将数据框中的每四行系列折叠成一个向量，覆盖缺失值答案

【问题标题】：Collapse every series of four rows in a data frame into a single vector, overwriting missing values将数据框中的每四行系列折叠成一个向量，覆盖缺失值
【发布时间】：2021-05-16 14:08:30
【问题描述】：

我想分析网站上的一些货币交易数据，但这些数据只能通过复制粘贴来访问。我将其复制到计算机的剪贴板并通过以下方式将其导入 R：

#df <- read.table("clipboard", header = FALSE, sep = "\t", stringsAsFactors = FALSE, na.strings = "", fill = TRUE)

但是当数据框被读入 R 时，它会将单个观察结果分成四行：

df <- structure(list(V1 = c("Buy", "Completed", "Fee1.00 USD", "Total199.00 USD", "Buy", "Completed", "Fee0.50 USD", "Total100.00 USD", "Buy", "Completed", "Fee0.64 USD", "Total127.00 USD"), V2 = c(NA, "2021-02-11 20:49:19", NA, NA, NA, "2021-02-11 20:48:03", NA, NA, NA, "2021-02-11 20:47:22", NA, NA), V3 = c(NA, "0.11057", NA, NA, NA, "82.146", NA, NA, NA, "30.15", NA, NA)), row.names = c(NA, 12L), class = "data.frame")
df

#               V1                  V2      V3
#1              Buy                <NA>    <NA>
#2        Completed 2021-02-11 20:49:19 0.11057
#3      Fee1.00 USD                <NA>    <NA>
#4  Total199.00 USD                <NA>    <NA>
#5              Buy                <NA>    <NA>
#6        Completed 2021-02-11 20:48:03  82.146
#7      Fee0.50 USD                <NA>    <NA>
#8  Total100.00 USD                <NA>    <NA>
#9              Buy                <NA>    <NA>
#10       Completed 2021-02-11 20:47:22   30.15
#11     Fee0.64 USD                <NA>    <NA>
#12 Total127.00 USD                <NA>    <NA>

因此，我想将每个四行系列折叠成一个，就像这样，它会覆盖作为数据导入过程的怪癖而生成的缺失值：

want <- structure(list(V1 = structure(c(1L, 1L, 1L), .Label = "Buy", class = "factor"), V2 = structure(c(1L, 1L, 1L), .Label = "Completed", class = "factor"), V3 = structure(3:1, .Label = c("2/11/2021 20:47", "2/11/2021 20:48", "2/11/2021 20:49"), class = "factor"), V4 = c(0.11057, 82.146,     30.15), V5 = structure(c(3L, 1L, 2L), .Label = c("Fee0.50 USD", "Fee0.64 USD", "Fee1.00 USD"), class = "factor"), V6 = structure(c(3L, 1L, 2L), .Label = c("Total100.00 USD", "Total127.00 USD", "Total199.00 USD"), class = "factor")), class = "data.frame", row.names = c(NA, -3L))
want

#   V1        V2        V3            V4      V5              V6
#1 Buy Completed 2/11/2021 20:49  0.11057 Fee1.00 USD Total199.00 USD
#2 Buy Completed 2/11/2021 20:48 82.14600 Fee0.50 USD Total100.00 USD
#3 Buy Completed 2/11/2021 20:47 30.15000 Fee0.64 USD Total127.00 USD

显然，事情仍然会有点混乱，因为我需要将一些字符串分成单独的列（例如 df$V5 = "Fee1.00 USD" 将变为 df$Fee = 1.00），但这是一个不同的问题。

我尝试添加一个 id 变量，然后将其从长形改造成宽形，as discussed here，但是通过获取我需要的值（例如“Fee1.00 USD”中的 1.00）并将它们作为新值，这变得更加混乱列名：

df$id <- gl((nrow(df)/4), 4)
reshape(df, timevar = "V1", idvar = "id", direction = "wide")

我已经尝试将数据框拆分为数据框列表as discussed here，但我仍然不确定如何折叠每个数据框并将其缝合在一起：

split(df, f = df$id)

将数据转换为正确格式的最佳方法是什么？

【问题讨论】：

标签： r dataframe data-binding split reshape

【解决方案1】：

这个怎么样：

library(dplyr)
library(tidyr)
df <- df %>% mutate(obs = rep(1:(nrow(.)/4), each=4))
df <- df %>% 
  pivot_longer(-obs, names_to="var", values_to="vals") %>% 
  na.omit() %>% 
  group_by(obs) %>% 
  mutate(col = seq_along(obs)) %>% 
  select(obs, col, vals) %>% 
  pivot_wider(names_from="col", names_prefix="V", values_from="vals")
df
# # A tibble: 3 x 7
# # Groups:   obs [3]
#     obs V1    V2        V3                  V4      V5          V6             
#   <int> <chr> <chr>     <chr>               <chr>   <chr>       <chr>          
# 1     1 Buy   Completed 2021-02-11 20:49:19 0.11057 Fee1.00 USD Total199.00 USD
# 2     2 Buy   Completed 2021-02-11 20:48:03 82.146  Fee0.50 USD Total100.00 USD
# 3     3 Buy   Completed 2021-02-11 20:47:22 30.15   Fee0.64 USD Total127.00 USD

【讨论】：

【解决方案2】：

Dave 的回答完美且简洁。如果由于某种原因有人不能使用外部包，我以他的脚本为指导，并尝试使用 base R 复制它：

df$id <- gl((nrow(df) / 4), 4)
df <- reshape(df, idvar = "id",
              v.names = "val",
              timevar = "var",
              times = names(df[1:3]),
              varying = names(df[1:3]),
              new.row.names = 1:1000,
              direction = "long")
df <- na.omit(df)
df <- df[order(df$id),]
df$col <- ave(seq_len(nrow(df)), df$id, FUN = seq_along)
df <- subset(df, select = c("id", "col", "val"))
df <- reshape(df, timevar = "col",
              idvar = "id",
              direction = "wide")
colnames(df) <- c("id", "V1", "V2", "V5", "V6", "V3", "V4")
varnames <- c("id", "V1", "V2", "V3", "V4", "V5", "V6")
df <- df[, varnames]
df

【讨论】：