我首先通过使用 group-by 和 mutate 计算组内的 ID 来计算每月总和。但是,当我尝试使用 cumsum 按组计算每月累计总和时,数据看起来不正确。如果有人能帮助我,那将非常有帮助。谢谢~ 假设原始数据框如下所示: 人员编号公司yyyy月 1 A 2011 一月 2 A 2011 一月 3 A 2011 二月 4 A 2011 二月 5 A 2011 ...
#6)Countsandproportions of logical values sum(x >10) , mean(y ==0) not_cancelled %>% group_by(year,month,day) %>% summarize(n_early = sum(dep_time <500)) not_cancelled %>% group_by(year,month,day) %>% summarize(hour_perc = mean(arr_delay >60)) #12多变量分组操作 daily <...
group_by(group) %>% mutate(cumulative_sum = cumsum(value)) df 上述代码中,首先加载dplyr包,然后创建一个示例的data.frame df。接下来,使用group_by()函数按照group列对df进行分组。然后,使用mutate()函数创建一个新的列cumulative_sum,并使用cumsum()函数计算每个组的累积和。最后,通过使用%>%运算...
cumulative_cap <- ppa_price_long %>% group_by(region) %>% summarise(cumulative_capacity = round(sum(capacity_mw))) %>% mutate(capacity_label = prettyNum(cumulative_capacity, big.mark = ",")) p3 <- ggplot(cumulative_cap, aes(x="", y=cumulative_capacity, fill=region))+ geom_bar(...
x)) { cumulative_sum_squared[i] <- sum(x[1:i])^2 } # 打印结果 print(cumulative_sum_...
RCUMSUM cumulative sum of elements, restarted after every zero. For vectors, RCUMSUM(X) is a vector containing the cumulative sum of the elements of X, with the summation restarting after a zero is encountered. For matrices, RCUMSUM(X) is a matrix the same size as X containing the ...
# Color by group (dose) e + geom_boxplot(aes(color = dose))+ scale_color_manual(values = c("#00AFBB", "#E7B800", "#FC4E07")) # Change fill color by group (dose) e + geom_boxplot(aes(fill = dose)) + scale_fill_manual(values = c("#00AFBB", "#E7B800", "#FC4E07...
relative cumulative f relative current relativedensity relative density of s relative diffusion co relative divergence relative divergence o relative eddy relative ellipse area relative entropy func relative equivalent relative erosion rati relative error relative evaporation relative evaporation relative failure...
1)Cumulative incidence plot,,其中。 结论:图上两条cumulative incidence curve相交-->PH假设不满足,PH假设不满足-\->图上两条cumulative incidence curve相交,即图上两条cumulative incidence curve相交是PH假设不满足的充分非必要条件。 说明:这里为什么不是,而是,这主要是与我们分析临床研究数据时的习惯相匹配,我们...
我创建的函数修改了数据集中的一些列。我希望应用于这两列的修改可以延续到pmap的第二次迭代和后续迭代。>% group_by(groupvar) %>% mutate(cumulative_sum=cumsum(newcol)) dataset$limited_cumulative_sum <- ifelsemutate(limited_cumulativ 浏览12提问于2020-02-24得票数 0 回答已采纳...