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Added Pandas Drop Duplicates node. Fixed Pandas Drop NA node to output a DataFrame instead of legacy JSON string.

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This commit is contained in:
HowToSD
2025-02-20 13:28:37 -08:00
parent 472565908b
commit fff4b58abb
7 changed files with 264 additions and 29 deletions
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__init__.py
+36 -27
View File
@@ -1,3 +1,4 @@
# This file is auto-generated. Do not edit manually.
from typing import Dict, Type, TypeVar
from .modules.cda.cda_float_create import CDAFloatCreate
from .modules.cda.cda_int_create import CDAIntCreate
@@ -17,6 +18,7 @@ from .modules.pandas_wrapper.pandas_as_float import PandasAsFloat
from .modules.pandas_wrapper.pandas_as_int import PandasAsInt
from .modules.pandas_wrapper.pandas_as_string import PandasAsString
from .modules.pandas_wrapper.pandas_columns import PandasColumns
from .modules.pandas_wrapper.pandas_cos import PandasCos
from .modules.pandas_wrapper.pandas_count import PandasCount
from .modules.pandas_wrapper.pandas_create import PandasCreate
from .modules.pandas_wrapper.pandas_create_with_index import PandasCreateWithIndex
@@ -28,12 +30,9 @@ from .modules.pandas_wrapper.pandas_div import PandasDiv
from .modules.pandas_wrapper.pandas_div_scalar_float import PandasDivScalarFloat
from .modules.pandas_wrapper.pandas_div_scalar_int import PandasDivScalarInt
from .modules.pandas_wrapper.pandas_div_series import PandasDivSeries
from .modules.pandas_wrapper.pandas_drop_duplicates import PandasDropDuplicates
from .modules.pandas_wrapper.pandas_dropna import PandasDropNA
from .modules.pandas_wrapper.pandas_exp import PandasExp
from .modules.pandas_wrapper.pandas_log import PandasLog
from .modules.pandas_wrapper.pandas_sin import PandasSin
from .modules.pandas_wrapper.pandas_cos import PandasCos
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
@@ -51,6 +50,7 @@ from .modules.pandas_wrapper.pandas_load_html import PandasLoadHTML
from .modules.pandas_wrapper.pandas_load_json import PandasLoadJSON
from .modules.pandas_wrapper.pandas_loc_cell_str import PandasLocCellStr
from .modules.pandas_wrapper.pandas_loc_row_series import PandasLocRowSeries
from .modules.pandas_wrapper.pandas_log import PandasLog
from .modules.pandas_wrapper.pandas_max import PandasMax
from .modules.pandas_wrapper.pandas_mean import PandasMean
from .modules.pandas_wrapper.pandas_median import PandasMedian
@@ -70,12 +70,13 @@ from .modules.pandas_wrapper.pandas_save_csv import PandasSaveCSV
from .modules.pandas_wrapper.pandas_save_json import PandasSaveJSON
from .modules.pandas_wrapper.pandas_select_columns import PandasSelectColumns
from .modules.pandas_wrapper.pandas_select_rows import PandasSelectRows
from .modules.pandas_wrapper.pandas_series_to_string import PandasSeriesToString
from .modules.pandas_wrapper.pandas_series_to_dataframe import PandasSeriesToDataFrame
from .modules.pandas_wrapper.pandas_series_to_string import PandasSeriesToString
from .modules.pandas_wrapper.pandas_show_dataframe import PandasShowDataFrame
from .modules.pandas_wrapper.pandas_show_index import PandasShowIndex
from .modules.pandas_wrapper.pandas_show_series import PandasShowSeries
from .modules.pandas_wrapper.pandas_show_text import PandasShowText
from .modules.pandas_wrapper.pandas_sin import PandasSin
from .modules.pandas_wrapper.pandas_sort import PandasSort
from .modules.pandas_wrapper.pandas_std import PandasStd
from .modules.pandas_wrapper.pandas_sub import PandasSub
@@ -84,14 +85,20 @@ from .modules.pandas_wrapper.pandas_sub_scalar_int import PandasSubScalarInt
from .modules.pandas_wrapper.pandas_sub_series import PandasSubSeries
from .modules.pandas_wrapper.pandas_sum import PandasSum
from .modules.pandas_wrapper.pandas_summary import PandasSummary
from .modules.pandas_wrapper.pandas_tan import PandasTan
from .modules.pandas_wrapper.pandas_to_string import PandasToString
from .modules.pandas_wrapper.pandas_transpose import PandasTranspose
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")
"""
NODE_CLASS_MAPPINGS (Dict[str, Type[T]]):
A dictionary mapping node names to their corresponding class implementations.
"""
NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
"CDAFloatCreate": CDAFloatCreate,
"CDAIntCreate": CDAIntCreate,
@@ -111,6 +118,7 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
"PandasAsInt": PandasAsInt,
"PandasAsString": PandasAsString,
"PandasColumns": PandasColumns,
"PandasCos": PandasCos,
"PandasCount": PandasCount,
"PandasCreate": PandasCreate,
"PandasCreateWithIndex": PandasCreateWithIndex,
@@ -122,12 +130,9 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
"PandasDivScalarFloat": PandasDivScalarFloat,
"PandasDivScalarInt": PandasDivScalarInt,
"PandasDivSeries": PandasDivSeries,
"PandasDropDuplicates": PandasDropDuplicates,
"PandasDropNA": PandasDropNA,
"PandasExp": PandasExp,
"PandasLog": PandasLog,
"PandasSin": PandasSin,
"PandasCos": PandasCos,
"PandasTan": PandasTan,
"PandasGroupBy": PandasGroupBy,
"PandasHead": PandasHead,
"PandasHorizontalConcat": PandasHorizontalConcat,
@@ -145,6 +150,7 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
"PandasLoadJSON": PandasLoadJSON,
"PandasLocCellStr": PandasLocCellStr,
"PandasLocRowSeries": PandasLocRowSeries,
"PandasLog": PandasLog,
"PandasMax": PandasMax,
"PandasMean": PandasMean,
"PandasMedian": PandasMedian,
@@ -154,22 +160,23 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
"PandasMulScalarFloat": PandasMulScalarFloat,
"PandasMulScalarInt": PandasMulScalarInt,
"PandasMulSeries": PandasMulSeries,
"PandasRename": PandasRename,
"PandasReplace": PandasReplace,
"PandasPow": PandasPow,
"PandasPowScalarFloat": PandasPowScalarFloat,
"PandasPowScalarInt": PandasPowScalarInt,
"PandasPowSeries": PandasPowSeries,
"PandasRename": PandasRename,
"PandasReplace": PandasReplace,
"PandasSaveCSV": PandasSaveCSV,
"PandasSaveJSON": PandasSaveJSON,
"PandasSelectColumns": PandasSelectColumns,
"PandasSelectRows": PandasSelectRows,
"PandasSeriesToString": PandasSeriesToString,
"PandasSeriesToDataFrame": PandasSeriesToDataFrame,
"PandasSeriesToString": PandasSeriesToString,
"PandasShowDataFrame": PandasShowDataFrame,
"PandasShowIndex": PandasShowIndex,
"PandasShowSeries": PandasShowSeries,
"PandasShowText": PandasShowText,
"PandasSin": PandasSin,
"PandasSort": PandasSort,
"PandasStd": PandasStd,
"PandasSub": PandasSub,
@@ -178,15 +185,18 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
"PandasSubSeries": PandasSubSeries,
"PandasSum": PandasSum,
"PandasSummary": PandasSummary,
"PandasTan": PandasTan,
"PandasToString": PandasToString,
"PandasTranspose": PandasTranspose,
"PandasVar": PandasVar,
"PandasVerticalConcat": PandasVerticalConcat,
"PandasVerticalSplit": PandasVerticalSplit
"PandasVerticalSplit": PandasVerticalSplit,
}
"""
NODE_CLASS_MAPPINGS (Dict[str, Type[T]]):
A dictionary mapping node names to their corresponding class implementations.
NODE_DISPLAY_NAME_MAPPINGS (Dict[str, str]):
A dictionary mapping node names to user-friendly display names.
