Pretty sure this is the issue with data types. I think what is happening is all the point forecasts are at the top of the dataframe so the first 1000+ rows of the quantile column are NA. So the tibble automatically assigns a logical data type to the quantile column. but then when it reads the whole file and sees that there are numbers it gets confused.
That makes sense. My job_data() function in zoltr is where I specify column types. For forecast queries we pass this col_types through get_resource() to readr::read_csv() :
"cDcccc?????????"
You see that we decided to let R figure out what to do with the columns that might be empty. This is because data types for those columns depend on target types.
This query causes the warning:
readr::problems(df)
->@nickreich says:
That makes sense. My job_data() function in zoltr is where I specify column types. For forecast queries we pass this col_types through get_resource() to readr::read_csv() :
"cDcccc?????????"
You see that we decided to let R figure out what to do with the columns that might be empty. This is because data types for those columns depend on target types.