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A Figure containing two Axes in different subplots. Four separate subplots, in order: bar plots for x and y, scatter plot and two line plots together. Only the second Axes is cleared with the cla() function: import matplotlib.pyplot as pltįigure 3. The following example creates a Figure and then plots two Axes in two different subplots.

The elements within the Axes are not dropped, however the current Axes can be redrawn with commands in the same script. The () function clears the current Axes state without closing the Axes. An Axes has at least an X-Axis and a Y-Axis, and may have a Z-Axis. It is the data plotting area in which most of the elements in a plot are located, including Axis, Tick, Line2D, Text, etc., and it also sets the coordinates. A Figure with the same elements cleared with the clf() function:Īxes is a container class within the top-level Figure container. A Figure not cleared with the clf() function:įigure 2.

#SUBPLOT SCATTER PLOT MATPLOTLIB HOW TO#

The following example shows how to create two identical Figures simultaneously, and then apply the clf() function only to Figure 2: import matplotlib.pyplot as pltįigure 1. You can use the () function to clear the current Figure’s state. Figure includes everything visualized in a plot, including one or more Axes. Used to clear the current Axes state without closing it.įigure is the top-level container object in a matplotlib plot.

Used to clear the current Figure’s state without closing it. There are two methods available for this purpose: For more advanced use cases you can use GridSpec for a more general subplot layout or Figure.addsubplot for adding subplots at arbitrary locations within the figure. This article focuses on how to clear a plot by clearing the current Axes and Figure state of a plot, without closing the plot window. pyplot.subplots creates a figure and a grid of subplots with a single call, while providing reasonable control over how the individual plots are created. Matplotlib’s pyplot API is stateful, which means that it stores the state of objects until a method is encountered that will clear the current state.

plt.close('all') fig, ax = plt.subplots(1, figsize=(12,6)) # plot and labels sc = ax.scatter(x,y) plt.xlabel(x_name) plt.ylabel(y_name) # cursor grid lines lnx = plt.plot(,, color='black', linewidth=0.3) lny = plt.plot(,, color='black', linewidth=0.3) lnx.set_linestyle('None') lny.set_linestyle('None') # annotation annot = ax.annotate("", xy=(0,0), xytext=(5,5),textcoords="offset points") t_visible(False) # xy limits plt.xlim(x.min()*0.95, x.max()*1.05) plt.ylim(y.min()*0.95, y.max()*1.05) def hover(event): # check if event was in the axis if event.inaxes = ax: # draw lines and make sure they're visible lnx.set_data(, ) lnx.set_linestyle('-') lny.set_data(, ) lny.set_linestyle('-') lnx.set_visible(True) lny.set_visible(True) # get the points contained in the event cont, ind = sc.contains(event) if cont: # change annotation position annot.xy = (event.xdata, event.ydata) # write the name of every point contained in the event t_text("".format(', '.join( for n in ind]))) t_visible(True) else: t_visible(False) else: lnx.set_visible(False) lny.set_visible(False) _connect("motion_notify_event", hover) plt.Matplotlib is a data visualization and graphical plotting library for Python. When it is, we change the text, position, and visibility of the annotation accordingly. We’ll create a blank annotation and check if the mouse position is over one of the plotted points. Great! We know how to add and modify elements in our plot and detect the movement of the cursor. The event we receive from mpl_connect at our hover function has some valuable properties let’s try to get the XY coordinates of the mouse. So even if some element is only displayed when a specific event is triggered, we still should define it outside of our function. The idea is to draw the chart with all the elements we’ll use and then use the events to modify those elements.