Drag’n’drop Pivot Tables and Charts for Jupyter/IPython Notebook, care of PivotTable.js

pip install pivottablejs or conda install pivottablejs

Note in the past, the conda command above installed pivottablejs-airgap instead of this library; apologies for any confusion this change may cause.

import pandas as pd
df = pd.read_csv("some_input.csv")

from pivottablejs import pivot_ui

pivot_ui(df)

Include any JSON-serializable option to PivotTable.js's pivotUI() function as a keyword argument.

pivot_ui(df, rows=['row_name'], cols=['col_name'])

Independently control the output file path and the URL used to access it from Jupyter, in case the default relative-URL behaviour is incompatible with Jupyter's settings.

pivot_ui(df, outfile_path="/x/y.html", url="http://localhost/a/b/x.html")