#### Python library Matplotlib

Matplotlib is a plotting library in Python. In this section we give a brief introduction to the `matplotlib.pyplot` module, which provides a plotting system similar to that of MATLAB. This is basically a library for 2-dimensional plotting with Python.

Matplotlib comes with a wide variety of graphical plots such as line plot, bar plot, histogram, scatter plot etc. Graphical plots helps us to understand trends, patterns, and to make correlations. They are really useful for getting quantitative information. Some of the sample plots are covered here.

#### 1. Line Plot

The most important function in matplotlib is `plot()`, which allows us to plot 2D data using line plotting. See the example below:

`import matplotlib.pyplot as plt# X-axes values x = [50, 20, 80, 40, 70] # Y-axes values y = [90, 50, 70, 30, 20] # Function to plot plt.plot(x,y) # Function to show the plot plt.show()`

Output: We can also plot multiple lines at once, and add a title, legend, and axis labels. See such an example of line plot below.

`import numpy as npimport matplotlib.pyplot as plt# Compute the x and y coordinates for points on a sine curvex = np.arange(0, 3 * np.pi, 0.1)y_sin = np.sin(x)y_cos = np.cos(x)# Plot the points using matplotlibplt.plot(x, y_sin)plt.plot(x, y_cos)plt.xlabel('x axes label')plt.ylabel('y axes label')plt.title('Sine and Cosine')plt.legend(['Sine', 'Cosine'])plt.show() # We must call plt.show() to make graphics appear`

Output: #### 2. Bar Plot

We can create bar plot with pyplot.bar(). See the example below:

`import matplotlib.pyplot as plt# X-axes values x = [6, 3, 9, 5, 7] # Y-axes values y = [10, 5, 8, 4, 2] # Function to bar plt.bar(x, y) # Function to show the plot plt.show() `

Output: #### 3. Histogram Plot

We can create histogram plot with pyplot.hist(). See the example below:

`import matplotlib.pyplot as plt# Y-axes values y = [9, 5, 7, 4, 2]   # Function to bar plt.hist(y)   # Function to show the plot plt.show() `

Output: #### 4. Scatter Plot

We can create scatter plot with pyplot.scatter(). See the example below:

`from matplotlib import pyplot as plt # X-axes values x = [6, 2, 9, 4, 5] # Y-axes values y = [9, 6, 7, 6, 3] # Function to plot scatter plt.scatter(x, y) # Function to show the plot plt.show() `

Output: 