.. currentmodule:: altair .. _user-guide-quantile-transform: Quantile ~~~~~~~~ The quantile transform calculates empirical `quantile `_ values for input data. If a groupby parameter is provided, quantiles are estimated separately per group. Among other uses, the quantile transform is useful for creating `quantile-quantile (Q-Q) plots `_. Here is an example of a quantile plot of normally-distributed data: .. altair-plot:: import altair as alt import pandas as pd import numpy as np np.random.seed(42) df = pd.DataFrame({'x': np.random.randn(200)}) alt.Chart(df).transform_quantile( 'x', step=0.01 ).mark_point().encode( x='prob:Q', y='value:Q' ) Transform Options ^^^^^^^^^^^^^^^^^ The :meth:`~Chart.transform_quantile` method is built on the :class:`~QuantileTransform` class, which has the following options: .. altair-object-table:: altair.QuantileTransform