This question already has answers here:
Convert the values in a column into row names in an existing data frame
(5 answers)
Closed 27 days ago.
I want to assign the first column as rownames of kirp.mut.
rownames(kirp.mut) <- kirp.mut[,1]
kirp.mut[,1] <- NULL
Traceback:
> rownames(kirp.mut) <- kirp.mut[,1]
Error in `.rowNamesDF<-`(x, value = value) : invalid 'row.names' length
In addition: Warning message:
Setting row names on a tibble is deprecated.
Dimensions:
> dim(kirp.mut)
[1] 283 8654
Class:
> class(kirp.mut)
[1] "tbl_df" "tbl" "data.frame"
typeof(kirp.mut)
[1] "list"
Data:
> dput(kirp.mut[1:10,1:10])
structure(list(sample_id = c("TCGA-2Z-A9J1-01A-11D-A382-10",
"TCGA-B9-A5W9-01A-11D-A28G-10", "TCGA-GL-A59R-01A-11D-A26P-10",
"TCGA-2Z-A9JM-01A-12D-A42J-10", "TCGA-A4-A57E-01A-11D-A26P-10",
"TCGA-BQ-7044-01A-11D-1961-08", "TCGA-HE-7130-01A-11D-1961-08",
"TCGA-UZ-A9Q0-01A-12D-A42J-10", "TCGA-HE-A5NI-01A-11D-A26P-10",
"TCGA-WN-A9G9-01A-12D-A36X-10"), NBPF1 = c(1, 0, 0, 0, 0, 0,
0, 0, 0, 0), CROCC = c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0), SF3A3 = c(1,
0, 0, 0, 0, 0, 0, 0, 0, 0), GUCA2A = c(1, 0, 0, 0, 0, 0, 0, 0,
0, 0), RAVER2 = c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0), ACADM = c(1,
0, 0, 0, 0, 0, 0, 0, 0, 0), PDE4DIP = c(1, 0, 0, 0, 0, 0, 0,
0, 0, 0), NUP210L = c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0), NCF2 = c(1,
0, 0, 0, 0, 0, 0, 0, 0, 0)), row.names = c(NA, -10L), class = c("tbl_df",
"tbl", "data.frame"))
A tibble cannot have row names assigned. You could convert it to another format, such as a data frame, then assign row names. You can also do this tidyverse solution using column_to_rownames on your tibble without explicitly converting to another form, but it will do so internally and return a data.frame:
library(tidyverse)
library(dplyr)
kirp.mut <- kirp.mut %>%
column_to_rownames(var = "sample_id")
See the technical documentation here on row names and tibbles
Convert to matrix, excluding 1st column, then assign rownames:
m <- as.matrix(kirp.mut[, -1])
rownames(m) <- kirp.mut$sample_id
Or to a dataframe
#convert tibble to data.frame, then add rownames
df <- as.data.frame(kirp.mut[, -1])
rownames(df) <- kirp.mut$sample_id
Related
I have a dataframe where each column is made up of zero along with one other number. For example:
I want to manipulate the dataframe so that columns that contain the same other number become one column where the value stays as the other number if the other number was present in every row, otherwise it turns to zero.
So for instance, I would want the dataframe above to look like
..1 ..2 ..3
1 2 3
0 2 0
0 0 0
1 0 0
The first row of the dataframe is 1 because the values were both 1 in the first row of the original. The second row of the first column is 0 because there were a 1 and a 0 in the row.
Here is some reproducible data:
structure(list(...1 = c(1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), ...2 = c(1, 0,
0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0), ...3 = c(2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), ...4 = c(3,
0, 0, 3, 0, 0, 0, 0, 3, 0, 0, 3, 0, 0, 0, 0, 3, 0, 0, 3, 0, 0,
0, 0, 0, 0, 0, 0), ...5 = c(3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), ...6 = c(3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)), row.names = c(NA,
-28L), class = "data.frame")
Here is a possible solution in base R, where dat is the data frame you provide in the question. We find the unique value for each column, assuming there is only one nonzero value in each column. Then we loop through the groups of columns with each unique value, applying the function all() to each row of the subsetted dataframe to identify rows with all nonzero values. Multiply the resulting logical vector by the value itself to get the desired result. Then store this vector in a list and bind to a data frame.
