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Coursera_Exercise_DataScience
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## Where I store my assignments... |
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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"# Data Science Tools and Ecosystem" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Author\n", | |
"Stefano Raneri" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"In this notebook, Data Science Tools and Ecosystem are summarized." | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"**Objectives:**\n", | |
"\n", | |
"- List popular languages for Data Science\n", | |
"\n", | |
"- List commonly used libraries for Data Science\n", | |
"\n", | |
"- List Data Science tools in a table\n", | |
"\n", | |
"- Demonstrate some arithmetic expressions such as minute to hours conversion.\n" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Some of the popular languages that Data Scientists use are:\n", | |
"\n", | |
"1. Python\n", | |
"2. R\n", | |
"3. SQL\n", | |
"4. Julia\n", | |
"5. Java\n", | |
"6. MATLAB\n", | |
"7. Scala" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Some of the commonly used libraries used by Data Scientists include:\n", | |
"\n", | |
"1. NumPy\n", | |
"2. Pandas\n", | |
"3. Matplotlib\n", | |
"4. Seaborn\n", | |
"5. Scikit-learn\n", | |
"6. TensorFlow\n", | |
"7. Keras\n", | |
"8. PyTorch\n", | |
"9. SciPy\n", | |
"10. NLTK" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Data Science Tools\n", | |
"\n", | |
"| Tools |\n", | |
"|---------------------|\n", | |
"| Jupyter Notebook |\n", | |
"| RStudio |\n", | |
"| Spyder |" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"### Below are a few examples of evaluating arithmetic expressions in Python" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 7, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"17" | |
] | |
}, | |
"execution_count": 7, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"# This a simple arithmetic expression to mutiply then add integers\n", | |
"(3*4)+5" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 8, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"3.3333333333333335" | |
] | |
}, | |
"execution_count": 8, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"# This will convert 200 minutes to hours by diving by 60\n", | |
"200/60" | |
] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 3", | |
"language": "python", | |
"name": "python3" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.11.9" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 2 | |
} |
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