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Group and ungroup — group_by.dtplyr_step • dtplyr - Tidyverse
Web3 mrt. 2015 · you can use: df %>% filter (!is.na (a)) to remove the NA in column a. Share Improve this answer Follow edited Aug 8, 2024 at 21:25 Petter Friberg 21.1k 9 60 107 … Web1 uur geleden · What I want to know is for a given time period (say > 250 in this example), how many measurements are above or below a given quantile value for a group over the entire data set. E.g., the 10th, 50th, and 90th quantiles calculated using the entire data set. greyhound chicago illinois
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WebThese are methods for dplyr's group_by () and ungroup () generics. Grouping is translated to the either keyby and by argument of [.data.table depending on the value of the arrange argument. Usage # S3 method for dtplyr_step group_by (.data, ..., .add = FALSE, arrange = TRUE) # S3 method for dtplyr_step ungroup (x, ...) Arguments .data A lazy_dt () Web27 mrt. 2024 · 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) Arguments Web2 feb. 2024 · In case you missed it, across () lets you conveniently express a set of actions to be performed across a tidy selection of columns. across () is very useful within summarise () and mutate (), but it’s hard to use it with filter () because it is not clear how the results would be combined into one logical vector. fidgets that start with l