R中不同的行数
Differing number of rows in R
我正在尝试将四个数据帧合并为一个数据帧，但我没能成功，因为行数似乎有误。每个数据框包含从 2021-02-28 到 2022-04-01 的股票价格信息。
#Loading stock data
install.packages("quantmod")
library(quantmod)
#Getting stock data for: Toyota (TYO), Renault (RNO.PA), Honda (HMC), Hyundai (HYMTF)
getSymbols(c("HMC", "HYMTF", "RNO.PA", "TYO" ), na.rm = TRUE)
#Creating individual data frames.
# Stock Honda.
stock_honda <- expand.grid("HMC" = HMC$HMC.Close) %>%
mutate(Date = row.names(as.data.frame(HMC))) %>%
mutate(across(Date, ~ . %>% str_remove("^X") %>% ymd())) %>%
subset(Date >"2021-02-28" & Date < "2022-04-01") %>%
rename(Close = HMC)
head(stock_honda)
#Stock Toyota
stock_tyo <- expand.grid("Toyota" = TYO$TYO.Close) %>%
mutate(Date = row.names(as.data.frame(TYO))) %>%
mutate(across(Date, ~. %>% str_remove("^X") %>% ymd()))%>%
subset(Date > "2021-02-28" & Date < "2022-04-01") %>%
rename(Close = Toyota)
head(stock_tyo)
# Stock Renault
stock_rno <- expand.grid("Rneault" = RNO.PA$RNO.PA.Close) %>%
mutate(Date = row.names(as.data.frame(RNO.PA))) %>%
mutate(across(Date, ~. %>% str_remove("^X") %>% ymd()))%>%
subset(Date > "2021-02-28" & Date < "2022-04-01")
head(stock_rno)
#Stock Hyundai
stock_hyundai <- expand.grid("HYMTF" = HYMTF$HYMTF.Close) %>%
mutate(Date = row.names(as.data.frame(HYMTF))) %>%
mutate(across(Date, ~ . %>% str_remove("^X") %>% ymd())) %>%
subset(Date >"2021-02-28" & Date < "2022-04-01") %>%
rename(Close = HYMTF)
head(stock_hyundai)
#Merging stocks data into one data frame
stocks <- data.frame("Honda" = stock_honda, "Hyundai" = stock_hyundai,
"Renault" = stock_rno, "Toyota" = stock_tyo)
head(stocks)
这给我以下错误：
Error in data.frame(Honda = stock_honda, Hyundai = stock_hyundai, Renault = stock_rno, :
arguments imply differing number of rows: 276, 282
```
行数不同。最好按 'Date' 列加入，因为 data.frame 要求所有列的长度相同。也可以通过在末尾填充 NA 来完成，但这可能会导致错误，因为我们假设所有数据集都具有相同的日期序列，没有任何中断。相反，连接将确保我们获得对应于相同 'Date' 的行，如果不存在，则由 NA
填充
library(zoo)
library(dplyr)
library(purrr)
library(stringr)
library(quantmod)
# keep the datasets in a list
out <- list(HMC, HYMTF, RNO.PA, TYO) %>%
# loop over the list with `map`
# convert each of the zoo objects to data.frame with `fortify.zoo`
map(~ fortify.zoo(.x) %>%
# select the Index and Close columns
select(Date = Index, ends_with('Close')) %>%
# remove the suffix Close if needed
rename_with(~ str_remove(.x, "\.Close"), ends_with("Close")) %>%
# filter the rows based on the Date column
filter(between(Date, as.Date("2021-02-28"),
as.Date("2022-04-01")))) %>%
# finally reduce the list of data.frames to a single data.frame by joining
reduce(full_join, by = 'Date')
-输出
> str(out)
'data.frame': 284 obs. of 5 variables:
$ Date : Date, format: "2021-03-01" "2021-03-02" "2021-03-03" "2021-03-04" ...
$ HMC : num 28.5 28.4 28.9 28.6 29.4 ...
$ HYMTF : num 49.3 48 48.9 46.7 45.7 ...
