How to change scales of a multifaceted graph in ggplot2

Question

I have a graph composed of 27 subplots, each corresponding to a state, some states, such as SP and RJ have values much higher than other states and the scale of the graph is in larger intervals. Is there any way that each subplot has its own scale? I’ve tried using coord_cartesian with the y_lim, but then ends up cutting the state of SP and disrupts the view.

Graph that is coming out:

Code I am using:

suppressPackageStartupMessages({
  library(tidyverse)
})

url <- httr::GET("https://xx9p7hp1p7.execute-api.us-east-1.amazonaws.com/prod/PortalGeral",
                 httr::add_headers("X-Parse-Application-Id" =
                                     "unAFkcaNDeXajurGB7LChj8SgQYS2ptm")) %>%
  httr::content() %>%
  '[['("results") %>%
  '[['(1) %>%
  '[['("arquivo") %>%
  '[['("url")

dados <- utils::read.csv2(url, stringsAsFactors = FALSE, fileEncoding = "latin1")
dados$data <- lubridate::as_date(dados$data)

rm(url)

dados %>% 
  mutate(variacaoCasosNovos = c(rep(NA, 7), diff(casosNovos, 7)),
         variacaoCasosNovos = ifelse(is.nan(variacaoCasosNovos), NA, variacaoCasosNovos),
         variacaoCasosNovos = ifelse(is.infinite(variacaoCasosNovos), NA, variacaoCasosNovos)) %>%
  filter(data > "2020-02-29") %>%
  mutate(cor = as.factor(ifelse(variacaoCasosNovos > 0, yes = 1, no = 0))) %>% 
  ggplot() +
  geom_col(aes(x = data, y = variacaoCasosNovos, fill = cor), na.rm = TRUE, color = "black", size = 0.1) +
  geom_hline(yintercept = 0) +
  guides(fill = FALSE) +
  labs(x = "", y = "Variação") +
  scale_x_date(date_labels = "%b %d", date_breaks = "2 week") +
  theme(text = element_text(size = 10), axis.text.x = element_text(angle = 45, hjust = 1)) +
  facet_wrap(~estado, nrow = 3)

Answer 1

Use the argument scales of function facet_wrap.

suppressPackageStartupMessages({
  library(tidyverse)
})

url <- httr::GET("https://xx9p7hp1p7.execute-api.us-east-1.amazonaws.com/prod/PortalGeral",
                 httr::add_headers("X-Parse-Application-Id" =
                                     "unAFkcaNDeXajurGB7LChj8SgQYS2ptm")) %>%
  httr::content() %>%
  '[['("results") %>%
  '[['(1) %>%
  '[['("arquivo") %>%
  '[['("url")

dados <- utils::read.csv2(url, stringsAsFactors = FALSE, fileEncoding = "latin1")
dados$data <- lubridate::as_date(dados$data)

rm(url)

dados %>% 
  mutate(variacaoCasosNovos = c(rep(NA, 7), diff(casosNovos, 7)),
         variacaoCasosNovos = ifelse(is.nan(variacaoCasosNovos), NA, variacaoCasosNovos),
         variacaoCasosNovos = ifelse(is.infinite(variacaoCasosNovos), NA, variacaoCasosNovos)) %>%
  filter(data > "2020-02-29") %>%
  mutate(cor = as.factor(ifelse(variacaoCasosNovos > 0, yes = 1, no = 0))) %>% 
  ggplot() +
  geom_col(aes(x = data, y = variacaoCasosNovos, fill = cor), na.rm = TRUE, color = "black", size = 0.1) +
  geom_hline(yintercept = 0) +
  guides(fill = FALSE) +
  labs(x = "", y = "Variação") +
  scale_x_date(date_labels = "%b %d", date_breaks = "2 week") +
  theme(text = element_text(size = 10), axis.text.x = element_text(angle = 45, hjust = 1)) +
  facet_wrap(~estado, nrow = 3, scales = "free_y")

^{Created on 2020-05-08 by the reprex package (v0.3.0)}