class: center, middle, inverse, title-slide # Importar y limpiar datos en R ## Programación para el análisis de datos ### Departamento de Ciencias Sociales, UCU - Martín Opertti --- # Segunda mitad de curso <table class="table table-striped table-hover table-condensed" style="font-size: 12px; margin-left: auto; margin-right: auto;"> <thead> <tr> <th style="text-align:left;position: sticky; top:0; background-color: #FFFFFF;"> Semana </th> <th style="text-align:left;position: sticky; top:0; background-color: #FFFFFF;"> Clase </th> </tr> </thead> <tbody> <tr> <td style="text-align:left;"> 2022-10-11 </td> <td style="text-align:left;"> Importar y limpiar datos en R </td> </tr> <tr> <td style="text-align:left;"> 2022-10-13 </td> <td style="text-align:left;"> Importar y limpiar datos en R </td> </tr> <tr> <td style="text-align:left;"> 2022-10-18 </td> <td style="text-align:left;"> Estadística descriptiva en R </td> </tr> <tr> <td style="text-align:left;"> 2022-10-20 </td> <td style="text-align:left;"> Estadística descriptiva en R </td> </tr> <tr> <td style="text-align:left;"> 2022-10-25 </td> <td style="text-align:left;"> Manipulación de datos en R </td> </tr> <tr> <td style="text-align:left;"> 2022-10-27 </td> <td style="text-align:left;"> Manipulación de datos en R </td> </tr> <tr> <td style="text-align:left;"> 2022-11-01 </td> <td style="text-align:left;"> Manipulación de datos en R II </td> </tr> <tr> <td style="text-align:left;"> 2022-11-03 </td> <td style="text-align:left;"> Visualización de datos en R </td> </tr> <tr> <td style="text-align:left;"> 2022-11-08 </td> <td style="text-align:left;"> Visualización de datos en R </td> </tr> <tr> <td style="text-align:left;"> 2022-11-10 </td> <td style="text-align:left;"> Estadística inferencial en R </td> </tr> <tr> <td style="text-align:left;"> 2022-11-15 </td> <td style="text-align:left;"> Parcial R </td> </tr> <tr> <td style="text-align:left;"> 2022-11-17 </td> <td style="text-align:left;"> R Markdown + Pauta trabajo final </td> </tr> <tr> <td style="text-align:left;"> 2022-11-22 </td> <td style="text-align:left;"> Progrmación avanzada </td> </tr> <tr> <td style="text-align:left;"> 2022-11-24 </td> <td style="text-align:left;"> Taller / Python </td> </tr> <tr> <td style="text-align:left;"> 2022-11-29 </td> <td style="text-align:left;"> Presentaciones </td> </tr> <tr> <td style="text-align:left;"> 2022-12-01 </td> <td style="text-align:left;"> Presentaciones y cierre </td> </tr> </tbody> </table> --- class: inverse, center, middle # Directorios de trabajo y proyectos de R (.Rproj) --- ## Directorios de trabajo - Para abrir en R un archivo guardado en tu computadora, debes especificar en qué carpeta está guardado, para esto hay varias opciones. Primero, puedes fijar un directorio por defecto: .codefont[ ```r # Puedo fijar el directorio de trabajo con la función setwd() # Fijar la carpeta donde vamos a importar y exportar los archivos: setwd("micompu/micarpeta") getwd() # Con está función puedo consultar el directorio ``` ] .codefont[ ```r # Ahora, si quiero leer un archivo que esté en "micompu/micarpeta" simplemente # escribo su nombre dentro de la función, en el lugar del "path". # Supongamos que tengo dentro de la carpeta "micarpeta" un excel con datos # de desempleo en Uruguay: library(readxl) desempleo_uru <- read_excel("data/desempleo.xlsx") head(desempleo_uru, 4) ``` ``` ## # A tibble: 4 x 2 ## Year tasa ## <dbl> <dbl> ## 1 1990 8.5 ## 2 1991 8.9 ## 3 1992 9 ## 4 1993 8.3 ``` ] --- ## Directorios de trabajo También podemos no fijar un directorio para la sesión e ir especificando los directorios completos dentro de cada función: ```r desempleo_uru <- read_excel("micompu/micarpeta/data/desempleo.xlsx") ``` --- ## Proyectos de R (.Rproj) - La mejor práctica para que nuestros scripts sean portables y reproducibles, es utilzar R Projects (`.Rproj`). - Para crear un `.Rproj` vamos a `File/New Project` y ahí nos encontramos con la opción de crear una carpeta para guardar los archivos o utilizar una carpeta ya existente. - Al crear un proyecto de R se creará un archivo de extensión `.Rproj`, cuando le damos click se inicia una nueva sesión de R cuyo directorio es por defecto la carpeta en la que está guardado. - Podemos usar directorios relativos dentro de la carpeta en la que se aloja nuestro `.Rproj` para importar y exportar datos a y desde R. Esto hace que uno pueda cambiar la carpeta o compartirla y el script correrá de igual manera (a diferencia de si utilizamos `setwd()`) --- ## Proyectos de R (.Rproj) Dentro de la carpeta del curso que ya crearon creen un proyecto de R. Para eso abran RStudio y desde ahí seleccionen `File/New Project` y seleccionen la opcion "Existing Directory" y luego seleccionen la carpeta del curso. .center[ <img src="ima/rproj.png" width="700px" /> ] --- ## Proyectos de R (.Rproj) Deberían ver en su carpeta algo así: .center[ <img src="ima/rproj3.png" width="1000px" /> ] --- ## Proyectos de R (.Rproj) - Abran el archivo `.Rproj` y desde ahí usando File/Open File abren los scripts dentro de la carpeta "scripts". Es importante que los abran desde la sesión que inicia el proyecto y no directamente haciendo click en el script. - Ya estamos listos para empezar! --- class: inverse, center, middle # Dialectos --- ## Ejercicio .content-box-blue[ *Supongamos que tengo estos datos:* ] ```r data ``` ``` ## # A tibble: 35 x 5 ## year gdp_lcu inflation unemployment presidente ## <dbl> <dbl> <dbl> <dbl> <chr> ## 1 1985 249277574100 72.2 NA Sanguinetti ## 2 1986 271238450500 76.4 NA Sanguinetti ## 3 1987 292918912000 63.6 NA Sanguinetti ## 4 1988 297256857900 62.2 NA Sanguinetti ## 5 1989 300538279400 80.4 NA Sanguinetti ## 6 1990 301431925100 113. NA Lacalle ## 7 1991 312099023700 102. 9.01 Lacalle ## 8 1992 336853433700 68.5 8.98 Lacalle ## 9 1993 345805469000 54.1 8.94 Lacalle ## 10 1994 370984750100 44.7 9 Lacalle ## # ... with 25 more rows ``` --- ## Ejercicio .content-box-blue[ *¿Qué quiero hacer con el código debajo?* ] .codefont[ ```r as.data.frame(t(sapply(X = split( x = data[which(data$presidente %in% c("Vázquez", "Sanguinetti")), which(colnames(data) %in% c("gdp_lcu", "inflation"))], f = data$presidente[which(data$presidente %in% c("Vázquez", "Sanguinetti"))], drop = TRUE), FUN = function(x) {apply(x, 2, mean)}))) ``` ] --- ## Ejercicio .content-box-blue[ *¿Qué quiero hacer con el código debajo?* ] ```r data_dt <- data setDT(data_dt) data_dt[presidente %in% c("Vázquez", "Sanguinetti"), c("presidente", "gdp_lcu", "inflation") ][ , lapply(.SD, mean), by = presidente] ``` --- ## Ejercicio .content-box-blue[ *¿Qué quiero hacer con el código debajo?* ] ```r data %>% filter(presidente %in% c("Vázquez", "Sanguinetti")) %>% select(presidente, gdp_lcu, inflation) %>% group_by(presidente) %>% summarise_all(mean) ``` --- ## R Base ```r as.data.frame(t(sapply(X = split( x = data[which(data$presidente %in% c("Vázquez", "Sanguinetti")), which(colnames(data) %in% c("gdp_lcu", "inflation"))], f = data$presidente[which(data$presidente %in% c("Vázquez", "Sanguinetti"))], drop = TRUE), FUN = function(x) {apply(x, 2, mean)}))) ``` ``` ## gdp_lcu inflation ## Sanguinetti 344923753631 46.168819 ## Vázquez 584455715198 7.416316 ``` --- ## Data.table ```r data_dt <- data setDT(data_dt) data_dt[presidente %in% c("Vázquez", "Sanguinetti"), c("presidente", "gdp_lcu", "inflation") ][ , lapply(.SD, mean), by = presidente] ``` ``` ## presidente gdp_lcu inflation ## 1: Sanguinetti 344923753631 46.168819 ## 2: Vázquez 584455715198 7.416316 ``` --- ## Tidyverse ```r data %>% filter(presidente %in% c("Vázquez", "Sanguinetti")) %>% select(presidente, gdp_lcu, inflation) %>% group_by(presidente) %>% summarise_all(mean) ``` ``` ## # A tibble: 2 x 3 ## presidente gdp_lcu inflation ## <chr> <dbl> <dbl> ## 1 Sanguinetti 344923753631. 46.2 ## 2 Vázquez 584455715198. 7.42 ``` --- ## Dialectos - Como vimos, en R podemos realizar una misma operación de muchas maneras distintas. Puesto de otra manera, R como lenguaje de programación tiene distintos "dialectos", esto es, paquetes (o conjuntos de paquetes) con sus propias funciones, sintaxis y comunidad de usuarios. - Para la mayoría de las funciones requeridas para un análisis de datos estándar (importar datos, manipular, modelar y visualizar) existen -de forma muy simplificada- tres grandes dialectos: [R Base](https://stat.ethz.ch/R-manual/R-devel/library/base/html/00Index.html), [tidyverse](https://www.tidyverse.org/) y [data.table](https://rdatatable.gitlab.io/data.table/). - Tidyverse es una colección de paquetes diseñados para el análisis de datos. Este conjunto de paquetes comparte una filosofía de diseño, grámatica y estructura de datos. - Las ventajas de Tidyverse están en su gramática (fácil de leer lo que invita a compartir y replicar), consistencia, alcance y su numerosa y creciente comunidad. --- ## Dialectos (ejemplo) .codefontchico[ ```r encuesta # Retomemos el data.frame "encuesta" ``` ``` ## edad ideologia voto ## 1 18 Izquierda Partido A ## 2 24 Izquierda Partido A ## 3 80 Derecha Partido C ``` ```r # Supongamos que quiero quedarme solo con las variables de edad y voto encuesta_base <- encuesta[ , c("edad", "voto")] # R Base colnames(encuesta_base) ``` ``` ## [1] "edad" "voto" ``` ```r encuesta_dt <- as.data.table(encuesta)[ , .(edad, voto)] # Datatable colnames(encuesta_dt) ``` ``` ## [1] "edad" "voto" ``` ```r encuesta_tidy <- select(encuesta, edad, voto) # Tidyverse colnames(encuesta_tidy) ``` ``` ## [1] "edad" "voto" ``` ] --- class: inverse, center, middle # Tidyverse --- ## Tidyverse Tidyverse cuenta con varios paquetes que sirven para distintos tipos de tareas específicas. Podemos cargar todos los paquetes de forma conjunta: .codefont[ ```r # install.packages("tidyverse") library(tidyverse) # install.packages("dplyr") library(dplyr) ``` ] .center[ <img src="ima/tidy.jpg" width="200px" /> ] --- ## Tidyverse La mejor manera de entender los principios de tidyverse es a través del libro del creador de tidyverse (Hadley Wickham) y Garrett Grolemund "R for Data Science de Hadley Wickham" (2018). .center[ <img src="ima/tidy_pr.png" width="600px" /> ] --- ## Tidyverse: paquetes .pull-left[Paquetes que Tidyverse carga: - [readr](https://readr.tidyverse.org/): importar y exportar datos - [dplyr](https://dplyr.tidyverse.org/): manipulación de datos - [tidyr](https://tidyr.tidyverse.org/): manipulación de datos - [ggplot2](https://ggplot2.tidyverse.org/): visualización de datos - [purr](https://purrr.tidyverse.org/): programación avanzada - [tibble](https://tibble.tidyverse.org/): estructura de datos - [forcats](https://forcats.tidyverse.org/): factores - [stringr](https://stringr.tidyverse.org/): variables de caracteres ] .pull-right[ <img src="ima/tidy_pack.jpg" width="500px" /> ] --- ## Tidyverse: paquetes Estos son algunos paquetes (para tareas más específicas) que forman parte del Tidyverse pero se tienen que cargar por separado: - [readxl](https://readxl.tidyverse.org/): importar datos (excel) - [haven](https://haven.tidyverse.org/): importar (Stata, SPSS, SAS) - [lubridate](https://lubridate.tidyverse.org/): manipulación de fechas - [rvest](https://rvest.tidyverse.org/): webscrapping - [glue](https://www.tidyverse.org/blog/2017/10/glue-1.2.0/): combinar data - [tidymodels](https://www.tidymodels.org/): modelar datos --- class: inverse, center, middle # Importar y exportar datos --- ## Importar datos - Hasta ahora trabajamos principalmente con datos ingresados manualmente con las funciones `c()` y `data.frame()` - Normalmente cuando trabajamos con datos solemos utilizar datos ya creados guardados en los formatos de otros programas (ej. Excel, Stata, SPSS) - Existen varios paquetes que permiten importar y exportar datos desde distintos formatos. Algunos de los más utilizados son [readr](https://readr.tidyverse.org/), [haven](https://haven.tidyverse.org/), [readxl](https://readxl.tidyverse.org/) y [utils](https://www.rdocumentation.org/packages/utils/versions/3.6.2) --- ## Importar datos desde distintos formatos Distintas funciones nos sirven para importar datos a R desde distintos formatos. Veamos algunos ejemplos: .codefont[ ```r # Con la función read_csv() del paquete readr importamos archivos .csv library(tidyverse) gapminder_csv <- read_csv("data/gapminder.csv") # Con la función read_excel() del paquete readxl importamos archivos excel library(readxl) gapminder_excel <- read_excel("data/gapminder.xlsx") ``` ] .codefont[ ```r # Vemos que los dataframes son iguales, tienen la mismas filas y columnas dim(gapminder_csv) ``` ``` ## [1] 1704 6 ``` ```r dim(gapminder_excel) ``` ``` ## [1] 1704 6 ``` ] --- ## Importar datos desde paquetes Algunos paquetes incluyen datos, por ejemplo, gapminder. En la documentación del paquete se encuentra el nombre de los datos. Con una simple asignación los podemos cargar ```r library(gapminder) data_gapminder <- gapminder head(data_gapminder) ``` ``` ## # A tibble: 6 x 6 ## country continent year lifeExp pop gdpPercap ## <fct> <fct> <int> <dbl> <int> <dbl> ## 1 Afghanistan Asia 1952 28.8 8425333 779. ## 2 Afghanistan Asia 1957 30.3 9240934 821. ## 3 Afghanistan Asia 1962 32.0 10267083 853. ## 4 Afghanistan Asia 1967 34.0 11537966 836. ## 5 Afghanistan Asia 1972 36.1 13079460 740. ## 6 Afghanistan Asia 1977 38.4 14880372 786. ``` --- ## Importar datos en otros formatos También es posible importar datos guardados en los formatos de otros softwares estadísticos como SPSS o Stata. Para esto usaremos el paquete haven. .codefont[ ```r library(haven) # SPSS gapminder_spss <- read_spss("data/gapminder.sav") # STATA gapminder_stata <- read_stata("data/gapminder.dta") ``` ] O podríamos llamar a la función y paquete dado que generalmente solo utilizamos una función de los paquetes que cargan datos (depende del caso obviamente) .codefont[ ```r # SPSS gapminder_spss <- haven::read_spss("data/gapminder.sav") # STATA gapminder_stata <- haven::read_stata("data/gapminder.dta") ``` ] --- ## Importar datos en formato R R también cuenta con sus propios formatos de almacenamiento de datos (`.rds` y `.Rdata` o `.rda`). Este enfoque es poco práctico si queremos usar los datos almacenados en otro programa, pero muy útil si solamente usaremos R dado que mantiene la información tal cual estaba en R (por ej. tipos de variables o atributos): .codefont[ ```r # Para esto no necesitamos cargar paquetes. # Guardar un objeto como .rds: saveRDS(object = data_gapminder, file = here::here("resultados/data_gapminder.rds")) # Leemos un archivo .rds miobjeto_rds <- readRDS(file = here::here("resultados/data_gapminder.rds")) # Con .rda se pueden guardar varios objetos al mismo tiempo! # Exportamos un archivo .Rdata save(data_gapminder, miobjeto_rds, file = here::here("resultados/dos_dataframes.Rdata")) # Importamos un archivo .Rdata load(here::here("resultados/dos_dataframes.Rdata")) ``` ] --- ## Exportar datos - También podemos guardar archivos desde R en otros formatos. - Con [readr](https://readr.tidyverse.org/) podemos exportar archivos en formato .csv - Con [writexl](https://cran.r-project.org/web/packages/writexl/writexl.pdf) podemos exportar directamente un excel. - Con [haven](https://www.rdocumentation.org/packages/haven/versions/2.3.1) podemos exportar achivos en formato .dta (Stata) y .sav (SPSS) .codefont[ ```r # Guardar .csv library(gapminder) data_gapminder <- gapminder write_excel_csv(data_gapminder, here::here("resultados/gapminder.csv")) # Guardar excel library(writexl) write_xlsx(data_gapminder, here::here("resultados/gapminder.xlsx")) # Guardar .dta (Stata) library(haven) write_dta(data_gapminder, here::here("resultados/gapminder.dta")) # Guardar .sav (SPSS) write_sav(data_gapminder, here::here("resultados/gapminder.sav")) # Guardar .sas (SAS) write_sas(data_gapminder, here::here("resultados/gapminder.sas")) ``` ] --- ## Argumentos .bold[Argumentos a tener en cuenta:] - .bold[Nombre de columnas:] a veces debemos especificar si queremos que la primera fila de nuestros datos sean el nombre de las variables - .bold[Nombre de filas:] de igual manera, a veces podemos especificar si queremos que la primera columna sea el nombre de las filas (sirve para identificadores de caso por ej.) - .bold[Etiquetas de variables:] cuando los datos que queremos importar tienen etiquetas (pasa mucho en encuestas) podemos cargarlas como etiquetas o cargar solamente la etiqueta como cadena o factores. Ver capítulo 4 de Urdinez, F. & Labrin, A. (Eds.) (2020) - .bold[Append:] algunas funciones permiten agregar filas debajo de un archivo (esto es muy útil para ir actualizando bases de datos) --- ## Ejercicio .content-box-blue[ *En la carpeta data encontrarán un archivo excel llamado "urudata_sheets", deben leer la segunda hoja del archivo* ] --- class: inverse, center, middle # Etiquetas --- ## Etiquetas cuando importamos datos - Cuando importamos datos que tienen etiquetas (por ejemplo de formatos como Stata o SPSS) debemos tener cuidado con cómo manejar estas etiquetas - Por ejemplo, supongamos que queremos leer los datos de una encuesta con dos variables, guardada en formato Stata (`.dta`), con el paquete `haven`: .codefont[ ```r data <- haven::read_stata("data/ej_encuesta.dta") head(data, 5) ``` ``` ## # A tibble: 5 x 2 ## P1 P14 ## <dbl+lbl> <dbl+lbl> ## 1 4 [Colonia] 1 [Muy mala] ## 2 18 [Tacuarembó] 2 [Mala] ## 3 15 [Salto] 5 [Muy buena] ## 4 1 [Artigas] 3 [Ni buena ni mala] ## 5 10 [Montevideo] 1 [Muy mala] ``` ] - Por defecto se leen como variables de tipo `double` (numérica) con etiquetas como atributos --- ## Etiquetas cuando importamos datos Si queremos quedarnos directamente con las etiquetas, podemos utilizar la función `as_factor`: ```r data <- haven::read_stata("data/ej_encuesta.dta") %>% haven::as_factor() head(data, 5) ``` ``` ## # A tibble: 5 x 2 ## P1 P14 ## <fct> <fct> ## 1 Colonia Muy mala ## 2 Tacuarembó Mala ## 3 Salto Muy buena ## 4 Artigas Ni buena ni mala ## 5 Montevideo Muy mala ``` --- class: inverse, center, middle # Factores --- ## Factores - Otro tipo de variables en R son los factores (factors), utilizados para representar data categórica. Estos suelen confundirse con las variables de caracteres pero tienen algunas diferencias. - Normalmente los factores son utilizados para las variables de caracteres con un número de valores posibles fijo y cierto orden (opcional) - A R le gusta transformar las variables de caracteres en factores al importarlas (si usamos R Base particularmente). - El paquete [forcats](https://forcats.tidyverse.org/) (dentro del Tidyverse) ayuda a manejar variables de caracteres y factores: - `fct_relevel()` cambia manualmente el orden de los niveles - `fct_reoder()` cambia el orden de los niveles de acuerdo a otra variable - `fct_infreq()` reordena un factor por la frecuencia de sus valores - `fct_lump()` collapsa los valores menos frecuentes en otra categoría "other". Es muy útil para preparar datos para tablas y gráficos --- ## Transformar factores .codefontchico[ ```r # Podemos chequear y coercionar factores data_gapminder <- gapminder is.factor(data_gapminder$continent) # Chequeo si es factor ``` ``` ## [1] TRUE ``` ```r levels(data_gapminder$continent) # Chequeo los niveles ``` ``` ## [1] "Africa" "Americas" "Asia" "Europe" "Oceania" ``` ```r # Transformo a caracter data_gapminder$continent <- as.character(data_gapminder$continent) class(data_gapminder$continent) ``` ``` ## [1] "character" ``` ```r # De vuelta a factor data_gapminder$continent <- as.factor(data_gapminder$continent) class(data_gapminder$continent) ``` ``` ## [1] "factor" ``` ] --- ## Crear y ordenar factores .codefont[ ```r # Para crear un factor usamos la función factor() paises_mercosur <- factor(c("Argentina", "Brasil", "Paraguay", "Uruguay")) table(paises_mercosur) ``` ``` ## paises_mercosur ## Argentina Brasil Paraguay Uruguay ## 1 1 1 1 ``` ```r # La función fct_relevel() nos permite reordenar los niveles del factor paises_mercosur <- fct_relevel(paises_mercosur, "Uruguay") table(paises_mercosur) ``` ``` ## paises_mercosur ## Uruguay Argentina Brasil Paraguay ## 1 1 1 1 ``` ] --- class: inverse, center, middle # Dataframes --- ## Dataframes: tibbles - La mayoría de los análisis de datos convencionales contienen dataframes. Cuando usamos los paquetes del tidyverse, generalmente trabajamos con "tibbles", que es muy similar a un dataframe pero con pequeños cambios. - Una de las principales diferencias es la forma en que se imprimen los datos. - La mayoría de las funciones del Tidyverse devuelven un tibble. .codefont[ ```r data_gapminder <- (gapminder) class(data_gapminder) # Ya es un tibble ``` ``` ## [1] "tbl_df" "tbl" "data.frame" ``` ```r data_gapminder <- as.data.frame(data_gapminder) class(data_gapminder) # Ahora solamente dataframe ``` ``` ## [1] "data.frame" ``` ] --- ## Dataframes: imprimir dataframe .codefont[ ```r print(data_gapminder) ``` ``` ## country continent year lifeExp pop gdpPercap ## 1 Afghanistan Asia 1952 28.80100 8425333 779.4453 ## 2 Afghanistan Asia 1957 30.33200 9240934 820.8530 ## 3 Afghanistan Asia 1962 31.99700 10267083 853.1007 ## 4 Afghanistan Asia 1967 34.02000 11537966 836.1971 ## 5 Afghanistan Asia 1972 36.08800 13079460 739.9811 ## 6 Afghanistan Asia 1977 38.43800 14880372 786.1134 ## 7 Afghanistan Asia 1982 39.85400 12881816 978.0114 ## 8 Afghanistan Asia 1987 40.82200 13867957 852.3959 ## 9 Afghanistan Asia 1992 41.67400 16317921 649.3414 ## 10 Afghanistan Asia 1997 41.76300 22227415 635.3414 ## 11 Afghanistan Asia 2002 42.12900 25268405 726.7341 ## 12 Afghanistan Asia 2007 43.82800 31889923 974.5803 ## 13 Albania Europe 1952 55.23000 1282697 1601.0561 ## 14 Albania Europe 1957 59.28000 1476505 1942.2842 ## 15 Albania Europe 1962 64.82000 1728137 2312.8890 ## 16 Albania Europe 1967 66.22000 1984060 2760.1969 ## 17 Albania Europe 1972 67.69000 2263554 3313.4222 ## 18 Albania Europe 1977 68.93000 2509048 3533.0039 ## 19 Albania Europe 1982 70.42000 2780097 3630.8807 ## 20 Albania Europe 1987 72.00000 3075321 3738.9327 ## 21 Albania Europe 1992 71.58100 3326498 2497.4379 ## 22 Albania Europe 1997 72.95000 3428038 3193.0546 ## 23 Albania Europe 2002 75.65100 3508512 4604.2117 ## 24 Albania Europe 2007 76.42300 3600523 5937.0295 ## 25 Algeria Africa 1952 43.07700 9279525 2449.0082 ## 26 Algeria Africa 1957 45.68500 10270856 3013.9760 ## 27 Algeria Africa 1962 48.30300 11000948 2550.8169 ## 28 Algeria Africa 1967 51.40700 12760499 3246.9918 ## 29 Algeria Africa 1972 54.51800 14760787 4182.6638 ## 30 Algeria Africa 1977 58.01400 17152804 4910.4168 ## 31 Algeria Africa 1982 61.36800 20033753 5745.1602 ## 32 Algeria Africa 1987 65.79900 23254956 5681.3585 ## 33 Algeria Africa 1992 67.74400 26298373 5023.2166 ## 34 Algeria Africa 1997 69.15200 