X<-data.frame(X1=LETTERS[1:5],X2=1:5)X[2,2]<-NA X[4,1]<-NA (1)去掉含有NA的行,可以选择只根据某一列来去除 drop_na(X) drop_na(X,X1) drop_na(X,X2) (2)替换NA replace_na(X$X2,0) (3)用上一行的值填充NA fill(X,X2) 完整操作:https://www.rstudio.com/resources/cheats...
5. separate_rows 函数:单行拆分成多行 (drink_df<-tibble(drink=c('Chocolate milk','Orange juice'),ingredients=c('milk, chocolate, sugar','oranges, sugar')))# 按逗号分隔符拆分 ingredients 列, 单行变多行drink_df%>%separate_rows(ingredients,sep=',') drink_df 6. replace_na 函数:替代空值...
6 Afghanistan AF AFG 1980 new sp m5564 NA 7 Afghanistan AF AFG 1980 new sp m65 NA 8 Afghanistan AF AFG 1980 new sp f014 NA 9 Afghanistan AF AFG 1980 new sp f1524 NA 10 Afghanistan AF AFG 1980 new sp f2534 NA # ... with 405,430 more rows 所有观测值都需要变换时: anscombe #>...
separate_rows将折叠行展开 unite多列合并为1列 unite 多列合并 library(tidyverse)library(magrittr) iris%>%as_tibble()%>%unite(.,col="Sepal",Sepal.Length:Sepal.Width,sep="|",remove=T,na.rm=F) Sepal Petal.Length Petal.Width Species<chr><dbl><dbl><fct>1 5.1|3.5 1.4 0.2 setosa 2 4.9...
#...with140more rows 读取其他格式数据: readxl:readxls(); readxlsx(); haven:打开SAS 、SPSS、Stata等外部数据。 02 — tibble:高级数据框(data.frame升级版) ——数据(列)类型一目了然 tibble是R语言中一个用来替换data.frame类型的扩展的数据框,tibble继承了data.frame,是弱类型的,同时与data.frame有...
with 40 more rows Loading tidySummarizedExperiment will automatically abstract this object as tibble, so we can display it and manipulate it with tidy tools. Although it looks different, and more tools (tidyverse) are available to us, this object is in fact a SummarizedExperiment object. class(...
lambda is a matrix whose rows are distributions of topics over tokens, or P(topic|token) lambda is useful for making predictions with a computationally-simple and efficient dot product and it may be interesting to analyze in its own right. alpha is the prior that tunes theta eta is the pri...
# ... with 22 more rows 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 1.3 选择: select() 用列名作参数来选择子数据集: select(mtcars_df, disp:wt) # A tibble: 32 x 4 disp hp drat wt * <dbl> <dbl> <dbl> <dbl> ...
11. Extract rows from the first table which are not matched in the second table Same way you can remove row information’s from the data frame while using anti_join function flights %>% anti_join(airways_beginning_with_a, by = "carrier") ...
因此我们需要更有效的代码、更容易记住语法和易于阅读的语法。而tidyr正是一个这样的包，它的唯一目的是...