Added SNS Histogram node.

modules/seaborn_wrapper/common.py

@@ -19,3 +19,24 @@ def common_input_types():
             "palette": ("STRING", {"default": ""})
         }
     }
+
+def common_input_types_y_only_bin():
+    """
+    Defines the input types for a plot function for types of charts that do
+    not require x-series data as input, but takes bins.
+
+    Returns:
+        Dict[str, Any]: A dictionary specifying required input types.
+    """
+    return {
+        "required": {
+            "dataframe": ("DATAFRAME", {}),
+            "y_column_name": ("STRING", {"default": ""}),
+            "title": ("STRING", {"default": ""}),
+            "y_axis_label": ("STRING", {"default": ""}),
+            # "legend_label": ("STRING", {"default": ""}),
+            "bins": ("INT", {"default": 10, "min": 2, "max": 200}),
+            "style": ("STRING", {"default": ""}),
+            "palette": ("STRING", {"default": ""})
+        }
+    }

modules/seaborn_wrapper/sns_histogram.py

@@ -0,0 +1,78 @@
+from typing import Any, Dict
+from matplotlib import pyplot as plt
+import pandas as pd
+import seaborn as sns
+from .common import common_input_types_y_only_bin
+from .util import plot_post_steps
+from .util import set_up_sns_style_palette
+from .util import process_y_columns_and_labels
+
+
+class SNSHistogram:
+    """
+    SNS Histogram:
+    Generates a histogram from a Pandas DataFrame using Seaborn.
+
+    Currently, plotting multiple series of data is not supported.
+    For style and palette parameters, refer to [SNS Line Plot documentation](sns_line.md).
+
+    category: Plot
+    """
+    
+    @classmethod
+    def INPUT_TYPES(cls) -> Dict[str, Any]:
+        """
+        Defines the input types for the `bar_chart` function.
+
+        Returns:
+            Dict[str, Any]: A dictionary specifying required input types.
+        """
+        return common_input_types_y_only_bin()
+
+    RETURN_TYPES: tuple = ("IMAGE",)
+    FUNCTION: str = "bar_chart"
+    CATEGORY: str = "Data Analysis"
+
+    def bar_chart(self,
+                  dataframe: pd.DataFrame,
+                  y_column_name: str,
+                  title: str,
+                  y_axis_label: str,
+                  # legend_label: str,
+                  bins: int,
+                  style: str=None,
+                  palette: str=None) -> tuple:
+        """
+        Generates a bar chart from a pandas DataFrame.
+
+        Args:
+            dataframe (DataFrame): The DataFrame.
+            y_column_name (str): The column name for the y-axis.
+            title (str): The title of the plot.
+            y_axis_label (str): The label for the y-axis data.
+            bins (int): Number of bins.
+            style (str): Style of the plot
+            palette (str): Palette of the plot
+        Returns:
+            tuple: A tuple containing the image tensor representation of the plot.
+        """
+        df = dataframe
+        set_up_sns_style_palette(style, palette)
+
+        # TODO: For future enhancement, restore legend_label as the last arg.
+        y_columns, labels = process_y_columns_and_labels(df, y_column_name, "")
+
+        # Create the plot
+        fig, ax = plt.subplots()
+        for i in range(len(y_columns)):
+            sns.histplot(df[y_columns[i]], bins=bins, ax=ax, label=labels[i])
+            break  # TODO: Remove this if we decide support multiple plots
+
+        return plot_post_steps(
+            fig,
+            ax,
+            plt,
+            title,
+            None,
+            y_axis_label,
+            None)

modules/seaborn_wrapper/util.py

@@ -90,7 +90,8 @@ def plot_post_steps(
 
     # Set title and labels
     ax.set_title(title)
-    ax.set_xlabel(x_axis_label)
+    if x_axis_label:
+        ax.set_xlabel(x_axis_label)
     ax.set_ylabel(y_axis_label)
 
     # Save the plot to a buffer