Question 1

How do I run the Python Data Science Handbook notebooks on Google Colab?

Accepted Answer

Click the Colab badge in the README or use the provided link to launch any notebook directly in Google Colab for free, executable execution without any local setup required.

Question 2

Is the Python Data Science Handbook updated for Python 3.9?

Accepted Answer

The book was tested with Python 3.5 and may require tweaks for newer versions; check the requirements.txt and adapt package versions as needed, as noted in the README for compatibility.

Question 3

Python Data Science Handbook vs DataCamp: which is better for learning Pandas?

Accepted Answer

The Handbook offers a free, in-depth reference with executable code for self-paced learning, while DataCamp provides interactive courses with structured paths; choose based on your preference for reading vs guided tutorials.

Question 4

How to set up a local conda environment for the Python Data Science Handbook?

Accepted Answer

Use 'conda create -n PDSH python=3.5 --file requirements.txt' as per the README, but be prepared to adjust package versions for your platform if dependencies clash, since exact versions may not be available.

Question 5

Can I use the Python Data Science Handbook text in my commercial project?

Accepted Answer

No, the text is under CC-BY-NC-ND license, which restricts commercial use; only the code is MIT licensed and can be used freely, as clarified in the license section of the README.

Question 6

What libraries does the Python Data Science Handbook cover?

Accepted Answer

It focuses on IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn, providing comprehensive coverage of these core tools for data analysis and visualization, as listed in the 'About' section.

Python Data Science Handbook

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