malariagen_data.af1.Af1.plot_samples_bar

Af1.plot_samples_bar(x: str, color: str | None = None, sort: bool = True, sample_sets: Sequence[str] | str | None = None, sample_query: str | None = None, sample_query_options: dict | None = None, template: Literal['ggplot2', 'seaborn', 'simple_white', 'plotly', 'plotly_white', 'plotly_dark', 'presentation', 'xgridoff', 'ygridoff', 'gridon', 'none'] | None = 'plotly_white', width: int | None = 800, height: int | None = 600, show: bool = True, renderer: str | None = None, **kwargs) → Figure | None

Plot a bar chart showing the number of samples available, grouped by some variable such as country or year.

Parameters

xstr

Name of sample metadata column to plot on the X axis.

colorstr or None, optional

Name of the sample metadata column to color bars by.

sortbool, optional, default: True

If True, sort the bars in size order.

sample_setssequence of str or str or None, optional

List of sample sets and/or releases. Can also be a single sample set or release.

sample_querystr or None, optional

A pandas query string to be evaluated against the sample metadata, to select samples to be included in the returned data.

sample_query_optionsdict or None, optional

A dictionary of arguments that will be passed through to pandas query() or eval(), e.g. parser, engine, local_dict, global_dict, resolvers.

template{‘ggplot2’, ‘seaborn’, ‘simple_white’, ‘plotly’, ‘plotly_white’, ‘plotly_dark’, ‘presentation’, ‘xgridoff’, ‘ygridoff’, ‘gridon’, ‘none’} or None, optional, default: ‘plotly_white’

The figure template name (must be a key in plotly.io.templates).

widthint or None, optional, default: 800

Figure width in pixels (px).

heightint or None, optional, default: 600

Figure height in pixels (px).

showbool, optional, default: True

If true, show the plot. If False, do not show the plot, but return the figure.

rendererstr or None, optional

The name of the renderer to use.

**kwargs

Passed through to px.bar().

Returns

Figure or None

A plotly figure (only returned if show=False).