然后,通过group_by函数按照month和id两列分组,并使用summarise函数计算每个组的唯一值计数(count)。 如果你想要查看计数结果,可以使用print(df_count)或者View(df_count)来查看数据框df_count的内容。 关于dplyr的更多详细信息和使用方法,可以参考腾讯云文档中关于dplyr的介绍:dplyr介绍。 请注意,以上回答仅针对dplyr在...
可以对分组后的tibble进行高效的统计操作;并且可以通过?summarise查看有哪些常用的统计函数 mtcars%>%group_by(cyl)%>%#分组统计,再纵向合并分组结果summarise(mean=mean(disp),n=n())# # A tibble:3x3# cyl mean n#<dbl><dbl><int>#14105.11#26183.7#38353.14# n()函数表示每个分类水平的数目,类似于table(...
从文件中读取数据 purrr:(提供好用的编程函数 tibble:data.frame升级款 stringr:处理字符,查找、替换等 forcats:处理因子问题?...:数据整理dplyr包的下述五个函数用法 4.1 筛选: filter 4.2 排列: arrange 4.3 选择: select 4.4 变形: mutate 4.5 汇总: summarise...#key:将原数据框中的所有列赋...
(gear) %>% summarise(across(where(is.numeric), ~ sum(.x, na.rm = TRUE))) %>% mutate("cyl" = "Total") ) %>% arrange( gear ) #> # A tibble: 11 x 3 #> cyl gear n #> <chr> <dbl> <int> #> 1 4 3 1 #> 2 6 3 2 #> 3 8 3 12 #> 4 Total 3 15 #> 5 4...
I am not sure how to satisfy the condition where I can group by the unique Subject value and find its duration, while meeting the Message == "" and Folder == "Outdata" conditions. Any help is appreciated. Thank you Update: I am getting output where the duration val...
dplyr's summarise is specially designed for functions that return a single value. If your function returns multiple/unequal values, you will have to resort to do(). You have to know beforehand about all your functions return value. DT[, list(x[1], y[1]), by = z] ## data.table syn...
Issues listbind_rows .id with NA values in names of list #7100 opened Nov 1, 2024 by muschellij2 dplyr 1.1.4 has two failing tests in Debian Testing #7099 opened Oct 31, 2024 by mr-c Feature request: A function to check if a set of variables form a unique ID in a ...
n_distinctEfficientlycountthenumberofuniquevaluesinavector. Description Thisisafasterandmoreconciseequivalentoflength(unique(x)) Usage n_distinct(x,na_rm=FALSE) Arguments xavectorofvalues na_rmifTRUEmissingvaluesdon’tcount Examples x-sample(1:10,1e5,rep=TRUE) length(unique(x)) n_distinct(x) ...
When you have an env-variable that is a character vector, you need to index into the .data pronoun with [[, like summarise(df, mean = mean(.data[[var]])). The following example uses .data to count the number of unique values in each variable of mtcars: ...
When you have an env-variable that is a character vector, you need to index into the .data pronoun with [[, like summarise(df, mean = mean(.data[[var]])). The following example uses .data to count the number of unique values in each variable of mtcars: ...