How can I represent one column's values using multiple columns in R where one new column is conditional? Looking at similar questions, I could not find one that matched my need. If one does contain a solution, please share its link. I have this dput-produced data: structur...
mutate( ) 为数据增加新列 mutate(df,vnew1=v1-v2,vnew2=vnew1+v3) 与基础包里的transform()函数接近,但mutate可以使用你刚刚创建的column...group_by和summarise的结合实现了对数据集分组分析,并进行统计量计算的一个功能。...官网上面有关于data.table包对于dplyr的提升和改进: ?...(sum_v1=sum(v...
I am trying to figure (with dplyr) how to summarise just one level of a grouping variable keeping all the rest the same. For example: library(dplyr)dat<-starwars%>%select(height,hair_color)%>%filter(!is.na(hair_color))dat%>%group_by(hair_color)%>%summarise(mean_height=mean(height))...
adds/updates DT1's column col with mul from DT2 on those rows where DT2's key column matches DT1. I don't think there is an exact equivalent of this operation in dplyr, i.e., without avoiding a *_join operation, which would have to copy the entire DT1 just to add ...
statedf %>% group_by(report_date,regvec) %>% summarize(tot=sum(value)) -> totals # Do a spot check on the totals - compare this to the original data frame # totals. There are differences in the column names but other than it's the ...
matches(x, ignore.case = TRUE) # column/variable matches regular expression x num_range("x", 1:5, width = 2) # column/variable from x01 to x05 one_of("x", "y", "z") # column/variable contains in x, y, z everything() # all column/variable ...
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group_by(year) %>% summarise(record_count = n()) By summarizing the data byyear, we can look specifically at the number of records for the year2001. We’re doing this to check that our filter operation worked correctly. This summary table shows that there is 522 records for the year20...
. But is it? Not at all: we just need to add one line and a bang-bang ( !!): starwars_mean <- function(var) { var <- enquo(var) starwars %>% group_by(!!var) %>% summarise(mean_height = mean(height, na.rm = TRUE), mean_mass = mean(mass, na.rm = TRUE), count = ...
Allprint()method methods invisibly return their input so you can interleaveprint()statements into a pipeline to see interim results. If you’ve managed to produce a 0-row data frame, dplyr won’t try to print the data, but will tell you the column names and types: ...