# How can Matplotlib be used to create multiple plots iteratively in Python?

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Matplotlib is a popular Python package that is used for data visualization. Visualizing data is a key step since it helps understand what is going on in the data without actually looking at the numbers and performing complicated computations. It helps in communicating the quantitative insights to the audience effectively.

Matplotlib is used to create 2 dimensional plots with the data. It comes with an object oriented API that helps in embedding the plots in Python applications. Matplotlib can be used with IPython shells, Jupyter notebook, Spyder IDE and so on.

It is written in Python. It is created using Numpy, which is the Numerical Python package in Python.

Python can be installed on Windows using the below command −

pip install matplotlib

The dependencies of Matplotlib are −

Python ( greater than or equal to version 3.4)
NumPy
Setuptools
Pyparsing
Libpng
Pytz
Free type
Six
Cycler
Dateutil

Let us understand how Matplotlib can be used to multiple plots in the same plot iteratively −

## Example

import numpy as np
import matplotlib.pyplot as plt

fig = plt.figure()
ax1.set_ylabel('Y−axis')
ax1.set_title('A simple plot')

t = np.arange(0.0, 1.0, 0.01)
s = np.sin(2*np.pi*t)
line, = ax1.plot(t, s, color='blue', lw=2)
np.random.seed(4567232)

ax2 = fig.add_axes([0.15, 0.1, 0.8, 0.3])
n, bins, patches = ax2.hist(np.random.randn(1000), 50,
facecolor='yellow', edgecolor='green')
ax2.set_xlabel('x−label')
plt.show()

## Output ## Explanation

• The required packages are imported and its alias is defined for ease of use.

• An empty figure is created using the ‘figure’ function.

• The ‘subplot’ function is used to create an area to plot the graph.

• The data values are created using the NumPy library.

• The ‘random’ library’s ‘seed’ function is used to create data points.

• The ‘add_subplot’ is used to create another new subplot to the newly created plot.

• The data is plotted using the ‘plot’ function.

• The set_xlabel, set_ylabel and set_title functions are used to provide labels for ‘X’ axis, ‘Y’ axis and title.

• It is shown on the console using the ‘show’ function.