$ RNO.PA: num 37.6 37.4 39.4 39.2 38.5 ...
$ TYO : num 8.94 8.8 9 9.1 9.22 9.29 9.15 9.1 9.07 9.26 ...
连接是这里最直接的选择，但转换为宽 formight 也可以解决问题..
一种data.table方法
library(data.table)
library(tibble)
# put everyting into a list, tibble::lst() uses the names
# of the objects added to the list as it's names... this comes
# in handy when we rowbind the list two code-lines down...
L <- tibble::lst(stock_honda, stock_hyundai, stock_rno, stock_tyo)
# convert to data.tables
L <- lapply(L, as.data.table)
# rowbind together
DT <- data.table::rbindlist(L, use.names = FALSE, idcol = "stock")
# cast to wide
final <- dcast(DT, Date ~ stock, value.var = "Close")
# Date stock_honda stock_hyundai stock_rno stock_tyo
# 1: 2021-03-01 28.48 49.26 37.635 8.94
# 2: 2021-03-02 28.40 48.03 37.420 8.80
# 3: 2021-03-03 28.88 48.89 39.370 9.00
# 4: 2021-03-04 28.60 46.70 39.175 9.10
# 5: 2021-03-05 29.39 45.74 38.550 9.22
# 6: 2021-03-08 29.48 45.50 40.075 9.29
# ...
在 运行ning getSymbols（其中 returns 字符向量，代码，代码名称并将数据放置在全局环境中这些名称的对象中）之后 运行 mget 将代码数据放入列表中并从中提取收盘价——您可能需要调整后的收盘价而不是收盘价，在这种情况下使用 Ad 而不是 Cl——然后合并它们并设置列名。 stocks 将是一个 xts 对象，每个代码有一列。如果您需要数据框，请保持原样或使用 fortify.zoo(stocks)。
library(quantmod)
tickers <- getSymbols(c("HMC", "HYMTF", "RNO.PA", "TYO" ))
stocks <- tickers |>
mget() |>
Map(f = Cl) |>
do.call(what = "merge") |>
setNames(tickers)
我正在尝试将四个数据帧合并为一个数据帧，但我没能成功，因为行数似乎有误。每个数据框包含从 2021-02-28 到 2022-04-01 的股票价格信息。
#Loading stock data
install.packages("quantmod")
library(quantmod)
#Getting stock data for: Toyota (TYO), Renault (RNO.PA), Honda (HMC), Hyundai (HYMTF)
getSymbols(c("HMC", "HYMTF", "RNO.PA", "TYO" ), na.rm = TRUE)
#Creating individual data frames.
# Stock Honda.
stock_honda <- expand.grid("HMC" = HMC$HMC.Close) %>%
mutate(Date = row.names(as.data.frame(HMC))) %>%
mutate(across(Date, ~ . %>% str_remove("^X") %>% ymd())) %>%
subset(Date >"2021-02-28" & Date < "2022-04-01") %>%
rename(Close = HMC)
head(stock_honda)
#Stock Toyota
stock_tyo <- expand.grid("Toyota" = TYO$TYO.Close) %>%
mutate(Date = row.names(as.data.frame(TYO))) %>%
mutate(across(Date, ~. %>% str_remove("^X") %>% ymd()))%>%
subset(Date > "2021-02-28" & Date < "2022-04-01") %>%
rename(Close = Toyota)
head(stock_tyo)
# Stock Renault
stock_rno <- expand.grid("Rneault" = RNO.PA$RNO.PA.Close) %>%
mutate(Date = row.names(as.data.frame(RNO.PA))) %>%
mutate(across(Date, ~. %>% str_remove("^X") %>% ymd()))%>%
subset(Date > "2021-02-28" & Date < "2022-04-01")
head(stock_rno)
#Stock Hyundai
stock_hyundai <- expand.grid("HYMTF" = HYMTF$HYMTF.Close) %>%
mutate(Date = row.names(as.data.frame(HYMTF))) %>%
mutate(across(Date, ~ . %>% str_remove("^X") %>% ymd())) %>%
subset(Date >"2021-02-28" & Date < "2022-04-01") %>%
rename(Close = HYMTF)
