- 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 basicformatting like color, marker and linestyle. It's a shortcut stringnotation 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 morecontrol 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 givingthe data in x and y, you can provide the object in the dataparameter 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')
If x and/or y are 2D arrays, a separate data set will be drawnfor every column. If both x and y 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:
>>> for col in range(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 the dataparameter.
By default, each line is assigned a different style specified by a'style cycle'. The fmt and line property parameters are onlynecessary 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, thecolumns represent separate data sets).
These arguments cannot be passed as keywords.
- fmtstr, optional
A format string, e.g. 'ro' for red circles. See the Notessection 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 in x and y.
Note
Technically there's a slight ambiguity in calls where thesecond 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 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.
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 and two offsets from the bottom left corner of the image
alpha
scalar 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
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
See also
- scatter
XY scatter plot with markers of varying size and/or color ( sometimes also called bubble chart).
Notes
Note
This is the pyplot wrapper for axes.Axes.plot.
Format Strings
See AlsoTrinidad and Tobago Newsday Archives15 Best Things to Do in Mablethorpe (Lincolnshire, England) - The Crazy TouristA 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 stylecycle 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 alsosupported, 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
'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
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 canadditionally use any matplotlib.colors spec, e.g. full names(
'green'
) or hex strings ('#008000'
).
Examples using matplotlib.pyplot.plot
#
Plotting masked and NaN values
Plotting masked and NaN values
Scatter Masked
Scatter Masked
Simple Plot
Simple Plot
Stairs Demo
Stairs Demo
Step Demo
Step Demo
Triinterp Demo
Triinterp Demo
Custom Figure subclasses
Custom Figure subclasses
Managing multiple figures in pyplot
Managing multiple figures in pyplot
Shared axis
Shared axis
Multiple subplots
Multiple subplots
Polar plot
Polar plot
Polar legend
Polar legend
Align y-labels
Align y-labels
Legend using pre-defined labels
Legend using pre-defined labels
Controlling style of text and labels using a dictionary
Controlling style of text and labels using a dictionary
Title positioning
Title positioning
Color by y-value
Color by y-value
Dolphins
Dolphins
Solarized Light stylesheet
Solarized Light stylesheet
Infinite lines
Infinite lines
Simple plot
Simple plot
Text and mathtext using pyplot
Text and mathtext using pyplot
Multiple lines using pyplot
Multiple lines using pyplot
Two subplots using pyplot
Two subplots using pyplot
Frame grabbing
Frame grabbing
Coords Report
Coords Report
Customize Rc
Customize Rc
Findobj Demo
Findobj Demo
Multipage PDF
Multipage PDF
Print Stdout
Print Stdout
Set and get properties
Set and get properties
transforms.offset_copy
transforms.offset_copy
Zorder Demo
Zorder Demo
Custom scale
Custom scale
Placing date ticks using recurrence rules
Placing date ticks using recurrence rules
CanvasAgg demo
CanvasAgg demo
Tool Manager
Tool Manager
Pyplot tutorial
Pyplot tutorial
Quick start guide
Quick start guide
Customizing Matplotlib with style sheets and rcParams
Customizing Matplotlib with style sheets and rcParams
Path effects guide
Path effects guide