Welcome to MicroFrame’s Documentation!#

MicroFrame#

MicroFrame is a lightweight educational data manipulation library designed to provide a pandas-like interface for students learning to work with real-world data. It is optimized for toy datasets and aims to introduce users to data analysis concepts without the overhead of pandas.

Features#

  • Efficient CSV Reading: Quickly and easily read CSV files to create MicroFrame objects, optimized for educational purposes and smaller datasets.

  • Data Type Handling: Advanced data type inference and explicit type setting offer both convenience and control over the structure of your data.

  • Flexible MicroFrame Objects: Utilize MicroFrame objects that mimic pandas DataFrame for intuitive data manipulation and analysis.

  • Clear Tabular Display: Use MicroFrame’s printing capabilities to generate well-formatted tabular representations of your data, making it easier to interpret and present.

  • Robust Data Manipulation: Perform a variety of data manipulation tasks with methods similar to pandas, such as filtering, column dtype modification and summarizing data.

  • Advanced Indexing: Access data efficiently with advanced indexing options, using the iloc method similar to pandas iloc method.

  • Data Conversion Tools: Seamlessly convert your MicroFrame objects to other formats, including NumPy arrays, with the to_numpy method for further numerical computation.

  • User-Friendly API: Experience a user-friendly API that mirrors pandas to facilitate the transition from educational projects to real-world data analysis.

Installation#

Install MicroFrame using pip:

pip install microframe

API Reference#

Documentation#

Indices and tables#