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.. currentmodule:: altair
.. _user-guide-quantile-transform:
Quantile
~~~~~~~~
The quantile transform calculates empirical `quantile <https://en.wikipedia.org/wiki/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 <https://en.wikipedia.org/wiki/Q%E2%80%93Q_plot>`_.
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
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