Added Pandas Create and Pandas Create with Index nodes to create a DataFrame from text
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HowToSD
@@ -3,6 +3,8 @@ from .modules.matplotlib.mpl_bar import MPLBar
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from .modules.matplotlib.mpl_line import MPLLine
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from .modules.matplotlib.mpl_scatter import MPLScatter
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from .modules.pandas_wrapper.pandas_columns import PandasColumns
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from .modules.pandas_wrapper.pandas_create import PandasCreate
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from .modules.pandas_wrapper.pandas_create_with_index import PandasCreateWithIndex
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from .modules.pandas_wrapper.pandas_head import PandasHead
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from .modules.pandas_wrapper.pandas_index import PandasIndex
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from .modules.pandas_wrapper.pandas_join import PandasJoin
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@@ -23,6 +25,8 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
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"MPLLine": MPLLine,
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"MPLScatter": MPLScatter,
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"PandasColumns": PandasColumns,
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"PandasCreate": PandasCreate,
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"PandasCreateWithIndex": PandasCreateWithIndex,
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"PandasHead": PandasHead,
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"PandasIndex": PandasIndex,
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"PandasJoin": PandasJoin,
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@@ -46,6 +50,8 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
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"MPLLine": "MPL Line Plot",
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"MPLScatter": "MPL Scatter Plot",
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"PandasColumns": "Pandas Columns",
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"PandasCreate": "Pandas Create",
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"PandasCreateWithIndex": "Pandas Create with Index",
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"PandasHead": "Pandas Head",
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"PandasIndex": "Pandas Index",
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"PandasJoin": "Pandas Join",
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@@ -15,6 +15,8 @@ You can right-click, select **Add Node**, go to **Data Analysis**, and look for
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|-------------------------|-------------------------------------|
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| **Pandas Load CSV** | Load a CSV file |
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| **Pandas Save CSV** | Save a DataFrame to a CSV file |
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| **Pandas Create** | Create a DataFrame from CSV text field |
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| **Pandas Create with Index** | Create a DataFrame from CSV text field containing index |
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| **Pandas Columns** | Extract column labels |
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| **Pandas Index** | Extract row labels (index) |
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| **Pandas Select Columns** | Select specific columns from a DataFrame |
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@@ -23,7 +25,7 @@ You can right-click, select **Add Node**, go to **Data Analysis**, and look for
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| **Pandas Head** | Extract the first few rows |
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| **Pandas Show DataFrame** | Display DataFrame contents |
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| **Pandas Show Text** | Display Text |
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| **Pandas Summary** | Show DataFrame statistics |
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| **Pandas Summary** | Extract DataFrame statistics |
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| **Pandas Sort** | Sort DataFrame by a column |
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| **Pandas To String** | Convert DataFrame to a string |
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| **MPL Bar Chart** | Generate a bar chart |
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@@ -44,11 +46,17 @@ CSV file path is relative to the ComfyUI installation directory unless you speci
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## Saving data
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Use **Pandas Save CSV** node to save the DataFrame to a CSV file.
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## Extracting column and row labels
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Use **Pandas Columns** and **Pandas Index** nodes. As these nodes outputs JSON-serialized Index object, to display the value, use **Pandas Show Text** node as shown below:
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## Creating DataFrame on the UI
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Use **Pandas Create** or **Pandas Create with Index** nodes. These nodes display the multiline text area where you can enter the data in CSV format.
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If the data contains an index column, use **Pandas Create with Index** and specify the index column.
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## Extracting column and row labels
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Use **Pandas Columns** and **Pandas Index** nodes. As these nodes output JSON-serialized Index object, to display the value, use **Pandas Show Text** node as shown below:
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## Selecting columns and rows
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Use **Pandas Select Columns** for selecting columns, **Pandas Select Rows** to select rows by a filter condition.
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@@ -91,8 +99,9 @@ This node has been copied to display text without requiring the user to install
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## Displaying DataFrame contents
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Use **Pandas Show DataFrame** node. When the number of rows is large, Pandas automatically hides middle rows during string conversion, so the display size should be always manageable.
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## Showing Show DataFrame statistics
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Use **Pandas Summary**.
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## Extracting DataFrame statistics
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Use **Pandas Summary** to extract statistics then connect the output to **Pandas Show Text** for display.
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## Sorting DataFrame by a column
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Use **Pandas Sort**.
