Many times when we do our EDA or machine learning predictions, in the end, we end up importing tons of libraries. Python, NumPy, Pandas, Sklearn, Seaborn, Matplotlib, Cross-validation, Regression etc. are the most commonly used libraries we import to achieve the magic.
This lovely tragedy comes in below format:
What if we don’t need to import all regular libraries again and again when we start new EDA or predictions. It will save a lot of time for us and avoid the mistakes made during import.
Thanks to python community who takes these issues seriously and blessed other developers with Pyforest which makes this import process easy and flexible. A big credit goes to streamline and almost fixed alias developers used to import. For e.g. pd for pandas, np for numpy and many more.
Steps to install
- use !pip install pyforest to install it from jupyter notebook
- use pip install pyforest to install it from Anacoda cmd prompt
How to use pyforest
No need to import any library.
Start using alias and functions to get functionality from line 1as below:
We can also check what and all libraries are imported during any step of EDA or prediction. Use active_imports() to see the list of libraries that have been imported by pyforest as below: