nodes/HowToSD-ComfyUI-Data-Analysis
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Added Pandas Load HTML, CDA Float Create, CDA Int Create, CDA String Create, CDA Text Create, CDA Show Float, CDA Show Int nodes.

Browse Source
This commit is contained in:
HowToSD
2025-02-19 12:59:11 -08:00
parent 345d9642da
commit 897f3e99f4
27 changed files with 562 additions and 10 deletions
Download Patch File Download Diff File Expand all files Collapse all files
__init__.py
+21
View File
@@ -1,5 +1,11 @@
from typing import Dict, Type, TypeVar
from .modules.cda.cda_float_create import CDAFloatCreate
from .modules.cda.cda_int_create import CDAIntCreate
from .modules.cda.cda_json_create import CDAJSONCreate
from .modules.cda.cda_show_float import CDAShowFloat
from .modules.cda.cda_show_int import CDAShowInt
from .modules.cda.cda_string_create import CDAStringCreate
from .modules.cda.cda_text_create import CDATextCreate
from .modules.matplotlib.mpl_bar import MPLBar
from .modules.matplotlib.mpl_line import MPLLine
from .modules.matplotlib.mpl_scatter import MPLScatter
@@ -33,6 +39,7 @@ from .modules.pandas_wrapper.pandas_join import PandasJoin
from .modules.pandas_wrapper.pandas_load_csv import PandasLoadCSV
from .modules.pandas_wrapper.pandas_load_csv_with_encoding import PandasLoadCSVWithEncoding
from .modules.pandas_wrapper.pandas_load_csv_with_index import PandasLoadCSVWithIndex
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
@@ -68,7 +75,13 @@ from .modules.pandas_wrapper.pandas_vertical_split import PandasVerticalSplit
T = TypeVar("T")
NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
"CDAFloatCreate": CDAFloatCreate,
"CDAIntCreate": CDAIntCreate,
"CDAJSONCreate": CDAJSONCreate,
"CDAShowFloat": CDAShowFloat,
"CDAShowInt": CDAShowInt,
"CDAStringCreate": CDAStringCreate,
"CDATextCreate": CDATextCreate,
"MPLBar": MPLBar,
"MPLLine": MPLLine,
"MPLScatter": MPLScatter,
@@ -102,6 +115,7 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
"PandasLoadCSV": PandasLoadCSV,
"PandasLoadCSVWithEncoding": PandasLoadCSVWithEncoding,
"PandasLoadCSVWithIndex": PandasLoadCSVWithIndex,
"PandasLoadHTML": PandasLoadHTML,
"PandasLoadJSON": PandasLoadJSON,
"PandasLocCellStr": PandasLocCellStr,
"PandasLocRowSeries": PandasLocRowSeries,
@@ -140,7 +154,13 @@ NODE_CLASS_MAPPINGS (Dict[str, Type[T]]):
"""
NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
"CDAFloatCreate": "CDA Float Create",
"CDAIntCreate": "CDA Int Create",
"CDAJSONCreate": "CDA JSON Create",
"CDAShowFloat": "CDA Show Float",
"CDAShowInt": "CDA Show Int",
"CDAStringCreate": "CDA String Create",
"CDATextCreate": "CDA Text Create",
"MPLBar": "MPL Bar Chart",
"MPLLine": "MPL Line Plot",
"MPLScatter": "MPL Scatter Plot",
@@ -174,6 +194,7 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
"PandasLoadCSV": "Pandas Load CSV",
"PandasLoadCSVWithEncoding": "Pandas Load CSV With Encoding",
"PandasLoadCSVWithIndex": "Pandas Load CSV With Index",
"PandasLoadHTML": "Pandas Load HTML",
"PandasLoadJSON": "Pandas Load JSON",
"PandasLocCellStr": "Pandas Loc Cell Str",
"PandasLocRowSeries": "Pandas Loc Row Series",
docs/reference/cda_float_create.md
+17
View File
@@ -0,0 +1,17 @@
# CDA Float Create
Creates a Python float using a value entered in the text field.
