Added Show Text, Columns, Index nodes

modules/pandas_wrapper/pandas_columns.py

@@ -0,0 +1,43 @@
+from typing import Any, Dict
+from io import StringIO
+import pandas as pd
+from .utils import index_to_jsons
+
+class PandasColumns:
+    """
+    PandasColumns:
+        A class for retrieving the column labels of a pandas DataFrame.
+    """
+    
+    @classmethod
+    def INPUT_TYPES(cls) -> Dict[str, Any]:
+        """
+        Defines the input types for the `columns` function.
+
+        Returns:
+            Dict[str, Any]: A dictionary specifying required input types.
+        """
+        return {
+            "required": {
+                "dataframe_json": ("STRING", {"multiline": True})
+            }
+        }
+
+    RETURN_TYPES: tuple = ("STRING",)
+    FUNCTION: str = "columns"
+    CATEGORY: str = "Data Analysis"
+
+    def columns(self, dataframe_json: str) -> tuple:
+        """
+        Returns the column labels of a pandas DataFrame.
+
+        Args:
+            dataframe_json (str): A JSON string representation of the DataFrame.
+
+        Returns:
+            tuple: A tuple containing a JSON string for the serialized pandas.Index containing columns.
+        """
+        # Deserialize JSON string to DataFrame
+        df = pd.read_json(StringIO(dataframe_json))
+        columns = df.columns
+        return (index_to_jsons(columns),)

modules/pandas_wrapper/pandas_index.py

@@ -0,0 +1,43 @@
+from typing import Any, Dict
+from io import StringIO
+import pandas as pd
+from .utils import index_to_jsons
+
+class PandasIndex:
+    """
+    PandasColumns:
+        A class for retrieving the row labels (index) of a pandas DataFrame.
+    """
+    
+    @classmethod
+    def INPUT_TYPES(cls) -> Dict[str, Any]:
+        """
+        Defines the input types for the `row_index` function.
+
+        Returns:
+            Dict[str, Any]: A dictionary specifying required input types.
+        """
+        return {
+            "required": {
+                "dataframe_json": ("STRING", {"multiline": True})
+            }
+        }
+
+    RETURN_TYPES: tuple = ("STRING",)
+    FUNCTION: str = "row_index"
+    CATEGORY: str = "Data Analysis"
+
+    def row_index(self, dataframe_json: str) -> tuple:
+        """
+        Returns the row labels (index) of a pandas DataFrame.
+
+        Args:
+            dataframe_json (str): A JSON string representation of the DataFrame.
+
+        Returns:
+            tuple: A tuple containing a JSON string for the serialized pandas.Index containing row labels.
+        """
+        # Deserialize JSON string to DataFrame
+        df = pd.read_json(StringIO(dataframe_json))
+        row_index = df.index
+        return (index_to_jsons(row_index),)

modules/pandas_wrapper/pandas_join.py

@@ -12,7 +12,7 @@ class PandasJoin:
     @classmethod
     def INPUT_TYPES(cls) -> Dict[str, Any]:
         """
-        Defines the input types for the `sort_rows` function.
+        Defines the input types for the `join` function.
 
         Returns:
             Dict[str, Any]: A dictionary specifying required input types.

modules/pandas_wrapper/pandas_show_text.py

@@ -0,0 +1,48 @@
+"""
+Almost all of this code was taken from
+https://github.com/pythongosssss/ComfyUI-Custom-Scripts/blob/main/py/show_text.py
+
+See credit/credit.md for the full license.
+"""
+
+class PandasShowText:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "text": ("STRING", {"forceInput": True}),
+            },
+            "hidden": {
+                "unique_id": "UNIQUE_ID",
+                "extra_pnginfo": "EXTRA_PNGINFO",
+            },
+        }
+
+    INPUT_IS_LIST = True
+    RETURN_TYPES = ("STRING",)
+    FUNCTION = "notify"
+    OUTPUT_NODE = True
+    OUTPUT_IS_LIST = (True,)
+
+    CATEGORY = "Data Analysis"
+
+    def notify(self, text, unique_id=None, extra_pnginfo=None):
+        if unique_id is not None and extra_pnginfo is not None:
+            if not isinstance(extra_pnginfo, list):
+                print("Error: extra_pnginfo is not a list")
+            elif (
+                not isinstance(extra_pnginfo[0], dict)
+                or "workflow" not in extra_pnginfo[0]
+            ):
+                print("Error: extra_pnginfo[0] is not a dict or missing 'workflow' key")
+            else:
+                workflow = extra_pnginfo[0]["workflow"]
+                node = next(
+                    (x for x in workflow["nodes"] if str(x["id"]) == str(unique_id[0])),
+                    None,
+                )
+                if node:
+                    node["widgets_values"] = [text]
+        else:
+            print("unique_id or extra_pnginfo is None.")
+        return {"ui": {"text": text}, "result": (text,)}

modules/pandas_wrapper/utils.py

@@ -0,0 +1,63 @@
+import json
+import pandas as pd
+
+def series_to_jsons(series: pd.Series) -> str:
+    """
+    Convert a pandas Series to a JSON string.
+
+    Args:
+        series (pd.Series): The pandas Series to convert.
+
+    Returns:
+        str: A JSON string representing the Series, including its data, index, and name.
+    """
+    array = [x.item() if hasattr(x, "item") else x for x in series.tolist()]  # Convert NumPy types to Python types
+    index = [x.item() if hasattr(x, "item") else x for x in series.index.tolist()]  # Convert index to Python types
+    name = series.name
+
+    d = {"array": array, "index": index, "name": name}
+
+    return json.dumps(d)
+
+def jsons_to_series(s: str) -> pd.Series:
+    """
+    Convert a JSON string to a pandas Series.
+
+    Args:
+        s (str): The JSON string representing the Series.
+
+    Returns:
+        pd.Series: The reconstructed pandas Series.
+    """
+    d = json.loads(s)
+    return pd.Series(data=d["array"], index=d["index"], name=d["name"])
+
+def index_to_jsons(index: pd.Index) -> str:
+    """
+    Convert a pandas Index to a JSON string.
+
+    Args:
+        index (pd.Index): The pandas Index to convert.
+
+    Returns:
+        str: A JSON string representing the Index, including its values and name.
+    """
+    index_list = [x.item() if hasattr(x, "item") else x for x in index.tolist()]  # Convert NumPy types to Python types
+    index_name = index.name  # Preserve index name
+
+    d = {"index": index_list, "name": index_name}
+
+    return json.dumps(d)
+
+def jsons_to_index(s: str) -> pd.Index:
+    """
+    Convert a JSON string to a pandas Index.
+
+    Args:
+        s (str): The JSON string representing the Index.
+
+    Returns:
+        pd.Index: The reconstructed pandas Index.
+    """
+    d = json.loads(s)
+    return pd.Index(d["index"], name=d.get("name"))  # Restore index with name