29072015 4797.2951 ## 35 Algeria Africa 2002 70.99400 31287142 5288.0404 ## 36 Algeria Africa 2007 72.30100 33333216 6223.3675 ## 37 Angola Africa 1952 30.01500 4232095 3520.6103 ## 38 Angola Africa 1957 31.99900 4561361 3827.9405 ## 39 Angola Africa 1962 34.00000 4826015 4269.2767 ## 40 Angola Africa 1967 35.98500 5247469 5522.7764 ## 41 Angola Africa 1972 37.92800 5894858 5473.2880 ## 42 Angola Africa 1977 39.48300 6162675 3008.6474 ## 43 Angola Africa 1982 39.94200 7016384 2756.9537 ## 44 Angola Africa 1987 39.90600 7874230 2430.2083 ## 45 Angola Africa 1992 40.64700 8735988 2627.8457 ## 46 Angola Africa 1997 40.96300 9875024 2277.1409 ## 47 Angola Africa 2002 41.00300 10866106 2773.2873 ## 48 Angola Africa 2007 42.73100 12420476 4797.2313 ## 49 Argentina Americas 1952 62.48500 17876956 5911.3151 ## 50 Argentina Americas 1957 64.39900 19610538 6856.8562 ## 51 Argentina Americas 1962 65.14200 21283783 7133.1660 ## 52 Argentina Americas 1967 65.63400 22934225 8052.9530 ## 53 Argentina Americas 1972 67.06500 24779799 9443.0385 ## 54 Argentina Americas 1977 68.48100 26983828 10079.0267 ## 55 Argentina Americas 1982 69.94200 29341374 8997.8974 ## 56 Argentina Americas 1987 70.77400 31620918 9139.6714 ## 57 Argentina Americas 1992 71.86800 33958947 9308.4187 ## 58 Argentina Americas 1997 73.27500 36203463 10967.2820 ## 59 Argentina Americas 2002 74.34000 38331121 8797.6407 ## 60 Argentina Americas 2007 75.32000 40301927 12779.3796 ## 61 Australia Oceania 1952 69.12000 8691212 10039.5956 ## 62 Australia Oceania 1957 70.33000 9712569 10949.6496 ## 63 Australia Oceania 1962 70.93000 10794968 12217.2269 ## 64 Australia Oceania 1967 71.10000 11872264 14526.1246 ## 65 Australia Oceania 1972 71.93000 13177000 16788.6295 ## 66 Australia Oceania 1977 73.49000 14074100 18334.1975 ## 67 Australia Oceania 1982 74.74000 15184200 19477.0093 ## 68 Australia Oceania 1987 76.32000 16257249 21888.8890 ## 69 Australia Oceania 1992 77.56000 17481977 23424.7668 ## 70 Australia Oceania 1997 78.83000 18565243 26997.9366 ## 71 Australia Oceania 2002 80.37000 19546792 30687.7547 ## 72 Australia Oceania 2007 81.23500 20434176 34435.3674 ## 73 Austria Europe 1952 66.80000 6927772 6137.0765 ## 74 Austria Europe 1957 67.48000 6965860 8842.5980 ## 75 Austria Europe 1962 69.54000 7129864 10750.7211 ## 76 Austria Europe 1967 70.14000 7376998 12834.6024 ## 77 Austria Europe 1972 70.63000 7544201 16661.6256 ## 78 Austria Europe 1977 72.17000 7568430 19749.4223 ## 79 Austria Europe 1982 73.18000 7574613 21597.0836 ## 80 Austria Europe 1987 74.94000 7578903 23687.8261 ## 81 Austria Europe 1992 76.04000 7914969 27042.0187 ## 82 Austria Europe 1997 77.51000 8069876 29095.9207 ## 83 Austria Europe 2002 78.98000 8148312 32417.6077 ## 84 Austria Europe 2007 79.82900 8199783 36126.4927 ## 85 Bahrain Asia 1952 50.93900 120447 9867.0848 ## 86 Bahrain Asia 1957 53.83200 138655 11635.7995 ## 87 Bahrain Asia 1962 56.92300 171863 12753.2751 ## 88 Bahrain Asia 1967 59.92300 202182 14804.6727 ## 89 Bahrain Asia 1972 63.30000 230800 18268.6584 ## 90 Bahrain Asia 1977 65.59300 297410 19340.1020 ## 91 Bahrain Asia 1982 69.05200 377967 19211.1473 ## 92 Bahrain Asia 1987 70.75000 454612 18524.0241 ## 93 Bahrain Asia 1992 72.60100 529491 19035.5792 ## 94 Bahrain Asia 1997 73.92500 598561 20292.0168 ## 95 Bahrain Asia 2002 74.79500 656397 23403.5593 ## 96 Bahrain Asia 2007 75.63500 708573 29796.0483 ## 97 Bangladesh Asia 1952 37.48400 46886859 684.2442 ## 98 Bangladesh Asia 1957 39.34800 51365468 661.6375 ## 99 Bangladesh Asia 1962 41.21600 56839289 686.3416 ## 100 Bangladesh Asia 1967 43.45300 62821884 721.1861 ## 101 Bangladesh Asia 1972 45.25200 70759295 630.2336 ## 102 Bangladesh Asia 1977 46.92300 80428306 659.8772 ## 103 Bangladesh Asia 1982 50.00900 93074406 676.9819 ## 104 Bangladesh Asia 1987 52.81900 103764241 751.9794 ## 105 Bangladesh Asia 1992 56.01800 113704579 837.8102 ## 106 Bangladesh Asia 1997 59.41200 123315288 972.7700 ## 107 Bangladesh Asia 2002 62.01300 135656790 1136.3904 ## 108 Bangladesh Asia 2007 64.06200 150448339 1391.2538 ## 109 Belgium Europe 1952 68.00000 8730405 8343.1051 ## 110 Belgium Europe 1957 69.24000 8989111 9714.9606 ## 111 Belgium Europe 1962 70.25000 9218400 10991.2068 ## 112 Belgium Europe 1967 70.94000 9556500 13149.0412 ## 113 Belgium Europe 1972 71.44000 9709100 16672.1436 ## 114 Belgium Europe 1977 72.80000 9821800 19117.9745 ## 115 Belgium Europe 1982 73.93000 9856303 20979.8459 ## 116 Belgium Europe 1987 75.35000 9870200 22525.5631 ## 117 Belgium Europe 1992 76.46000 10045622 25575.5707 ## 118 Belgium Europe 1997 77.53000 10199787 27561.1966 ## 119 Belgium Europe 2002 78.32000 10311970 30485.8838 ## 120 Belgium Europe 2007 79.44100 10392226 33692.6051 ## 121 Benin Africa 1952 38.22300 1738315 1062.7522 ## 122 Benin Africa 1957 40.35800 1925173 959.6011 ## 123 Benin Africa 1962 42.61800 2151895 949.4991 ## 124 Benin Africa 1967 44.88500 2427334 1035.8314 ## 125 Benin Africa 1972 47.01400 2761407 1085.7969 ## 126 Benin Africa 1977 49.19000 3168267 1029.1613 ## 127 Benin Africa 1982 50.90400 3641603 1277.8976 ## 128 Benin Africa 1987 52.33700 4243788 1225.8560 ## 129 Benin Africa 1992 53.91900 4981671 1191.2077 ## 130 Benin Africa 1997 54.77700 6066080 1232.9753 ## 131 Benin Africa 2002 54.40600 7026113 1372.8779 ## 132 Benin Africa 2007 56.72800 8078314 1441.2849 ## 133 Bolivia Americas 1952 40.41400 2883315 2677.3263 ## 134 Bolivia Americas 1957 41.89000 3211738 2127.6863 ## 135 Bolivia Americas 1962 43.42800 3593918 2180.9725 ## 136 Bolivia Americas 1967 45.03200 4040665 2586.8861 ## 137 Bolivia Americas 1972 46.71400 4565872 2980.3313 ## 138 Bolivia Americas 1977 50.02300 5079716 3548.0978 ## 139 Bolivia Americas 1982 53.85900 5642224 3156.5105 ## 140 Bolivia Americas 1987 57.25100 6156369 2753.6915 ## 141 Bolivia Americas 1992 59.95700 6893451 2961.6997 ## 142 Bolivia Americas 1997 62.05000 7693188 3326.1432 ## 143 Bolivia Americas 2002 63.88300 8445134 3413.2627 ## 144 Bolivia Americas 2007 65.55400 9119152 3822.1371 ## 145 Bosnia and Herzegovina Europe 1952 53.82000 2791000 973.5332 ## 146 Bosnia and Herzegovina Europe 1957 58.45000 3076000 1353.9892 ## 147 Bosnia and Herzegovina Europe 1962 61.93000 3349000 1709.6837 ## 148 Bosnia and Herzegovina Europe 1967 64.79000 3585000 2172.3524 ## 149 Bosnia and Herzegovina Europe 1972 67.45000 3819000 2860.1698 ## 150 Bosnia and Herzegovina Europe 1977 69.86000 4086000 3528.4813 ## 151 Bosnia and Herzegovina Europe 1982 70.69000 4172693 4126.6132 ## 152 Bosnia and Herzegovina Europe 1987 71.14000 4338977 4314.1148 ## 153 Bosnia and Herzegovina Europe 1992 72.17800 4256013 2546.7814 ## 154 Bosnia and Herzegovina Europe 1997 73.24400 3607000 4766.3559 ## 155 Bosnia and Herzegovina Europe 2002 74.09000 4165416 6018.9752 ## 156 Bosnia and Herzegovina Europe 2007 74.85200 4552198 7446.2988 ## 157 Botswana Africa 1952 47.62200 442308 851.2411 ## 158 Botswana Africa 1957 49.61800 474639 918.2325 ## 159 Botswana Africa 1962 51.52000 512764 983.6540 ## 160 Botswana Africa 1967 53.29800 553541 1214.7093 ## 161 Botswana Africa 1972 56.02400 619351 2263.6111 ## 162 Botswana Africa 1977 59.31900 781472 3214.8578 ## 163 Botswana Africa 1982 61.48400 970347 4551.1421 ## 164 Botswana Africa 1987 63.62200 1151184 6205.8839 ## 165 Botswana Africa 1992 62.74500 1342614 7954.1116 ## 166 Botswana Africa 1997 52.55600 1536536 8647.1423 ## 167 Botswana Africa 2002 46.63400 1630347 11003.6051 ## 168 Botswana Africa 2007 50.72800 1639131 12569.8518 ## 169 Brazil Americas 1952 50.91700 56602560 2108.9444 ## 170 Brazil Americas 1957 53.28500 65551171 2487.3660 ## 171 Brazil Americas 1962 55.66500 76039390 3336.5858 ## 172 Brazil Americas 1967 57.63200 88049823 3429.8644 ## 173 Brazil Americas 1972 59.50400 100840058 4985.7115 ## 174 Brazil Americas 1977 61.48900 114313951 6660.1187 ## 175 Brazil Americas 1982 63.33600 128962939 7030.8359 ## 176 Brazil Americas 1987 65.20500 142938076 7807.0958 ## 177 Brazil Americas 1992 67.05700 155975974 6950.2830 ## 178 Brazil Americas 1997 69.38800 168546719 7957.9808 ## 179 Brazil Americas 2002 71.00600 179914212 8131.2128 ## 180 Brazil Americas 2007 72.39000 190010647 9065.8008 ## 181 Bulgaria Europe 1952 59.60000 7274900 2444.2866 ## 182 Bulgaria Europe 1957 66.61000 7651254 3008.6707 ## 183 Bulgaria Europe 1962 69.51000 8012946 4254.3378 ## 184 Bulgaria Europe 1967 70.42000 8310226 5577.0028 ## 185 Bulgaria Europe 1972 70.90000 8576200 6597.4944 ## 186 Bulgaria Europe 1977 70.81000 8797022 7612.2404 ## 187 Bulgaria Europe 1982 71.08000 8892098 8224.1916 ## 188 Bulgaria Europe 1987 71.34000 8971958 8239.8548 ## 189 Bulgaria Europe 1992 71.19000 8658506 6302.6234 ## 190 Bulgaria Europe 1997 70.32000 8066057 5970.3888 ## 191 Bulgaria Europe 2002 72.14000 7661799 7696.7777 ## 192 Bulgaria Europe 2007 73.00500 7322858 10680.7928 ## 193 Burkina Faso Africa 1952 31.97500 4469979 543.2552 ## 194 Burkina Faso Africa 1957 34.90600 4713416 617.1835 ## 195 Burkina Faso Africa 1962 37.81400 4919632 722.5120 ## 196 Burkina Faso Africa 1967 40.69700 5127935 794.8266 ## 197 Burkina Faso Africa 1972 43.59100 5433886 854.7360 ## 198 Burkina Faso Africa 1977 46.13700 5889574 743.3870 ## 199 Burkina Faso Africa 1982 48.12200 6634596 807.1986 ## 200 Burkina Faso Africa 1987 49.55700 7586551 912.0631 ## 201 Burkina Faso Africa 1992 50.26000 8878303 931.7528 ## 202 Burkina Faso Africa 1997 50.32400 10352843 946.2950 ## 203 Burkina Faso Africa 2002 50.65000 12251209 1037.6452 ## 204 Burkina Faso Africa 2007 52.29500 14326203 1217.0330 ## 205 Burundi Africa 1952 39.03100 2445618 339.2965 ## 206 Burundi Africa 1957 40.53300 2667518 379.5646 ## 207 Burundi Africa 1962 42.04500 2961915 355.2032 ## 208 Burundi Africa 1967 43.54800 3330989 412.9775 ## 209 Burundi Africa 1972 44.05700 3529983 464.0995 ## 210 Burundi Africa 1977 45.91000 3834415 556.1033 ## 211 Burundi Africa 1982 47.47100 4580410 559.6032 ## 212 Burundi Africa 1987 48.21100 5126023 621.8188 ## 213 Burundi Africa 1992 44.73600 5809236 631.6999 ## 214 Burundi Africa 1997 45.32600 6121610 463.1151 ## 215 Burundi Africa 2002 47.36000 7021078 446.4035 ## 216 Burundi Africa 2007 49.58000 8390505 430.0707 ## 217 Cambodia Asia 1952 39.41700 4693836 368.4693 ## 218 Cambodia Asia 1957 41.36600 5322536 434.0383 ## 219 Cambodia Asia 1962 43.41500 6083619 496.9136 ## 220 Cambodia Asia 1967 45.41500 6960067 523.4323 ## 221 Cambodia Asia 1972 40.31700 7450606 421.6240 ## 222 Cambodia Asia 1977 31.22000 6978607 524.9722 ## 223 Cambodia Asia 1982 50.95700 7272485 624.4755 ## 224 Cambodia Asia 1987 53.91400 8371791 683.8956 ## 225 Cambodia Asia 1992 55.80300 10150094 682.3032 ## 226 Cambodia Asia 1997 56.53400 11782962 734.2852 ## 227 Cambodia Asia 2002 56.75200 12926707 896.2260 ## 228 Cambodia Asia 2007 59.72300 14131858 1713.7787 ## 229 Cameroon Africa 1952 38.52300 5009067 1172.6677 ## 230 Cameroon Africa 1957 40.42800 5359923 1313.0481 ## 231 Cameroon Africa 1962 42.64300 5793633 1399.6074 ## 232 Cameroon Africa 1967 44.79900 6335506 1508.4531 ## 233 Cameroon Africa 1972 47.04900 7021028 1684.1465 ## 234 Cameroon Africa 1977 49.35500 7959865 1783.4329 ## 235 Cameroon Africa 1982 52.96100 9250831 2367.9833 ## 236 Cameroon Africa 1987 54.98500 10780667 2602.6642 ## 237 Cameroon Africa 1992 54.31400 12467171 1793.1633 ## 238 Cameroon Africa 1997 52.19900 14195809 1694.3375 ## 239 Cameroon Africa 2002 49.85600 15929988 1934.0114 ## 240 Cameroon Africa 2007 50.43000 17696293 2042.0952 ## 241 Canada Americas 1952 68.75000 14785584 11367.1611 ## 242 Canada Americas 1957 69.96000 17010154 12489.9501 ## 243 Canada Americas 1962 71.30000 18985849 13462.4855 ## 244 Canada Americas 1967 72.13000 20819767 16076.5880 ## 245 Canada Americas 1972 72.88000 22284500 18970.5709 ## 246 Canada Americas 1977 74.21000 23796400 22090.8831 ## 247 Canada Americas 1982 75.76000 25201900 22898.7921 ## 248 Canada Americas 1987 76.86000 26549700 26626.5150 ## 249 Canada Americas 1992 77.95000 28523502 26342.8843 ## 250 Canada Americas 1997 78.61000 30305843 28954.9259 ## 251 Canada Americas 2002 79.77000 31902268 33328.9651 ## 252 Canada Americas 2007 80.65300 33390141 36319.2350 ## 253 Central African Republic Africa 1952 35.46300 1291695 1071.3107 ## 254 Central African Republic Africa 1957 37.46400 1392284 1190.8443 ## 255 Central African Republic Africa 1962 39.47500 1523478 1193.0688 ## 256 Central African Republic Africa 1967 41.47800 1733638 1136.0566 ## 257 Central African Republic Africa 1972 43.45700 1927260 1070.0133 ## 258 Central African Republic Africa 1977 46.77500 2167533 1109.3743 ## 259 Central African Republic Africa 1982 48.29500 2476971 956.7530 ## 260 Central African Republic Africa 1987 50.48500 2840009 844.8764 ## 261 Central African Republic Africa 1992 49.39600 3265124 747.9055 ## 262 Central African Republic Africa 1997 46.06600 3696513 740.5063 ## 263 Central African Republic Africa 2002 43.30800 4048013 738.6906 ## 264 Central African Republic Africa 2007 44.74100 4369038 706.0165 ## 265 Chad Africa 1952 38.09200 2682462 1178.6659 ## 266 Chad Africa 1957 39.88100 2894855 1308.4956 ## 267 Chad Africa 1962 41.71600 3150417 1389.8176 ## 268 Chad Africa 1967 43.60100 3495967 1196.8106 ## 269 Chad Africa 1972 45.56900 3899068 1104.1040 ## 270 Chad Africa 1977 47.38300 4388260 1133.9850 ## 271 Chad Africa 1982 49.51700 4875118 797.9081 ## 272 Chad Africa 1987 51.05100 5498955 952.3861 ## 273 Chad Africa 1992 51.72400 6429417 1058.0643 ## 274 Chad Africa 1997 51.57300 7562011 1004.9614 ## 275 Chad Africa 2002 50.52500 8835739 1156.1819 ## 276 Chad Africa 2007 50.65100 10238807 1704.0637 ## 277 Chile Americas 1952 54.74500 6377619 3939.9788 ## 278 Chile Americas 1957 56.07400 7048426 4315.6227 ## 279 Chile Americas 1962 57.92400 7961258 4519.0943 ## 280 Chile Americas 1967 60.52300 8858908 5106.6543 ## 281 Chile Americas 1972 63.44100 9717524 5494.0244 ## 282 Chile Americas 1977 67.05200 10599793 4756.7638 ## 283 Chile Americas 1982 70.56500 11487112 5095.6657 ## 284 Chile Americas 1987 72.49200 12463354 5547.0638 ## 285 Chile Americas 1992 74.12600 13572994 7596.1260 ## 286 Chile Americas 1997 75.81600 14599929 10118.0532 ## 287 Chile Americas 2002 77.86000 15497046 10778.7838 ## 288 Chile Americas 2007 78.55300 16284741 13171.6388 ## 289 China Asia 1952 44.00000 556263527 400.4486 ## 290 China Asia 1957 50.54896 637408000 575.9870 ## 291 China Asia 1962 44.50136 665770000 487.6740 ## 292 China Asia 1967 58.38112 754550000 612.7057 ## 293 China Asia 1972 63.11888 862030000 676.9001 ## 294 China Asia 1977 63.96736 943455000 741.2375 ## 295 China Asia 1982 65.52500 1000281000 962.4214 ## 296 China Asia 1987 67.27400 1084035000 1378.9040 ## 297 China Asia 1992 68.69000 1164970000 1655.7842 ## 298 China Asia 1997 70.42600 1230075000 2289.2341 ## 299 China Asia 2002 72.02800 1280400000 3119.2809 ## 300 China Asia 2007 72.96100 1318683096 4959.1149 ## 301 Colombia Americas 1952 50.64300 12350771 2144.1151 ## 302 Colombia Americas 1957 55.11800 14485993 2323.8056 ## 303 Colombia Americas 1962 57.86300 17009885 2492.3511 ## 304 Colombia Americas 1967 59.96300 19764027 2678.7298 ## 305 Colombia Americas 1972 61.62300 22542890 3264.6600 ## 306 Colombia Americas 1977 63.83700 25094412 3815.8079 ## 307 Colombia Americas 1982 66.65300 27764644 4397.5757 ## 308 Colombia Americas 1987 67.76800 30964245 4903.2191 ## 309 Colombia Americas 1992 68.42100 34202721 5444.6486 ## 310 Colombia Americas 1997 70.31300 37657830 6117.3617 ## 311 Colombia Americas 2002 71.68200 41008227 5755.2600 ## 312 Colombia Americas 2007 72.88900 44227550 7006.5804 ## 313 Comoros Africa 1952 40.71500 153936 1102.9909 ## 314 Comoros Africa 1957 42.46000 170928 1211.1485 ## 315 Comoros Africa 1962 44.46700 191689 1406.6483 ## 316 Comoros Africa 1967 46.47200 217378 1876.0296 ## 317 Comoros Africa 1972 48.94400 250027 1937.5777 ## 318 Comoros Africa 1977 50.93900 304739 1172.6030 ## 319 Comoros Africa 1982 52.93300 348643 1267.1001 ## 320 Comoros Africa 1987 54.92600 395114 1315.9808 ## 321 Comoros Africa 1992 57.93900 454429 1246.9074 ## 322 Comoros Africa 1997 60.66000 527982 1173.6182 ## 323 Comoros Africa 2002 62.97400 614382 1075.8116 ## 324 Comoros Africa 2007 65.15200 710960 986.1479 ## 325 Congo, Dem. Rep. Africa 1952 39.14300 14100005 780.5423 ## 326 Congo, Dem. Rep. Africa 1957 40.65200 15577932 905.8602 ## 327 Congo, Dem. Rep. Africa 1962 42.12200 17486434 896.3146 ## 328 Congo, Dem. Rep. Africa 1967 44.05600 19941073 861.5932 ## 329 Congo, Dem. Rep. Africa 1972 45.98900 23007669 904.8961 ## 330 Congo, Dem. Rep. Africa 1977 47.80400 26480870 795.7573 ## 331 Congo, Dem. Rep. Africa 1982 47.78400 30646495 673.7478 ## 332 Congo, Dem. Rep. Africa 1987 47.41200 35481645 672.7748 ## 333 Congo, Dem. Rep. Africa 1992 45.54800 41672143 457.7192 ## 334 Congo, Dem. Rep. Africa 1997 42.58700 47798986 312.1884 ## 335 Congo, Dem. Rep. Africa 2002 44.96600 55379852 241.1659 ## 336 Congo, Dem. Rep. Africa 2007 46.46200 64606759 277.5519 ## 337 Congo, Rep. Africa 1952 42.11100 854885 2125.6214 ## 338 Congo, Rep. Africa 1957 45.05300 940458 2315.0566 ## 339 Congo, Rep. Africa 1962 48.43500 1047924 2464.7832 ## 340 Congo, Rep. Africa 1967 52.04000 1179760 2677.9396 ## 341 Congo, Rep. Africa 1972 54.90700 1340458 3213.1527 ## 342 Congo, Rep. Africa 1977 55.62500 1536769 3259.1790 ## 343 Congo, Rep. Africa 1982 56.69500 1774735 4879.5075 ## 344 Congo, Rep. Africa 1987 57.47000 2064095 4201.1949 ## 345 Congo, Rep. Africa 1992 56.43300 2409073 4016.2395 ## 346 Congo, Rep. Africa 1997 52.96200 2800947 3484.1644 ## 347 Congo, Rep. Africa 2002 52.97000 3328795 3484.0620 ## 348 Congo, Rep. Africa 2007 55.32200 3800610 3632.5578 ## 349 Costa Rica Americas 1952 57.20600 926317 2627.0095 ## 350 Costa Rica Americas 1957 60.02600 1112300 2990.0108 ## 351 Costa Rica Americas 1962 62.84200 1345187 3460.9370 ## 352 Costa Rica Americas 1967 65.42400 1588717 4161.7278 ## 353 Costa Rica Americas 1972 67.84900 1834796 5118.1469 ## 354 Costa Rica Americas 1977 70.75000 2108457 5926.8770 ## 355 Costa Rica Americas 1982 73.45000 2424367 5262.7348 ## 356 Costa Rica Americas 1987 74.75200 2799811 5629.9153 ## 357 Costa Rica Americas 1992 75.71300 3173216 6160.4163 ## 358 Costa Rica Americas 1997 77.26000 3518107 6677.0453 ## 359 Costa Rica Americas 2002 78.12300 3834934 7723.4472 ## 360 Costa Rica Americas 2007 78.78200 4133884 9645.0614 ## 361 Cote d'Ivoire Africa 1952 40.47700 2977019 1388.5947 ## 362 Cote d'Ivoire Africa 1957 42.46900 3300000 1500.8959 ## 363 Cote d'Ivoire Africa 1962 44.93000 3832408 1728.8694 ## 364 Cote d'Ivoire Africa 1967 47.35000 4744870 2052.0505 ## 365 Cote d'Ivoire Africa 1972 49.80100 6071696 2378.2011 ## 366 Cote d'Ivoire Africa 1977 52.37400 7459574 2517.7365 ## 367 Cote d'Ivoire Africa 1982 53.98300 9025951 2602.7102 ## 368 Cote d'Ivoire Africa 1987 54.65500 10761098 2156.9561 ## 369 Cote d'Ivoire Africa 1992 52.04400 12772596 1648.0738 ## 370 Cote d'Ivoire Africa 1997 47.99100 14625967 1786.2654 ## 371 Cote d'Ivoire Africa 2002 46.83200 16252726 1648.8008 ## 372 Cote d'Ivoire Africa 2007 48.32800 18013409 1544.7501 ## 373 Croatia Europe 1952 61.21000 3882229 3119.2365 ## 374 Croatia Europe 1957 64.77000 3991242 4338.2316 ## 375 Croatia Europe 1962 67.13000 4076557 5477.8900 ## 376 Croatia Europe 1967 68.50000 4174366 6960.2979 ## 377 Croatia Europe 1972 69.61000 4225310 9164.0901 ## 378 Croatia Europe 1977 70.64000 4318673 11305.3852 ## 379 Croatia Europe 1982 70.46000 4413368 13221.8218 ## 380 Croatia Europe 1987 71.52000 4484310 13822.5839 ## 381 Croatia Europe 1992 72.52700 4494013 8447.7949 ## 382 Croatia Europe 1997 73.68000 4444595 9875.6045 ## 383 Croatia Europe 2002 74.87600 4481020 11628.3890 ## 384 Croatia Europe 2007 75.74800 4493312 14619.2227 ## 385 Cuba Americas 1952 59.42100 6007797 5586.5388 ## 386 Cuba Americas 1957 62.32500 6640752 6092.1744 ## 387 Cuba Americas 1962 65.24600 7254373 5180.7559 ## 388 Cuba Americas 1967 68.29000 8139332 5690.2680 ## 389 Cuba Americas 1972 70.72300 8831348 5305.4453 ## 390 Cuba Americas 1977 72.64900 9537988 6380.4950 ## 391 Cuba Americas 1982 73.71700 9789224 7316.9181 ## 392 Cuba Americas 1987 74.17400 10239839 7532.9248 ## 393 Cuba Americas 1992 74.41400 10723260 5592.8440 ## 394 Cuba Americas 1997 76.15100 10983007 5431.9904 ## 395 Cuba Americas 2002 77.15800 11226999 6340.6467 ## 396 Cuba Americas 2007 78.27300 11416987 8948.1029 ## 397 Czech Republic Europe 1952 66.87000 9125183 6876.1403 ## 398 Czech Republic Europe 1957 69.03000 9513758 8256.3439 ## 399 Czech Republic Europe 1962 69.90000 9620282 10136.8671 ## 400 Czech Republic Europe 1967 70.38000 9835109 11399.4449 ## 401 Czech Republic Europe 1972 70.29000 9862158 13108.4536 ## 402 Czech Republic Europe 1977 70.71000 10161915 14800.1606 ## 403 Czech Republic Europe 1982 70.96000 10303704 15377.2285 ## 404 Czech Republic Europe 1987 71.58000 10311597 16310.4434 ## 405 Czech Republic Europe 1992 72.40000 10315702 14297.0212 ## 406 Czech Republic Europe 1997 74.01000 10300707 16048.5142 ## 407 Czech Republic Europe 2002 75.51000 10256295 17596.2102 ## 408 Czech Republic Europe 2007 76.48600 10228744 22833.3085 ## 409 Denmark Europe 1952 70.78000 4334000 9692.3852 ## 410 Denmark Europe 1957 71.81000 4487831 11099.6593 ## 411 Denmark Europe 1962 72.35000 4646899 13583.3135 ## 412 Denmark Europe 1967 72.96000 4838800 15937.2112 ## 413 Denmark Europe 1972 73.47000 4991596 18866.2072 ## 414 Denmark Europe 1977 74.69000 5088419 20422.9015 ## 415 Denmark Europe 1982 74.63000 5117810 21688.0405 ## 416 Denmark Europe 1987 74.80000 5127024 25116.1758 ## 417 Denmark Europe 1992 75.33000 5171393 26406.7399 ## 418 Denmark Europe 1997 76.11000 5283663 29804.3457 ## 419 Denmark Europe 2002 77.18000 5374693 32166.5001 ## 420 Denmark Europe 2007 78.33200 5468120 35278.4187 ## 421 Djibouti Africa 1952 34.81200 63149 2669.5295 ## 422 Djibouti Africa 1957 37.32800 71851 2864.9691 ## 423 Djibouti Africa 1962 39.69300 89898 3020.9893 ## 424 Djibouti Africa 1967 42.07400 127617 3020.0505 ## 425 Djibouti Africa 1972 44.36600 178848 3694.2124 ## 426 Djibouti Africa 1977 46.51900 228694 3081.7610 ## 427 Djibouti Africa 1982 48.81200 305991 2879.4681 ## 428 Djibouti Africa 1987 50.04000 311025 2880.1026 ## 429 Djibouti Africa 1992 51.60400 384156 2377.1562 ## 430 Djibouti Africa 1997 53.15700 417908 1895.0170 ## 431 Djibouti Africa 2002 53.37300 447416 1908.2609 ## 432 Djibouti Africa 2007 54.79100 496374 2082.4816 ## 433 Dominican Republic Americas 1952 45.92800 2491346 1397.7171 ## 434 Dominican Republic Americas 1957 49.82800 2923186 1544.4030 ## 435 Dominican Republic Americas 1962 53.45900 3453434 1662.1374 ## 436 Dominican Republic Americas 1967 56.75100 