Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----plot_names, echo=FALSE, cache=FALSE--------------------------------------
df <- structure(list(X1 = "Maria", X2 = "Ben", X3 = "Claudia", X4 = "Adam",
X5 = "Hannah", X6 = "Robert"), class = "data.frame", row.names = "**Customers:**")
knitr::kable(df, col.names = NULL)
## ----package structure, echo=FALSE, cache=FALSE-------------------------------
df <- structure(list(API = c("https://genderize.io", "https://agify.io", "https://nationalize.io"),
`R function` = c("`genderize(name)`", "`agify(name)`", "`nationalize(name)`"),
`Estimated variable` = c("Gender", "Age", "Nationality")),
class = "data.frame", row.names = c(NA, -3L))
knitr::kable(df, row.names = FALSE)
## ----result, echo=FALSE, cache=FALSE------------------------------------------
df <- structure(list(X1 = c("Maria", "female", "21", "CY"), X2 = c("Ben",
"male", "48", "AU"), X3 = c("Claudia", "female", "45", "CL"),
X4 = c("Adam", "male", "34", "PL"), X5 = c("Hannah", "female",
"27", "SL"), X6 = c("Robert", "male", "59", "US")), row.names = c("**Customers:**",
"**Estimated gender:**", "**Estimated age:**", "**Estimated nationality:**"
), class = "data.frame")
knitr::kable(df, col.names = NULL)
## ----setup, cache=FALSE-------------------------------------------------------
library("DemografixeR")
## ----save API function, eval=FALSE--------------------------------------------
# save_api_key(key = "__YOUR_API_KEY__")
## ----genderize, eval=TRUE, echo=TRUE, cache=FALSE-----------------------------
customers_names <- c("Maria", "Ben", "Claudia",
"Adam", "Hannah", "Robert")
customers_predicted_gender <- genderize(name = customers_names)
customers_predicted_gender # Print results
## ----genderize_class, cache=FALSE---------------------------------------------
class(customers_predicted_gender)
## ----genderize_dataframe_print, eval=FALSE------------------------------------
# gender_df <- genderize(name = customers_names, simplify = FALSE)
# customers_names %>%
# genderize(simplify = FALSE) %>%
# knitr::kable(row.names = FALSE)
#
## ----genderize_dataframe_calculate, cache=FALSE, echo=FALSE-------------------
df <- structure(list(name = c("Maria", "Ben", "Claudia", "Adam", "Hannah", "Robert"),
type = c("gender", "gender", "gender", "gender", "gender", "gender"),
gender = c("female", "male", "female", "male", "female", "male"),
probability = c(0.98, 0.95, 0.98, 0.98, 0.97, 0.99),
count = c(334287L, 77991L, 118604L, 116396L, 13198L, 177418L)),
row.names = c(5L, 2L, 3L, 1L, 4L, 6L), class = "data.frame")
knitr::kable(df, row.names = FALSE)
## ----agify_print, cache=FALSE, eval=FALSE-------------------------------------
# customers_predicted_age <- agify(name = customers_names, simplify = FALSE)
#
# customers_names %>%
# agify(simplify = FALSE) %>%
# knitr::kable(row.names = FALSE)
#
## ----agify_calculate, cache=FALSE, echo=FALSE---------------------------------
df <- structure(list(name = c("Maria", "Ben", "Claudia", "Adam", "Hannah", "Robert"),
type = c("age", "age", "age", "age", "age", "age"),
age = c(21L, 48L, 45L, 34L, 27L, 59L),
count = c(517258L, 75632L, 110105L, 110754L, 12843L, 160915L)),
row.names = c(5L, 2L, 3L, 1L, 4L, 6L), class = "data.frame")
knitr::kable(df, row.names = FALSE)
## ----nationality_print, cache=FALSE, eval=FALSE-------------------------------
# customers_predicted_nationality <- nationalize(name = customers_names, simplify = FALSE)
#
# customers_names %>%
# nationalize(simplify = FALSE) %>%
# knitr::kable(row.names = FALSE)
#
## ----nationality_calculate, cache=FALSE, echo=FALSE---------------------------
df <- structure(list(name = c("Maria", "Ben", "Claudia", "Adam", "Hannah", "Robert"),
type = c("nationality", "nationality", "nationality", "nationality", "nationality", "nationality"),
