quak /kwæk/

an anywidget for data that talks like a duck

about

quak is a scalable data profiler for quickly scanning large tables.

• interactive 🖱️ mouse over column summaries, cross-filter, sort, and slice rows.
• fast ⚡ built with Mosaic; views are expressed as SQL queries lazily executed by DuckDB.
• flexible 🔄 supports many data types and formats via Apache Arrow and the dataframe interchange protocol.
• reproducible 📓 a UI for building complex SQL queries; materialize views in the kernel for further analysis.

install

Warning

quak is a prototype exploring a high-performance data profiler based on anywidget. It is not production-ready. Expect bugs. Open-sourced for SciPy 2024.

pip install quak

usage

The easiest way to get started with quak is using the IPython cell magic.

%load_ext quak

import pandas as pd

df = pd.read_csv("https://raw.githubusercontent.com/vega/vega-datasets/main/data/airports.csv")
df

Any cell that returns an object implementing the Python dataframe interchange protocol (i.e., a dataframe-like "thing") will be rendered using quak.Widget, rather than the default renderer.

Alternatively, you can use quak.Widget directly:

import polars as pl
import quak

df = pl.read_csv("https://raw.githubusercontent.com/vega/vega-datasets/main/data/airports.csv")
quak.Widget(df)

contributing

Contributors welcome! Check the Contributors Guide to get started. Note: I'm wrapping up my PhD, so I might be slow to respond. Please open an issue before contributing a new feature.