## Input
| Name | Data type |
|---|---|
| data | String |
## Output
| Data type |
|---|
| Float |
<HR>
Category: IO
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
docs/reference/cda_int_create.md
+17
View File
@@ -0,0 +1,17 @@
# CDA Int Create
Creates a Python int using a value entered in the text field.
## Input
| Name | Data type |
|---|---|
| data | String |
## Output
| Data type |
|---|
| Int |
<HR>
Category: IO
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
docs/reference/cda_show_float.md
+17
View File
@@ -0,0 +1,17 @@
# C D A Show Float
Displays a floating-point number as text.
## Input
| Name | Data type |
|---|---|
| float_scalar | Float |
## Output
| Data type |
|---|
| String |
<HR>
Category: Display data
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
docs/reference/cda_show_int.md
+17
View File
@@ -0,0 +1,17 @@
# C D A Show Int
Displays a Pandas Int as text.
## Input
| Name | Data type |
|---|---|
| int_scalar | Int |
## Output
| Data type |
|---|
| String |
<HR>
Category: Display data
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
docs/reference/cda_string_create.md
+17
View File
@@ -0,0 +1,17 @@
# CDA String Create
Creates a Python String using a value entered in a single-line text field.
## Input
| Name | Data type |
|---|---|
| data | String |
## Output
| Data type |
|---|
| String |
<HR>
Category: IO
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
docs/reference/cda_text_create.md
+17
View File
@@ -0,0 +1,17 @@
# CDA Text Create
Creates a Python String using a value entered in a multi-line text field.
## Input
| Name | Data type |
|---|---|
| data | String |
## Output
| Data type |
|---|
| String |
<HR>
Category: IO
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
docs/reference/node_reference.md
+7
View File
@@ -45,6 +45,8 @@
## Display data
| Node | Description |
| --- | --- |
| [C D A Show Float](cda_show_float.md) | Displays a floating-point number as text. |
| [C D A Show Int](cda_show_int.md) | Displays a Pandas Int as text. |
| [Pandas Index To String](pandas_index_to_string.md) | Converts a pandas Index to a string representation. |
| [Pandas Series To String](pandas_series_to_string.md) | Converts a pandas Series to a string representation. |
| [Pandas Show Data Frame](pandas_show_dataframe.md) | Displays a Pandas DataFrame as text. |
@@ -55,12 +57,17 @@
## IO
| Node | Description |
| --- | --- |
| [CDA Float Create](cda_float_create.md) | Creates a Python float using a value entered in the text field. |
| [CDA Int Create](cda_int_create.md) | Creates a Python int using a value entered in the text field. |
| [CDA JSON Create](cda_json_create.md) | Creates a serialized JSON object using values entered in the text field. |
| [CDA String Create](cda_string_create.md) | Creates a Python String using a value entered in a single-line text field. |
| [CDA Text Create](cda_text_create.md) | Creates a Python String using a value entered in a multi-line text field. |
| [Pandas Create](pandas_create.md) | Creates a pandas DataFrame using values entered in the text field. |
| [Pandas Create With Index](pandas_create_with_index.md) | Creates a pandas DataFrame using values entered in the text field. Input data is assumed to have an index. |
| [Pandas Load CSV](pandas_load_csv.md) | Loads CSV files into a pandas DataFrame. |
| [Pandas Load CSV With Encoding](pandas_load_csv_with_encoding.md) | Loads CSV files into a pandas DataFrame. |
| [Pandas Load CSV With Index](pandas_load_csv_with_index.md) | Loads CSV files into a pandas DataFrame. |
| [Pandas Load HTML](pandas_load_html.md) | Scans HTML files for tables and returns the number of DataFrames, with each table represented as a separate DataFrame and the list of those DataFrames. |
| [Pandas Load JSON](pandas_load_json.md) | Loads JSON files into a pandas DataFrame. |
| [Pandas Save CSV](pandas_save_csv.md) | Saves a PandasDataFrame to a CSV file. |
| [Pandas Save JSON](pandas_save_json.md) | Saves a PandasDataFrame to a JSON file. |
docs/reference/pandas_load_html.md
+27
View File
@@ -0,0 +1,27 @@
# Pandas Load HTML
Scans HTML files for tables and returns the number of DataFrames, with each table represented as a separate DataFrame and the list of those DataFrames.
