Package 'pipr'

convert arguments and values of a function to a string to parse into other functions

Description

convert arguments and values of a function to a string to parse into other functions

Usage

args_to_string(il)

Arguments

il	list from as.list(environment()) right after the function is called.

Value

character

---

Build request version 2

Description

Build request version 2

Usage

build_request(server, api_version, endpoint, ...)

Arguments

server	character: Server. For WB internal use only
api_version	character: API version
endpoint	character: PIP API endpoint
...	other parameters

Value

httr2 request

---

build_request, OLD version

Description

build_request, OLD version

Usage

build_request_old(server, api_version, endpoint, ...)

Arguments

server	character: Server. For WB internal use only
api_version	character: API version
endpoint	character: PIP API endpoint
...	other parameters

Value

httr2 request

---

call a table from .pip env

Description

call a table from .pip env

Usage

call_aux(table = NULL)

Arguments

table

character: name of table in .pip env. If NULL, it displays the names of tables available in .pip env

Value

data frame of auxiliary table

Examples

# call one table

get_aux("gdp", assign_tb = TRUE, replace = TRUE) # PR 63
call_aux("gdp")

# see the name of several tables in memory
tb <- c("cpi", "ppp", "pop")
lapply(tb, get_aux, assign_tb = TRUE, replace = TRUE) # PR 63
call_aux()

---

Change the list-output to dataframe (Function from pipapi)

Description

Change the list-output to dataframe (Function from pipapi)

Usage

change_grouped_stats_to_csv(out)

Arguments

out	output from wbpip::gd_compute_pip_stats

Value

dataframe

---

Check internet connection and API status

Description

Check internet connection and API status

Usage

check_api(api_version = "v1", server = NULL)

Arguments

api_version	character: API version
server	character: Server. For WB internal use only

Value

character

Examples

## Not run: 
check_api()

## End(Not run)

---

Datt (1998) grouped data for rural india, 1983

Description

Dataset from Datt (1998) with grouped data for rural India in 1983.

Usage

datt_rural

Format

A data frame with 13 observations on the following 6 variables:

monthly_pc_exp

Welfare range class

mean_monthly_pc_exp

Mean welfare for given welfare range class

percentage_of_persons

Percentage of individuals in given welfare class

L

Cumulative welfare

p

Cumulative population

area

rural

@source Datt, G. (1998). See get_cp vignette.

---

Grouped data for urban india, 1983

Description

Dataset from Sarvekshana N26 Vol 9 N 4, created by the author following Datt(1998) methodology with grouped data for urban India in 1983.

Usage

datt_urban

Format

A data frame with 13 observations on the following 6 variables:

monthly_pc_exp

Welfare range class

mean_monthly_pc_exp

Mean welfare for given welfare range class

percentage_of_persons

Percentage of individuals in given welfare class

L

Cumulative welfare

p

Cumulative population

area

urban

@source Sarvekshana N26 Vol 9 N 4, and Datt, G. (1998) for methodology. See get_cp vignette.

---

Deletes content of the cache folder

Description

Deletes content of the cache folder

Usage

delete_cache()

Value

Side effect. Deletes files.

Examples

## Not run: delete_cache()

---

Display available auxiliary tables

Description

Display available auxiliary tables

Usage

display_aux(
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  simplify = TRUE,
  server = NULL,
  assign_tb = TRUE
)

Arguments

version	character: Data version. See get_versions()
ppp_version	ppp year to be used
release_version	date when the data was published in YYYYMMDD format
api_version	character: API version
format	character: Response format either of c("rds", "json", "csv")
simplify	logical: If TRUE (the default) the response is returned as a tibble
server	character: Server. For WB internal use only
assign_tb	logical: Whether to assign table to .pip env. Default is TRUE

Value

invisible tibble with names of auxiliary tables

Examples

## Not run: 
display_aux()

## End(Not run)

---

Get auxiliary data

Description

get_aux() Get an auxiliary dataset. If no table is specified a vector with possible inputs will be returned.

get_countries() Returns a table countries with their full names, ISO codes, and associated region code

Usage

get_aux(
  table = NULL,
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  simplify = TRUE,
  server = NULL,
  assign_tb = FALSE,
  replace = FALSE
)

get_countries(
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  server = NULL
)

get_regions(
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  server = NULL
)

get_cpi(
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  server = NULL
)

get_dictionary(
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  server = NULL
)

get_gdp(
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  server = NULL
)

get_incgrp_coverage(
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  server = NULL
)

get_interpolated_means(
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  server = NULL
)

get_hfce(
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  server = NULL
)

get_pop(
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  server = NULL
)

get_pop_region(
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  server = NULL
)

get_ppp(
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  server = NULL
)

get_region_coverage(
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  server = NULL
)

get_survey_means(
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  server = NULL
)

Arguments

table	Aux table
version	character: Data version. See get_versions()
ppp_version	ppp year to be used
release_version	date when the data was published in YYYYMMDD format
api_version	character: API version
format	character: Response format either of c("rds", "json", "csv")
simplify	logical: If TRUE (the default) the response is returned as a tibble
server	character: Server. For WB internal use only
assign_tb	assigns table to specified name to the .pip environment. If FALSE no assignment will performed. If TRUE, the table will be assigned to exactly the same name as the one of the desired table. If character, the table will be assigned to that name.
replace	logical: force replacement of aux files in .pip env. Default is FALSE.

