You would need to do the same for the y axis and also for minor ticks in case it's needed. Note that in the above I only changed the ticker for the x axis and also only for the major ticks.

So, you can create a figure and then set the desired axis as the current axis using plt.sca. Xfmt = ()Ī_major_formatter(xfmt)Īxes.plot(np.random.randn(10)*100+100, np.linspace(-3,3,10), matplotlib xgboost shap Share Improve this question Follow asked 12 hours ago There 494 6 18 Add a comment 1 Answer Sorted by: 0 Looking at the source code, the function does not create it's own figure. Add a subplot to the current figure, with nrows2, ncols1, at index1 (ax0) Using twinx () method, create a twin of axes with a shared X-axis but independent Y-axis (ax1). # The new ticker needs new locator and formatters To share secondary Y-axis between subplots in matplotlib, we can take the following steps Create x for data points. # Now remove axes from the grouper for xaxisĪxes.get_shared_x_axes().remove(axes) 1 Hello, Im trying to build an orthogonal-views volume viewer in Matplotlib like this one: For this to work, I need to share the y-axis of the YZ (right) view/subplot with the x-axis of the XZ (bottom) view/subplot. The parameter nrows is used to indicate the number of rows and the parameter ncols is used to indicate the number of columns of the subplot grid. set a new Ticker with the respective new locator and formatterįig, axes = plt.subplots(3, 4, sharex='row', sharey='row', squeeze=False)Īx.plot(*np.random.randn(2,10), marker='o', ls='').The problem is (as points out) that the ticker is still the same for all axes. As points out in the their answer, you can use ax.get_shared_x_axes() to obtain a Grouper object that contains all the linked axes, and then. Normally, each of these subplots has their own x-axis and y-axis, because they often have significantly varying data, hence there is no need to share any of.

Matplotlib subplot share y