Package 'econtools'

Title: Enrich and Analyze Sovereign-Level Economic Data
Description: Provides a consistent set of functions for enriching and analyzing sovereign-level economic data. Economists, data scientists, and financial professionals can use the package to add standardized identifiers, demographic and macroeconomic indicators, and derived metrics such as gross domestic product per capita or government expenditure shares.
Authors: Christoph Scheuch [aut, cre, cph] (ORCID: <https://orcid.org/0009-0004-0423-6819>)
Maintainer: Christoph Scheuch <[email protected]>
License: MIT + file LICENSE
Version: 0.1.1.9000
Built: 2026-05-11 09:36:58 UTC
Source: https://github.com/tidy-intelligence/r-econtools

Help Index

Add GDP to Country Data

Description

Add GDP to Country Data

Usage

add_gdp_column(
  df,
  id_column,
  id_type = "iso3_code",
  date_column = NULL,
  target_column = "gdp",
  usd = TRUE
)

Arguments

df

A data frame containing country identifiers.
id_column

Name of the column containing country identifiers.
id_type

Type of country identifier. Defaults to "iso3_code".
date_column

Optional. Name of the column containing dates for time-specific data.
target_column

Name of the output column. Defaults to "gdp".
usd

Logical. Indicates whether GDP should be in USD or local currency. Defaults to "TRUE".

Value

A data frame with an additional column containing GDP data.

Examples

# Add most recent GDP values
df <- data.frame(country = c("USA", "CHN", "DEU"))
result <- add_gdp_column(df, id_column = "country")

# Add year-specific GDP values
df <- data.frame(country = c("USA", "CHN"), year = c(2019, 2020))
result <- add_gdp_column(df, id_column = "country", date_column = "year")

Add Government Expenditure to Country Data

Description

Add Government Expenditure to Country Data

Usage

add_gov_exp_column(
  df,
  id_column,
  id_type = "iso3_code",
  date_column = NULL,
  target_column = "gov_exp"
)

Arguments

df

A data frame containing country identifiers.
id_column

Name of the column containing country identifiers.
id_type

Type of country identifier. Defaults to "iso3_code".
date_column

Optional. Name of the column containing dates for time-specific data.
target_column

Name of the output column. Defaults to "gov_exp".

Value

A data frame with an additional column containing government expenditure data.

Examples

# Add government expenditure
df <- data.frame(country = c("USA", "GBR", "FRA"))
result <- add_gov_exp_column(df, id_column = "country")

# With years
df <- data.frame(country = c("USA", "GBR"), year = c(2010, 2020))
result <- add_gov_exp_column(df, id_column = "country", date_column = "year")

Add Government Expenditure as Share of GDP to Country Data

Description

Add Government Expenditure as Share of GDP to Country Data

Usage

add_gov_exp_share_column(
  df,
  id_column,
  id_type = "iso3_code",
  date_column = NULL,
  target_column = "gov_exp_share"
)

Arguments

df

A data frame containing country identifiers.
id_column

Name of the column containing country identifiers.
id_type

Type of country identifier. Defaults to "iso3_code".
date_column

Optional. Name of the column containing dates for time-specific data.
target_column

Name of the output column. Defaults to "gov_exp".

Value

A data frame with an additional column containing government expenditure as share of GDP data.

Examples

# Add government expenditure share of GDP
df <- data.frame(country = c("USA", "JPN", "AUS"))
result <- add_gov_exp_share_column(df, id_column = "country")

# With specific years
df <- data.frame(country = c("USA", "JPN"), year = c(2015, 2020))
result <- add_gov_exp_share_column(
  df, id_column = "country", date_column = "year"
)

Add Income Levels to Country Data

Description

Add Income Levels to Country Data

Usage

add_income_level_column(
  df,
  id_column,
  id_type = "iso3_code",
  target_column = "income_level"
)

Arguments

df

A data frame containing country identifiers.
id_column

Name of the column containing country identifiers.
id_type

Type of country identifier. Defaults to "iso3_code".
target_column

Name of the output column. Defaults to "income_level".

Value

A data frame with a additional columns containing the income level ID and name.

Examples

# Add income levels using ISO3 codes
df <- data.frame(country = c("USA", "NGA", "IND"))
result <- add_income_level_column(df, id_column = "country")

Add ISO-3 Codes to Country Data

Description

Add ISO-3 Codes to Country Data

Usage

add_iso3_codes_column(df, id_column, target_column = "iso3_code")

Arguments

df

A data frame containing country identifiers.
id_column

Name of the column containing country identifiers.
target_column

Name of the output column. Defaults to "iso3_code".

