Added Pandas Replace to replace part or whole string in each DataFrame cell using a regular expression.

__init__.py

@@ -52,6 +52,7 @@ from .modules.pandas_wrapper.pandas_mul import PandasMul
 from .modules.pandas_wrapper.pandas_mul_series import PandasMulSeries
 from .modules.pandas_wrapper.pandas_pow import PandasPow
 from .modules.pandas_wrapper.pandas_pow_series import PandasPowSeries
+from .modules.pandas_wrapper.pandas_replace import PandasReplace
 from .modules.pandas_wrapper.pandas_save_csv import PandasSaveCSV
 from .modules.pandas_wrapper.pandas_save_json import PandasSaveJSON
 from .modules.pandas_wrapper.pandas_select_columns import PandasSelectColumns
@@ -126,6 +127,7 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
     "PandasMode": PandasMode,
     "PandasMul": PandasMul,
     "PandasMulSeries": PandasMulSeries,
+    "PandasReplace": PandasReplace,
     "PandasPow": PandasPow,
     "PandasPowSeries": PandasPowSeries,
     "PandasSaveCSV": PandasSaveCSV,
@@ -207,6 +209,7 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
     "PandasMulSeries": "Pandas Mul Series",
     "PandasPow": "Pandas Pow",
     "PandasPowSeries": "Pandas Pow Series",
+    "PandasReplace": "Pandas Replace",
     "PandasSaveCSV": "Pandas Save CSV",
     "PandasSaveJSON": "Pandas Save JSON",
     "PandasSelectColumns": "Pandas Select Columns",

docs/reference/node_reference.md

@@ -21,6 +21,7 @@
 | --- | --- |
 | [Pandas Drop NA](pandas_dropna.md) | Drops missing values from a pandas DataFrame. |
 | [Pandas Is NA](pandas_isna.md) | Checks a pandas DataFrame for missing values. |
+| [Pandas Replace](pandas_replace.md) | Replaces part or all of a string in each DataFrame cell with a specified string using a wildcard for matching.  If you want to remove some characters, then leave the replace_string field blank. |
 ## Data subset selection
 | Node | Description |
 | --- | --- |

docs/reference/pandas_replace.md

@@ -0,0 +1,19 @@
+# Pandas Replace
+Replaces part or all of a string in each DataFrame cell with a specified string using a wildcard for matching.  If you want to remove some characters, then leave the replace_string field blank.
+
+## Input
+| Name | Data type |
+|---|---|
+| dataframe | DataFrame |
+| regex | String |
+| replacement_string | String |
+
+## Output
+| Data type |
+|---|
+| DataFrame |
+
+<HR>
+Category: Data cleansing
+
+ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.

modules/pandas_wrapper/pandas_replace.py

@@ -0,0 +1,44 @@
+from typing import Any, Dict
+import pandas as pd
+
+
+class PandasReplace:
+    """
+    Replaces part or all of a string in each DataFrame cell with a specified string using a wildcard for matching.  If you want to remove some characters, then leave the replace_string field blank.
+
+    category: Data cleansing
+    """
+    
+    @classmethod
+    def INPUT_TYPES(cls) -> Dict[str, Any]:
+        """
+        Defines the input types for the function.
+
+        Returns:
+            Dict[str, Any]: A dictionary specifying required input types.
+        """
+        return {
+            "required": {
+                "dataframe": ("DATAFRAME", {}),
+                "regex": ("STRING", {"default": ""}),
+                "replacement_string": ("STRING", {"default": ""})
+            }
+        }
+
+    RETURN_TYPES: tuple = ("DATAFRAME",)
+    FUNCTION: str = "f"
+    CATEGORY: str = "Data Analysis"
+
+    def f(self, dataframe: pd.DataFrame, regex: str, replacement_string: str) -> tuple:
+        """
+        Replaces part or all of a string in each DataFrame cell with a specified string using a wildcard for matching.
+
+        Args:
+            dataframe (DataFrame): The target DataFrame.
+            regex (str): A regular expression pattern.
+
+        Returns:
+            tuple: A tuple containing the DataFrame.
+        """
+        df2 = dataframe.replace({regex: replacement_string}, regex=True)
+        return (df2,)

modules/pandas_wrapper/utils.py

@@ -2,6 +2,7 @@ import json
 import numpy as np
 import pandas as pd
 
+
 def series_to_jsons(series: pd.Series) -> str:
     """
     Convert a pandas Series to a JSON string.

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "data-analysis"
 description = "Data analysis custom modules for ComfyUI - Use Pandas & Matplotlib within ComfyUI"
-version = "1.1.7"
+version = "1.1.8"
 license = {file = "LICENSE"}
 
 [project.urls]