"""
NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
@@ -202,12 +212,13 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
"MPLScatter": "MPL Scatter Plot",
"PandasAdd": "Pandas Add",
"PandasAddScalarFloat": "Pandas Add Scalar Float",
"PandasAddScalarInt":" Pandas Add Scalar Int",
"PandasAddScalarInt": "Pandas Add Scalar Int",
"PandasAddSeries": "Pandas Add Series",
"PandasAsFloat": "Pandas As Float",
"PandasAsInt": "Pandas As Int",
"PandasAsString": "Pandas As String",
"PandasColumns": "Pandas Columns",
"PandasCos": "Pandas Cos",
"PandasCount": "Pandas Count",
"PandasCreate": "Pandas Create",
"PandasCreateWithIndex": "Pandas Create With Index",
@@ -219,12 +230,9 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
"PandasDivScalarFloat": "Pandas Div Scalar Float",
"PandasDivScalarInt": "Pandas Div Scalar Int",
"PandasDivSeries": "Pandas Div Series",
"PandasDropDuplicates": "Pandas Drop Duplicates",
"PandasDropNA": "Pandas Drop NA",
"PandasExp": "Pandas Exp",
"PandasLog": "Pandas Log",
"PandasSin": "Pandas Sin",
"PandasCos": "Pandas Cos",
"PandasTan": "Pandas Tan",
"PandasGroupBy": "Pandas Group By",
"PandasHead": "Pandas Head",
"PandasHorizontalConcat": "Pandas Horizontal Concat",
@@ -242,6 +250,7 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
"PandasLoadJSON": "Pandas Load JSON",
"PandasLocCellStr": "Pandas Loc Cell Str",
"PandasLocRowSeries": "Pandas Loc Row Series",
"PandasLog": "Pandas Log",
"PandasMax": "Pandas Max",
"PandasMean": "Pandas Mean",
"PandasMedian": "Pandas Median",
@@ -261,12 +270,13 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
"PandasSaveJSON": "Pandas Save JSON",
"PandasSelectColumns": "Pandas Select Columns",
"PandasSelectRows": "Pandas Select Rows",
"PandasSeriesToString": "Pandas Series To String",
"PandasSeriesToDataFrame": "Pandas Series To DataFrame",
"PandasSeriesToString": "Pandas Series To String",
"PandasShowDataFrame": "Pandas Show DataFrame",
"PandasShowIndex": "Pandas Show Index",
"PandasShowSeries": "Pandas Show Series",
"PandasShowText": "Pandas Show Text",
"PandasSin": "Pandas Sin",
"PandasSort": "Pandas Sort",
"PandasStd": "Pandas Std",
"PandasSub": "Pandas Sub",
@@ -275,21 +285,20 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
"PandasSubSeries": "Pandas Sub Series",
"PandasSum": "Pandas Sum",
"PandasSummary": "Pandas Summary",
"PandasTan": "Pandas Tan",
"PandasToString": "Pandas To String",
"PandasTranspose": "Pandas Transpose",
"PandasVar": "Pandas Var",
"PandasVerticalConcat": "Pandas Vertical Concat",
"PandasVerticalSplit": "Pandas Vertical Split"
"PandasVerticalSplit": "Pandas Vertical Split",
}
"""
NODE_DISPLAY_NAME_MAPPINGS (Dict[str, str]):
A dictionary mapping node names to user-friendly display names.
"""
"""
Below two lines were taken from:
https://github.com/pythongosssss/ComfyUI-Custom-Scripts/blob/main/__init__.py
See credit/credit.md for the full license.
"""
WEB_DIRECTORY = "./web"
__all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS", "WEB_DIRECTORY"]
dev/scripts/init_py_generate.py
+169
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@@ -0,0 +1,169 @@
"""
Generate top level __init__.py.
Run this at the project root if you add a new .py file.
To skip the python file from included, put
```
pragma: skip_doc
```
in the docstring for the class. This pragma is used for both node reference as well as __init__.py.
```
"""
import os
import ast
import pathlib
from typing import TypeVar
T = TypeVar("T")
MODULES_DIR = "modules"
def extract_classes_from_file(file_path):
with open(file_path, "r", encoding="utf-8") as f:
tree = ast.parse(f.read(), filename=file_path)
classes = []
for node in ast.walk(tree):
if isinstance(node, ast.ClassDef):
docstring = ast.get_docstring(node)
if docstring and "pragma: skip_doc" in docstring:
continue
classes.append(node.name)
return classes
def format_display_name(class_name):
result = []
first_lower_encountered = False
i = 0
while i < len(class_name):
if i > 0 and class_name[i].isupper():
if first_lower_encountered or (i + 1 < len(class_name) and class_name[i + 1].islower()):
result.append(" ")
elif not first_lower_encountered and (i + 1 < len(class_name) and class_name[i + 1].isupper()):
if i + 2 < len(class_name) and class_name[i + 2].islower():
result.append(" ")
if class_name[i].islower():
first_lower_encountered = True
# Special case for JSON and CSV
if class_name[i:i+4] == "JSON":
if result and result[-1] != " ":
result.append(" ")
result.append("JSON")
if i + 4 < len(class_name) and class_name[i + 4].isupper():
result.append(" ")
i += 3 # Skip processed letters
elif class_name[i:i+3] == "CSV":
if result and result[-1] != " ":
result.append(" ")
result.append("CSV")
if i + 3 < len(class_name) and class_name[i + 3].isupper():
result.append(" ")
i += 2 # Skip processed letters
else:
result.append(class_name[i])
i += 1
# Ensure acronyms at the start are not incorrectly split (like "CD A" instead of "CDA")
final_result = "".join(result)
# TODO: Reduce hack below
replace_pairs = [
("CD A", "CDA"),
("H T M L", "HTML"),
("MP L", "MPL"),
(" N A", " NA"),
("Data Frame", "DataFrame"),
("MPL Bar", "MPL Bar Chart"),
("MPL Line", "MPL Line Plot"),
("MPL Scatter", "MPL Scatter Plot")
]
for p in replace_pairs:
final_result = final_result.replace(p[0], p[1])
return " ".join(final_result.split()) # Remove unintended extra spaces
def discover_modules():
module_entries = []
for py_file in pathlib.Path(MODULES_DIR).rglob("*.py"):
relative_path = py_file.relative_to(MODULES_DIR).with_suffix("")
module_import_path = ".modules." + str(relative_path).replace(os.sep, ".")
