在单独的行 R 之后清除组中除第一行之外的变量

Question

我必须完成 3 件事：

由 Col 拆分的单独行："Date" 包含不同的年份。
EXCEPT Col :"Fix" , 只保留 FIRST row within a group 有数据。

计算 Col : "Price" 偶数除以拆分的行数。

# Dataset call df 

Name Fix Price   Date 
Tom  600  500     2016-01-01
John 800  400     2016-01-03;2016-01-09
Mary 1100 1000    2016-01-04;2017-09-01;2017-08-10;2018-01-01
Joe  30   25      2016-01-04;2017-09-01
Paul 400  304     2015-01-02
Alex 505  238     2018-01-02;2018-02-02

# Targeted df

Name Fix  Price   Date 
Tom  600  500     2016-01-01
John 800  400     2016-01-03;2016-01-09
Mary 1100 250     2016-01-04
Mary 0    250     2017-09-01
Mary 0    250     2017-08-10
Mary 0    250     2018-01-01
Joe  30   12.5    2016-01-04
Joe  0    12.5    2017-09-01
Paul 400  304     2015-01-02
Alex 505  238     2018-01-02;2018-02-02

我有实现 1 和 3 的方法，但我无法制作 2，因为我不知道 fill() 的任何 Diverse 函数。

# Find the SPLIT TARGET first :
inds <- sapply(strsplit(df$Date, ";"), function(x) 
length(unique(format(as.Date(x), "%Y"))) > 1) ### This approach actually 
does not works in my actual data when over 1 Million rows , i chunk it into a smaller data 
to fit this approach's limit.

library(tidyverse)
library(stringr)

#Select those indices 

df[inds, ] %>% mutate(Price = Price / (str_count(Date,";") + 1)) %>%
separate_rows(Date, sep = ";") %>%
bind_rows(df[!inds,])

*请提醒您不能使用 Col : " Name " 作为某些内容，因为它们仅表示数据集具有其他必须由 separate_rows
复制的值我怎样才能清除第 2 点？这让我发疯。感谢您提前提出任何意见

Answer 1

dt = read.table(text = "
Name Fix Price   Date 
                Tom  600  500     2016-01-01
                John 800  400     2016-01-03;2016-01-09
                Mary 1100 1000    2016-01-04;2017-09-01;2017-08-10;2018-01-01
                Joe  30   25      2016-01-04;2017-09-01
                Paul 400  304     2015-01-02
                Alex 505  238     2018-01-02;2018-02-02
                ", header=T, stringsAsFactors=F)

library(tidyverse)
library(lubridate)

dt %>%
  separate_rows(Date, sep=";") %>%                     # separate dates
  group_by(Name, year = year(ymd(Date))) %>%           # for each Name and year of the date
  summarise(Fix = unique(Fix),                         # keep Fix
            Price = unique(Price),                     # keep Price
            Date = paste0(Date, collapse = ";")) %>%   # combine dates with same year
  mutate(Fix = ifelse(row_number() > 1, 0, Fix),       # update Fix values
         Price = Price/length(Price)) %>%              # divide Price by number of rows
  ungroup()                                            # forget the grouping

# # A tibble: 9 x 5
#   Name   year   Fix Price Date                 
#   <chr> <dbl> <dbl> <dbl> <chr>                
# 1 Alex   2018   505 238   2018-01-02;2018-02-02
# 2 Joe    2016    30  12.5 2016-01-04           
# 3 Joe    2017     0  12.5 2017-09-01           
# 4 John   2016   800 400   2016-01-03;2016-01-09
# 5 Mary   2016  1100 333.  2016-01-04           
# 6 Mary   2017     0 333.  2017-09-01;2017-08-10
# 7 Mary   2018     0 333.  2018-01-01           
# 8 Paul   2015   400 304   2015-01-02           
# 9 Tom    2016   600 500   2016-01-01

在单独的行 R 之后清除组中除第一行之外的变量

Clear the variables except first row in a group after separate row R

r

tail

tidyverse