raffalib-python documentation

raffalib-python is a small library of helper functions for data wrangling.

Its main purpose is to enrich pandas and polars with STATA-like logging and .docx export capabilities, but it also bundles assorted utilities for logging, pickling, progress bars, Selenium, SQLAlchemy, and bibliometrics.

Highlights

  • STATA-like logging — wrap a pandas/polars pipeline in startlog() / endlog() and get a log line describing how many rows, columns, or cell values changed (and optionally how long it took).

  • Logging joins — a join() wrapper (for both backends) that logs where the output rows came from: left only, right only, both, dropped rows, and duplicate keys.

  • Frequency & cross tables — freq() and crosstab() accessors for quick tabulations.

  • Word export — write any DataFrame straight to a .docx table with to_docx().

A taste

import pandas as pd
import numpy as np
import raffalib
import raffalib.pandas  # registers the `.raffa` accessor

raffalib.create_logger(rich=False, fmt="{message}")

df = pd.DataFrame(
    {
        "species": ["Adelie", "Adelie", "Adelie", "Gentoo", "Gentoo", "Chinstrap"],
        "bill_depth_mm": [18.7, np.nan, 18.0, np.nan, 16.3, 17.9],
        "body_mass_g": [3750.0, 3800.0, np.nan, 4500.0, 5700.0, 3500.0],
    }
)
df = df.raffa.startlog().dropna(subset=["bill_depth_mm"]).raffa.endlog()
# -> Removed 2/6 (33.33%) rows. New shape: (4, 3).
# -> Took: 0.01 seconds

New here? Start with Quickstart, then browse the Examples for the full tour. The complete API reference is generated from the source docstrings under API Reference in the sidebar.

Note

This project is under active development.