In this section of the tutorial, you’ll become familiar with creating basic scatter plots using Matplotlib. You can use scatter plots to explore the relationship between two variables, for example by looking for any correlation between them. fig, (ax1, ax2) = plt.subplots(2, figsize=(9,6))Īx1.plot(xs, rawsignal) # plot rawsignal in the first AxesĪx1.set(title='Signal') # set the title of the first AxesĪx2.plot(abs(fft)) # plot FFT in the second AxesĪx2.set(ylim=(0, 100), title='FFT') # set title and y-limit of the second Axesīoth sets of codes produce the same following output. A scatter plot is a visual representation of how two variables relate to each other. Axes instances define set() method which can be used to set a whole host of properties including y-limit/title etc. Which is a plot which axis limits varies from (-1, 1) in both x and y, with a margin set with this piece of code: plt.figure () plt.show (data) Add some margin l, r, b, t plt.axis () dx, dy r-l, t-b plt.axis ( l-0.1dx, r+0.1dx, b-0.1dy, t+0.1dy) The problem is 'cause I have more 'complex' plot in which some changes had to me made. Then again, using the object-oriented interface is less verbose and clearer. Plt.subplot(2, 1, 1, title='Signal') # first subplot You can control the limits of X and Y axis of your plots using matplotlib function plt.xlim() and plt.ylim(). Here we’ll cover different examples related to the set axis range using matplotlib. Plt.figure(figsize=(9,6)) # create figure Basic Scatterplot with Defined Axis Limits. In this Python Matplotlib tutorial, we’ll discuss the Matplotlib set axis range. It's also possible to set ylim/ xlim at the time of adding a subplot to the existing figure instance ( plt.subplot admits ylim= argument).
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