## Input
| Name | Data type |
|---|---|
| file_path | String |
## Output
| Data type |
|---|
| Int |
| DataFrame |
| DataFrame |
| DataFrame |
| DataFrame |
| DataFrame |
| DataFrame |
| DataFrame |
| DataFrame |
| DataFrame |
| DataFrame |
<HR>
Category: IO
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
examples/datasets/0.html
+8
View File
@@ -0,0 +1,8 @@
<html>
<head>
</head>
<body>
Empty HTML
</body>
</head>
</html>
examples/datasets/1.html
+12
View File
@@ -0,0 +1,12 @@
<html>
<head>
</head>
<body>
<table>
<tr><td>A</td><td>B</td></tr>
<tr><td>1</td><td>10</td></tr>
<tr><td>2</td><td>20</td></tr>
</table>
</body>
</head>
</html>
examples/datasets/2.html
+20
View File
@@ -0,0 +1,20 @@
<html>
<head>
</head>
<body>
<h2>First</h2>
<table>
<tr><td>A</td><td>B</td></tr>
<tr><td>1</td><td>10</td></tr>
<tr><td>2</td><td>20</td></tr>
</table>
<h2>Second</h2>
<table>
<tr><td>X</td><td>Y</td></tr>
<tr><td>9.87</td><td>98.76</td></tr>
<tr><td>8.76</td><td>87.65</td></tr>
</table>
</body>
</head>
</html>
examples/workflows/load_html.json
+1
View File
File diff suppressed because one or more lines are too long
examples/workflows/variable_create.json
+1
View File
@@ -0,0 +1 @@
{"last_node_id":9,"last_link_id":4,"nodes":[{"id":6,"type":"CDAShowFloat","pos":[85.68311309814453,3906.311279296875],"size":[315,76],"flags":{},"order":5,"mode":0,"inputs":[{"name":"float_scalar","type":"FLOAT","link":2,"widget":{"name":"float_scalar"}}],"outputs":[{"name":"STRING","type":"STRING","links":null,"shape":6}],"properties":{"Node name for S&R":"CDAShowFloat"},"widgets_values":[0,"123.45"]},{"id":7,"type":"PandasShowText","pos":[87.57423400878906,4041.531494140625],"size":[315,76],"flags":{},"order":6,"mode":0,"inputs":[{"name":"text","type":"STRING","link":3,"widget":{"name":"text"}}],"outputs":[{"name":"STRING","type":"STRING","links":null,"shape":6}],"properties":{"Node name for S&R":"PandasShowText"},"widgets_values":["","apple"]},{"id":5,"type":"CDAShowInt","pos":[83.79193878173828,3764.472900390625],"size":[315,76],"flags":{},"order":4,"mode":0,"inputs":[{"name":"int_scalar","type":"INT","link":1,"widget":{"name":"int_scalar"}}],"outputs":[{"name":"STRING","type":"STRING","links":null,"shape":6}],"properties":{"Node name for S&R":"CDAShowInt"},"widgets_values":[0,"123"]},{"id":2,"type":"CDAFloatCreate","pos":[-392.78460693359375,3904.42041015625],"size":[315,58],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[{"name":"FLOAT","type":"FLOAT","links":[2],"slot_index":0}],"properties":{"Node name for S&R":"CDAFloatCreate"},"widgets_values":["123.45"]},{"id":3,"type":"CDAStringCreate","pos":[-393.7301025390625,4041.530517578125],"size":[315,58],"flags":{},"order":2,"mode":0,"inputs":[],"outputs":[{"name":"STRING","type":"STRING","links":[3],"slot_index":0}],"properties":{"Node name for S&R":"CDAStringCreate"},"widgets_values":["apple"]},{"id":1,"type":"CDAIntCreate","pos":[-393.7300720214844,3766.364501953125],"size":[315,58],"flags":{},"order":0,"mode":0,"inputs":[],"outputs":[{"name":"INT","type":"INT","links":[1],"slot_index":0}],"properties":{"Node name for S&R":"CDAIntCreate"},"widgets_values":["123"]},{"id":4,"type":"CDATextCreate","pos":[-393.73004150390625,4182.42138671875],"size":[316.78826904296875,126.24412536621094],"flags":{},"order":3,"mode":0,"inputs":[],"outputs":[{"name":"STRING","type":"STRING","links":[4],"slot_index":0}],"properties":{"Node name for