cat( "Original Dataframe\n" ) print (df) # Creating an extra variable column # "log_Age" which is log of variable column "Age" # Using mutate() command newDf = mutate(df, log_Age = log(Age)) cat( "After creating extra variable column\n" ) print (newDf) 输出如下: Original Data...
R语言使用Hmisc包的label函数为dataframe中的特定变量(数据列)添加变量标签(variable labels) y <- 'this is a test string of r' y # create a data frame from scratch age <- c(25, 30, 56) …
with abbreviated variable names ¹boxoffice, ²doubanscore, ³duration, ## # ⁴showtime, ⁵director movie_excel = data.frame(movie) #可转为数据框格式 head(movie_excel) ## name boxoffice doubanscore type duration showtime ## 1 叶问3 77060.44 6.4 动作 105 2016/3...
data=data.frame(status=status,monocyte=monocyte,macrophage=macrophage,NK=NK,B=B,T=T)data$Status<-factor(data$status,c('Normal','FL','FH','DH','Tumor'))#ggplot2画图需要宽数据变成长数据 melt.data<-melt(data,variable.name='Cell',value.name='ratio')#配色 colors=c('#F08784','#A3A500...
我想得到dataframe中特定列的平均值,并将这些平均值存储在R中的向量中。 列的特定变量名存储在向量中。对于那些特定的变量(取决于用户输入),我想计算平均值并将其存储在一个向量中,我可以在这个向量上循环,然后在代码的另一部分使用它。 我尝试了以下操作,e.g.: ...
mutate()R语言中的函数用于在 DataFrame 中添加新变量,这些变量是通过对现有变量进行操作而形成的。 用法:mutate(x, expr) 参数: x:数据帧 expr:对变量的操作 范例1: # R program to add new variables# in a data frame# Loading librarylibrary(dplyr)# Create a data framed <- data.frame( name = ...
R语言dataframe数据转换 1 构建数据框df x为factor变量,2010和2011位数值变量 2. 用reshape2::melt将2维数据转换为一维数据 df_melt<-reshape2::melt(df,id.vars="x",variable.name="year",value.name="value") Arguments 经过melt变换之后的df_melt...
Histogram on a categorical variable 基于分类变量的直方图 生成不同种类的频率图 通过调整 width, 你可以调整条形的厚度 1 2 3 4 5 6 7 8 9 library(ggplot2) theme_set(theme_classic()) # Histogram on a Categorical variable g <- ggplot(mpg, aes(manufacturer)) g + geom_bar(aes(fill=class),...
subset() on a categorical variable A better way to do this is to use the subset() function to select the rows where the name column is equal to Dan. Notice that their needs to be a double equals sign, known as a relational operator. # This works, but is not informative nor robust ...
(winequality-white.csv) into R using a dataframe (Note: There is botha red and white wine file, we will use white!). Excluding the quality targetvariable, use hclust to perform a hierarchical clustering of the data with singleas well as complete linkage. You will need to decide on ...