Added Pandas Exp, Log, Sin, Cos, Tan nodes and updated Pandas DataFrame Summary node to output a DataFrame instead of a string. Added node reference pages.

This commit is contained in:
HowToSD
2025-02-18 16:45:39 -08:00
parent e63b1e54ce
commit 27533783ad
134 changed files with 1802 additions and 118 deletions
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@@ -73,7 +73,7 @@ Note: GPU is not required to run this custom module.
This custom node module requires pandas and matplotlib, which are not included in the default ComfyUI installation. If you install this module using ComfyUI Manager, these packages should be installed automatically. However, if installation fails, refer to the pandas and matplotlib documentation for manual installation.
## How to Use
Refer to [User's Guide](docs/ug.md)
Refer to [User's Guide](docs/ug.md) or check out [Node Reference](reference/node_reference.md)
For a practical example, see the tutorial on baseball data: [How to Find Out Who Had the Most Hits](docs/baseball_example1.md).
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@@ -15,6 +15,11 @@ from .modules.pandas_wrapper.pandas_create_with_index import PandasCreateWithInd
from .modules.pandas_wrapper.pandas_div import PandasDiv
from .modules.pandas_wrapper.pandas_div_series import PandasDivSeries
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
@@ -78,6 +83,11 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
"PandasDiv": PandasDiv,
"PandasDivSeries": PandasDivSeries,
"PandasDropNA": PandasDropNA,
"PandasExp": PandasExp,
"PandasLog": PandasLog,
"PandasSin": PandasSin,
"PandasCos": PandasCos,
"PandasTan": PandasTan,
"PandasGroupBy": PandasGroupBy,
"PandasHead": PandasHead,
"PandasHorizontalConcat": PandasHorizontalConcat,
@@ -143,6 +153,11 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
"PandasDiv": "Pandas Div",
"PandasDivSeries": "Pandas Div Series",
"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",
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"""
Generate node reference documents.
Run this at the project root if you update a docstring of the node source file.
To skip the python file from included in the reference, put
```
pragma: skip_doc
```
in the docstring for the class.
To use a custom node name, put the node name on the first line of the docstring for the class with ":".
e.g.
```
CDA JSON Create:
Creates a serialized JSON object using values entered in the text field.
```
"""
import os
import re
import ast
from collections import defaultdict
from typing import Dict, List
# Mapping for data type conversion
data_type_mapping = {
"DATAFRAME": "DataFrame",
"PDSERIES": "Series",
"PDINDEX": "Index"
}
def convert_data_type(data_type: str) -> str:
"""Convert type to the required format."""
if data_type in data_type_mapping:
return data_type_mapping[data_type]
return data_type.lower().capitalize()
def extract_class_info(class_def: ast.ClassDef) -> Dict[str, str]:
"""Extract class name, title, category, and docstring."""
class_name = class_def.name
docstring = ast.get_docstring(class_def) or ""
if "pragma: skip_doc" in docstring:
return None
lines = docstring.split("\n")
title = None
category = "Miscellaneous"
if len(lines) > 1 and lines[0].strip().endswith(":") and lines[0].strip()[0].isupper():
title = lines.pop(0).strip().rstrip(":")
if not title:
title = "# " + " ".join(re.findall(r'[A-Z][a-z]*', class_name))
else:
title = f"# {title}"
description_lines = []
for line in lines:
if line.strip().startswith("category:"):
category = line.split(":", 1)[-1].strip()
else:
description_lines.append(line)
description = "\n".join(description_lines).strip()
return {"title": title, "description": description, "class_name": class_name, "first_sentence": description_lines[0] if description_lines else "", "category": category}
def extract_input_types(class_def: ast.ClassDef) -> str:
"""Extract INPUT_TYPES definition."""
