# Select all but one column (e.g., listing_id) airbnb_listings %>% select(-listing_id) # Select all columns within a range airbnb_listings %>% select(country : year_listed) # Reorder columns using relocate() airbnb_listings %>% relocate(city, country) # Rename a column using renam...
在我看来，在利用dplyr时，实现这一点的最简化和最通用的方法是使用dplyr::select_if，但要比@wjchulme建议的方法更直接（尽管这是一个不错的技巧）：dplyr
select(df, V4:V6) select(df, num_range("V", 4:6)) # Drop variables select(iris, -starts_with("Petal")) select(iris, -ends_with("Width")) select(iris, -contains("etal")) select(iris, -matches(".t.")) select(iris, -Petal.Length, -Petal.Width) # Rename variables: # * sele...
fst数据处理的函数后缀位:_fst,这里select_fst函数用于选择列。 sys_time_print({ ft %>% select_fst(Logical) %>% count_dt(Logical) -> res }) res slice_fst:用于选择行操作。然后分组求和 sys_time_print({ ft %>% slice_fst(1:1000) ...
dplyr_data-wrangling-cheatsheet(R语言 dplyr 学习神器)
In this chapter, you'll revisit dplyr pipelines and enhance your column selection skills with helper functions and regular expressions. Ver detalhes Be fruitful and dplyr 50XP select() vs. filter() 50XP A great selection 100XP Mutation necessary ...
dplyr: A grammar of data manipulation. Contribute to tidyverse/dplyr development by creating an account on GitHub.
11 slice_fst:选择行;select_fst:选择列;filter_fst按照行过滤 这几个函数其实就是来处理fst格式的,会进一步缩短时间。大数据必备。 ## Not run: fst::write_fst(iris,"iris_test.fst") # parse the file but not reading it parse_fst("iris_test.fst") -> ft # ft class(ft) lapply(ft,class) ...
tibble::rownames_to_column('CarName') %>% select_se(c('CarName', 'cyl', 'gear', 'hp', 'wt')) %>% add_group_indices(groupingVars = groupingVars, indexColumn = 'groupID') %>% add_group_sub_indices(groupingVars = groupingVars, ...
New pull() generic for extracting a single column either by name or position (either from the left or the right). Thanks to @paulponcet for the idea (#2054). This verb is powered with the new select_var() internal helper, which is exported as well. It is like select_vars() but re...