This function is deprecated because the CalCOFI API is being phased out
in favor of direct DuckDB database access. Query bottle measurement data
with cc_get_db() and aggregate using dplyr for time series analysis.
Usage
get_timeseries(
variable = "ctdcast_bottle.t_deg_c",
aoi_wkt = NULL,
depth_m_min = NULL,
depth_m_max = NULL,
date_beg = NULL,
date_end = NULL,
time_step = "year",
stats = c("p10", "mean", "p90")
)Arguments
- variable
Variable to fetch from the CalCOFI API. One of
table_fieldvalues fromget_variables(). Default is"ctdcast_bottle.t_deg_c".- aoi_wkt
Area of interest (AOI), spatially described as well-known text (WKT).
- depth_m_min
Minimum depth range in meters, e.g. 0. Default is
NULL, as in not filtered.- depth_m_max
Maximum depth range in meters, e.g. 5351. Default is
NULL, as in not filtered.- date_beg
Beginning of date range, e.g."1949-02-28". Default is
NULL, as in not filtered.- date_end
End of date range, e.g. "2020-01-26". Default is
NULL, as in not filtered.- time_step
Time step over which to summarize. One of: a sequential increment ("decade","year","year.quarter","year.month","year.week","date"), or a climatology ("quarter","month","week","julianday","hour"). Default is
"year".- stats
Statistics to show per
date_step. Acceptable values include any combination of: "avg", "median", "min", "max", "sd" or "p#" where "sd" is the standard deviation and "p#" represents the percentile value 0 to 100 within available range of values. Default isc("p10", "mean", "p90").
Examples
if (FALSE) { # \dontrun{
# deprecated - use DuckDB queries instead:
con <- cc_get_db()
d <- DBI::dbGetQuery(con, "
SELECT EXTRACT(YEAR FROM c.datetime_utc) AS year,
AVG(bm.measurement_value) AS avg_temp
FROM bottle_measurement bm
JOIN bottle b ON bm.bottle_id = b.bottle_id
JOIN casts c ON b.cast_id = c.cast_id
WHERE bm.measurement_type = 'temperature'
GROUP BY year ORDER BY year")
} # }