The modern Python data stack in one place. Polars and PyArrow lead the new wave of high-performance columnar processing; pandas and NumPy remain the foundations every Python data engineer learns; Matplotlib, Plotly, Streamlit, and Dash turn data into interactive interfaces. Pick the tool that matches your workload — these tutorials cover every layer.
Modern dataframes — Polars & PyArrow
- How To Use Polars for Fast DataFrame Operations in Python
- How To Use Polars for Faster DataFrames in Python
- How To Use Python PyArrow for Columnar Data Processing
- How To Read and Write Parquet Files in Python with PyArrow
Foundational — pandas & NumPy
- How To Clean Messy Data with Python and Pandas
- How To Use NumPy Arrays for Scientific Computing in Python
- How To Work With CSV Files in Python Using the csv Module and Pandas
Visualisation — Matplotlib & Plotly
- How To Create Plots and Charts with Matplotlib in Python
- How To Use Python Plotly for Interactive Data Visualizations
Interactive data apps — Streamlit & Dash
Functional utilities — pydash
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