iris %>%select(last_col()) %>% head()# 最后一个变量 iris %>%select(last_col(offset =2)) %>% head()# 倒数第3个变量 iris %>%select(one_of(c("Petal.Length","Petal.Width"))) %>% head() iris %>% group_by(Species) %>%select(group_cols()) %>% distinct() %>% head()#...
> threshold表示对每一列的值进行条件判断,判断是否大于阈值。rowSums()函数用于计算每一行中满足条件的列数,并将结果存储在新的变量condition_count中。 最后,可以查看计算结果。 代码语言:txt 复制 # 查看计算结果 print(data$condition_count) 上述代码将打印出每一行中符合条件的列数。
library(dplyr) # 加载数据集 data <- read.csv("data.csv") # 应用dplyr函数 data_processed <- data %>% select(all_of(names(.))) %>% filter(condition) %>% arrange(column) %>% mutate(new_variable = expression) %>% summarize(summary_statistic) %>% join(another_data, by = "common_...
The true= and false= legs of if_else will be recycled to the length of the condition argument but condition will not be recycled to the length of true and false. Also recycling means making longer. ... G. Grothendieck 266k answeredSep 21 at 17:46 ...
2 Summing rows on certain conditions in R 2 Conditionally, sum column based on two other column values 2 Sum across rows but only the cells that meet a condition 0 Conditional rowwise sum of subset of columns in specific row dplyr 3 Sum all rows wherever cell value meets cond...
keep rows matching criteria # base R approach to view all flights on January 1flights[flights$Month==1&flights$DayofMonth==1,]# dplyr approach# note: you can use comma or ampersand to represent AND conditionfilter(flights,Month==1,DayofMonth==1)# use pipe for OR conditionfilter(flights,...
dplyris based on the idea that when working with data there are a number of common activities one will pursue: reading, filtering rows on some condition, selecting or excluding columns, arranging/sorting, grouping, summarize, merging/joining, and mutating/transforming columns. There are other activ...
The SQL generation set operations (intersect(),setdiff(),union(), andunion_all()) on databases has been considerably improved. By default, the component SELECT are surrounded with parentheses, except on SQLite. The SQLite backend will now throw an error if you attempt a set operation on a ...
filter(tbl/data.fram, condition) and output a data.frame, filter rows/observation ```{r filter in dplyr} # Load dplyr package in a safer way if(!suppressWarnings(require(dplyr))) { install.packages('dplyr') require(dplyr) } df <- data.frame( ...
So that’s howfilter()works. It’s checking logical conditions. If the logical condition or conditions are not met, then the row is filtered out. Example: city equal Austin OR city equals Houston Let’s try another example. Here, we’ll keep rows wherecityequals Austinorcityequals Houston...