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Get tabular data

Source: R/get_v1_data.R
spod_get.Rd

This function creates a DuckDB lazy table connection object from the specified type and zones. It checks for missing data and downloads it if necessary. The connnection is made to the raw CSV files in gzip archives, so analysing the data through this connection may be slow if you select more than a few days. You can manipulate this object using {dplyr} functions such as select, filter, mutate, group_by, summarise, etc. In the end of any sequence of commands you will need to add collect to execute the whole chain of data manipulations and load the results into memory in an R data.frame/tibble. See codebooks for v1 and v2 data in vignettes with spod_codebook(1) and spod_codebook(2) (spod_codebook).

If you want to analyse longer periods of time (especiially several months or even the whole data over several years), consider using the spod_convert and then spod_connect.

Usage

spod_get(
  type = c("od", "origin-destination", "os", "overnight_stays", "nt", "number_of_trips"),
  zones = c("districts", "dist", "distr", "distritos", "municipalities", "muni",
    "municip", "municipios"),
  dates = NULL,
  data_dir = spod_get_data_dir(),
  quiet = FALSE,
  max_mem_gb = max(4, spod_available_ram() - 4),
  max_n_cpu = parallelly::availableCores() - 1,
  max_download_size_gb = 1,
  duckdb_target = ":memory:",
  temp_path = spod_get_temp_dir()
)

Arguments

type

The type of data to download. Can be "origin-destination" (or ust "od"), or "number_of_trips" (or just "nt") for v1 data. For v2 data "overnight_stays" (or just "os") is also available. More data types to be supported in the future. See codebooks for v1 and v2 data in vignettes with spod_codebook(1) and spod_codebook(2) (spod_codebook).

zones

The zones for which to download the data. Can be "districts" (or "dist", "distr", or the original Spanish "distritos") or "municipalities" (or "muni", "municip", or the original Spanish "municipios") for both data versions. Additionaly, these can be "large_urban_areas" (or "lua", or the original Spanish "grandes_areas_urbanas", or "gau") for v2 data (2022 onwards).

dates

A character or Date vector of dates to process. Kindly keep in mind that v1 and v2 data follow different data collection methodologies and may not be directly comparable. Therefore, do not try to request data from both versions for the same date range. If you need to compare data from both versions, please refer to the respective codebooks and methodology documents. The v1 data covers the period from 2020-02-14 to 2021-05-09, and the v2 data covers the period from 2022-01-01 to the present until further notice. The true dates range is checked against the available data for each version on every function run.

The possible values can be any of the following:

  • For the spod_get() function, the dates can be set to "cached_v1" or "cached_v2" to request data from cached v1 (2020-2021) or v2 (2022 onwards). In this case, the function will identify and use all data files that have been downloaded and cached locally, e.g. using a separate previous call to spod_download_data().

  • A single date in ISO (YYYY-MM-DD) or YYYYMMDD format. character or Date object.

  • A vector of dates in ISO (YYYY-MM-DD) or YYYYMMDD format. character or Date object. Can be any non-consecutive sequence of dates.

  • A date range

    • eigher a character or Date object of length 2 with clearly named elements start and end in ISO (YYYY-MM-DD) or YYYYMMDD format. E.g. c(start = "2020-02-15", end = "2020-02-17");

    • or a character object of the form YYYY-MM-DD_YYYY-MM-DD or YYYYMMDD_YYYYMMDD. For example, 2020-02-15_2020-02-17 or 20200215_20200217.

  • A regular expression to match dates in the format YYYYMMDD. character object. For example, ^202002 will match all dates in February 2020.

data_dir

The directory where the data is stored. Defaults to the value returned by spod_get_data_dir() which returns the value of the environment variable SPANISH_OD_DATA_DIR or a temporary directory if the variable is not set.

quiet

A logical value indicating whether to suppress messages. Default is FALSE.

max_mem_gb

The maximum memory to use in GB. A conservative default is 3 GB, which should be enough for resaving the data to DuckDB form a folder of CSV.gz files while being small enough to fit in memory of most even old computers. For data analysis using the already converted data (in DuckDB or Parquet format) or with the raw CSV.gz data, it is recommended to increase it according to available resources.

max_n_cpu

The maximum number of threads to use. Defaults to the number of available cores minus 1.

max_download_size_gb

The maximum download size in gigabytes. Defaults to 1.

duckdb_target

(Optional) The path to the duckdb file to save the data to, if a convertation from CSV is reuqested by the spod_convert function. If not specified, it will be set to ":memory:" and the data will be stored in memory.

temp_path

The path to the temp folder for DuckDB for intermediate spilling in case the set memory limit and/or physical memory of the computer is too low to perform the query. By default this is set to the temp directory in the data folder defined by SPANISH_OD_DATA_DIR environment variable. Otherwise, for queries on folders of CSV files or parquet files, the temporary path would be set to the current R working directory, which probably is undesirable, as the current working directory can be on a slow storage, or storage that may have limited space, compared to the data folder.

Value

A DuckDB lazy table connection object of class tbl_duckdb_connection.

Examples

if (FALSE) { # \dontrun{

# create a connection to the v1 data
Sys.setenv(SPANISH_OD_DATA_DIR = "~/path/to/your/cache/dir")
dates <- c("2020-02-14", "2020-03-14", "2021-02-14", "2021-02-14", "2021-02-15")
od_dist <- spod_get(type = "od", zones = "distr", dates = dates)

# od dist is a table view filtered to the specified dates

# access the source connection with all dates
# list tables
DBI::dbListTables(od_dist$src$con)
} # }