🚀 Exciting news for R enthusiasts! My latest blog post shares techniques to rename factor levels in R, making categorical data more meaningful. From levels() to plyr and forcats, learn step by step with easy examples. Let's spark a conversation and elevate our R skills together!
🚀 Elevate your data manipulation skills in R! Learn how to rename data frame columns with ease using base R functions like names(), colnames(), and setNames(). Clarity and consistency await – dive in and code like a pro! 💻 #RProgramming#DataScience#DataAnalysis#R#RStats#Coding
In base R, we can filter rows where a column is between two values using bracket notation or the subset() function along with logical operators like >=, <=, &, and !. The key is creating a logical test that checks if values are within our desired range.
For example, to filter rows where the column "value" is between 5 and 8
Learn how to set a data frame column as the index for faster data access and streamlined operations.
In R, utilize the setDT() function from #datatable or column_to_rownames() from #tibble to seamlessly set your desired column as the index. Try it out with your datasets and experience the boost in productivity!
The dcast function from R's data.table package provides a fast way to reshape data from long to wide format. It aggregates values like a pivot table in just one line. For example, to aggregate mtcars hp by cyl:
🚀 Explore data types in R with simple functions like typeof(), class(), and is.*(). Dive into coding adventures, unlock data's power, and discover endless possibilities! Try it out today! 💻📊
Level up your data wrangling! Learn how to add index columns in R – both base & tidyverse Choose your weapon & customize! Ready to try? Create your own data frame & experiment! Share your creations & challenges!
Wrangling dates in R got you pulling your hair? ⏱️ Time travel to mastery with these 3 powerful tools:
Base R's seq.Date: Your daily/weekly/monthly hero.
lubridate's seq: Filter magic for specific weekdays. Analyze those Tuesdays!
timetk's tk_make_timeseries: Define complex sequences in a simple table. Easy time travel!
Drowning in daily data? Conquer weekly analysis with R's strftime() magic! Extract ISO week numbers & group your data like a pro. Ready to level up? Explore "U" for Sunday starts & packages for more grouping power. Challenge: calc weekly averages, peak sales, etc. Share your data wrangling wins in the comments!
R data mystery: is that column a date? ️♀️ Fear not! Unleash lubridate's date magic & healthyR.ts' time series power to unmask them! 🪄 Explore formats, validate time series, conquer your data! Ready? Test these tools, share your finds! Happy coding, clear dates await!
Master date manipulation in R with two simple methods: 1) Use ifelse() to create an indicator column, and 2) Utilize subsetting to filter data based on date range. Essential for various data tasks. Try it out and enhance your R skills!
Unleash Excel date power in R! Convert formats to proper dates effortlessly. With as.Date() & convertToDateTime(), transform data for smoother analysis. Dive into R, empower your data journey! Try it yourself & elevate your analysis game!
🚀 Dive into the world of data exploration with R! 📊 Uncover the earliest date lurking within your dataset using the power of R. With just a few lines of code, you can conquer this challenge and gain valuable insights into your data.
🚀 Mastering time manipulation in R is crucial for data professionals, and today we're tackling a common task: subtracting hours from time objects! 💡
In this engaging post, we explored two powerful methods: using base R functions and the popular lubridate package. With base R, we can perform basic arithmetic operations on time objects, while lubridate simplifies complex date-time calculations.
🚀 Dive into the world of statistical magic with TidyDensity's bootstrap_stat_plot()! 📊✨ Uncover the nuances of your data using R with this powerful function. 🤓
Example 1 explores central tendency, visualizing bootstrapped means, mins, maxes, and standard deviations. Example 2 customizes the plot for a cleaner look. 💡
Dive into the latest tidyAML release! 🌟 The spotlight is on the new .drop_na parameter, enhancing the functionality of fast_classification() and fast_regression() functions.
🌟 Join Pfizer's exclusive webinar covering their journey from SAS to R with Natalia Andriychuk from Pfizer. Discover how they're shaping the future with community-driven development.