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Added CDA JSON Create and Pandas Iloc Rows DataFrame nodes.

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HowToSD
2025-02-16 12:36:43 -08:00
parent a76ec5241b
commit 9976ae4aa4
8 changed files with 146 additions and 10 deletions
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__init__.py
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@@ -1,4 +1,5 @@
from typing import Dict, Type, TypeVar
from .modules.cda.cda_json_create import CDAJSONCreate
from .modules.matplotlib.mpl_bar import MPLBar
from .modules.matplotlib.mpl_line import MPLLine
from .modules.matplotlib.mpl_scatter import MPLScatter
@@ -7,6 +8,7 @@ from .modules.pandas_wrapper.pandas_create import PandasCreate
from .modules.pandas_wrapper.pandas_create_with_index import PandasCreateWithIndex
from .modules.pandas_wrapper.pandas_head import PandasHead
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
from .modules.pandas_wrapper.pandas_join import PandasJoin
from .modules.pandas_wrapper.pandas_load_csv import PandasLoadCSV
@@ -27,6 +29,7 @@ from .modules.pandas_wrapper.pandas_to_string import PandasToString
T = TypeVar("T")
NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
"CDAJSONCreate": CDAJSONCreate,
"MPLBar": MPLBar,
"MPLLine": MPLLine,
"MPLScatter": MPLScatter,
@@ -35,6 +38,7 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
"PandasCreateWithIndex": PandasCreateWithIndex,
"PandasHead": PandasHead,
"PandasIlocRowSeries": PandasIlocRowSeries,
"PandasIlocRowsDataFrame": PandasIlocRowsDataFrame,
"PandasIndex": PandasIndex,
"PandasJoin": PandasJoin,
"PandasLoadCSV": PandasLoadCSV,
@@ -58,6 +62,7 @@ NODE_CLASS_MAPPINGS (Dict[str, Type[T]]):
"""
NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
"CDAJSONCreate": "CDA JSON Create",
"MPLBar": "MPL Bar Chart",
"MPLLine": "MPL Line Plot",
"MPLScatter": "MPL Scatter Plot",
@@ -66,6 +71,7 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
"PandasCreateWithIndex": "Pandas Create With Index",
"PandasHead": "Pandas Head",
"PandasIlocRowSeries": "Pandas Iloc Row Series",
"PandasIlocRowsDataFrame": "Pandas Iloc Rows DataFrame",
"PandasIndex": "Pandas Index",
"PandasJoin": "Pandas Join",
"PandasLoadCSV": "Pandas Load CSV",
docs/images/iloc_rows_dataframe.png
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docs/ug.md
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@@ -11,6 +11,8 @@ To connect the DataFrame JSON string output from one Pandas node to another, mov
### How to add a node
You can right-click, select **Add Node**, go to **Data Analysis**, and look for the following nodes:
### List of nodes
**Data loading, creation, saving**
| Node Name | Functionality |
|-------------------------|-------------------------------------|
| **Pandas Load CSV** | Load a CSV file |
@@ -19,21 +21,43 @@ You can right-click, select **Add Node**, go to **Data Analysis**, and look for
| **Pandas Save CSV** | Save a DataFrame to a CSV file |
| **Pandas Create** | Create a DataFrame from CSV text field |
| **Pandas Create With Index** | Create a DataFrame from CSV text field containing index |
| **CDA JSON Create** | Create JSON from a string entered in a text field |
**Selecting subset of data**
| Node Name | Functionality |
|-------------------------|-------------------------------------|
| **Pandas Columns** | Extract column labels |
| **Pandas Index** | Extract row labels (index) |
| **Pandas Select Columns** | Select specific columns from a DataFrame |
| **Pandas Select Rows** | Filter rows based on conditions |
| **Pandas Iloc Row Series** | Select a row by row integer position |
| **Pandas Iloc Rows DataFrame** | Select rows by the list of row integer positions |
| **Pandas Loc Row Series** | Select a row by row label (index) |
| **Pandas Loc Cell Str** | Select a cell by row label (index) and column label (index) |
| **Pandas Join** | Join two DataFrames |
| **Pandas Head** | Extract the first few rows |
**Manipulating data**
| Node Name | Functionality |
|-------------------------|-------------------------------------|
| **Pandas Join** | Join two DataFrames |
| **Pandas Sort** | Sort DataFrame by a column |
**Displaying data**
| Node Name | Functionality |
|-------------------------|-------------------------------------|
| **Pandas Show DataFrame** | Display DataFrame contents |
| **Pandas Show Text** | Display Text |
| **Pandas Summary** | Extract DataFrame statistics |
| **Pandas Sort** | Sort DataFrame by a column |
**Converting to displayable string**
| Node Name | Functionality |
|-------------------------|-------------------------------------|
| **Pandas Series To String** | Convert Series to a displayable string |
| **Pandas To String** | Convert DataFrame to a displayable string |
**Plot, chart**
| Node Name | Functionality |
|-------------------------|-------------------------------------|
| **MPL Bar Chart** | Generate a bar chart |
| **MPL Line Plot** | Generate a line plot |
| **MPL Scatter Plot** | Generate a scatter plot |
@@ -52,12 +76,14 @@ CSV file path is relative to the ComfyUI installation directory unless you speci
## Saving data
Use **Pandas Save CSV** node to save the DataFrame to a CSV file.
