{"id":21423468,"url":"https://github.com/nafisalawalidris/data-analysis-with-python","last_synced_at":"2025-03-16T20:26:11.641Z","repository":{"id":163626423,"uuid":"637560355","full_name":"nafisalawalidris/Data-Analysis-with-Python","owner":"nafisalawalidris","description":"This repo features Jupyter Notebook labs for learning data analysis with Python. Explore data acquisition, wrangling, visualization, modeling, and evaluation. 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Each lab focuses on a specific aspect of data analysis, including data acquisition, data wrangling, exploratory data analysis, model development and model evaluation and refinement.\u003c/p\u003e\n\n\u003ch2\u003eLab Topics\u003c/h2\u003e\n\n\u003col\u003e\n  \u003cli\u003eData Acquisition: Learn different methods to acquire data and load datasets into Jupyter Notebook.\u003c/li\u003e\n  \u003cli\u003eData Wrangling: Handle missing values, correct data format, standardize and normalise data.\u003c/li\u003e\n  \u003cli\u003eExploratory Data Analysis: Explore features to predict car prices using visualization and descriptive statistics.\u003c/li\u003e\n  \u003cli\u003eModel Development: Develop prediction models to estimate car prices.\u003c/li\u003e\n  \u003cli\u003eModel Evaluation and Refinement: Evaluate, refine, and select the best prediction models using techniques like Ridge Regression and Grid Search.\u003c/li\u003e\n\u003c/ol\u003e\n\n\u003ch2\u003eGetting Started\u003c/h2\u003e\n\n\u003cp\u003eTo run the lab notebooks locally, follow these steps:\u003c/p\u003e\n\n\u003col\u003e\n  \u003cli\u003eClone the repository: \u003ccode\u003egit clone https://github.com/your-username/data-analysis-with-python.git\u003c/code\u003e\u003c/li\u003e\n  \u003cli\u003eNavigate to the repository: \u003ccode\u003ecd data-analysis-with-python\u003c/code\u003e\u003c/li\u003e\n  \u003cli\u003eCreate a virtual environment: \u003ccode\u003epython -m venv env\u003c/code\u003e\u003c/li\u003e\n  \u003cli\u003eActivate the virtual environment:\n    \u003cul\u003e\n      \u003cli\u003eFor Windows: \u003ccode\u003eenv\\Scripts\\activate\u003c/code\u003e\u003c/li\u003e\n      \u003cli\u003eFor macOS/Linux: \u003ccode\u003esource env/bin/activate\u003c/code\u003e\u003c/li\u003e\n    \u003c/ul\u003e\n  \u003c/li\u003e\n  \u003cli\u003eInstall the required dependencies: \u003ccode\u003epip install -r requirements.txt\u003c/code\u003e\u003c/li\u003e\n  \u003cli\u003eStart Jupyter Notebook: \u003ccode\u003ejupyter notebook\u003c/code\u003e\u003c/li\u003e\n  \u003cli\u003eOpen the desired lab notebook and start learning!\u003c/li\u003e\n\u003c/ol\u003e\n\n\u003ch2\u003eRequirements\u003c/h2\u003e\n\n\u003cp\u003eThe labs in this repository require the following dependencies:\u003c/p\u003e\n\n\u003cul\u003e\n  \u003cli\u003ePython 3\u003c/li\u003e\n  \u003cli\u003eJupyter Notebook\u003c/li\u003e\n  \u003cli\u003ePandas\u003c/li\u003e\n  \u003cli\u003eNumPy\u003c/li\u003e\n  \u003cli\u003eMatplotlib\u003c/li\u003e\n  \u003cli\u003eSeaborn\u003c/li\u003e\n  \u003cli\u003eScikit-learn\u003c/li\u003e\n\u003c/ul\u003e\n\n\u003cp\u003eYou can install the required dependencies by running \u003ccode\u003epip install -r requirements.txt\u003c/code\u003e.\u003c/p\u003e\n\n\u003ch2\u003eContributing\u003c/h2\u003e\n\n\u003cp\u003eContributions are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request.\u003c/p\u003e\n\n\u003ch2\u003eLicense\u003c/h2\u003e\n\n\u003cp\u003eThis repository is licensed under the MIT License. See the \u003ca href=\"LICENSE\"\u003eLICENSE\u003c/a\u003e file for more details.\u003c/p\u003e\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnafisalawalidris%2Fdata-analysis-with-python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnafisalawalidris%2Fdata-analysis-with-python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnafisalawalidris%2Fdata-analysis-with-python/lists"}