plotnine.stats.stat_quantile

class plotnine.stats.stat_quantile(*args, **kwargs)[source]

Compute quantile regression lines

Usage

stat_quantile(mapping=None, data=None, geom='quantile', position='identity',
              na_rm=False, quantiles=(0.25, 0.5, 0.75), method_args={},
              formula='y ~ x', **kwargs)

Only the mapping and data can be positional, the rest must be keyword arguments. **kwargs can be aesthetics (or parameters) used by the geom.

Parameters:
mapping : aes, optional

Aesthetic mappings created with aes(). If specified and inherit.aes=True, it is combined with the default mapping for the plot. You must supply mapping if there is no plot mapping.

Aesthetic Default value
x  
y  

The bold aesthetics are required.

Options for computed aesthetics

'quantile'  # quantile
'group'     # group identifier

Calculated aesthetics are accessed using the calc function. e.g. 'stat(quantile)'.

data : dataframe, optional

The data to be displayed in this layer. If None, the data from from the ggplot() call is used. If specified, it overrides the data from the ggplot() call.

geom : str or stat, optional (default: quantile)

The statistical transformation to use on the data for this layer. If it is a string, it must be the registered and known to Plotnine.

position : str or position, optional (default: identity)

Position adjustment. If it is a string, it must be registered and known to Plotnine.

na_rm : bool, optional (default: False)

If False, removes missing values with a warning. If True silently removes missing values.

quatiles : tuple, optional (default: (0.25, 0.5, 0.75))

Quantiles of y to compute

formula : str, optional (default: 'y ~ x')

Formula relating y variables to x variables

method_args : dict, optional

Extra arguments passed on to the model fitting method, statsmodels.regression.quantile_regression.QuantReg.fit().