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pull(): Extract column values as a vector. Select(): Extract one or multiple columns as a data table. Select_if(): Select columns based on a particular condition. Helper functions — starts_with(), ends_with(), contains(), matches(), one_of(): Select columns/variables based on their names.
Subset using brackets by extracting the rows and columns we want. Subset using brackets by omitting the rows and columns we don't want. Subset using brackets in combination with the which() function and the in operator. Subset using the subset() function.
Suggested clip R — How to extract a single column from a data. Frame as a data. Frame YouTubeStart of suggested client of suggested clip R — How to extract a single column from a data. Frame as a data. Frame
Suggested clip R — How to extract a single column from a data. Frame as a data. Frame YouTubeStart of suggested client of suggested clip R — How to extract a single column from a data. Frame as a data. Frame
0:47 5:04 Suggested clip Export Data from R (CSV, TXT and other formats) | R Tutorial 1.6 YouTubeStart of suggested client of suggested clip Export Data from R (CSV, TXT and other formats) | R Tutorial 1.6
0:34 7:12 Suggested clip R tutorial — Learn How to Subset, Extend & Sort Data Frames in R YouTubeStart of suggested client of suggested clip R tutorial — Learn How to Subset, Extend & Sort Data Frames in R
Subset using brackets by extracting the rows and columns we want. Subset using brackets by omitting the rows and columns we don't want. Subset using brackets in combination with the which() function and the in operator. Subset using the subset() function.
Subletting Data. R has powerful indexing features for accessing object elements. These features can be used to select and exclude variables and observations. The following code snippets demonstrate ways to keep or delete variables and observations and to take random samples from a dataset.

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