S&R":"CDATextCreate"},"widgets_values":["banana\ncoconut"]},{"id":9,"type":"PandasShowText","pos":[87.57412719726562,4180.52783203125],"size":[315,76],"flags":{},"order":7,"mode":0,"inputs":[{"name":"text","type":"STRING","link":4,"widget":{"name":"text"}}],"outputs":[{"name":"STRING","type":"STRING","links":null,"shape":6}],"properties":{"Node name for S&R":"PandasShowText"},"widgets_values":["","banana\ncoconut"]}],"links":[[1,1,0,5,0,"INT"],[2,2,0,6,0,"FLOAT"],[3,3,0,7,0,"STRING"],[4,4,0,9,0,"STRING"]],"groups":[],"config":{},"extra":{"ds":{"scale":0.8812857471534622,"offset":[790.8771468343749,-3534.127789960823]},"node_versions":{"data-analysis":"c37db048eb1c8dbe3e84b9056337b7aa1cc6a026"},"ue_links":[]},"version":0.4}
modules/cda/cda_float_create.py
+40
View File
@@ -0,0 +1,40 @@
from typing import Any, Dict
class CDAFloatCreate:
"""
CDA Float Create:
Creates a Python float using a value entered in the text field.
category: IO
"""
@classmethod
def INPUT_TYPES(cls) -> Dict[str, Any]:
"""
Defines the input types for the `create` function.
Returns:
Dict[str, Any]: A dictionary specifying required input types.
"""
return {
"required": {
"data": ("STRING", {"multiline": False}),
}
}
RETURN_TYPES: tuple = ("FLOAT",)
FUNCTION: str = "create"
CATEGORY: str = "Data Analysis"
def create(self, data: str) -> tuple:
"""
creating a Python float for the text entered in the text field.
Args:
data (str): String value in the text field.
Returns:
tuple: A tuple containing the float converted from the text.
"""
return (float(data),)
modules/cda/cda_int_create.py
+41
View File
@@ -0,0 +1,41 @@
from typing import Any, Dict
class CDAIntCreate:
"""
CDA Int Create:
Creates a Python int using a value entered in the text field.
category: IO
"""
@classmethod
def INPUT_TYPES(cls) -> Dict[str, Any]:
"""
Defines the input types for the `create` function.
Returns:
Dict[str, Any]: A dictionary specifying required input types.
"""
return {
"required": {
"data": ("STRING", {"multiline": False}),
}
}
RETURN_TYPES: tuple = ("INT",)
FUNCTION: str = "create"
CATEGORY: str = "Data Analysis"
def create(self, data: str) -> tuple:
"""
creating a Python int for the text entered in the text field.
Args:
data (str): String value in the text field.
Returns:
tuple: A tuple containing the int converted from the text.
"""
return (int(data),)
modules/cda/cda_show_float.py
+62
View File
@@ -0,0 +1,62 @@
"""
This code is based on
https://github.com/pythongosssss/ComfyUI-Custom-Scripts/blob/main/py/show_text.py
See credit/credit.md for the full license.
"""
import sys
class CDAShowFloat:
"""
Displays a floating-point number as text.
category: Display data
"""
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"float_scalar": ("FLOAT", {"default": 0.0, "min": sys.float_info.min, "max": sys.float_info.max})
},
"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, float_scalar, unique_id=None, extra_pnginfo=None):
text = 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:
float_val = float_scalar[0]
text = [str(float_val)] # wrap in list
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 # [text]
else:
print("unique_id or extra_pnginfo is None.")
# "ui" value is the one that is shown on the node UI.
# Note that "ui" return value needs to a list of strings.
return {"ui": {"text": text},
"result": (text,)}
modules/cda/cda_show_int.py
+60
View File
@@ -0,0 +1,60 @@
"""
This code is based on
https://github.com/pythongosssss/ComfyUI-Custom-Scripts/blob/main/py/show_text.py
See credit/credit.md for the full license.
