Package 'tidyBdE'

Title: Download Data from Bank of Spain
Description: Tools to download data series from 'Banco de España' ('BdE') on 'tibble' format. 'Banco de España' is the national central bank and, within the framework of the Single Supervisory Mechanism ('SSM'), the supervisor of the Spanish banking system along with the European Central Bank. This package is in no way sponsored endorsed or administered by 'Banco de España'.
Authors: Diego H. Herrero [aut, cre, cph]
Maintainer: Diego H. Herrero <[email protected]>
License: GPL (>= 3)
Version: 0.3.8
Built: 2024-12-20 12:37:07 UTC
Source: https://github.com/rOpenSpain/tidyBdE

Help Index


Load BdE catalogs

Description

Load the time-series catalogs provided by BdE.

Usage

bde_catalog_load(
  catalog = c("ALL", "BE", "SI", "TC", "TI", "PB"),
  parse_dates = TRUE,
  cache_dir = NULL,
  update_cache = FALSE,
  verbose = FALSE
)

Arguments

catalog

A single value indicating the catalogs to be updated or "ALL" as a shorthand. See Details.

parse_dates

Logical. If TRUE the dates would be parsed using bde_parse_dates().

cache_dir

A path to a cache directory. The directory can also be set via options with options(bde_cache_dir = "path/to/dir").

update_cache

Logical. If TRUE the requested file would be updated on the cache_dir.

verbose

Logical TRUE or FALSE, display information useful for debugging.

Details

Accepted values for catalog are:

CODE PUBLICATION UPDATE FREQUENCY FREQUENCY
"BE" Statistical Bulletin Daily Monthly
"SI" Summary Indicators Daily Daily
"TC" Exchange Rates Daily Daily
"TI" Interest Rates Daily Daily
"PB" Bank Lending Survey Quarterly Quarterly

Use "ALL" as a shorthand for updating all the catalogs at a glance.

If the requested catalog is not cached bde_catalog_update() is invoked.

Value

A tibble object.

Source

Time-series bulk data download.

See Also

Other catalog: bde_catalog_search(), bde_catalog_update()

Examples

bde_catalog_load("TI", verbose = TRUE)

Update BdE catalogs

Description

Update the time-series catalogs provided by BdE.

Usage

bde_catalog_update(
  catalog = c("ALL", "BE", "SI", "TC", "TI", "PB"),
  cache_dir = NULL,
  verbose = FALSE
)

Arguments

catalog

A vector of characters indicating the catalogs to be updated or "ALL" as a shorthand. See Details.

cache_dir

A path to a cache directory. The directory can also be set via options with options(bde_cache_dir = "path/to/dir").

verbose

Logical TRUE or FALSE, display information useful for debugging.

Details

Accepted values for catalog are:

CODE PUBLICATION UPDATE FREQUENCY FREQUENCY
"BE" Statistical Bulletin Daily Monthly
"SI" Summary Indicators Daily Daily
"TC" Exchange Rates Daily Daily
"TI" Interest Rates Daily Daily
"PB" Bank Lending Survey Quarterly Quarterly

Use "ALL" as a shorthand for updating all the catalogs at a glance.

Value

None. Downloads the catalog file(s) to the local machine.

Source

Time-series bulk data download.

See Also

Other catalog: bde_catalog_load(), bde_catalog_search()

Examples

bde_catalog_update("TI", verbose = TRUE)

Relevant Indicators of Spain

Description

Set of helper functions for downloading some of the most relevant macroeconomic indicators of Spain.

Usage

bde_ind_gdp_var(series_label = "GDP_YoY", ...)

bde_ind_unemployment_rate(series_label = "Unemployment_Rate", ...)

bde_ind_euribor_12m_monthly(series_label = "Euribor_12M_Monthly", ...)

bde_ind_euribor_12m_daily(series_label = "Euribor_12M_Daily", ...)

bde_ind_cpi_var(series_label = "Consumer_price_index_YoY", ...)

bde_ind_ibex_monthly(series_label = "IBEX_index_month", ...)

bde_ind_ibex_daily(series_label = "IBEX_index_day", ...)

bde_ind_gdp_quarterly(series_label = "GDP_quarterly_value", ...)

bde_ind_population(series_label = "Population_Spain", ...)

