jedoyt /
web-scraping-with-python-notes
A collection of Jupyter Notebooks containing notes and exercises from a course from DataCamp
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⑂ 0 forks◯ 0 issuesUpdated Mar 11, 2019
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harrystaley / repository
A collection of Jupyter notebooks showcasing my progress and completion of data science coursework on DataCamp, featuring exploratory data analysis and Python-based projects. Note: These materials are intended for personal demonstration and not for academic dishonesty.
# DataCamp
Welcome to my DataCamp repository! This repository contains a series of Jupyter notebooks that document my progress and achievements in various data science courses offered by DataCamp. The notebooks primarily focus on exploratory data analysis and Python-based projects.
Please note that the content in this repository is intended for personal demonstration of my skills and learning journey. It is not intended for use in academic dishonesty or as a substitute for doing your own coursework.
## Project Structure
The repository is organized as follows:
- **/notebooks**: This directory contains all the Jupyter notebooks, each corresponding to different modules or projects completed on DataCamp.
- **/data**: Sample datasets used in the notebooks for analysis and visualization.
- **/scripts**: Contains Python scripts that supplement the Jupyter notebooks, if applicable.
- **/images**: Any images or graphics used in the notebooks for explanation or visualization purposes.
## Setup and Installation
To get started with these notebooks, you'll need to set up a Python environment and install some dependencies. Here's how you can do it:
### Prerequisites
- Python 3.x
- pip (Python package installer)
### Installation
1. Clone this repository to your local machine using:
```bash
git clone https://github.com/your-username/DataCamp.git
Navigate to the cloned repository:
cd DataCamp
Install the required Python packages:
pip install -r requirements.txt
To open and run the notebooks, start Jupyter Notebook:
jupyter notebook
This will open the Jupyter Notebook interface in your browser, where you can open and run the notebooks.
To use the notebooks, simply navigate to the /notebooks directory after launching Jupyter Notebook. Here you can open any notebook you wish to view or edit.
Example:
Introduction_to_Python.ipynb to start with the basics of Python used in the DataCamp courses.Each notebook is self-contained and includes both the necessary code and datasets needed for execution.
Contributions to this repository are welcome, especially from fellow DataCamp students who wish to collaborate on projects or enhance the existing notebooks.
To contribute:
git checkout -b feature-branch).git commit -am 'Add some feature').git push origin feature-branch).Please make sure to update tests as appropriate.
This project is licensed under the MIT License - see the LICENSE.md file for details.
Happy Coding!
This README.md provides a comprehensive guide for users to understand, set up, and use the repository effectively. It also encourages collaboration and proper usage etiquette.
Selected from shared topics, language and repository description—not editorial ratings.
jedoyt /
A collection of Jupyter Notebooks containing notes and exercises from a course from DataCamp