We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Joint Plot Viz has messed up (overlapping labels on) axes
**Describe the bug**

If you look at the x and y axis on http://www.scikit-yb.org/en/latest/api/features/scatter.html#joint-plot-visualization you will see that the labels are overlapping.

**To Reproduce**

Create a joint plot as shown in the docs



**Expected behavior**

Labels on axes should be clear.


**Desktop (please complete the following information):**
 - OS: macOS
 - Python Version 3.6.4
 - Yellowbrick Version 0.8


Joint Plot Viz has messed up (overlapping labels on) axes
**Describe the bug**

If you look at the x and y axis on http://www.scikit-yb.org/en/latest/api/features/scatter.html#joint-plot-visualization you will see that the labels are overlapping.

**To Reproduce**

Create a joint plot as shown in the docs



**Expected behavior**

Labels on axes should be clear.


**Desktop (please complete the following information):**
 - OS: macOS
 - Python Version 3.6.4
 - Yellowbrick Version 0.8



--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `docs/api/features/jointplot.py`
Content:
```
1 import pandas as pd
2 import matplotlib.pyplot as plt
3 
4 from yellowbrick.features import JointPlotVisualizer
5 
6 
7 def jointplot(X, y, outpath, **kwargs):
8     # Create a new figure and axes
9     fig = plt.figure()
10     ax = fig.add_subplot(111)
11 
12     # Create the visualizer
13     visualizer = JointPlotVisualizer(ax=ax, **kwargs)
14     visualizer.fit(X, y)
15     visualizer.transform(X)
16 
17     # Save to disk
18     visualizer.poof(outpath=outpath)
19     plt.savefig(outpath)
20 
21 
22 if __name__ == '__main__':
23 
24     # Load the regression data set
25     data = pd.read_csv("../../../examples/data/concrete/concrete.csv")
26 
27     feature = 'cement'
28     target = 'strength'
29 
30     # Get the X and y data from the DataFrame
31     Xs = data[feature]
32     ys = data[target]
33 
34     # Draw the joint plot visualizer
35     jointplot(Xs, ys, "images/jointplot.png", feature=feature, target=target)
36 
37     # Draw the joint plot visualizer with hexadecimal scatter plot
38     jointplot(Xs, ys, "images/jointplot_hex.png", feature=feature, target=target, joint_plot='hex')
39
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/docs/api/features/jointplot.py b/docs/api/features/jointplot.py
--- a/docs/api/features/jointplot.py
+++ b/docs/api/features/jointplot.py
@@ -5,12 +5,8 @@
 
 
 def jointplot(X, y, outpath, **kwargs):
-    # Create a new figure and axes
-    fig = plt.figure()
-    ax = fig.add_subplot(111)
-
     # Create the visualizer
-    visualizer = JointPlotVisualizer(ax=ax, **kwargs)
+    visualizer = JointPlotVisualizer(**kwargs)
     visualizer.fit(X, y)
     visualizer.transform(X)

{"golden_diff": "diff --git a/docs/api/features/jointplot.py b/docs/api/features/jointplot.py\n--- a/docs/api/features/jointplot.py\n+++ b/docs/api/features/jointplot.py\n@@ -5,12 +5,8 @@\n \n \n def jointplot(X, y, outpath, **kwargs):\n-    # Create a new figure and axes\n-    fig = plt.figure()\n-    ax = fig.add_subplot(111)\n-\n     # Create the visualizer\n-    visualizer = JointPlotVisualizer(ax=ax, **kwargs)\n+    visualizer = JointPlotVisualizer(**kwargs)\n     visualizer.fit(X, y)\n     visualizer.transform(X)\n", "issue": "Joint Plot Viz has messed up (overlapping labels on) axes\n**Describe the bug**\r\n\r\nIf you look at the x and y axis on http://www.scikit-yb.org/en/latest/api/features/scatter.html#joint-plot-visualization you will see that the labels are overlapping.\r\n\r\n**To Reproduce**\r\n\r\nCreate a joint plot as shown in the docs\r\n\r\n\r\n\r\n**Expected behavior**\r\n\r\nLabels on axes should be clear.\r\n\r\n\r\n**Desktop (please complete the following information):**\r\n - OS: macOS\r\n - Python Version 3.6.4\r\n - Yellowbrick Version 0.8\r\n\r\n\nJoint Plot Viz has messed up (overlapping labels on) axes\n**Describe the bug**\r\n\r\nIf you look at the x and y axis on http://www.scikit-yb.org/en/latest/api/features/scatter.html#joint-plot-visualization you will see that the labels are overlapping.\r\n\r\n**To Reproduce**\r\n\r\nCreate a joint plot as shown in the docs\r\n\r\n\r\n\r\n**Expected behavior**\r\n\r\nLabels on axes should be clear.\r\n\r\n\r\n**Desktop (please complete the following information):**\r\n - OS: macOS\r\n - Python Version 3.6.4\r\n - Yellowbrick Version 0.8\r\n\r\n\n", "before_files": [{"content": "import pandas as pd\nimport matplotlib.pyplot as plt\n\nfrom yellowbrick.features import JointPlotVisualizer\n\n\ndef jointplot(X, y, outpath, **kwargs):\n    # Create a new figure and axes\n    fig = plt.figure()\n    ax = fig.add_subplot(111)\n\n    # Create the visualizer\n    visualizer = JointPlotVisualizer(ax=ax, **kwargs)\n    visualizer.fit(X, y)\n    visualizer.transform(X)\n\n    # Save to disk\n    visualizer.poof(outpath=outpath)\n    plt.savefig(outpath)\n\n\nif __name__ == '__main__':\n\n    # Load the regression data set\n    data = pd.read_csv(\"../../../examples/data/concrete/concrete.csv\")\n\n    feature = 'cement'\n    target = 'strength'\n\n    # Get the X and y data from the DataFrame\n    Xs = data[feature]\n    ys = data[target]\n\n    # Draw the joint plot visualizer\n    jointplot(Xs, ys, \"images/jointplot.png\", feature=feature, target=target)\n\n    # Draw the joint plot visualizer with hexadecimal scatter plot\n    jointplot(Xs, ys, \"images/jointplot_hex.png\", feature=feature, target=target, joint_plot='hex')\n", "path": "docs/api/features/jointplot.py"}], "after_files": [{"content": "import pandas as pd\nimport matplotlib.pyplot as plt\n\nfrom yellowbrick.features import JointPlotVisualizer\n\n\ndef jointplot(X, y, outpath, **kwargs):\n    # Create the visualizer\n    visualizer = JointPlotVisualizer(**kwargs)\n    visualizer.fit(X, y)\n    visualizer.transform(X)\n\n    # Save to disk\n    visualizer.poof(outpath=outpath)\n    plt.savefig(outpath)\n\n\nif __name__ == '__main__':\n\n    # Load the regression data set\n    data = pd.read_csv(\"../../../examples/data/concrete/concrete.csv\")\n\n    feature = 'cement'\n    target = 'strength'\n\n    # Get the X and y data from the DataFrame\n    Xs = data[feature]\n    ys = data[target]\n\n    # Draw the joint plot visualizer\n    jointplot(Xs, ys, \"images/jointplot.png\", feature=feature, target=target)\n\n    # Draw the joint plot visualizer with hexadecimal scatter plot\n    jointplot(Xs, ys, \"images/jointplot_hex.png\", feature=feature, target=target, joint_plot='hex')\n", "path": "docs/api/features/jointplot.py"}]}