Arguments

series_label

Optional. Character vector or value. Allows to specify a custom label for the series extracted. It should have the same length than series_code.

...

Arguments passed on to bde_series_load

out_format

Defines if the format must be returned as a "long" dataset or a "wide" dataset. Possible values are "wide" or "long". See Value for Details and Section Examples.

parse_numeric

Logical. If TRUE the columns would be parsed to double (numeric) values. See Note.

extract_metadata

Logical TRUE/FALSE. On TRUE the output is the metadata of the requested series.

parse_dates

Logical. If TRUE the dates would be parsed using bde_parse_dates().

update_cache

Logical. If TRUE the requested file would be updated on the cache_dir.

cache_dir

A path to a cache directory. The directory can also be set via options with options(bde_cache_dir = "path/to/dir").

verbose

Logical TRUE or FALSE, display information useful for debugging.

Details

This functions are convenient wrappers of bde_series_load() referencing specific series. Use ⁠verbose = TRUE, extract_metadata = TRUE⁠ options to see the specification and the source.

Value

A tibble with the required series.

See Also

bde_series_load(), bde_catalog_search()

Examples

bde_ind_gdp_var()

Parse dates

Description

This function is tailored for the date formatting used on this package, so it may fail if it is used for another datasets. See Examples for checking which formats would be considered.

Date Formats

FREQUENCY FORMAT EXAMPLES
Daily / Business day DD MMMMYYYY 02 FEB2019
Monthly MMM YYYY MAR 2020
Quarterly MMM YYYY, where MMM is the first or the last month of the quarter, depending on the value of its variable OBSERVED. For the first quarter of 2020: ENE 2020, MAR 2020
Half-yearly MMM YYYY, where MMM is the first or the last month of the halfyear period, depending on the value of its variable OBSERVED. For the first half of 2020: ENE 2020, JUN 2020
Annual YYYY 2020

Usage

bde_parse_dates(dates_to_parse)

Arguments

dates_to_parse

Dates to parse

Details

Tries to parse strings representing dates using as.Date()

Value

A Date object.

See Also

as.Date()

Examples

# Formats parsed
would_parse <- c(
  "02 FEB2019", "15 ABR 1890", "MAR 2020", "ENE2020",
  "2020", "12-1993", "01-02-2014", "01/02/1990"
)

parsed_ok <- bde_parse_dates(would_parse)

class(parsed_ok)

tibble::tibble(raw = would_parse, parsed = parsed_ok)

#-----------------------------------

# Formats not admitted
wont_parse <- c("JAN2001", "2010-01-12", "01 APR 2017", "01/31/1990")

parsed_fail <- bde_parse_dates(wont_parse)

class(parsed_fail)

tibble::tibble(raw = wont_parse, parsed = parsed_fail)

Load BdE full time-series files

Description

Load a full time-series file provided by BdE.

Usage

bde_series_full_load(
  series_csv,
  parse_dates = TRUE,
  parse_numeric = TRUE,
  cache_dir = NULL,
  update_cache = FALSE,
  verbose = FALSE,
  extract_metadata = FALSE
)

Arguments

series_csv

csv file of a series, as defined in the field ⁠Nombre del archivo con los valores de la serie⁠ of the corresponding catalog. See bde_catalog_load().

parse_dates

Logical. If TRUE the dates would be parsed using bde_parse_dates().

parse_numeric

Logical. If TRUE the columns would be parsed to double (numeric) values. See Note.

cache_dir

A path to a cache directory. The directory can also be set via options with options(bde_cache_dir = "path/to/dir").

update_cache

Logical. If TRUE the requested file would be updated on the cache_dir.

verbose

Logical TRUE or FALSE, display information useful for debugging.

extract_metadata

Logical TRUE/FALSE. On TRUE the output is the metadata of the requested series.

Details

About BdE file naming

The series name is a positional code showing the location of the table. For example, table be_6_1 represents the Table 1, Chapter 6 of the Statistical Bulletin ("BE"). Although it is a unique value, it is subject to change (i.e. a new table is inserted before).

For that reason, the function bde_series_load() is more suitable for extracting specific time-series.

Value

A tibble with a field Date and the alias of the fields series as described on the catalogs. See bde_catalog_load().

