WebJan 4, 2024 · If you’re not really familiar with it, dplyr is a data manipulation package for R. Moreover, dplyr is one of the modules of the so-called “Tidyverse.”. The Tidyverse is a … WebOct 6, 2024 · cur_svy_wts: Get the full-sample weights for the current context; dplyr_filter_joins: Filtering joins from dplyr; dplyr_single: Single table verbs from dplyr and tidyr; get_var_est: Get the variance estimates for a survey estimate; group_by: Group a (survey) dataset by one or more variables. group_map_dfr: Apply a function to each group
R: Information about the "current" group or variable
WebMar 27, 2024 · cur_group () gives the group keys, a tibble with one row and one column for each grouping variable. cur_group_id () gives a unique numeric identifier for the current group. cur_group_rows () gives the row indices for the current group. cur_column () gives the name of the current column (in across () only). WebCannot retrieve contributors at this time. #' Turns implicit missing values into explicit missing values. This is a wrapper. #' completing missing combinations of data. #' With grouped data frames, `complete ()` operates _within_ each group. Because. #' of this, you cannot complete a grouping column. #' use instead of `NA` for missing combinations. gitpac international
Information about the "current" group or variable — …
Web這是一種方法,我最初為集合添加一個組標識符(我假設你在實際集合中有這個),然后在制作一個更長的類型數據集之后,我按這個id分組,標識符有最大的價值。 然后,我在初始 df 和這組具有 largest_value word、summarize 和 rename 的鍵行之間使用內部連接。 WebApr 10, 2024 · mara April 13, 2024, 6:40am #3 This may look a little funky because I, too, had to create your data by splitting things up, since it wasn't in copy-pasteable format. If each race is at a unique datetime, you can use that datetime to group_by () and then get the group index using cur_group_id (). WebMar 19, 2024 · this should come very close to what you are looking for. only the order of indices within groups is not as in your desired outcome. guess it requires some finetuning with sort or factor levels. dat %>% group_by (year, site, crop) %>% group_map (~mutate (.,index=group_indices (.,trt))) #> # A tibble: 12 x 6 #> # Groups: year, site, crop [3 ... furniture mecca warehouse