Title: South Africa Macroeconomic Database API
Version: 0.3.0
Description: An R API providing access to a relational database with macroeconomic time series data for South Africa, obtained from the South African Reserve Bank (SARB) and Statistics South Africa (STATSSA), and updated on a weekly basis via the EconData https://www.econdata.co.za/ platform and automated scraping of the SARB and STATSSA websites. The database is maintained at the Department of Economics at Stellenbosch University.
BugReports: https://github.com/Stellenbosch-Econometrics/SAMADB-Issues/issues
License: GPL-3
Encoding: UTF-8
Imports: DBI, RMySQL, writexl, data.table, collapse (≥ 2.0.0)
RoxygenNote: 7.2.3
Depends: R (≥ 3.3.0)
Suggests: testthat (≥ 3.0.0)
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2024-05-24 15:59:22 UTC; sebastiankrantz
Author: Sebastian Krantz [aut, cre]
Maintainer: Sebastian Krantz <sebastian.krantz@graduateinstitute.ch>
Repository: CRAN
Date/Publication: 2024-05-24 18:00:08 UTC

South Africa Macroeconomic Database API

Description

An R API providing access to a relational database with public macroeconomic data for South Africa, obtained from from the South African Reserve Bank (SARB) and Statistics South Africa (STATSSA), and updated on a regular basis via the EconData (https://www.econdata.co.za/) platform and automated scraping of the SARB and STATSSA websites. The database is maintained at the Department of Economics at Stellenbosch University.

Functions

Functions and data providing information about the available data

sm_datasources()
sm_datasets()
sm_series()

Function to retrieve the data from the database

sm_data()

Functions to reshape data and add temporal identifiers

sm_pivot_wider()
sm_pivot_longer()
sm_expand_date()

Function to export wide format data to Excel

sm_write_excel()

Helper functions to convert inputs to R dates and transpose the data

sm_as_date()
sm_transpose()

Global Macros with core ID variables in the database

.SAMADB_ID
.SAMADB_T

Global Identifier Macros

Description

The macro .SAMADB_ID contains the string c("dsid", "series") denoting the names of ID variables that identify the cross-sectional dimension in the database. All series codes are unique across datasets.

The macro .SAMADB_T contains the string c("date", "year", "quarter", "month", "day") denoting temporal identifiers generated by sm_expand_date. The "date" variable is sufficient to uniquely identify a point in time in the database.

Each value in the database is uniquely identified by dsid, series and date.

Usage

.SAMADB_ID
.SAMADB_T

See Also

samadb

Examples

.SAMADB_ID
.SAMADB_T

Coerce Vectors to Dates

Description

This function coerces date strings i.e. "YYYY-MM-DD" or "YYYY-MM", years e.g. 2015 (numeric or character), year-quarters e.g. "2015Q1" or "2015-Q1", year-months e.g. "2015M01" or "2015-M01" or numeric values representing dates (e.g. previously imported Excel date) to a regular R date.

Usage

sm_as_date(x, end = FALSE, origin = "1899-12-30")

Arguments

x

a character date string "YYYY-MM-DD" or "YYYY-MM", year-quarter "YYYYQN" or "YYYY-QN", year-month "YYYYMNN" or "YYYY-MNN" or calendar year YYYY (numeric or character), or a numeric value corresponding to a date that can be passed to as.Date.numeric.

end

logical. TRUE replaces missing time information with a period end-date which is the last day of the period. FALSE replaces missing month and day information with "-01", so the year date is the 1st of January, and for months / quarters the 1st day of the month / quarter.

origin

a date or date-string that can be used as reference for converting numeric values to dates. The default corresponds to dates generated in Excel for Windows. See as.Date.numeric.

Value

A Date vector.

See Also

sm_expand_date, samadb

Examples

sm_as_date("2011-05")
sm_as_date(2011)
sm_as_date("2011Q1")
sm_as_date("2011Q1", end = TRUE)
sm_as_date("2011M2")
sm_as_date("2011M2", end = TRUE)

Retrieve Data from the Database

Description

This is the main function of the package to retrieve data from the database.

