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This Python script utilizes exponential regression to project future values based on historical data provided by the user. It offers a simple and intuitive interface for inputting quarterly or monthly data and generates projections for the upcoming periods.

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MobinMithun/ExponentialRegressionProjection

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Exponential Regression Projection

forthebadge made-with-python

This Python script utilizes exponential regression to project future values based on historical data provided by the user. It offers a simple and intuitive interface for inputting quarterly or monthly data and generates projections for the upcoming periods.

Usage

  1. Input Data: The user is prompted to input either quarterly or monthly data along with the corresponding values.
  2. Projection Calculation: The script calculates future projections using exponential regression.
  3. Visualization: It visualizes both the actual data and the projected values using a bar chart.
  4. Display Projections: The script also displays the future projections for the next 4 quarters or months.

Features

  • Supports both quarterly and monthly data input.
  • Calculates projections using exponential regression.
  • Visualizes data and projections for easy interpretation.
  • Provides a clear display of future projections.

Requirements

  • Python 3.x
  • NumPy (!pip install numpy)
  • Matplotlib (!pip install matplotlib)

Getting Started

  1. Clone the repository: git clone https://github.com/MobinMithun/ExponentialRegressionProjection.git
  2. Navigate to the project directory: cd ExponentialRegressionProjection
  3. Install dependencies: pip install -r requirements.txt
  4. Run the script: python ExponentialRegressionProjection.ipynb

Contributing

Contributions are welcome! If you have any ideas for improvements or new features, feel free to submit a pull request.

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This Python script utilizes exponential regression to project future values based on historical data provided by the user. It offers a simple and intuitive interface for inputting quarterly or monthly data and generates projections for the upcoming periods.

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