Value

If simplify = FALSE, it returns a list of class "pip_api". If simplify = TRUE, it returns a tibble with the requested data. This is the default. Only for get_aux(), If assign_tb = TRUE or character, it returns TRUE when data was assign properly to .pip env. FALSE, if it was not assigned.

Functions

• get_countries(): Returns a table countries with their full names, ISO codes, and associated region code

• get_regions(): Returns a table regional grouping used for computing aggregate poverty statistics.

• get_cpi(): Returns a table of Consumer Price Index (CPI) values used for poverty and inequality computations. statistics

• get_dictionary(): Returns a data dictionary with a description of all variables available through the PIP API.

• get_gdp(): Returns a table of Growth Domestic Product (GDP) values used for poverty and inequality statistics.

• get_incgrp_coverage(): Returns a table of survey coverage for low and lower-middle income countries. If this coverage is less than 50%, World level aggregate statistics will not be computed.

• get_interpolated_means(): Returns a table of key information and statistics for all years for which poverty and inequality statistics are either available (household survey exists) or extra- / interpolated. Please see get_dictionary for more information about each variable available in this table.

• get_hfce(): Returns a table of Household Final Consumption Expenditure (HFCE) values used for poverty and inequality computations.

• get_pop(): Returns a table of population values used for poverty and inequality computations.

• get_pop_region(): Returns a table of total population by region-year. These values are used for the computation of regional aggregate poverty statistics.

• get_ppp(): Returns a table of Purchasing Power Parity (PPP) values used for poverty and inequality computations.

• get_region_coverage(): Return a table of regional survey coverage: Percentage of available surveys for a specific region-year.

• get_survey_means(): Returns a table of all available surveys and associated key statistics. Please see get_dictionary for more information about each variable available in this table.

Examples

## Not run: 
# Get list of tables
x <- get_aux()

# Get GDP data
df <- get_aux("gdp")

# Get countries
df <- get_aux("countries")

# Display auxiliary tables
get_aux()

# Display and assign to .pip env the selected auxiliary table
get_aux(assign_tb = TRUE)

# Bind gdp table to "gdp" in .pip env
get_aux("gdp", assign_tb = TRUE)

# Bind gdp table to "new_name" in .pip env
get_aux("gdp", assign_tb = "new_name")


## End(Not run)
## Not run: 
# Short hand to get countries
get_countries()

## End(Not run)
## Not run: 
# Short hand to get regions
get_regions()

## End(Not run)
## Not run: 
# Short hand to get cpi
get_cpi()

## End(Not run)
## Not run: 
# Short hand to get dictionary
get_dictionary()

## End(Not run)
## Not run: 
# Short hand to get gdp
get_gdp()

## End(Not run)
## Not run: 
# Short hand to get incgrp_coverage
get_incgrp_coverage()

## End(Not run)
## Not run: 
# Short hand to get interpolated_means
get_interpolated_means()

## End(Not run)
## Not run: 
# Short hand to get hfce
get_hfce()

## End(Not run)
## Not run: 
# Short hand to get pop
get_pop()

## End(Not run)
## Not run: 
# Short hand to get pop_region
get_pop_region()

## End(Not run)
## Not run: 
# Short hand to get ppp
get_ppp()

## End(Not run)
## Not run: 
# Short hand to get region_coverage
get_region_coverage()

## End(Not run)
## Not run: 
# Short hand to get survey_means
get_survey_means()

## End(Not run)

---

Provides some information about cached items

Description

Provides some information about cached items

Usage

get_cache_info()

Value

character.

Examples

## Not run: get_cache_info()

---

Get Country Profiles

Description

Get Country Profiles

Usage

get_cp(
  country = "all",
  povline = 2.15,
  version = NULL,
  ppp_version = 2017,
  release_version = NULL,
  api_version = "v1",
  format = c("arrow", "rds", "json", "csv"),
  simplify = TRUE,
  server = NULL
)

Arguments

country	character: A vector with one or more country ISO 3 codes or 'all'
povline	numeric: Poverty line
version	character: Data version. See get_versions()
ppp_version	ppp year to be used
release_version	date when the data was published in YYYYMMDD format
api_version	character: API version
format	character: Response format either of c("rds", "json", "csv")
simplify	logical: If TRUE (the default) the response is returned as a tibble
server	character: Server. For WB internal use only

Value

If simplify = FALSE, it returns a list of class "pip_api". If simplify = TRUE, it returns a tibble with the requested data. This is the default. Only for get_aux(), If assign_tb = TRUE or character, it returns TRUE when data was assign properly to .pip env. FALSE, if it was not assigned.

