If you use the matplotlib object-oriented approach, this is a simple task using ax.set_xticklabels() and ax.set_yticklabels(). Here we can just set them to an empty list to remove any labels: import matplotlib.pyplot as plt # Create Figure and Axes instances fig,ax = plt.subplots(1) # Make your plot, set your axes labels ax.plot(sim_1[‘t’],sim_1[‘V’],’k’) ax.set_ylabel(‘V’) ax.set_xlabel(‘t’) # … Read more
The names of objects Matplotlib is strongly object oriented and its principal objects are the figure and the axes (I find the name axes a bit misleading, but probably it’s just me). You can think of the figure as a canvas, of which you typically specify the dimensions and possibly e.g., the background color etc … Read more
I usually use the second one of these: from matplotlib.pyplot import cm import numpy as np #variable n below should be number of curves to plot #version 1: color = cm.rainbow(np.linspace(0, 1, n)) for i, c in zip(range(n), color): plt.plot(x, y, c=c) #or version 2: color = iter(cm.rainbow(np.linspace(0, 1, n))) for i in range(n): c … Read more
To plot multiple graphs on the same figure you will have to do: from numpy import * import math import matplotlib.pyplot as plt t = linspace(0, 2*math.pi, 400) a = sin(t) b = cos(t) c = a + b plt.plot(t, a, ‘r’) # plotting t, a separately plt.plot(t, b, ‘b’) # plotting t, b separately … Read more
In matplotlib versions >= 1.5, you can print the rcParam called axes.prop_cycle: print(plt.rcParams[‘axes.prop_cycle’].by_key()[‘color’]) # [u’#1f77b4′, u’#ff7f0e’, u’#2ca02c’, u’#d62728′, u’#9467bd’, u’#8c564b’, u’#e377c2′, u’#7f7f7f’, u’#bcbd22′, u’#17becf’] Or equivalently, in python2: print plt.rcParams[‘axes.prop_cycle’].by_key()[‘color’] In versions < 1.5, this was called color_cycle: print plt.rcParams[‘axes.color_cycle’] # [u’b’, u’g’, u’r’, u’c’, u’m’, u’y’, u’k’] Note that the default color cycle changed … Read more
Just use import matplotlib.pyplot as plt plt.show() This command tells the system to draw the plot in Pycharm. Example: plt.imshow(img.reshape((28, 28))) plt.show()
You can pass just left or right to set_xlim: plt.gca().set_xlim(left=0) For the y axis, use bottom or top: plt.gca().set_ylim(bottom=0)
Change your subplot settings to: plt.subplot(1, 2, 1) … plt.subplot(1, 2, 2) The parameters for subplot are: number of rows, number of columns, and which subplot you’re currently on. So 1, 2, 1 means “a 1-row, 2-column figure: go to the first subplot.” Then 1, 2, 2 means “a 1-row, 2-column figure: go to the … Read more
This FutureWarning isn’t from Pandas, it is from numpy, here’s how to reproduce the warning nearer to the source of the trouble: import numpy as np print(np.__version__) # Numpy version ‘1.12.0’ ‘x’ in np.arange(5) #Future warning thrown here FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison False Another … Read more
When plotting a plot using matplotlib: How to remove the box of the legend? plt.legend(frameon=False) How to change the color of the border of the legend box? leg = plt.legend() leg.get_frame().set_edgecolor(‘b’) How to remove only the border of the box of the legend? leg = plt.legend() leg.get_frame().set_linewidth(0.0) For the matplotlib object oriented approach: axes.legend(frameon=False) leg … Read more