tabular legend layout for matplotlib

ε祈祈猫儿з 提交于 2019-11-28 12:15:14

Not a very easy question but I figured it out. The trick I use is to initialize an empty rectangle which acts as a handle. These additional empty handles are used to construct the table. I get rid of any excessive space using handletextpad:

import numpy
import pylab
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle

fig = plt.figure()
ax = fig.add_subplot(111)

im1 ,= ax.plot(range(10), pylab.randn(10), "r--")
im2 ,= ax.plot(range(10), pylab.randn(10), "g--")
im3 ,= ax.plot(range(10), pylab.randn(10), "b--")
im4 ,= ax.plot(range(10), pylab.randn(10), "r.")
im5 ,= ax.plot(range(10), pylab.randn(10), "g.")
im6 ,= ax.plot(range(10), pylab.randn(10), "b.")
im7 ,= ax.plot(range(10), pylab.randn(10), "r^")
im8 ,= ax.plot(range(10), pylab.randn(10), "g^")
im9 ,= ax.plot(range(10), pylab.randn(10), "b^")

# create blank rectangle
extra = Rectangle((0, 0), 1, 1, fc="w", fill=False, edgecolor='none', linewidth=0)

#Create organized list containing all handles for table. Extra represent empty space
legend_handle = [extra, extra, extra, extra, extra, im1, im2, im3, extra, im4, im5, im6, extra, im7, im8, im9]

#Define the labels
label_row_1 = [r"$f_{i,j}$", r"$i = 1$", r"$i = 2$", r"$i = 3$"]
label_j_1 = [r"$j = 1$"]
label_j_2 = [r"$j = 2$"]
label_j_3 = [r"$j = 3$"]
label_empty = [""]

#organize labels for table construction
legend_labels = numpy.concatenate([label_row_1, label_j_1, label_empty * 3, label_j_2, label_empty * 3, label_j_3, label_empty * 3])

#Create legend
ax.legend(legend_handle, legend_labels, 
          loc = 9, ncol = 4, shadow = True, handletextpad = -2)

plt.show()

If you need to create a readable table, you can use PrettyTable module

For example in python2.7 this code

from prettytable import PrettyTable

x = PrettyTable(["City name", "Area", "Population", "Annual Rainfall"])
x.align["City name"] = "l" # Left align city names
x.padding_width = 1 # One space between column edges and contents (default)
x.add_row(["Adelaide",1295, 1158259, 600.5])
x.add_row(["Brisbane",5905, 1857594, 1146.4])
x.add_row(["Darwin", 112, 120900, 1714.7])
x.add_row(["Hobart", 1357, 205556, 619.5])
x.add_row(["Sydney", 2058, 4336374, 1214.8])
x.add_row(["Melbourne", 1566, 3806092, 646.9])
x.add_row(["Perth", 5386, 1554769, 869.4])
print x

Can produce this output:

+-----------+------+------------+-----------------+
| City name | Area | Population | Annual Rainfall |
+-----------+------+------------+-----------------+
| Adelaide  | 1295 |  1158259   |      600.5      |
| Brisbane  | 5905 |  1857594   |      1146.4     |
| Darwin    | 112  |   120900   |      1714.7     |
| Hobart    | 1357 |   205556   |      619.5      |
| Sydney    | 2058 |  4336374   |      1214.8     |
| Melbourne | 1566 |  3806092   |      646.9      |
| Perth     | 5386 |  1554769   |      869.4      |
+-----------+------+------------+-----------------+
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