4049146 1653.7230 ## 437 Dominican Republic Americas 1972 59.63100 4671329 2189.8745 ## 438 Dominican Republic Americas 1977 61.78800 5302800 2681.9889 ## 439 Dominican Republic Americas 1982 63.72700 5968349 2861.0924 ## 440 Dominican Republic Americas 1987 66.04600 6655297 2899.8422 ## 441 Dominican Republic Americas 1992 68.45700 7351181 3044.2142 ## 442 Dominican Republic Americas 1997 69.95700 7992357 3614.1013 ## 443 Dominican Republic Americas 2002 70.84700 8650322 4563.8082 ## 444 Dominican Republic Americas 2007 72.23500 9319622 6025.3748 ## 445 Ecuador Americas 1952 48.35700 3548753 3522.1107 ## 446 Ecuador Americas 1957 51.35600 4058385 3780.5467 ## 447 Ecuador Americas 1962 54.64000 4681707 4086.1141 ## 448 Ecuador Americas 1967 56.67800 5432424 4579.0742 ## 449 Ecuador Americas 1972 58.79600 6298651 5280.9947 ## 450 Ecuador Americas 1977 61.31000 7278866 6679.6233 ## 451 Ecuador Americas 1982 64.34200 8365850 7213.7913 ## 452 Ecuador Americas 1987 67.23100 9545158 6481.7770 ## 453 Ecuador Americas 1992 69.61300 10748394 7103.7026 ## 454 Ecuador Americas 1997 72.31200 11911819 7429.4559 ## 455 Ecuador Americas 2002 74.17300 12921234 5773.0445 ## 456 Ecuador Americas 2007 74.99400 13755680 6873.2623 ## 457 Egypt Africa 1952 41.89300 22223309 1418.8224 ## 458 Egypt Africa 1957 44.44400 25009741 1458.9153 ## 459 Egypt Africa 1962 46.99200 28173309 1693.3359 ## 460 Egypt Africa 1967 49.29300 31681188 1814.8807 ## 461 Egypt Africa 1972 51.13700 34807417 2024.0081 ## 462 Egypt Africa 1977 53.31900 38783863 2785.4936 ## 463 Egypt Africa 1982 56.00600 45681811 3503.7296 ## 464 Egypt Africa 1987 59.79700 52799062 3885.4607 ## 465 Egypt Africa 1992 63.67400 59402198 3794.7552 ## 466 Egypt Africa 1997 67.21700 66134291 4173.1818 ## 467 Egypt Africa 2002 69.80600 73312559 4754.6044 ## 468 Egypt Africa 2007 71.33800 80264543 5581.1810 ## 469 El Salvador Americas 1952 45.26200 2042865 3048.3029 ## 470 El Salvador Americas 1957 48.57000 2355805 3421.5232 ## 471 El Salvador Americas 1962 52.30700 2747687 3776.8036 ## 472 El Salvador Americas 1967 55.85500 3232927 4358.5954 ## 473 El Salvador Americas 1972 58.20700 3790903 4520.2460 ## 474 El Salvador Americas 1977 56.69600 4282586 5138.9224 ## 475 El Salvador Americas 1982 56.60400 4474873 4098.3442 ## 476 El Salvador Americas 1987 63.15400 4842194 4140.4421 ## 477 El Salvador Americas 1992 66.79800 5274649 4444.2317 ## 478 El Salvador Americas 1997 69.53500 5783439 5154.8255 ## 479 El Salvador Americas 2002 70.73400 6353681 5351.5687 ## 480 El Salvador Americas 2007 71.87800 6939688 5728.3535 ## 481 Equatorial Guinea Africa 1952 34.48200 216964 375.6431 ## 482 Equatorial Guinea Africa 1957 35.98300 232922 426.0964 ## 483 Equatorial Guinea Africa 1962 37.48500 249220 582.8420 ## 484 Equatorial Guinea Africa 1967 38.98700 259864 915.5960 ## 485 Equatorial Guinea Africa 1972 40.51600 277603 672.4123 ## 486 Equatorial Guinea Africa 1977 42.02400 192675 958.5668 ## 487 Equatorial Guinea Africa 1982 43.66200 285483 927.8253 ## 488 Equatorial Guinea Africa 1987 45.66400 341244 966.8968 ## 489 Equatorial Guinea Africa 1992 47.54500 387838 1132.0550 ## 490 Equatorial Guinea Africa 1997 48.24500 439971 2814.4808 ## 491 Equatorial Guinea Africa 2002 49.34800 495627 7703.4959 ## 492 Equatorial Guinea Africa 2007 51.57900 551201 12154.0897 ## 493 Eritrea Africa 1952 35.92800 1438760 328.9406 ## 494 Eritrea Africa 1957 38.04700 1542611 344.1619 ## 495 Eritrea Africa 1962 40.15800 1666618 380.9958 ## 496 Eritrea Africa 1967 42.18900 1820319 468.7950 ## 497 Eritrea Africa 1972 44.14200 2260187 514.3242 ## 498 Eritrea Africa 1977 44.53500 2512642 505.7538 ## 499 Eritrea Africa 1982 43.89000 2637297 524.8758 ## 500 Eritrea Africa 1987 46.45300 2915959 521.1341 ## 501 Eritrea Africa 1992 49.99100 3668440 582.8585 ## 502 Eritrea Africa 1997 53.37800 4058319 913.4708 ## 503 Eritrea Africa 2002 55.24000 4414865 765.3500 ## 504 Eritrea Africa 2007 58.04000 4906585 641.3695 ## 505 Ethiopia Africa 1952 34.07800 20860941 362.1463 ## 506 Ethiopia Africa 1957 36.66700 22815614 378.9042 ## 507 Ethiopia Africa 1962 40.05900 25145372 419.4564 ## 508 Ethiopia Africa 1967 42.11500 27860297 516.1186 ## 509 Ethiopia Africa 1972 43.51500 30770372 566.2439 ## 510 Ethiopia Africa 1977 44.51000 34617799 556.8084 ## 511 Ethiopia Africa 1982 44.91600 38111756 577.8607 ## 512 Ethiopia Africa 1987 46.68400 42999530 573.7413 ## 513 Ethiopia Africa 1992 48.09100 52088559 421.3535 ## 514 Ethiopia Africa 1997 49.40200 59861301 515.8894 ## 515 Ethiopia Africa 2002 50.72500 67946797 530.0535 ## 516 Ethiopia Africa 2007 52.94700 76511887 690.8056 ## 517 Finland Europe 1952 66.55000 4090500 6424.5191 ## 518 Finland Europe 1957 67.49000 4324000 7545.4154 ## 519 Finland Europe 1962 68.75000 4491443 9371.8426 ## 520 Finland Europe 1967 69.83000 4605744 10921.6363 ## 521 Finland Europe 1972 70.87000 4639657 14358.8759 ## 522 Finland Europe 1977 72.52000 4738902 15605.4228 ## 523 Finland Europe 1982 74.55000 4826933 18533.1576 ## 524 Finland Europe 1987 74.83000 4931729 21141.0122 ## 525 Finland Europe 1992 75.70000 5041039 20647.1650 ## 526 Finland Europe 1997 77.13000 5134406 23723.9502 ## 527 Finland Europe 2002 78.37000 5193039 28204.5906 ## 528 Finland Europe 2007 79.31300 5238460 33207.0844 ## 529 France Europe 1952 67.41000 42459667 7029.8093 ## 530 France Europe 1957 68.93000 44310863 8662.8349 ## 531 France Europe 1962 70.51000 47124000 10560.4855 ## 532 France Europe 1967 71.55000 49569000 12999.9177 ## 533 France Europe 1972 72.38000 51732000 16107.1917 ## 534 France Europe 1977 73.83000 53165019 18292.6351 ## 535 France Europe 1982 74.89000 54433565 20293.8975 ## 536 France Europe 1987 76.34000 55630100 22066.4421 ## 537 France Europe 1992 77.46000 57374179 24703.7961 ## 538 France Europe 1997 78.64000 58623428 25889.7849 ## 539 France Europe 2002 79.59000 59925035 28926.0323 ## 540 France Europe 2007 80.65700 61083916 30470.0167 ## 541 Gabon Africa 1952 37.00300 420702 4293.4765 ## 542 Gabon Africa 1957 38.99900 434904 4976.1981 ## 543 Gabon Africa 1962 40.48900 455661 6631.4592 ## 544 Gabon Africa 1967 44.59800 489004 8358.7620 ## 545 Gabon Africa 1972 48.69000 537977 11401.9484 ## 546 Gabon Africa 1977 52.79000 706367 21745.5733 ## 547 Gabon Africa 1982 56.56400 753874 15113.3619 ## 548 Gabon Africa 1987 60.19000 880397 11864.4084 ## 549 Gabon Africa 1992 61.36600 985739 13522.1575 ## 550 Gabon Africa 1997 60.46100 1126189 14722.8419 ## 551 Gabon Africa 2002 56.76100 1299304 12521.7139 ## 552 Gabon Africa 2007 56.73500 1454867 13206.4845 ## 553 Gambia Africa 1952 30.00000 284320 485.2307 ## 554 Gambia Africa 1957 32.06500 323150 520.9267 ## 555 Gambia Africa 1962 33.89600 374020 599.6503 ## 556 Gambia Africa 1967 35.85700 439593 734.7829 ## 557 Gambia Africa 1972 38.30800 517101 756.0868 ## 558 Gambia Africa 1977 41.84200 608274 884.7553 ## 559 Gambia Africa 1982 45.58000 715523 835.8096 ## 560 Gambia Africa 1987 49.26500 848406 611.6589 ## 561 Gambia Africa 1992 52.64400 1025384 665.6244 ## 562 Gambia Africa 1997 55.86100 1235767 653.7302 ## 563 Gambia Africa 2002 58.04100 1457766 660.5856 ## 564 Gambia Africa 2007 59.44800 1688359 752.7497 ## 565 Germany Europe 1952 67.50000 69145952 7144.1144 ## 566 Germany Europe 1957 69.10000 71019069 10187.8267 ## 567 Germany Europe 1962 70.30000 73739117 12902.4629 ## 568 Germany Europe 1967 70.80000 76368453 14745.6256 ## 569 Germany Europe 1972 71.00000 78717088 18016.1803 ## 570 Germany Europe 1977 72.50000 78160773 20512.9212 ## 571 Germany Europe 1982 73.80000 78335266 22031.5327 ## 572 Germany Europe 1987 74.84700 77718298 24639.1857 ## 573 Germany Europe 1992 76.07000 80597764 26505.3032 ## 574 Germany Europe 1997 77.34000 82011073 27788.8842 ## 575 Germany Europe 2002 78.67000 82350671 30035.8020 ## 576 Germany Europe 2007 79.40600 82400996 32170.3744 ## 577 Ghana Africa 1952 43.14900 5581001 911.2989 ## 578 Ghana Africa 1957 44.77900 6391288 1043.5615 ## 579 Ghana Africa 1962 46.45200 7355248 1190.0411 ## 580 Ghana Africa 1967 48.07200 8490213 1125.6972 ## 581 Ghana Africa 1972 49.87500 9354120 1178.2237 ## 582 Ghana Africa 1977 51.75600 10538093 993.2240 ## 583 Ghana Africa 1982 53.74400 11400338 876.0326 ## 584 Ghana Africa 1987 55.72900 14168101 847.0061 ## 585 Ghana Africa 1992 57.50100 16278738 925.0602 ## 586 Ghana Africa 1997 58.55600 18418288 1005.2458 ## 587 Ghana Africa 2002 58.45300 20550751 1111.9846 ## 588 Ghana Africa 2007 60.02200 22873338 1327.6089 ## 589 Greece Europe 1952 65.86000 7733250 3530.6901 ## 590 Greece Europe 1957 67.86000 8096218 4916.2999 ## 591 Greece Europe 1962 69.51000 8448233 6017.1907 ## 592 Greece Europe 1967 71.00000 8716441 8513.0970 ## 593 Greece Europe 1972 72.34000 8888628 12724.8296 ## 594 Greece Europe 1977 73.68000 9308479 14195.5243 ## 595 Greece Europe 1982 75.24000 9786480 15268.4209 ## 596 Greece Europe 1987 76.67000 9974490 16120.5284 ## 597 Greece Europe 1992 77.03000 10325429 17541.4963 ## 598 Greece Europe 1997 77.86900 10502372 18747.6981 ## 599 Greece Europe 2002 78.25600 10603863 22514.2548 ## 600 Greece Europe 2007 79.48300 10706290 27538.4119 ## 601 Guatemala Americas 1952 42.02300 3146381 2428.2378 ## 602 Guatemala Americas 1957 44.14200 3640876 2617.1560 ## 603 Guatemala Americas 1962 46.95400 4208858 2750.3644 ## 604 Guatemala Americas 1967 50.01600 4690773 3242.5311 ## 605 Guatemala Americas 1972 53.73800 5149581 4031.4083 ## 606 Guatemala Americas 1977 56.02900 5703430 4879.9927 ## 607 Guatemala Americas 1982 58.13700 6395630 4820.4948 ## 608 Guatemala Americas 1987 60.78200 7326406 4246.4860 ## 609 Guatemala Americas 1992 63.37300 8486949 4439.4508 ## 610 Guatemala Americas 1997 66.32200 9803875 4684.3138 ## 611 Guatemala Americas 2002 68.97800 11178650 4858.3475 ## 612 Guatemala Americas 2007 70.25900 12572928 5186.0500 ## 613 Guinea Africa 1952 33.60900 2664249 510.1965 ## 614 Guinea Africa 1957 34.55800 2876726 576.2670 ## 615 Guinea Africa 1962 35.75300 3140003 686.3737 ## 616 Guinea Africa 1967 37.19700 3451418 708.7595 ## 617 Guinea Africa 1972 38.84200 3811387 741.6662 ## 618 Guinea Africa 1977 40.76200 4227026 874.6859 ## 619 Guinea Africa 1982 42.89100 4710497 857.2504 ## 620 Guinea Africa 1987 45.55200 5650262 805.5725 ## 621 Guinea Africa 1992 48.57600 6990574 794.3484 ## 622 Guinea Africa 1997 51.45500 8048834 869.4498 ## 623 Guinea Africa 2002 53.67600 8807818 945.5836 ## 624 Guinea Africa 2007 56.00700 9947814 942.6542 ## 625 Guinea-Bissau Africa 1952 32.50000 580653 299.8503 ## 626 Guinea-Bissau Africa 1957 33.48900 601095 431.7905 ## 627 Guinea-Bissau Africa 1962 34.48800 627820 522.0344 ## 628 Guinea-Bissau Africa 1967 35.49200 601287 715.5806 ## 629 Guinea-Bissau Africa 1972 36.48600 625361 820.2246 ## 630 Guinea-Bissau Africa 1977 37.46500 745228 764.7260 ## 631 Guinea-Bissau Africa 1982 39.32700 825987 838.1240 ## 632 Guinea-Bissau Africa 1987 41.24500 927524 736.4154 ## 633 Guinea-Bissau Africa 1992 43.26600 1050938 745.5399 ## 634 Guinea-Bissau Africa 1997 44.87300 1193708 796.6645 ## 635 Guinea-Bissau Africa 2002 45.50400 1332459 575.7047 ## 636 Guinea-Bissau Africa 2007 46.38800 1472041 579.2317 ## 637 Haiti Americas 1952 37.57900 3201488 1840.3669 ## 638 Haiti Americas 1957 40.69600 3507701 1726.8879 ## 639 Haiti Americas 1962 43.59000 3880130 1796.5890 ## 640 Haiti Americas 1967 46.24300 4318137 