如何克服错误:“尝试在小于二维的对象上设置‘列名’"在 xts 对象中 [英] How to overcome error:"attempt to set 'colnames' on an object with less than two dimension" in xts object
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问题描述
我想在使用 quantmod 包生成的SPY"数据帧的末尾添加一个开盘价作为新行,我使用以下代码来绑定新行,但出现错误
I would like to add an open price as a new row at the end of a "SPY" data frame that was produce using the quantmod package, I used the following code in order to rbind the new row but I got an error
# rm(list = ls()) # generally considered as bad manner in an MWE
require(quantmod)
options(scipen=999)
spy <- getSymbols(("SPY") , src = 'yahoo', from = '2016-01-01', auto.assign = T)
spy<-cbind(SPY)
tail(SPY)
SPY.Open SPY.High SPY.Low SPY.Close SPY.Volume SPY.Adjusted
2016-01-14 189.55 193.26 187.66 191.93 240795600 191.93
2016-01-15 186.77 188.76 185.52 187.81 324846400 187.81
2016-01-19 189.96 190.11 186.20 188.06 190196000 188.06
2016-01-20 185.03 187.50 181.02 185.65 280016900 185.65
2016-01-21 186.21 188.87 184.64 186.69 189174000 186.69
2016-01-22 189.78 190.76 188.88 190.52 163849600 190.52
我想手动将新行插入到间谍数据集中,所以我尝试创建一个新的 xts 对象,而不是使用 rbind
函数,但在这些行之后出现错误:>
I would like to insert new row manually into the spy dataset, so I tried to create a new xts object and than to use an rbind
function but I got an error after those lines :
q <- c("2016-01-25",100,200,200,200,200,200) # creating the data
colnames(q) <- colnames(SPY) # creating column names as in SPY
但是我遇到了一个错误:
But I got an error:
Error in `colnames<-`(`*tmp*`, value = c("SPY.Open", "SPY.High", "SPY.Low", :
attempt to set 'colnames' on an object with less than two dimensions # creating the column names
如何在数据框的顶部添加这个手工制作的行?
How can I add this hand made row on the data frame's top ?
推荐答案
您可能想要:
q <- data.frame(100,200,200,200,200,200)
colnames(q) <- colnames(SPY)
q <- xts(q, as.Date("2016-01-26"))
# SPY.Open SPY.High SPY.Low SPY.Close SPY.Volume SPY.Adjusted
# 2016-01-26 100 200 200 200 200 200
class(SPY)
# [1] "xts" "zoo"
class(q)
# [1] "xts" "zoo"
tail(rbind(SPY, q))
# SPY.Open SPY.High SPY.Low SPY.Close SPY.Volume SPY.Adjusted
# 2016-01-19 189.96 190.11 186.20 188.06 190196000 188.06
# 2016-01-20 185.03 187.50 181.02 185.65 280016900 185.65
# 2016-01-21 186.21 188.87 184.64 186.69 189174000 186.69
# 2016-01-22 189.78 190.76 188.88 190.52 163849600 190.52
# 2016-01-25 189.92 190.15 187.41 187.64 122676200 187.64
# 2016-01-26 100.00 200.00 200.00 200.00 200 200.00
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