Installing and Using
To install and use
pdvega run the following commands:
$ pip install pdvega $ jupyter nbextension install --sys-prefix --py vega3
The first command installs the pdvega
Python package along with its dependencies (Pandas and vega3).
The second command above installs the vega3 Jupyter notebook extension, which
is required for
pdvega plots to display automatically in the notebook.
pdvega in the Jupyter Notebook¶
vega3 are correctly installed, you can create a
visualization within the Jupyter notebook by executing a cell with a plot
command as the last statement in the cell. For example:
import pandas as pd import pdvega # adds vgplot attribute to Pandas objects data = pd.Series([1,2,3,2,3,4,3,4,5]) data.vgplot()
You can also explicitly call the
plot.display() method to display a plot
saved in a variable:
plot = data.vgplot() plot.display()
pdvega in JupyterLab¶
JupyterLab is the next phase
of evolution for the Jupyter notebook. For reasons related to its under-the-hood
implementation, the current version of
pdvega will not work in JupyterLab: the
main reason is that the new MIME-based rendering used by JupyterLab is not yet supported
in the vega3 library that
pdvega depends on.
We hope to address this incompatibility soon!
pdvega Outside Jupyter¶
If you wish to use
pdvega outside the Jupyter notebook, you can save the
plot specification to a JSON file:
import json plot = data.vgplot() json.dump(plot.spec, 'plot.json')
Saving Visualizations to PNG or SVG¶
To save a visualization to PNG, you can use the link generated below the
rendered plot. Programmatic saving of figures is not currently supported
from within Python, though it is possible using the
command-line tools provided in the vega-lite npm package.