input_table = ""
for node in class_def.body:
if isinstance(node, ast.FunctionDef) and node.name == "INPUT_TYPES":
for stmt in ast.walk(node):
if isinstance(stmt, ast.Dict):
for key, value in zip(stmt.keys, stmt.values):
if isinstance(key, ast.Constant) and isinstance(value, ast.Tuple) and len(value.elts) > 0:
param_name = key.value
data_type = value.elts[0].value if isinstance(value.elts[0], ast.Constant) else ""
input_table += f"| {param_name} | {convert_data_type(data_type)} |\n"
return "## Input\n| Name | Data type |\n|---|---|\n" + input_table if input_table else ""
def extract_return_types(class_def: ast.ClassDef) -> str:
"""Extract RETURN_TYPES value."""
for node in class_def.body:
# Look for assignment or annotated assignment (type hint) statement.
# Node target is the RHS.
if (
isinstance(node, ast.Assign) and
any(target.id == "RETURN_TYPES" for target in node.targets if isinstance(target, ast.Name))
) or (
isinstance(node, ast.AnnAssign) and
isinstance(node.target, ast.Name) and
node.target.id == "RETURN_TYPES"
):
if isinstance(node.value, ast.Tuple):
return_types = [convert_data_type(elt.value) for elt in node.value.elts if isinstance(elt, ast.Constant)]
return "## Output\n| Data type |\n|---|\n" + "".join(f"| {rtype} |\n" for rtype in return_types)
return ""
def process_python_file(file_path: str, output_dir: str, node_list: Dict[str, List[str]]):
"""Process a single Python file and generate corresponding Markdown."""
with open(file_path, "r", encoding="utf-8") as f:
tree = ast.parse(f.read(), filename=file_path)
for node in tree.body:
if isinstance(node, ast.ClassDef):
class_info = extract_class_info(node)
if not class_info:
return
input_section = extract_input_types(node)
output_section = extract_return_types(node)
category = class_info["category"]
file_name = os.path.splitext(os.path.basename(file_path))[0] + ".md"
output_path = os.path.join(output_dir, file_name)
with open(output_path, "w", encoding="utf-8") as md_file:
md_file.write(f"{class_info['title']}\n{class_info['description']}\n\n")
if input_section:
md_file.write(input_section + "\n")
if output_section:
md_file.write(output_section + "\n")
md_file.write("<HR>\n")
md_file.write(f"Category: {category}\n\n")
md_file.write(f"ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.\n")
node_list[category].append((class_info['title'][2:], file_name, class_info['first_sentence']))
def generate_node_list(output_dir: str, node_list: Dict[str, List[str]]):
"""Generate node_reference.md file."""
node_list_path = os.path.join(output_dir, "node_reference.md")
with open(node_list_path, "w", encoding="utf-8") as md_file:
md_file.write("# Node Reference\n")
for category in sorted(node_list.keys()):
md_file.write(f"## {category}\n| Node | Description |\n| --- | --- |\n")
for title, file_name, description in sorted(node_list[category]):
md_file.write(f"| [{title}]({file_name}) | {description} |\n")
def main():
"""Main function to process all Python files under modules/**.py."""
source_dir = "modules"
output_dir = "docs/reference"
os.makedirs(output_dir, exist_ok=True)
node_list = defaultdict(list)
for root, _, files in os.walk(source_dir):
for file in files:
if file.endswith(".py"):
file_path = os.path.join(root, file)
process_python_file(file_path, output_dir, node_list)
generate_node_list(output_dir, node_list)
if __name__ == "__main__":
main()
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# CDA JSON Create
Creates a serialized JSON object using values entered in the text field.
## Input
| Name | Data type |
|---|---|
| data | String |
## Output
| Data type |
|---|
| String |
<HR>
Category: IO
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# MPL Bar Chart
Generates a bar chart from a Pandas DataFrame.
## Output
| Data type |
|---|
| Image |
<HR>
Category: Plot
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# MPL Line Plot
Generates a line plot from a pandas DataFrame.
## Output
| Data type |
|---|
| Image |
<HR>
Category: Plot
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# MPL Scatter Plot
Generates a scatter plot from a pandas DataFrame.
