Compare versions of PIP

compare_pip_versions.R

#   ____________________________________________________________________________
#   country level                                                           ####

sr0 <- pipr::get_stats("SYR", fill_gaps = TRUE, server = "dev")
sr1 <-
  pipr::get_stats("SYR",
                  fill_gaps = TRUE,
                  server = "dev",
                  version = "20220428_2011_02_02_PROD")
setDT(sr0)
setDT(sr1)

to_keep <- c("country_code", "year", "headcount", "mean")
sr0 <- sr0[, ..to_keep]
sr1 <- sr1[, ..to_keep]

setnames(sr0, c("headcount", "mean"), c("hc_0503", "mn_0503"))
setnames(sr1, c("headcount", "mean"), c("hc_0408", "mn_0408"))

sr <- joyn::merge(sr0, sr1, reportvar = FALSE)
sr <- sr[year >= 2010]

sr <- 
  melt(sr, 
       measure.vars = patterns(headcount = "^hc_", mean = "^mn_"), 
       id.vars = "year", 
       variable.name = "source")

sr_hc <- 
  ggplot(sr, aes(x = year, 
                 y = headcount, 
                 color = source)) +
  geom_line() +
  geom_point() +
  theme_minimal() +
  theme(
    legend.position = "bottom", 
    legend.title = element_blank()
    
  ) +
  scale_colour_discrete(labels = c("May 03", "Apr 08")) +
  labs(y = "Poverty headcount (\\$1.9)", 
       title = "Syria (Poverty)")
sr_hc


sr_mn <- 
  ggplot(sr, aes(x = year, 
                 y = mean, 
                 color = source)) +
  geom_line() +
  geom_point() +
  theme_minimal() +
  theme(
    legend.position = "bottom", 
    legend.title = element_blank()
    
  ) +
  scale_colour_discrete(labels = c("May 03", "Apr 08")) +
  labs(y = "Mean", 
       title = "Syria (Mean)")
sr_mn


#   ____________________________________________________________________________
#   regional level                                                          ####


sr0 <- pipr::get_wb(server = "dev")
sr1 <-
  pipr::get_wb(server = "dev",
               version = "20220428_2011_02_02_PROD")
setDT(sr0)
setDT(sr1)


to_keep <- c("region_code", "year", "headcount", "mean")
sr0 <- sr0[, ..to_keep]
sr1 <- sr1[, ..to_keep]

setnames(sr0, c("headcount", "mean"), c("hc_0503", "mn_0503"))
setnames(sr1, c("headcount", "mean"), c("hc_0408", "mn_0408"))

sr <- joyn::merge(sr0, sr1, reportvar = FALSE)
sr <- sr[year >= 2010]

sr <- 
  melt(sr, 
       measure.vars = patterns(headcount = "^hc_", mean = "^mn_"), 
       id.vars = c("region_code", "year"), 
       variable.name = "source")

mna <- sr[region_code == "MNA"]

mna_hc <- 
  ggplot(mna, aes(x = year, 
                 y = headcount, 
                 color = source)) +
  geom_line() +
  geom_point() +
  theme_minimal() +
  theme(
    legend.position = "bottom", 
    legend.title = element_blank()
    
  ) +
  scale_colour_discrete(labels = c("May 03", "Apr 08")) +
  labs(y = "Poverty headcount (\\$1.9)", 
       title = "Middle East and North Africa (Poverty)")
mna_hc


mna_mn <- 
  ggplot(mna, aes(x = year, 
                 y = mean, 
                 color = source)) +
  geom_line() +
  geom_point() +
  theme_minimal() +
  theme(
    legend.position = "bottom", 
    legend.title = element_blank()
    
  ) +
  scale_colour_discrete(labels = c("May 03", "Apr 08")) +
  labs(y = "Mean", 
       title = "Middle East and North Africa (Mean)")
mna_mn


#   ____________________________________________________________________________
#   world                                                                   ####


wld <- sr[region_code == "WLD"]

wld_hc <- 
  ggplot(wld, aes(x = year, 
                  y = headcount, 
                  color = source)) +
  geom_line() +
  geom_point() +
  theme_minimal() +
  theme(
    legend.position = "bottom", 
    legend.title = element_blank()
    
  ) +
  scale_colour_discrete(labels = c("May 03", "Apr 08")) +
  labs(y = "Poverty headcount (\\$1.9)", 
       title = "World (Poverty)")
wld_hc


wld_mn <- 
  ggplot(wld, aes(x = year, 
                  y = mean, 
                  color = source)) +
  geom_line() +
  geom_point() +
  theme_minimal() +
  theme(
    legend.position = "bottom", 
    legend.title = element_blank()
    
  ) +
  scale_colour_discrete(labels = c("May 03", "Apr 08")) +
  labs(y = "Mean", 
       title = "World (Mean)")
wld_mn