I'm super excited to introduce the new parallel processing functionality in modeltime. It's perfect for speeding up hyperparameter tuning of forecast models using parallel processing.
The siuba python library brings the power of R's dplyr and the tidyverse to Python. Gain access to functions like group_by(), mutate(), summarize(), and more!
Pandas Profiling is an awesome python package for Exploratory Data Analysis (EDA). It extends pandas for statistical summaries including correlations, missing values, distributions, and descriptive statistics. It's great for understanding Data Quality too!
Python for Data Science Automation is an innovative course designed to teach data analysts how to convert business processes to python-based data science automations.
Now you can make publication-ready storyboards. Patchwork makes it simple to combine separate ggplots into the same graphic.
I love ggplot2 for plotting. The grammar of graphics allows us to add elements to plots. Tables seem to be forgotten in terms of an intuitive grammar with tidy data philosophy - Until now.
Productivity is essential in data science. Businesses need value quickly so they can make decisions. Corrmorrant gets this.