{"id":26868906,"url":"https://github.com/cintia0528/data_cleaning_and_analytics-python","last_synced_at":"2026-01-08T06:49:07.770Z","repository":{"id":189928778,"uuid":"681590784","full_name":"Cintia0528/Data_Cleaning_and_Analytics-Python","owner":"Cintia0528","description":"Evaluate if aggressive discounting benefits Eniac long-term, considering differing views on customer acquisition and brand positioning. 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The board wants an **immediate answer** to whether the company should continue **discounting** or not. **The data is compromised**, therefore before analysis we must **clean** the data and **assess its quality**, in addition to defining how it **impairs our decision-making ability**.\n\n### Challenge: \n*How to clean and assure the data's quality without losing too much information, so as to retain enough data for decision making?* \n\n## Approach\nEvaluate the database:\n1. Clean data for unreadable entries, duplicates and other obvious errors\n2. Assess the remaining data for quality - remove compromised orders\n3. Note the constraints the loss of data caused in our ability to make decisions\n4. Basis of decision making: comparison between the recommended prices, and product catalog and the actual sales\n5. Note recommendations; how to improve data collection and further research questions\n\n## Deliverables\n5 minute **PowerPoint presentation** found [here](https://drive.google.com/file/d/1v3fMzSTz0JX0YVLydWhl2BjVN6A2yels/view?usp=sharing) to the Board of Directors, that summarizes the findings and suggests a course of action.\n**Python code** is found [here](https://github.com/Cintia0528/Data-Cleaning-and-Analysis-with-Python.git).\n\n### Colab Files\n  1. Files starting with 2 are the data cleaning files, each table its own file\n  2. Files starting with 3 are the data quality files\n  3. Files starting with 4 are the data analysis files\n\n## Skills \u0026 Tools\n1. Data Cleaning \u0026 Quality Assurance\n2. Data Visualization \u0026 Storytelling\n3. Colab \u0026 Jupyter Notebook\n4. Python: Pandas, Seaborn, Matplotlib\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcintia0528%2Fdata_cleaning_and_analytics-python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcintia0528%2Fdata_cleaning_and_analytics-python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcintia0528%2Fdata_cleaning_and_analytics-python/lists"}