Added Pandas Is NA and Pandas Drop NA nodes.

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(),)