我有一个非常大的数据集,其中我有一个时间列的列,我希望将时间接近的行(范围:.1 - .2秒间隔)组合成一个平均值.
以下是数据外观的示例:
BPM seconds
63.9 61.899
63.9 61.902
63.8 61.910
62.1 130.94
62.1 130.95
61.8 211.59
63.8 280.5
60.3 290.4
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所以我想要结合前3行,然后是之后的2行,其余的将是独立的.意思是我希望数据看起来像这样:
BPM seconds
63.9 61.904
62.1 130.95
61.8 211.59
63.8 280.5
60.3 290.4
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我们需要创建组,这是重要的一点,其余的是标准聚合:
cumsum(!c(0, diff(df1$seconds)) < 0.2)
# [1] 0 0 0 1 1 2 3 4
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然后使用聚合聚合:
aggregate(df1[, 2], list(cumsum(!c(0, diff(df1$seconds)) < 0.2)), mean)
# Group.1 x
# 1 0 61.90367
# 2 1 130.94500
# 3 2 211.59000
# 4 3 280.50000
# 5 4 290.40000
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或者使用dplyr:
library(dplyr)
df1 %>%
group_by(myGroup = cumsum(!c(0, diff(seconds)) < 0.2)) %>%
summarise(BPM = first(BPM),
seconds = mean(seconds))
# # A tibble: 5 x 3
# myGroup BPM seconds
# <int> <dbl> <dbl>
# 1 0 63.9 61.9
# 2 1 62.1 131.
# 3 2 61.8 212.
# 4 3 63.8 280.
# 5 4 60.3 290.
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可重复的示例数据:
df1 <- read.table(text = "BPM seconds
63.9 61.899
63.9 61.902
63.8 61.910
62.1 130.94
62.1 130.95
61.8 211.59
63.8 280.5
60.3 290.4", header = TRUE)
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