col_vals <- apply(dat, 2, max)
columns <- list()
for (val in unique(col_vals)) {
columns[[length(columns) + 1]] <- val * apply(dat[, col_vals == val, drop = FALSE], 1, all)
}
as.data.frame(do.call(cbind, columns))
I have a data frame that look something like this
> dput(tes)
structure(list(path = structure(1:6, .Label = c("1893-chicago-fair",
"1960s-afghanistan", "1970s-iran", "1980s-new-york", "20-bizarre-vintage-ads",
"20-bizarre-vintage-ads?utm_campaign=6678&utm_medium=rpages&utm_source=Facebook&utm_term=1e8e704f7b587515c72e6cf7895d55fd110b652c480d98c1440f0a7acba5fb0e",
"20-photos-segregation-america-show-far-weve-come-much-farther-go",
"7-bizarre-cultural-practices", "7-creepy-abandoned-cities?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=4015a7368b588ff09694c96ba720c58f4e7f41a05b4181908b582bae682bef5e",
"a-brief-history-of-hippies", "abandoned-photographs", "albert-kahn",
"amazing-facts", "american-bison-extinction-1800s", "american-english-vs-british-english",
"andre-the-giant-photos", "andre-the-giant-photos??utm_source=facebook&sr_source=lift_facebook&utm_campaign=simplereach_andre-the-giant-photos&utm_medium=social",
"andre-the-giant-photos?grvVariant=d27feef0bfad84d60f335d3a8d241d9e",
"andre-the-giant-photos?grvVariant=d27feef0bfad84d60f335d3a8d241d9e&utm_campaign=gravityus2_142deb68f67fb1a99e7b80250fecc932&utm_medium=referral&utm_source=gravity",
"andre-the-giant-photos?grvVariant=d27feef0bfad84d60f335d3a8d241d9e&utm_campaign=gravityus2_16d63cf07ecf656f602b2d6b209344f7&utm_medium=referral&utm_source=gravity",
"andre-the-giant-photos?grvVariant=d27feef0bfad84d60f335d3a8d241d9e&utm_campaign=gravityus2_713050ecffc51540af02b2246ddf57dd&utm_medium=referral&utm_source=gravity",
"andre-the-giant-photos?grvVariant=d27feef0bfad84d60f335d3a8d241d9e&utm_campaign=gravityus2_c5bb3bc5e9408e0ad52ec9e787bd8654&utm_medium=referral&utm_source=gravity",
"andre-the-giant-photos?sr_source=lift_facebook&utm_campaign=simplereach_andre-the-giant-photos&utm_medium=social&utm_source=facebook",
"astounding-aerial-photography", "astounding-aerial-photography?utm_campaign=7002&utm_medium=rpages&utm_source=Facebook&utm_term=38e9e903d9ba59106d8b4d19be593f3de7ff8b91b12eafa03f2e382228f7b0d1",
"august-landmesser", "ben-franklin", "best-all-that-is-interesting-articles",
"bigfoot-facts", "celebrity-school-photos?grvVariant=82c0ce57a33dfd0209bdefc878665de0&utm_campaign=gravityus2_bc8646aefd6d0a16af03d7caf248f226&utm_medium=referral&utm_source=gravity",
"coolest-mushrooms?utm_campaign=taboolaINTL&utm_medium=referral&utm_source=taboola",
"craziest-ways-drugs-smuggled", "creepy-halloween-costumes",
"danakil-depression", "dark-john-lennon-quotes", "david-bowie-quotes",
"days-in-groundhog-day", "death-photos", "death-photos?utm_campaign=taboolaINTL&utm_medium=referral&utm_source=taboola",
"dr-seuss-quotes", "dream-chaser-spacecraft", "dust-bowl", "earth-two-planets",
"eixample-barcelona", "email-to-space", "evil-science-experiments",
"famous-incest", "famous-spies", "fun-facts-trivia", "golden-age-air-travel?utm_campaign=taboolaINTL&utm_medium=referral&utm_source=taboola",
"gross-foods", "gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=106965c54919c24bf37356500ec50f0709b1de621d6950bb4c5d48759ea3677e",
"gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=184e0ee39e66af82f9b124b904f6e07964b211e902cb0dc00c28771ff46163a2",
"gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=1a0ddea7bed770d5473c45e9f8d81dfd0c4fdd232f207c6b88b53c41ff220c59",
"gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=538659f1fc53f28d2c87b93ac73973681c1a46a04954964ab6c52ed1ab09b33a",
"gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=87caf0acb91ae2b202f1b00ad9eaad3fef20bbfb23405b9047fb2b5a5462ab9c",
"gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=91eae42c8fc9568103d46e0b6b6ec08fc34fd68b2e1918ffe2333ec73035c95a",
"gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=a72946874b2003a8e40635c6cf10c851d4e1c0ed45e645d69663214239550602",
"gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=ab594f0a1be002c8c3db297e8d33b04678af40e6a6469ac815884ae0a014b3a3",
"gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=fb1e333dd58cb7bb9251ec52290aae21771149f73e083440047068a69aaeae09",
"hilarious-insults", "hippie-communes", "hippie-communes?grvVariant=fda07538efb1c25617f7cc3d09c37c79",
"hippie-communes?grvVariant=fda07538efb1c25617f7cc3d09c37c79&utm_campaign=gravityus2_e3cd42d4745768460dab4694a972fd82&utm_medium=referral&utm_source=gravity",
"hippie-communes?pp=0", "history-of-the-vibrator", "history-of-the-vibrator?utm_campaign=whfbpd&utm_medium=social&utm_source=facebook",
"homosexuality-norm", "hunger-games-facts?utm_campaign=6905&utm_medium=rpages&utm_source=Facebook&utm_term=1a9e42ac8abb6ffa90bf0542206505e74d3df12114a2c4445527fb2b88ef8880",
"influential-photographs", "ingeniously-creative-ads", "insane-cults",
"insane-rulers", "inspirational-quotes", "inspirational-quotes?utm_medium=referral&utm_source=taboolainternal",
"interesting-facts-about-the-world", "interesting-quotes", "krokodil",
"making-a-murderer-theories", "maya-angelou-greatest-quotes",
"medieval-torture-devices", "milky-way-colorado", "montreal-metro",
"most-popular-female-names-in-america", "neil-degrasse-tyson-tweets",
"new-york-city-cinemagraphs", "new-york-subways-1980s", "north-korea-photographs",
"north-korea-photographs?utm_campaign=taboolaINTL&utm_medium=referral&utm_source=taboola",
"north-korea-photographs?utm_medium=referral&utm_source=taboolainternal",
"obama-aging", "pablo-escobar", "pablo-escobar??utm_source=facebook",
"pablo-escobar??utm_source=facebook&sr_source=lift_facebook&utm_campaign=simplereach_pablo-escobar&utm_medium=social",
"pablo-escobar?utm_campaign=whfbpd&utm_medium=social&utm_source=facebook",
"panda-facts", "photo-of-the-day-nasa-releases-crystal-clear-image-of-pluto",
"pollution-in-china-photographs", "pollution-in-china-photographs?utm_campaign=3434&utm_medium=rpages&utm_source=Facebook&utm_term=1a0ddea7bed770d5473c45e9f8d81dfd0c4fdd232f207c6b88b53c41ff220c59",
"pollution-in-china-photographs?utm_campaign=3434&utm_medium=rpages&utm_source=Facebook&utm_term=e28a76c1572c36c3a13965e52b4b2ea10518eb9f9c79c4bc84cfb85db16be81e",
"pollution-in-china-photographs?utm_campaign=6806&utm_medium=rpages&utm_source=Facebook&utm_term=1a0ddea7bed770d5473c45e9f8d81dfd0c4fdd232f207c6b88b53c41ff220c59",
"pollution-in-china-photographs?utm_campaign=7048&utm_medium=rpages&utm_source=Facebook&utm_term=2ef4bd7b6cd587601d6eeb35925282a1ed095ebbd4e9e4c0337ef868c7de7a0b",
"pollution-in-china-photographs?utm_campaign=7458&utm_medium=rpages&utm_source=Facebook&utm_term=b9e79a51cd4daf4c3ec02accce75b3e1fc9a22cb3133460c9c32a4f2f9cdb68c",
"powerful-photos-of-2014", "real-x-files", "romanovs-last-days",
"science-of-human-decay", "scientific-discoveries-2015", "scully-effect",
"serial-killer-quotes", "shah-iran", "six-of-the-craziest-gods-in-mythology",
"space-facts", "sun-facts", "sunken-cities", "sunken-ships",
"super-bowl-i-facts", "superhero-movies", "surreal-places", "syrian-civil-war-photographs",
"the-five-greatest-mysteries-of-human-history", "the-four-most-important-battles-of-ancient-greece",
"the-most-colorful-cities-in-the-world", "titanic-facts", "titanic-facts?utm_campaign=6385&utm_medium=rpages&utm_source=Facebook&utm_term=f5905e878216d14e20457ee3265caf6c10022d9545609edfb9a3cb0642c1a310",
"titanic-facts?utm_campaign=6899&utm_medium=rpages&utm_source=Facebook&utm_term=b9e79a51cd4daf4c3ec02accce75b3e1fc9a22cb3133460c9c32a4f2f9cdb68c",
"titanic-facts?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=106965c54919c24bf37356500ec50f0709b1de621d6950bb4c5d48759ea3677e",
