matplotlib.axes.Axes.plot #

Axes.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 byx,y.

The optional parameterfmt is a convenient way for defining basicformatting like color, marker and linestyle. It's a shortcut stringnotation described in theNotes 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 useLine2D properties as keyword arguments for morecontrol on the appearance. Line properties andfmt 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 withfmt, 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 indexobj['y']). Instead of givingthe data inx andy, you can provide the object in thedataparameter and just give the labels forx andy:

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

All indexable objects are supported. This could e.g. be adict, apandas.DataFrame 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 callplot multiple times.Example:
```
>>>plot(x1,y1,'bo')>>>plot(x2,y2,'go')
```
Ifx and/ory are 2D arrays, a separate data set will be drawnfor every column. If bothx andy are 2D, they must have thesame shape. If only one of them is 2D with shape (N, m) the othermust have length N and will be used for every data set m.
Example:
```
>>>x=[1,2,3]>>>y=np.array([[1,2],[3,4],[5,6]])>>>plot(x,y)
```
is equivalent to:
```
>>>forcolinrange(y.shape[1]):...plot(x,y[:,col])
```
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 alldatasets. Also, this syntax cannot be combined with thedataparameter.

By default, each line is assigned a different style specified by a'style cycle'. Thefmt and line property parameters are onlynecessary if you want explicit deviations from these defaults.Alternatively, you can also change the style cycle usingrcParams["axes.prop_cycle"] (default:cycler('color',['#1f77b4','#ff7f0e','#2ca02c','#d62728','#9467bd','#8c564b','#e377c2','#7f7f7f','#bcbd22','#17becf'])).

Parameters:

x, yarray-like or float

The horizontal / vertical coordinates of the data points.x values are optional and default torange(len(y)).

Commonly, these parameters are 1D arrays.

They can also be scalars, or two-dimensional (in that case, thecolumns represent separate data sets).

These arguments cannot be passed as keywords.

fmtstr, optional

A format string, e.g. 'ro' for red circles. See theNotessection for a full description of the format strings.

Format strings are just an abbreviation for quickly settingbasic line properties. All of these and more can also becontrolled by keyword arguments.

This argument cannot be passed as keyword.

dataindexable object, optional

An object with labelled data. If given, provide the label names toplot inx andy.

Note

Technically there's a slight ambiguity in calls where thesecond label is a validfmt.plot('n','o',data=obj)could beplt(x,y) orplt(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 stringplot('n','o','',data=obj).

Returns:

list ofLine2D: A list of lines representing the plotted data.

Other Parameters:

scalex, scaleybool, default: True

These parameters determine if the view limits are adapted to thedata limits. The values are passed on toautoscale_view.

**kwargsLine2D properties, optional

kwargs are used to specify properties like a line label (forauto 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 specify multiple lines with one plot call, the kwargs applyto all those lines. In case the label object is iterable, eachelement is used as labels for each set of data.

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 and two offsets from the bottom left corner of the image
`alpha`	float or None
`animated`	bool
`antialiased` or`aa`	bool
`clip_box`	`BboxBase` or None
`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` or`SubFigure`
`fillstyle`	{'full', 'left', 'right', 'bottom', 'top', 'none'}
`gapcolor`	color or None
`gid`	str
`in_layout`	bool
`label`	object
`linestyle` or`ls`	{'-', '--', '-.', ':', '', (offset, on-off-seq), ...}
`linewidth` or`lw`	float
`marker`	marker style string,`Path` or`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]
`mouseover`	bool
`path_effects`	list of`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

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
`'8'`	octagon marker
`'s'`	square marker
`'p'`	pentagon marker
`'P'`	plus (filled) marker
`'*'`	star marker
`'h'`	hexagon1 marker
`'H'`	hexagon2 marker
`'+'`	plus marker
`'x'`	x marker
`'X'`	x (filled) marker
`'D'`	diamond marker
`'d'`	thin_diamond marker
`'\|'`	vline marker
`'_'`	hline marker

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

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

Movatterモバイル変換

matplotlib.axes.Axes.plot#

Examples usingmatplotlib.axes.Axes.plot#

matplotlib.axes.Axes.plot #

Examples using`matplotlib.axes.Axes.plot`#