How do you plot a line graph in python?

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.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 drawn for every column. If both x and y are 2D, they must have the same shape. If only one of them is 2D with shape (N, m) the other must 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 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 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: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.

**kwargsLine2D 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 specify multiple lines with one plot call, the kwargs apply to all those lines. In case the label object is iterable, each element 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

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'}

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

AbstractPathEffect

picker

float or callable[[Artist, Event], tuple[bool, dict]]

pickradius

unknown

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

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

'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 can additionally use any matplotlib.colors spec, e.g. full names ('green') or hex strings ('#008000').

Examples using matplotlib.pyplot.plot#

How do I make a line plot in Python?

To create a line plot, pass an array or list of numbers as an argument to Matplotlib's plt. plot() function. The command plt. show() is needed at the end to show the plot..
plt. title('').</div> <div class='ListData'>plt. xlabel('<x-axis label string>').</div> <div class='ListData'>plt. ylabel('<y-axis label string>').</div> <div class='ListData'>plt. ... .</div> <div class='ListData'>ptl. ... .</div> <div class='ListData'>plt. ... .</div> </div> <h3 id="how-do-i-draw-a-line-in-matplotlib-plot">How do I draw a line in Matplotlib plot?</h3> <div class="blockAnswer_acceptedAnswer"><div class='ListData'><span class="FCUp0c rQMQod">As of matplotlib 3.3, you can do this with plt. axline((x1, y1), (x2, y2)) .</span>.</div> <div class='ListData'>This does not draw lines, it draws line segments between given points. ... .</div> <div class='ListData'>Yes, matplotlib draws line segments... the way lines are drawn, you can't extend lines to infinity. ... .</div> <div class='ListData'>"the way lines are drawn, you can't extend lines to infinity" -- why not?.</div> </div> <h3 id="which-method-is-used-to-generate-line-chart-in-python">Which method is used to generate line chart in Python?</h3> <div class="blockAnswer_acceptedAnswer">You can use the <span class="FCUp0c rQMQod">plot(x,y)</span> method to create a line chart.</div> <h3 id="how-do-i-plot-a-line-graph-in-numpy">How do I plot a line graph in NumPy?</h3> <div class="blockAnswer_acceptedAnswer">For plotting graphs in Python, we will <span class="FCUp0c rQMQod">use the Matplotlib library</span>. Matplotlib is used along with NumPy data to plot any type of graph. 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