Note

This function tries to coerce the columns to numbers. For some series a warning may be displayed if the parser fails. You can override the default behavior with parse_numeric = FALSE

See Also

Other series: bde_series_load()

Examples

# Metadata
bde_series_full_load("TI_1_1.csv", extract_metadata = TRUE)

# Data
bde_series_full_load("TI_1_1.csv")

Load a single BdE time-series

Description

The series alias is a positional code showing the location (column and/or row) of the series in the table. However, although it is unique, it is not a good candidate to be used as the series ID, as it is subject to change. If a series changes position in the table, its alias will also change.

To ensure series can still be identified, even after these changes, they are assigned a sequential number (series_code on this function) which will remain unchanged throughout the series' lifetime.

Note that a single series could be used on different tables, so it can have several aliases. If you need to search by alias it is recommended to use bde_series_full_load().

Usage

bde_series_load(
  series_code,
  series_label = NULL,
  out_format = "wide",
  parse_dates = TRUE,
  parse_numeric = TRUE,
  cache_dir = NULL,
  update_cache = FALSE,
  verbose = FALSE,
  extract_metadata = FALSE
)

Arguments

series_code

a numeric (or coercible with base::as.double() value or vector with time-series code(s), as defined in the field ⁠Número secuencial⁠ of the corresponding series. See bde_catalog_load().

series_label

Optional. Character vector or value. Allows to specify a custom label for the series extracted. It should have the same length than series_code.

out_format

Defines if the format must be returned as a "long" dataset or a "wide" dataset. Possible values are "wide" or "long". See Value for Details and Section Examples.

parse_dates

Logical. If TRUE the dates would be parsed using bde_parse_dates().

parse_numeric

Logical. If TRUE the columns would be parsed to double (numeric) values. See Note.

cache_dir

A path to a cache directory. The directory can also be set via options with options(bde_cache_dir = "path/to/dir").

update_cache

Logical. If TRUE the requested file would be updated on the cache_dir.

verbose

Logical TRUE or FALSE, display information useful for debugging.

extract_metadata

Logical TRUE/FALSE. On TRUE the output is the metadata of the requested series.

Details

Load a single time-series provided by BdE.

Value

A tibble with a field Date and :

  • With out_format = "wide" each series is presented in a separate column with the name defined by series_label.

  • With out_format = "long" the tibble would have two more columns, serie_name with the labels of each series and serie_value with the value of the series.

"wide" format is more suitable for exporting to a .csv file while "long" format is more suitable for producing plots with ggplot2::ggplot(). See also tidyr::pivot_longer() and tidyr::pivot_wider().

Note

This function tries to coerce the columns to numbers. For some series a warning may be displayed if the parser fails. You can override the default behavior with parse_numeric = FALSE

See Also

bde_catalog_load(), bde_catalog_search(), bde_indicators()

Other series: bde_series_full_load()

Examples

# Metadata
bde_series_load(573234, verbose = TRUE, extract_metadata = TRUE)

# Data
bde_series_load(573234, extract_metadata = FALSE)

# Vectorized
bde_series_load(c(573234, 573214),
  series_label = c("US/EUR", "GBP/EUR"),
  extract_metadata = TRUE
)

wide <- bde_series_load(c(573234, 573214),
  series_label = c("US/EUR", "GBP/EUR")
)

# Wide format
wide


# Long format
long <- bde_series_load(c(573234, 573214),
  series_label = c("US/EUR", "GBP/EUR"),
  out_format = "long"
)

long


# Use with ggplot
library(ggplot2)


ggplot(long, aes(Date, serie_value)) +
  geom_line(aes(group = serie_name, color = serie_name)) +
  scale_color_bde_d() +
  theme_tidybde()

BdE color palettes

Description

Custom palettes based on the publications of BdE. These are manual palettes with a maximum of 6 colors.

Usage

bde_tidy_palettes(
  n = 6,
  palette = c("bde_vivid_pal", "bde_rose_pal", "bde_qual_pal"),
  alpha = NULL,
  rev = FALSE
)

Arguments

n

The number of colors (⁠>= 1⁠) to be in the palette.

palette

A valid palette name.

alpha

An alpha-transparency level in the range ⁠[0,1]⁠ (0 means transparent and 1 means opaque). A missing, i.e., alpha = NULL, does not add opacity codes ("FF") to the individual color hex codes. See ggplot2::alpha().

rev

Logical indicating whether the ordering of the colors should be reversed.

