首页 > 解决方案 > n 个不同的最高/最低值的最小值、最大值、平均值,并将它们与时间序列数据一起绘制在 R 中的同一图表上

问题描述

我正在处理一个带有 unix 时间戳的大型时间序列数据集(有近 10 万条记录)。我需要min, mean, max, avg_of_lowest_n, avg_of_top_nvalue列。我可以得到min, mean, max如下:

tapply(df$value, df$pattern, min)
tapply(df$value, df$pattern, mean)
tapply(df$value, df$pattern, max)

现在,我需要为每个模式(组)在另外两列中mean获取lowest n distinct values和。我可以从下面得到最低和最高的 n (比如 5 个值),但我认为不是由每个组(模式)的不同5 个值计算出来的,在这里我需要知道,我该怎么做。top n distinct valuesmeanmean

setDT(df_stat) #requires Data.table
df_n[order(value)][, list(mean_of_low_5=mean(value[1:5])), by=pattern]
df_n[order(-value)][, list(mean_of_top_5=mean(value[1:5])), by=pattern]

任何简单的方法都受到高度赞赏。

样本数据-

df <- structure(list(pattern = c(462L, 462L, 462L, 462L, 462L, 462L, 
462L, 462L, 462L, 462L, 462L, 463L, 463L, 463L, 463L, 463L, 463L, 
463L, 463L, 463L, 463L, 463L, 463L, 463L, 463L, 464L, 464L, 464L, 
464L, 464L, 464L, 464L, 464L, 464L, 464L, 464L, 464L, 464L, 465L, 
465L, 465L, 465L, 465L, 466L, 466L, 466L, 466L, 466L, 466L, 466L, 
466L, 466L, 466L, 466L, 466L, 961L, 961L, 961L, 961L, 961L, 961L, 
961L), value = c(5.8e+10, 4.35e+10, 3.96e+10, 3.6e+10, 3.48e+10, 
3.3e+10, 3.3e+10, 3.3e+10, 3.3e+10, 3.3e+10, 3.3e+10, 1e+09, 
1e+09, 1e+09, 1e+09, 1e+09, 1e+09, 1e+09, 1e+09, 1e+09, 1e+09, 
1e+09, 1e+09, 1e+09, 1e+09, 3.3e+10, 3.3e+10, 3.3e+10, 3.3e+10, 
3.3e+10, 3.3e+10, 3.3e+10, 3.3e+10, 3.3e+10, 3.3e+10, 3.3e+10, 
3.3e+10, 3.3e+10, 3e+10, 3e+10, 3e+10, 3e+10, 3e+10, 3.3e+10, 
3.3e+10, 3.3e+10, 3.3e+10, 3.3e+10, 3.3e+10, 3.3e+10, 3.3e+10, 
3.3e+10, 3.2e+10, 3.2e+10, 3.2e+10, 2.6e+10, 2.6e+10, 2.6e+10, 
2.6e+10, 2.6e+10, 2.6e+10, 2.6e+10), timestamp = c(1590604157L, 
1590604157L, 1590604157L, 1590604157L, 1590604157L, 1590604157L, 
1590604157L, 1590604157L, 1590604157L, 1590604157L, 1590604157L, 
1590604170L, 1590604170L, 1590604170L, 1590604170L, 1590604170L, 
1590604170L, 1590604170L, 1590604170L, 1590604170L, 1590604170L, 
1590604170L, 1590604170L, 1590604170L, 1590604170L, 1590604213L, 
1590604213L, 1590604213L, 1590604213L, 1590604213L, 1590604213L, 
1590604213L, 1590604213L, 1590604213L, 1590604213L, 1590604213L, 
1590604213L, 1590604213L, 1590604226L, 1590604226L, 1590604226L, 
1590604226L, 1590604226L, 1590604239L, 1590604239L, 1590604239L, 
1590604239L, 1590604239L, 1590604239L, 1590604239L, 1590604239L, 
1590604239L, 1590604239L, 1590604239L, 1590604239L, 1590610895L, 
1590610895L, 1590610895L, 1590610895L, 1590610895L, 1590610895L, 
1590610895L)), class = "data.frame", row.names = c(NA, -62L))

标签: rggplot2statisticstime-series

解决方案


您可以使用以下命令在一个管道中进行所有计算dplyr

library(dplyr)

df %>%
  group_by(pattern) %>%
  summarise(min_val = min(value), 
            max_val = max(value), 
            mean_val = mean(value), 
            lowest_n_val = mean(head(unique(sort(value)), 5)),
            highest_n_val = mean(tail(unique(sort(value)), 5)))

如果您有数据,您可以添加na.rm. =TRUE上述所有功能NA


推荐阅读