At the moment I am selecting columns the usual way:
`df$column1`
But I want to loop through the columns of my dataframe into a plot function, and when I use the method:
`df[,1]`
I get the error:
Don't know how to automatically pick scale for object of type data.frame. Defaulting to continuous.
Error in is.finite(x) : default method not implemented for type 'list'
So what would be the best way to select columns of the dataframe so that I can easily loop through the columns and avoid this error.
You can access dataframe columns using double square brackets e.g. df[[1]] prints the first column. For more info on why/how/etc, see Dave Tang's blog post: https://davetang.org/muse/2013/08/16/double-square-brackets-in-r
Related
I wanted to use left join function for these two datasets.
Let me call the upper one as "a", and
enter image description here
the lower one is "b".
enter image description here
But it didn't work, and I found that it's because common variable(column) used to join them are incompatible types. Thus, I wanted to join these by "link_id" but that of a is integer and that of b is character.
Both are data frame as you can see in the pictures, and I thought this would be easy to solve, by running "as.integer(b)". But the error 'list' object cannot be coerced to type 'integer' was returned despite I saw the data type is dataframe by using str function...
And I also tried "as.integer(b$link_id)", but 'warning message : NAs introduced by coersion' was returned. But there wasn't any NA value in dataframe. When I ignore this warning message and run left_join(a, b), it still returns it can't because of incompatible types of key variable...
So what should I do now? I think currently the best option is finding the way list to dataframe.
Convert b$link_id to numeric and then use merge :
b$link_id=as.numeric(b$link_id)
merge(a,b,by="link_id")
I'm getting this error a lot in using tweenr in RStudio on mac but I'm unable to replicate it using dummy dataset. My dataset is a list of data frames with I want to apply tween_states. Works fine on dummy data, but always return Error in col2rgb(d) : invalid color name and recognise my first character column as a 'color' whenever I use real data.
Hard to be sure, but I think you are passing too many columns to the tweenr function.
The data you send to the tweenr function should be trimmed column wise to only contain the columns used as argument names and one additional column of values that will be tweened
Getting the same issue! I fixed it by making sure the first column only has numbers, no strings. For whatever reason the first column is interpreted as colors if it contains strings. I didn't need to trim any columns down as the other poster suggested.
this might be a dumb/obvious question but unfortunately I haven't had much luck finding information about it online so I thought I'd ask it here. Basically, I'm working with the data.table package in R and I have imported a data set into R where, in a particular column, the values can be both numeric values and character values (and even blank/empty values), and I want to be able to obtain a value from that column and use it for calculations.
The thing about the data.table package though is that when you import a file using the fread() function it automatically sets all values in that file as a character data type, so this can cause a few issues since this means that all numbers are automatically character types as well. I have worked around this slightly by using the as.numeric() function so that if a value obtained from that column is a number then it can be easily converted to numeric type and used in calculations. However, since the column also contains other characters (specifically, it can also have \N or N as values) and since it can also contain blank/empty values, then this means the as.numeric() function will show up with an error. For example, I initially wrote an IF loop to detect whether a column cell had a character value or a numeric value as follows:
if( as.numeric(..{Reference to column cell from file here}...) == NA ) {
x <- 0
}
(where x is just some variable), but it did not work and instead gave the output:
Error in if ((as.numeric(.... :
missing value where TRUE/FALSE needed
In addition: Warning message:
In eval(expr, envir, enclos) : NAs introduced by coercion
(I should note that is.numeric() also did not work since all values in a data.table data set are automatically character values so this function always gives FALSE regardless of it's actual data type).
So clearly I need a better function or method to work around this. Is there a function capable of reading a 'character' value from a column and being able to detect whether that value is truly a numeric type or character type (or even neither, in the case of an empty cell)? Thanks in advance
I did some reading on similar SO questions, but couldn't figure out how to resolve my error.
I have written the following string of code:
points[paste0(score.avail,"_pts")] <-
Map('*', points[score.avail], mget(paste0(score.avail,'_m')) )
Essentially, I have a list of columns in the 'points' data frame, defined by 'score.avail'. I am multiplying each of the columns by a respective constant, defined as the paste0(score.avail, '_m') expression. It appends new fields based on the multiplication, given by paste0(score.avail, "_pts") expression.
I have used this function before in a similar setup with no issues. However, I am now getting the following error:
Error in .Primitive("*")(dots[[1L]][[1L]], dots[[2L]][[1L]]) :
non-numeric argument to binary operator
I'm pretty sure R is telling me that one of the fields I'm trying to multiply is not numeric. However, I have checked all my fields, and they are numeric. I have even tried running a line as.numeric(score.avail) but that doesn't help. I also ran the following to remove NA's in the fields (before the Map function above).
for(col in score.avail){
points[is.na(get(col)) & (data.source == "average" |
data.source == "averageWeighted"), (col) := 0]}
The thing that stumps me is that this expression has worked with no issues before.
Update
I did some more digging by separating out each component of my original function. I'm getting odd output when running points[score.avail]. Previously when I ran this, it would return just the columns for all of my rows. Now, however, I'm getting none of the rows in my original data frame -- rather, it is imputing the column names in the 'score.avail' list as rows and filling in NA's everywhere (this is clearly the source of my problem).
I think this is because I'm using the object I'm pointing to is a data.table with keyvars set. Previously with this function, I had been pointing to a data frame.
Off to try a few more things.
Another Update
I was able to solve my problem by copying the 'points' object using as.data.frame(). However, I will leave the question open to see if anyone knows how to reset the data table key vars so that the function I specified above will work.
I was able to solve my problem by copying the 'points' object using as.data.frame(). Apparently classifying the object as a data.table was causing my headaches.
I am using the tabular() function to produce tables in r (tables library).
I want to compute CI's from the data in the output (let mytable be the output from tabular()). Simple enough I thought, except when I go to call a value from the matrix, I get the error Error in mytable[1, i] - 1 : non-numeric argument to binary operator. I thought this was odd, as when I call up a particular cell of the matrix (where as.matrix returned true for mytable), for example mytable[1, i] for some i, I get an interger. I then do the as.list for mytable and get true also, so I am not sure what this means. I guess the tabular() function stores the results as a special kind of matrix.
I am only trying to pull out the mean,sdev, and n, which I am able to just by typing the cell location, for example mytable[1, i] would return an 86. However, when I try to call up the value in qt(.975,df=(mytable[1,i]-1)) for example, I get the error above. Not sure really how to approach this except to manually enter the values into another matrix (which I would like to avoid). Or, if I can compute CI's directly in the tabular() function that would work also. Cheers.
I shall quote for you the Value section of the documentation on the function ?tabular:
An object of S3 class "tabular". This is a matrix of mode list, whose
entries are computed summary values, with the following attributes:
rowLabels - A matrix of labels for the rows. This will have the same
number of rows as the main matrix, but may have multiple columns for
different nested levels of labels. If a label covers multiple rows, it
is entered in the first row, and NA is used to fill following rows.
colLabels - Like rowLabels, but labelling the columns.
table - The original table expression being displayed. A list of the
original format specifications are attached as a "fmtlist" attribute.
formats - A matrix of the same shape as the main result, containing NA
for default formatting, or an index into the format list.
As the documentation says, each element of the matrix is a list. If your tabular object is called tab type tab[1,1] and you should see a list containing one of your table values. If I wanted to modify that value, I would probably do something like:
tab[1,1]$term <- value
just like you would modify values in any other list.
Type attributes(tab) and you'll see the items listed above, containing a lot of the formatting information and row/col headers.