Usage

sm_data(
  dsid = NULL,
  series = NULL,
  from = NULL,
  to = NULL,
  freq = NULL,
  labels = TRUE,
  wide = TRUE,
  expand.date = FALSE,
  ordered = TRUE,
  return.query = FALSE,
  ...
)

Arguments

dsid

character. (Optional) id's of datasets matching the 'dsid' column of the 'DATASET' table (retrieved using sm_datasets()). If used, all series from the dataset are returned, in addition to any other series selected with series.

series

character. (Optional) codes of series matching the 'series' column of the 'SERIES' table (retrieved using sm_series()). If 'dsid' is also specificed, the two are combined using SQL 'OR' i.e. these series are retrieved in addition to all series matched through 'dsid'.

from

set the start time of the data retrieved by either supplying a start date, a date-string of the form "YYYY-MM-DD" or "YYYY-MM", year-quarters of the form "YYYYQN" or "YYYY-QN", or a numeric year YYYY (numeric or character). These expressions are converted to a regular date by sm_as_date.

to

same as from: to set the time period until which data is retrieved. For expressions that are not full "YYYY-MM-DD" dates, the last day of the period is chosen.

freq

character. Return only series at a certain frequency. Allowed are values "D" (Daily), "W" (Weekly), "M" (Monthly), "Q" (Quarterly), "A" (Annual), "AF" (Fiscal Years), matching the 'freq' column in the 'SERIES' table (retrieved using sm_series()).

labels

logical. TRUE will also return labels (series descriptions) along with the series codes.

wide

logical. TRUE calls sm_pivot_wider on the result. FALSE returns the data in a long format without missing values (suitable for ggplot2).

expand.date

logical. TRUE will call sm_expand_date on the result.

ordered

logical. TRUE orders the result by 'date' and, if !is.null(dsid), labels = TRUE or !is.null(freq), by series, maintaining a fixed order of series. FALSE does not explicitly order the result, to the benefit of faster query execution.

return.query

logical. TRUE will not query the database but instead return the constructed SQL query as a character string (for debugging purposes).

...

further arguments passed to sm_pivot_wider (if wide = TRUE) or sm_expand_date (if expand.date = TRUE), no conflicts between these two.

Details

Series from datasets at different frequencies can be queried, but, if wide = TRUE, this will result in missing values in the lower frequency series.

Value

A data.table with the result of the query.

See Also

sm_pivot_wider, sm_expand_date, samadb

Examples


# Return all electricity indicators from 2000
sm_data("ELECTRICITY", from = 2000)

Retrieve Datasets Table

Description

This function pulls and return a table called 'DATASET' from the database.

Usage

sm_datasets(ordered = TRUE)

Arguments

ordered

logical. TRUE orders the result in the order data was entered into the database, while FALSE returns the result in a random order, to the benefit of faster query execution.

Details

The 'DATASET' table gives information about the different datasets fetched from different providers at regular intervals. It provides a unique id for each dataset, the frequency of data, the number of records (datapoints) in each dataset, the minimum and maximum time coverage, when the dataset was last updated, and information about the data source, provider, and method of data access.

Value

A data.table with information about the available datasets in the database.

See Also

sm_datasources, sm_series, samadb

Examples


sm_datasets()

Retrieve Data Sources Table

Description

This function pulls and returns a table called 'DATASOURCE' from the database.

Usage

sm_datasources(ordered = TRUE)

Arguments

ordered

logical. TRUE orders the result in the order data was entered into the database, while FALSE returns the result in a random order, to the benefit of faster query execution.

Details

The 'DATASOURCE' table gives information about the sources of data in this database, including the source website, and the number of datasets available from the source.

Value

A data.table with information about the sources of data in the database.

See Also

sm_datasets, sm_series, samadb

Examples


sm_datasources()

Generate Temporal Identifiers from a Date Column

Description

This function expands a date column and generates additional temporal identifiers from it (year, month, quarter, day).

