Added Pandas Load CSV with Index node.

README.md

@@ -5,7 +5,7 @@
 
 ComfyUI-Data-Analysis is a custom module for analyzing data using Pandas and Matplotlib within ComfyUI.
 
-Nodes include:
+Here are some of the included nodes:
 
 - Loading a CSV file as a DataFrame
 - Saving a DataFrame to a CSV file

__init__.py

@@ -9,6 +9,7 @@ from .modules.pandas_wrapper.pandas_head import PandasHead
 from .modules.pandas_wrapper.pandas_index import PandasIndex
 from .modules.pandas_wrapper.pandas_join import PandasJoin
 from .modules.pandas_wrapper.pandas_load_csv import PandasLoadCSV
+from .modules.pandas_wrapper.pandas_load_csv_with_index import PandasLoadCSVWithIndex
 from .modules.pandas_wrapper.pandas_save_csv import PandasSaveCSV
 from .modules.pandas_wrapper.pandas_select_columns import PandasSelectColumns
 from .modules.pandas_wrapper.pandas_select_rows import PandasSelectRows
@@ -31,6 +32,7 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
     "PandasIndex": PandasIndex,
     "PandasJoin": PandasJoin,
     "PandasLoadCSV": PandasLoadCSV,
+    "PandasLoadCSVWithIndex": PandasLoadCSVWithIndex,
     "PandasSaveCSV": PandasSaveCSV,
     "PandasSelectColumns": PandasSelectColumns,
     "PandasSelectRows": PandasSelectRows,
@@ -56,6 +58,7 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
     "PandasIndex": "Pandas Index",
     "PandasJoin": "Pandas Join",
     "PandasLoadCSV": "Pandas Load CSV",
+    "PandasLoadCSVWithIndex": "Pandas Load CSV with Index",
     "PandasSaveCSV": "Pandas Save CSV",
     "PandasSelectColumns": "Pandas Select Columns",
     "PandasSelectRows": "Pandas Select Rows",

docs/ug.md

@@ -14,6 +14,7 @@ You can right-click, select **Add Node**, go to **Data Analysis**, and look for
 | Node Name               | Functionality                        |
 |-------------------------|-------------------------------------|
 | **Pandas Load CSV**     | Load a CSV file                    |
+| **Pandas Load CSV with Index**     | Load a CSV file containing index |
 | **Pandas Save CSV**     | Save a DataFrame to a CSV file     |
 | **Pandas Create**     | Create a DataFrame from CSV text field |
 | **Pandas Create with Index**     | Create a DataFrame from CSV text field containing index |
@@ -37,7 +38,7 @@ A faster way is to double-click the canvas to open the node search dialog.
 The examples directory contains workflows that load data from an example dataset included in this package. These workflows should give you a good idea about how to use these nodes.
 
 ## Loading data
-Use **Pandas Load CSV** node to load a CSV.
+Use **Pandas Load CSV** node to load a CSV, or **Pandas Load CSV with Index** node if the CSV contains an index column.
 ![Pandas Load CSV node](images/load.jpg)
 
 This will emit the DataFrame in a JSON string.

examples/datasets/car_sales.csv

@@ -0,0 +1,4 @@
+Index,Name,Sales
+A,Foo,10000
+B,Bar,20000
+C,Baz,30000

modules/pandas_wrapper/pandas_load_csv_with_index.py

@@ -0,0 +1,49 @@
+from typing import Any, Dict
+from io import StringIO
+import pandas as pd
+
+
+class PandasLoadCSVWithIndex:
+    """
+    PandasLoadCSV:
+        A class for loading CSV files into a pandas DataFrame.
+        Input data is assume to have an index.
+    """
+    
+    @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}),
+                "index_col": ("INT", {"default": 0, "min": 0, "max": 10000})
+            }
+        }
+
+    RETURN_TYPES: tuple = ("STRING",)
+    FUNCTION: str = "load_csv"
+    CATEGORY: str = "Data Analysis"
+
+    def load_csv(self, file_path: str, index_col: int=0) -> tuple:
+        """
+        Loads a CSV file into a pandas DataFrame and converts it to a JSON string.
+        Input data is assume to have an index.
+
+        Args:
+            file_path (str): The path to the CSV file.
+
+        Returns:
+            tuple: A tuple containing a JSON string representation of the DataFrame.
+        """
+        # Read CSV file into DataFrame
+        df = pd.read_csv(file_path, index_col=index_col)
+
+        # Convert DataFrame to JSON
+        result_json = df.to_json()
+
+        return (result_json,)

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "data-analysis"
 description = "Data analysis custom modules for ComfyUI - Use Pandas & Matplotlib within ComfyUI"
-version = "1.0.7"
+version = "1.0.8"
 license = {file = "LICENSE"}
 
 [project.urls]