plotnine.stat_summary

stat_summary(
    mapping=None,
    data=None,
    *,
    geom="pointrange",
    position="identity",
    na_rm=False,
    fun_data="mean_cl_boot",
    fun_y=None,
    fun_ymin=None,
    fun_ymax=None,
    fun_args=None,
    random_state=None,
    **kwargs
)

Calculate summary statistics depending on x

Parameters

mapping : aes = None

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

"ymin"  # ymin computed by the summary function
"ymax"  # ymax computed by the summary function
"n"     # Number of observations at a position

Calculated aesthetics are accessed using the after_stat function. e.g. after_stat('ymin').

data : DataFrame = None

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 | 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.

position : str | position = "identity"

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

na_rm : bool = False

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

fun_data : str | callable = "mean_cl_boot"

If string, it should be 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.

fun_y : callable = None

Any function that takes a array_like and returns a value

fun_ymin : callable = None

Any function that takes an array_like and returns a value

fun_ymax : callable = None

Any function that takes an array_like and returns a value

fun_args : dict = 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_state : int | RandomState = None

Seed or Random number generator to use. If None, then numpy global generator numpy.random is used.

**kwargs : Any = {}

Aesthetics or parameters used by the geom.

Notes

If any of fun_y, fun_ymin or fun_ymax are provided, the value of fun_data will be ignored.

Parameters

Notes

See Also