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PyTrendsPlus 📈📊\n\nA Python library to fetch and analyze Google Trends data with additional functionalities such as data visualization 📊, keyword suggestions 💡, and trend predictions 🔮.\n\n## Installation 🛠️\n\nTo install the library, run the following command:\n\n\n\n```\npip install pytrendsplus\n```\n\n## Configuration\n\nFirst, you need to import the library and create an instance of the `PyTrendsPlus` class:\n\n```python\nfrom pytrendsplus import PyTrendsPlus\n\ntrends = PyTrendsPlus()\n```\n## Usage\n\n### Fetch Google Trends Data\nTo fetch Google Trends data for a list of keywords and a specified time range:\n\n```\nkeywords = ['Python', 'JavaScript']\ntime_range = '2020-01-01 2020-02-01'\ndata = trends.fetch_data(keywords, time_range)\n```\n\n### Data Visualization\nTo visualize the fetched data as a line chart:\n\n```\ntrends.plot_line_chart(data, title='Google Trends Interest Over Time')\n```\n\n### Keyword Suggestions\nTo get keyword suggestions based on a given keyword:\n\n```\nkeyword = 'Python'\nsuggestions = trends.get_suggestions(keyword)\nprint(suggestions)\n```\n\n### Trend Predictions\nTo predict future trends based on the fetched data:\n\n```\npredictions = trends.predict_trends(data)\nprint(predictions)\n```\n\n### Export data\nTo export the fetched data to a CSV or JSON file:\n\n```\nfile_name = 'data.csv'\ntrends.export_data(data, file_name)\n\nfile_name = 'data.json'\ntrends.export_data(data, file_name)\n```\n\n## Examples\nTo demonstrate the usage of the pytrendsplus library, you can create a script with the following code:\n\n```commandline\nfrom pytrendsplus import PyTrendsPlus\n\n# Create an instance of the PyTrendsPlus class\ntrends = PyTrendsPlus()\n\n# Fetch Google Trends data\nkeywords = ['Python', 'JavaScript']\ntime_range = '2020-01-01 2020-02-01'\ndata = trends.fetch_data(keywords, time_range)\n\n# Visualize the data as a line chart\ntrends.plot_line_chart(data, title='Google Trends Interest Over Time')\n\n# Get keyword suggestions\nkeyword = 'Python'\nsuggestions = trends.get_suggestions(keyword)\nprint(suggestions)\n\n# Predict future trends\npredictions = trends.predict_trends(data)\nprint(predictions)\n\n# Export the data to a CSV file\nfile_name = 'data.csv'\ntrends.export_data(data, file_name)\n\n# Export the data to a JSON file\nfile_name = 'data.json'\ntrends.export_data(data, file_name)\n```\n\nSave this script as example.py and run it with the command:\n\n```\npython example.py\n```\n\n## License\nMIT License\n\n## Credits\n\n### Shout out to GeneralMills for creating the pytrends library which this library scaffolds off of\n### https://github.com/GeneralMills/pytrends","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkaneda2004%2Fpytrendsplus","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkaneda2004%2Fpytrendsplus","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkaneda2004%2Fpytrendsplus/lists"}