3)使用连接函数(full_join/left_join/inner_join),对同一周期的多个数据表做纵向延伸,做横断面研究 4)使用filter函数,做基于条件的纳排处理 5)使用recode_factor函数,对变量取值做映射编码并为因子类型 6)使用mutate函数,做变量设计和衍生 7)使用rename函数,对变量名做重命名 8)使用case_when函数和if_else函数,...
dplyr::filter()函数对上述新产生的变量的数据df,进行筛选。只要符合am=1给提取出来,或者对符合am=1,gear=4条件的输出。 # filterdf=mtcars%>%as.tbl()%>%dplyr::select(mpg,cyl,am,gear)%>%mutate(mpg1=mpg,new=mpg*cyl)df%>%dplyr::filter(am==1)df%>%dplyr::filter(am==1&gear==4) 5.数...
The data.table cheat sheet helps you master the syntax of this R package, and helps you to do data manipulations. Karlijn Willems 2 min tutorial Getting Started with the Tidyverse: Tutorial Start analyzing titanic data with R and the tidyverse: learn how to filter, arrange, summarise, mutate...
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...
dplyr::filter()函数对上述新产生的变量的数据df,进行筛选。只要符合am=1给提取出来,或者对符合am=1,gear=4条件的输出。 代码语言:javascript 复制 # filter df=mtcars%>%as.tbl()%>%dplyr::select(mpg,cyl,am,gear)%>%mutate(mpg1=mpg,new=mpg*cyl)df%>%dplyr::filter(am==1)df%>%dplyr::filter...
# install.packages("pak") pak::pak("tidyverse/dplyr") Cheat Sheet Usage library(dplyr) starwars %>% filter(species == "Droid") #> # A tibble: 6 × 14 #> name height mass hair_color skin_color eye_color birth_year sex gender #> <chr> <int> <dbl> <chr> <chr> <chr> <dbl>...
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(). ...
sample_n(filter(gapminder, continent == "Asia" & lifeExp < 65), 2) ## # A tibble: 2 × 6 ## country continent year lifeExp pop gdpPercap ## <fctr> <fctr> <int> <dbl> <int> <dbl> ## 1 China Asia 1957 50.54896 637408000 575.987 ...
filter(bill_length_mm < 34) %>% select(species, sex, bill_length_mm) ## # A tibble: 3 x 3 ## species sex bill_length_mm ## <fct> <fct> <dbl> ## 1 Adelie female 33.5 ## 2 Adelie female 33.1 ## 3 Adelie female 32.1 ...
Cheat Sheet Usage library(dplyr)starwars%>% filter(species=="Droid")#> # A tibble: 6 x 14#> name height mass hair_color skin_color eye_color birth_year sex gender#> <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr>#> 1 C-3PO 167 75 <NA> gold yellow 112 none mas...