The first step is to import matplotlib, which will be used to plot data on graphs:
import matplotlib.pyplot as plt
This function is used to plot a graph:
plt.plot(x,y)
There can be many parameters for this function defining its styles. We have to provide at least x and y coordinates.
This method returns a 2D graph.
class matplotlib.lines.Line2D(xdata, ydata, linewidth=None, linestyle=None, color=None, marker=None, markersize=None, markeredgewidth=None, markeredgecolor=None, markerfacecolor=None, markerfacecoloralt='none', fillstyle=None, antialiased=None, dash_capstyle=None, solid_capstyle=None, dash_joinstyle=None, solid_joinstyle=None, pickradius=5, drawstyle=None, markevery=None, **kwargs)
We can create test data that will be used as shown in the example below. We can get the output by clicking the “Run” button.
import matplotlib.pyplot as plt# datasets x and y are lists, but they can also be, for instance, numpy arrays or pd.Series.x = [1, 2, 3, 4, 5]y = [25, 32, 34, 20, 25]# plotplt.plot(x, y)
In the code above:
Lines 5 and 6: We define x and y coordinates.
Line 8: We call the built-in function of matplotlib to plot a graph.
The output can be enhanced by changing its styles and colors, and parameters can be passed to the plt.plot(parameters..) function to depict the different styles. We can get the updated output by clicking the “Run” button in the example below:
import matplotlib.pyplot as plt# datasets x and y are lists, but they can also be, for instance, numpy arrays or pd.Series.x = [1, 2, 3, 4, 5]y = [25, 32, 34, 20, 25]# plotplt.plot(x, y, color='red' , marker='o', markersize=20, linestyle='--', linewidth=4)
In the code above:
matplotlib to plot a graph with different parameters for our styling.Free Resources