The nested tibble from downloadDMRs() relies on the user mapping column types to unnest the dmr column:
library(dplyr)
library(echor)
df <- tibble::tibble(permit = c("TX0021474", "TX0023051", "TXG130053"))
df <- downloadDMRs(df, idColumn = permit, start_date = "01/01/2010",
end_date = "12/30/2017", parameter_code = "50050")
df %>% tidyr::unnest(dmr)
Results in the following message:
Error: Column `monitoring_location_code` can't be converted from character to numeric
I have to follow up with the following to unnest the data:
df %>%
mutate(n = purrr::map(dmr, ~nrow(.))) %>%
mutate(dmr = purrr::map(dmr, ~mutate(.x,
version_nmbr = as.character(version_nmbr),
monitoring_location_code = as.character(monitoring_location_code),
exceedence_pct = as.character(exceedence_pct),
rnc_detection_date = as.character(rnc_detection_date),
rnc_resolution_code = as.character(rnc_resolution_code),
rnc_resolution_date = as.character(rnc_resolution_date),
days_late = as.character(days_late),
nodi_code = as.character(nodi_code),
dmr_value_nmbr = as.numeric(dmr_value_nmbr),
dmr_value_standard_units = as.numeric(dmr_value_standard_units),
limit_value_nmbr = as.numeric(limit_value_nmbr),
limit_value_standard_units = as.numeric(limit_value_standard_units)))) %>%
tidyr::unnest(dmr)
The user should not have to figure this out, but if the above code is hardcoded, it will be prone to breaking if the columns returned by the API ever change.
The nested tibble from
downloadDMRs()relies on the user mapping column types to unnest the dmr column:Results in the following message:
I have to follow up with the following to unnest the data:
The user should not have to figure this out, but if the above code is hardcoded, it will be prone to breaking if the columns returned by the API ever change.