假设你的变量x可以取“a”或“b”的值。现在问这个问题：“is x not equal to a OR is x not ...
(10)寻找男企鹅(公企鹅) 函数filter() 中的逻辑运算符 OperatorMeaning == Equal to > Greater than < Less than >= Greater than or equal to <= Less than or equal to != Not equal to %in% in is.na is a missing value (NA) !is.na is not a missing value & and | or # ---1 pengu...
假设你的变量x可以取“a”或“b”的值。现在问这个问题：“is x not equal to a OR is x not ...
not_canceled <- flights %>% filter(!is.na(dep_delay), !is.na(arr_delay)) not_cancelled %>% count(dest) not_cancelled %>% count(tailnum, wt = distance) # 可以先分组再求每组的长度。 not_cancelled %>% group_by(dest) %>% summarise(n = length(dest)) not_cancelled %>% group_by...
dplyr不再提供all.equal.tbl_df()方法。 coalesce() df_patch (via coalesce) is too picky about types distinct()在处理不存在的变量时候会报错,之前是警告 filter()、mutate()、summarise()提供了更详细的报错信息 当所有列均为逻辑向量时,filter()处理数据框结果通过用&减少它们。意味着我们可以结合across与...
filter(x, TRUE, TRUE)now just returnsx(#1210), it doesn't internally modify the first argument (#971), and it now works with rowwise data (#1099). It once again works with data tables (#906). glimpse()also prints out the number of variables in addition to the number of observation...
Filtering joins, which filter observations from one table based on whether or not they match an observation in the other table:semi_join(),anti_join(). Set operations, which combine the observations in two data sets as if they were set elements:intersect(),union(),setdiff(). ...
##Notrun: if(require(microbenchmark)has_lahman()){ lahman_local-lahman_srcs(df,dt) teams-lapply(lahman_local,function(x)x%%tbl(Teams)) compare_tbls(teams,function(x)x%%filter(yearID==2010)) bench_tbls(teams,function(x)x%%filter(yearID==2010)) #Youcanalsosupplyarbitraryadditionalarguments...
dplyr::filter(iris,Sepal.Length>7) Extractrowsthatmeetlogicalcriteria. dplyr::distinct(iris) Removeduplicaterows. dplyr::sample_frac(iris,0.5,replace=TRUE) Randomlyselectfractionofrows. dplyr::sample_n(iris,10,replace=TRUE) Randomlyselectnrows. ...
dplyr::rename(tb, y = year) Rename the columns of a data frame.tidyr::spread(pollution, size, amount) Spread rows into columns.tidyr::separate(storms, date, c("y", "m", "d")) Separate one column into several.dplyr::filter(iris, Sepal.Length > 7) Extract rows that meet logical...