The Essentials of Data Science

The Essentials of Data Science

  • The Grammar and Graphics of Data Science58:50

    The Grammar and Graphics of Data Science

    Data science is the process of turning data into understanding and actionable insight. Two key data science tools are data manipulation and visualization.

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  • RStudio IDE Cheat Sheet

    RStudio IDE Cheat Sheet

    No matter what you do with R, the RStudio IDE can help you do it faster. This cheat sheet will guide you through the most useful features of the IDE, as well as the long list of keyboard shortcuts.

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  • What's new with readxl? A Tidyverse solution for reading data stored in xls or xlsx format52:22

    What's new with readxl? A Tidyverse solution for reading data stored in xls or xlsx format

    What's new with readxl? A Tidyverse solution for reading data stored in xls or xlsx format

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  • Introducing blogdown, a new R package to make blogs and websites with R Markdown1:02:43

    Introducing blogdown, a new R package to make blogs and websites with R Markdown

    The most typical use of R Markdown is to create a single output document from a source document, and there is no special organization of the output documents.

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  • Best practices for working with databases48:11

    Best practices for working with databases

    Get the most out of joining R forces with database forces. We will review key concepts, share the latest in R packages, and demo useful techniques.

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  • R-Hub Overview43:53

    R-Hub Overview

    The R-hub builder is an R package build and continuous integration service. It aims to simplify the R package development process: creating a package, building binaries and continuous integration.

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  • Sparklyr: Using Spark with RMarkdown40:56

    Sparklyr: Using Spark with RMarkdown

    RStudio recently announced a new open-source package called sparklyr that facilitates a connection between R and Spark using a full-fledged dplyr backend with support for the entirety of Spark’s MLlib

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  • Introducing bookdown53:41

    Introducing bookdown

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  • Reproducible Reporting58:02

    Reproducible Reporting

    It doesn’t matter how great your analysis is unless you can share it with others – easily. R Markdown and knitr make it easy to intermingle code and text to generate compelling reports and presentatio

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  • Interactive Reporting1:01:07

    Interactive Reporting

    In a static report, you answer known questions. With a dynamic report, you give the reader the tools to answer their own questions.

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  • Shiny Cheat Sheet

    Shiny Cheat Sheet

    This cheat sheet provides a tour of the Shiny package and explains how to build and customize an interactive app.

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  • Data wrangling with R and RStudio55:39

    Data wrangling with R and RStudio

    55:40

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  • Data Transformation Cheat Sheet

    Data Transformation Cheat Sheet

    This cheat sheet will guide you through the grammar, reminding you how to select, filter, arrange, mutate, summarise, group, and join data frames and tibbles.

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  • Getting started with R Markdown1:02:44

    Getting started with R Markdown

    Cut and paste for reporting doesn’t cut it anymore! In this webinar you’ll learn to write reports quickly and effectively with the R Markdown package.

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  • R Markdown Cheat Sheet

    R Markdown Cheat Sheet

    R Markdown is an authoring format that makes it easy to write reusable reports with R.

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  • Working with Big Data in R49:47

    Working with Big Data in R

    R is the go to language for data exploration and development, but what role can R play in production with big data?

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  • Introducing Notebooks50:51

    Introducing Notebooks

    R Markdown Notebooks are a powerful new construct in RStudio combining the strengths of the R Markdown ecosystem with the interactivity and immediacy of a notebook.

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  • Introducing flexdashboards45:59

    Introducing flexdashboards

    Flexdashboard is an easy way to quickly create dashboards, ideal for publishing visualizations with flexible and easy to specify layouts.

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  • Data Visualization Cheat Sheet

    Data Visualization Cheat Sheet

    The ggplot2 package lets you make beautiful and customizable plots of your data.

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  • Getting Data into R44:42

    Getting Data into R

    You can’t use R for data analysis unless you can get your data into R. Getting your data into R can be a major hassle, so in the last few months Hadley Wickham has been working hard to make it easier.

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