Added Pandas Load Excel node to read Excel file and added dependency on openpyxl package.

.gitignore

@@ -1,5 +1,7 @@
 __pycache__/
 **/__pycache__/
-datasets/
 models/
 *.pth
+/datasets/
+!*/foo/
+examples/datasets/.~lock*

__init__.py

@@ -67,6 +67,7 @@ from .modules.pandas_wrapper.pandas_kurtosis import PandasKurtosis
 from .modules.pandas_wrapper.pandas_load_csv import PandasLoadCSV
 from .modules.pandas_wrapper.pandas_load_csv_with_encoding import PandasLoadCSVWithEncoding
 from .modules.pandas_wrapper.pandas_load_csv_with_index import PandasLoadCSVWithIndex
+from .modules.pandas_wrapper.pandas_load_excel import PandasLoadExcel
 from .modules.pandas_wrapper.pandas_load_html import PandasLoadHTML
 from .modules.pandas_wrapper.pandas_load_json import PandasLoadJSON
 from .modules.pandas_wrapper.pandas_loc_cell_str import PandasLocCellStr
@@ -300,6 +301,7 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
     "PandasLoadCSV": PandasLoadCSV,
     "PandasLoadCSVWithEncoding": PandasLoadCSVWithEncoding,
     "PandasLoadCSVWithIndex": PandasLoadCSVWithIndex,
+    "PandasLoadExcel": PandasLoadExcel,
     "PandasLoadHTML": PandasLoadHTML,
     "PandasLoadJSON": PandasLoadJSON,
     "PandasLocCellStr": PandasLocCellStr,
@@ -536,6 +538,7 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
     "PandasLoadCSV": "Pandas Load CSV",
     "PandasLoadCSVWithEncoding": "Pandas Load CSV With Encoding",
     "PandasLoadCSVWithIndex": "Pandas Load CSV With Index",
+    "PandasLoadExcel": "Pandas Load Excel",
     "PandasLoadHTML": "Pandas Load HTML",
     "PandasLoadJSON": "Pandas Load JSON",
     "PandasLocCellStr": "Pandas Loc Cell Str",

docs/reference/node_reference.md

@@ -109,6 +109,7 @@
 | [Pandas Load CSV](pandas_load_csv.md) | Loads CSV files into a pandas DataFrame. |
 | [Pandas Load CSV With Encoding](pandas_load_csv_with_encoding.md) | Loads CSV files into a pandas DataFrame. |
 | [Pandas Load CSV With Index](pandas_load_csv_with_index.md) | Loads CSV files into a pandas DataFrame. |
+| [Pandas Load Excel](pandas_load_excel.md) | Loads Excel files into a pandas DataFrame. |
 | [Pandas Load HTML](pandas_load_html.md) | Scans an HTML file or webpage for tables and returns the number of DataFrames  |
 | [Pandas Load JSON](pandas_load_json.md) | Loads JSON files into a pandas DataFrame. |
 | [Pandas Save CSV](pandas_save_csv.md) | Saves a PandasDataFrame to a CSV file. |

docs/reference/pandas_load_excel.md

@@ -0,0 +1,23 @@
+# Pandas Load Excel
+Loads Excel files into a pandas DataFrame.
+
+This node uses read_excel method.
+See [Pandas documentation](https://pandas.pydata.org/docs/reference/api/pandas.read_excel.html) for details.
+
+If sheet_name is not specified, first sheet will be read.
+
+## Input
+| Name | Data type |
+|---|---|
+| file_path | String |
+| sheet_name | String |
+
+## Output
+| Data type |
+|---|
+| DataFrame |
+
+<HR>
+Category: IO
+
+ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.