"""
class CDAShowInt:
"""
Displays a Pandas Int as text.
category: Display data
"""
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"int_scalar": ("INT", {"default": 0, "min": -1, "max": 2**31})
},
"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, int_scalar, unique_id=None, extra_pnginfo=None):
text = 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:
int_val = int_scalar[0]
text = [str(int_val)] # wrap in list
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 # [text]
else:
print("unique_id or extra_pnginfo is None.")
# "ui" value is the one that is shown on the node UI.
# Note that "ui" return value needs to a list of strings.
return {"ui": {"text": text},
"result": (text,)}
modules/cda/cda_string_create.py
+41
View File
@@ -0,0 +1,41 @@
from typing import Any, Dict
class CDAStringCreate:
"""
CDA String Create:
Creates a Python String using a value entered in a single-line text field.
category: IO
"""
@classmethod
def INPUT_TYPES(cls) -> Dict[str, Any]:
"""
Defines the input types for the `create` function.
Returns:
Dict[str, Any]: A dictionary specifying required input types.
"""
return {
"required": {
"data": ("STRING", {"multiline": False}),
}
}
RETURN_TYPES: tuple = ("STRING",)
FUNCTION: str = "create"
CATEGORY: str = "Data Analysis"
def create(self, data: str) -> tuple:
"""
creating a Python String for the text entered in the text field.
Args:
data (str): String value in the text field.
Returns:
tuple: A tuple containing the string converted from the text.
"""
return (data,)
modules/cda/cda_text_create.py
+41
View File
@@ -0,0 +1,41 @@
from typing import Any, Dict
class CDATextCreate:
"""
CDA Text Create:
Creates a Python String using a value entered in a multi-line text field.
category: IO
"""
@classmethod
def INPUT_TYPES(cls) -> Dict[str, Any]:
"""
Defines the input types for the `create` function.
Returns:
Dict[str, Any]: A dictionary specifying required input types.
"""
return {
"required": {
"data": ("STRING", {"multiline": True}),
}
}
RETURN_TYPES: tuple = ("STRING",)
FUNCTION: str = "create"
CATEGORY: str = "Data Analysis"
def create(self, data: str) -> tuple:
"""
creating a Python String for the text entered in the text field.
Args:
data (str): String value in the text field.
Returns:
tuple: A tuple containing the string converted from the text.
"""
return (data,)
modules/pandas_wrapper/pandas_load_csv.py
+2 -2
View File
@@ -31,13 +31,13 @@ class PandasLoadCSV:
def load_csv(self, file_path: str) -> tuple:
"""
Loads a CSV file into a pandas DataFrame and converts it to a JSON string.
Loads a CSV file into a pandas DataFrame.
Args:
file_path (str): The path to the CSV file.
Returns:
tuple: A tuple containing a JSON string representation of the DataFrame.
tuple: A tuple containing a DataFrame.
"""
# Read CSV file into DataFrame
df = pd.read_csv(file_path)
modules/pandas_wrapper/pandas_load_csv_with_encoding.py
+2 -2
View File
@@ -32,7 +32,7 @@ class PandasLoadCSVWithEncoding:
def load_csv(self, file_path: str, encoding: str) -> tuple:
"""
Loads a CSV file into a pandas DataFrame and converts it to a JSON string. Allows specifying the file encoding to support formats other than UTF-8.
Loads a CSV file into a pandas DataFrame. Allows specifying the file encoding to support formats other than UTF-8.
Refer to the below documents for the list of encodings:
https://docs.python.org/3/library/codecs.html#standard-encodings
@@ -42,7 +42,7 @@ class PandasLoadCSVWithEncoding:
encoding (str): Encoding of the file.
Returns:
tuple: A tuple containing a JSON string representation of the DataFrame.
tuple: A tuple containing a DataFrame.
"""
# Read CSV file into DataFrame
df = pd.read_csv(file_path, encoding=encoding)
modules/pandas_wrapper/pandas_load_csv_with_index.py
+2 -2
View File
@@ -33,14 +33,14 @@ class PandasLoadCSVWithIndex:
def load_csv(self, file_path: str, index_col: int=0) -> tuple:
"""
Loads a CSV file into a pandas DataFrame and converts it to a JSON string.
