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Keep rows that match a condition — filter • dplyr - tidyverse
https://dplyr.tidyverse.org/reference/filter.html
WEBThe filter() function is used to subset a data frame, retaining all rows that satisfy your conditions. To be retained, the row must produce a value of TRUE for all conditions. Note that when a condition evaluates to NA the row will be dropped, unlike base subsetting with [. Usage. filter(.data, ..., .by = NULL, .preserve = FALSE) Arguments.
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dplyr filter(): Filter/Select Rows based on conditions
https://cmdlinetips.com/2020/08/dplyr-filter-filter-select-rows-based-on-conditions/
WEBAnd in this tidyverse tutorial, we will learn how to use dplyr’s filter () function to select or filter rows from a data frame with multiple examples. First, we will start with how to select rows of a dataframe based on a value of a single column or variable.
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Filtering Data in R 10 Tips -tidyverse package | R-bloggers
https://www.r-bloggers.com/2021/05/filtering-data-in-r-10-tips-tidyverse-package/
WEBMay 17, 2021 · In this tutorial, you will learn the filter R functions from the tidyverse package. The main idea is to showcase different ways of filtering from the data set. Filtering data is one of the common tasks in the data analysis process. When you want to remove or extract a part of the data use tidyverse package ’filter ()’ function.
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A Grammar of Data Manipulation • dplyr - tidyverse
https://dplyr.tidyverse.org/
WEBOverview. dplyr is a grammar of data manipulation, providing a consistent set of verbs that help you solve the most common data manipulation challenges: select() picks variables based on their names. filter() picks cases based on their values. summarise() reduces multiple values down to a single summary.
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Filter within a selection of variables — filter_all • dplyr - tidyverse
https://dplyr.tidyverse.org/reference/filter_all.html
WEBFilter within a selection of variables. Source: R/colwise-filter.R. Scoped verbs ( _if, _at, _all) have been superseded by the use of if_all() or if_any() in an existing verb. See vignette("colwise") for details. These scoped filtering verbs apply a predicate expression to a selection of variables.
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How to Filter in R: A Detailed Introduction to the dplyr Filter
https://www.r-bloggers.com/2019/04/how-to-filter-in-r-a-detailed-introduction-to-the-dplyr-filter-function/
WEBfilter () selects rows based on their values. mutate () creates new variables. select () picks columns by name. summarise () calculates summary statistics. arrange () sorts the rows. The beauty of dplyr is that the syntax of all of these functions is very similar, and they all work together nicely.
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A Quick and Dirty Guide to the Dplyr Filter Function
https://www.sharpsightlabs.com/blog/dplyr-filter/
WEBJul 4, 2018 · filter() will keep any row where city == 'Austin' or city == 'Houston'. All of the other rows will be filtered out. Filtering using the %in% operator. Let’s say that you want to filter your data so that it’s in one of three values. For example, let’s filter the data so the returned rows are for Austin, Houston, or Dallas.
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filter: Keep rows that match a condition in tidyverse/dplyr: A …
https://rdrr.io/github/tidyverse/dplyr/man/filter.html
WEBFeb 13, 2024 · Description. The filter() function is used to subset a data frame, retaining all rows that satisfy your conditions. To be retained, the row must produce a value of TRUE for all conditions. Note that when a condition evaluates to NA the row will be dropped, unlike base subsetting with [ . Usage. filter(.data, ..., .by = NULL, .preserve = FALSE)
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5 Manipulating data with dplyr | Introduction to R - tidyverse
https://bookdown.org/ansellbr/WEHI_tidyR_course_book/manipulating-data-with-dplyr.html
WEBManipulating data with dplyr. The dplyr package, part of the tidyverse, is designed to make manipulating and transforming data as simple and intuitive as possible. A guiding principle for tidyverse packages (and RStudio), is to minimize the number of keystrokes and characters required to get the results you want.
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dplyr: select, filter, mutate - GitHub Pages
https://nuitrcs.github.io/r-tidyverse/html/dplyr1.html
WEBdplyr is at the core of the tidyverse. It is for working with data frames. It contains six main functions, each a verb, of actions you frequently take with a data frame. We’re covering 3 of those functions today (select, filter, mutate), and 3 more next session (group_by, summarize, arrange).
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