data_group <- data %>% # Group data group_by(gr1, gr2) %>% dplyr::summarize(gr_sum = sum(values)) %>% as.data.frame() data_group # Print grouped dataBy executing the previous R code we have created Table 2, i.e. a data frame that has been grouped by two variables....
but my actual data each of the variables have 10+ levels, so the table is very long and hard to read. I would prefer something like this, which I created using: dat1%>%group_by(category)%>%summarize(mean.age1=mean(value[age==1]),mean.age2=mean(value[age==2])) ...
我们可以使用group_modify来完成这个任务。
Sum multiple variables by group [duplicate] Ask Question Asked 9 years, 1 month ago Modified 9 years, 1 month ago Viewed 9k times Part of R Language Collective 2 This question already has answers here: Group by multiple columns and sum other multiple columns (7 answers) Closed ...
The odds ratio (OR) provides a measure of the strength of relationship between two variables, most commonly an exposure and a dichotomous outcome. It is most commonly used in a case control study where it is defined as “the ratio of the odds of being exposed in the group with the outcom...
# load germancredit data data(germancredit) # Example I # binning of two variables in germancredit dataset # using tree method bins2_tree = woebin(germancredit, y="creditability", x=c("credit.amount","housing"), method="tree") bins2_tree ## Not run: # using chimerge method bins2_...
group_by(性别) %>% summarise(是否留过级 = sum(是否留过级)) 看来,留级的学生人数在男女之间有很大的不同,更多的男学生留级。更多没有接受过学前教育的学生留级。这一观察结果表明,性别和学前教育可能对留级有预测作用。 构建二元逻辑回归模型 R默认安装了基础包,其中包括运行GLM的glm函数。glm的参数与lm的参...
group=c(rep("rd1",length(RD1)),rep("rd2",length(RD2))) ) str(df) ## 'data.frame': 22 obs. of 2 variables: ## $ rd : num 2.78 3.23 4.2 4.87 5.12 6.21 7.18 8.05 8.56 9.6 ... ## $ group: chr "rd1" "rd1" "rd1" "rd1" ... ...
# Check that the tibble is grouped by two variables.group_vars(tib_2_gr)# Use the summarize() function once.tib_1_gr=my_t%>%group_by(Col_one, Col_two)%>%summarize(Num_Rows=n())# Check that the new tibble is grouped by only one variable after using summarize().group_vars(tib_...
分组数据可视为特殊的多组数据,区别是:在多组数据中各数值型变量的观测值指向不同的对象,而分组数据是指同一个数值型变量的观测值按另一个变量分成若干子集,这些子集指向同一个变量。 下面通过DAAG中的数据集cuckoos来看一下分组数据的特殊图形描述方法。