program in a code editor demonstrating a switch statement. The program presents a menu with options to view balance, deposit money, withdraw money, or exit. The terminal output shows the user selecting option 3 (withdraw money) and the program displaying the balance as $1000.
Stylized code snippet illustrating the structure of a switch statement in C. The code includes cases for constant1 and constant2, each with a break statement, and a default case for handling unmatched conditions. The design mimics a modern code editor with a dark theme and colored syntax highlighting.


💡 Did you know you can use slice_max() in dplyr to find rows with max values in R? Or stick with trusty which.max() in base R? Learn these and more in my latest guide! 🖥️
📚

Dive in here: https://www.spsanderson.com/steveondata/posts/2024-12-10/

#R #RStats #Programming #Data #LearnR #Blog
Code snippet in a dark-themed editor demonstrating how to use the which.max() function in R to select the row with the maximum value. The example creates a data frame with columns ID and Value, and identifies the row where the Value column is at its maximum.


📊 Struggling to find the row with the max value in R? My new post has you covered! Learn 3 methods: which.max(), base R subsetting, and slice_max() from dplyr. Perfect for R programmers of all levels! 🖋️✨

Read & comment here: https://www.spsanderson.com/steveondata/posts/2024-12-10/

#R #RStats #Programming #DataScience #Tips #Blog
Code snippet in a dark-themed editor demonstrating how to use the which.max() function in R to select the row with the maximum value. The example creates a data frame with columns ID and Value, and identifies the row where the Value column is at its maximum.


🔢 Struggling to identify the column with the highest value in your R data frame? This guide has you covered with step-by-step examples using max.col(), apply(), and more!

💡 Start coding smarter today: https://www.spsanderson.com/steveondata/posts/2024-12-09/

#R #RStats #Programming #DataScience #Code #Blog
A code snippet displayed in a dark-themed code editor. The R code assigns column names corresponding to the maximum values in each row of a data frame (df) to a variable max_col_names using colnames(df)[max_col], and prints the result using print(max_col_names). The editor has visual indicators for close, minimize, and maximize buttons.


🚀 Want to find the column with the max value for each row in R? Learn how to do it using base R, dplyr, and data.table! 🛠️ Perfect for R programmers looking to streamline their data analysis.

Check it out here: https://www.spsanderson.com/steveondata/posts/2024-12-09/

#R #RStats #Programming #Data #Tips #Blog
A code snippet displayed in a dark-themed code editor. The R code assigns column names corresponding to the maximum values in each row of a data frame (df) to a variable max_col_names using colnames(df)[max_col], and prints the result using print(max_col_names). The editor has visual indicators for close, minimize, and maximize buttons.


🤖 Ready to simplify machine learning in R? Meet {healthyR.ai}! This package is your go-to for exploring, transforming, and modeling data with ease. Perfect for R programmers looking to streamline workflows in healthcare and beyond.

Learn more: https://www.spsanderson.com/steveondata/posts/2024-06-24/index.html

#R #RStats #Programming #AI #ML #Blog 📈


📊 Missing values slowing you down? Learn how to find columns with all NA values in base R using efficient techniques like is.na() and apply(). Code examples included! 💡

👉 Read the full guide: https://www.spsanderson.com/steveondata/posts/2024-12-05/

#R #RStats #Programming #DataAnalysis #NAvalues #Blog #RProgramming #Data
ALT text: A screenshot of R code in a dark-themed editor. The code demonstrates how to create a sample data frame with four columns: "A" with numbers 1 to 5, "B" and "D" with all `NA` values, and "C" with letters "a" to "e". Below, the code identifies columns with all missing values using `colSums(is.na())` and stores the result in the variable `all_na_cols`, which is then printed. The code highlights R functions and syntax in different colors.


