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Added Pandas Horizontal Split and Vertical Split nodes.

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HowToSD
2025-02-18 21:16:52 -08:00
parent 9c668c78d7
commit 345d9642da
8 changed files with 148 additions and 4 deletions
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__init__.py
+8 -3
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@@ -23,6 +23,7 @@ from .modules.pandas_wrapper.pandas_tan import PandasTan
from .modules.pandas_wrapper.pandas_group_by import PandasGroupBy
from .modules.pandas_wrapper.pandas_head import PandasHead
from .modules.pandas_wrapper.pandas_horizontal_concat import PandasHorizontalConcat
from .modules.pandas_wrapper.pandas_horizontal_split import PandasHorizontalSplit
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
@@ -62,7 +63,7 @@ from .modules.pandas_wrapper.pandas_summary import PandasSummary
from .modules.pandas_wrapper.pandas_to_string import PandasToString
from .modules.pandas_wrapper.pandas_var import PandasVar
from .modules.pandas_wrapper.pandas_vertical_concat import PandasVerticalConcat
from .modules.pandas_wrapper.pandas_vertical_split import PandasVerticalSplit
T = TypeVar("T")
@@ -91,6 +92,7 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
"PandasGroupBy": PandasGroupBy,
"PandasHead": PandasHead,
"PandasHorizontalConcat": PandasHorizontalConcat,
"PandasHorizontalSplit": PandasHorizontalSplit,
"PandasIlocRowSeries": PandasIlocRowSeries,
"PandasIlocRowsDataFrame": PandasIlocRowsDataFrame,
"PandasIndex": PandasIndex,
@@ -129,7 +131,8 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
"PandasSummary": PandasSummary,
"PandasToString": PandasToString,
"PandasVar": PandasVar,
"PandasVerticalConcat": PandasVerticalConcat
"PandasVerticalConcat": PandasVerticalConcat,
"PandasVerticalSplit": PandasVerticalSplit
}
"""
NODE_CLASS_MAPPINGS (Dict[str, Type[T]]):
@@ -161,6 +164,7 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
"PandasGroupBy": "Pandas Group By",
"PandasHead": "Pandas Head",
"PandasHorizontalConcat": "Pandas Horizontal Concat",
"PandasHorizontalSplit": "Pandas Horizontal Split",
"PandasIlocRowSeries": "Pandas Iloc Row Series",
"PandasIlocRowsDataFrame": "Pandas Iloc Rows DataFrame",
"PandasIndex": "Pandas Index",
@@ -199,7 +203,8 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
"PandasSummary": "Pandas Summary",
"PandasToString": "Pandas To String",
"PandasVar": "Pandas Var",
"PandasVerticalConcat": "Pandas Vertical Concat"
"PandasVerticalConcat": "Pandas Vertical Concat",
"PandasVerticalSplit": "Pandas Vertical Split"
}
"""
NODE_DISPLAY_NAME_MAPPINGS (Dict[str, str]):
docs/reference/node_reference.md
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@@ -95,6 +95,8 @@
| Node | Description |
| --- | --- |
| [Pandas Horizontal Concat](pandas_horizontal_concat.md) | Horizontally concatenates two pandas DataFrames. |
| [Pandas Horizontal Split](pandas_horizontal_split.md) | Horizontally splits a Pandas DataFrame into two pandas DataFrames. |
| [Pandas Join](pandas_join.md) | Merges two pandas DataFrames based on a common column. |
| [Pandas Sort](pandas_sort.md) | Sorts a pandas DataFrame by a specified column. |
| [Pandas Vertical Concat](pandas_vertical_concat.md) | Vertically concatenates two pandas DataFrames. |
| [Pandas Vertical Split](pandas_vertical_split.md) | Vertically splits a Pandas DataFrame into two pandas DataFrames. |
docs/reference/pandas_horizontal_split.md
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@@ -0,0 +1,19 @@
