collect_and_normalize | R Documentation |
Collect data from connection and normalize cansim table output
collect_and_normalize( connection, replacement_value = "val_norm", normalize_percent = TRUE, default_month = "07", default_day = "01", factors = FALSE, strip_classification_code = FALSE, disconnect = FALSE )
connection |
A connection to a local StatCan table SQLite database as returned by |
replacement_value |
(Optional) the name of the column the manipulated value should be returned in. Defaults to adding the 'val_norm' value field. |
normalize_percent |
(Optional) When |
default_month |
The default month that should be used when creating Date objects for annual data (default set to "07") |
default_day |
The default day of the month that should be used when creating Date objects for monthly data (default set to "01") |
factors |
(Optional) Logical value indicating if dimensions should be converted to factors. (Default set to |
strip_classification_code |
(Optional) Logical value indicating if classification code should be stripped from names. (Default set to |
disconnect |
(Optional) Logical value to indicate if the database connection should be disconnected. (Default is |
A tibble with the collected and normalized data
## Not run: library(dplyr) con <- get_cansim_sqlite("34-10-0013") data <- con %>% filter(GEO=="Ontario") %>% collect_and_normalize() disconnect_cansim_sqlite(con) ## End(Not run)
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