我想使用rename_ (还是rename?)在函数中重命名一列。例如,假设下面的函数中有rename(as_tibble(iris),petal = Petal.Width)` rr <- function(toRename, newName, dt) { rename_(dt, .dots = rlang::expr(list(!! newName = toRename))) } 在其中,我可以传递一个数据集来重命名,以及将重...
continent_year_index <- which(gapminder["continent"] == "Americas" & gapminder["year"] == 2007) # pull only those rows and show the country and life expectency columns gapminder[continent_year_index, c("country", "lifeExp")] select:选择列 gapminder %>% select(country, gdpPercap) 同样...
library(dplyr) # 创建一个包含列名的向量 columns <- c("column1", "column2", "column3") # 创建一个空的数据框 df <- data.frame() # 使用for循环遍历列名向量 for (col in columns) { # 使用!!和:=运算符创建或修改列 df <- df %>% mutate(!!col := 0) } # 打印结果 print(df) ...
.before = 1 #新变量将会出现在表格的最左边 .after = columns_name #将会出现在指定变量名字的后面 .keep = 'used' #只保留在mutate中进行处理的以及计算得到的变量的列 #例如——— flights |> mutate( gain = dep_delay - arr_delay, speed = distance / air_time * 60, .before = 1 ) #> #...
Error in rename(., age = Characteristics..age., genotype = Characteristics..genotype.) : object 'Characteristics..age.' not foundWhich doesn't make sense since columns exist in the data frame:pData(raw_data)$Characteristics..genotype.
select columns/variable by name/match rules ```{r select function in dplyr} # Load dplyr package in a safer way if(!suppressWarnings(require(dplyr))) { install.packages('dplyr') require(dplyr) } df <- data.frame( color = c("blue", "black", "blue", "blue", "black"), ...
By creating a shallow copy using shallow(), we understand that you don't want to modify the original object. We take care of everything internally to ensure that while also ensuring to copy columns you modify only when it is absolutely necessary. When implemented, this should settle the refe...
dplyr: A grammar of data manipulation. Contribute to tidyverse/dplyr development by creating an account on GitHub.
Whencolumn-binding,rowsarematchedbyposition,notvaluesoalldata framesmusthavethesamenumberofrows.Tomatchbyvalue,notposition, seeleft_joinetc.Whenrow-binding,columnsarematchedbyname,andany valuesthatdon’tmatchwillbefilledwithNA. Value bind_rowsandbind_colsalwaysreturnatbl_df Deprecatedfunctions rbind_list...
rename()修改列名 mutate()创建新列 relocate()修改列顺序 行聚合 summarise()根据运算方式聚合为一行 Pipe - 管道操作 所有的dplyr与plydata函数均取data frame为第一个参数,所以与之每个函数中放入data frame,管道操作提供了一个数据处理的流水线,通过%>%和>>符号实现。