fuzzy-df 0.1.1

Fuzzy merging and matching utilities for pandas Dataframes.

fuzzy-df

fuzzy-df is a Python package that provides utilities for performing fuzzy matching and merging on pandas DataFrames and Series. It leverages the power of rapidfuzz for efficient similarity computations and integrates seamlessly with pandas.

Features

• Fuzzy Matching: Match elements between two pandas Series based on similarity scores.
• Fuzzy Merging: Merge pandas DataFrames or Series using fuzzy matching logic.
• Customizable: Configure similarity score thresholds and specify custom column names for scores.

Installation

You can install fuzzy-df using pip:

pip install fuzzy-df

Usage

Fuzzy Matching

Use the fuzz_match function to perform fuzzy matching between two pandas Series:

import pandas as pd
from fuzzy_df.match import fuzz_match

comp_left = pd.Series(["apple", "banana", "cherry"])
comp_right = pd.Series(["apples", "grape", "bananas", "apple"])

matches = fuzz_match(comp_left, comp_right, score_cutoff=70)
print(matches)

Output:

   left_index  right_index       score
0           0            0   90.909088
1           0            3  100.000000
2           1            2   92.307693

Fuzzy Merging

Use the fuzz_merge function to merge two pandas DataFrames or Series based on fuzzy matching:

import pandas as pd
from fuzzy_df.merge import fuzz_merge

left = pd.DataFrame(
   {"id_left": [1, 2], "name_left": ["foo", "bar"]})
right = pd.DataFrame(
   {"id_right": [3, 4, 5, 6], "name_right": ["baz", "bear", "fool", "food"]})

merged = fuzz_merge(left, right, left_on="name_left",
                  right_on="name_right", score_cutoff=70)

print(merged)

Output:

   id_right name_right  id_left name_left  left_index  right_index      score
2         4       bear        2       bar           1            1  85.714287
0         5       fool        1       foo           0            2  85.714287
1         6       food        1       foo           0            3  85.714287

Building

Building with uv

To build the project using uv, follow these steps:

1. Setup python version: Overide the .python-version to test out on supported python version >=3.10:

   echo 3.13 > .python-version
   

2. Run the build command: Navigate to the project directory and execute the following command:

   uv build
   

   This will package the project and prepare it for distribution.

3. Verify the build: After the build process completes, you should see the generated distribution files in the dist/ directory. You can verify them by listing the contents:

   ls dist/
   

4. Install the built package locally (optional): To test the built package, you can install it locally using pip:

   pip install dist/fuzzy_df-<version>.tar.gz
   

Replace <version> with the actual version number of the package.

For more information on uv, refer to its documentation.

Testing

To run tests, follow these steps:

1. Install the package in editable mode:

   uv pip install -e .
   

2. Run the test suite using pytest:

   uv run pytest
   

This will execute all the tests and display the results in the terminal.

Contributing

Contributions are welcome! Feel free to open issues or submit pull requests on the GitHub repository.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Author

Developed by Iman-Budi Pranakasih. For inquiries, contact [e-mail].