Python-bloggers

Introduction In the last post in this series I am going to look at calling Python from R. Even though Excel now provides a means of calling Python scripts directly, using the =PY() formula in a worksheet, there are still occasions when it is beneficial...

Importing data is a key step in the data science workflow. It also has a huge responsibility. How you import (or connect to) a dataset has consequences for how you work with that data throughout a project, because a Pandas DataFrame (say) requir...

New nnetsauce version with CustomBackPropRegressor and ElasticNet2Regressor: python examples included.

mlsauce (home to a model-agnostic gradient boosting algorithm) can now be installed from PyPI.

Visualizing seasonality is a critical analytical skill in business because many essential metrics like sales, revenue, or demand often follow predictable seasonal patterns. Understanding these patterns helps businesses anticipate periods of peak activity, manage inventory, allocate resources effectively, and create accurate forecasts. Python in Excel makes seasonal analysis especially straightforward. ...

When working with complex datasets, especially panel data common in finance, managing multiple levels of indexing can quickly become overwhelming in traditional Excel. This is where Pandas’ MultiIndex feature shines. A MultiIndex in Pandas lets you efficiently handle data indexed across multiple dimensions, such as financial metrics tracked over time ...

Are you ready to expand your knowledge in R, Python, Shiny, and Posit while becoming a more valuable asset to your team? Jumping Rivers is here to help you do just that with our free monthly webinar series designed for data professionals at all l...