Welcome to the exercises for reviewing matplotlib! Take your time with these, Matplotlib can be tricky to understand at first. These are relatively simple plots, but they can be hard if this is your first time with matplotlib, feel free to reference the solutions as you go along.
Also don't worry if you find the matplotlib syntax frustrating, we actually won't be using it that often throughout the course, we will switch to using seaborn and pandas built-in visualization capabilities. But, those are built-off of matplotlib, which is why it is still important to get exposure to it!
NOTE: ALL THE COMMANDS FOR PLOTTING A FIGURE SHOULD ALL GO IN THE SAME CELL. SEPARATING THEM OUT INTO MULTIPLE CELLS MAY CAUSE NOTHING TO SHOW UP.
Follow the instructions to recreate the plots using this data:
In [45]:
import numpy as np
x = np.arange(0,100)
y = x*2
z = x**2
Import matplotlib.pyplot as plt and set %matplotlib inline if you are using the jupyter notebook. What command do you use if you aren't using the jupyter notebook?
In [46]:
import matplotlib.pyplot as plt
%matplotlib inline
# plt.show() for non-notebook users
In [47]:
fig = plt.figure()
ax = fig.add_axes([0,0,1,1])
ax.plot(x,y)
ax.set_xlabel('x')
ax.set_ylabel('y')
ax.set_title('title')
Out[47]:
In [48]:
fig = plt.figure()
ax1 = fig.add_axes([0,0,1,1])
ax2 = fig.add_axes([0.2,0.5,.2,.2])
Now plot (x,y) on both axes. And call your figure object to show it.
In [49]:
ax1.plot(x,y)
ax1.set_xlabel('x')
ax1.set_ylabel('y')
ax2.plot(x,y)
ax2.set_xlabel('x')
ax2.set_ylabel('y')
fig # Show figure object
Out[49]:
In [50]:
fig = plt.figure()
ax = fig.add_axes([0,0,1,1])
ax2 = fig.add_axes([0.2,0.5,.4,.4])
Now use x,y, and z arrays to recreate the plot below. Notice the xlimits and y limits on the inserted plot:
In [51]:
ax.plot(x,z)
ax.set_xlabel('X')
ax.set_ylabel('Z')
ax2.plot(x,y)
ax2.set_xlabel('X')
ax2.set_ylabel('Y')
ax2.set_title('zoom')
ax2.set_xlim(20,22)
ax2.set_ylim(30,50)
fig
Out[51]:
In [52]:
# Empty canvas of 1 by 2 subplots
fig, axes = plt.subplots(nrows=1, ncols=2)
Now plot (x,y) and (x,z) on the axes. Play around with the linewidth and style
In [53]:
axes[0].plot(x,y,color="blue", lw=3, ls='--')
axes[1].plot(x,z,color="red", lw=3, ls='-')
fig
Out[53]:
See if you can resize the plot by adding the figsize() argument in plt.subplots() are copying and pasting your previous code.
In [54]:
fig, axes = plt.subplots(nrows=1, ncols=2,figsize=(12,2))
axes[0].plot(x,y,color="blue", lw=5)
axes[0].set_xlabel('x')
axes[0].set_ylabel('y')
axes[1].plot(x,z,color="red", lw=3, ls='--')
axes[1].set_xlabel('x')
axes[1].set_ylabel('z')
Out[54]: