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87 lines
2.5 KiB
Python
87 lines
2.5 KiB
Python
"""
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Starbucks Analysis Program
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HangZhou Dianzi University 2023-2024 Semester Final Project
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This module serves as the main entry point for the program, coordinating the work of various components
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including data processing, visualization, and analysis.
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Main functionalities:
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1. Read and process Starbucks global store data
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2. Perform data cleaning and transformation
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3. Generate data visualization charts
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4. Conduct data analysis and output results
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Dependencies:
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- data_processor: For data processing tasks
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- visualizer: For data visualization
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- analyzer: For data analysis
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- config_manager: For managing configuration information
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"""
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from data_processor import DataProcessor, fill_city
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from visualizer import Visualizer
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from analyzer import Analyzer
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from config_manager import ConfigManager
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def main():
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"""
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Main function that coordinates the execution flow of the entire program.
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Key steps:
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1. Initialize the configuration manager
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2. Read and process data
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3. Display data statistics
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4. Perform data cleaning and transformation
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5. Save the processed data
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6. Generate visualization charts
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7. Process Starbucks data for China
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8. Conduct data analysis and output results
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No parameters, no return value
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"""
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config = ConfigManager()
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processor = DataProcessor(config.get('input_file'))
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print("前五行数据：")
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print(processor.head)
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print("\n缺失值情况：")
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print(processor.missing_data)
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print("\nCity字段缺失的数据：")
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print(processor.city_null)
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processor.apply_function(fill_city, 'City')
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print("\n填充后的埃及(EG)数据：")
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print(processor.filter_by_country('EG'))
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unique_brands = processor.df['Brand'].unique()
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print("\n唯一的Brand值：", unique_brands)
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processor.replace_values('Brand', dict.fromkeys(unique_brands, 'Starbucks'))
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processor.save_to_csv(config.get('output_file'))
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print(f"\n数据已保存到{config.get('output_file')}")
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Visualizer.plot_top_countries(processor.df)
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Visualizer.plot_top_cities(processor.df)
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cn_starbucks = processor.filter_by_country('CN')
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print("\n中国星巴克分布（前五行）：")
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print(cn_starbucks.head())
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cn_starbucks.to_csv(config.get('cn_output_file'), index=False)
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print(f"\n中国星巴克数据已保存到{config.get('cn_output_file')}")
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Visualizer.plot_top_cn_cities(cn_starbucks)
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analyzer = Analyzer()
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analysis = analyzer.analyze_data(processor.df)
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print(analyzer.format_analysis(analysis))
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if __name__ == "__main__":
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main()
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