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9 posts tagged with "data science"

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· 2 min read

Reticulate is an R library that lets you execute Python code from within R. Recently, I attempted to use reticulate to access numpy from Python. Numpy was installed, but I kept getting the following message:

> reticulate::py_config()
python: /usr/home/sam.edwardes/rstudio-demos/applications/shiny-for-r-with-reticulate/.venv/bin/python3
libpython: /opt/python/3.10.11/lib/
pythonhome: /usr/home/sam.edwardes/rstudio-demos/applications/shiny-for-r-with-reticulate/.venv:/usr/home/sam.edwardes/rstudio-demos/applications/shiny-for-r-with-reticulate/.venv
version: 3.10.11 (main, Jun 4 2023, 22:34:21) [GCC 11.3.0]
numpy: [NOT FOUND]

· 4 min read

As a data scientist one of the most common questions I get from colleagues and clients is how to get started on learning R. There is a plethora of great options out there today. Some of which are paid, and some of which are free.

· 5 min read

One of the funnest (and most frustrating) parts of data science is the vast array of tools available to us. It can be overwhelming where to start. Every now and then I like to completely wipe my computer clean, and then reinstall everything from scratch. This helps clean up my computer, and make sure everything is running smoothly.

· 9 min read

When a UFC match ends with a knock-out or submission there is never any doubt who the better fighter was. But only 54% of fights end with a knock-out or submission. The other 45% of fights go to the judges score cards.