Compare group_by and group_by_ - R Tutorial

Contents

• Introduction Introduction

  • Welcome

    47s
  • What you should know

    25s
  • Exercise files

    1m 3s
• 1. Getting Started with the tidyverse 1. Getting Started with the tidyverse

  • What is the tidyverse?

    5m 36s
  • Why use the tidyverse?

    3m 45s
  • Strengths of the tidyverse

    6m 50s
  • Set up R and RStudio for the tidyverse

    10m 40s
  • Maintain the tidyverse

    3m 53s
  • Prevent issues with plyr and dplyr

    5m 11s
• 2. Being Tidy with RStudio Projects 2. Being Tidy with RStudio Projects

  • Why should you use projects in RStudio?

    4m 20s
  • Disable auto-saving of RData for reproducibility

    4m 31s
  • Create a new project

    4m 12s
• 3. Introducing the %>% Operator 3. Introducing the %>% Operator

  • What is the %>% operator?

    6m 25s
  • Identify where to use %>%

    4m 55s
  • Signficance of %>%

    6m 45s
  • Alternate options to %>%

    1m 31s
• 4. Importing, Modifying, and Filtering Data 4. Importing, Modifying, and Filtering Data

  • Separate raw and clean data folders

    2m 48s
  • Import .xlsx files with readxl in R

    12m 19s
  • Import .csv files with readr into R

    5m 38s
  • Is it a data frame or a tibble?

    10m 43s
  • Select and filter data

    9m 32s
  • Convert strings to dates with mutate

    6m 40s
  • Separating columns into multiple columns

    6m 36s
  • Filter out NA values

    3m 35s
  • Export .csv files with readr

    5m 6s
  • Export .rdata objects for later

    4m 51s
• 5. Summarizing and Tabulating Data in the tidyverse 5. Summarizing and Tabulating Data in the tidyverse

  • Sample data and cross-validation with dplyr

    4m 8s
  • Categorizing data with group_by

    7m 7s
  • Count members of subgroups within groups with n()

    3m 51s
  • Cumulative sums and more: cumsum, cumall, and cumany

    11m 52s
  • Create group summaries

    7m 26s
  • Remember to ungroup before moving on

    7m 44s
• 6. Wide and Long Data 6. Wide and Long Data

  • Identify if data is wide or long

    5m 45s
  • The benefits of long (or tidy) data

    12m 48s
  • Convert data from wide to long

    7m 46s
  • Convert data from long to wide

    3m 32s
• 7. select(), select_(), !!!, and Non-Standard Evaluation 7. select(), select_(), !!!, and Non-Standard Evaluation

  • Non-standard evaluation and programming with the tidyverse

    8m 45s
  • Compare group_by and group_by_

    4m 39s
  • Tidy evaluation, quo, and !!

    5m 44s
• Conclusion Conclusion

  • Next steps

    30s