1452.0577 ## 641 Haiti Americas 1972 48.04200 4698301 1654.4569 ## 642 Haiti Americas 1977 49.92300 4908554 1874.2989 ## 643 Haiti Americas 1982 51.46100 5198399 2011.1595 ## 644 Haiti Americas 1987 53.63600 5756203 1823.0160 ## 645 Haiti Americas 1992 55.08900 6326682 1456.3095 ## 646 Haiti Americas 1997 56.67100 6913545 1341.7269 ## 647 Haiti Americas 2002 58.13700 7607651 1270.3649 ## 648 Haiti Americas 2007 60.91600 8502814 1201.6372 ## 649 Honduras Americas 1952 41.91200 1517453 2194.9262 ## 650 Honduras Americas 1957 44.66500 1770390 2220.4877 ## 651 Honduras Americas 1962 48.04100 2090162 2291.1568 ## 652 Honduras Americas 1967 50.92400 2500689 2538.2694 ## 653 Honduras Americas 1972 53.88400 2965146 2529.8423 ## 654 Honduras Americas 1977 57.40200 3055235 3203.2081 ## 655 Honduras Americas 1982 60.90900 3669448 3121.7608 ## 656 Honduras Americas 1987 64.49200 4372203 3023.0967 ## 657 Honduras Americas 1992 66.39900 5077347 3081.6946 ## 658 Honduras Americas 1997 67.65900 5867957 3160.4549 ## 659 Honduras Americas 2002 68.56500 6677328 3099.7287 ## 660 Honduras Americas 2007 70.19800 7483763 3548.3308 ## 661 Hong Kong, China Asia 1952 60.96000 2125900 3054.4212 ## 662 Hong Kong, China Asia 1957 64.75000 2736300 3629.0765 ## 663 Hong Kong, China Asia 1962 67.65000 3305200 4692.6483 ## 664 Hong Kong, China Asia 1967 70.00000 3722800 6197.9628 ## 665 Hong Kong, China Asia 1972 72.00000 4115700 8315.9281 ## 666 Hong Kong, China Asia 1977 73.60000 4583700 11186.1413 ## 667 Hong Kong, China Asia 1982 75.45000 5264500 14560.5305 ## 668 Hong Kong, China Asia 1987 76.20000 5584510 20038.4727 ## 669 Hong Kong, China Asia 1992 77.60100 5829696 24757.6030 ## 670 Hong Kong, China Asia 1997 80.00000 6495918 28377.6322 ## 671 Hong Kong, China Asia 2002 81.49500 6762476 30209.0152 ## 672 Hong Kong, China Asia 2007 82.20800 6980412 39724.9787 ## 673 Hungary Europe 1952 64.03000 9504000 5263.6738 ## 674 Hungary Europe 1957 66.41000 9839000 6040.1800 ## 675 Hungary Europe 1962 67.96000 10063000 7550.3599 ## 676 Hungary Europe 1967 69.50000 10223422 9326.6447 ## 677 Hungary Europe 1972 69.76000 10394091 10168.6561 ## 678 Hungary Europe 1977 69.95000 10637171 11674.8374 ## 679 Hungary Europe 1982 69.39000 10705535 12545.9907 ## 680 Hungary Europe 1987 69.58000 10612740 12986.4800 ## 681 Hungary Europe 1992 69.17000 10348684 10535.6285 ## 682 Hungary Europe 1997 71.04000 10244684 11712.7768 ## 683 Hungary Europe 2002 72.59000 10083313 14843.9356 ## 684 Hungary Europe 2007 73.33800 9956108 18008.9444 ## 685 Iceland Europe 1952 72.49000 147962 7267.6884 ## 686 Iceland Europe 1957 73.47000 165110 9244.0014 ## 687 Iceland Europe 1962 73.68000 182053 10350.1591 ## 688 Iceland Europe 1967 73.73000 198676 13319.8957 ## 689 Iceland Europe 1972 74.46000 209275 15798.0636 ## 690 Iceland Europe 1977 76.11000 221823 19654.9625 ## 691 Iceland Europe 1982 76.99000 233997 23269.6075 ## 692 Iceland Europe 1987 77.23000 244676 26923.2063 ## 693 Iceland Europe 1992 78.77000 259012 25144.3920 ## 694 Iceland Europe 1997 78.95000 271192 28061.0997 ## 695 Iceland Europe 2002 80.50000 288030 31163.2020 ## 696 Iceland Europe 2007 81.75700 301931 36180.7892 ## 697 India Asia 1952 37.37300 372000000 546.5657 ## 698 India Asia 1957 40.24900 409000000 590.0620 ## 699 India Asia 1962 43.60500 454000000 658.3472 ## 700 India Asia 1967 47.19300 506000000 700.7706 ## 701 India Asia 1972 50.65100 567000000 724.0325 ## 702 India Asia 1977 54.20800 634000000 813.3373 ## 703 India Asia 1982 56.59600 708000000 855.7235 ## 704 India Asia 1987 58.55300 788000000 976.5127 ## 705 India Asia 1992 60.22300 872000000 1164.4068 ## 706 India Asia 1997 61.76500 959000000 1458.8174 ## 707 India Asia 2002 62.87900 1034172547 1746.7695 ## 708 India Asia 2007 64.69800 1110396331 2452.2104 ## 709 Indonesia Asia 1952 37.46800 82052000 749.6817 ## 710 Indonesia Asia 1957 39.91800 90124000 858.9003 ## 711 Indonesia Asia 1962 42.51800 99028000 849.2898 ## 712 Indonesia Asia 1967 45.96400 109343000 762.4318 ## 713 Indonesia Asia 1972 49.20300 121282000 1111.1079 ## 714 Indonesia Asia 1977 52.70200 136725000 1382.7021 ## 715 Indonesia Asia 1982 56.15900 153343000 1516.8730 ## 716 Indonesia Asia 1987 60.13700 169276000 1748.3570 ## 717 Indonesia Asia 1992 62.68100 184816000 2383.1409 ## 718 Indonesia Asia 1997 66.04100 199278000 3119.3356 ## 719 Indonesia Asia 2002 68.58800 211060000 2873.9129 ## 720 Indonesia Asia 2007 70.65000 223547000 3540.6516 ## 721 Iran Asia 1952 44.86900 17272000 3035.3260 ## 722 Iran Asia 1957 47.18100 19792000 3290.2576 ## 723 Iran Asia 1962 49.32500 22874000 4187.3298 ## 724 Iran Asia 1967 52.46900 26538000 5906.7318 ## 725 Iran Asia 1972 55.23400 30614000 9613.8186 ## 726 Iran Asia 1977 57.70200 35480679 11888.5951 ## 727 Iran Asia 1982 59.62000 43072751 7608.3346 ## 728 Iran Asia 1987 63.04000 51889696 6642.8814 ## 729 Iran Asia 1992 65.74200 60397973 7235.6532 ## 730 Iran Asia 1997 68.04200 63327987 8263.5903 ## 731 Iran Asia 2002 69.45100 66907826 9240.7620 ## 732 Iran Asia 2007 70.96400 69453570 11605.7145 ## 733 Iraq Asia 1952 45.32000 5441766 4129.7661 ## 734 Iraq Asia 1957 48.43700 6248643 6229.3336 ## 735 Iraq Asia 1962 51.45700 7240260 8341.7378 ## 736 Iraq Asia 1967 54.45900 8519282 8931.4598 ## 737 Iraq Asia 1972 56.95000 10061506 9576.0376 ## 738 Iraq Asia 1977 60.41300 11882916 14688.2351 ## 739 Iraq Asia 1982 62.03800 14173318 14517.9071 ## 740 Iraq Asia 1987 65.04400 16543189 11643.5727 ## 741 Iraq Asia 1992 59.46100 17861905 3745.6407 ## 742 Iraq Asia 1997 58.81100 20775703 3076.2398 ## 743 Iraq Asia 2002 57.04600 24001816 4390.7173 ## 744 Iraq Asia 2007 59.54500 27499638 4471.0619 ## 745 Ireland Europe 1952 66.91000 2952156 5210.2803 ## 746 Ireland Europe 1957 68.90000 2878220 5599.0779 ## 747 Ireland Europe 1962 70.29000 2830000 6631.5973 ## 748 Ireland Europe 1967 71.08000 2900100 7655.5690 ## 749 Ireland Europe 1972 71.28000 3024400 9530.7729 ## 750 Ireland Europe 1977 72.03000 3271900 11150.9811 ## 751 Ireland Europe 1982 73.10000 3480000 12618.3214 ## 752 Ireland Europe 1987 74.36000 3539900 13872.8665 ## 753 Ireland Europe 1992 75.46700 3557761 17558.8155 ## 754 Ireland Europe 1997 76.12200 3667233 24521.9471 ## 755 Ireland Europe 2002 77.78300 3879155 34077.0494 ## 756 Ireland Europe 2007 78.88500 4109086 40675.9964 ## 757 Israel Asia 1952 65.39000 1620914 4086.5221 ## 758 Israel Asia 1957 67.84000 1944401 5385.2785 ## 759 Israel Asia 1962 69.39000 2310904 7105.6307 ## 760 Israel Asia 1967 70.75000 2693585 8393.7414 ## 761 Israel Asia 1972 71.63000 3095893 12786.9322 ## 762 Israel Asia 1977 73.06000 3495918 13306.6192 ## 763 Israel Asia 1982 74.45000 3858421 15367.0292 ## 764 Israel Asia 1987 75.60000 4203148 17122.4799 ## 765 Israel Asia 1992 76.93000 4936550 18051.5225 ## 766 Israel Asia 1997 78.26900 5531387 20896.6092 ## 767 Israel Asia 2002 79.69600 6029529 21905.5951 ## 768 Israel Asia 2007 80.74500 6426679 25523.2771 ## 769 Italy Europe 1952 65.94000 47666000 4931.4042 ## 770 Italy Europe 1957 67.81000 49182000 6248.6562 ## 771 Italy Europe 1962 69.24000 50843200 8243.5823 ## 772 Italy Europe 1967 71.06000 52667100 10022.4013 ## 773 Italy Europe 1972 72.19000 54365564 12269.2738 ## 774 Italy Europe 1977 73.48000 56059245 14255.9847 ## 775 Italy Europe 1982 74.98000 56535636 16537.4835 ## 776 Italy Europe 1987 76.42000 56729703 19207.2348 ## 777 Italy Europe 1992 77.44000 56840847 22013.6449 ## 778 Italy Europe 1997 78.82000 57479469 24675.0245 ## 779 Italy Europe 2002 80.24000 57926999 27968.0982 ## 780 Italy Europe 2007 80.54600 58147733 28569.7197 ## 781 Jamaica Americas 1952 58.53000 1426095 2898.5309 ## 782 Jamaica Americas 1957 62.61000 1535090 4756.5258 ## 783 Jamaica Americas 1962 65.61000 1665128 5246.1075 ## 784 Jamaica Americas 1967 67.51000 1861096 6124.7035 ## 785 Jamaica Americas 1972 69.00000 1997616 7433.8893 ## 786 Jamaica Americas 1977 70.11000 2156814 6650.1956 ## 787 Jamaica Americas 1982 71.21000 2298309 6068.0513 ## 788 Jamaica Americas 1987 71.77000 2326606 6351.2375 ## 789 Jamaica Americas 1992 71.76600 2378618 7404.9237 ## 790 Jamaica Americas 1997 72.26200 2531311 7121.9247 ## 791 Jamaica Americas 2002 72.04700 2664659 6994.7749 ## 792 Jamaica Americas 2007 72.56700 2780132 7320.8803 ## 793 Japan Asia 1952 63.03000 86459025 3216.9563 ## 794 Japan Asia 1957 65.50000 91563009 4317.6944 ## 795 Japan Asia 1962 68.73000 95831757 6576.6495 ## 796 Japan Asia 1967 71.43000 100825279 9847.7886 ## 797 Japan Asia 1972 73.42000 107188273 14778.7864 ## 798 Japan Asia 1977 75.38000 113872473 16610.3770 ## 799 Japan Asia 1982 77.11000 118454974 19384.1057 ## 800 Japan Asia 1987 78.67000 122091325 22375.9419 ## 801 Japan Asia 1992 79.36000 124329269 26824.8951 ## 802 Japan Asia 1997 80.69000 125956499 28816.5850 ## 803 Japan Asia 2002 82.00000 127065841 28604.5919 ## 804 Japan Asia 2007 82.60300 127467972 31656.0681 ## 805 Jordan Asia 1952 43.15800 607914 1546.9078 ## 806 Jordan Asia 1957 45.66900 746559 1886.0806 ## 807 Jordan Asia 1962 48.12600 933559 2348.0092 ## 808 Jordan Asia 1967 51.62900 1255058 2741.7963 ## 809 Jordan Asia 1972 56.52800 1613551 2110.8563 ## 810 Jordan Asia 1977 61.13400 1937652 2852.3516 ## 811 Jordan Asia 1982 63.73900 2347031 4161.4160 ## 812 Jordan Asia 1987 65.86900 2820042 4448.6799 ## 813 Jordan Asia 1992 68.01500 3867409 3431.5936 ## 814 Jordan Asia 1997 69.77200 4526235 3645.3796 ## 815 Jordan Asia 2002 71.26300 5307470 3844.9172 ## 816 Jordan Asia 2007 72.53500 6053193 4519.4612 ## 817 Kenya Africa 1952 42.27000 6464046 853.5409 ## 818 Kenya Africa 1957 44.68600 7454779 944.4383 ## 819 Kenya Africa 1962 47.94900 8678557 896.9664 ## 820 Kenya Africa 1967 50.65400 10191512 1056.7365 ## 821 Kenya Africa 1972 53.55900 12044785 1222.3600 ## 822 Kenya Africa 1977 56.15500 14500404 1267.6132 ## 823 Kenya Africa 1982 58.76600 17661452 1348.2258 ## 824 Kenya Africa 1987 59.33900 21198082 1361.9369 ## 825 Kenya Africa 1992 59.28500 25020539 1341.9217 ## 826 Kenya Africa 1997 54.40700 28263827 1360.4850 ## 827 Kenya Africa 2002 50.99200 31386842 1287.5147 ## 828 Kenya Africa 2007 54.11000 35610177 1463.2493 ## 829 Korea, Dem. Rep. Asia 1952 50.05600 8865488 1088.2778 ## 830 Korea, Dem. Rep. Asia 1957 54.08100 9411381 1571.1347 ## 831 Korea, Dem. Rep. Asia 1962 56.65600 10917494 1621.6936 ## 832 Korea, Dem. Rep. Asia 1967 59.94200 12617009 2143.5406 ## 833 Korea, Dem. Rep. Asia 1972 63.98300 14781241 3701.6215 ## 834 Korea, Dem. Rep. Asia 1977 67.15900 16325320 4106.3012 ## 835 Korea, Dem. Rep. Asia 1982 69.10000 17647518 4106.5253 ## 836 Korea, Dem. Rep. Asia 1987 70.64700 19067554 4106.4923 ## 837 Korea, Dem. Rep. Asia 1992 69.97800 20711375 3726.0635 ## 838 Korea, Dem. Rep. Asia 1997 67.72700 21585105 1690.7568 ## 839 Korea, Dem. Rep. Asia 2002 66.66200 22215365 1646.7582 ## 840 Korea, Dem. Rep. Asia 2007 67.29700 23301725 1593.0655 ## 841 Korea, Rep. Asia 1952 47.45300 20947571 1030.5922 ## 842 Korea, Rep. Asia 1957 52.68100 22611552 1487.5935 ## 843 Korea, Rep. Asia 1962 55.29200 26420307 1536.3444 ## 844 Korea, Rep. Asia 1967 57.71600 30131000 2029.2281 ## 845 Korea, Rep. Asia 1972 62.61200 33505000 3030.8767 ## 846 Korea, Rep. Asia 1977 64.76600 36436000 4657.2210 ## 847 Korea, Rep. Asia 1982 67.12300 39326000 5622.9425 ## 848 Korea, Rep. Asia 1987 69.81000 41622000 8533.0888 ## 849 Korea, Rep. Asia 1992 72.24400 