pivottablejs: the Python module
Drag’n’drop Pivot Tables and Charts for Jupyter/IPython Notebook, care of PivotTable.js
Installation
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.
Usage
import pandas as pd
df = pd.read_csv("some_input.csv")
from pivottablejs import pivot_ui
pivot_ui(df)
Advanced Usage
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")

with the columns values in the far left horizontal box and the plot dropdown on top of that. This needs dragging of each column to the second horizontal box to visualize the column contents or the plots.
from the other issue as well as