Examples

## Not run: 
# One country, all years with default ppp_version = 2017
res <- get_cp(country = "AGO")

# All countries, povline = 1.9
res <- get_cp(povline = 1.9)

# All countries and years with default values
res <- get_cp()

## End(Not run)

---

Get Country Profiles Key Indicators

Description

Get Country Profiles Key Indicators

Usage

get_cp_ki(
  country = NULL,
  povline = 2.15,
  version = NULL,
  ppp_version = 2017,
  release_version = NULL,
  api_version = "v1",
  simplify = TRUE,
  server = NULL
)

Arguments

country	character: A vector with one or more country ISO 3 codes or 'all'
povline	numeric: Poverty line
version	character: Data version. See get_versions()
ppp_version	ppp year to be used
release_version	date when the data was published in YYYYMMDD format
api_version	character: API version
simplify	logical: If TRUE (the default) the response is returned as a tibble
server	character: Server. For WB internal use only

Value

If simplify = FALSE, it returns a list of class "pip_api". If simplify = TRUE, it returns a tibble with the requested data. This is the default. Only for get_aux(), If assign_tb = TRUE or character, it returns TRUE when data was assign properly to .pip env. FALSE, if it was not assigned.

Examples

## Not run: 
# One country, all years with default ppp_version = 2017
res <- get_cp(country = "IDN")

# All countries, povline = 1.9
res <- get_cp(country = "IDN", povline = 1.9)


## End(Not run)

---

Get grouped stats

Description

Get grouped stats from the PIP API.

Usage

get_gd(
  cum_welfare,
  cum_population,
  estimate = c("stats", "lorenz", "params"),
  requested_mean = NULL,
  povline = NULL,
  popshare = NULL,
  lorenz = NULL,
  n_bins = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  simplify = TRUE,
  server = NULL
)

Arguments

cum_welfare	numeric: Cumulative welfare values, expressed in shares. Any length. They should be monotonically increasing, and sum to 1.
cum_population	numeric: Cumulative population values, expressed in shares. Any length. They should be monotonically increasing, and sum to 1.
estimate	character: One of "stats", "lorenz", "params".
requested_mean	numeric: Requested mean.
povline	numeric: Poverty line. Required for estimate = "stats".
popshare	numeric: Proportion of the population living below the poverty line
lorenz	character: Lorenz curve methodology. Either "lb" or "lq".
n_bins	numeric: Number of bins. Required for estimate = "lorenz".
api_version	character: API version
format	character: Response format either of c("rds", "json", "csv")
simplify	logical: If TRUE (the default) the response is returned as a tibble
server	character: Server. For WB internal use only

Value

data.frame

Examples

## Not run: 

datt_data <- data.frame(p = c(0.0092, 0.0339, 0.0850, 0.160, 0.2609, 0.4133,
                              0.5497, 0.7196, 0.8196, 0.9174, 0.9570, 0.9751,
                              1),
                       L = c(0.00208, 0.001013, 0.03122, 0.07083, 0.12808,
                             0.23498, 0.34887, 0.51994, 0.64270, 0.79201,
                             0.86966, 0.91277, 1))

# estimate = 'stats': retrieve poverty statistics.
stats <- get_gd(cum_welfare = datt_data$L, cum_population = datt_data$p,
                estimate = "stats",
                requested_mean = 19, # default is 1.
                povline = 2.15)  # default is 1.

# estimate = 'lorenz': retrieve Lorenz curve data points for a specified number of bins.

## Best lorenz curve methodolody selected by default:
lorenz <- get_gd(cum_welfare = datt_data$L,
                 cum_population = datt_data$p,
                 estimate = "lorenz",
                 n_bins = 100)  # must be specified, default is NULL.

## Specify lorenz curve methodology:
### Beta Lorenz ("lb")
lorenz_lb <- get_gd(cum_welfare = datt_data$L,
                 cum_population = datt_data$p,
                 estimate = "lorenz",
                 lorenz = "lb",
                 n_bins = 100)

### Quadratic Lorenz ("lq")
lorenz_lq <- get_gd(cum_welfare = datt_data$L,
                 cum_population = datt_data$p,
                 estimate = "lorenz",
                 lorenz = "lq",
                 n_bins = 100)

# estimate = 'params': retrieve regression parameters used for the lorenz curve estimation.
params <- get_gd(cum_welfare = datt_data$L,
                 cum_population = datt_data$p,
                 estimate = "params")

## End(Not run)

---

Get PIP info

Description

Get information about the API.