## Output
| Data type |
|---|
| Image |
<HR>
Category: Plot
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# Node Reference
## Aggregation
| Node | Description |
| --- | --- |
| [Pandas Group By](pandas_group_by.md) | Computes aggregate values for groups in a DataFrame. |
## Arithmetic method
| Node | Description |
| --- | --- |
| [Pandas Add](pandas_add.md) | Adds two pandas DataFrames. |
| [Pandas Add Series](pandas_add_series.md) | Adds a Pandas Series to a pandas DataFrames. |
| [Pandas Div](pandas_div.md) | Divides two pandas DataFrames. |
| [Pandas Div Series](pandas_div_series.md) | Divides a Pandas DataFrame by a Pandas Series. |
| [Pandas Mul](pandas_mul.md) | Multiplies two pandas DataFrames. |
| [Pandas Mul Series](pandas_mul_series.md) | Multiplies a Pandas DataFrame by a Pandas Series. |
| [Pandas Pow](pandas_pow.md) | Exponentiates two pandas DataFrames. |
| [Pandas Pow Series](pandas_pow_series.md) | Raises a Pandas DataFrame to the power of a Pandas Series. |
| [Pandas Sub](pandas_sub.md) | Subtracts a Pandas DataFrame from another DataFrame. |
| [Pandas Sub Series](pandas_sub_series.md) | Subtracts a Pandas Series from a Pandas DataFrame. |
## Data cleansing
| Node | Description |
| --- | --- |
| [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. |
## Data subset selection
| Node | Description |
| --- | --- |
| [Pandas Head](pandas_head.md) | Retrieves the first few rows of a pandas DataFrame. |
| [Pandas Iloc Row Series](pandas_iloc_row_series.md) | Selects a row from a pandas DataFrame and returning it as a Series. |
| [Pandas Iloc Rows Data Frame](pandas_iloc_rows_dataframe.md) | Selects rows from a pandas DataFrame and returning it as a DataFrame. |
| [Pandas Loc Cell Str](pandas_loc_cell_str.md) | Selects a cell from a pandas DataFrame and output as a string. |
| [Pandas Loc Row Series](pandas_loc_row_series.md) | Selects a row from a pandas DataFrame and output as a Series. |
| [Pandas Select Columns](pandas_select_columns.md) | Selects specific columns from a pandas DataFrame. |
| [Pandas Select Rows](pandas_select_rows.md) | Selects specific rows from a pandas DataFrame based on a condition. |
## Data type conversion
| Node | Description |
| --- | --- |
| [Pandas As Float](pandas_as_float.md) | Converts all cells in a pandas DataFrame to float type. |
| [Pandas As Int](pandas_as_int.md) | Converts all cells in a pandas DataFrame to integer type. |
| [Pandas As String](pandas_as_string.md) | Converts all cells in a pandas DataFrame to string type. |
## DataFrame information
| Node | Description |
| --- | --- |
| [Pandas Columns](pandas_columns.md) | Retrieves the column labels of a pandas DataFrame. |
| [Pandas Index](pandas_index.md) | Retrieves the row labels (index) of a pandas DataFrame. |
## Display data
| Node | Description |
| --- | --- |
| [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. |
| [Pandas Show Index](pandas_show_index.md) | Displays a Pandas Index as text. |
| [Pandas Show Series](pandas_show_series.md) | Displays a Pandas Series as text. |
| [Pandas Show Text](pandas_show_text.md) | Displays a string. |
| [Pandas To String](pandas_to_string.md) | Converts a pandas DataFrame to a string representation. |
## IO
| Node | Description |
| --- | --- |
| [CDA JSON Create](cda_json_create.md) | Creates a serialized JSON object using values entered in the 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 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. |
## Math
| Node | Description |
| --- | --- |
| [Pandas Cos](pandas_cos.md) | Apply the cosine function to a pandas DataFrame and converting non-numeric values to NaN. |
| [Pandas Exp](pandas_exp.md) | Apply the exponential function to a pandas DataFrame and converting non-numeric values to NaN. |
| [Pandas Log](pandas_log.md) | Applying the natural logarithm function to a pandas DataFrame and converting non-numeric values to NaN. |
| [Pandas Sin](pandas_sin.md) | Applies the sine function to a pandas DataFrame and converting non-numeric values to NaN. |
| [Pandas Tan](pandas_tan.md) | Applies the tangent function to a pandas DataFrame and converting non-numeric values to NaN. |
## Plot
| Node | Description |
| --- | --- |
| [MPL Bar Chart](mpl_bar.md) | Generates a bar chart from a Pandas DataFrame. |
| [MPL Line Plot](mpl_line.md) | Generates a line plot from a pandas DataFrame. |
| [MPL Scatter Plot](mpl_scatter.md) | Generates a scatter plot from a pandas DataFrame. |
## Summary statistics
| Node | Description |
| --- | --- |
| [Pandas Count](pandas_count.md) | Computes the count of a pandas DataFrame. |
| [Pandas Max](pandas_max.md) | Computes the max of a pandas DataFrame. |