modules/pandas_wrapper/pandas_load_excel.py

@@ -0,0 +1,55 @@
+from typing import Any, Dict
+from io import StringIO
+import pandas as pd
+
+
+class PandasLoadExcel:
+    """
+    Loads Excel files into a pandas DataFrame.
+
+    This node uses read_excel method.
+    See [Pandas documentation](https://pandas.pydata.org/docs/reference/api/pandas.read_excel.html) for details.
+
+    If sheet_name is not specified, first sheet will be read.
+
+    category: IO
+    """
+    
+    @classmethod
+    def INPUT_TYPES(cls) -> Dict[str, Any]:
+        """
+        Defines the input types for the `load_csv` function.
+
+        Returns:
+            Dict[str, Any]: A dictionary specifying required input types.
+        """
+        return {
+            "required": {
+                "file_path": ("STRING", {"multiline": False}),
+                "sheet_name": ("STRING", {"default": ""}),
+                
+            }
+        }
+
+    RETURN_TYPES: tuple = ("DATAFRAME",)
+    FUNCTION: str = "f"
+    CATEGORY: str = "Data Analysis"
+
+    @classmethod
+    def IS_CHANGED(cls, **kw):
+        return float("NaN")
+
+    def f(self, file_path: str, sheet_name: str) -> tuple:
+        """
+        Loads an Excel file into a pandas DataFrame.
+
+        Args:
+            file_path (str): The path to the Excel file.
+
+        Returns:
+            tuple: A tuple containing a DataFrame.
+        """
+        if len(sheet_name) == 0:
+            sheet_name = 0  # Read first sheet
+        df = pd.read_excel(file_path, sheet_name=sheet_name)
+        return (df,)

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "data-analysis"
 description = "Data analysis custom modules for ComfyUI – Integrates Pandas, Seaborn and Matplotlib into ComfyUI, featuring extensive PyTorch wrapper nodes for seamless tensor operations. Experimental PyTorch model training was added in v2.0."
-version = "2.0.4"
+version = "2.0.5"
 license = {file = "LICENSE"}
 
 [project.urls]

requirements.txt

@@ -2,4 +2,5 @@ matplotlib>=3.10.0
 pandas>=2.2.3
 seaborn>=0.13.2
 scipy>=1.14.1
-scikit-learn>=1.6.1
+scikit-learn>=1.6.1
+openpyxl>=3.1.5

tests/pandas_wrapper/pandas_load_excel_test.py

@@ -0,0 +1,64 @@
+import os
+import sys
+import unittest
+import pandas as pd
+
+PROJECT_ROOT = os.path.realpath(os.path.join(os.path.dirname(__file__), "..", ".."))
+MODULE_ROOT = os.path.join(PROJECT_ROOT, "modules")
+sys.path.append(MODULE_ROOT)
+from pandas_wrapper.pandas_load_excel import PandasLoadExcel
+
+
+class TestPandasLoadExcel(unittest.TestCase):
+    def setUp(self):
+        """Set up test data."""
+        self.node = PandasLoadExcel()
+        self.test_file_path = os.path.join(
+                                os.path.dirname(__file__), "..", "..",
+                                "examples", "datasets", "test_file.xlsx")
+        
+        self.test_data_list = [
+            (
+                "Sheet1",
+                pd.DataFrame(
+                    {
+                        "Item": ["Bat", "Racquet", "Glove", "Hockey stick", "Soccer ball"],
+                        "Qty": [3, 4, 5, 6, 7]
+                    },
+                    index = [0, 1, 2, 3, 4]
+                ),
+            ),
+            (
+                "FruitPrice",
+                pd.DataFrame(
+                    {
+                        "Fruit": ["Apple", "Banana", "Coconut", "Donut"],
+                        "Price": [1.23, 2.34, 3.45, 4.56]
+                    },
+                    index = [0, 1, 2, 3]
+                )
+            ),
+            (
+                "",  # Leaving the sheet name blank should read the first sheet.
+                pd.DataFrame(
+                    {
+                        "Item": ["Bat", "Racquet", "Glove", "Hockey stick", "Soccer ball"],
+                        "Qty": [3, 4, 5, 6, 7]
+                    },
+                    index = [0, 1, 2, 3, 4]
+                ),
+            ),
+        ]
+    def test_read_excel(self):
+        """Reads multiple sheets from an excel file.
+        """
+        for test_data in self.test_data_list:
+            with self.subTest(test_data=test_data):
+                sheet_name = test_data[0]
+                expected = test_data[1]
+                df = self.node.f(self.test_file_path, sheet_name=sheet_name)[0]
+                pd.testing.assert_frame_equal(df, expected)
+
+
+if __name__ == "__main__":
+    unittest.main()