Solar wind in situ data suitable for machine learning (python numpy arrays): STEREO-A/B, Wind, Parker Solar Probe, Ulysses, Venus Express, MESSENGER

**work in progress** don't use yet!<br>These are solar wind in situ data arrays in python pickle suitable for machine learning, i.e. the arrays consist only of numbers, no strings, no datetime objects.<br>Made with https://github.com/cmoestl/heliocats <br><br>Load in python with e.g.:<br>&gt; import pickle&gt; filepsp='psp_2018_2019_numpy.p'&gt; [psp,hpsp]=pickle.load(open(filepsp, "rb" ) ) <br>plot time vs total field&gt; import matplotlib.pyplot as plt&gt; plt.plot(psp[:,0],psp[:,1])<br><br>Times psp[:,0 ]are in matplotlib format. Variable 'hpsp' contains a header with the variable names for each column.<br><br>