Gathering multiple data columns currently in factor form - r

Question

I have a dataset of train carloads. It currently has a number (weekly carload) listed for each company (the row) for each week (the columns) over the course of a couple years (100+ columns). I want to gather this into just two columns: a date and loads.
It currently looks like this:
3/29/2017 4/5/2017 4/12/2017 4/19/2017
32.7 31.6 32.3 32.5
20.5 21.8 22.0 22.3
24.1 24.1 23.6 23.4
24.9 24.7 24.8 26.5
I'm looking for:
Date Load
3/29/2017 32.7
3/29/2017 20.5
3/29/2017 24.1
3/29/2017 24.9
4/5/2017 31.6
I've been doing various versions of the following:
rail3 <- rail2 %>%
gather(`3/29/2017`:`1/24/2018`, key = "date", value = "loads")
When I do this it makes a dataset called rail3, but it didn't make the new columns I wanted. It only made the dataset 44 times longer than it was. And it gave me the following message:
Warning message:
attributes are not identical across measure variables;
they will be dropped
I'm assuming this is because the date columns are currently coded as factors. But I'm also not sure how to convert 100+ columns from factors to numeric. I've tried the following and various other methods:
rail2["3/29/2017":"1/24/2018"] <- lapply(rail2["3/29/2017":"1/24/2018"], as.numeric)
None of this has worked. Let me know if you have any advice. Thanks!

Answer 1

If you want to avoid warnings when gathering and want date and numeric output in final df you can do:
library(tidyr)
library(hablar)
# Data from above but with factors
rail2<-read.table(header=TRUE, text="3/29/2017 4/5/2017 4/12/2017 4/19/2017
32.7 31.6 32.3 32.5
20.5 21.8 22.0 22.3
24.1 24.1 23.6 23.4
24.9 24.7 24.8 26.5", check.names=FALSE) %>%
as_tibble() %>%
convert(fct(everything()))
# Code
rail2 %>%
convert(num(everything())) %>%
gather("date", "load") %>%
convert(dte(date, .args = list(format = "%m/%d/%Y")))
Gives:
# A tibble: 16 x 2
date load
<date> <dbl>
1 2017-03-29 32.7
2 2017-03-29 20.5
3 2017-03-29 24.1
4 2017-03-29 24.9
5 2017-04-05 31.6

Answer 2

Here is a possible solution:
rail2<-read.table(header=TRUE, text="3/29/2017 4/5/2017 4/12/2017 4/19/2017
32.7 31.6 32.3 32.5
20.5 21.8 22.0 22.3
24.1 24.1 23.6 23.4
24.9 24.7 24.8 26.5", check.names=FALSE)
library(tidyr)
# gather the data from columns and convert to long format.
rail3 <- rail2 %>% gather(key="date", value="load")
rail3
# date load
#1 3/29/2017 32.7
#2 3/29/2017 20.5
#3 3/29/2017 24.1
#4 3/29/2017 24.9
#5 4/5/2017 31.6
#6 4/5/2017 21.8
#7 ...