I can't figure out why this version of plyr's rename function isn't working.
I have a dataframe where I have a single column that ends up being named seq(var_slcut_trucknumber_min, var_slcut_trucknumber_max) because I made it like this:
df_metbal_slcut <- as.data.frame(seq(var_slcut_trucknumber_min,var_slcut_trucknumber_max))
The terms var_slcut_trucknumber_min and var_slcut_trucknumber_max are defined as the min and max of another column.
However, when trying to rename it by the following code,
var_temp <- names(df_metbal_slcut)
df_metbal_slcut <- rename(df_metbal_slcut, c(var_temp="trucknumber"))
I get an error as follows:
The following `from` values were not present in `x`: var_temp
I don't understand why. I know that I can easily do this as colnames(df_metbal_slcut)[1] <- "trucknumber", but I'm an R n00b, and I was looking at a data manipulation tutorial that said that learning plyr was the way to go, so here I am stuck on this.
Try this instead:
df_metbal_slcut <- rename(df_metbal_slcut, setNames("trucknumber",var_temp))
The reason it wasn't working was that c(var_temp = "trucknumber") creates a named vector with the name var_temp, which is not what you were intending. When creating named objects using the tag = value syntax, R won't evaluate variables. It assumes that you literally want the name to be var_temp.
More broadly, it might make sense to name the column more sensibly when initially creating the data frame again using setNames.
Related
I want to create a pivot table from my data set in excel to R. I have been following this tutorial on how to do this: http://excel2r.com/pivot-tables-in-r-basic-pivot-table-columns-and-metrics/ . I have used the codes mentioned in this tutorial by replacing it with my own data variables, but I keep getting an error message noting: Error: select() doesn't handle lists.
What does this error message mean and how I can I fix this?
The R-Script I have been using from the tutorial is:
library(dplyr)
library(tidyr)
pivot <- df %>%
select(Product.Category, Region, Customer.Segment, Sales)%>%
group_by(Product.Category, Region, Customer.Segment) %>%
summarise(TotalSales = sum(Sales))
Thank you in advance for the help!
By your error message: "select() doesn't handle lists.", I supose that your object called df isn't a dataframe.
Maybe you have a dataframe inside a list.
Try this in your R console:
class(df)
If the class is a list, you need take off the dataframe from the list. You can do this by the position. Probably in the first position. df[[1]]
The functions that you are using, works only for dataframes in general. (And tibbles, that is a another type of dataframe)
Like this example:
I hope it works for you.
And, for the next time, try to make an reproducible example.
You could at least print your dataframe original, before try to use these functions, that way I could help you efficiently.
I am trying to take R code, stored in cells of the content column of a dataframe, and analyze the functions used by applying the Tidycode package. However, I first need to convert the data to a Matahari tibble before applying an unnest_calls() function.
Here is the data:
data <- read.csv("https://github.com/making-data-science-count/TidyTuesday-Analysis/raw/master/db-tmp/cleaned%20database.csv")
I have tried doing this in a number of different ways, including extracting each row (in the content column ) as an Rfile and then reading it back in with Tidycode calls, for example:
tmp<-data$content2[1])
writeLines(tmp, "tmp.R") #I've also used save() and write()
rfile<-tidycode::read_rfiles("tmp.R")
But, I keep getting errors such as: "Error in parse(text = x) : <text>:1:14: unexpected symbol
1: library(here)library"
Ultimately, what I would like to do is analyze the different types of code per file, and keep that linked with the other data in the data dataframe, such as date and username.
Any help would be greatly appreciated!
I want to load dataset from package ElemStatLearn in R studio.
But when I load the dataset, my Global Environment panel shows
library("ElemStatLearn")
data("nci")
However, when I execute
View("nci")
I can see the whole data but cannot export it to a dataframe.
How can I convert or export this dataset into a dataframe?
You can do
df <- data.frame(nci)
Another way to go around would be
df <- get(data("nci"))
If you had done anything with the name nci that required it's modification or evaluation, the R engine would have at that point pulled in the values and you would no longer have had a promise. Instead, you asked to look not at an R name but at an R literal character value. The value of "nci" is just "nci". The value of nci on the other hand has 6,830 entries when I try to look at it.
The data function can accept a character value for purposes of retrieving an externally stored object, but the View function expects a real (unquoted) R name. Or you could have used: View(as.name("nci") )
I'm brand new to R and am having difficulty with something very basic. I'm importing data from an excel file like this:
data1 <- read.csv(file.choose(), header=TRUE)
When I try to look at the data in the table by column, R doesn't recognize the column headers as objects. This is what it looks like
summary(Square.Feet)
Error in summary(Square.Feet) : object 'Square.Feet' not found
I need to run a regression and I'm having the same problem. Any help would be much appreciated.
Yes it recognizes, you have to tell R to select the dataframe so:
summary(data1$Square.Feet)
Where "data" is the name of your dataframe, and after the dollar goes the name of the variable
Hope it helps
UPDATE
As suggested below, you can use the following:
data1 <- read.csv(file.choose(), header=TRUE)
attach(data1)
This way, by doing "attach", you avoid to write everytime the name of the dataset, so we would go from
summary(data1$Square.Feet)
To this point after attaching the data:
summary(Square.Feet)
However I DO NOT recommend to do it, because if you load other datasets you may mess everything as it's quite common that variables have the same names, among other major problems, see here (Thanks Ben Bolker for your contribution): here , here, here and
here
if you want a summary of all data fields, then
summary(data1)
or you can use the 'with' helper function
with(data1, summary(Square.Feet))
I using the Alteryx R Tool to sign an amazon http request. To do so, I need the hmac function that is included in the digest package.
I'm using a text input tool that includes the key and a datestamp.
Key= "foo"
datastamp= "20120215"
Here's the issue. When I run the following script:
the.data <- read.Alteryx("1", mode="data.frame")
write.Alteryx(base64encode(hmac(the.data$key,the.data$datestamp,algo="sha256",raw = TRUE)),1)
I get an incorrect result when compared to when I run the following:
write.Alteryx(base64encode(hmac("foo","20120215",algo="sha256",raw = TRUE)),1)
The difference being when I hardcode the values for the key and object I get the correct result. But if use the variables from the R data frame I get incorrect output.
Does the data frame alter the data in someway. Has anyone come across this when working with the R Tool in Alteryx.
Thanks for your input.
The issue appears to be that when creating the data frame, your character variables are converted to factors. The way to fix this with the data.frame constructor function is
the.data <- data.frame(Key="foo", datestamp="20120215", stringsAsFactors=FALSE)
I haven't used read.Alteryx but I assume it has a similar way of achieving this.
Alternatively, if your data frame has already been created, you can convert the factors back into character:
write.Alteryx(base64encode(hmac(
as.character(the.data$Key),
as.character(the.data$datestamp),
algo="sha256",raw = TRUE)),1)