kanaries/pygwalker

PyGWalker is a Python library that turns a pandas dataframe, the standard table-shaped object data scientists work with in Python, into an interactive visual interface, right inside a Jupyter Notebook. Instead of writing more code each time you want to look at your data a different way, you drag and drop columns into rows, columns, and color slots to build charts, the way you would in Tableau. The name is a play on "Python binding of Graphic Walker", under the hood it integrates Jupyter with Graphic Walker, which the README calls an open-source alternative to Tableau. You install it with pip install pygwalker or with conda from conda-forge. The basic usage is two lines after loading your dataframe: import pygwalker as pyg, then walker = pyg.walk(df). The interactive UI then appears in the notebook and you can build visualisations, zoom, pan, filter, change the chart type, create concat views by adding multiple measures, or split into a facet view by dropping a dimension into rows or columns. The README also lists features for cleaning and transforming the data visually, spotting outliers, and creating new variables from existing ones, as well as natural-language queries. There is a separate R wrapper called GWalkR, and a no-code Desktop App for working offline without writing code. You would use it when you have a dataframe and want to explore it visually without writing chart code each time, or when you want a Tableau-style point-and-click experience embedded in your notebook. The full README is longer than what was provided.