更改tibble包中的子集；先前工作的代码出现了新错误

问题描述

下面的代码创建的原始数据与我正在使用的类似。我编写了一些代码，使用tibble软件包中的add_row函数将其重新格式化。现在我遇到了一个错误（此代码在2020年4月之后有效）。子集的规则似乎由于软件包的更新而变得更加严格了？我想知道是否有人可以帮助纠正此错误... 首先创建数据

# Create replicate of raw data
date <- seq(from = as.Date('1999-01-01'),to = as.Date('2013-12-31'),by = 'day')

temp <- rnorm(5479,15,5)

precip <- rlnorm(5479)

rawdata <- data.frame(date=date,temp=round(temp,digits = 2),precip=round(precip,digits = 2))
# Add columns needed to run code
rawdata$year <- as.numeric(substr(rawdata$date,1,4))
rawdata$month <- as.numeric(substr(rawdata$date,6,7))
rawdata$chardate <- format(rawdata$date,'%Y-%h-%d') # create abbreviated month column
rawdata$charmonth <- substr(rawdata$chardate,8)   # for formatting
rawdata$charmonth <- as.character(rawdata$charmonth)
rawdata$day <- as.numeric(substr(rawdata$date,9,10))
rawdata$uniqdate <- rawdata$year*100+as.numeric(rawdata$day)+rawdata$month*10 
rawdata$uniqmonth <- (rawdata$year*100)+rawdata$month# create unique month identifier
rawdata$yr <- NA # This column will be filled only in the new rows to be added

# Create weather object to Feed the for loop below----
weather <- data.frame(year = rawdata$year,month = rawdata$month,day = rawdata$day,charmonth = rawdata$charmonth,uniqmonth = rawdata$uniqmonth,uniqdate = rawdata$uniqdate,temp = rawdata$temp,precip = rawdata$precip,yr = rawdata$yr)

# weather$charmonth <- as.character(rawdata$charmonth)

现在出现错误...我正尝试在每个月的数据顶部添加一行，其中包含该月的天数，缩写三个字母的月份（jan，feb，mar等）。）和年份。

library(tibble) # package containing the add_row function
# create empty list to put all of the monthly dataframes in
newdat <- list() 

# the following loop will  create a dataframe for each month and put in a list
for(i in unique(weather$uniqmonth)) { # for every unique month value
  # create object nam that is of the format 'df.uniqmonth'
  nam <- paste("df",i,sep = ".")    
  # create object dat that contains all data for each unique month
  dat <- weather[weather$uniqmonth==i,]
  # add a row of data at the start of each dataframe with the days in month,month abbr.,year
  dat <- add_row(dat,year = NA,month = NA,day = NA,charmonth = NA,uniqmonth = NA,uniqdate = NA,# the line below is the info we are adding in the columns we will keep
                 temp = na.omit(max(dat$day)),precip = unique(dat$charmonth),yr = unique(dat$year),.before = 1)
  # just keep required columns
  dat <- data.frame(dat$temp,dat$precip,dat$yr) 
  # add new dataframe to a list,using the new name
  newdat[[nam]] <- dat 
}

** 您可以运行循环，也可以逐行运行（设置i = 199901），并且错误相同：

错误：无法结合..1$precip和..2$precip。

最终，我应该能够运行以下命令以获得所需的输出，并在文本编辑器中完成该输出（删除尾部逗号）。 **

# Merge all data into a dataframe
full_data <- do.call("rbind",newdat)

# turn NA's into blanks
full_data[is.na(full_data)] <- ""

**感谢您为解决此错误提供的帮助！

这就是我需要的最终产品

a <- c("Jan",round(rnorm(31,5),"Feb",round(rnorm(28,5,"Mar",digits = 2))
b <- c(31,rlnorm(31),28,rlnorm(28),31,rlnorm(31))
c <- c(1999,rep(NA,31),1999,28),31))

final_data <- data.frame(temp = a,precip = round(b,digits=2),year = c)

解决方法

经过长时间的讨论，最终结果不是传统的CSV，因此需要一些弯曲。

鉴于weather开始看起来像这样：

head(weather)
# # A tibble: 6 x 9
#    year month   day charmonth uniqmonth uniqdate  temp precip yr   
#   <dbl> <dbl> <dbl> <chr>         <dbl>    <dbl> <dbl>  <dbl> <lgl>
# 1  1999     1     1 Jan          199901   199911 13.8    2.03 NA   
# 2  1999     1     2 Jan          199901   199912 10.8    2.53 NA   
# 3  1999     1     3 Jan          199901   199913  8.78   3.15 NA   
# 4  1999     1     4 Jan          199901   199914 14.3    0.63 NA   
# 5  1999     1     5 Jan          199901   199915 18.5    0.47 NA   
# 6  1999     1     6 Jan          199901   199916 10.4    0.39 NA

所需的输出（full_data）在文件中如下所示：

Jan,31,1999
13.83,2.03
10.76,2.53
8.78,3.15
...truncated...
18.74,0.79
Feb,28,1999
17.47,1.62
9.15,0.48
...truncated...
18.36,2.26
Mar,1999
20.53,2.65
11.1,2.58
19.52,0.33
...truncated...

关键是输出实际上是两列：precip和temp，但是每一“天”都需要一个三列的标题。

我认为最简单的处理方法是首先group_by主分组变量（uniqmonth），然后do对每组数据进行处理。这种“东西”实际上是：（1）创建新的标题行，即charmonth,max(day)和year。由于该逗号比普通CSV中的逗号要多，因此我将在第一个字段中插入逗号，并告诉write.table不要引用它。这是一种解决方法，但是...有效。

library(dplyr)
weather %>%
  group_by(uniqmonth) %>%
  do({
    bind_rows(
      tibble(temp = paste(.$charmonth[1],max(.$day),sep = ","),precip = as.character(.$year[1])),mutate_all(select(.,temp,precip),as.character)
    )
  }) %>%
  ungroup() %>%
  select(-uniqmonth) %>%
  write.table(.,file = "quux.csv",quote = FALSE,",row.names = FALSE,col.names = FALSE)

r r tibble