43805450 12104.2787 ## 850 Korea, Rep. Asia 1997 74.64700 46173816 15993.5280 ## 851 Korea, Rep. Asia 2002 77.04500 47969150 19233.9882 ## 852 Korea, Rep. Asia 2007 78.62300 49044790 23348.1397 ## 853 Kuwait Asia 1952 55.56500 160000 108382.3529 ## 854 Kuwait Asia 1957 58.03300 212846 113523.1329 ## 855 Kuwait Asia 1962 60.47000 358266 95458.1118 ## 856 Kuwait Asia 1967 64.62400 575003 80894.8833 ## 857 Kuwait Asia 1972 67.71200 841934 109347.8670 ## 858 Kuwait Asia 1977 69.34300 1140357 59265.4771 ## 859 Kuwait Asia 1982 71.30900 1497494 31354.0357 ## 860 Kuwait Asia 1987 74.17400 1891487 28118.4300 ## 861 Kuwait Asia 1992 75.19000 1418095 34932.9196 ## 862 Kuwait Asia 1997 76.15600 1765345 40300.6200 ## 863 Kuwait Asia 2002 76.90400 2111561 35110.1057 ## 864 Kuwait Asia 2007 77.58800 2505559 47306.9898 ## 865 Lebanon Asia 1952 55.92800 1439529 4834.8041 ## 866 Lebanon Asia 1957 59.48900 1647412 6089.7869 ## 867 Lebanon Asia 1962 62.09400 1886848 5714.5606 ## 868 Lebanon Asia 1967 63.87000 2186894 6006.9830 ## 869 Lebanon Asia 1972 65.42100 2680018 7486.3843 ## 870 Lebanon Asia 1977 66.09900 3115787 8659.6968 ## 871 Lebanon Asia 1982 66.98300 3086876 7640.5195 ## 872 Lebanon Asia 1987 67.92600 3089353 5377.0913 ## 873 Lebanon Asia 1992 69.29200 3219994 6890.8069 ## 874 Lebanon Asia 1997 70.26500 3430388 8754.9639 ## 875 Lebanon Asia 2002 71.02800 3677780 9313.9388 ## 876 Lebanon Asia 2007 71.99300 3921278 10461.0587 ## 877 Lesotho Africa 1952 42.13800 748747 298.8462 ## 878 Lesotho Africa 1957 45.04700 813338 335.9971 ## 879 Lesotho Africa 1962 47.74700 893143 411.8006 ## 880 Lesotho Africa 1967 48.49200 996380 498.6390 ## 881 Lesotho Africa 1972 49.76700 1116779 496.5816 ## 882 Lesotho Africa 1977 52.20800 1251524 745.3695 ## 883 Lesotho Africa 1982 55.07800 1411807 797.2631 ## 884 Lesotho Africa 1987 57.18000 1599200 773.9932 ## 885 Lesotho Africa 1992 59.68500 1803195 977.4863 ## 886 Lesotho Africa 1997 55.55800 1982823 1186.1480 ## 887 Lesotho Africa 2002 44.59300 2046772 1275.1846 ## 888 Lesotho Africa 2007 42.59200 2012649 1569.3314 ## 889 Liberia Africa 1952 38.48000 863308 575.5730 ## 890 Liberia Africa 1957 39.48600 975950 620.9700 ## 891 Liberia Africa 1962 40.50200 1112796 634.1952 ## 892 Liberia Africa 1967 41.53600 1279406 713.6036 ## 893 Liberia Africa 1972 42.61400 1482628 803.0055 ## 894 Liberia Africa 1977 43.76400 1703617 640.3224 ## 895 Liberia Africa 1982 44.85200 1956875 572.1996 ## 896 Liberia Africa 1987 46.02700 2269414 506.1139 ## 897 Liberia Africa 1992 40.80200 1912974 636.6229 ## 898 Liberia Africa 1997 42.22100 2200725 609.1740 ## 899 Liberia Africa 2002 43.75300 2814651 531.4824 ## 900 Liberia Africa 2007 45.67800 3193942 414.5073 ## 901 Libya Africa 1952 42.72300 1019729 2387.5481 ## 902 Libya Africa 1957 45.28900 1201578 3448.2844 ## 903 Libya Africa 1962 47.80800 1441863 6757.0308 ## 904 Libya Africa 1967 50.22700 1759224 18772.7517 ## 905 Libya Africa 1972 52.77300 2183877 21011.4972 ## 906 Libya Africa 1977 57.44200 2721783 21951.2118 ## 907 Libya Africa 1982 62.15500 3344074 17364.2754 ## 908 Libya Africa 1987 66.23400 3799845 11770.5898 ## 909 Libya Africa 1992 68.75500 4364501 9640.1385 ## 910 Libya Africa 1997 71.55500 4759670 9467.4461 ## 911 Libya Africa 2002 72.73700 5368585 9534.6775 ## 912 Libya Africa 2007 73.95200 6036914 12057.4993 ## 913 Madagascar Africa 1952 36.68100 4762912 1443.0117 ## 914 Madagascar Africa 1957 38.86500 5181679 1589.2027 ## 915 Madagascar Africa 1962 40.84800 5703324 1643.3871 ## 916 Madagascar Africa 1967 42.88100 6334556 1634.0473 ## 917 Madagascar Africa 1972 44.85100 7082430 1748.5630 ## 918 Madagascar Africa 1977 46.88100 8007166 1544.2286 ## 919 Madagascar Africa 1982 48.96900 9171477 1302.8787 ## 920 Madagascar Africa 1987 49.35000 10568642 1155.4419 ## 921 Madagascar Africa 1992 52.21400 12210395 1040.6762 ## 922 Madagascar Africa 1997 54.97800 14165114 986.2959 ## 923 Madagascar Africa 2002 57.28600 16473477 894.6371 ## 924 Madagascar Africa 2007 59.44300 19167654 1044.7701 ## 925 Malawi Africa 1952 36.25600 2917802 369.1651 ## 926 Malawi Africa 1957 37.20700 3221238 416.3698 ## 927 Malawi Africa 1962 38.41000 3628608 427.9011 ## 928 Malawi Africa 1967 39.48700 4147252 495.5148 ## 929 Malawi Africa 1972 41.76600 4730997 584.6220 ## 930 Malawi Africa 1977 43.76700 5637246 663.2237 ## 931 Malawi Africa 1982 45.64200 6502825 632.8039 ## 932 Malawi Africa 1987 47.45700 7824747 635.5174 ## 933 Malawi Africa 1992 49.42000 10014249 563.2000 ## 934 Malawi Africa 1997 47.49500 10419991 692.2758 ## 935 Malawi Africa 2002 45.00900 11824495 665.4231 ## 936 Malawi Africa 2007 48.30300 13327079 759.3499 ## 937 Malaysia Asia 1952 48.46300 6748378 1831.1329 ## 938 Malaysia Asia 1957 52.10200 7739235 1810.0670 ## 939 Malaysia Asia 1962 55.73700 8906385 2036.8849 ## 940 Malaysia Asia 1967 59.37100 10154878 2277.7424 ## 941 Malaysia Asia 1972 63.01000 11441462 2849.0948 ## 942 Malaysia Asia 1977 65.25600 12845381 3827.9216 ## 943 Malaysia Asia 1982 68.00000 14441916 4920.3560 ## 944 Malaysia Asia 1987 69.50000 16331785 5249.8027 ## 945 Malaysia Asia 1992 70.69300 18319502 7277.9128 ## 946 Malaysia Asia 1997 71.93800 20476091 10132.9096 ## 947 Malaysia Asia 2002 73.04400 22662365 10206.9779 ## 948 Malaysia Asia 2007 74.24100 24821286 12451.6558 ## 949 Mali Africa 1952 33.68500 3838168 452.3370 ## 950 Mali Africa 1957 35.30700 4241884 490.3822 ## 951 Mali Africa 1962 36.93600 4690372 496.1743 ## 952 Mali Africa 1967 38.48700 5212416 545.0099 ## 953 Mali Africa 1972 39.97700 5828158 581.3689 ## 954 Mali Africa 1977 41.71400 6491649 686.3953 ## 955 Mali Africa 1982 43.91600 6998256 618.0141 ## 956 Mali Africa 1987 46.36400 7634008 684.1716 ## 957 Mali Africa 1992 48.38800 8416215 739.0144 ## 958 Mali Africa 1997 49.90300 9384984 790.2580 ## 959 Mali Africa 2002 51.81800 10580176 951.4098 ## 960 Mali Africa 2007 54.46700 12031795 1042.5816 ## 961 Mauritania Africa 1952 40.54300 1022556 743.1159 ## 962 Mauritania Africa 1957 42.33800 1076852 846.1203 ## 963 Mauritania Africa 1962 44.24800 1146757 1055.8960 ## 964 Mauritania Africa 1967 46.28900 1230542 1421.1452 ## 965 Mauritania Africa 1972 48.43700 1332786 1586.8518 ## 966 Mauritania Africa 1977 50.85200 1456688 1497.4922 ## 967 Mauritania Africa 1982 53.59900 1622136 1481.1502 ## 968 Mauritania Africa 1987 56.14500 1841240 1421.6036 ## 969 Mauritania Africa 1992 58.33300 2119465 1361.3698 ## 970 Mauritania Africa 1997 60.43000 2444741 1483.1361 ## 971 Mauritania Africa 2002 62.24700 2828858 1579.0195 ## 972 Mauritania Africa 2007 64.16400 3270065 1803.1515 ## 973 Mauritius Africa 1952 50.98600 516556 1967.9557 ## 974 Mauritius Africa 1957 58.08900 609816 2034.0380 ## 975 Mauritius Africa 1962 60.24600 701016 2529.0675 ## 976 Mauritius Africa 1967 61.55700 789309 2475.3876 ## 977 Mauritius Africa 1972 62.94400 851334 2575.4842 ## 978 Mauritius Africa 1977 64.93000 913025 3710.9830 ## 979 Mauritius Africa 1982 66.71100 992040 3688.0377 ## 980 Mauritius Africa 1987 68.74000 1042663 4783.5869 ## 981 Mauritius Africa 1992 69.74500 1096202 6058.2538 ## 982 Mauritius Africa 1997 70.73600 1149818 7425.7053 ## 983 Mauritius Africa 2002 71.95400 1200206 9021.8159 ## 984 Mauritius Africa 2007 72.80100 1250882 10956.9911 ## 985 Mexico Americas 1952 50.78900 30144317 3478.1255 ## 986 Mexico Americas 1957 55.19000 35015548 4131.5466 ## 987 Mexico Americas 1962 58.29900 41121485 4581.6094 ## 988 Mexico Americas 1967 60.11000 47995559 5754.7339 ## 989 Mexico Americas 1972 62.36100 55984294 6809.4067 ## 990 Mexico Americas 1977 65.03200 63759976 7674.9291 ## 991 Mexico Americas 1982 67.40500 71640904 9611.1475 ## 992 Mexico Americas 1987 69.49800 80122492 8688.1560 ## 993 Mexico Americas 1992 71.45500 88111030 9472.3843 ## 994 Mexico Americas 1997 73.67000 95895146 9767.2975 ## 995 Mexico Americas 2002 74.90200 102479927 10742.4405 ## 996 Mexico Americas 2007 76.19500 108700891 11977.5750 ## 997 Mongolia Asia 1952 42.24400 800663 786.5669 ## 998 Mongolia Asia 1957 45.24800 882134 912.6626 ## 999 Mongolia Asia 1962 48.25100 1010280 1056.3540 ## 1000 Mongolia Asia 1967 51.25300 1149500 1226.0411 ## 1001 Mongolia Asia 1972 53.75400 1320500 1421.7420 ## 1002 Mongolia Asia 1977 55.49100 1528000 1647.5117 ## 1003 Mongolia Asia 1982 57.48900 1756032 2000.6031 ## 1004 Mongolia Asia 1987 60.22200 2015133 2338.0083 ## 1005 Mongolia Asia 1992 61.27100 2312802 1785.4020 ## 1006 Mongolia Asia 1997 63.62500 2494803 1902.2521 ## 1007 Mongolia Asia 2002 65.03300 2674234 2140.7393 ## 1008 Mongolia Asia 2007 66.80300 2874127 3095.7723 ## 1009 Montenegro Europe 1952 59.16400 413834 2647.5856 ## 1010 Montenegro Europe 1957 61.44800 442829 3682.2599 ## 1011 Montenegro Europe 1962 63.72800 474528 4649.5938 ## 1012 Montenegro Europe 1967 67.17800 501035 5907.8509 ## 1013 Montenegro Europe 1972 70.63600 527678 7778.4140 ## 1014 Montenegro Europe 1977 73.06600 560073 9595.9299 ## 1015 Montenegro Europe 1982 74.10100 562548 11222.5876 ## 1016 Montenegro Europe 1987 74.86500 569473 11732.5102 ## 1017 Montenegro Europe 1992 75.43500 621621 7003.3390 ## 1018 Montenegro Europe 1997 75.44500 692651 6465.6133 ## 1019 Montenegro Europe 2002 73.98100 720230 6557.1943 ## 1020 Montenegro Europe 2007 74.54300 684736 9253.8961 ## 1021 Morocco Africa 1952 42.87300 9939217 1688.2036 ## 1022 Morocco Africa 1957 45.42300 11406350 1642.0023 ## 1023 Morocco Africa 1962 47.92400 13056604 1566.3535 ## 1024 Morocco Africa 1967 50.33500 14770296 1711.0448 ## 1025 Morocco Africa 1972 52.86200 16660670 1930.1950 ## 1026 Morocco Africa 1977 55.73000 18396941 2370.6200 ## 1027 Morocco Africa 1982 59.65000 20198730 2702.6204 ## 1028 Morocco Africa 1987 62.67700 22987397 2755.0470 ## 1029 Morocco Africa 1992 65.39300 25798239 2948.0473 ## 1030 Morocco Africa 1997 67.66000 28529501 2982.1019 ## 1031 Morocco Africa 2002 69.61500 31167783 3258.4956 ## 1032 Morocco Africa 2007 71.16400 33757175 3820.1752 ## 1033 Mozambique Africa 1952 31.28600 6446316 468.5260 ## 1034 Mozambique Africa 1957 33.77900 7038035 495.5868 ## 1035 Mozambique Africa 1962 36.16100 7788944 556.6864 ## 1036 Mozambique Africa 1967 38.11300 8680909 566.6692 ## 1037 Mozambique Africa 1972 40.32800 9809596 724.9178 ## 1038 Mozambique Africa 1977 42.49500 11127868 502.3197 ## 1039 Mozambique Africa 1982 42.79500 12587223 462.2114 ## 1040 Mozambique Africa 1987 42.86100 12891952 389.8762 ## 1041 Mozambique Africa 1992 44.28400 13160731 410.8968 ## 1042 Mozambique Africa 1997 46.34400 16603334 472.3461 ## 1043 Mozambique Africa 2002 44.02600 18473780 633.6179 ## 1044 Mozambique Africa 2007 42.08200 19951656 823.6856 ## 1045 Myanmar Asia 1952 36.31900 20092996 331.0000 ## 1046 Myanmar Asia 1957 41.90500 21731844 350.0000 ## 1047 Myanmar Asia 1962 45.10800 23634436 388.0000 ## 1048 Myanmar Asia 1967 49.37900 25870271 349.0000 ## 1049 Myanmar Asia 1972 53.07000 28466390 357.0000 ## 1050 Myanmar Asia 1977 56.05900 31528087 371.0000 ## 1051 Myanmar Asia 1982 58.05600 34680442 424.0000 ## 1052 Myanmar Asia 1987 58.33900 38028578 385.0000 ## 1053 Myanmar Asia 1992 59.32000 40546538 347.0000 ## 1054 Myanmar Asia 1997 60.32800 43247867 415.0000 ## 1055 Myanmar Asia 2002 59.90800 45598081 611.0000 ## 1056 Myanmar Asia 2007 62.06900 47761980 944.0000 ## 1057 Namibia Africa 1952 41.72500 485831 2423.7804 ## 1058 Namibia Africa 1957 45.22600 548080 