Question

我能够将每日的H，L，C数据转换为每月的H，L，C数据：

library(xts)
data(sample_matrix)
samplexts <- as.xts(sample_matrix)
to.monthly(sample xts)

但是如何从每日数据中轻松获取每月平均值？

Answer 1

使用xts的方法有2种

简单方法：使用apply.x函数（其中x是句点）。在这种情况下，apply.monthly：

apply.monthly(samplexts, mean)
               Open     High      Low    Close
2007-01-31 50.21140 50.31528 50.12072 50.22791
2007-02-28 50.78427 50.88091 50.69639 50.79533
2007-03-31 49.53185 49.61232 49.40435 49.48246
2007-04-30 49.62687 49.71287 49.53189 49.62978
2007-05-31 48.31942 48.41694 48.18960 48.26699
2007-06-30 47.47717 47.57592 47.38255 47.46899

或更复杂的使用period.apply的方法，该方法用于调用apply.monthly和其他apply.x函数。如果apply.x函数缺少时间段，这可以为您提供更精细的控制。

period.apply(samplexts, INDEX = endpoints(samplexts, on = "months"), FUN = mean)
               Open     High      Low    Close
2007-01-31 50.21140 50.31528 50.12072 50.22791
2007-02-28 50.78427 50.88091 50.69639 50.79533
2007-03-31 49.53185 49.61232 49.40435 49.48246
2007-04-30 49.62687 49.71287 49.53189 49.62978
2007-05-31 48.31942 48.41694 48.18960 48.26699
2007-06-30 47.47717 47.57592 47.38255 47.46899

Answer 2

这是使用dplyr软件包的一种方法

# create sequence of data
dates = seq(as.Date('2011-01-01'),as.Date('2011-12-31'),by = 1)
data = data.frame(dates, num = rnorm(1:365))

# create month and year column
data$month = lubridate::month(data$dates)
data$year = lubridate::year(data$dates)

# view data
head(data)

# load library
library(dplyr)

# summarize data as needed
data %>% group_by(year,month) %>% summarize(numMean = mean(num)) %>% as.data.frame

R：将每日数据转换为每月平均值

2 个答案: