BarChart#

class qf_lib.plotting.charts.bar_chart.BarChart(orientation: Orientation, stacked: bool = True, index_translator: IndexTranslator = None, thickness: float = 0.8, start_x: Any = None, end_x: Any = None, upper_y: float = None, lower_y: float = None, **plot_settings)[source]#

Bases: Chart

Creates a new bar chart with the specified orientation.

Parameters:

  • orientation (Orientation) – The orientation of the bar chart, either Horizontal or Vertical.

  • stacked (bool) – default: True; if True then bars corresponding to different DataElementDecorators will be stacked. Otherwise bars will be plotted next to each other.

  • index_translator (IndexTranslator) – the mapper of index coordinates (e.g. you may use labels as index in a pandas series and this translator will ensure that it is plotted correctly)

  • thickness (float) – how thick should each bar be (expressed in numeric data coordinates system)

  • start_x (datetime.datetime) – The date where the x-axis should begin.

  • end_x (datetime.datetime) – The date where the x-axis should end.

  • upper_y (float) – The upper bound of the y-axis.

  • lower_y (float) – The lower bound of the y-axis.

  • plot_settings – Keyword arguments to pass to the plot function.

apply_data_element_decorators(data_element_decorators: List[DataElementDecorator]) → Any[source]#

Plots all DataElementDecorators added to a chart. This function should set legend_artist field in each plotted DataElementDecorator (if applicable).

Parameters:

data_element_decorators (List[DataElementDecorator]) – non-empty list of DataElementDecorators that should be plotted on the chart

plot(figsize: Tuple[float, float] = None)[source]#

Plots the chart. The underlying figure stays hidden until the show() method is called.

Parameters:

figsize (Tuple[float, float]) – The figure size to draw the chart at in inches. This is a tuple of (width, height) passed directly to matplotlib’s plot function. The values are expressed in inches.