| [Pandas Mean](pandas_mean.md) | Computes the mean of a pandas DataFrame. |
| [Pandas Median](pandas_median.md) | Computes the median of a pandas DataFrame. |
| [Pandas Min](pandas_min.md) | Computes the min of a pandas DataFrame. |
| [Pandas Mode](pandas_mode.md) | Computes the mode of a pandas DataFrame. |
| [Pandas Std](pandas_std.md) | Computes the standard deviation of a pandas DataFrame. |
| [Pandas Sum](pandas_sum.md) | Computes the sum of a pandas DataFrame. |
| [Pandas Summary](pandas_summary.md) | Analyzes and summarizes a pandas DataFrame. |
| [Pandas Var](pandas_var.md) | Computes the variance of a pandas DataFrame. |
## Transformation
| Node | Description |
| --- | --- |
| [Pandas Horizontal Concat](pandas_horizontal_concat.md) | Horizontally concatenates 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. |
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# Pandas Add
Adds two pandas DataFrames.
## Input
| Name | Data type |
|---|---|
| a_dataframe | DataFrame |
| b_dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Arithmetic method
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# Pandas Add Series
Adds a Pandas Series to a pandas DataFrames.
## Input
| Name | Data type |
|---|---|
| a_dataframe | DataFrame |
| b_series | Series |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Arithmetic method
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# Pandas As Float
Converts all cells in a pandas DataFrame to float type.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Data type conversion
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# Pandas As Int
Converts all cells in a pandas DataFrame to integer type.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Data type conversion
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# Pandas As String
Converts all cells in a pandas DataFrame to string type.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Data type conversion
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# Pandas Columns
Retrieves the column labels of a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| Index |
<HR>
Category: DataFrame information
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# Pandas Cos
Apply the cosine function to a pandas DataFrame and converting non-numeric values to NaN.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Math
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# Pandas Count
Computes the count of a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| Series |
<HR>
Category: Summary statistics
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# Pandas Create
Creates a pandas DataFrame using values entered in the text field.
## Input
| Name | Data type |
|---|---|
| data | String |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: IO
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# Pandas Create With Index
Creates a pandas DataFrame using values entered in the text field. Input data is assumed to have an index.
## Input
| Name | Data type |
|---|---|
| data | String |
| index_col | Int |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: IO
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# Pandas Div
Divides two pandas DataFrames.
## Input
| Name | Data type |
|---|---|
| a_dataframe | DataFrame |
| b_dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Arithmetic method
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# Pandas Div Series
Divides a Pandas DataFrame by a Pandas Series.
## Input
| Name | Data type |
|---|---|
| a_dataframe | DataFrame |
| b_series | Series |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Arithmetic method
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# Pandas Drop NA
Drops missing values from a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Data cleansing
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# Pandas Exp
Apply the exponential function to a pandas DataFrame and converting non-numeric values to NaN.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Math
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# Pandas Group By
Computes aggregate values for groups in a DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
| column_name | String |
| aggragate_function | |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Aggregation
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# Pandas Head
Retrieves the first few rows of a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
| rows | Int |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Data subset selection
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# Pandas Horizontal Concat
Horizontally concatenates two pandas DataFrames.
