We will learn about the scatter plot from the matplotlib library. It is used for plotting various plots in Python like scatter plot, bar charts, pie charts, line plots, histograms, 3-D plots and many more. That suggestion likely working is supported by testing in Jupyter sessions provided by the MyBInder service launched from here where the steps to install scanpy under here were followed and then the first couple of code cells in the included 'analysis-visualization-spatial.ipynb' run to define an annotated data matrix adata, before using this code to test the plotting of a scatter plot like OP was using: ax = sc.pl. Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. (You can leave off the semi-colon if the ax.set_ylim(0,50) won't be the last line in a Jupyter cell.) works for sc.pl.rank_genes_groups_violin().)Īpplying that to your case, I suggest you should use: ax = sc.pl.scatter(adata, x = 'total_counts', y='pct_counts_mt',show=False) (ivirshup had show=False in use there however, I didn't pick up on that until seeing Workhorse's comment and what is returned by .scatter isn't iterable so that the use of for ax. Scatter plots where one axis is categorical. Adding in show=False will get a matplotlib axes object ( matplotlib.axes._axes.Axes) returned that can then be adjusted using ax.set_ylim(), similar to ivirshup's suggestion here. Matplotlib 3.7.1 documentation Skip to main content Plot types Examples Tutorials Reference User guide Develop Releases stable Section Navigation matplotlib matplotlib.afm matplotlib.animation matplotlib.artist matplotlib. Scatter plots can be made using any type of cartesian axis, including linear, logarithmic, categorical or date axes. I had been seeing the sc.pl.scatter() based on something like the OP had was returning nothing. from matplotlib import pyplot as plt from mpltoolkits.mplot3d import Axes3D fig plt.figure () ax fig.addsubplot (111, projection'3d') data np.random.rand (3, 100) x, y, z data for show c np.arange (len (x)) / len (x) create some colours p ax.scatter (x, y, z, cplt.cm.magma (0.5c)) ax.setxlabel ('\psi1') ax. Looking at the .scatter documentation, it seems the equivalent is the show setting. ![]() ![]() The key that I found to making this work is based on a note in Workhorse's comment under here in which they noted you needed the setting return_fig=True for sc.pl.dotplot(). Make a scatter plot of x vs y, where x and y are sequence like objects of the same length. Suggest you should try: ax = sc.pl.scatter(adata, x = 'total_counts', y='pct_counts_mt',show=False)
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