Visualizando la tasa de paro diaria y anual de USA desde 1980 en R. Un ejemplo de uso de los paquetes readr, tibble, magrittr, dplyr, ggplot2, scales y lubridate de tidyverse.

tasa_paro.R

library(tidyverse)

economics_raw <- read_csv("https://gist.githubusercontent.com/jrosell/cf35e54a70914a3b23946c0a0d3a2cee/raw/47e52b910ecb23c3c7a8c549c9fd277797bd9970/economics_long.csv")
print(economics_raw, n = 5)

glimpse(economics_raw)

economics_raw %>%
    glimpse(x = .)

economics_raw %>%
    select(date, variable, value) %>% 
    glimpse()

economics_raw %>%
    select(date, variable, value) %>% 
    count(variable, sort = TRUE)

economics_raw %>%
    select(date, variable, value) %>% 
    ggplot(aes(x = date, y = value))

economics_raw %>%
    select(date, variable, value) %>% 
    ggplot(aes(date, value, colour = variable)) +
    geom_line()

economics_raw %>%
    select(date, variable, value) %>% 
    pivot_wider(names_from = variable, values_from = value) %>% 
    glimpse()

economics_raw %>%
    select(date, variable, value) %>% 
    pivot_wider(names_from = variable, values_from = value) %>% 
    mutate(paro = unemploy / pop) %>% 
    glimpse()

economics_raw %>%
    select(date, variable, value) %>% 
    pivot_wider(names_from = variable, values_from = value) %>% 
    mutate(paro = unemploy / pop) %>% 
    select(date, paro) %>% 
    glimpse()

economics_raw %>%
    select(date, variable, value) %>% 
    pivot_wider(names_from = variable, values_from = value) %>% 
    mutate(paro = unemploy / pop) %>% 
    select(date, paro) %>% 
    arrange(date) %>% 
    glimpse()

economics_raw %>%
    select(date, variable, value) %>% 
    pivot_wider(names_from = variable, values_from = value) %>% 
    mutate(paro = unemploy / pop) %>% 
    select(date, paro) %>% 
    arrange(date) %>% 
    filter(date >= '1980-01-01') %>% 
    glimpse() -> economics_dia

ggplot(economics_dia, aes(x = date, y = paro))

ggplot(economics_dia, aes(x = date, y = paro)) +
    geom_line() 

ggplot(economics_dia, aes(x = date, y = paro)) +
    geom_line() +
    scale_y_continuous(labels = scales::percent_format())

ggplot(economics_dia, aes(x = date, y = paro)) +
    geom_line() +
    scale_y_continuous(labels = scales::percent_format()) +
    labs(
        title = "Ratio de paro diario desde 1980 en USA",
        x = "Día",
        y =  "% Ratio de paro"
    )

tasa_paro_diaria_1980 <- function(df) {
    data <- df %>%
        select(date, variable, value) %>% 
        pivot_wider(names_from = variable, values_from = value) %>% 
        mutate(paro = unemploy / pop) %>% 
        select(date, paro) %>% 
        arrange(date) %>% 
        filter(date >= '1980-01-01')
    p <- ggplot(data, aes(x = date, y = paro)) +
        geom_line() +
        scale_y_continuous(labels = scales::percent_format()) +
        labs(
            title = "Tasa de paro diaria desde 1980 en USA",
            x = "Día",
            y =  "% paro"
        )
    return(p)
}

tasa_paro_diaria_1980(economics_raw)


economics_raw %>%
    select(date, variable, value) %>% 
    pivot_wider(names_from = variable, values_from = value) %>% 
    mutate(paro = unemploy / pop) %>% 
    select(date, paro) %>% 
    arrange(date) %>% 
    filter(date >= '1980-01-01') %>% 
    group_by(anual = lubridate::floor_date(date, unit = "years")) %>% 
    summarize(paro = median(paro)) %>% 
    glimpse() -> economics_anual

ggplot(economics_anual, aes(x = anual, y = paro)) +
    geom_line() +
    scale_y_continuous(labels = scales::percent_format()) +
    labs(
        title = "Ratio de paro anual desde 1980 en USA",
        x = "Año",
        y =  "% Ratio de paro"
    )

tasa_paro_anual_1980 <- function(df) {
    data <- df %>%
        select(date, variable, value) %>% 
        pivot_wider(names_from = variable, values_from = value) %>% 
        mutate(paro = unemploy / pop) %>% 
        select(date, paro) %>% 
        arrange(date) %>% 
        filter(date >= '1980-01-01') %>% 
        group_by(anual = lubridate::floor_date(date, unit = "years")) %>% 
        summarize(paro = median(paro))
    p <- ggplot(data, aes(x = anual, y = paro)) +
        geom_line() +
        scale_y_continuous(labels = scales::percent_format()) +
        labs(
            title = "Ratio de paro anual desde 1980 en USA",
            x = "Año",
            y =  "% Ratio de paro"
        )
    return(p)
}

tasa_paro_anual_1980(economics_raw)