plotnine.stats.stat_summary_bin

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

Summarise y values at x intervals

Usage

stat_summary_bin(mapping=None, data=None, geom='pointrange',
                 position='identity', na_rm=False, binwidth=None, bins=30,
                 fun_ymax=None, breaks=None, boundary=None, fun_data=None,
                 fun_args=None, fun_y=None, fun_ymin=None, 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:
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

'bin'    # bin identifier
'width'  # bin width
'ymin'   # ymin computed by the summary function
'ymax'   # ymax computed by the summary function

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

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: 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 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.

binwidth : float or tuple, optional (default: None)

The width of the bins. The default is to use bins bins that cover the range of the data. You should always override this value, exploring multiple widths to find the best to illustrate the stories in your data.

bins : int or tuple, optional (default: 30)

Number of bins. Overridden by binwidth.

breaks : array-like(s), optional (default: None)

Bin boundaries. This supercedes the binwidth, bins and boundary arguments.

boundary : float or tuple, optional (default: None)

A boundary between two bins. As with center, things are shifted when boundary is outside the range of the data. For example, to center on integers, use width=1 and boundary=0.5, even if 1 is outside the range of the data. At most one of center and boundary may be specified.

fun_data : str or function, optional

One of ['mean_cl_boot', 'mean_cl_normal', 'mean_sdl', 'median_hilow'] or any function that takes a array and returns a dataframe with three rows indexed as y, ymin and ymax. Defaults to 'mean_cl_boot'.

fun_y : function, 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_ymax : function, optional (default: None)

Any function that takes an array-like and returns a value

fun_args : dict, 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_state : int or RandomState, optional

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

Notes

The binwidth, bins, breaks and bounary arguments can be a tuples with two values ((xaxis-value, yaxis-value)) of the required type.