"titanic-facts?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=538659f1fc53f28d2c87b93ac73973681c1a46a04954964ab6c52ed1ab09b33a",
"titanic-facts?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=91eae42c8fc9568103d46e0b6b6ec08fc34fd68b2e1918ffe2333ec73035c95a",
"titanic-facts?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=ab594f0a1be002c8c3db297e8d33b04678af40e6a6469ac815884ae0a014b3a3",
"titanic-facts?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=d1864657a05e5b716bb5cb16a29f068a55652eb39fb669ea9c22a6486198f227",
"titanic-facts?utm_campaign=7292&utm_medium=rpages&utm_source=Facebook&utm_term=f5905e878216d14e20457ee3265caf6c10022d9545609edfb9a3cb0642c1a310",
"us-veterans-portraits", "vintage-disneyland", "wall-street-early-20th-century",
"what-we-love-this-week-the-incredible-last-words-of-famous-historical-figures",
"woodstock-photos", "zombie-proof-house"), class = "factor"),
`0089` = c(0, 0, 0, 0, 0, 1), `0096` = c(0, 0, 0, 0, 0, 0
), `02` = c(0, 0, 0, 0, 0, 0), `0215` = c(0, 0, 0, 0, 0,
0), `0225` = c(0, 0, 0, 0, 0, 0), `0252` = c(0, 0, 0, 0,
0, 0), `0271` = c(0, 0, 0, 0, 0, 0), `0272` = c(0, 0, 0,
0, 0, 0), `03` = c(0, 0, 0, 0, 1, 1)), .Names = c("path",
"0089", "0096", "02", "0215", "0225", "0252", "0271", "0272",
"03"), row.names = c(NA, 6L), class = "data.frame")
and I need to apply the min(x,1) function such that this function scan each value in the dataframe (except first column which is not numeric) and return the min(x,1). that way I have only zero's and one's.
I have tried:
f <- function(x) min(1,x)
res1<-do.call(f,tes[,2:ncol(tes)])
but that does not output the right result.
Any help aapreciated
We can use pmin
tes[,-1] <- pmin(1, as.matrix(tes[,-1]))
Or if we need only binary values
tes[,-1] <- +(!!tes[,-1])
I have a data frame df in the following form:
v2 v3
2.3 c(1,5,8,2)
1.2 c(2,4,3,2)
The typeof(df$v3[1]) is list, and I want to convert it to vector. So I write a `sapply`` function and run it:
df$v3 <- sapply(
df$v3,
function(x) {x <- unlist(x)}
)
But it just keeps running and does not generate any result. I also tried lapply but it can't give me the expected result. Instead, it again generates a list.
Any my dput(droplevels(head(df))) result is :
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0))), .Names = c("V2", "V3"), row.names = c(NA,
-6L), .internal.selfref = <pointer: 0x102010578>, class = c("data.table", "data.frame"))
Could you please tell me how to solve it?
EDIT:
I run the df$V3 <- unlist(df$V3) for a long time. But the type is still list and a warning is generated:
Warning messages:
1: In `[<-.data.table`(x, j = name, value = value) :
Supplied 496450000 items to be assigned to 99290 items of column 'V3' (496350710 unused)
2: In `[<-.data.table`(x, j = name, value = value) :
Coerced 'double' RHS to 'list' to match the column's type; may have truncated precision. Either change the target column to 'double' first (by creating a new 'double' vector length 99290 (nrows of entire table) and assign that; i.e. 'replace' column), or coerce RHS to 'list' (e.g. 1L, NA_[real|integer]_, as.*, etc) to make your intent clear and for speed. Or, set the column type correctly up front when you create the table and stick to it, please.
I was wondering if there was a way to select specific columns via a sequence and create new variables from this.
So for example, if I had 8 columns with n observations, how could I create 4 variables that selects 2 rows sequentially? My dataset is much larger than this and I have 1416 variables with 62 observations each (I have pasted a link to the spreadsheet below, whereby the first column and row represent names). I would like to create new dataframes from this named as sites 1-12. So site 1 = df[,1:117]; site 2 = df [,119:237] etc.
