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A Go application providing real-time Bitcoin price aggregation and next-day price prognosis using CoinGecko API. Features include historical price data over the last 7 days and trend analysis for future price predictions.

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RamazanKara/bitcoin-price-aggregator-go

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Bitcoin Price Aggregator & Next Day Trend Prognosis

Introduction

This Go application provides historical price data for Bitcoin over the last 7 days and predicts the price for the next day, along with identifying the trend (upwards, downwards, or stable). The application fetches data from the CoinGecko API and uses a linear regression model for the prognosis. It includes preprocessing steps to prepare the data for more accurate predictions.

Installation

To set up this project, you need to have Go installed on your system.

  1. Clone the repository:

    git clone [repository-url]
  2. Navigate to the project directory:

    cd bitcoin-prognosis

Usage

Run the application with the following command:

go run cmd/main/main.go

This will output the Bitcoin prices for the last 7 days and the prognosis for the next day, including the price trend. You are free to also include any of the pkgs into your own application.

Data Preprocessing

The application includes a preprocessing module that prepares the historical Bitcoin price data for the prognosis. This preprocessing includes handling missing values and removing outliers, providing a cleaner dataset for the prediction model.

Testing

To run the tests for this application, use the following command in the project directory:

go test -v ./...

The tests cover the functionality of fetching Bitcoin prices and the prognosis algorithm.

Contributing

Contributions to this project are welcome. Please fork the repository and submit a pull request with your changes.

License

This project is open source and available under the MIT License.

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A Go application providing real-time Bitcoin price aggregation and next-day price prognosis using CoinGecko API. Features include historical price data over the last 7 days and trend analysis for future price predictions.

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