Value

A data frame with an additional column containing the ISO-3 code.

Examples

# Convert country names to ISO3 codes
df <- data.frame(name = c("United States", "Canada", "Mexico"))
result <- add_iso3_codes_column(df, id_column = "name")

Add Population Column to Country Data

Description

Add Population Column to Country Data

Usage

add_population_column(
  df,
  id_column,
  id_type = "iso3_code",
  date_column = NULL,
  target_column = "population"
)

Arguments

df

A data frame containing country identifiers.
id_column

Name of the column containing country identifiers.
id_type

Type of country identifier. Defaults to "iso3_code".
date_column

Optional. Name of the column containing dates for time-specific data.
target_column

Name of the output column. Defaults to "population".

Value

A data frame with an additional column containing population data.

Examples

# Add population data using ISO3 codes
df <- data.frame(country = c("USA", "CAN", "MEX"))
result <- add_population_column(df, id_column = "country")

# Add population data with specific dates
df <- data.frame(country = c("USA", "CAN"), year = c(2019, 2020))
result <- add_population_column(
 df, id_column = "country", date_column = "year"
)

Add Population Density Column to Country Data

Description

Add Population Density Column to Country Data

Usage

add_population_density_column(
  df,
  id_column,
  id_type = "iso3_code",
  date_column = NULL,
  target_column = "population_density"
)

Arguments

df

A data frame containing country identifiers.
id_column

Name of the column containing country identifiers.
id_type

Type of country identifier. Defaults to "iso3_code".
date_column

Optional. Name of the column containing dates for time-specific data.
target_column

Name of the output column. Defaults to "population_density".

Value

A data frame with an additional column containing population density data.

Examples

# Add population density using ISO3 codes
df <- data.frame(country = c("FRA", "DEU", "ESP"))
result <- add_population_density_column(df, id_column = "country")

# Add population density with year
df <- data.frame(country = c("FRA", "DEU"), year = c(2015, 2020))
result <- add_population_density_column(
  df, id_column = "country", date_column = "year"
)

Add Population Share Column to Country Data

Description

Add Population Share Column to Country Data

Usage

add_population_share_column(
  df,
  id_column,
  id_type = "iso3_code",
  date_column = NULL,
  value_column = "value",
  target_column = "population_share"
)

Arguments

df

A data frame containing country identifiers.
id_column

Name of the column containing country identifiers.
id_type

Type of country identifier. Defaults to "iso3_code".
date_column

Optional. Name of the column containing dates for time-specific data.
value_column

Name of the column containing the value to divided by population.
target_column

Name of the output column. Defaults to "population_share".

Value

A data frame with an additional column containing a new column with a value divided by population.

Examples

# Compute value as a share of population
df <- data.frame(country = c("USA", "CAN"), value = c(1000, 2000))
result <- add_population_share_column(
  df, id_column = "country", value_column = "value"
)

# With year-specific values
df <- data.frame(
  country = c("USA", "CAN"),
  year = c(2019, 2020),
  value = c(1500, 1800)
)
result <- add_population_share_column(
  df, id_column = "country", date_column = "year"
)

Add Poverty Ratio Column to Country Data

Description

Add Poverty Ratio Column to Country Data

Usage

add_poverty_ratio_column(
  df,
  id_column,
  id_type = "iso3_code",
  date_column = NULL,
  target_column = "poverty_ratio"
)

Arguments

df

A data frame containing country identifiers.
id_column

Name of the column containing country identifiers.
id_type

Type of country identifier. Defaults to "iso3_code".
date_column

Optional. Name of the column containing dates for time-specific data.
target_column

Name of the output column. Defaults to "poverty_ratio".

Value

A data frame with an additional column containing poverty ratio data.

Examples

# Add poverty ratio using ISO3 codes
df <- data.frame(country = c("USA", "IND", "BRA"))
result <- add_poverty_ratio_column(df, id_column = "country")

# Add poverty ratio with specific dates
df <- data.frame(country = c("USA", "IND"), year = c(2018, 2020))
result <- add_poverty_ratio_column(
  df, id_column = "country", date_column = "year"
)

Add Short Names to Country Data

Description

Add Short Names to Country Data

Usage

add_short_names_column(df, id_column, target_column = "name_short")

Arguments

df

A data frame containing country identifiers.
id_column

Name of the column containing country identifiers.
target_column

Name of the output column. Defaults to "name_short".

Value

A data frame with an additional column containing the short names.

Examples

# Add short names using ISO3 codes
df <- data.frame(country = c("USA", "FRA", "JPN"))
result <- add_short_names_column(df, id_column = "country")