I have a very large panel composed of many countries throughout many years. For a sample, say I have

structure(list(country = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 9L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 
10L, 10L, 10L, 10L), .Label = c("Bangladesh", "Barbados", "Benin", 
"Burundi", "Cameroon", "Chile", "Cyprus", "Ecuador", "Equatorial Guinea", 
"Gabon", "Ghana", "Guatemala", "Guinea", "Guyana", "Haiti", "India", 
"Jamaica", "Jordan", "Lebanon", "Liberia", "Madagascar", "Mali", 
"Mexico", "Morocco", "Mozambique", "Nepal", "Nicaragua", "Niger", 
"Oman", "Pakistan", "Panama", "Papua New Guinea", "Peru", "Rwanda", 
"Senegal", "Seychelles", "Sierra Leone", "Singapore", "Sri Lanka", 
"Sudan", "Togo", "Trinidad and Tobago", "Tunisia", "Turkey", 
"Uganda", "Zambia", "Zimbabwe"), class = c("pseries", "factor"
)), date = structure(c(12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 
20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 40L, 
41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 
54L, 1L, 2L, 3L, 4L, 5L, 6L), .Label = c("1965", "1966", "1967", 
"1968", "1969", "1970", "1971", "1972", "1973", "1974", "1975", 
"1976", "1977", "1978", "1979", "1980", "1981", "1982", "1983", 
"1984", "1985", "1986", "1987", "1988", "1989", "1990", "1991", 
"1992", "1993", "1994", "1995", "1996", "1997", "1998", "1999", 
"2000", "2001", "2002", "2003", "2004", "2005", "2006", "2007", 
"2008", "2009", "2010", "2011", "2012", "2013", "2014", "2015", 
"2016", "2017", "2018"), class = c("pseries", "factor")), dist = c(-2.44153863355447, 
-0.565497304455015, 1.4222058591902, 1.18583114700364, 0.936095936859405, 
-0.40582369098349, 2.08296049774769, -1.59377116576285, 0.316969269882462, 
-0.562808458278515, -0.438155688763343, 0.824980940313303, -0.60293744113302, 
0.397182279339227, 1.34777053122572, 0.00539983501313633, 0.0528824118570846, 
-0.838507946421168, 0.220969370384196, -1.06945294612116, 0.157324834050942, 
0.244080457191975, 0.215931770884978, 0.226176571912671, 0.197663973781873, 
0.183399695771442, 0.334605869075331, 0.0683789169881243, -0.0432432418415798, 
-0.191834311017179, -0.368292801016647, -0.572222256415503, -0.838601784768107, 
-1.15213567684887, -1.49844386483361, 2.39265920977342, 1.90573467650352, 
1.3362714819111, 0.158391029649629, 1.12699318386612, 2.38996532864524
), dummy = c(0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 
1, 0, 1, 1)), row.names = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 
10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 400L, 
401L, 402L, 403L, 404L, 405L, 406L, 407L, 408L, 409L, 410L, 411L, 
412L, 413L, 414L, 415L, 416L, 417L, 418L, 419L, 420L), class = "data.frame")

I would like to extract some countries and plot the variable "diff" for each of them. In other words, I would like to create different, several plots, for a sample of countries out of my panel.

I'm guessing I could start by

countries=c("Bangladesh", "Equatorial Guinea")

for (i in 1:length(countries)) {
  assign(countries[i],data_split[[i]])
 }

and then for the plots should be something similar, but I'm lost on the first part.

CodePudding user response：

You can split the data using split and then loop over the components of that result. The below gives just a default plot, but you can adjust it if required.

data_split <- split(data, data$country)

for (country in names(data_split)) {
  country_data <- data_split[[country]]
  if (nrow(country_data) > 0) {
    plot(as.numeric(country_data$date), country_data$dist, main = country)
  }
}

That said, like the commenters noted, facet_grid or facet_wrap is in my opinion a more elegant method to do the same. You can subset your data to select only the countries you want, before creating the plot.

Something like this:

countries <- c("Bangladesh", "Equatorial Guinea")
ggplot(data[data$country %in% countries, ], aes(as.numeric(as.character(date)), dist))  
  geom_line()  
  facet_wrap(~ country)