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Get meaningful statistical insights on TCC data, in an easy-to-use Streamlit application.

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dimboump/tcc-stats

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Statistics for TCC

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Installation and Usage

  1. Clone the repository:

    git clone [email protected]:dimboump/tcc-stats
  2. Install the dependencies and run the script:

    • Windows:

      pip install -r requirements.txt
      python tcc_stats.py
    • Linux/macOS:

      pip3 install -r requirements.txt
      python3 tcc_stats.py

Options:

Option Data Type Description Default
-p, --path str or pathlib.Path Path to or name of the TCC data directory. data/
-y, --years int, Sequence[int] Years to include in the statistics. You can specify a single year or multiple years, by separating them with a space. 2018-today
-m, --months int, Sequence[int] Months to include in the statistics. To specify multiple months, separate them with a comma. 12 months if the year is in the past, current month since January of this year otherwise
-o, --output str or pathlib.Path Path to or name of the output file (with extension). Can also be an Excel file (.xlsx, .xls). If the path/file doens't exist, it will be created or, if it does, will be overwritten. export.csv
-v, --verbose bool Print more information about the data, along with a small sample (max 10 rows) before and after preprocessing. False
-h, --help Show help message and exit.