Loads a CSV file into a pandas DataFrame.
Input data is assume to have an index.
Args:
file_path (str): The path to the CSV file.
Returns:
tuple: A tuple containing a JSON string representation of the DataFrame.
tuple: A tuple containing a DataFrame.
"""
# Read CSV file into DataFrame
df = pd.read_csv(file_path, index_col=index_col)
modules/pandas_wrapper/pandas_load_html.py
+68
View File
@@ -0,0 +1,68 @@
from typing import Any, Dict
import pandas as pd
class PandasLoadHTML:
"""
Pandas Load HTML:
Scans HTML files for tables and returns the number of DataFrames, with each table represented as a separate DataFrame and the list of those DataFrames.
category: IO
"""
@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": {
"file_path": ("STRING", {"multiline": False}),
}
}
# TODO: Reference doc generator script cannot parse programatically defined
# list yet, so we need to list return types for now.
RETURN_TYPES: tuple = ("INT",
"DATAFRAME", "DATAFRAME", "DATAFRAME","DATAFRAME",
"DATAFRAME", "DATAFRAME", "DATAFRAME", "DATAFRAME",
"DATAFRAME", "DATAFRAME")
RETURN_NAMES: tuple = ("Number of DataFrames",
"DataFrame1", "DataFrame2", "DataFrame3", "DataFrame4",
"DataFrame5", "DataFrame6", "DataFrame7", "DataFrame8",
"DataFrame9", "DataFrame10")
assert(len(RETURN_NAMES) == len(RETURN_TYPES))
FUNCTION: str = "f"
CATEGORY: str = "Data Analysis"
def f(self, file_path: str) -> tuple:
"""
Loads an HTML file into a pandas DataFrame.
Args:
file_path (str): The path to the HTML file. The path can be a URL.
Returns:
tuple: A tuple containing a DataFrame.
"""
try:
dfs = pd.read_html(file_path, flavor="lxml")
except:
dfs = []
num_dfs = 0
if dfs is None:
num_dfs = 0
dfs = []
else:
num_dfs = len(dfs)
df_slot_count = len(PandasLoadHTML.RETURN_TYPES) - 1
filler_count = df_slot_count - num_dfs
empty_dfs = [pd.DataFrame({})] * filler_count # If filler = 0, this will still return []
dfs_out = dfs + empty_dfs
return tuple([num_dfs] + dfs_out)
modules/pandas_wrapper/pandas_load_json.py
+2 -2
View File
@@ -31,13 +31,13 @@ class PandasLoadJSON:
def load_json(self, file_path: str) -> tuple:
"""
Loads a JSON file into a pandas DataFrame and converts it to a JSON string.
Loads a JSON file into a pandas DataFrame.
Args:
file_path (str): The path to the JSON file.
Returns:
tuple: A tuple containing a JSON string representation of the DataFrame.
tuple: A tuple containing a DataFrame.
"""
# Read JSON file into DataFrame
df = pd.read_json(file_path)
pyproject.toml
+1 -1
View File
@@ -1,7 +1,7 @@
[project]
name = "data-analysis"
description = "Data analysis custom modules for ComfyUI - Use Pandas & Matplotlib within ComfyUI"
version = "1.1.6"
version = "1.1.7"
license = {file = "LICENSE"}
[project.urls]
web/js/ShowText.js
+1 -1
View File
@@ -12,7 +12,7 @@ import { ComfyWidgets } from "../../../scripts/widgets.js";
app.registerExtension({
name: "HowToSD.ShowText",
async beforeRegisterNodeDef(nodeType, nodeData, app) {
if (nodeData.name === "PandasShowText") { // This needs to match NODE_CLASS_MAPPINGS in Python
if (["PandasShowText", "CDAShowInt", "CDAShowFloat"].includes(nodeData.name)) { // This needs to match NODE_CLASS_MAPPINGS in Python
function populate(text) {
if (this.widgets) {
for (let i = 1; i < this.widgets.length; i++) {