Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. Pyplot is a state-based interface to a Matplotlib module which provides a MATLAB-like interface. There are various plots which can be used in Pyplot are Line Plot, Contour, Histogram, Scatter, 3D Plot, etc.
matplotlib.pyplot.subplots_adjust() Function
The subplots_adjust() function in pyplot module of matplotlib library is used to tune the subplot layout.
Syntax: matplotlib.pyplot.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=None, hspace=None)
Parameters: This method accept the following parameters that are described below:
- left : This parameter is the left side of the subplots of the figure.
- right : This parameter is the right side of the subplots of the figure.
- bottom : This parameter is the bottom of the subplots of the figure.
- top : This parameter is the top of the subplots of the figure.
- wspace : This parameter is the amount of width reserved for space between subplots expressed as a fraction of the average axis width.
- hspace : This parameter is the amount of height reserved for space between subplots expressed as a fraction of the average axis height.
Below examples illustrate the matplotlib.pyplot.subplots_adjust() function in matplotlib.pyplot:
Example 1:
# Implementation of matplotlib function import matplotlib.pyplot as plt x = [1, 12, 3, 9] y = [1, 4, 9, 16] labels = ['Geeks1', 'Geeks2', 'Geeks3', 'Geeks4'] plt.plot(x, y) plt.xticks(x, labels, rotation ='vertical') plt.margins(0.2) plt.subplots_adjust(bottom = 0.15) plt.title('matplotlib.pyplot.subplots_adjust() Example') plt.show() |
Output:
Example 2:
# Implementation of matplotlib function import numpy as np import matplotlib.pyplot as plt from matplotlib.widgets import TextBox fig, ax = plt.subplots() plt.subplots_adjust(bottom = 0.2) t = np.arange(-2.0, 2.0, 0.001) s = np.sin(t)+np.cos(2 * t) initial_text = "sin(t) + cos(2t)"l, = plt.plot(t, s, lw = 2) def submit(text): ydata = eval(text) l.set_ydata(ydata) ax.set_ylim(np.min(ydata), np.max(ydata)) plt.draw() axbox = plt.axes([0.4, 0.05, 0.3, 0.075]) text_box = TextBox(axbox, 'Formula Used : ', initial = initial_text) text_box.on_submit(submit) fig.suptitle('matplotlib.pyplot.subplots_adjust() Example') plt.show() |
Output:
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