matplotlib.axes.Axes.plot¶
-
Axes.
plot
(self, *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
, 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 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
rcParams["axes.prop_cycle"]
(default:cycler('color', ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf'])
).Parameters: - x, yarray-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.
- fmtstr, 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.
- dataindexable 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 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 of
Line2D
A list of lines representing the plotted data.
Other Parameters: - scalex, scaleybool, default: True
These parameters determine 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 call, 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 or None animated
bool antialiased
or aabool clip_box
Bbox
clip_on
bool clip_path
Patch or (Path, Transform) or None color
or ccolor contains
unknown dash_capstyle
{'butt', 'round', 'projecting'} dash_joinstyle
{'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 lwfloat marker
marker style string, Path
orMarkerStyle
markeredgecolor
or meccolor markeredgewidth
or mewfloat markerfacecolor
or mfccolor markerfacecoloralt
or mfcaltcolor markersize
or msfloat markevery
None or int or (int, int) or slice or List[int] or float or (float, float) or List[bool] path_effects
AbstractPathEffect
picker
unknown 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 nomarker
, 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'
).