Usage

sm_expand_date(
  x,
  gen = c("year", "quarter", "month"),
  origin = "1899-12-30",
  keep.date = TRUE,
  remove.missing.date = TRUE,
  sort = TRUE,
  as.factor = TRUE,
  name = "date",
  ...
)

Arguments

x

either a vector of class 'Date', or coercible to date using as.Date, or a data frame / list containing with a date-column called name.

gen

character. A vector of identifiers to generate from x. The possible identifiers are found in .SAMADB_T.

origin

character / Date. Passed to as.Date: for converting numeric x to date. The default reflects converting date-numbers from Excel for Windows.

keep.date

logical. TRUE will keep the date variable in the resulting dataset, FALSE will remove the date variable in favor of the generated identifiers.

remove.missing.date

logical. TRUE will remove missing values in x. If x is a dataset, rows missing the date variable will be removed.

sort

logical. TRUE will sort the data by the date column.

as.factor

TRUE will generate quarters and months as factor variables. It is also possible to use as.factor = "ordered" to generate ordered factors. FALSE will generate quarters and months as integer variables.

name

character. The name of the date variable to expand.

...

not used.

Value

A data.table containing the computed identifiers as columns. See Examples.

See Also

sm_as_date, samadb

Examples

# First a basic example
x <- seq.Date(as.Date("1999-01-01"), as.Date("2000-01-01"), by = "month")
sm_expand_date(x)
sm_expand_date(x, gen = .SAMADB_T[-1L], keep.date = FALSE)

# Now using the API
sm_expand_date(sm_data("BUSINESS_CYCLES"))

# Same thing
sm_data("BUSINESS_CYCLES", expand.date = TRUE)

Reshape Column-Based Data to Long Format

Description

This function automatically reshapes wide (column-based) data into a long format akin to the format of the raw data coming from the database (sm_data(..., wide = FALSE)). Internally it uses melt from data.table.

Usage

sm_pivot_longer(
  data,
  id_cols = intersect(.SAMADB_T, names(data)),
  to_value = setdiff(names(data), id_cols),
  variable_name = "series",
  value_name = "value",
  label_name = "label",
  na.rm = TRUE,
  variable.factor = TRUE,
  label.factor = TRUE,
  ...
)

Arguments

data

a wide format data frame where all series have their own column.

id_cols

character. Temporal identifiers of the data. By default all variables in .SAMADB_T are selected.

to_value

character. The names of all series to be stacked into the long format data frame.

variable_name

character. The name of the variable to store the names of the series.

value_name

character. The name of the variable to store the data values.

label_name

character. The name of the variable to store the series labels.

na.rm

logical. TRUE will remove all missing values from the long data frame.

variable.factor, label.factor

logical. TRUE will code the "series" and "label" columns as factors, which is more memory efficient.

...

further arguments passed to melt.

Value

A data.table with the reshaped data.

See Also

sm_pivot_wider, samadb

Examples


# Return all electricity indicators from the year 2000 onwards
data <- sm_data("ELECTRICITY", from = 2000)
sm_pivot_longer(data)

Reshape Long API Data to Column-Based Format

Description

This function automatically reshapes long (stacked) raw data from the API (sm_data(..., wide = FALSE)) to a wide format where each variable has its own column. Internally it uses pivot from collapse.

Usage

sm_pivot_wider(
  data,
  id_cols = intersect(.SAMADB_T, names(data)),
  names_from = "series",
  values_from = "value",
  labels_from = if (any(names(data) == "label")) "label" else NULL,
  expand.date = FALSE,
  ...
)

Arguments

data

raw data from the API: A long format data frame where all values are stacked in a value column.

id_cols

character. Temporal identifiers of the data. By default all variables in .SAMADB_T are selected.

names_from

character. The column containing the series codes. These will become the names of the new columns in the wider data format.

values_from

character. The column containing the data values.

labels_from

character. The column containing the labels describing the series.

expand.date

logical. TRUE will call sm_expand_date on the data after reshaping.

...

further arguments passed to pivot or sm_expand_date.

Value

A data.table with the reshaped data.

