This repository serves as a hub for various Cheat Sheets related to the field of Data Science (with Python and R). What sets these Cheat Sheets apart is their multidimensional approach to enhancing the learning experience. Each Cheat Sheet is made available in three distinct formats: PDF, Streamlit, and Google Colab.
This threefold approach to guarantee that learners can interact with the content in a manner that aligns with their preferences and learning style.
| Topic | Streamlit | Google Colab | |
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| python |  |
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| numpy | |
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| pandas | |
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| matplotlib | |
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| scikit-learn | |
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| polars | |
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| Topic | Streamlit | Google Colab | |
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| dplyr | |
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| ggplot2 | |
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| forcats | |
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Note: The PDF format cheat sheets included here are authored by other contributors and have been used as sources of inspiration for the content presented.
A cheat sheet is a concise and informative reference guide that provides quick and easy access to essential information or instructions about a specific topic.
It's designed to help individuals quickly understand key concepts, commands, formulas, or procedures without having to search through lengthy documentation or resources. Cheat sheets are often used as handy reference tools for tasks that require familiarity with specific details or steps, such as programming languages, software applications, or academic subjects. They serve as a valuable aid for both beginners and experienced practitioners by condensing important information into a single, easily digestible format.
Streamlit is an open-source Python library that simplifies and accelerates the process of creating interactive web applications for data science and machine learning projects. It allows developers, data scientists, and researchers to transform data scripts into shareable web applications quickly and with minimal effort.
Jupyter Notebook is an open-source web application that provides an interactive and flexible environment for creating, sharing, and executing documents that contain live code, equations, visualizations, and explanatory text. It's widely used by researchers, data scientists, educators, and professionals to develop and present code-based projects, analyses, and reports.
Google Colab, short for Google Colaboratory, is a cloud-based, interactive development environment provided by Google that enables users to write, execute, and share Python code in a collaborative and convenient manner. It's particularly popular among researchers, data scientists, and educators for its ease of use and the fact that it doesn't require any setup or installation.
