🖥 ده کتابخانه کوچک پایتون برای کار با داده ها

• PyGWalker: PyGWalker simplifies the workflow for analyzing and visualizing data in Jupyter Notebook by turning a pandas data frame (or polars data frame) into a Tableau-style user interface for visual exploration.

• SciencePlots: Creates professional matplotlib plots for presentations, research papers, and more.

• CleverCSV: Eliminates parsing errors when reading CSV files with Pandas.
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• Fastparquet: Speeds up pandas I/O by 5x.

• Bottleneck: Speeds up NumPy methods by 25x. Especially if the array has NaN values.

• Multipledispatch: Provides methods for overloading functions in Python.

• Aquarel: Additional matplotlib plot styles.

• Modelstore: A library of machine learning models for better tracking of model performance.

• Pigeon: Helps you annotate data with mouse clicks in Jupyter notebook.

• Nbcommands: Helps you easily search code in Jupyter notebooks instead of doing it manually.

📌More details with code examples


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#Python_tricks
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