Reputation: 153
Hi I have data from yahoo in data frame for different stocks (columns symbol) . I want to create dataframe(tibble) with 1 row per stock with a column which would contain nested stock data as xts object. THe picture of result and reproducible example added. any help appreciated
library(purrr)
library(tidyverse)
library(tidyr)
df<-structure(list(symbol = c("AAPL", "AAPL", "AAPL", "AAPL", "AAPL",
"AMZN", "AMZN", "AMZN", "AMZN", "AMZN", "MSFT", "MSFT", "MSFT",
"MSFT", "MSFT"), date = structure(c(18295, 16700, 17571, 18305,
18086, 17834, 17696, 17438, 16850, 18016, 18376, 17935, 18085,
17626, 17724), class = "Date"), adjusted = c(76.636299, 26.198639,
37.847511, 80.852463, 49.627182, 1530.420044, 1723.859985, 961.349976,
534.900024, 1926.52002, 173.645462, 103.308533, 134.968887, 89.195686,
101.034645)), row.names = c(NA, -15L), class = c("tbl_df", "tbl",
"data.frame"))
df%>%group_by(symbol)%>%
nest()%>%
mutate(xts_obj=map(data,~as.xts(order_by=.$date)))
Upvotes: 2
Views: 154
Reputation: 887098
Here, we may need to remove the 'date' column by going into xts
object
library(dplyr)
library(xts)
library(purrr)
ndf <- df %>%
group_by(symbol) %>%
nest %>%
mutate(xts_obj = map(data, ~ xts(.x %>% select(-date), order.by = .x$date)))
ndf
# A tibble: 3 x 3
# Groups: symbol [3]
# symbol data xts_obj
# <chr> <list> <list>
#1 AAPL <tibble [5 × 2]> <xts [5 × 1]>
#2 AMZN <tibble [5 × 2]> <xts [5 × 1]>
#3 MSFT <tibble [5 × 2]> <xts [5 × 1]>
Or make it more dynamic by selecting only numeric
columns
df %>%
group_by(symbol) %>%
nest %>%
mutate(xts_obj = map(data, ~ .x %>%
select(where(is.numeric)) %>%
xts(., order.by = .x$date)))
ndf$xts_obj[[1]]
# adjusted
#2015-09-22 26.19864
#2018-02-09 37.84751
#2019-07-09 49.62718
#2020-02-03 76.63630
#2020-02-13 80.85246
Based on the OP's image, it is showing the xts_obj
column as a list
with 0
elements
ndf0$xts_obj[[1]]
#Data:
#numeric(0)
Upvotes: 2