## Input
| Name | Data type |
|---|---|
| a_dataframe | DataFrame |
| b_dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Transformation
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# Pandas Iloc Row Series
Selects a row from a pandas DataFrame and returning it as a Series.
The row is specified by its integer position, similar to an index in other software.
Note: In Pandas, "index" refers to a unique label assigned to each row. See https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.iloc.html
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
| row_integer_position | Int |
## Output
| Data type |
|---|
| Series |
<HR>
Category: Data subset selection
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# Pandas Iloc Rows Data Frame
Selects rows from a pandas DataFrame and returning it as a DataFrame.
Rows are specified by the list of integer positions.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
| row_int_pos_list_json | String |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Data subset selection
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# Pandas Index
Retrieves the row labels (index) of a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| Index |
<HR>
Category: DataFrame information
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# Pandas Index To String
Converts a pandas Index to a string representation.
## Input
| Name | Data type |
|---|---|
| index | Index |
## Output
| Data type |
|---|
| String |
<HR>
Category: Display data
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# Pandas Is NA
Checks a pandas DataFrame for missing values.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Data cleansing
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# Pandas Join
Merges two pandas DataFrames based on a common column.
## Input
| Name | Data type |
|---|---|
| left_dataframe | DataFrame |
| right_dataframe | DataFrame |
| on_column_name | String |
| join_method | |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Transformation
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# Pandas Load CSV
Loads CSV files into a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| file_path | String |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: IO
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# Pandas Load CSV With Encoding
Loads CSV files into a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| file_path | String |
| encoding | String |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: IO
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# Pandas Load CSV With Index
Loads CSV files into a pandas DataFrame.
Input data is assume to have an index.
## Input
| Name | Data type |
|---|---|
| file_path | String |
| index_col | Int |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: IO
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# Pandas Load JSON
Loads JSON files into a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| file_path | String |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: IO
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# Pandas Loc Cell Str
Selects a cell from a pandas DataFrame and output as a string.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
| row_index | String |
| row_index_type | |
| column_label | String |
| column_label_type | |
## Output
| Data type |
|---|
| String |
<HR>
Category: Data subset selection
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# Pandas Loc Row Series
Selects a row from a pandas DataFrame and output as a Series.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
| row_index | String |
| row_index_type | |
## Output
| Data type |
|---|
| Series |
<HR>
Category: Data subset selection
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# Pandas Log
Applying the natural logarithm function to a pandas DataFrame and converting non-numeric values to NaN.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Math
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# Pandas Max
Computes the max of a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| Series |
<HR>
Category: Summary statistics
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# Pandas Mean
Computes the mean of a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| Series |
<HR>
Category: Summary statistics
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# Pandas Median
Computes the median of a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| Series |
<HR>
Category: Summary statistics
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# Pandas Min
Computes the min of a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| Series |
<HR>
Category: Summary statistics
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# Pandas Mode
Computes the mode of a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Summary statistics
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# Pandas Mul
Multiplies two pandas DataFrames.
## Input
| Name | Data type |
|---|---|
| a_dataframe | DataFrame |
| b_dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Arithmetic method
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# Pandas Mul Series
Multiplies a Pandas DataFrame by a Pandas Series.
## Input
| Name | Data type |
|---|---|
| a_dataframe | DataFrame |
| b_series | Series |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Arithmetic method
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# Pandas Pow
Exponentiates two pandas DataFrames.
## Input
| Name | Data type |
|---|---|
| a_dataframe | DataFrame |
| b_dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Arithmetic method
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# Pandas Pow Series
Raises a Pandas DataFrame to the power of a Pandas Series.
