summarise(across(height:mass, ~ mean(.x, na.rm =TRUE)))#> # A tibble: 1 × 2#> height mass#> <dbl> <dbl>#> 1 174. 97.3# The _if() variants apply a predicate function (a function that# returns TRUE or FALSE) to determine the relevant subset of# columns. Here we apply mean...
假设数据以 tibble 格式保存。数据集如果用于统计与绘图，需要满足一定的格式要求，(Wickham, 2014) 称之...
library(tidyverse) # Original original_output <- my_df %>% group_by(group_id) %>% summarize( some_date = ifelse( all(is.na(some_date)), NA, last(some_date[!is.na(some_date)], default = NA))) # Proposed new_output <- my_df %>% summarise( .by = group_id, last_date =...
flight <int>, tailnum <chr>, origin <chr>, dest <chr>, ## # air_time <dbl>, distance <dbl>, hour <dbl>, minute <dbl>, time_hour <dttm> delay <- summarise(by_tailnum, count = n(),#计算航班的数量 dist = mean(distance, na.rm = TRUE),#计算平均距离 delay = mean(arr...
<- df %>% summarise_all(~ any(. > 2 & . < 5)) %>% # 计算每列是否满足条件 filter_all(~ !is.na(.)) %>% # 过滤掉不满足条件的列(即 NA 值) select_if(~ .) %>% # 选择满足条件的列 colnames() %>% # 获取列名 df[.] # 根据列名选择列 # 打印结果 print(selected_colu...
select()Selecting columns (variables)SELECT filter()Filter (subset) rows.WHERE group_by()Group the dataGROUP BY summarise()Summarise (or aggregate) data- arrange()Sort the dataORDER BY join()Joining data frames (tables)JOIN mutate()Creating New VariablesCOLUMN ALIAS ...
Currently summarise_at/summarise_if/summarize_at/summarize_if can only be used once, on a single selection of column variables. It's easy to conceive cases when one might want to, e.g. group by date, and summarise mean values for all numeric columns, but the first value for character ...
across()可以轻松地将相同的转换应用于多个列,允许您在 "data-masking" 函数(如summarise()和mutate())中使用select()语义。有关更多详细信息,请参阅vignette("colwise")。 if_any()和if_all()对选定的列应用相同的谓词函数,并将结果合并到单个逻辑向量中:当任何选定列的谓词为TRUE时,if_any()为TRUE;当所有...
summarise()、summarise_at()、summarise_all()、summarise_if() count() groupby()、ungroup()、groups()、group_vars() dplyr包中的相关函数 library(tidyverse) setwd("E:/R/tidyverse/pre") LST <- read.csv("LST.csv") # NAME 春季 夏季 秋季 冬季 ...
Example 1: Sums of Columns Using dplyr Package In this Example, I’ll explain how to use the replace,is.na, summarise_all, andsumfunctions. You can see the colSums in the previous output: The column sum of x1 is 15, the column sum of x2 is 7, the column sum of x3 is 35, and...