matplotlib 3.5.1

NotesOther ParametersParametersReturns
plot_date(self, x, y, fmt='o', tz=None, xdate=True, ydate=False, *, data=None, **kwargs)
.. admonition:: Discouraged
    This method exists for historic reasons and will be deprecated in
    the future.

    - ``datetime``-like data should directly be plotted using
      `~.Axes.plot`.
    -  If you need to plot plain numeric data as :ref:`date-format` or
       need to set a timezone, call ``ax.xaxis.axis_date`` /
       ``ax.yaxis.axis_date`` before `~.Axes.plot`. See
       `.Axis.axis_date`.

Similar to :None:None:`.plot`, this plots y vs. x as lines or markers. However, the axis labels are formatted as dates depending on xdate and ydate. Note that :None:None:`.plot` will work with datetime and numpy.datetime64 objects without resorting to this method.

Notes

If you are using custom date tickers and formatters, it may be necessary to set the formatters/locators after the call to :None:None:`.plot_date`. :None:None:`.plot_date` will set the default tick locator to .AutoDateLocator (if the tick locator is not already set to a .DateLocator instance) and the default tick formatter to .AutoDateFormatter (if the tick formatter is not already set to a .DateFormatter instance).

Other Parameters

data : indexable object, optional

If given, the following parameters also accept a string s , which is interpreted as data[s] (unless this raises an exception):

x, y

**kwargs :

Keyword arguments control the .Line2D properties:

Properties: agg_filter: a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array alpha: scalar or None animated: bool antialiased or aa: bool clip_box: .Bbox clip_on: bool clip_path: Patch or (Path, Transform) or None color or c: color dash_capstyle: .CapStyle or {'butt', 'projecting', 'round'} dash_joinstyle: .JoinStyle or {'miter', 'round', 'bevel'} dashes: sequence of floats (on/off ink in points) or (None, None) data: (2, N) array or two 1D arrays drawstyle or ds: {'default', 'steps', 'steps-pre', 'steps-mid', 'steps-post'}, default: 'default' figure: .Figure fillstyle: {'full', 'left', 'right', 'bottom', 'top', 'none'} gid: str in_layout: bool label: object linestyle or ls: {'-', '--', '-.', ':', '', (offset, on-off-seq), ...} linewidth or lw: float marker: marker style string, ~.path.Path or ~.markers.MarkerStyle markeredgecolor or mec: color markeredgewidth or mew: float markerfacecolor or mfc: color markerfacecoloralt or mfcalt: color markersize or ms: float markevery: None or int or (int, int) or slice or list[int] or float or (float, float) or list[bool] path_effects: .AbstractPathEffect picker: float or callable[[Artist, Event], tuple[bool, dict]] pickradius: float rasterized: bool sketch_params: (scale: float, length: float, randomness: float) snap: bool or None solid_capstyle: .CapStyle or {'butt', 'projecting', 'round'} solid_joinstyle: .JoinStyle or {'miter', 'round', 'bevel'} transform: unknown url: str visible: bool xdata: 1D array ydata: 1D array zorder: float

Parameters

x, y : array-like

The coordinates of the data points. If xdate or ydate is True, the respective values x or y are interpreted as Matplotlib dates <date-format> .

fmt : str, optional

The plot format string. For details, see the corresponding parameter in :None:None:`.plot`.

tz : timezone string or `datetime.tzinfo`, default: :rc:`timezone`

The time zone to use in labeling dates.

xdate : bool, default: True

If True, the x-axis will be interpreted as Matplotlib dates.

ydate : bool, default: False

If True, the y-axis will be interpreted as Matplotlib dates.

Returns

list of `.Line2D`

Objects representing the plotted data.

Plot coercing the axis to treat floats as dates.

See Also

matplotlib.dates

Helper functions on dates.

matplotlib.dates.date2num

Convert dates to num.

matplotlib.dates.drange

Create an equally spaced sequence of dates.

matplotlib.dates.num2date

Convert num to dates.

Examples

See :

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


File: /matplotlib/axes/_axes.py#1638
type: <class 'function'>
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