Missing values giving you a headache? 😩 Whether it’s replacing with the mean, median, or zeros, this guide will boost your R skills! 📊 Learn how to clean up your data like a pro and make your analysis shine. ✨
📖

Dive in here: https://www.spsanderson.com/steveondata/posts/2024-12-02/

#R #RStats #Programming #DataScience #Coding #Blog #RProgramming
A code snippet displayed in a dark-themed editor window shows how to replace missing values (NA) in a vector in R. The code defines a vector v with values c(10, NA, 20, 30, NA, 50). It calculates the mean of the non-missing values using mean(v, na.rm = TRUE) and assigns it to mean_v. Then, it replaces the NA values in v with mean_v. The updated vector v is printed at the end. The editor window features a gray background with red, yellow, and green buttons in the top-left corner.


Struggling with missing values in R? 🤔 NAs can mess up your analysis, but don’t worry! Learn easy and effective ways to replace them in your data. From basic replacements to advanced techniques, this guide has you covered. Check it out and share your thoughts! 💡
📖

Read more: https://www.spsanderson.com/steveondata/posts/2024-12-02/

#R #RStats #Programming #Data #Tips #Blog #RProgramming
A code snippet displayed in a dark-themed editor window shows how to replace missing values (NA) in a vector in R. The code defines a vector v with values c(10, NA, 20, 30, NA, 50). It calculates the mean of the non-missing values using mean(v, na.rm = TRUE) and assigns it to mean_v. Then, it replaces the NA values in v with mean_v. The updated vector v is printed at the end. The editor window features a gray background with red, yellow, and green buttons in the top-left corner.


Highly recommended job opening for a data journalist at Deutsche Welle https://jobs.dw.com/Vacancies/2227/Description/2
Small but growing team, great for #rstats folks.
Among data-analysis related professions, I feel #DataJournalism is really a great option. Also for journalists, I feel #DataJournalism is really a great option.

Check out some of their work: https://dw.com/data


🚀 Simplify your R programming workflow by mastering column deletion! Our latest guide covers multiple methods to remove columns from data frames. Perfect for data cleaning and manipulation.

Explore the full article here: https://www.spsanderson.com/steveondata/posts/2024-11-26/

#R #RStats #Programming #DataScience #Learn #Blog #select #subset #RProgramming #Coding #CodingTips
 A screenshot of R code demonstrating how to create a data frame and delete specific columns. The code creates a data frame with columns A, B, C, and D, and then uses the subset() function to remove columns B and D.


🛠️ Need to clean up your data frames in R? Check out our step-by-step guide on deleting multiple columns efficiently! Learn how to use subset(), select(), and more. Dive in and streamline your data manipulation process!

Read more: https://www.spsanderson.com/steveondata/posts/2024-11-26/

#R #RStats #Programming #Data #Tips #Blog #subset #select
 A screenshot of R code demonstrating how to create a data frame and delete specific columns. The code creates a data frame with columns A, B, C, and D, and then uses the subset() function to remove columns B and D.


🛠️ Master string comparison in R with practical examples and bonus tips! Whether you're dealing with case sensitivity or vector comparisons, this guide has you covered.

Read more and comment your experiences! https://www.spsanderson.com/steveondata/posts/2024-11-25/

#R #RStats #Programming #Code #Learn #Blog #RProgramming #strings #stringr #stringi
A screenshot of R code comparing two strings, "Hello" and "hello", using a case-insensitive comparison. The code converts both strings to lowercase with tolower() and checks if they are equal. If they are, it prints "The strings are equal (case-insensitive)." Otherwise, it prints "The strings are not equal." The code is displayed in a dark-themed code editor.


🚀 Dive into the world of administrative data with {healthyR.data}! Discover how this powerful tool can streamline your data exploration and testing processes. Perfect for R programmers and healthcare analysts!

Read more and share your thoughts: https://www.spsanderson.com/steveondata/posts/2024-07-01/index.html

#R #RStats #Programming #Data #Health #Blog #RProgramming


🚀 Dive into the world of administrative data with {healthyR.data}! Discover how this powerful tool can streamline your data exploration and testing processes. Perfect for R programmers and healthcare analysts!

