adds docstrings

app/analysis/plot_heat_user-activity-hour.py

@@ -7,13 +7,30 @@ import matplotlib
 matplotlib.use('Agg')
 
 class PlotActivityHeatmap(BasePlotAnalysis):
+    """
+    Class for analyzing user activity trends over multiple days and generating a heatmap.
+
+    Attributes:
+    name (str): The name of the analysis.
+    description (str): A brief description of the analysis.
+    plot_filename (str): The filename for the output plot.
+    note (str): Additional notes for the analysis.
+    """
     name = "Activity Heatmap"
     description = "Displays user activity trends over multiple days using a heatmap. Generates a downloadable PNG image."
     plot_filename = "activity_heatmap.png"
     note = ""
     
     def transform_data(self, df: pd.DataFrame) -> pd.DataFrame:
-        """Transform data for the heatmap"""
+        """
+        Transform data for the heatmap.
+
+        Parameters:
+        df (pd.DataFrame): The input DataFrame containing user activity data.
+
+        Returns:
+        pd.DataFrame: The transformed DataFrame with activity counts by hour.
+        """
         active_counts = df[df['was_active']].pivot_table(
             index='name', 
             columns='hour', 
@@ -25,7 +42,12 @@ class PlotActivityHeatmap(BasePlotAnalysis):
         return active_counts.sort_values(by='total_active_minutes', ascending=False)
 
     def plot_data(self, df: pd.DataFrame):
-        """Generate heatmap plot"""
+        """
+        Generate heatmap plot.
+
+        Parameters:
+        df (pd.DataFrame): The transformed DataFrame containing activity counts by hour.
+        """
         plt.figure(figsize=(12, 8))
         sns.heatmap(df.loc[:, df.columns != 'total_active_minutes'], cmap='viridis', cbar_kws={'label': 'Count of was_active == True'})
         plt.xlabel('Hour of Day')