added plot_teams function to plot all team's stats for a season(s)

docs/plotting.md

@@ -107,3 +107,28 @@ plt.show()
 
 ![](images/plot_bb_profile_example.png)
 
+---
+`plot_team(data, x_axis, y_axis, title=None)`
+
+## Arguments
+
+`data`: Fangraphs team data from either team_batting or team_pitching
+
+`x_axis`: name of stat to be plotted as the x_axis of the chart
+
+`y_axis`: name of stat to be plotted as the y_axis of the chart
+
+`title`: title for your chart
+
+# Example
+
+```python
+from pybaseball import plot_teams, team_batting
+
+data = team_batting(2023)
+
+plot_teams(data, "HR", "BB")
+```
+![Plot Teams_2023_BB/HR](images/plot_teams_example.png)
+
+`

pybaseball/__init__.py

@@ -94,6 +94,7 @@
 from .team_game_logs import team_game_logs
 from .plotting import plot_stadium
 from .plotting import spraychart
+from .plotting import plot_teams
 from .datasources.fangraphs import (fg_batting_data, fg_pitching_data, fg_team_batting_data, fg_team_fielding_data,
                                     fg_team_pitching_data)
 from .split_stats import get_splits

pybaseball/plotting.py

@@ -5,6 +5,7 @@
 
 from matplotlib import axes
 from matplotlib import patches
+from matplotlib.offsetbox import OffsetImage, AnnotationBbox
 import matplotlib.path
 import matplotlib.pyplot as plt
 import numpy as np
@@ -187,3 +188,63 @@ def plot_bb_profile(df: pd.DataFrame, parameter: Optional[str] = "launch_angle")
         bins = np.arange(df_skimmed[parameter].min(), df_skimmed[parameter].max(), 2)
         plt.hist(df_skimmed[parameter], bins=bins, alpha=0.5, label=bb_type.replace("_", " ").capitalize())
         plt.tick_params(labelsize=12)
+
+
+def plot_teams(data: pd.DataFrame, x_axis: str, y_axis: str, title: Optional[str] = None) -> None:
+    """Plots a scatter plot with each MLB team
+
+    Args:
+        data: (pandas.DataFrame)
+            pandas.DataFrame of Fangraphs team data (retrieved through team_batting or team_pitching)
+        x_axis: (str)
+            Stat name to be plotted as the x_axis of the chart
+        y_axis: (str)
+            Stat name to be plotted as the y_axis of the chart
+        title: (str), default = None
+            Optional: Title of the plot
+    """
+
+    data = data[['Team', x_axis, y_axis]]
+
+    fig, ax = plt.subplots()
+
+    for index, row in data.iterrows():
+
+        # Get path of team logo
+        path = Path(CUR_PATH, '../docs/images/logos', f"{row['Team']}.png")
+
+        # Read in the image from the folder location
+        img = OffsetImage(plt.imread(path, format="png"), zoom=.3)
+
+        # Convert the image into a plottable object
+        ab = AnnotationBbox(img, (float(row[x_axis]), float(row[y_axis])), frameon=False)
+
+        # Plot the MLB logo
+        ax.add_artist(ab)
+
+    # add some spacing to the x axis and y axis so the logos stay within the bounds of the chart
+    x_axis_spacing = (data[x_axis].max() - data[x_axis].min()) * .1
+    y_axis_spacing = (data[y_axis].max() - data[y_axis].min()) * .1
+
+    # set the axis with the spacing from above
+    plt.xlim([data[x_axis].min() - x_axis_spacing, data[x_axis].max() + x_axis_spacing])
+    plt.ylim([data[y_axis].min() - y_axis_spacing, data[y_axis].max() + y_axis_spacing])
+
+    # Plot league average for y axis variable
+    plt.axhline(y=data[y_axis].mean(), color='k', linestyle='-')
+    plt.text(data[x_axis].min() - x_axis_spacing * .9, data[y_axis].mean() + y_axis_spacing * .1, 'league average')
+
+    # Plot league average for x axis variable
+    plt.axvline(x=data[x_axis].mean(), color='k', linestyle='-')
+    plt.text(data[x_axis].mean() + x_axis_spacing * .05, data[y_axis].min() - y_axis_spacing * .8, 'league average',
+             rotation=90)
+
+    # Add title and labels
+    if not title:
+        title = f'Plot of Team {x_axis}/Team {y_axis}'
+
+    plt.title(title)
+    plt.xlabel(x_axis)
+    plt.ylabel(y_axis)
+
+    plt.show()