# Pandas Horizontal Split
Horizontally splits a Pandas DataFrame into two pandas DataFrames.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
| column_integer_position | Int |
## Output
| Data type |
|---|
| DataFrame |
| DataFrame |
<HR>
Category: Transformation
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
docs/reference/pandas_vertical_split.md
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@@ -0,0 +1,19 @@
# Pandas Vertical Split
Vertically splits a Pandas DataFrame into two pandas DataFrames.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
| row_integer_position | Int |
## Output
| Data type |
|---|
| DataFrame |
| DataFrame |
<HR>
Category: Transformation
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
examples/workflows/split.json
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@@ -0,0 +1 @@
{"last_node_id":70,"last_link_id":74,"nodes":[{"id":68,"type":"PandasHorizontalSplit","pos":[-126.66181182861328,2918.54736328125],"size":[317.4000244140625,78],"flags":{},"order":3,"mode":0,"inputs":[{"name":"dataframe","type":"DATAFRAME","link":74}],"outputs":[{"name":"Left DataFrame","type":"DATAFRAME","links":[72],"slot_index":0},{"name":"Right DataFrame","type":"DATAFRAME","links":[73],"slot_index":1}],"properties":{"Node name for S&R":"PandasHorizontalSplit"},"widgets_values":[1]},{"id":69,"type":"PandasShowDataFrame","pos":[485.1441345214844,3092.146484375],"size":[210,121.16669464111328],"flags":{},"order":7,"mode":0,"inputs":[{"name":"dataframe","type":"DATAFRAME","link":73}],"outputs":[{"name":"STRING","type":"STRING","links":null,"shape":6}],"properties":{"Node name for S&R":"PandasShowDataFrame"},"widgets_values":[" B C\n0 12.3 Dog\n1 23.4 Cat\n2 34.5 Rabbit"]},{"id":64,"type":"PandasCreate","pos":[-300.70599365234375,2670.06005859375],"size":[210,123.86104583740234],"flags":{},"order":0,"mode":0,"inputs":[],"outputs":[{"name":"DATAFRAME","type":"DATAFRAME","links":[68,71,74],"slot_index":0}],"properties":{"Node name for S&R":"PandasCreate"},"widgets_values":["A,B,C\n10,12.3,Dog\n20,23.4,Cat\n30,34.5,Rabbit"]},{"id":70,"type":"PandasShowDataFrame","pos":[218.49526977539062,3108.108642578125],"size":[210,103.45830535888672],"flags":{},"order":6,"mode":0,"inputs":[{"name":"dataframe","type":"DATAFRAME","link":72}],"outputs":[{"name":"STRING","type":"STRING","links":null,"shape":6}],"properties":{"Node name for S&R":"PandasShowDataFrame"},"widgets_values":[" A\n0 10\n1 20\n2 30"]},{"id":32,"type":"PandasShowDataFrame","pos":[-20.655092239379883,2675.75244140625],"size":[210,104.88404083251953],"flags":{},"order":2,"mode":0,"inputs":[{"name":"dataframe","type":"DATAFRAME","link":71}],"outputs":[{"name":"STRING","type":"STRING","links":null,"shape":6}],"properties":{"Node name for S&R":"PandasShowDataFrame"},"widgets_values":[" A B C\n0 10 12.3 Dog\n1 20 23.4 Cat\n2 30 34.5 Rabbit"]},{"id":65,"type":"PandasVerticalSplit","pos":[-134.28067016601562,2448.783203125],"size":[330,78],"flags":{},"order":1,"mode":0,"inputs":[{"name":"dataframe","type":"DATAFRAME","link":68}],"outputs":[{"name":"Top DataFrame","type":"DATAFRAME","links":[69],"slot_index":0},{"name":"Bottom DataFrame","type":"DATAFRAME","links":[70],"slot_index":1}],"properties":{"Node name for S&R":"PandasVerticalSplit"},"widgets_values":[2]},{"id":67,"type":"PandasShowDataFrame","pos":[229.82748413085938,2517.0009765625],"size":[272.933349609375,101],"flags":{},"order":5,"mode":0,"inputs":[{"name":"dataframe","type":"DATAFRAME","link":70}],"outputs":[{"name":"STRING","type":"STRING","links":null,"shape":6}],"properties":{"Node name for