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July 20, 2024 04:21
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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"<center>\n", | |
" <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DS0105EN-SkillsNetwork/labs/Module2/images/SN_web_lightmode.png\" width=\"300\" alt=\"cognitiveclass.ai logo\">\n", | |
"</center>\n" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"#### Add your code below following the instructions given in the course\n" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"# Data Science Tools and Ecosystem" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"In this notebook, Data Science Tools and Ecosystem are summarized." | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Some of the popular languages that Data Scientists use are:\n", | |
"- Python\n", | |
"- R\n", | |
"- Scala" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Some of the commonly used libraries used by Data Scientists include:\n", | |
"- Pandas\n", | |
"- SciPy\n", | |
"- Matplotlib" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"tags": [] | |
}, | |
"source": [ | |
"## Data Science Tools\n", | |
"\n", | |
"| Tool name | \n", | |
"|-----------|\n", | |
"| Jupyter Notebooks |\n", | |
"| Google Colab |\n", | |
"| Pandas" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"### Below are a few examples of evaluating arithmetic expressions in Python" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": { | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"17.0" | |
] | |
}, | |
"execution_count": 1, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"(3*4)+5." | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"This will convert 200 minutes to hours by diving by 60." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"metadata": { | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"3.3333333333333335" | |
] | |
}, | |
"execution_count": 2, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"200/60" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Objectives:\n", | |
"- List popular languages for Data Science\n", | |
"- List common libraries for Data Science\n" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"metadata": {}, | |
"outputs": [], | |
"source": [] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python", | |
"language": "python", | |
"name": "conda-env-python-py" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.7.12" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 4 | |
} |
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