matplotlib
diff --git a/‎examples/animation/random_walk.py
Copy file name to clipboardExpand all lines: examples/animation/random_walk.py
+11-12Lines changed: 11 additions & 12 deletions b/‎examples/animation/random_walk.py
Copy file name to clipboardExpand all lines: examples/animation/random_walk.py
+11-12Lines changed: 11 additions & 12 deletions
diff --git a/‎tutorials/toolkits/mplot3d.py
Copy file name to clipboardExpand all lines: tutorials/toolkits/mplot3d.py
+9-12Lines changed: 9 additions & 12 deletions b/‎tutorials/toolkits/mplot3d.py
Copy file name to clipboardExpand all lines: tutorials/toolkits/mplot3d.py
+9-12Lines changed: 9 additions & 12 deletions
@@ -7,31 +7,29 @@
 
 import numpy as np
 import matplotlib.pyplot as plt
-import mpl_toolkits.mplot3d.axes3d as p3
 import matplotlib.animation as animation
 
 # Fixing random state for reproducibility
 np.random.seed(19680801)
 
 
-def Gen_RandLine(length, dims=2):
+def gen_rand_line(length, dims=2):
     """
     Create a line using a random walk algorithm
 
     length is the number of points for the line.
     dims is the number of dimensions the line has.
     """
-    lineData = np.empty((dims, length))
-    lineData[:, 0] = np.random.rand(dims)
+    line_data = np.empty((dims, length))
+    line_data[:, 0] = np.random.rand(dims)
     for index in range(1, length):
         # scaling the random numbers by 0.1 so
         # movement is small compared to position.
         # subtraction by 0.5 is to change the range to [-0.5, 0.5]
         # to allow a line to move backwards.
-        step = ((np.random.rand(dims) - 0.5) * 0.1)
-        lineData[:, index] = lineData[:, index - 1] + step
-
-    return lineData
+        step = (np.random.rand(dims) - 0.5) * 0.1
+        line_data[:, index] = line_data[:, index - 1] + step
+    return line_data
 
 
 def update_lines(num, dataLines, lines):
@@ -41,12 +39,13 @@ def update_lines(num, dataLines, lines):
         line.set_3d_properties(data[2, :num])
     return lines
 
+
 # Attaching 3D axis to the figure
 fig = plt.figure()
-ax = p3.Axes3D(fig)
+ax = fig.add_subplot(projection="3d")
 
 # Fifty lines of random 3-D lines
-data = [Gen_RandLine(25, 3) for index in range(50)]
+data = [gen_rand_line(25, 3) for index in range(50)]
 
 # Creating fifty line objects.
 # NOTE: Can't pass empty arrays into 3d version of plot()
@@ -65,7 +64,7 @@ def update_lines(num, dataLines, lines):
 ax.set_title('3D Test')
 
 # Creating the Animation object
-line_ani = animation.FuncAnimation(fig, update_lines, 25, fargs=(data, lines),
-                                   interval=50, blit=False)
+line_ani = animation.FuncAnimation(
+    fig, update_lines, 25, fargs=(data, lines), interval=50)
 
 plt.show()
@@ -14,24 +14,21 @@
 
 Getting started
 ---------------
-An Axes3D object is created just like any other axes using
-the projection='3d' keyword.
-Create a new :class:`matplotlib.figure.Figure` and
-add a new axes to it of type :class:`~mpl_toolkits.mplot3d.Axes3D`::
+3D Axes (of class `Axes3D`) are created by passing the ``projection="3d"``
+keyword argument to `Figure.add_subplot`::
 
    import matplotlib.pyplot as plt
-   from mpl_toolkits.mplot3d import Axes3D
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')
 
-.. versionadded:: 1.0.0
-   This approach is the preferred method of creating a 3D axes.
+.. versionchanged:: 1.0.0
+   Prior to Matplotlib 1.0.0, `Axes3D` needed to be directly instantiated with
+   ``from mpl_toolkits.mplot3d import Axes3D; ax = Axes3D(fig)``.
 
-.. note::
-   Prior to version 1.0.0, the method of creating a 3D axes was
-   different. For those using older versions of matplotlib, change
-   ``ax = fig.add_subplot(111, projection='3d')``
-   to ``ax = Axes3D(fig)``.
+.. versionchanged:: 3.2.0
+   Prior to Matplotlib 3.2.0, it was necessary to explicitly import the
+   :mod:`mpl_toolkits.mplot3d` module to make the '3d' projection to
+   `Figure.add_subplot`.
 
 See the :ref:`toolkit_mplot3d-faq` for more information about the mplot3d
 toolkit.