Datasets in R: Selecting, Filtering, Ordering, & Grouping Data

R Programming 4.0+    |    Intermediate
  • 12 Videos | 1h 34m 30s
  • Includes Assessment
  • Earns a Badge
Data analysis often requires performing a series of complex transformations. R makes this hassle-free via the forward pipe operator for chaining operations, data selection and filtering based on conditional operations, and grouping and aggregating options to compute summaries. Learn how to carry out all these operations in this course. Task you'll carry out include using logical and relational operators to perform conditional filtering, sampling records at random, and computing the top N records based on values in a variable. You'll also learn to use the forward pipe operator in the magrittr package and tibbles, the next-generation data frame, to store and transform your data. You'll round this course off by performing ordering, grouping, and aggregations on your data. When you're finished, you'll have a solid grasp of complex operations on data frames and be able to apply these concepts using the R programming language.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    edit data frame columns to be of the right data type
    select variables from data frames
    filter data using relational operators
    use the select() function and chaining to filter data in tibbles
    use the %>% operator and the filter() function to filter tibbles
  • sample rows using sample() and select top N rows using top_n()
    change columns to be of their logically correct data type
    use the order() and arrange() functions to sort data frames
    create crosstabs and view the aggregate statistics of data frames
    view aggregate statistics of tibbles with summarize() and group_by()
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    2m 5s
    UP NEXT
  • Playable
    2. 
    Formatting Columns to Have the Right Data Type
    7m 6s
  • Locked
    3. 
    Selecting Specific Rows and Columns
    6m 22s
    FREE ACCESS
  • Locked
    4. 
    Filtering Operations on Data Frame Rows
    10m 49s
    FREE ACCESS
  • Locked
    5. 
    Selecting and Filtering Using Packages in tidyverse
    10m 27s
    FREE ACCESS
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    6. 
    Using the dplyr filter() Function
    8m 19s
    FREE ACCESS
  • Locked
    7. 
    Retrieving Samples and Top N Results
    7m 17s
    FREE ACCESS
  • Locked
    8. 
    Specifying the Correct Data Types for Columns
    7m 17s
    FREE ACCESS
  • Locked
    9. 
    Sorting Using Order and Arrange
    9m 21s
    FREE ACCESS
  • Locked
    10. 
    Grouping and Aggregations on Data Frames
    12m 8s
    FREE ACCESS
  • Locked
    11. 
    Grouping and Aggregation Using dplyr
    11m 21s
    FREE ACCESS
  • Locked
    12. 
    Course Summary
    1m 59s
    FREE ACCESS

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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