head(stock_hyundai)
#Merging stocks data into one data frame
stocks <- data.frame("Honda" = stock_honda, "Hyundai" = stock_hyundai,
"Renault" = stock_rno, "Toyota" = stock_tyo)
head(stocks)
这给我以下错误：
Error in data.frame(Honda = stock_honda, Hyundai = stock_hyundai, Renault = stock_rno, :
arguments imply differing number of rows: 276, 282
```
行数不同。最好按 'Date' 列加入，因为 data.frame 要求所有列的长度相同。也可以通过在末尾填充 NA 来完成，但这可能会导致错误，因为我们假设所有数据集都具有相同的日期序列，没有任何中断。相反，连接将确保我们获得对应于相同 'Date' 的行，如果不存在，则由 NA
library(zoo)
library(dplyr)
library(purrr)
library(stringr)
library(quantmod)
# keep the datasets in a list
out <- list(HMC, HYMTF, RNO.PA, TYO) %>%
# loop over the list with `map`
# convert each of the zoo objects to data.frame with `fortify.zoo`
map(~ fortify.zoo(.x) %>%
# select the Index and Close columns
select(Date = Index, ends_with('Close')) %>%
# remove the suffix Close if needed
rename_with(~ str_remove(.x, "\.Close"), ends_with("Close")) %>%
# filter the rows based on the Date column
filter(between(Date, as.Date("2021-02-28"),
as.Date("2022-04-01")))) %>%
# finally reduce the list of data.frames to a single data.frame by joining
reduce(full_join, by = 'Date')
-输出
> str(out)
'data.frame': 284 obs. of 5 variables:
$ Date : Date, format: "2021-03-01" "2021-03-02" "2021-03-03" "2021-03-04" ...
$ HMC : num 28.5 28.4 28.9 28.6 29.4 ...
$ HYMTF : num 49.3 48 48.9 46.7 45.7 ...
$ RNO.PA: num 37.6 37.4 39.4 39.2 38.5 ...
$ TYO : num 8.94 8.8 9 9.1 9.22 9.29 9.15 9.1 9.07 9.26 ...
连接是这里最直接的选择，但转换为宽 formight 也可以解决问题..
一种data.table方法
library(data.table)
library(tibble)
# put everyting into a list, tibble::lst() uses the names
# of the objects added to the list as it's names... this comes
# in handy when we rowbind the list two code-lines down...
L <- tibble::lst(stock_honda, stock_hyundai, stock_rno, stock_tyo)
# convert to data.tables
L <- lapply(L, as.data.table)
# rowbind together
DT <- data.table::rbindlist(L, use.names = FALSE, idcol = "stock")
# cast to wide
final <- dcast(DT, Date ~ stock, value.var = "Close")
# Date stock_honda stock_hyundai stock_rno stock_tyo
# 1: 2021-03-01 28.48 49.26 37.635 8.94
# 2: 2021-03-02 28.40 48.03 37.420 8.80
# 3: 2021-03-03 28.88 48.89 39.370 9.00
# 4: 2021-03-04 28.60 46.70 39.175 9.10
# 5: 2021-03-05 29.39 45.74 38.550 9.22
# 6: 2021-03-08 29.48 45.50 40.075 9.29
# ...
在 运行ning getSymbols（其中 returns 字符向量，代码，代码名称并将数据放置在全局环境中这些名称的对象中）之后 运行 mget 将代码数据放入列表中并从中提取收盘价——您可能需要调整后的收盘价而不是收盘价，在这种情况下使用 Ad 而不是 Cl——然后合并它们并设置列名。 stocks 将是一个 xts 对象，每个代码有一列。如果您需要数据框，请保持原样或使用 fortify.zoo(stocks)。
library(quantmod)
tickers <- getSymbols(c("HMC", "HYMTF", "RNO.PA", "TYO" ))
stocks <- tickers |>
mget() |>
Map(f = Cl) |>
do.call(what = "merge") |>
setNames(tickers)