Adding an arbitrary line to a matplotlib plot in ipython notebook

Question

I'm rather new to both python/matplotlib and using it through the ipython notebook. I'm trying to add some annotation lines to an existing graph and I can't figure out how to render the lines on a graph. So, for example, if I plot the following:

import numpy as np
np.random.seed(5)
x = arange(1, 101)
y = 20 + 3 * x + np.random.normal(0, 60, 100)
p =  plot(x, y, "o")

I get the following graph:

beautiful scatter plot

So how would I add a vertical line from (70,100) up to (70,250)? What about a diagonal line from (70,100) to (90,200)?

I've tried a few things with Line2D() resulting in nothing but confusion on my part. In R I would simply use the segments() function which would add line segments. Is there an equivalent in matplotlib?

Paul Roub · Accepted Answer · 2017-02-09 23:35:06Z

231

You can directly plot the lines you want by feeding the plot command with the corresponding data (boundaries of the segments):

plot([x1, x2], [y1, y2], color='k', linestyle='-', linewidth=2)

(of course you can choose the color, line width, line style, etc.)

From your example:

import numpy as np
import matplotlib.pyplot as plt

np.random.seed(5)
x = np.arange(1, 101)
y = 20 + 3 * x + np.random.normal(0, 60, 100)
plt.plot(x, y, "o")


# draw vertical line from (70,100) to (70, 250)
plt.plot([70, 70], [100, 250], 'k-', lw=2)

# draw diagonal line from (70, 90) to (90, 200)
plt.plot([70, 90], [90, 200], 'k-')

plt.show()

new chart

edited Feb 9, 2017 at 23:35

Paul Roub

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answered Oct 12, 2012 at 19:43

gcalmettes

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8 Comments

W.P. McNeill Over a year ago

Minor correction, the code above should read x = np.arange(1, 101).

Alexey Over a year ago

This will not draw a line, but only a segment. The question how to draw a line throw two given points remains unanswered.

Rmano Over a year ago

The problem I see that these segments will be accounted as plots, disrupting legends....

gcalmettes Over a year ago

@Rmano you can avoid the segments to be taken in account in the legend by adding a label argument starting with "_". Ex: plt.plot([70, 70], [100, 250], 'k-', lw=2, label="_not in legend")

pookie Over a year ago

The fact that 90 is used both as x2 and and y1 leads to a lot of ambiguity. For anyone viewing this, note that [70, 90] does not refer to a single point at location x1,y1. For reference, here are the meanings of the values: [x1: 70, x2: 90], [y1: 90, y2: 200]

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Curious Watcher · Accepted Answer · 2022-02-06 20:29:20Z

89

It's not too late for the newcomers.

plt.axvline(x, color='r') # vertical
plt.axhline(x, color='r') # horizontal

It takes the range of y as well, using ymin and ymax.

edited Feb 6, 2022 at 20:29

Curious Watcher

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answered Nov 21, 2014 at 22:27

Fanglin

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2 Comments

Michelle Welcks Over a year ago

The min/max parameters of axhline and axvline are scalar values between 0 and 1 that plot lines in reference to the plot's edge. Although a good tool, it's probably not a the best solution to the author's problem statement of drawing annotation lines.

Bonnie Over a year ago

This is perfect for wanting to add an annotation line in the background that spans the whole graph. If I use the chosen solution above to draw a vertical line at x=1, I have to specify the min and max y, and then the plot resizes automatically with a buffer, so the line doesn't stretch across the entire plot, and that's a hassle. This is more elegant and doesn't resize the plot.

Ozan Öğreden · Accepted Answer · 2016-08-11 09:47:19Z

43

Using vlines:

import numpy as np
np.random.seed(5)
x = arange(1, 101)
y = 20 + 3 * x + np.random.normal(0, 60, 100)
p =  plot(x, y, "o")
vlines(70,100,250)

The basic call signatures are:

vlines(x, ymin, ymax)
hlines(y, xmin, xmax)

edited Aug 11, 2016 at 9:47

Ozan Öğreden

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answered Oct 12, 2012 at 17:46

Austin Richardson

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2 Comments

JD Long Over a year ago

that's excellent. I had not seen the vline() or hline() functions. What about diagonal lines? I edited the question to add the diagonal bit now that you've shown me the h & v lines.

Austin Richardson Over a year ago

Try making a DataFrame containing the x,y coordinates and plotting them with style='k-'

Qualia · Accepted Answer · 2019-09-03 20:41:09Z

Rather than abusing plot or annotate, which will be inefficient for many lines, you can use matplotlib.collections.LineCollection:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection

np.random.seed(5)
x = np.arange(1, 101)
y = 20 + 3 * x + np.random.normal(0, 60, 100)
plt.plot(x, y, "o")

# Takes list of lines, where each line is a sequence of coordinates
l1 = [(70, 100), (70, 250)]
l2 = [(70, 90), (90, 200)]
lc = LineCollection([l1, l2], color=["k","blue"], lw=2)

plt.gca().add_collection(lc)

plt.show()

Figure with two lines plotted via LineCollection

It takes a list of lines [l1, l2, ...], where each line is a sequence of N coordinates (N can be more than two).

The standard formatting keywords are available, accepting either a single value, in which case the value applies to every line, or a sequence of M values, in which case the value for the ith line is values[i % M].

zarak · Accepted Answer · 2017-09-17 23:10:30Z

Matplolib now allows for 'annotation lines' as the OP was seeking. The annotate() function allows several forms of connecting paths and a headless and tailess arrow, i.e., a simple line, is one of them.

ax.annotate("",
            xy=(0.2, 0.2), xycoords='data',
            xytext=(0.8, 0.8), textcoords='data',
            arrowprops=dict(arrowstyle="-",
                      connectionstyle="arc3, rad=0"),
            )

In the documentation it says you can draw only an arrow with an empty string as the first argument.

From the OP's example:

%matplotlib notebook
import numpy as np
import matplotlib.pyplot as plt

np.random.seed(5)
x = np.arange(1, 101)
y = 20 + 3 * x + np.random.normal(0, 60, 100)
plt.plot(x, y, "o")


# draw vertical line from (70,100) to (70, 250)
plt.annotate("",
              xy=(70, 100), xycoords='data',
              xytext=(70, 250), textcoords='data',
              arrowprops=dict(arrowstyle="-",
                              connectionstyle="arc3,rad=0."), 
              )

# draw diagonal line from (70, 90) to (90, 200)
plt.annotate("",
              xy=(70, 90), xycoords='data',
              xytext=(90, 200), textcoords='data',
              arrowprops=dict(arrowstyle="-",
                              connectionstyle="arc3,rad=0."), 
              )

plt.show()

Example inline image

Just as in the approach in gcalmettes's answer, you can choose the color, line width, line style, etc..

Here is an alteration to a portion of the code that would make one of the two example lines red, wider, and not 100% opaque.

# draw vertical line from (70,100) to (70, 250)
plt.annotate("",
              xy=(70, 100), xycoords='data',
              xytext=(70, 250), textcoords='data',
              arrowprops=dict(arrowstyle="-",
                              edgecolor = "red",
                              linewidth=5,
                              alpha=0.65,
                              connectionstyle="arc3,rad=0."), 
              )

You can also add curve to the connecting line by adjusting the connectionstyle.

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