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@@ -0,0 +1 @@
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{"last_node_id":4,"last_link_id":2,"nodes":[{"id":1,"type":"PandasCreate","pos":[-326.9039306640625,1636.5106201171875],"size":[210,138.73008728027344],"flags":{},"order":0,"mode":0,"inputs":[],"outputs":[{"name":"STRING","type":"STRING","links":[1],"slot_index":0}],"properties":{"Node name for S&R":"PandasCreate"},"widgets_values":["A,B\n1,10\n2,20\n3,30"]},{"id":4,"type":"PandasShowDataFrame","pos":[-64.19639587402344,1834.85595703125],"size":[217.840576171875,134.7733612060547],"flags":{},"order":3,"mode":0,"inputs":[{"name":"dataframe_json","type":"STRING","link":2,"widget":{"name":"dataframe_json"}}],"outputs":[{"name":"STRING","type":"STRING","links":null,"shape":6}],"properties":{"Node name for S&R":"PandasShowDataFrame"},"widgets_values":[""," A B\nUS 1 10\nFrance 2 20\nGermany 3 30"]},{"id":3,"type":"PandasCreateWithIndex","pos":[-324.8951416015625,1834.365478515625],"size":[210,134.33523559570312],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[{"name":"STRING","type":"STRING","links":[2],"slot_index":0}],"properties":{"Node name for S&R":"PandasCreateWithIndex"},"widgets_values":["index,A,B\nUS,1,10\nFrance,2,20\nGermany,3,30",0]},{"id":2,"type":"PandasShowDataFrame","pos":[-64.8188705444336,1635.102783203125],"size":[216.83184814453125,135.75343322753906],"flags":{},"order":2,"mode":0,"inputs":[{"name":"dataframe_json","type":"STRING","link":1,"widget":{"name":"dataframe_json"}}],"outputs":[{"name":"STRING","type":"STRING","links":null,"shape":6}],"properties":{"Node name for S&R":"PandasShowDataFrame"},"widgets_values":[""," A B\n0 1 10\n1 2 20\n2 3 30"]}],"links":[[1,1,0,2,0,"STRING"],[2,3,0,4,0,"STRING"]],"groups":[],"config":{},"extra":{"ds":{"scale":1.5305009021021516,"offset":[477.1330786503176,-1565.7063254190393]},"node_versions":{"data-analysis":"3e5a6d6efce2f08933edccaf9e1c1e38896df00b"},"ue_links":[]},"version":0.4}
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@@ -0,0 +1,46 @@
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from typing import Any, Dict
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from io import StringIO
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import pandas as pd
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class PandasCreate:
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"""
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PandasLoadCSV:
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A class for creating a pandas DataFrame using values entered in the text field.
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"""
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@classmethod
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def INPUT_TYPES(cls) -> Dict[str, Any]:
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"""
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Defines the input types for the `create` function.
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Returns:
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Dict[str, Any]: A dictionary specifying required input types.
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"""
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return {
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"required": {
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"data": ("STRING", {"multiline": True}),
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}
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}
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RETURN_TYPES: tuple = ("STRING",)
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FUNCTION: str = "create"
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CATEGORY: str = "Data Analysis"
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def create(self, data: str) -> tuple:
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"""
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Create a pandas DataFrame using values entered in the text field and converts it to a JSON string.
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Args:
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file_path (str): The path to the CSV file.
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Returns:
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tuple: A tuple containing a JSON string representation of the DataFrame.
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"""
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# Read CSV file into DataFrame
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df = pd.read_csv(StringIO(data))
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# Convert DataFrame to JSON
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result_json = df.to_json()
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return (result_json,)
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@@ -0,0 +1,49 @@
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from typing import Any, Dict
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from io import StringIO
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import pandas as pd
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class PandasCreateWithIndex:
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"""
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PandasLoadCSV:
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A class for creating a pandas DataFrame using values entered in the text field.
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Input data is assume to have an index.
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"""
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@classmethod
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def INPUT_TYPES(cls) -> Dict[str, Any]:
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"""
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Defines the input types for the `create` function.
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Returns:
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Dict[str, Any]: A dictionary specifying required input types.
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"""
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return {
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"required": {
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"data": ("STRING", {"multiline": True}),
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"index_col": ("INT", {"default": 0, "min": 0, "max": 10000})
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}
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}
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RETURN_TYPES: tuple = ("STRING",)
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FUNCTION: str = "create"
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CATEGORY: str = "Data Analysis"
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def create(self, data: str, index_col: int=0) -> tuple:
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"""
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Create a pandas DataFrame using values entered in the text field and converts it to a JSON string.
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Input data is assume to have an index.
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Args:
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file_path (str): The path to the CSV file.
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Returns:
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tuple: A tuple containing a JSON string representation of the DataFrame.
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"""
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# Read CSV file into DataFrame
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df = pd.read_csv(StringIO(data), index_col=index_col)
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# Convert DataFrame to JSON
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result_json = df.to_json()
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return (result_json,)
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+1
-1
@@ -1,7 +1,7 @@
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[project]
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name = "data-analysis"
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description = "Data analysis custom modules for ComfyUI - Use Pandas & Matplotlib within ComfyUI"
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version = "1.0.6"
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version = "1.0.7"
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license = {file = "LICENSE"}
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[project.urls]
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