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Expand data frame based on new column

I have the following framework:

df <- data.frame(
     month=c("July", "August", "August"),
     day=c(31, 1, 2),
     time=c(12, 12, 12))

   month day time
1   July  31   12
2 August   1   12
3 August   2   12

I have a text file times (decimal) and I want to replace the "time" column at all times from the text file. There are several days in the text file with over 300 entries for each.

7-31-2016 #the days are all concatenated together, this line represents the beginning of one day (July 31)
13.12344
13.66445
13.76892
...
8-1-2016 #here is another day (August 1)
14.50333
14.52000
14.53639
...

However, the text file is much longer than the current data frame - it contains 393 entries. So I would like the resulting data file to look something like this:

    month   day       time
5    July    31   13.12344
6    July    31   13.66445
7    July    31   13.76892
.....
393 August    1   14.50333
394 August    1   14.52000
394 August    1   14.53639

Basically, I just need to expand my current dataframe to match the number of records from the new file, keeping the same day. Hope this makes sense.

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3 answers 


# Create txt data
txt <- data.frame(x = c('7-31-2016', '13.12344', '13.66445', '13.76892', '8-1-2016', '14.50333', '14.52000', '14.53639'))
# Load Your data 
df <- data.frame(
  month=c("July", "August", "August"),
  day=c(31, 1, 2),
  time=c(12, 12, 12))

# Need a year to join dates
df$year <- 2016

# Create date column
df$date <- as.Date(paste0(df$month, "/", df$day, "/", df$year), format = "%B/%d/%Y")

# Find values with dashes, then replaces with /
txt$dash <- grepl('-', txt$x)
txt$x <- gsub("-", "/", txt$x)

# Adds new columns
library(dplyr)
txt <- mutate(txt, date = ifelse(dash==TRUE, as.Date(x, format = "%m/%d/%Y"), NA))
txt <- mutate(txt, time = ifelse(dash==FALSE, as.numeric(x), NA))

# Fill down values
library(zoo)
txt$date <- na.locf(txt$date)

# Removes NA and keeps necessary columns
txt <- txt[!is.na(txt$time),]
txt <- txt[c("date", "time")]

# Merge
output <- merge(df, txt, by = "date")


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So you want to concatenate an existing data.frame df

that only has 3 lines, with new_text

which has a lot. Using:

merge(df, new_text, all.y = T) #all.y will interpolate new rows for the ones that don't match


For more information see ?merge

.

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Make the txt file into a merge dataframe

:

 df$V2=as.numeric(df$V1)
 Temp=is.na(df$V2)
 df$V2=NA
 df$V2[Temp]=df$V1[Temp]
 df$V2=na.locf(df$V2)
 df=df[!Temp,]

        V1        V2
2 13.12344 7/31/2016
3 13.66445 7/31/2016
4 13.76892 7/31/2016
6 14.50333  8/1/2016
7    14.52  8/1/2016
8 14.53639  8/1/2016
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