S&R":"PandasShowDataFrame"},"widgets_values":[" A B C\n2 30 34.5 Rabbit"]},{"id":66,"type":"PandasShowDataFrame","pos":[230.1259307861328,2341.906982421875],"size":[260.433349609375,108.5],"flags":{},"order":4,"mode":0,"inputs":[{"name":"dataframe","type":"DATAFRAME","link":69}],"outputs":[{"name":"STRING","type":"STRING","links":null,"shape":6}],"properties":{"Node name for S&R":"PandasShowDataFrame"},"widgets_values":[" A B C\n0 10 12.3 Dog\n1 20 23.4 Cat"]}],"links":[[68,64,0,65,0,"DATAFRAME"],[69,65,0,66,0,"DATAFRAME"],[70,65,1,67,0,"DATAFRAME"],[71,64,0,32,0,"DATAFRAME"],[72,68,0,70,0,"DATAFRAME"],[73,68,1,69,0,"DATAFRAME"],[74,64,0,68,0,"DATAFRAME"]],"groups":[],"config":{},"extra":{"ds":{"scale":0.8264462809917354,"offset":[380.23215878327846,-2286.7820859816943]},"node_versions":{"data-analysis":"a5de56622e0e408bdf3d7488fca526526a2d3ec2"},"ue_links":[]},"version":0.4}
modules/pandas_wrapper/pandas_horizontal_split.py
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@@ -0,0 +1,49 @@
from typing import Any, Dict
import pandas as pd
class PandasHorizontalSplit:
"""
Horizontally splits a Pandas DataFrame into two pandas DataFrames.
category: Transformation
"""
@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", {}),
"column_integer_position": ("INT", {"default": 0, "min": -1, "max": 2**31})
}
}
RETURN_TYPES: tuple = ("DATAFRAME", "DATAFRAME")
RETURN_NAMES: tuple = ("Left DataFrame", "Right DataFrame")
FUNCTION: str = "f"
CATEGORY: str = "Data Analysis"
def f(self, dataframe: pd.DataFrame, column_integer_position: int) -> tuple:
"""
Horizontally splits a Pandas DataFrame into two pandas DataFrames.
Args:
dataframe (pd.DataFrame): The DataFrame to split.
column_integer_position (int): The column integer position where the split occurs.
The left DataFrame contains columns [0, column_integer_position-1],
and the right DataFrame contains columns [column_integer_position, end].
Returns:
tuple: A tuple containing the left and right DataFrames.
"""
df_left = dataframe.iloc[:,:column_integer_position]
df_right = dataframe.iloc[:,column_integer_position:]
return (df_left, df_right)
modules/pandas_wrapper/pandas_vertical_split.py
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@@ -0,0 +1,49 @@
from typing import Any, Dict
import pandas as pd
class PandasVerticalSplit:
"""
Vertically splits a Pandas DataFrame into two pandas DataFrames.
category: Transformation
"""
@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", {}),
"row_integer_position": ("INT", {"default": 0, "min": -1, "max": 2**31})
}
}
RETURN_TYPES: tuple = ("DATAFRAME", "DATAFRAME")
RETURN_NAMES: tuple = ("Top DataFrame", "Bottom DataFrame")
FUNCTION: str = "f"
CATEGORY: str = "Data Analysis"
def f(self, dataframe: pd.DataFrame, row_integer_position: int) -> tuple:
"""
Vertically splits a Pandas DataFrame into two pandas DataFrames.
Args:
dataframe (pd.DataFrame): The DataFrame to split.
row_integer_position (int): The row integer position where the split occurs.
The top DataFrame contains rows [0, row_integer_position-1],
and the bottom DataFrame contains rows [row_integer_position, end].
Returns:
tuple: A tuple containing the top and bottom DataFrames.
"""
df_top = dataframe.iloc[:row_integer_position]
df_bottom = dataframe.iloc[row_integer_position:]
return (df_top, df_bottom)
pyproject.toml
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@@ -1,7 +1,7 @@
[project]
name = "data-analysis"
description = "Data analysis custom modules for ComfyUI - Use Pandas & Matplotlib within ComfyUI"
version = "1.1.5"
version = "1.1.6"
license = {file = "LICENSE"}
[project.urls]