Remove single characters without changing the numbers from an r dataframe - r

Question

My dataframe has many arrows, ">" and "<"s in it alongside some of the element values. I want to remove these characters but keep the numbers. I only know how to replace the entire element with NA with the following code.
df <- apply(df, 1:2, gsub, pattern = "<|>", replacement = "")
Will someone please help me edit this so that it keeps the element numbers too, instead of throwing the entire thing out?
Dataframe:
structure(list(`Analyte Sample` = c(1, 2, 3, 4, 5, 6, 7, 8,
9, 10, 11, 12, 13, 14), A = c("4190", "6665", "7435", "2052",
"783", "322", "199", "90", "46", "17", "8", "3", "3", "<1↓"
), B = c("11569", "6677", "3852", "983.88", "589", "359", "203",
"68", "33", "12", "6", "<2↓", "4", "<1↓"), C = c("20453",
"7699", "2499", "707.98", "412", "328", "156", "88", "39", "27",
"17", "<1↓", "<3↓", "<1↓"), D = c("7893", ">20000↑",
"1623", "685.64", "321", "644", "112", "65", "35", "29", "9",
"5", "<3↓", "<1↓"), E = c("320", "15444", "2049", "1065",
"389", "365", "145", "77", "38", "16", "9", "6", "<2↓", "<2↓"
), F = c("7438", ">21999↑", "3472", "1057", "563", "401", "167",
"89", "46", "19", "6", "<1↓", "<1↓", "<1↓"), G = c(7345,
9001, 2473, 1138, 516, 403, 134, 81, 37, 17, 8, 6, 4, 3), H = c("9004",
"3998", "2299", "964.88", "499", "341", "112", "88", "39", "32",
"<29↓", "<30↓", "<31↓", "<29↓"), I = c("8434", "8700",
"2217", "1263", "567", "352", "153", "80", "43", "18", "9", "2",
"3", "<1↓"), J = c("7734", "6733", "2092", "1115", "637", "332",
"155", "82", "37", "17", "10", "4", "1", "<1↓"), K = c(">3718↑",
">3000↑", "2118", "862.13", "426", "355", "143", "78", "44",
"22", "11", "<4↓", "<4↓", "<3↓"), L = c(6345, 7688, 2311,
1195, 647, 366, 177, 83, 41, 20, 8, 6, 3, 2), M = c("4222", ">25587↑",
"1846", "814.61", "422", "314", "154", "86", "41", "27", "21",
"<2↓", "<2↓", "<3↓"), N = c("6773", "8934", "2381", "1221",
"677", "356", "146", "89", "40", "17", "10", "5", "2", "<2↓"
), O = c(">2200↑", ">2133↑", ">2000↑", "564.5", "226",
"476", "111", "60", "32", "36", "18", "<10↓", "<1↓", "<2↓"
)), class = c("spec_tbl_df", "tbl_df", "tbl", "data.frame"), row.names = c(NA,
-14L), spec = structure(list(cols = list(`Analyte Sample` = structure(list(), class = c("collector_double",
"collector")), A = structure(list(), class = c("collector_character",
"collector")), B = structure(list(), class = c("collector_character",
"collector")), C = structure(list(), class = c("collector_character",
"collector")), D = structure(list(), class = c("collector_character",
"collector")), E = structure(list(), class = c("collector_character",
"collector")), F = structure(list(), class = c("collector_character",
"collector")), G = structure(list(), class = c("collector_double",
"collector")), H = structure(list(), class = c("collector_character",
"collector")), I = structure(list(), class = c("collector_character",
"collector")), J = structure(list(), class = c("collector_character",
"collector")), K = structure(list(), class = c("collector_character",
"collector")), L = structure(list(), class = c("collector_double",
"collector")), M = structure(list(), class = c("collector_character",
"collector")), N = structure(list(), class = c("collector_character",
"collector")), O = structure(list(), class = c("collector_character",
"collector"))), default = structure(list(), class = c("collector_guess",
"collector")), skip = 1), class = "col_spec"))

Answer 1

You can use lapply() which returns a list and assign it back to df[]. [] is to keep the original attributes, i.e. a class of data.frame. You will see that df becomes what you want.
df[] <- lapply(df, gsub, pattern = "<|>", replacement = "")

Answer 2

I think in your case the best would be to use a regular expression. Using tidyverse:
df %>% mutate_at(vars(A:O), ~ as.numeric(gsub("[^0-9]*([0-9]*).*", "\\1", .)))
If you specifically want only to change values which start with a < or >, you do the following:
df %>% mutate_at(vars(A:O), ~ as.numeric(gsub("[<>]*([0-9]*).*", "\\1", .)))
Of course, you can also use apply... but mind the way apply changes the data frame into a matrix before applying the function (the columns which are numbers will have spaces prefixed, so we need to include space in the pattern):
apply(df, 2, function(x) gsub("[ <>]*([0-9]*).*", "\\1", x))
Explanation:
The pattern [0-9]* matches a digit any number of times. The pattern [^0-9] matches anything but a digit any number of times.

Answer 3

You can try one of these options:
#Code 1
df <- apply(df, 1:2, function(x) gsub(pattern = "<|>", replacement = "",x))
#Code 2
df <- sapply(df,function(x) gsub(pattern = "<|>", replacement = "",x))
Just be careful that the output can be a matrix, so you will have to transform again to dataframe using as.data.frame().