country_id = c("CY", "AU", "CL", "PL", "SL", "US"),
probability = c(0.0550797623186088, 0.0665534047056411, 0.0559340459826196, 0.0905835974781003, 0.267325397602591, 0.0909442129069588)),
row.names = c(5L, 2L, 3L, 1L, 4L, 6L), class = "data.frame")
knitr::kable(df, row.names = FALSE)
## ----country_id, cache=FALSE--------------------------------------------------
us_customers_predicted_gender<-genderize(name = customers_names,
country_id = "US")
us_customers_predicted_gender
us_customers_predicted_age<-agify(name = customers_names,
country_id = "US")
us_customers_predicted_age
## ----supported_countries_print, cache=FALSE, eval=FALSE-----------------------
# supported_countries(type = "genderize") %>%
# head(5) %>%
# knitr::kable(row.names = FALSE)
## ----supported_countries_calculate, cache=FALSE, echo=FALSE-------------------
df <- structure(list(country_id = c("AD", "AE", "AF", "AG", "AI"),
name = c("Andorra", "United Arab Emirates", "Afghanistan", "Antigua and Barbuda", "Anguilla"),
total = c(29783L, 145847L, 23531L, 1723L, 1081L)),
row.names = c(NA, 5L), class = "data.frame")
knitr::kable(df, row.names = FALSE)
## ----country_id_multi_print, cache=FALSE, eval=FALSE--------------------------
# agify(name = c("Hannah", "Ben"),
# country_id = c("US", "GB"),
# simplify = FALSE) %>%
# knitr::kable(row.names = FALSE)
#
## ----country_id_multi_calculate, cache=FALSE, echo=FALSE----------------------
df <- structure(list(name = c("Hannah", "Ben"),
type = c("age", "age"),
age = c(54L, 38L),
count = c(67L, 1980L),
country_id = c("US", "GB")),
row.names = 2:1, class = "data.frame")
knitr::kable(df, row.names = FALSE)
## ----meta_parameter_print, cache=FALSE, eval=FALSE----------------------------
# genderize(name = "Hannah",
# simplify = FALSE,
# meta = TRUE) %>%
# knitr::kable(row.names = FALSE)
## ----meta_parameter_calculate, cache=FALSE, echo=FALSE------------------------
df <- structure(list(name = "Hannah",
type = "gender",
gender = "female",
probability = 0.97,
count = 13198L,
api_rate_limit = 1000L,
api_rate_remaining = 977L,
api_rate_reset = 7218L,
api_request_timestamp =
structure(1588715982, class = c("POSIXct", "POSIXt"), tzone = "GMT")),
row.names = 1L, class = "data.frame")
knitr::kable(df, row.names = FALSE)
## ----sliced_false_print, cache=FALSE, eval=FALSE------------------------------
# nationalize(name = "Matthias",
# simplify = FALSE,
# sliced=FALSE) %>%
# knitr::kable(row.names = FALSE)
## ----sliced_false_calculate, cache=FALSE, echo=FALSE--------------------------
df <- structure(list(name = c("Matthias", "Matthias", "Matthias"),
type = c("nationality", "nationality", "nationality"),
country_id = c("DE", "AT", "CH"),
probability = c(0.41616382151, 0.265062479571606, 0.1106921611552)),
row.names = c(NA, 3L), class = "data.frame")
knitr::kable(df, row.names = FALSE)
## ----customers_end_print, echo=TRUE, cache=FALSE, eval=FALSE------------------
# library(dplyr)
#
# df<-data.frame("Customers:"=c("Maria", "Ben", "Claudia",
# "Adam", "Hannah", "Robert"),
# stringsAsFactors = FALSE,
# check.names = FALSE)
#
# df <- df %>% mutate(`Estimated gender:`= genderize(`Customers:`),
# `Estimated age:`= agify(`Customers:`),
# `Estimated nationality:`= nationalize(`Customers:`))
#
# df %>% t() %>% knitr::kable(col.names = NULL)
#
## ----customers_end_calc, echo=FALSE, cache=FALSE------------------------------
df <- structure(
c("Maria", "female", "21", "CY", "Ben", "male", "48",
"AU", "Claudia", "female", "45", "CL", "Adam", "male", "34",
"PL", "Hannah", "female", "27", "SL", "Robert", "male", "59", "US"),
.Dim = c(4L, 6L),
.Dimnames = list(c("Customers:", "Estimated gender:", "Estimated age:", "Estimated nationality:"), NULL))
knitr::kable(df, col.names = NULL)
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