I am planning on using this code for future datasets with even more variables so some form of loop or sequence function would be very effective if anyone could shed any light on how to achieve this?
https://www.dropbox.com/s/p1a5cu567lxntmw/MyData.csv?dl=0
Thank you in advance.
James
p.s #nrussell I have copied and pasted the output of the code you mentioned below, it follows on as a series of numbers like those displayed.
dput(z[ , 1:10])
structure(list(1 = c(0, 0, 0, 0, 0, 0, 0, 0, 0.0311410340342049,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0.0207444023791158, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0312971643732546,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0376287494579976, 0, 0, 0, 0, 0,
0, 0),......... 10 = c(0, 0, 0, 0, 0.119280313679916,
0, 0, 0.301029995663981, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.715681882079494,
0.136831816210901, 0, 0, 0, 0.0273663632421801, 0, 0, 0, 0.0547327264843602,
0, 0, 0, 0, 0.0231561535126139, 0, 0, 0.0903089986991944, 0,
0, 0.0752574989159953, 0.159368821233872, 0.0272640716982664,
0.0177076468037636, 0, 0, 0.120411998265592, 0, 0, 0, 0, 0.0322532138211408,
0.0250858329719984, 0, 0, 0, 0.119280313679916, 0, 0.172922500085254,
0.225772496747986, 0, 0, 0, 0.0954242509439325, 0)), .Names = c("1",
"2", "3", "4", "5", "6", "7", "8", "9", "10"), class = "data.frame", row.names = c(NA,
-62L))
We could split the dataset ('df') with '1416' columns to equal size '118' columns by creating a grouping index with gl
lst <- setNames(lapply(split(1:ncol(df), as.numeric(gl(ncol(df), 118,
ncol(df)))), function(i) df[,i]), paste0('site', 1:12))
Or you can create the 'lst' without using the split
lst <- setNames(lapply(seq(1, ncol(df), by = 118),
function(i) df[i:(i+117)]), paste0('site', 1:12))
If we need to create 12 dataset objects in the global environment, list2env is an option (I would prefer to work within the 'lst' itself)
list2env(lst, envir=.GlobalEnv)
Using a small dataset ('df1') with '8' columns
lst1 <- setNames(lapply(split(1:ncol(df1), as.numeric(gl(ncol(df1),
2, ncol(df1)))), function(i) df1[,i]), paste0('site', 1:4))
list2env(lst1, envir=.GlobalEnv)
head(site1,3)
# V1 V2
#1 6 12
#2 4 7
#3 14 14
head(site4,3)
# V7 V8
#1 10 2
#2 5 4
#3 5 0
data
set.seed(24)
df1 <- as.data.frame(matrix(sample(0:20, 8*10, replace=TRUE), ncol=8))
I'd like to melt the dataframe so that in one column I have dates and in a second I have username as the variable and finally the value.
I'm getting this error:
Error in as.Date.numeric(value) : 'origin' must be supplied
and while I understand the error I'm not exactly sure how to get around it.
A small sample of the data is:
structure(list(created_at = structure(c(14007, 14008, 14009,
14010, 14011, 14012), class = "Date"), benjamin = c(16, 0, 0,
0, 0, 0), byron = c(0, 0, 0, 0, 0, 0), cameronc = c(0, 0, 0,
0, 0, 0), daniel = c(0, 0, 0, 0, 0, 0), djdiaz = c(0, 0, 0, 0,
0, 0), gene = c(16, 77, 64, 38, 72, 36), joel = c(0, 0, 0, 0,
0, 2), kerem = c(0, 0, 0, 0, 0, 0), sophia = c(0, 0, 0, 0, 0,
0), SuperMoonMan = c(0, 0, 0, 0, 0, 0)), .Names = c("created_at",
"benjamin", "byron", "cameronc", "daniel", "djdiaz", "gene",
"joel", "kerem", "sophia", "SuperMoonMan"), row.names = c(NA,
6L), class = c("cast_df", "data.frame"))
Thanks for your help.
Try converting the created_at variable into a character vector. melt also doesn't seem to like the cast_df class, but I had success by resetting the class to just data.frame. Like so:
df <- as.data.frame(df)
df$created_at <- as.character(df$created_at)
library(reshape)
melt(df)
You error is caused by rbind used in melt, which is consequence of wrong data to melt. I don't know how you create your cast_df data.frame, but it missing attributes (idvars and rdimnames) which are required by melt.cast_df.
That is why wkmor1 solution works, melt.data.frame don't need this arguments. And without converting Date to character it can be done as:
df <- as.data.frame(df)
melt(df, id="created_at")