stat_summary(mapping=None, data=None, geom='pointrange', position='identity',
             na_rm=False, fun_y=None, fun_args=None, fun_ymax=None,
             fun_ymin=None, fun_data='mean_cl_boot', random_state=None,
             **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:
mappingaes, 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
The bold aesthetics are required.
Options for computed aesthetics
'ymin'  # ymin computed by the summary function
'ymax'  # ymax computed by the summary function
Calculated aesthetics are accessed using the after_stat function.
e.g. after_stat('ymin').
datadataframe, 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.
geomstr or geom, optional (default: geom_pointrange)
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.
positionstr or position, optional (default: position_identity)
Position adjustment. If it is a string, it must be registered and known to Plotnine.
na_rmbool, optional (default: False)
If False, removes missing values with a warning. If True silently removes missing values.
fun_datastr or function, optional
One of:
# Bootstrapped mean, confidence interval
# Arguments:
#     n_samples - No. of samples to draw
#     confidence_interval
#     random_state
'mean_cl_boot'
# Mean, C.I. assuming normal distribution
# Arguments:
#     confidence_interval
'mean_cl_normal'
# Mean, standard deviation * constant
# Arguments:
#     mult - multiplication factor
'mean_sdl'
# Median, outlier quantiles with equal tail areas
# Arguments:
#     confidence_interval
'median_hilow'
# Mean, Standard Errors * constant
# Arguments:
#     mult - multiplication factor
'mean_se'
or any function that takes a array and returns a dataframe
with three columns named y, ymin and ymax.
Defaults to 'mean_cl_boot'.
fun_yfunction, optional (default: None)
Any function that takes a array-like and returns a value
fun_ymin : function (default:None)
Any function that takes an array-like and returns a value
fun_ymaxfunction, optional (default: None)
Any function that takes an array-like and returns a value
fun_argsdict, optional (default: None)
Arguments to any of the functions. Provided the names of the
arguments of the different functions are in not conflict, the
arguments will be assigned to the right functions. If there is
a conflict, create a wrapper function that resolves the
ambiguity in the argument names.
random_stateint or RandomState, optional
Seed or Random number generator to use. If None, then
numpy global generator numpy.random is used.