## Creating DataFrame on the UI
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.
## Creating data on the UI
To construct a DataFrame on the UI, 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.
If the data contains an index column, use **Pandas Create with Index** and specify the index column.
![Pandas Columns and Pandas Index](images/columns_index.png)
Use **CDA JSON Create** to create JSON from a string entered in a text field. For example, if you want to create a list for a node that requires the list of integers for input, this node is ideal.
## Extracting column and row labels
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:
@@ -70,7 +96,13 @@ Use **Pandas Select Rows** to select rows by a filter condition.
![Pandas select subset](images/subset.jpg)
You can use **Pandas Loc Row Series** to select a row by row label (index), or you can use **Pandas Iloc Row Series** to select a row by row integer position. Both nodes returns a JSON-serialized Series object.
You can use **Pandas Loc Row Series** to select a row by row label (index).
You can use **Pandas Iloc Row Series** to select a row by row integer position.
These nodes returns a JSON-serialized Series object.
You can use **Pandas Iloc Rows DataFrame** to select rows by the list of row integer positions. This node returns a JSON-serialized DataFrame object.
You need to pass the list of integers to this node. This can be done by using the **CDA JSON Create** node.
![Pandas Iloc Rows DataFrame](images/iloc_rows_dataframe.png)
For **Pandas Loc Row Series**, data type of the labels needs to be specified as shown below:
![Pandas Loc Row Series](images/loc_row_series.png)
modules/cda/cda_json_create.py
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from typing import Any, Dict
import json
class CDAJSONCreate:
"""
CDAJSONCreate:
A class for creating a serialized JSON object using values entered in the text field.
"""
@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 serialized JSON object using values entered in the text field.
Args:
data (str): String value in the text field.
Returns:
tuple: A tuple containing a JSON string representation of the DataFrame.
"""
# Convert to JSON
json_obj = json.loads(data)
# Serialize to a string
result_jsons = json.dumps(json_obj)
return (result_jsons,)
modules/pandas_wrapper/pandas_create.py
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@@ -5,7 +5,7 @@ import pandas as pd
class PandasCreate:
"""
PandasLoadCSV:
PandasCreate:
A class for creating a pandas DataFrame using values entered in the text field.
"""
@@ -32,7 +32,7 @@ class PandasCreate:
Create a pandas DataFrame using values entered in the text field and converts it to a JSON string.
Args:
file_path (str): The path to the CSV file.
data (str): String value in the text field.
Returns:
tuple: A tuple containing a JSON string representation of the DataFrame.
modules/pandas_wrapper/pandas_create_with_index.py
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@@ -5,7 +5,7 @@ import pandas as pd
class PandasCreateWithIndex:
"""
PandasLoadCSV:
PandasCreateWithIndex:
A class for creating a pandas DataFrame using values entered in the text field.
Input data is assume to have an index.
"""
@@ -35,7 +35,8 @@ class PandasCreateWithIndex:
Input data is assume to have an index.
Args:
file_path (str): The path to the CSV file.
data (str): String value in the text field.
index_col (int): Position of the index column.
Returns:
tuple: A tuple containing a JSON string representation of the DataFrame.
modules/pandas_wrapper/pandas_iloc_rows_dataframe.py
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@@ -0,0 +1,52 @@
from typing import Any, Dict
from io import StringIO
import json
import pandas as pd
from .utils import series_to_jsons
class PandasIlocRowsDataFrame:
"""
PandasIlocRowsDataFrame:
A class for selecting rows from a pandas DataFrame and returning it as a DataFrame.
Rows are specified by the list of integer positions.
"""
@classmethod
def INPUT_TYPES(cls) -> Dict[str, Any]:
"""
Defines the input types for the `select_rows` function.
Returns:
Dict[str, Any]: A dictionary specifying required input types.
"""
return {
"required": {
"dataframe_json": ("STRING", {"multiline": True}),
"row_int_pos_list_json": ("STRING", {"multiline": False})
}
}
RETURN_TYPES: tuple = ("STRING",)
FUNCTION: str = "select_rows"
CATEGORY: str = "Data Analysis"
def select_rows(self, dataframe_json: str,
row_int_pos_list_json: str) -> tuple:
"""
Select rows from a pandas DataFrame and returning it as a DataFrame.
Rows are specified by the list of integer positions and returned as
the JSON serialized DataFrame object.
Args:
dataframe_json (str): A JSON string representation of the DataFrame.
row_int_pos_list_json (str): A list containing row integer positions.
Returns:
tuple: A tuple containing the value of the row in string. The string is
a JSON string containing the serialized Pandas Series object.
"""
# Deserialize JSON string to DataFrame
df = pd.read_json(StringIO(dataframe_json))
row_int_pos_list = json.loads(row_int_pos_list_json)
df2 = df.iloc[row_int_pos_list]
return (df2.to_json(),)
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 = "1.0.13"
version = "1.0.14"
license = {file = "LICENSE"}
[project.urls]