https://github.com/teja-1403/create-and-share-your-jupyter-notebook

Coursera: Tools for Data Science - Final Assignment Instructions: Create and Share Your Jupyter Notebook
https://github.com/teja-1403/create-and-share-your-jupyter-notebook

jupyter-notebook

Last synced: 7 days ago
JSON representation

Coursera: Tools for Data Science - Final Assignment Instructions: Create and Share Your Jupyter Notebook

• Host: GitHub
• URL: https://github.com/teja-1403/create-and-share-your-jupyter-notebook
• Owner: teja-1403
• Created: 2025-01-25T07:31:59.000Z (13 days ago)
• Default Branch: main
• Last Pushed: 2025-01-25T07:34:36.000Z (13 days ago)
• Last Synced: 2025-01-25T08:21:23.081Z (13 days ago)
• Topics: jupyter-notebook
• Language: Jupyter Notebook
• Homepage: https://www.coursera.org/learn/open-source-tools-for-data-science/ungradedWidget/VWCTU/final-assignment-instructions-create-and-share-your-jupyter-notebook
• Size: 0 Bytes
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Create and Share Your Jupyter Notebook

This repository contains the Jupyter Notebook titled **DataScienceEcosystem.ipynb**, created as part of the final assignment for the Data Science course. The notebook provides an overview of tools, languages, and libraries used in Data Science along with examples of basic Python arithmetic operations.

## Notebook Overview

The notebook covers the following key aspects:

1. **Title and Introduction**: Overview of the tools and ecosystem in Data Science.

2. **Languages for Data Science**: Lists popular programming languages used by Data Scientists.

3. **Libraries in Data Science**: Describes commonly used libraries in the Data Science field.

4. **Development Tools**: A table showcasing open-source tools used in Data Science.

5. **Arithmetic Operations**: Examples of arithmetic operations in Python for educational purposes.

6. **Objectives**: Summarizes the key takeaways from the notebook.

7. **Author Details**: Includes the author's name.

## Exercises Included

The notebook consists of the following exercises:

1. **Markdown Cells**:

   - Title of the notebook.

   - Introduction to Data Science tools and ecosystem.

   - List of popular languages and libraries in Data Science.

   - Table of tools used in Data Science.

   - List of objectives covered.

   - Author details.

2. **Code Cells**:

   - Multiplication and addition example: Evaluates the expression `(3*4)+5`.

   - Conversion example: Converts 200 minutes into hours.

## Screenshots

Below are the screenshot names corresponding to each exercise:

1. **Notebook Cover**: `1-notebook.png`

2. **Title**: `2-title.png`

3. **Introduction**: `3-intro.png`

4. **Data Science Languages**: `4-dslanguages.png`

5. **Data Science Libraries**: `5-dslibraries.png`

6. **Tools Table**: `6-dstools.png`

7. **Arithmetic Examples Introduction**: `7-introarithmetic.png`

8. **Multiply and Add Integers**: `8-multiplyandaddintegers.png`

9. **Minutes to Hours Conversion**: `9-hourstominutes.png`

10. **Objectives**: `10-objectives.png`

11. **Author Details**: `11-authordetails.png`