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# Matplotlib.pyplot.plot() function in Python

Matplotlib is a library in Python and it is numerical â€“ 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.plot() Function

The plot() function in pyplot module of matplotlib library is used to make a 2D hexagonal binning plot of points x, y.

Syntax: matplotlib.pyplot.plot(\*args, scalex=True, scaley=True, data=None, \*\*kwargs)

Parameters: This method accept the following parameters that are described below:

• x, y: These parameter are the horizontal and vertical coordinates of the data points. x values are optional.
• fmt: This parameter is an optional parameter and it contains the string value.
• data: This parameter is an optional parameter and it is an object with labelled data.

Returns: This returns the following:

• lines : This returns the list of Line2D objects representing the plotted data.
• Below examples illustrate the matplotlib.pyplot.plot() function in matplotlib.pyplot:

Example 1:

 # Implementation of matplotlib function       import matplotlib.pyplot as plt import numpy as np     plt.plot([1, 2, 3]) plt.title('matplotlib.pyplot.plot() example 1') plt.draw() plt.show()

Output:

Example 2:

 # Implementation of matplotlib function     import matplotlib.pyplot as plt import numpy as np     # Fixing random state for reproducibility np.random.seed(19680801)     # create random data xdata = np.random.random([2, 10])     # split the data into two parts xdata1 = xdata[0, :] xdata2 = xdata[1, :]     # sort the data so it makes clean curves xdata1.sort() xdata2.sort()     # create some y data points ydata1 = xdata1 ** 2ydata2 = 1 - xdata2 ** 3    # plot the data plt.plot(xdata1, ydata1, color ='tab:blue') plt.plot(xdata2, ydata2, color ='tab:orange')         # set the limits plt.xlim([0, 1]) plt.ylim([0, 1])   plt.title('matplotlib.pyplot.plot() example 2')     # display the plot plt.show()

Output: