Added Pandas Is NA and Pandas Drop NA nodes.

__init__.py

@@ -6,11 +6,13 @@ from .modules.matplotlib.mpl_scatter import MPLScatter
 from .modules.pandas_wrapper.pandas_columns import PandasColumns
 from .modules.pandas_wrapper.pandas_create import PandasCreate
 from .modules.pandas_wrapper.pandas_create_with_index import PandasCreateWithIndex
+from .modules.pandas_wrapper.pandas_dropna import PandasDropNA
 from .modules.pandas_wrapper.pandas_group_by import PandasGroupBy
 from .modules.pandas_wrapper.pandas_head import PandasHead
 from .modules.pandas_wrapper.pandas_iloc_row_series import PandasIlocRowSeries
 from .modules.pandas_wrapper.pandas_iloc_rows_dataframe import PandasIlocRowsDataFrame
 from .modules.pandas_wrapper.pandas_index import PandasIndex
+from .modules.pandas_wrapper.pandas_isna import PandasIsNA
 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_encoding import PandasLoadCSVWithEncoding
@@ -39,11 +41,13 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
     "PandasColumns": PandasColumns,
     "PandasCreate": PandasCreate,
     "PandasCreateWithIndex": PandasCreateWithIndex,
+    "PandasDropNA": PandasDropNA,
     "PandasGroupBy": PandasGroupBy,
     "PandasHead": PandasHead,
     "PandasIlocRowSeries": PandasIlocRowSeries,
     "PandasIlocRowsDataFrame": PandasIlocRowsDataFrame,
     "PandasIndex": PandasIndex,
+    "PandasIsNA": PandasIsNA,
     "PandasJoin": PandasJoin,
     "PandasLoadCSV": PandasLoadCSV,
     "PandasLoadCSVWithEncoding": PandasLoadCSVWithEncoding,
@@ -75,11 +79,13 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
     "PandasColumns": "Pandas Columns",
     "PandasCreate": "Pandas Create",
     "PandasCreateWithIndex": "Pandas Create With Index",
+    "PandasDropNA": "Pandas Drop NA",
     "PandasGroupBy": "Pandas Group By",
     "PandasHead": "Pandas Head",
     "PandasIlocRowSeries": "Pandas Iloc Row Series",
     "PandasIlocRowsDataFrame": "Pandas Iloc Rows DataFrame",
     "PandasIndex": "Pandas Index",
+    "PandasIsNA": "Pandas Is NA",
     "PandasJoin": "Pandas Join",
     "PandasLoadCSV": "Pandas Load CSV",
     "PandasLoadCSVWithEncoding": "Pandas Load CSV With Encoding",

docs/ug.md

@@ -52,6 +52,12 @@ You can right-click, select **Add Node**, go to **Data Analysis**, and look for
 | **Pandas Show Text**    | Display Text        |
 | **Pandas Summary**      | Extract DataFrame statistics          |
 
+**Missing value processing**
+| Node Name               | Functionality                        |
+|-------------------------|-------------------------------------|
+| **Pandas Is NA**  | Check DataFrame for missing values      |
+| **Pandas Drop NA**  | Drop missing values from DataFrame    |
+
 **Converting to displayable string**
 | Node Name               | Functionality                        |
 |-------------------------|-------------------------------------|
@@ -173,6 +179,11 @@ The workflow file examples/workflows/join.json contains all of the above cases.
 ## Extract the first few rows
 Use **Pandas Head**.
 
+## Missing value processing
+Use **Pandas Is NA** for checking DataFrame for missing values, and **Pandas Drop NA** for dropping missing values from DataFrame.
+
+![Pandas Is NA](images/isna.png)
+
 ## Display text ##
 Use **Pandas Show Text** node.
 

modules/pandas_wrapper/pandas_dropna.py

@@ -0,0 +1,42 @@
+from typing import Any, Dict
+from io import StringIO
+import pandas as pd
+from .utils import index_to_jsons
+
+class PandasDropNA:
+    """
+    PandasColumns:
+        A class for droping missing values from a pandas DataFrame.
+    """
+    
+    @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_json": ("STRING", {"multiline": True})
+            }
+        }
+
+    RETURN_TYPES: tuple = ("STRING",)
+    FUNCTION: str = "dropna"
+    CATEGORY: str = "Data Analysis"
+
+    def dropna(self, dataframe_json: str) -> tuple:
+        """
+        Returns a DataFrame with missing values removed.
+
+        Args:
+            dataframe_json (str): A JSON string representation of the DataFrame.
+
+        Returns:
+            tuple: A tuple containing a JSON string for the DataFrame.
+        """
+        # Deserialize JSON string to DataFrame
+        df = pd.read_json(StringIO(dataframe_json))
+        return (df.dropna().to_json(),)

modules/pandas_wrapper/pandas_isna.py

@@ -0,0 +1,42 @@
+from typing import Any, Dict
+from io import StringIO
+import pandas as pd
+from .utils import index_to_jsons
+
+class PandasIsNA:
+    """
+    PandasColumns:
+        A class for checking a pandas DataFrame for missing values.
+    """
+    
+    @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_json": ("STRING", {"multiline": True})
+            }
+        }
+
+    RETURN_TYPES: tuple = ("STRING",)
+    FUNCTION: str = "isna"
+    CATEGORY: str = "Data Analysis"
+
+    def isna(self, dataframe_json: str) -> tuple:
+        """
+        Returns a DataFrame with boolean values with True indicating a missing value.
+
+        Args:
+            dataframe_json (str): A JSON string representation of the DataFrame.
+
+        Returns:
+            tuple: A tuple containing a JSON string for the DataFrame.
+        """
+        # Deserialize JSON string to DataFrame
+        df = pd.read_json(StringIO(dataframe_json))
+        return (df.isna().to_json(),)

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "data-analysis"
 description = "Data analysis custom modules for ComfyUI - Use Pandas & Matplotlib within ComfyUI"
-version = "1.0.17"
+version = "1.0.18"
 license = {file = "LICENSE"}
 
 [project.urls]