✅ Updated with bonus resources and guidesĭata Visualization in Python with Matplotlib and Pandas is a book designed to take absolute beginners to Pandas and Matplotlib, with basic Python knowledge, and allow them to build a strong foundation for advanced work with these libraries - from simple plots to animated 3D plots with interactive buttons. ✅ Updated regularly for free (latest update in April 2021) ✅ 30-day no-question money-back guarantee Then, you can set styles, such as linestyles or colors, which accept the typical Matplotlib styling options.

We've set them to be from 0 to 1, since that's the distribution of the np.random.rand() call as well.

Then, the ymin and ymax arguments - these are the height of the lines. We've supplied, marking two points, though you can go from 0.n points here. The vlines() function accepts a few arguments - a scalar, or 1D array of X-values that you'd like to draw lines on. Let's start off with the vlines() function: import matplotlib.pyplot as pltĪx.vlines(, 0, 1, linestyles= 'dashed', colors= 'red') Draw Vertical Lines on Matplotlib Plot with PyPlot.vlines() Naturally, you can also call these methods on the Axes object. There are two ways we can draw lines, using the vlines() or axvline() functions of the PyPlot instance. For example, let's draw vertical lines on the 20 and 100 marks. Now, since we've set a seed, we can replicate this random image as many times as we'd like.

Matplotlib annotate vertical line