## Input
| Name | Data type |
|---|---|
| a_dataframe | DataFrame |
| b_series | Series |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Arithmetic method
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# Pandas Save CSV
Saves a PandasDataFrame to a CSV file.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
| file_path | String |
## Output
| Data type |
|---|
| String |
<HR>
Category: IO
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# Pandas Save JSON
Saves a PandasDataFrame to a JSON file.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
| file_path | String |
## Output
| Data type |
|---|
| String |
<HR>
Category: IO
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# Pandas Select Columns
Selects specific columns from a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
| column_names | String |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Data subset selection
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# Pandas Select Rows
Selects specific rows from a pandas DataFrame based on a condition.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
| condition | String |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Data subset selection
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# Pandas Series To String
Converts a pandas Series to a string representation.
## Input
| Name | Data type |
|---|---|
| series | Series |
## Output
| Data type |
|---|
| String |
<HR>
Category: Display data
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# Pandas Show Data Frame
Displays a Pandas DataFrame as text.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| String |
<HR>
Category: Display data
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# Pandas Show Index
Displays a Pandas Index as text.
## Input
| Name | Data type |
|---|---|
| index_list | Index |
## Output
| Data type |
|---|
| String |
<HR>
Category: Display data
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# Pandas Show Series
Displays a Pandas Series as text.
## Input
| Name | Data type |
|---|---|
| series_list | Series |
## Output
| Data type |
|---|
| String |
<HR>
Category: Display data
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# Pandas Show Text
Displays a string.
## Input
| Name | Data type |
|---|---|
| text | String |
## Output
| Data type |
|---|
| String |
<HR>
Category: Display data
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# Pandas Sin
Applies the sine function to a pandas DataFrame and converting non-numeric values to NaN.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Math
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# Pandas Sort
Sorts a pandas DataFrame by a specified column.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
| column_name | String |
| ascending | Boolean |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Transformation
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# Pandas Std
Computes the standard deviation of a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| Series |
<HR>
Category: Summary statistics
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# Pandas Sub
Subtracts a Pandas DataFrame from another DataFrame.
## Input
| Name | Data type |
|---|---|
| a_dataframe | DataFrame |
| b_dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Arithmetic method
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# Pandas Sub Series
Subtracts a Pandas Series from a Pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| a_dataframe | DataFrame |
| b_series | Series |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Arithmetic method
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# Pandas Sum
Computes the sum of a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| Series |
<HR>
Category: Summary statistics
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# Pandas Summary
Analyzes and summarizes a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Summary statistics
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# Pandas Tan
Applies the tangent function to a pandas DataFrame and converting non-numeric values to NaN.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Math
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# Pandas To String
Converts a pandas DataFrame to a string representation.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| String |
<HR>
Category: Display data
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# Pandas Var
Computes the variance of a pandas DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
## Output
| Data type |
|---|
| Series |
<HR>
Category: Summary statistics
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# Pandas Vertical Concat
Vertically concatenates two pandas DataFrames.
## Input
| Name | Data type |
|---|---|
| a_dataframe | DataFrame |
| b_dataframe | DataFrame |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Transformation
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# User's Guide
For a complete list of nodes, refer to [the Node reference](reference/node_reference.md).
## Basic Concepts
### How to connect nodes for DataFrame
To connect the DataFrame output from one Pandas node to another, move the wire toward the top-left of the text field. You may need to hover around the corner to find the correct connection point.
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class CDAJSONCreate:
"""
CDAJSONCreate:
A class for creating a serialized JSON object using values entered in the text field.
CDA JSON Create:
Creates a serialized JSON object using values entered in the text field.
category: IO
"""
@classmethod
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class MPLBar:
"""
MPLBar:
A class for generating bar charts from a pandas DataFrame.
MPL Bar Chart:
Generates a bar chart from a Pandas DataFrame.
category: Plot
"""
@classmethod
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class MPLLine:
"""
MPLPlotLine:
A class for generating line plots from a pandas DataFrame.
MPL Line Plot:
Generates a line plot from a pandas DataFrame.
category: Plot
"""
@classmethod
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class MPLScatter:
"""
MPLPlotScatter:
A class for generating scatter plots from a pandas DataFrame.
