text: Title: JointPlotVisualizer produces different visualizations depending on how the figure and axes objects are defined
  Body: **Describe the bug**
  JointPlotVisualizer produces different visualizations depending on how the figure and axes objects are defined.  
  
  If the figure and axes are defined in the following manner:
  
  _, ax = plt.subplots()
  visualizer = JointPlotVisualizer(ax=ax, feature=feature, target=target, joint_plot="hex")
  
  The results are as follows:
  
  1) feature and target labels are displayed in the image
  2) the tick labels are displayed only on the left and bottom axes
  3) there are issues with the tick label values
  
  On the other hand, if the figure and axes are defined as such:
  
  fig = plt.figure()
  ax = fig.add_subplot()
  
  The results are as follows:
  
  1) the feature and target labels are not displayed
  2) the tick labels show up in all the axes
  3) the tick label values are displayed with more meaningful values
  
  Refer to the following jupyter notebook to see a demonstration of the differences:
  
  https://github.com/pdamodaran/yellowbrick/blob/develop/examples/pdamodaran/JointPlot_Examples.ipynb
  
  NOTE: any fixes to this issue should be considered in conjunction with the following issues:
  
  https://github.com/DistrictDataLabs/yellowbrick/issues/434
  https://github.com/DistrictDataLabs/yellowbrick/issues/214
  