有条件地向 data.frame 添加行 [英] adding rows to data.frame conditionally
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问题描述
我有一个大型的 data.frame
花卉和水果,用于 30 年的调查.我想在某些行中添加零 (0),这些行代表植物没有 flowers
或 fruits
的特定月份的个体(因为它是季节性物种).
I have a big data.frame
of flowers and fruits in a plant for a 30 years survey. I want to add zeros (0) in some rows which represent individuals in specific months where the plant did not have flowers
or fruits
(because it is a seasonal species).
例子:
Year Month Flowers Fruits
2004 6 25 2
2004 7 48 4
2005 7 20 1
2005 8 16 1
我想添加不包含在零值中的月份,所以我想在一个函数中识别缺失的月份并用 0 填充它们.
I want to add the months that are not included with values of zero so I was thinking in a function that recognize the missing months and fill them with 0.
谢谢.
推荐答案
## x is the data frame you gave in the question
x <- data.frame(
Year = c(2004, 2004, 2005, 2005),
Month = c(6, 7, 7, 8),
Flowers = c(25, 48, 20, 16),
Fruits = c(2, 4, 1, 1)
)
## y is the data frame that will provide the missing values,
## so you can replace 2004 and 2005 with whatever your desired
## time interval is
y <- expand.grid(Year = 2004:2005, Month = 1:12)
## this final step fills in missing dates and replaces NA's with zeros
library(tidyr)
x <- merge(x, y, all = TRUE) %>%
replace_na(list(Flowers = 0, Fruits = 0))
## if you don't want to use tidyr, you can alternatively do
x <- merge(x, y, all = TRUE)
x[is.na(x)] <- 0
看起来像这样:
head(x, 10)
# Year Month Flowers Fruits
# 1 2004 1 0 0
# 2 2004 2 0 0
# 3 2004 3 0 0
# 4 2004 4 0 0
# 5 2004 5 0 0
# 6 2004 6 25 2
# 7 2004 7 48 4
# 8 2004 8 0 0
# 9 2004 9 0 0
# 10 2004 10 0 0
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