First, I feel weird posting an answer against the co-lead developer of matplotlib. Obviously, @tacaswell knows matplotlib far better than I ever will. But at the same time, his answer wasn't dynamic enough for me. I needed a caption that would always be based on the position of the xlabel, and couldn't just use text annotations.
I considered simply changing the xlabel to add a newline and the caption text, but that wouldn't clearly differentiate the caption, and
you can't do things like change the text size or make it italic in the middle of a text string.
I solved this by using matplotlib's TeX capabilities. Here's my solution:
from matplotlib import pyplot as plt
from matplotlib import rc
import numpy as np
from pylab import *
rc['text', usetex=True]
file = open['distribution.txt', 'r']
txt="I need the caption to be present a little below X-axis"
x=[]
y=[]
for line in file:
new=line.rstrip[]
mystring=new.split["\t"]
x.append[mystring[0]]
y.append[mystring[1]]
fig = plt.figure[]
ax1 = fig.add_axes[[0.1,0.4,0.8,0.5]]
ax1.set_title["This is my title"]
ax1.set_xlabel[r'\begin{center}X-axis\\*\textit{\small{' + txt + r'}}\end{center}']
ax1.set_ylabel['Y-axis']
ax1.scatter[x,y, c='r']
plt.xlim[0, 1.05]
plt.ylim[0, 2.5]
plt.show[]
I did the same thing with the random scatter plot from tacaswell's answer, and here's my result:
One warning: if you tweak this to take input string variables, the strings may not be properly escaped for use with TeX. Escaping LaTeX code is already covered on Stack Overflow, at //stackoverflow.com/a/25875504/1404311 . I used that directly, and then could take arbitrary xlabels and captions.
To add caption below X-axis for a scatter plot, we can use text[] method for the current figure.
Steps
Create x and y data points using numpy.
Create a new figure or activate an existing figure using figure[] method.
Plot the scatter points with x and y data points.
To add caption to the figure, use text[] method.
Adjust the padding between and around the subplots.
To display the figure, use show[] method.
Example
import numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = np.random.rand[10] y = np.random.rand[10] fig = plt.figure[] plt.scatter[x, y, c=y] fig.text[.5, .0001, "Scatter Plot", ha='center'] plt.tight_layout[] plt.show[]
Output
Updated on 06-May-2021 13:00:19
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Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.
Matplotlib.pyplot.title[]
The title[] method in matplotlib module is used to specify title of the visualization depicted and displays the title using various attributes.
Syntax: matplotlib.pyplot.title[label, fontdict=None, loc=’center’, pad=None, **kwargs]
Parameters:
label[str]: This argument refers to the actual title text string of the visualization depicted.fontdict[dict] : This argument controls the appearance of the text such as text size, text alignment etc. using a dictionary. Below is the default fontdict:fontdict = {‘fontsize’: rcParams[‘axes.titlesize’],
‘fontweight’ : rcParams[‘axes.titleweight’],
‘verticalalignment’: ‘baseline’,
‘horizontalalignment’: loc}loc[str]: This argument refers to the location of the title, takes string values like'center','left'and'right'.pad[float]: This argument refers to the offset of the title from the top of the axes, in points. Its default values in None.- **kwargs: This argument refers to the use of other keyword arguments as text properties such as
color,fonstyle,linespacing,backgroundcolor,rotationetc.Return Type: The
title[]method returns a string that represents the title text itself.
Below are some examples to illustrate the use of title[] method:
Example 1: Using matplotlib.pyplot to depict a linear graph and display its title using matplotlib.pyplot.title[].
Python3
import matplotlib.pyplot as plt
y =
[0,1,2,3,4,5]
x= [0,5,10,15,20,25]
plt.plot[x, y, color='green']
plt.xlabel['x']
plt.ylabel['y']
plt.title["Linear graph"]
plt.show[]
Output:
In the above example, only the label argument is assigned as “Linear graph” in the title[] method and the other parameters are assigned to their default values. Assignment of the label argument is the minimum requirement to display the title of a visualization.
Example 2: Using matplotlib.pyplot to depict a ReLU function graph and display its title using
matplotlib.pyplot.title[].
Python3
import matplotlib.pyplot as plt
x = [-5,-4,-3,-2,-1,0,1,2, 3, 4, 5]
y = []
for i in range[len[x]]:
y.append[max[0,x[i]]]
plt.plot[x, y, color='green']
plt.xlabel['x']
plt.ylabel['y']
plt.title[label="ReLU function graph",
fontsize=40,
color="green"]
Output:
The above program illustrates the use of label argument, fontsize key of the fontdict argument and color argument which
is an extra parameter[due to **kwargs] which changes the color of the text.
Example 3: Using matplotlib.pyplot to depict a bar graph and display its title using matplotlib.pyplot.title[].
Python3
import matplotlib.pyplot as plt
import numpy as np
language = ['C','C++','Java','Python']
users = [80,60,130,150]
index =
np.arange[len[language]]
plt.bar[index, users, color='green']
plt.xlabel['Users']
plt.ylabel['Language']
plt.xticks[index, language]
plt.title[label='Number of Users of a particular Language',
fontweight=10,
pad='2.0']
Output:
Here, the
fontweight key of the fontdict argument and pad argument is used in the title[] method along with the label parameter.
Example 4: Using matplotlib.pyplot to depict a pie chart and display its title using matplotlib.pyplot.title[].
Python3
from matplotlib import pyplot as plt
foodPreference = ['Vegetarian', 'Non Vegetarian',
'Vegan', 'Eggitarian']
consumers =
[30,100,10,60]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.axis['equal']
ax.pie[consumers, labels = foodPreference,
autopct='%1.2f%%']
plt.title[label="Society Food Preference",
loc="left",
fontstyle='italic']
Output:
In the above data visualization of the pie chart, label, fontweight
keyword from fontdict and fontstyle[**kwargs] argument[takes string values such as 'italic', 'bold' and 'oblique'] is used in the title[] method to display the title of the pie chart.
Example 5: Using matplotlib.pyplot to visualize a signal in a graph and display
its title using matplotlib.pyplot.title[].
Python3
from matplotlib import pyplot
import numpy
signalTime = numpy.arange[0, 100, 0.5];
signalAmplitude = numpy.sin[signalTime]
pyplot.plot[signalTime, signalAmplitude, color ='green']
pyplot.xlabel['Time']
pyplot.ylabel['Amplitude']
pyplot.title["Signal",
loc='right',
rotation=45]
Output:
Here, the label argument is assigned to 'signal' , loc argument is assigned to 'right' and the rotation argument [**kwargs] which takes angle value in degree is assigned to 45 degrees.
Example 6: Using matplotlib.pyplot to show an image and display its title using matplotlib.pyplot.title[].
Python3
from PIL import
ImageTk, Image
from matplotlib import pyplot as plt
testImage = Image.open['g4g.png']
plt.title["Geeks 4 Geeks",
fontsize='20',
backgroundcolor='green',
color='white']
plt.imshow[testImage]
Output:
In
the above example, the title of an image is displayed using the title[] method having arguments label as "Geeks 4 Geeks", fontsize key from fontdict as '20', backgroundcolor and color are extra parameters having string values 'green' and 'white' respectively.