Example 1: Replace Character or Numeric Values in Data Frame Let’s first replicate our original data in a new data object: data1<-data# Replicate data Now, let’s assume that we want to change every character value “A” to the character string “XXX”. Then we can apply the following...
data_new2 <- data # Duplicate data frame data_new2[col_repl] <- sapply(data_new2[col_repl], # Replace values in certain columns function(x) replace(x, x %in% val_repl, 99)) data_new2 # Print updated data frameBy running the previous R syntax, we have created Table 3, i.e. ...
values: 替换值45 对缺失值NA的处理 1、直接删除 直接采用函数na.omit()来去掉带有NA的行,也可以使用tidyr包的drop_na()函数来指定去除哪一列的NA ,drop_na(df,X1) # 去除X1列的NA 2 填充法 用其他数值填充数据框中的缺失值NA。 2.1 df[is.na(df)] #df[is.na(df)] = 0 2.2 replace_na() ...
To replace zero with previous value in an R data frame column, we can use na.locf function of zoo package but to apply this we first need to replace the zero values with NA. For example, if we have a data frame called df that contains a column say Rate then we can use the below...
Returns a data frame containing the matrix of the correlation coefficients. The output has an attribute named “pvalue”, which contains the matrix of the correlation test p-values. cor_get_pval(): extract a correlation matrix p-values from an object of class cor_mat(). cor_pmat(): ...
(position=position_jitterdodge(), # jitter for h-dist, dodge for grouped dists pch=21, #圆形 alpha=0.4) + # transparency scale_x_discrete(limits=c("E8.5","E9.5","E10.5","E11.5")) + scale_fill_manual(values=c('#f2a340','#998fc2')) + # custom colors in hex code my_theme(...
2 修改列中元素函数:str_replace/recode/mapvalues # str_replace替换列中单个元素 stringr::str_replace(df$conference, "West", "Western") ## [1] "Western" "Western" "East" "East" stringr::str_replace(df$team, "team_", "") ## [1] "A" "B" "C" "D" # str_replace_all替换列...
mydata<-data.frame(A=runif(20,0,100),B=sample(LETTERS[1:5],20,replace=TRUE)) mydata[sample(1:20,5,replace=FALSE),"A"]<-NA #认为构造了5个缺失值。 #unique函数通常用于去重: unique(mydata$B) #对含有重复值得向量进行去重 dplyr::distinct(mydata,B) #对含有重复值字段的数据框去重 ...
> d <-data.frame(matrix(sample(c(NA,1:4),12, replace = TRUE),4))>d X1 X2 X31NA41212NA31424NA NA4 1,把变量的缺失值替换为默认值 替换数据框中变量X1的缺失值,使用within()函数,不会修改数据框的数据,需要把函数返回的结果重新赋值给d对象: ...
函数replace()用于把向量中指定位置的元素替换为指定的值(或向量): replace(x, list, values) 参数注释: list:整数向量,指定被替换的元素的位置 values:替换的值(或向量) 例如,把向量的第1个、第3个和第7个的元素值替换为0: > replace(1:9,c(1,3,7),0) ...