有没有更简洁的方法来整理数据框列表？

Question

我使用 API returns 数据帧列表（Rblpapi bdh() 函数）。我想使用列表的 names() 作为组合单个数据框中的新列，将数据放入整齐的格式。我有一个解决方案，但我怀疑它容易出错并且比需要的慢。

#create example data set
library(tidyr)

obsA <- data_frame(
  date = as.Date('2009-01-01') + 0:2,
  X = rnorm(3, 0, 1),
  Y = rnorm(3, 0, 2),
  Z = rnorm(3, 0, 4)
)
obsB <- data_frame(
  date = as.Date('2009-01-01') + 0:2,
  X = rnorm(3, 10, 1),
  Y = rnorm(3, 10, 2),
  Z = rnorm(3, 10, 4)
)

obs<-list(obsA=obsA,obsB=obsB)

我可以轻松创建单个数据框，但它会将各个列表名称放入唯一的行名称中。

#create single data frame
obs_long<-do.call("rbind",obs)

#don't like this
rownames(obs_long)
#[1] "obsA.1" "obsA.2" "obsA.3" "obsB.1" "obsB.2" "obsB.3"
names(obs_long)
#[1] "date" "X"    "Y"    "Z"

我可以拉出该行，使用正则表达式删除添加的行标识符，然后 mutate() 到一个新列。

#Full solution but ungainly.
# Extra step to convert row names to a column.  Risk of parsing error if
# a period is in item name.
tidy_obs<-do.call("rbind",obs) #%>%
  mutate(item=str_extract(rownames(.),"[A-Za-z0-9 ]+"))%>%
  select(date,item,everything())%>%
  group_by(item)%>%arrange(date)

# > tidy_obs
# # A tibble: 6 x 5
# # Groups:   item [2]
# date         item          X         Y         Z
#   <date>      <chr>      <dbl>     <dbl>     <dbl>
# 1 2009-01-01  obsA -0.1030362  2.274885 -4.134265
# 2 2009-01-01  obsB  8.4210832  7.604203 13.449731
# 3 2009-01-02  obsA -0.2279141 -2.748717  4.372599
# 4 2009-01-02  obsB 12.8940563 10.594164  8.108275
# 5 2009-01-03  obsA  0.5749725 -4.041280 -0.524420
# 6 2009-01-03  obsB 10.1158769 12.684331  8.248651

这行得通，但我想知道是否有更直接的方法可以避免 mutate() and/or 的额外步骤 str_extract() 的解析异常风险。谢谢！

Answer 1

您可以将 dplyr::bind_rows 与 .id 参数一起使用：

.id Data frame identifier.

When .id is supplied, a new column of identifiers is created to link each row to its original data frame. The labels are taken from the named arguments to bind_rows(). When a list of data frames is supplied, the labels are taken from the names of the list. If no names are found a numeric sequence is used instead.

bind_rows(obs, .id = "item")

# A tibble: 6 x 5
#   item       date           X          Y         Z
#  <chr>     <date>       <dbl>      <dbl>     <dbl>
#1  obsA 2009-01-01 -1.73508885 -0.4402811  7.342978
#2  obsA 2009-01-02  1.17149983 -0.5429690  8.167079
#3  obsA 2009-01-03  0.08631895 -0.1430551  5.925108
#4  obsB 2009-01-01  9.66203430  7.1094147 15.577023
#5  obsB 2009-01-02 10.43062660  9.6160614 15.077929
#6  obsB 2009-01-03  8.80792988  8.9604396  7.413831

Answer 2

也可能与 data.table 的 rbindlist:

library(data.table)
rbindlist(obs, idcol = "item")
#   item       date          X         Y         Z
#1: obsA 2009-01-01 -0.2900620  2.694434  2.555925
#2: obsA 2009-01-02 -1.0221531 -4.172495 -4.357794
#3: obsA 2009-01-03  0.2389569 -1.088882 -4.944420
#4: obsB 2009-01-01  9.4713142 10.433553  9.319284
#5: obsB 2009-01-02 10.0967994 11.941084 13.589136
#6: obsB 2009-01-03  9.9403227 11.727769 17.792899

基础 R 方法也可能是使用 Map 和 Reduce:

Reduce(rbind, Map(function(x,name) cbind(x,item = name), obs, names(obs)))

有没有更简洁的方法来整理数据框列表？

is there a cleaner way to tidy a list of data frames?

r

dplyr

tidyr