To customize the axes, we can modify properties such as the labels, tick marks, and their appearance. For example, to set custom labels for the x-axis and y-axis, use the 'xlabel()' and 'ylabel()' functions, re
ax2.set_xlim([0,T]) # This just reverses the y-tick marks. ticks=list(range(0,T+1,50)) ax2.set_yticks(ticks) ax2.set_yticklabels(ticks[::-1]) ax2.margins(0) forcptincpts: ax1.axvline(cpt,c='r',ls='dotted') ax2.axvline(cpt,c='r',ls='dotted') plt.tight_layout...
df7273747576def timestamp2datetime(value):77value =time.localtime(value)78dt = time.strftime('%Y-%m-%d %H:%M:%S', value)79returndt8081828384'''85frommatplotlib import pyplotasplt86tt = data['context_timestamp']87plt.plot(tt)88# 可以看出时间是没有排好的,有一定的错位。如果做成online的模...
Matplotlibis one of the most widely used data visualization libraries in Python. Much of Matplotlib's popularity comes from its customization options - you can tweak just about any element from itshierarchy of objects. In this tutorial, we'll take a look at how tochange the tick frequency in...