MPL Scatter Plot:
Generates a scatter plot from a pandas DataFrame.
category: Plot
"""
@classmethod
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class PandasAdd:
"""
PandasAdd:
A class for adding two pandas DataFrames.
Adds two pandas DataFrames.
category: Arithmetic method
"""
@classmethod
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class PandasAddSeries:
"""
PandasAdd:
A class for adding a Pandas Series to a pandas DataFrames.
Adds a Pandas Series to a pandas DataFrames.
category: Arithmetic method
"""
@classmethod
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class PandasAsFloat:
"""
PandasAsFloat:
A class for converting all cells in a pandas DataFrame to float type.
Converts all cells in a pandas DataFrame to float type.
category: Data type conversion
"""
@classmethod
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class PandasAsInt:
"""
PandasAsInt:
A class for converting all cells in a pandas DataFrame to integer type.
Converts all cells in a pandas DataFrame to integer type.
category: Data type conversion
"""
@classmethod
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class PandasAsString:
"""
PandasAsString:
A class for converting all cells in a pandas DataFrame to string type.
Converts all cells in a pandas DataFrame to string type.
category: Data type conversion
"""
@classmethod
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class PandasColumns:
"""
PandasColumns:
A class for retrieving the column labels of a pandas DataFrame.
Retrieves the column labels of a pandas DataFrame.
category: DataFrame information
"""
@classmethod
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from typing import Any, Dict
import pandas as pd
import numpy as np
class PandasCos:
"""
Apply the cosine function to a pandas DataFrame and converting non-numeric values to NaN.
category: Math
"""
@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:
"""
Converts non-numeric values to NaN and applies the cosine function to the DataFrame.
The cosine function returns the ratio of the adjacent side to the hypotenuse in a right triangle,
or equivalently, the x-coordinate of a point on the unit circle.
Args:
dataframe (DataFrame): The DataFrame.
Returns:
tuple: A tuple containing the processed DataFrame.
"""
dataframe = dataframe.apply(pd.to_numeric, errors='coerce')
dataframe = np.cos(dataframe)
return (dataframe,)
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class PandasCount:
"""
PandasCount:
A class for computing the count of a pandas DataFrame.
Computes the count of a pandas DataFrame.
category: Summary statistics
"""
@classmethod
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class PandasCreate:
"""
PandasCreate:
A class for creating a pandas DataFrame using values entered in the text field.
Creates a pandas DataFrame using values entered in the text field.
category: IO
"""
@classmethod
@@ -5,9 +5,9 @@ import pandas as pd
class PandasCreateWithIndex:
"""
PandasCreateWithIndex:
A class for creating a pandas DataFrame using values entered in the text field.
Input data is assume to have an index.
Creates a pandas DataFrame using values entered in the text field. Input data is assumed to have an index.
category: IO
"""
@classmethod
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class PandasDiv:
"""
PandasDiv:
A class for dividing two pandas DataFrames.
Divides two pandas DataFrames.
category: Arithmetic method
"""
@classmethod
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class PandasDivSeries:
"""
PandasDivSeries:
A class for dividing a Pandas DataFrame by a Pandas Series.
Divides a Pandas DataFrame by a Pandas Series.
category: Arithmetic method
"""
@classmethod
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class PandasDropNA:
"""
PandasColumns:
A class for droping missing values from a pandas DataFrame.
Pandas Drop NA:
Drops missing values from a pandas DataFrame.
category: Data cleansing
"""
@classmethod
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from typing import Any, Dict
import pandas as pd
import numpy as np
class PandasExp:
"""
Apply the exponential function to a pandas DataFrame and converting non-numeric values to NaN.
category: Math
"""
@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:
"""
Converts non-numeric values to NaN and applies the exponential function to the DataFrame.
Args:
dataframe (DataFrame): The DataFrame.
Returns:
tuple: A tuple containing the processed DataFrame.
