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Factor-Based Imputation for Missing Data
For most vintages the most recent month seems to be missing when loading (downloaded) fredmd csv files with the fred_md() function. For instance when loading the first vintage (1999-08.csv), the last available month is June whereas some observations are available for July in the csv file.
After looking in the code I think it is because of line 51 in fredmd.R : rawdata <- rawdata[1:(nrow(rawdata) - 1), ] # remove NA rows
I think the last raw should be removed only if it contains only missing values
Is the data set fredmd_description updated?
It seems it doesn't not contain the recent changes, e.g. for VXOCLSx changed to VIXCLSx.
To replicate:
fl <- "https://files.stlouisfed.org/files/htdocs/fred-md/quarterly/current.csv" df <- fredqd(file = fl, transform = TRUE)
It returns the following error:
Error in 1:ind_notna : result would be too long a vector
In addition: Warning message:
In min(which(is.na(rawdata[, 1]))) :
no non-missing arguments to min; returning Inf
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