matplotlib: make plots in functions and then add each to a single subplot figure

Question

I haven't been able to find a solution to this.. Say I define some plotting function so that I don't have to copy-paste tons of code every time I make similar plots...

What I'd like to do is use this function to create a few different plots individually and then put them together as subplots into one figure. Is this even possible? I've tried the following but it just returns blanks:

import numpy as np import matplotlib.pyplot as plt  # function to make boxplots def make_boxplots(box_data):      fig, ax = plt.subplots()      box = ax.boxplot(box_data)      #plt.show()      return ax  # make some data: data_1 = np.random.normal(0,1,500) data_2 = np.random.normal(0,1.1,500)  # plot it box1 = make_boxplots(box_data=data_1) box2 = make_boxplots(box_data=data_2)  plt.close('all')  fig, ax = plt.subplots(2)  ax[0] = box1 ax[1] = box2  plt.show() 

Answer 1

I tend to use the following template

def plot_something(data, ax=None, **kwargs):     ax = ax or plt.gca()     # Do some cool data transformations...     return ax.boxplot(data, **kwargs) 

Then you can experiment with your plotting function by simply calling plot_something(my_data) and you can specify which axes to use like so.

fig, (ax1, ax2) = plt.subplots(2) plot_something(data1, ax1, color='blue') plot_something(data2, ax2, color='red') 

Adding the kwargs allows you to pass in arbitrary parameters to the plotting function such as labels, line styles, or colours.

The line ax = ax or plt.gca() uses the axes you have specified or gets the current axes from matplotlib (which may be new axes if you haven't created any yet).