Learn efficient ways to collapse text by group in R! Explore base R's aggregate(), dplyr's group_by() and summarise(), and data.table's grouping. Mastering these techniques enhances data preprocessing skills. Try these examples with your datasets to optimize workflows. Happy coding! 📊💻
👍 In R, you can easily extract specific columns from a data frame by their numerical positions. For instance, to grab the second column from a data frame df, you can use df[, 2].
🙅♂️ You can also exclude columns by using negative indexing, such as df[, -2] to exclude the second column.
#KDE will mentor ten projects in Google Summer of Code (#GSoC) this year, including two projects for #LabPlot, a FREE, open source and cross-platform #DataVisualization and #DataAnalysis software.
The plotting, statistical, and data selection tools in the mapdata.py data explorer (https://pypi.org/project/mapdata/) can be used even if you don't have any map data. Just add dummy latitude and longitude values to the data table. Zeroes will do. The map and the dummy columns can both be hidden, and you can then explore the data table with the other available tools.
We dive deep into simplifying outlier detection in R using #easystats to follow good practices and make your data analysis more robust and replicable. Check it out! #Rstats#DataAnalysis@rstats
As data analysts, we know that no model is perfect. Residuals, the differences between observed and predicted values, offer valuable insights into the strengths and weaknesses of our models. Introducing the plot_regression_residuals() function from the tidyAML R package - a game-changer for visualizing regression residuals.
Feeling stuck with Excel for data analysis? You're not alone! Excel is fantastic, but for truly powerful insights and visualizations, it can fall short.
Here's what you'll gain:
🧐 * Advanced data manipulation & cleaning
💻 * Powerful statistical analysis & modeling
📉 * Eye-catching data visualizations
🌟 * Seamless integration back to Excel
If you work with spectra or multivariate regression and don't want to reinvent the wheel, check it out. If it doesn't do what you need it to do, let me know and we can add capabilities to make it work for you! #python#spectroscopy#lpsc2024#data#OpenSource#DataAnalysis#ML
🚀 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
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 Mastodon Recent Posts Data Collector retrieves recent public posts and replies from a specified public Mastodon server.
The Mastodon Hashtag Search Data Collector retrieves recent public posts and replies with a specified hashtag from any public Mastodon server.
Users of Communalytic EDU can retrieve up to 5,000 recent posts and replies from Mastodon, while Communalytic PRO users can retrieve up to 50,000. Communalytic users can start collecting data immediately without first having to create a Mastodon account or apply for a separate Mastodon API key.
These new data collectors will provide Communalytic users with a systematic way to collect publicly available Mastodon data for academic research and are being released as part of our work developing research tools, techniques, and visualization dashboards to support computational social science.
For more details, see Communalytic’s Tutorials page."
'The return of the ancestral human remains of Australian and other Indigenous peoples held in anthropological collections could be sped up using machine-based deep learning according to a new study led by QUT computer scientists.'
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!
Unlock Excel's potential with "Extending Excel with Python and R"! Seamlessly integrate Python and R for advanced data analysis, visualization, and automation. Import/export data, automate tasks, execute VBA macros, perform statistical analysis, create ggplot2/matplotlib graphs, and call functions directly from VBA. Whether beginner or expert, this book elevates Excel skills. Pre-order! Amazon: https://www.amazon.com/dp/1804610690/ref=tsm_1_fb_lk
Time-traveling in R Skip ahead (or rewind!) days with ease using lubridate & timetk. Add weeks, months, or even years! Master dates, analyze time series, and share your tricks! Let's conquer time together! #RStats#dataanalysis
FreeCodeCamp released a new course for data analysis with Python 🐍using astronomical data. The course covers the foundations of data analysis, focusing on the following:
✅ Python core commands
✅ Functions
✅ Working with tabular data
✅ Data visualization