Value

A vector of colors.

See Also

Other bde_plot: scales_bde, theme_tidybde()

Examples

# BdE vivid pal
scales::show_col(bde_tidy_palettes(palette = "bde_vivid_pal"),
  labels = FALSE
)

# BdE rose pal
scales::show_col(bde_tidy_palettes(palette = "bde_rose_pal"), labels = FALSE)

# BdE qual pal
scales::show_col(bde_tidy_palettes(palette = "bde_qual_pal"), labels = FALSE)

BdE scales for ggplot2

Description

Scales to be used with the ggplot2 package. Discrete palettes are named as ⁠scale_*_bde_d⁠ while continuous palettes are named ⁠scale_*_bde_c⁠.

Usage

scale_color_bde_d(
  palette = c("bde_vivid_pal", "bde_rose_pal", "bde_qual_pal"),
  alpha = NULL,
  rev = FALSE,
  ...
)

scale_fill_bde_d(
  palette = c("bde_vivid_pal", "bde_rose_pal", "bde_qual_pal"),
  alpha = NULL,
  rev = FALSE,
  ...
)

scale_color_bde_c(
  palette = c("bde_rose_pal", "bde_vivid_pal", "bde_qual_pal"),
  alpha = NULL,
  rev = FALSE,
  guide = "colorbar",
  ...
)

scale_fill_bde_c(
  palette = c("bde_rose_pal", "bde_vivid_pal", "bde_qual_pal"),
  alpha = NULL,
  rev = FALSE,
  guide = "colorbar",
  ...
)

Arguments

palette

Name of the BdE palette to apply. See bde_tidy_palettes() for details.

alpha

An alpha-transparency level in the range ⁠[0,1]⁠ (0 means transparent and 1 means opaque). A missing, i.e., alpha = NULL, does not add opacity codes ("FF") to the individual color hex codes. See ggplot2::alpha().

rev

Logical indicating whether the ordering of the colors should be reversed.

...

Further arguments of ggplot2::discrete_scale() or ggplot2::continuous_scale().

guide

A function used to create a guide or its name. See guides() for more information.

Value

A ggplot2 color scale.

See Also

ggplot2::discrete_scale(), ggplot2::continuous_scale()

Other bde_plot: bde_tidy_palettes(), theme_tidybde()

Examples

library(ggplot2)

set.seed(596)
txsamp <- subset(
  txhousing,
  city %in% c(
    "Houston", "Fort Worth",
    "San Antonio", "Dallas", "Austin"
  )
)

ggplot(txsamp, aes(x = sales, y = median)) +
  geom_point(aes(colour = city)) +
  scale_color_bde_d() +
  theme_minimal()


ggplot(txsamp, aes(x = sales, y = median)) +
  geom_point(aes(colour = city)) +
  scale_color_bde_d("bde_qual_pal") +
  theme_minimal()

BdE ggplot2 theme

Description

A custom ggplot2 theme based on the publications of BdE.

Usage

theme_tidybde(...)

Arguments

...

Arguments passed on to ggplot2::theme_classic

base_size

base font size, given in pts.

base_family

base font family

base_line_size

base size for line elements

base_rect_size

base size for rect elements

Details

Theme based on ggplot2::theme_classic().

Value

A ggplot2 theme().

See Also

ggplot2::theme_classic()

Other bde_plot: bde_tidy_palettes(), scales_bde

Examples

library(ggplot2)
library(dplyr)
library(tidyr)

series_TC <- bde_series_full_load("TC_1_1.csv")

# If download was OK then plot
if (nrow(series_TC) > 0) {
  series_TC <- series_TC[c(1, 2)]

  series_TC_pivot <- series_TC %>%
    filter(
      Date >= "2020-01-01" & Date <= "2020-12-31",
      !is.na(series_TC[[2]])
    )

  names(series_TC_pivot) <- c("x", "y")

  ggplot(series_TC_pivot, aes(x = x, y = y)) +
    geom_line(linewidth = 0.8, color = bde_tidy_palettes(n = 1)) +
    labs(
      title = "Title",
      subtitle = "Some metric",
      caption = "Bank of Spain"
    ) +
    theme_tidybde()
}