https://github.com/willie-conway/data-science-tools-and-ecosystem
🧠 Explore essential Data Science 🧪 tools, 🧰 libraries, and 🐍 Python arithmetic basics — perfect for beginners!
https://github.com/willie-conway/data-science-tools-and-ecosystem
data-science jupyter keras notebooks numpy pandas python pytorch
Last synced: 2 months ago
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🧠 Explore essential Data Science 🧪 tools, 🧰 libraries, and 🐍 Python arithmetic basics — perfect for beginners!
- Host: GitHub
- URL: https://github.com/willie-conway/data-science-tools-and-ecosystem
- Owner: Willie-Conway
- Created: 2025-01-25T11:15:59.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-05-25T02:42:50.000Z (5 months ago)
- Last Synced: 2025-07-06T02:40:54.898Z (3 months ago)
- Topics: data-science, jupyter, keras, notebooks, numpy, pandas, python, pytorch
- Language: Jupyter Notebook
- Homepage:
- Size: 7.81 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 📊 Data Science Tools & Arithmetic with Python 🐍
## Overview 👋🏿
Welcome to this notebook! In this document, we will explore the essential **tools, libraries, and programming languages** used in the field of **Data Science**. You'll also see some basic arithmetic operations demonstrated using **Python**.
This notebook aims to provide:
* 🔍 An overview of popular programming languages used in Data Science
* 📚 Key libraries for data analysis and machine learning
* 🛠️ Useful tools that help data scientists in their workflow
* ➕➖✖️➗ Simple arithmetic operations in Python
Let's dive into the exciting world of Data Science tools and technologies! 🚀
---
## Data Science Tools and Ecosystem 🌐
In this notebook, you'll find a summary of the Data Science tools and ecosystem, including:
### Objectives 🎯
* List popular libraries used in Data Science
* List open-source development environments and tools commonly used
* Introduce simple arithmetic expression evaluation in Python
---
### Popular Languages for Data Science 🗣️
* 🐍 **Python**
* 🗃️ **SQL**
* 📊 **R**
* 🔣 **Julia**
---
### Commonly Used Libraries 📦
* 🔢 **NumPy** — for numerical computing
* 🧠 **Keras** — for deep learning
* 🐼 **Pandas** — for data manipulation and analysis
* 🔥 **PyTorch** — for machine learning and AI
---
### Data Science Tools 🧰
* 📓 **Jupyter Notebooks** — interactive notebooks for coding and visualization
* 📊 **RStudio** — integrated development environment for R
* ☁️ **Apache Zeppelin** — web-based notebook for data ingestion, discovery, and visualization
---
## Arithmetic Expressions in Python 🧮
Here are some examples of evaluating arithmetic expressions:
```python
# Addition ➕
print(3 + 3) # Output: 6
# Subtraction ➖
print(3 - 3) # Output: 0
# Multiplication ✖️
print(3 * 3) # Output: 9
# Division ➗
print(3 / 3) # Output: 1.0
# Multiply then add
print((3 * 4) + 5) # Output: 17
# Convert 200 minutes to hours
print(200 / 60) # Output: 3.3333333333333335
```
---
## Summary of Objectives 📌
* List popular programming languages for Data Science
* Identify commonly used libraries in the field
* Introduce data science tools and ecosystems
* Demonstrate arithmetic expression evaluation in Python
* Provide examples such as converting minutes to hours
---
## Author ✍🏿
**Willie Conway**
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Feel free to reach out if you have questions or want to contribute! Happy Data Science journey! 🎉📈
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