Working with External Data Sources - R Programming For Data Science | Lecture Notes - YNetStudyHub
R Programming For Data Science

Working with External Data Sources

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Techniques for importing and exporting data from external sources such as CSV files, databases, APIs, and web scraping using R.

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Working with External Data Sources – Structured Study Notes 1. Overview External data sources are any repositories that reside outside your primary application or analysis environment. They can be databases, web APIs, cloud storage, flat files, or streaming services. Integrating them allows you to enrich your models, dashboards, or applications with up‑to‑date and domain‑specific information. 2....…

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Unit Syllabus 28 Topics
1
Introduction to R Programming
Data Types and Data Structures in R
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Data Manipulation with dplyr
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Data Visualization with ggplot2
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Working with External Data Sources
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Statistical Analysis with R
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Machine Learning Basics in R
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Text Mining and Natural Language Processing in R
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Time Series Analysis in R
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R Markdown for Reproducible Research
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Introduction to R Programming
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Data Types and Data Structures in R
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Control Structures and Functions in R
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Data Import and Export in R
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Data Wrangling and Cleaning
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Data Visualization with ggplot2
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Statistical Analysis with R
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Machine Learning with R
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Reporting and Presenting Results
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Best Practices and Advanced Topics
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Introduction to R Programming
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Data Manipulation in R
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Data Visualization with ggplot2
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Statistical Analysis in R
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Working with APIs and Web Scraping in R
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Machine Learning Basics in R
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Text Mining and Natural Language Processing in R
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Shiny App Development
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