class_names = extract_classes_from_file(py_file)
for class_name in class_names:
display_name = format_display_name(class_name)
module_entries.append((module_import_path, class_name, display_name))
return module_entries
def get_class_mappings_doc():
return """
\"\"\"
NODE_CLASS_MAPPINGS (Dict[str, Type[T]]):
A dictionary mapping node names to their corresponding class implementations.
\"\"\"
"""
def get_display_name_mappings_doc():
return """
\"\"\"
NODE_DISPLAY_NAME_MAPPINGS (Dict[str, str]):
A dictionary mapping node names to user-friendly display names.
\"\"\"
"""
def get_license_doc():
return """
\"\"\"
Below two lines were taken from:
https://github.com/pythongosssss/ComfyUI-Custom-Scripts/blob/main/__init__.py
See credit/credit.md for the full license.
\"\"\"
"""
def generate_init_content(import_statements, node_class_mappings, node_display_name_mappings):
return f"""# This file is auto-generated. Do not edit manually.
from typing import Dict, Type, TypeVar
{os.linesep.join(import_statements)}
T = TypeVar("T")
{get_class_mappings_doc()}
NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {{
{os.linesep.join(node_class_mappings)}
}}
{get_display_name_mappings_doc()}
NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {{
{os.linesep.join(node_display_name_mappings)}
}}
{get_license_doc()}
WEB_DIRECTORY = "./web"
__all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS", "WEB_DIRECTORY"]
"""
def generate_init():
module_entries = discover_modules()
import_statements = sorted([f"from {entry[0]} import {entry[1]}" for entry in module_entries])
node_class_mappings = sorted([f' "{entry[1]}": {entry[1]},' for entry in module_entries])
node_display_name_mappings = sorted([f' "{entry[1]}": "{entry[2]}",' for entry in module_entries])
template = generate_init_content(import_statements, node_class_mappings, node_display_name_mappings)
with open("__init__.py", "w", encoding="utf-8") as f:
f.write(template)
if __name__ == "__main__":
generate_init()
docs/reference/node_reference.md
+1
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@@ -36,6 +36,7 @@
## Data cleansing
| Node | Description |
| --- | --- |
| [Pandas Drop Duplicates](pandas_drop_duplicates.md) | Drops duplicate rows from a Pandas DataFrame. |
| [Pandas Drop NA](pandas_dropna.md) | Drops missing values from a pandas DataFrame. |
| [Pandas Is NA](pandas_isna.md) | Checks a pandas DataFrame for missing values. |
| [Pandas Replace](pandas_replace.md) | Replaces part or all of a string in each DataFrame cell with a specified string using a wildcard for matching. If you want to remove some characters, then leave the replace_string field blank. |
docs/reference/pandas_drop_duplicates.md
+17
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@@ -0,0 +1,17 @@
# Pandas Drop Duplicates
Drops duplicate rows from a Pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Data cleansing
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
modules/pandas_wrapper/pandas_drop_duplicates.py
+39
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@@ -0,0 +1,39 @@
from typing import Any, Dict
import pandas as pd
class PandasDropDuplicates:
"""
Drops duplicate rows from a Pandas DataFrame.
category: Data cleansing
"""
@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", {})
}
}
RETURN_TYPES: tuple = ("DATAFRAME",)
FUNCTION: str = "f"
CATEGORY: str = "Data Analysis"
def f(self, dataframe: pd.DataFrame) -> tuple:
"""
Drops duplicate rows from a Pandas DataFrame.
Args:
dataframe (DataFrame): The DataFrame.
Returns:
tuple: A tuple containing the DataFrame.
"""
return (dataframe.drop_duplicates(),)
modules/pandas_wrapper/pandas_dropna.py
+1 -1
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@@ -37,4 +37,4 @@ class PandasDropNA:
Returns:
tuple: A tuple containing the DataFrame.
"""
return (dataframe.dropna().to_json(),)
return (dataframe.dropna(),)
pyproject.toml
+1 -1
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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 = "1.1.12"
version = "1.1.13"
license = {file = "LICENSE"}
[project.urls]