Setup

library(tidyverse)

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library(janitor)

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library(plotly)

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load("TFR_long.Rdata")
load("IMR_long.Rdata")

Check for Mismatches

miss = anti_join(IMR_long,
                 TFR_long,
                 by = c("country_name","year"))
nrow(miss)

## [1] 0

Join

IMR_TFR = IMR_long %>% 
   left_join(TFR_long,
        by = c("country_name",
               "country_code",
               "year"))
glimpse(IMR_TFR)

## Rows: 16,226
## Columns: 5
## $ country_name <chr> "Aruba", "Aruba", "Aruba", "Aruba", "Aruba", "Aruba", "Ar…
## $ country_code <chr> "ABW", "ABW", "ABW", "ABW", "ABW", "ABW", "ABW", "ABW", "…
## $ year         <dbl> 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 196…
## $ IMR          <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ TFR          <dbl> 4.820, 4.655, 4.471, 4.271, 4.059, 3.842, 3.625, 3.417, 3…

Do a scatterplot of TFR by IMR

g = IMR_TFR %>% 
  ggplot(aes(IMR,TFR,group = country_name)) +
  geom_point(size = .1)
ggplotly(g)

Improve on this