Metadata-Version: 2.4
Name: findmyjoint
Version: 0.0.1
Summary: A utility to find potential join keys (matching columns) across multiple pandas DataFrames.
Project-URL: Homepage, https://github.com/Rudra-G-23/Find-My-Joint
Project-URL: Issues, https://github.com/Rudra-G-23/Find-My-Joint/issues
Author-email: Rudra Prasad Bhuyan <rudraprasadbhuyan999@gmial.com>
License: Copyright (c) 2025 Rudra Prasad Bhuyan
        
        Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
License-File: LICENSE
Keywords: data-analysis,data-engineering,join,pandas,schema,visualization
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.8
Requires-Dist: pandas>=1.3
Requires-Dist: pyvis>=0.3
Requires-Dist: rapidfuzz>=2.0
Description-Content-Type: text/markdown

# FindMyJoint

A Python utility to analyze and compare columns across multiple pandas DataFrames, suggesting potential join keys and visualizing the relationships.

When working with multiple disparate datasets, finding common columns to join them on is a tedious manual task. findmyjoint automates this by:

1. Profiling each DataFrame's columns (dtype, uniqueness, nulls).
2. Comparing all possible column pairs across datasets.
3. Scoring pairs based on name similarity (using rapidfuzz) and content similarity (using Jaccard index).
4. Suggesting join confidence levels.
5. Visualizing the connections as an interactive network graph (using pyvis).

## Installation
You will be able to install this via pip once it's published:


```bash
pip install findmyjoint
```


## Quickstart

You can get a comparison matrix or an interactive graph with a single line of code.

### 1. Create toy datasets
```bash
df1 = pd.DataFrame({
    'age': [21, 25, 30, 45],
    'name': ['Alice', 'Bob', 'Charlie', 'David'],
    'user_id': ['001', '002', '003', '004']
})

df2 = pd.DataFrame({
    'Age': ['21', '25', '30', '45'],
    'full_name': ['Alice', 'Bob', 'Charlie', 'David'],
    'customer_id': [1, 2, 3, 4]
})

df3 = pd.DataFrame({
    'client_identifier': ['001', '002', '003', '004'],
    'location': ['USA', 'CAN', 'USA', 'MEX'],
    'years_old': [21, 25, 30, 45]
})

datasets = [df1, df2, df3]
names = ['hr', 'crm', 'finance']

# 2. Get the comparison matrix
print("--- Comparison Matrix ---")
matrix = fmj.compare(datasets, names=names, name_threshold=0.6)
print(matrix.head())

# 3. Generate the interactive network graph
print("\n--- Generating Network Graph ---")

# This will create and automatically open 'joint_graph.html'
fmj.network(datasets, names=names, threshold=0.6)
print("Graph 'joint_graph.html' created.")
```