"""
dataframe = dataframe.apply(pd.to_numeric, errors='coerce')
dataframe = np.exp(dataframe)
return (dataframe,)
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class PandasGroupBy:
"""
PandasGroupBy:
A class for computing aggregate values for groups in a DataFrame.
Computes aggregate values for groups in a DataFrame.
category: Aggregation
"""
@classmethod
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class PandasHead:
"""
PandasHead:
A class for retrieving the first few rows of a pandas DataFrame.
Retrieves the first few rows of a pandas DataFrame.
category: Data subset selection
"""
@classmethod
@@ -4,8 +4,9 @@ import pandas as pd
class PandasHorizontalConcat:
"""
PandasHorizontalConcat:
A class for horizontally concatenating two pandas DataFrames.
Horizontally concatenates two pandas DataFrames.
category: Transformation
"""
@classmethod
@@ -5,10 +5,11 @@ from .utils import series_to_jsons
class PandasIlocRowSeries:
"""
PandasLocRowSeries:
A class for selecting a row from a pandas DataFrame and returning it as a Series.
The row is specified by its integer position, similar to an index in other software.
Note: In Pandas, "index" refers to a unique label assigned to each row. See https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.iloc.html
Selects a row from a pandas DataFrame and returning it as a Series.
The row is specified by its integer position, similar to an index in other software.
Note: In Pandas, "index" refers to a unique label assigned to each row. See https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.iloc.html
category: Data subset selection
"""
@classmethod
@@ -6,9 +6,10 @@ 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.
Selects rows from a pandas DataFrame and returning it as a DataFrame.
Rows are specified by the list of integer positions.
category: Data subset selection
"""
@classmethod
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class PandasIndex:
"""
PandasColumns:
A class for retrieving the row labels (index) of a pandas DataFrame.
Retrieves the row labels (index) of a pandas DataFrame.
category: DataFrame information
"""
@classmethod
@@ -4,8 +4,9 @@ import pandas as pd
class PandasIndexToString:
"""
PandasIndexToString:
A class for converting a pandas Index to a string representation.
Converts a pandas Index to a string representation.
category: Display data
"""
@classmethod
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@@ -4,8 +4,10 @@ import pandas as pd
class PandasIsNA:
"""
PandasColumns:
A class for checking a pandas DataFrame for missing values.
Pandas Is NA:
Checks a pandas DataFrame for missing values.
category: Data cleansing
"""
@classmethod
+3 -2
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@@ -5,8 +5,9 @@ import pandas as pd
class PandasJoin:
"""
PandasJoin:
A class for merging two pandas DataFrames based on a common column.
Merges two pandas DataFrames based on a common column.
category: Transformation
"""
@classmethod
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@@ -5,8 +5,10 @@ import pandas as pd
class PandasLoadCSV:
"""
PandasLoadCSV:
A class for loading CSV files into a pandas DataFrame.
Pandas Load CSV:
Loads CSV files into a pandas DataFrame.
category: IO
"""
@classmethod
@@ -5,8 +5,10 @@ import pandas as pd
class PandasLoadCSVWithEncoding:
"""
PandasLoadCSVWithEncoding:
A class for loading CSV files into a pandas DataFrame.
Pandas Load CSV With Encoding:
Loads CSV files into a pandas DataFrame.
category: IO
"""
@classmethod
@@ -5,9 +5,11 @@ import pandas as pd
class PandasLoadCSVWithIndex:
"""
PandasLoadCSV:
A class for loading CSV files into a pandas DataFrame.
Input data is assume to have an index.
Pandas Load CSV With Index:
Loads CSV files into a pandas DataFrame.
Input data is assume to have an index.
category: IO
"""
@classmethod
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@@ -5,8 +5,10 @@ import pandas as pd
class PandasLoadJSON:
"""
PandasLoadJSON:
A class for loading JSON files into a pandas DataFrame.
Pandas Load JSON:
Loads JSON files into a pandas DataFrame.
category: IO
"""
@classmethod

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