See Also

sm_pivot_longer, samadb

Examples


# Return all electricity indicators from the year 2000 onwards
sm_pivot_wider(sm_data("ELECTRICITY", from = 2000, wide = FALSE))

Retrieve Series Table

Description

This function pulls the 'SERIES' table from the database, providing information about the time series in the database. Each series is given a code which unique across datasets.

Usage

sm_series(
  dsid = NULL,
  series = NULL,
  dataset.info = FALSE,
  ordered = TRUE,
  return.query = FALSE
)

Arguments

dsid

character. (Optional) id's of datasources matching the 'dsid' column of the 'DATASET' table (retrieved using sm_datasets()) for which series information is to be returned.

series

character. (Optional) codes of series for which information in to be returned. If 'dsid' is also specificed, the two are combined using SQL 'OR' i.e. these series are retrieved in addition to all series matched through 'dsid'.

dataset.info

logical. TRUE returns additional information from the 'DATASET' table (the dataset name, when data was last updated, the source id and the data provider and access mode).

ordered

logical. TRUE returns the series in a fixed order, while FALSE returns the result in a random order, to the benefit of faster query execution.

return.query

logical. TRUE will not query the database but instead return the constructed SQL query as a character string (for debugging purposes).

Details

Each series is given a code which is unique across datasets. Each series also has a label describing the series. Further information recorded are the series frequency, unit, whether it was seasonally adjusted, number of observations, minimum and maximum date, and (optionally) topic, alternative code provided by the data source (data retrieved from EconData uses EconData codes as series codes, so the 'src_code' field gives the codes used by the SARB or STATSSA), or further comments on the series.

Value

A data.table with information about the available series in the database.

See Also

sm_datasources, sm_datasets, sm_data, samadb

Examples


# By default returns all series
sm_series()

# Adding information about the dataset and provider
sm_series(dataset.info = TRUE)

# Only series in the QB
sm_series("QB")

Transpose a Wide Dataset to a Row-Based Format

Description

This function is called by sm_write_excel with option transpose = TRUE to generate a row-based tabular data format from a wide data frame in R that is suitable for exporting to Excel.

Usage

sm_transpose(data, date.format = "%d/%m/%Y")

Arguments

data

a wide format data frame where each column is a variable and the first variable uniquely identifies the data.

date.format

a format for date columns which is passed to format.Date. When transposing wide, dates are converted to character. The default R YYYY-MM-DD format for dates is often not recognized by Excel. By default dates are transformed to DD/MM/YYYY format which Excel (UK English) recognizes. Putting FALSE here does not transform dates into another format.

Value

A transposed data frame or data.table (the class of the input is preserved).

See Also

transpose, sm_pivot_wider, sm_write_excel, samadb

Examples


sm_transpose(sm_data("ELECTRICITY"))

Export Wide Data to Excel

Description

This function exports a wide format dataset to a column- (default) or row-oriented Excel format.

Usage

sm_write_excel(
  data,
  ...,
  transpose = FALSE,
  transpose.date.format = "%d/%m/%Y"
)

Arguments

data

a wide dataset from sm_data or reshaped to a wide format with sm_pivot_wider.

...

further arguments to write_xlsx. As a minimum a path needs to be supplied that ends with the name of the Excel file. See Examples.

transpose

logical. If TRUE, the result is returned in a row-oriented Excel format. The default is column oriented (same as the dataset in R).

transpose.date.format

argument passed to sm_transpose, setting the format of date columns when data is transposed.

Value

Writes an Excel file to the specified path (no return value).

See Also

sm_transpose, write_xlsx, samadb

Examples

## Not run: 
# Getting electricity indicators from 2000
data <- sm_data("ELECTRICITY", from = 2000)

# Saving to different Excel formats
sm_write_excel(data, "ELECTRICITY.xlsx")
sm_write_excel(data, "ELECTRICITY.xlsx", transpose = TRUE)

# Saving to alternative path
sm_write_excel(data, "C:/Users/.../ELECTRICITY.xlsx")

## End(Not run)