Statistics bar
The
add_stat_bar()
method allows to add a
bar containing statistics for the plot’s data.The stat bar can be customized through specific parameters:
stats
: list of the statistics values to display,
nb_digits
: number of significant digits number to display (defaults to 4).
The default statistics bar display contains the following statistics:
Number of measurements
Minimum
Mean
Median
Maximum
Standard deviation
Add a bar containing number, minimum, mean, median, maximum and
standard deviation information.
Parameters
----------
position
position of the stat bar (top, bottom, left, right)
(default to top)
stats
List of the statistics to display in the stat bar.
nb_digits
Number of significant digits for statistics values.
params
Bar's parameters.
Note
Statistics bar can be fully customized using AxeParams.
Note
For merged plots, configuring plot’s legend(s) will update plot’s reference(s) in the statistics bar.
from casys import AxeParams, CasysPlot, PlotParams
plot = CasysPlot(
data=ad,
data_name="SLA box stat",
stat="std",
plot_params=PlotParams(color_limits=(0, 1)),
)
param = AxeParams(
label={
"fontsize": "x-small",
"color": "red"
},
position="bottom"
)
plot.add_stat_bar(nb_digits=7, stats=["mean", "nbr", "max", "median"], params=param)
plot.show()

Note
When using the
add_plot()
method, nb_digits
parameter value is specific to each plot. For added plots without a nb_digits
specification,
the statistics bar number of digits will align on the main plot.The
stats
parameter is set by the main plot stats
parameter value for all added plots
(ignoring their own stats
specification).plot_1 = CasysPlot(
data=ad,
data_name="SLA box stat",
stat="std",
plot_params=PlotParams(color_limits=(0, 1)),
)
plot_1.add_stat_bar(nb_digits=3, stats=["mean", "nbr", "max", "median"], params=param)
plot_2 = CasysPlot(
data=ad,
data_name="SLA",
plot="map",
plot_params=PlotParams(color_limits=(0, 1)),
)
plot_2.add_stat_bar(nb_digits=7, stats=["mean", "nbr", "max", "median", "min", "std"], params=param)
plot_1.add_plot(plot_2)
plot_1.show()
