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 November 2020.

Organizations want Data Science, Cloud, and Apps. Here's how Docker plays a part in the essential skills of 2021.

Solar power is a form of renewable clean energy that is created when photons from the sun excite elections in a photovoltaic panel, generating electricity. The power generated is usually tracked via sensor with measurements happening on a time based cadence.

Demand Forecasting is a technique for estimation of probable demand for a product or services. It is based on the analysis of past demand for that product or service in the present market condition.

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.