Read more and share your thoughts: https://www.spsanderson.com/steveondata/posts/2024-07-01/index.html

#R #RStats #Programming #Data #Health #Blog #RProgramming


🛠️ Master the art of column comparison in R with practical examples and tips! Perfect for data analysis and ensuring data integrity. Read the full guide and let us know how it helps your projects! 📈💡

#R #RStats #Programming #DataScience #Tips #RProgramming #blog

https://www.spsanderson.com/steveondata/posts/2024-11-21/
Screenshot of R code comparing two columns in a data frame. The code creates a data frame with columns col1 and col2, then checks for equality using the == operator. The output shows a logical vector: TRUE, TRUE, FALSE, TRUE, FALSE.
Watercolor illustration of two construction workers in hard hats and reflective vests examining two large, rusted steel letters "R" at a construction site. The background features cranes and steel beams under a hazy sky.


🚀 Dive into the world of R programming with our latest guide on comparing two columns! Whether you're checking for matches or differences, this comprehensive tutorial has you covered. Check it out and share your thoughts! 📊🔍

#R #RStats #Programming #Data #Code #RProgramming #Blog

https://www.spsanderson.com/steveondata/posts/2024-11-21/
Screenshot of R code comparing two columns in a data frame. The code creates a data frame with columns col1 and col2, then checks for equality using the == operator. The output shows a logical vector: TRUE, TRUE, FALSE, TRUE, FALSE.
Watercolor illustration of two construction workers in hard hats and reflective vests examining two large, rusted steel letters "R" at a construction site. The background features cranes and steel beams under a hazy sky.


🏥 Unlock the potential of administrative data using {healthyR.data}. Whether you're testing functions or downloading CMS data, this package has you covered.

Explore the details at https://www.spsanderson.com/steveondata/posts/2024-07-01/ and join the conversation!

#R #RStats #Programming #Data #Healthcare #blog #Health #CMS


💡 Discover the art of vector combination in R! Our detailed guide at https://www.spsanderson.com/steveondata/posts/2024-11-19/ covers everything from basic to advanced techniques.

Experiment with these methods and share your insights in the comments!

#R #RStats #Programming #Innovation #Explore #RProgramming #vector #DataFrames #blog


📊 Want to make your R data manipulation more efficient? Discover 4 essential subsetting techniques in our new post!

Visit https://www.spsanderson.com/steveondata/posts/2024-11-12/ and share your thoughts in the comments!

#R #RStats #Programming #Data #Learn #Blog #dplyr #datatable



🚀 Dive into the world of R with our latest guide on subsetting data frames! Learn 4 practical methods to streamline your data analysis.

Check it out at https://www.spsanderson.com/steveondata/posts/2024-11-12/ and let us know your favorite method!

#R #RStats #Programming #Data #Tips #dplyr #datatable #Blog



📊 Unlock the power of the $ operator in R! Perfect for beginners, this guide shows you how to access list elements and data frame columns effortlessly.

Dive in now: https://www.spsanderson.com/steveondata/posts/2024-11-06/

#R #RStats #Programming #DataScience #Code #RProgramming #blog



🚀 New to R? Discover how the setdiff() function can simplify your data analysis! Check out my guide for easy-to-follow examples and best practices. Dive in and start coding today! 📊🔍

Read more: https://www.spsanderson.com/steveondata/posts/2024-11-05/

#R #RStats #Programming #Data #LearnR #RProgramming #setdiff #blog



🛠️ New to R programming? Discover how the NOT IN operator can simplify your data filtering tasks.

My guide breaks it down with easy-to-follow examples.

Read and comment! 📈🔗 https://www.spsanderson.com/steveondata/posts/2024-11-04/

#R #RStats #Programming #Learn #Tips #RProgramming #blog



Every year we run a "graph crimes" lecture for my data analysis class - so #rstats people - what are the most egregious crimes you have seen committed this year? #graphcrimes
A pictograph for average female height per country. Each bar has been replaced by the female icon -  with a truncated y axis starting at 5' 0" it makes it appear as though an Indian woman stands at knee height compared to the average Latvian woman