Making multiple ARIMA Time Series models in R used to be difficult. But, with the purrr nest() function and modeltime, forecasting has never been easier. Learn how to make many ARIMA models in this tutorial.
Group Split and Map are SECRET TOOLS in my data science arsenal. Combining them will help us scale up to 15 linear regression summaries to assess relationship strength and combine in a GT table.
In this post, we start out where we left off in 'Python and R - Part 1: Exploring Data with Datatable'. We load our cleaned big MT Cars data set in order visualize the data with Python plotnine.
Pivoting wider is essential for making summary tables that go into reports and help humans understand key information.
Each month, we release tons of great content on R for Business. These are the 5 Top Articles in R for Business over the past month. We have some great ones in October. Let's dive in.
The across() function was released in dplyr 1.0.0. It's a new tidyverse function that extends group_by and summarize for multiple column and function summaries.
Python’s datatable was launched by h2o two years ago and is still in alpha stage with cautions that it may still be unstable and features may be missing or incomplete. We found that it feels very similar to the R version...
relocate() is like arrange() for columns. It keeps all of the columns, but provides much more flexibility for reordering. Notice how all of the columns are returned.
Why create PDF's manually when you can automate PDFs with R? That's exactly what I show you how to do in this video showcasing parameterized Rmarkdown.
The biggest thing I missed when I transititioned from Excel to R was PIVOT TABLES! Seriously, Pivot Tables are so useful. You can summarize and reshape (aka Pivot) data so easily with them in Excel.
I'm super excited to introduce modeltime.ensemble, a new time series forecasting package designed to extend modeltime with ensemble methods like stacking, weighting, and averaging.