matplotlib.pyplot.plot

matplotlib.pyplot.plot(*args, scalex=True, scaley=True, data=None, **kwargs) [source]

Plot y versus x as lines and/or markers.

Call signatures:

plot([x], y, [fmt], *, data=None, **kwargs)
plot([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)

The coordinates of the points or line nodes are given by x, y.

The optional parameter fmt is a convenient way for defining basic formatting like color, marker and linestyle. It's a shortcut string notation described in the Notes section below.

>>> plot(x, y)        # plot x and y using default line style and color
>>> plot(x, y, 'bo')  # plot x and y using blue circle markers
>>> plot(y)           # plot y using x as index array 0..N-1
>>> plot(y, 'r+')     # ditto, but with red plusses

You can use Line2D properties as keyword arguments for more control on the appearance. Line properties and fmt can be mixed. The following two calls yield identical results:

>>> plot(x, y, 'go--', linewidth=2, markersize=12)
>>> plot(x, y, color='green', marker='o', linestyle='dashed',
...      linewidth=2, markersize=12)

When conflicting with fmt, keyword arguments take precedence.

Plotting labelled data

There's a convenient way for plotting objects with labelled data (i.e. data that can be accessed by index obj['y']). Instead of giving the data in x and y, you can provide the object in the data parameter and just give the labels for x and y:

>>> plot('xlabel', 'ylabel', data=obj)

All indexable objects are supported. This could e.g. be a dict, a pandas.DataFame or a structured numpy array.

Plotting multiple sets of data

There are various ways to plot multiple sets of data.

• The most straight forward way is just to call plot multiple times. Example:

  >>> plot(x1, y1, 'bo')
  >>> plot(x2, y2, 'go')
  

• Alternatively, if your data is already a 2d array, you can pass it directly to x, y. A separate data set will be drawn for every column.

  Example: an array a where the first column represents the x values and the other columns are the y columns:

  >>> plot(a[0], a[1:])
  

• The third way is to specify multiple sets of [x], y, [fmt] groups:

  >>> plot(x1, y1, 'g^', x2, y2, 'g-')
  

  In this case, any additional keyword argument applies to all datasets. Also this syntax cannot be combined with the data parameter.

By default, each line is assigned a different style specified by a 'style cycle'. The fmt and line property parameters are only necessary if you want explicit deviations from these defaults. Alternatively, you can also change the style cycle using the 'axes.prop_cycle' rcParam.

Parameters:	x, y : array-like or scalar The horizontal / vertical coordinates of the data points. x values are optional and default to range(len(y)). Commonly, these parameters are 1D arrays. They can also be scalars, or two-dimensional (in that case, the columns represent separate data sets). These arguments cannot be passed as keywords. fmt : str, optional A format string, e.g. 'ro' for red circles. See the Notes section for a full description of the format strings. Format strings are just an abbreviation for quickly setting basic line properties. All of these and more can also be controlled by keyword arguments. This argument cannot be passed as keyword. data : indexable object, optional An object with labelled data. If given, provide the label names to plot in x and y. Note Technically there's a slight ambiguity in calls where the second label is a valid fmt. plot('n', 'o', data=obj) could be plt(x, y) or plt(y, fmt). In such cases, the former interpretation is chosen, but a warning is issued. You may suppress the warning by adding an empty format string plot('n', 'o', '', data=obj).
Returns:	lines A list of Line2D objects representing the plotted data.
Other Parameters:	scalex, scaley : bool, optional, default: True These parameters determined if the view limits are adapted to the data limits. The values are passed on to autoscale_view. **kwargs : Line2D properties, optional kwargs are used to specify properties like a line label (for auto legends), linewidth, antialiasing, marker face color. Example: >>> plot([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2) >>> plot([1,2,3], [1,4,9], 'rs', label='line 2') If you make multiple lines with one plot command, the kwargs apply to all those lines. Here is a list of available Line2D properties: Property Description 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 float animated bool antialiased or aa bool clip_box Bbox clip_on bool clip_path [(Path, Transform) | Patch | None] color or c color contains callable dash_capstyle {'butt', 'round', 'projecting'} dash_joinstyle {'miter', 'round', 'bevel'} dashes sequence of floats (on/off ink in points) or (None, None) 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 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) path_effects AbstractPathEffect picker float or callable[[Artist, Event], Tuple[bool, dict]] pickradius float rasterized bool or None sketch_params (scale: float, length: float, randomness: float) snap bool or None solid_capstyle {'butt', 'round', 'projecting'} solid_joinstyle {'miter', 'round', 'bevel'} transform matplotlib.transforms.Transform url str visible bool xdata 1D array ydata 1D array zorder float

See also

scatter

XY scatter plot with markers of varying size and/or color ( sometimes also called bubble chart).

Notes

Format Strings

A format string consists of a part for color, marker and line:

fmt = '[marker][line][color]'

Each of them is optional. If not provided, the value from the style cycle is used. Exception: If line is given, but no marker, the data will be a line without markers.

Other combinations such as [color][marker][line] are also supported, but note that their parsing may be ambiguous.

Markers

character	description
'.'	point marker
','	pixel marker
'o'	circle marker
'v'	triangle_down marker
'^'	triangle_up marker
'<'	triangle_left marker
'>'	triangle_right marker
'1'	tri_down marker
'2'	tri_up marker
'3'	tri_left marker
'4'	tri_right marker
's'	square marker
'p'	pentagon marker
'*'	star marker
'h'	hexagon1 marker
'H'	hexagon2 marker
'+'	plus marker
'x'	x marker
'D'	diamond marker
'd'	thin_diamond marker
'|'	vline marker
'_'	hline marker

Line Styles

character	description
'-'	solid line style
'--'	dashed line style
'-.'	dash-dot line style
':'	dotted line style

Example format strings:

'b'    # blue markers with default shape
'or'   # red circles
'-g'   # green solid line
'--'   # dashed line with default color
'^k:'  # black triangle_up markers connected by a dotted line

Colors

The supported color abbreviations are the single letter codes

character	color
'b'	blue
'g'	green
'r'	red
'c'	cyan
'm'	magenta
'y'	yellow
'k'	black
'w'	white

and the 'CN' colors that index into the default property cycle.

If the color is the only part of the format string, you can additionally use any matplotlib.colors spec, e.g. full names ('green') or hex strings ('#008000').

Examples using matplotlib.pyplot.plot