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A package for analyzing and visualizing EUR/USD forex data

Project description

EUR/USD Exchange Rate Analyzer

Course: Introduction to Python

This repository contains a Python package for analyzing and forecasting EUR/USD historical exchange rate data. It includes tools for data loading, preprocessing, exploratory data analysis, visualization, and time series forecasting using Facebook's Prophet library.

The package is built to support:

  • Time series forecasting
  • Exchange rate trend and volatility analysis

Dataset Overview

Source: Historical EUR/USD exchange rate data (2000–2025)

Frequency: Daily

Rows: 11,284

Columns: 7

Format: CSV

Columns:

  • Date – Date of recorded exchange rate (Format: DD-MM-YYYY)
  • Price – Closing price of EUR/USD
  • Open – Opening price
  • High – Highest price of the day
  • Low – Lowest price of the day
  • Vol. – Volume (all values are NaN)
  • Change % – Percent change from previous day (as string with % sign)

Installation

To install the package locally, clone this repository and install the required dependencies:

git clone https://github.com/nisher07/EURUSD_Analysis.git

Make sure you have Prophet, pandas, matplotlib, seaborn, and scikit-learn installed. If not, add them via:

pip install prophet pandas matplotlib seaborn scikit-learn

Usage Example

Here’s how to use the package after importing:

from EURUSD_package import DataLoader, DataAnalyzer, DataVisualizer,
AnalyzeForecast

# 1. Load and preprocess the dataset
loader = DataLoader("EURUSD_data.csv")
loader.load_data()
loader.preprocess_data()

# 2. Analyze the dataset
analyzer = DataAnalyzer(loader.data)
print(analyzer.describe_data())

# 3. Forecast future values
forecast = AnalyzeForecast(loader.data)
forecast.perform_forecasting()

For a full walkthrough, check the TUTORIAL.ipynb notebook in this repo.

License

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

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