df-datefixer 1.0.1

A package to automatically standardize dates in Pandas DataFrames.

df-datefixer

A lightweight Python library to standardize date columns in Pandas DataFrames. It automatically handles multiple date formats, missing values, problematic entries, multi-column fixing, optional datetime conversion, and more.

Installation

Install via pip:

pip install df-datefixer

Usage

Basic usage:

import pandas as pd
from df_datefixer.fixer import fix_dates

df = pd.DataFrame({
    'event_date': ['2022-01-01', '1/2/2022', 'bad-date', None]
})

fixed_df = fix_dates(df, column="event_date", target_format="%Y-%m-%d", missing_value="0")

print(fixed_df)

Multiple columns, datetime conversion, and custom placeholders:

df = pd.DataFrame({
    'start_date': ['2022-01-01', '1/2/2022', 'bad-date', None],
    'end_date': ['2022-02-01', 'invalid', '03-03-2022', None]
})

fixed_df = fix_dates(df, columns=['start_date', 'end_date'], convert_to_datetime=True, missing_value="NaT")

print(fixed_df)

Important note about datetime conversion:

If you set convert_to_datetime=True with a custom missing_value, your column might be converted to object type instead of datetime, because custom placeholders might not be datetime-compatible. For pure datetime operations, leaving missing_value as "NaT" (default datetime placeholder) is recommended.

Parameters

• df: A pandas DataFrame
• column: Column name containing dates (single column)
• columns: List of column names to fix simultaneously
• target_format: Desired standardized date format (default is "%Y-%m-%d")
• missing_value: Replacement for missing/unparsable dates (default is "0")
• verbose: Print details about problematic dates (default is True)
• convert_to_datetime: Converts fixed dates to pandas datetime type if True (default is False)
• inplace: Modifies DataFrame in place if True, else returns a new DataFrame (default is False)

Development

Set up virtual environment

python -m venv venv
source venv/bin/activate  # on macOS/Linux
.\venv\Scripts\activate  # on Windows

Clone repository and install dependencies

git clone https://github.com/kyriaki-mvr/df-datefixer.git
cd df-datefixer
pip install -e .
pip install pytest

Run tests

pytest tests

PyPI

See the package on PyPI - df-datefixer.

License

df-datefixer is licensed under the MIT License. See LICENSE for details.

Contributing

Contributions and issues are welcome! Please open an issue or submit a pull request on GitHub.