Usage

get_pip_info(api_version = "v1", server = NULL)

Arguments

api_version	character: API version
server	character: Server. For WB internal use only

Value

list

Examples

## Not run: 
get_pip_info()

## End(Not run)

---

Get poverty and inequality statistics

Description

Get poverty and inequality statistics

Usage

get_stats(
  country = "all",
  year = "all",
  povline = NULL,
  popshare = NULL,
  fill_gaps = FALSE,
  nowcast = FALSE,
  subgroup = NULL,
  welfare_type = c("all", "income", "consumption"),
  reporting_level = c("all", "national", "urban", "rural"),
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  api_version = "v1",
  format = c("arrow", "rds", "json", "csv"),
  simplify = TRUE,
  server = NULL
)

get_wb(
  year = "all",
  povline = NULL,
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  simplify = TRUE,
  server = NULL
)

get_agg(
  year = "all",
  povline = NULL,
  version = NULL,
  ppp_version = NULL,
  release_version = NULL,
  aggregate = NULL,
  api_version = "v1",
  format = c("rds", "json", "csv"),
  simplify = TRUE,
  server = NULL
)

Arguments

country	character: A vector with one or more country ISO 3 codes or 'all'
year	integer: A vector with one or more years or 'all'
povline	numeric: Poverty line
popshare	numeric: Proportion of the population living below the poverty line
fill_gaps	logical: If TRUE, will interpolate / extrapolate values for missing years
nowcast	logical: If TRUE, will return nowcast estimates.
subgroup	character: If used result will be aggregated for predefined sub-groups. Either 'wb_regions' or 'none'.
welfare_type	character: Welfare type either of c("all", "income", "consumption")
reporting_level	character: Geographical reporting level either of c("all", "national", "urban", "rural")
version	character: Data version. See get_versions()
ppp_version	ppp year to be used
release_version	date when the data was published in YYYYMMDD format
api_version	character: API version
format	character: Response format either of c("rds", "json", "csv")
simplify	logical: If TRUE (the default) the response is returned as a tibble
server	character: Server. For WB internal use only
aggregate	character: Aggregate name. See get_aux("countries") for available options.

Value

If simplify = FALSE, it returns a list of class "pip_api". If simplify = TRUE, it returns a tibble with the requested data. This is the default. Only for get_aux(), If assign_tb = TRUE or character, it returns TRUE when data was assign properly to .pip env. FALSE, if it was not assigned.

Examples

## Not run: 
# One country-year
res <- get_stats(country = "AGO", year = 2000)

# All years for a specific country
res <- get_stats(country = "AGO", year = "all")

# All countries and years
res <- get_stats(country = "all", year = "all")

# All countries and years w/ alternative poverty line
res <- get_stats(country = "all", year = "all", povline = 3.2)

# Fill gaps for years without available survey data
res <- get_stats(country = "all", year = "all", fill_gaps = TRUE)

# Proportion living below the poverty line
res <- get_stats(country = "all", year = "all", popshare = .4)

# World Bank global and regional aggregates
res <- get_stats("all", year = "all", subgroup = "wb")

# Short hand to get WB global/regional stats
res <- get_wb()

# Short hand to get fcv stats
res <- get_agg(aggregate = "fcv", server = "qa")

# Custom aggregates
res <- get_stats(c("ARG", "BRA"), year = "all", subgroup = "none")

## End(Not run)

---

Get versions

Description

Get available data versions.

Usage

get_versions(api_version = "v1", server = NULL, simplify = TRUE)

Arguments

api_version	character: API version
server	character: Server. For WB internal use only
simplify	logical: If TRUE (the default) the response is returned as a tibble

Value

tibble or list

Examples

## Not run: 
get_versions()

## End(Not run)

---

parse_error_body

Description

Helper function to parse error messages generated by the PIP API

Usage

parse_error_body(resp)

Arguments

resp	A httr response

Value

character

---

pip_is_transient

Description

Helper function to determine if an error is due to the number of requests going over the rate limit

Usage

pip_is_transient(resp)

Arguments

resp	A httr response

Value

logical

---

retry_after

Description

Helper function to determine how much time to wait before a new query can be sent

Usage

retry_after(resp)

Arguments

resp	A httr response

Value

numeric

---

Unnest the key indicators

Description

Unnest the key indicators

Usage

unnest_ki(out)

Arguments

out	parsed and simplified output from cp-key-indicators endpoint

Value

data frame, unnested.

Functions

• unnest_ki(): takes the simplified output from cp-key-indicators endpoint and unnests it.

---