R 在空白处拆分列并替换数据

Question

I have a dataframe that looks like this:

Data

structure(list(col1 = c("Arizona", "Florida", "Montreal"), col2 = c("5½ -130", 
"5 -135", "5½ -125")), row.names = c(NA, -3L), class = "data.frame")

Col1     Col2
Arizona  5½ -130
Florida  5 -135
Montreal 5½ -125

I need it to look like this (splitting Col2 into two columns based on " " AND replacing ½ with.5)

Col1      Col2     Col3
Arizona   5.5       -130
Florida   5         -135
Montreal  5.5       -125

Answer 1

https://tidyr.tidyverse.org/reference/separate.html

    libarary(tidyverse)
    df <- data.frame( 
              Team = c("Arizona","Florida","Montreal"),     
              Col2 = c("5½ -130", "5 -135", "5½ -125")
    )

 new_df <-  separate(df, 2, into=c("odds", "payout100"), sep= " ")


   new_df
          Team  odds    payout100
    1  Arizona   5½      -130
    2  Florida    5      -135
    3 Montreal   5½      -125

   new_df$odds <- as.numeric(str_replace_all(new_df$odds, "5[^ ]", "5.5"))

    new_df

         Team   odds     payout100
    1  Arizona  5.5      -130
    2  Florida  5.0      -135
    3 Montreal  5.5      -125

The call to stringr::str_replace_all changes a 5 followed by anything other than a space to 5.5. This assumes that the only character to follow the integers will be the 1/2 which is an unusual character (not a digit or a letter).

The call

         str_replace_all(new_df$odds, "([0-9]+)[^ ]", "\\1.5")

makes the same change for all numbers that might start the odds. Note stringr is loaded automatically when you load the tidyverse package.

Also note that I made up the new column names. It looks like something do with betting on the NHL playoffs so I based my column names on that. Otherwise the arguments I used are the data frame object, the position of column being split (2), and what charcater(s) is/are used to separate the column. In this case, a blank space.

Answer 2

using data from @Tho Vu:

> df %>% 
    separate( col2, into=c("Col2", "Col3"), sep= " ") %>% 
    mutate(Col2 = gsub("½", ".05", Col2) %>% as.numeric)
      col1 Col2 Col3
1  Arizona 5.05 -130
2  Florida 5.00 -135
3 Montreal 5.05 -125

Answer 3

You can try this approach

library(tidyverse)
library(stringr)
df <- structure(list(col1 = c("Arizona", "Florida", "Montreal"), 
                     col2 = c("5½ -130", "5 -135", "5½ -125")), row.names = c(NA, -3L), class = "data.frame")

df2 <- df %>% 
  mutate(col3 = str_extract_all(col2, regex("(-.*)")), 
     col2 = str_replace_all(col2, regex("(-.*)"), ""),
     col2 = str_replace_all(col2, regex("½"), ".5"))

df2$col2 <- as.numeric(df2$col2)

#       col1 col2 col3
# 1  Arizona 5.5  -130
# 2  Florida 5.00 -135
# 3 Montreal 5.5  -125