https://github.com/nafisalawalidris/data-analysis-with-python

This repo features Jupyter Notebook labs for learning data analysis with Python. Explore data acquisition, wrangling, visualization, modeling, and evaluation. Enhance your skills in Python data analysis.
https://github.com/nafisalawalidris/data-analysis-with-python

data-acquisition data-analysis data-science data-wrangling exploratory-data-analysis feature-engineering machine-learning model-development model-evaluation-and-refinement pandas

Last synced: about 1 month ago
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This repo features Jupyter Notebook labs for learning data analysis with Python. Explore data acquisition, wrangling, visualization, modeling, and evaluation. Enhance your skills in Python data analysis.

• Host: GitHub
• URL: https://github.com/nafisalawalidris/data-analysis-with-python
• Owner: nafisalawalidris
• Created: 2023-05-07T23:15:33.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-06-26T22:53:29.000Z (over 1 year ago)
• Last Synced: 2023-10-07T00:25:13.982Z (about 1 year ago)
• Topics: data-acquisition, data-analysis, data-science, data-wrangling, exploratory-data-analysis, feature-engineering, machine-learning, model-development, model-evaluation-and-refinement, pandas
• Language: Jupyter Notebook
• Homepage:
• Size: 3.09 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
Data Analysis with Python


This repository contains a collection of Jupyter Notebook labs for learning data analysis with Python. 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.


Lab Topics




  
Data Acquisition: Learn different methods to acquire data and load datasets into Jupyter Notebook.

  
Data Wrangling: Handle missing values, correct data format, standardize and normalise data.

  
Exploratory Data Analysis: Explore features to predict car prices using visualization and descriptive statistics.

  
Model Development: Develop prediction models to estimate car prices.

  
Model Evaluation and Refinement: Evaluate, refine, and select the best prediction models using techniques like Ridge Regression and Grid Search.



Getting Started


To run the lab notebooks locally, follow these steps:




  
Clone the repository: git clone https://github.com/your-username/data-analysis-with-python.git



  
Navigate to the repository: cd data-analysis-with-python



  
Create a virtual environment: python -m venv env



  
Activate the virtual environment:

    


      
For Windows: env\Scripts\activate



      
For macOS/Linux: source env/bin/activate



    

  

  
Install the required dependencies: pip install -r requirements.txt



  
Start Jupyter Notebook: jupyter notebook



  
Open the desired lab notebook and start learning!



Requirements


The labs in this repository require the following dependencies:




  
Python 3

  
Jupyter Notebook

  
Pandas

  
NumPy

  
Matplotlib

  
Seaborn

  
Scikit-learn



You can install the required dependencies by running pip install -r requirements.txt.


Contributing


Contributions are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request.


License


This repository is licensed under the MIT License. See the LICENSE file for more details.