funcnodes-pandas

funcnodes-pandas is an extension for the Funcnodes framework that allows you to manipulate Pandas DataFrames and Series using FuncNodes' visual node-based system. It provides a collection of nodes for performing typical operations on Pandas data structures, such as conversions, data manipulations, and calculations.

This library enables no-code and low-code workflows for Pandas by providing drag-and-drop functionality in a visual interface. It also supports Python-based scripting to handle more complex operations.

Features

• DataFrame Conversion:

  • Convert DataFrames to dictionaries and vice versa.
  • Handle CSV and Excel files easily using DataFrame nodes.

• Data Manipulation:

  • Add, drop, and manipulate rows and columns of a DataFrame.
  • Handle missing data with nodes for fillna, dropna, ffill, and bfill.
  • Perform merges and joins with intuitive nodes for merge, concatenate, and join.

• Math & Statistical Operations:

  • Perform descriptive statistics like mean, sum, std, var, and corr.
  • Evaluate custom expressions directly on DataFrames using the eval node.

• Masking & Filtering:

  • Apply masks to filter DataFrame data.
  • Use conditions to filter rows and columns dynamically.

• Grouping & Aggregation:

  • Group data using groupby and aggregate it with sum, mean, count, etc.
  • Easily convert groups into lists of DataFrames.

• Series Support:

  • Nodes for converting Series to lists and dictionaries.
  • Access individual elements using iloc and loc.
  • Perform string operations on Series.

Installation

Install the package with:

pip install funcnodes-pandas

Ensure that you have Pandas and FuncNodes installed.

Getting Started

Here's an overview of the basic programmatically usage of funcnodes-pandas.

1. Convert a DataFrame to a Dictionary

import pandas as pd
import funcnodes_pandas as fnpd

df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
node = fnpd.to_dict()
node.inputs['df'].value = df
await node
print(node.outputs['dict'].value)

This code converts a DataFrame to a dictionary using the to_dict node.

2. Filling Missing Data

node = fnpd.fillna()
node.inputs["df"].value = df
node.inputs["value"].value = 0
await node
print(node.outputs["out"].value)

The fillna node fills missing data in a DataFrame.

3. Group By Operations

node = fnpd.group_by()
node.inputs["df"].value = df
node.inputs["by"].value = "A"
await node
print(node.outputs["grouped"].value)

This groups data based on column A in the DataFrame.

Testing

The repository contains a suite of tests to ensure that the various functionalities of funcnodes-pandas work as expected. The tests are based on unittest and IsolatedAsyncioTestCase. You can run the tests using:

python -m unittest discover

Test cases for operations such as groupby, add_column, dropna, etc., are included.

Contribution

Feel free to contribute to this project by submitting pull requests. You can help by adding new nodes, fixing bugs, or enhancing documentation.

License

This project is licensed under the MIT License.

Contact

For any questions or issues, please open an issue on the GitHub repository.