2621.4481 ## 1059 Namibia Africa 1962 48.38600 621392 3173.2156 ## 1060 Namibia Africa 1967 51.15900 706640 3793.6948 ## 1061 Namibia Africa 1972 53.86700 821782 3746.0809 ## 1062 Namibia Africa 1977 56.43700 977026 3876.4860 ## 1063 Namibia Africa 1982 58.96800 1099010 4191.1005 ## 1064 Namibia Africa 1987 60.83500 1278184 3693.7313 ## 1065 Namibia Africa 1992 61.99900 1554253 3804.5380 ## 1066 Namibia Africa 1997 58.90900 1774766 3899.5243 ## 1067 Namibia Africa 2002 51.47900 1972153 4072.3248 ## 1068 Namibia Africa 2007 52.90600 2055080 4811.0604 ## 1069 Nepal Asia 1952 36.15700 9182536 545.8657 ## 1070 Nepal Asia 1957 37.68600 9682338 597.9364 ## 1071 Nepal Asia 1962 39.39300 10332057 652.3969 ## 1072 Nepal Asia 1967 41.47200 11261690 676.4422 ## 1073 Nepal Asia 1972 43.97100 12412593 674.7881 ## 1074 Nepal Asia 1977 46.74800 13933198 694.1124 ## 1075 Nepal Asia 1982 49.59400 15796314 718.3731 ## 1076 Nepal Asia 1987 52.53700 17917180 775.6325 ## 1077 Nepal Asia 1992 55.72700 20326209 897.7404 ## 1078 Nepal Asia 1997 59.42600 23001113 1010.8921 ## 1079 Nepal Asia 2002 61.34000 25873917 1057.2063 ## 1080 Nepal Asia 2007 63.78500 28901790 1091.3598 ## 1081 Netherlands Europe 1952 72.13000 10381988 8941.5719 ## 1082 Netherlands Europe 1957 72.99000 11026383 11276.1934 ## 1083 Netherlands Europe 1962 73.23000 11805689 12790.8496 ## 1084 Netherlands Europe 1967 73.82000 12596822 15363.2514 ## 1085 Netherlands Europe 1972 73.75000 13329874 18794.7457 ## 1086 Netherlands Europe 1977 75.24000 13852989 21209.0592 ## 1087 Netherlands Europe 1982 76.05000 14310401 21399.4605 ## 1088 Netherlands Europe 1987 76.83000 14665278 23651.3236 ## 1089 Netherlands Europe 1992 77.42000 15174244 26790.9496 ## 1090 Netherlands Europe 1997 78.03000 15604464 30246.1306 ## 1091 Netherlands Europe 2002 78.53000 16122830 33724.7578 ## 1092 Netherlands Europe 2007 79.76200 16570613 36797.9333 ## 1093 New Zealand Oceania 1952 69.39000 1994794 10556.5757 ## 1094 New Zealand Oceania 1957 70.26000 2229407 12247.3953 ## 1095 New Zealand Oceania 1962 71.24000 2488550 13175.6780 ## 1096 New Zealand Oceania 1967 71.52000 2728150 14463.9189 ## 1097 New Zealand Oceania 1972 71.89000 2929100 16046.0373 ## 1098 New Zealand Oceania 1977 72.22000 3164900 16233.7177 ## 1099 New Zealand Oceania 1982 73.84000 3210650 17632.4104 ## 1100 New Zealand Oceania 1987 74.32000 3317166 19007.1913 ## 1101 New Zealand Oceania 1992 76.33000 3437674 18363.3249 ## 1102 New Zealand Oceania 1997 77.55000 3676187 21050.4138 ## 1103 New Zealand Oceania 2002 79.11000 3908037 23189.8014 ## 1104 New Zealand Oceania 2007 80.20400 4115771 25185.0091 ## 1105 Nicaragua Americas 1952 42.31400 1165790 3112.3639 ## 1106 Nicaragua Americas 1957 45.43200 1358828 3457.4159 ## 1107 Nicaragua Americas 1962 48.63200 1590597 3634.3644 ## 1108 Nicaragua Americas 1967 51.88400 1865490 4643.3935 ## 1109 Nicaragua Americas 1972 55.15100 2182908 4688.5933 ## 1110 Nicaragua Americas 1977 57.47000 2554598 5486.3711 ## 1111 Nicaragua Americas 1982 59.29800 2979423 3470.3382 ## 1112 Nicaragua Americas 1987 62.00800 3344353 2955.9844 ## 1113 Nicaragua Americas 1992 65.84300 4017939 2170.1517 ## 1114 Nicaragua Americas 1997 68.42600 4609572 2253.0230 ## 1115 Nicaragua Americas 2002 70.83600 5146848 2474.5488 ## 1116 Nicaragua Americas 2007 72.89900 5675356 2749.3210 ## 1117 Niger Africa 1952 37.44400 3379468 761.8794 ## 1118 Niger Africa 1957 38.59800 3692184 835.5234 ## 1119 Niger Africa 1962 39.48700 4076008 997.7661 ## 1120 Niger Africa 1967 40.11800 4534062 1054.3849 ## 1121 Niger Africa 1972 40.54600 5060262 954.2092 ## 1122 Niger Africa 1977 41.29100 5682086 808.8971 ## 1123 Niger Africa 1982 42.59800 6437188 909.7221 ## 1124 Niger Africa 1987 44.55500 7332638 668.3000 ## 1125 Niger Africa 1992 47.39100 8392818 581.1827 ## 1126 Niger Africa 1997 51.31300 9666252 580.3052 ## 1127 Niger Africa 2002 54.49600 11140655 601.0745 ## 1128 Niger Africa 2007 56.86700 12894865 619.6769 ## 1129 Nigeria Africa 1952 36.32400 33119096 1077.2819 ## 1130 Nigeria Africa 1957 37.80200 37173340 1100.5926 ## 1131 Nigeria Africa 1962 39.36000 41871351 1150.9275 ## 1132 Nigeria Africa 1967 41.04000 47287752 1014.5141 ## 1133 Nigeria Africa 1972 42.82100 53740085 1698.3888 ## 1134 Nigeria Africa 1977 44.51400 62209173 1981.9518 ## 1135 Nigeria Africa 1982 45.82600 73039376 1576.9738 ## 1136 Nigeria Africa 1987 46.88600 81551520 1385.0296 ## 1137 Nigeria Africa 1992 47.47200 93364244 1619.8482 ## 1138 Nigeria Africa 1997 47.46400 106207839 1624.9413 ## 1139 Nigeria Africa 2002 46.60800 119901274 1615.2864 ## 1140 Nigeria Africa 2007 46.85900 135031164 2013.9773 ## 1141 Norway Europe 1952 72.67000 3327728 10095.4217 ## 1142 Norway Europe 1957 73.44000 3491938 11653.9730 ## 1143 Norway Europe 1962 73.47000 3638919 13450.4015 ## 1144 Norway Europe 1967 74.08000 3786019 16361.8765 ## 1145 Norway Europe 1972 74.34000 3933004 18965.0555 ## 1146 Norway Europe 1977 75.37000 4043205 23311.3494 ## 1147 Norway Europe 1982 75.97000 4114787 26298.6353 ## 1148 Norway Europe 1987 75.89000 4186147 31540.9748 ## 1149 Norway Europe 1992 77.32000 4286357 33965.6611 ## 1150 Norway Europe 1997 78.32000 4405672 41283.1643 ## 1151 Norway Europe 2002 79.05000 4535591 44683.9753 ## 1152 Norway Europe 2007 80.19600 4627926 49357.1902 ## 1153 Oman Asia 1952 37.57800 507833 1828.2303 ## 1154 Oman Asia 1957 40.08000 561977 2242.7466 ## 1155 Oman Asia 1962 43.16500 628164 2924.6381 ## 1156 Oman Asia 1967 46.98800 714775 4720.9427 ## 1157 Oman Asia 1972 52.14300 829050 10618.0385 ## 1158 Oman Asia 1977 57.36700 1004533 11848.3439 ## 1159 Oman Asia 1982 62.72800 1301048 12954.7910 ## 1160 Oman Asia 1987 67.73400 1593882 18115.2231 ## 1161 Oman Asia 1992 71.19700 1915208 18616.7069 ## 1162 Oman Asia 1997 72.49900 2283635 19702.0558 ## 1163 Oman Asia 2002 74.19300 2713462 19774.8369 ## 1164 Oman Asia 2007 75.64000 3204897 22316.1929 ## 1165 Pakistan Asia 1952 43.43600 41346560 684.5971 ## 1166 Pakistan Asia 1957 45.55700 46679944 747.0835 ## 1167 Pakistan Asia 1962 47.67000 53100671 803.3427 ## 1168 Pakistan Asia 1967 49.80000 60641899 942.4083 ## 1169 Pakistan Asia 1972 51.92900 69325921 1049.9390 ## 1170 Pakistan Asia 1977 54.04300 78152686 1175.9212 ## 1171 Pakistan Asia 1982 56.15800 91462088 1443.4298 ## 1172 Pakistan Asia 1987 58.24500 105186881 1704.6866 ## 1173 Pakistan Asia 1992 60.83800 120065004 1971.8295 ## 1174 Pakistan Asia 1997 61.81800 135564834 2049.3505 ## 1175 Pakistan Asia 2002 63.61000 153403524 2092.7124 ## 1176 Pakistan Asia 2007 65.48300 169270617 2605.9476 ## 1177 Panama Americas 1952 55.19100 940080 2480.3803 ## 1178 Panama Americas 1957 59.20100 1063506 2961.8009 ## 1179 Panama Americas 1962 61.81700 1215725 3536.5403 ## 1180 Panama Americas 1967 64.07100 1405486 4421.0091 ## 1181 Panama Americas 1972 66.21600 1616384 5364.2497 ## 1182 Panama Americas 1977 68.68100 1839782 5351.9121 ## 1183 Panama Americas 1982 70.47200 2036305 7009.6016 ## 1184 Panama Americas 1987 71.52300 2253639 7034.7792 ## 1185 Panama Americas 1992 72.46200 2484997 6618.7431 ## 1186 Panama Americas 1997 73.73800 2734531 7113.6923 ## 1187 Panama Americas 2002 74.71200 2990875 7356.0319 ## 1188 Panama Americas 2007 75.53700 3242173 9809.1856 ## 1189 Paraguay Americas 1952 62.64900 1555876 1952.3087 ## 1190 Paraguay Americas 1957 63.19600 1770902 2046.1547 ## 1191 Paraguay Americas 1962 64.36100 2009813 2148.0271 ## 1192 Paraguay Americas 1967 64.95100 2287985 2299.3763 ## 1193 Paraguay Americas 1972 65.81500 2614104 2523.3380 ## 1194 Paraguay Americas 1977 66.35300 2984494 3248.3733 ## 1195 Paraguay Americas 1982 66.87400 3366439 4258.5036 ## 1196 Paraguay Americas 1987 67.37800 3886512 3998.8757 ## 1197 Paraguay Americas 1992 68.22500 4483945 4196.4111 ## 1198 Paraguay Americas 1997 69.40000 5154123 4247.4003 ## 1199 Paraguay Americas 2002 70.75500 5884491 3783.6742 ## 1200 Paraguay Americas 2007 71.75200 6667147 4172.8385 ## 1201 Peru Americas 1952 43.90200 8025700 3758.5234 ## 1202 Peru Americas 1957 46.26300 9146100 4245.2567 ## 1203 Peru Americas 1962 49.09600 10516500 4957.0380 ## 1204 Peru Americas 1967 51.44500 12132200 5788.0933 ## 1205 Peru Americas 1972 55.44800 13954700 5937.8273 ## 1206 Peru Americas 1977 58.44700 15990099 6281.2909 ## 1207 Peru Americas 1982 61.40600 18125129 6434.5018 ## 1208 Peru Americas 1987 64.13400 20195924 6360.9434 ## 1209 Peru Americas 1992 66.45800 22430449 4446.3809 ## 1210 Peru Americas 1997 68.38600 24748122 5838.3477 ## 1211 Peru Americas 2002 69.90600 26769436 5909.0201 ## 1212 Peru Americas 2007 71.42100 28674757 7408.9056 ## 1213 Philippines Asia 1952 47.75200 22438691 1272.8810 ## 1214 Philippines Asia 1957 51.33400 26072194 1547.9448 ## 1215 Philippines Asia 1962 54.75700 30325264 1649.5522 ## 1216 Philippines Asia 1967 56.39300 35356600 1814.1274 ## 1217 Philippines Asia 1972 58.06500 40850141 1989.3741 ## 1218 Philippines Asia 1977 60.06000 46850962 2373.2043 ## 1219 Philippines Asia 1982 62.08200 53456774 2603.2738 ## 1220 Philippines Asia 1987 64.15100 60017788 2189.6350 ## 1221 Philippines Asia 1992 66.45800 67185766 2279.3240 ## 1222 Philippines Asia 1997 68.56400 75012988 2536.5349 ## 1223 Philippines Asia 2002 70.30300 82995088 2650.9211 ## 1224 Philippines Asia 2007 71.68800 91077287 3190.4810 ## 1225 Poland Europe 1952 61.31000 25730551 4029.3297 ## 1226 Poland Europe 1957 65.77000 28235346 4734.2530 ## 1227 Poland Europe 1962 67.64000 30329617 5338.7521 ## 1228 Poland Europe 1967 69.61000 31785378 6557.1528 ## 1229 Poland Europe 1972 70.85000 33039545 8006.5070 ## 1230 Poland Europe 1977 70.67000 34621254 9508.1415 ## 1231 Poland Europe 1982 71.32000 36227381 8451.5310 ## 1232 Poland Europe 1987 70.98000 37740710 9082.3512 ## 1233 Poland Europe 1992 70.99000 38370697 7738.8812 ## 1234 Poland Europe 1997 72.75000 38654957 10159.5837 ## 1235 Poland Europe 2002 74.67000 38625976 12002.2391 ## 1236 Poland Europe 2007 75.56300 38518241 15389.9247 ## 1237 Portugal Europe 1952 59.82000 8526050 3068.3199 ## 1238 Portugal Europe 1957 61.51000 8817650 3774.5717 ## 1239 Portugal Europe 1962 64.39000 9019800 4727.9549 ## 1240 Portugal Europe 1967 66.60000 9103000 6361.5180 ## 1241 Portugal Europe 1972 69.26000 8970450 9022.2474 ## 1242 Portugal Europe 1977 70.41000 9662600 10172.4857 ## 1243 Portugal Europe 1982 72.77000 9859650 11753.8429 ## 1244 Portugal Europe 1987 74.06000 9915289 13039.3088 ## 1245 Portugal Europe 1992 74.86000 9927680 16207.2666 ## 1246 Portugal Europe 1997 75.97000 10156415 17641.0316 ## 1247 Portugal Europe 2002 77.29000 10433867 19970.9079 ## 1248 Portugal Europe 2007 78.09800 10642836 20509.6478 ## 1249 Puerto Rico Americas 1952 64.28000 2227000 3081.9598 ## 1250 Puerto Rico Americas 1957 68.54000 2260000 3907.1562 ## 1251 Puerto Rico Americas 1962 69.62000 2448046 5108.3446 ## 1252 Puerto Rico Americas 1967 71.10000 2648961 6929.2777 ## 1253 Puerto Rico Americas 1972 72.16000 2847132 9123.0417 ## 1254 Puerto Rico Americas 1977 73.44000 3080828 9770.5249 ## 1255 Puerto Rico Americas 1982 73.75000 3279001 10330.9891 ## 1256 Puerto Rico Americas 1987 74.63000 3444468 12281.3419 ## 1257 Puerto Rico Americas 1992 73.91100 3585176 14641.5871 ## 1258 Puerto Rico Americas 1997 74.91700 3759430 16999.4333 ## 1259 Puerto Rico Americas 2002 77.77800 3859606 18855.6062 ## 1260 Puerto Rico Americas 2007 78.74600 3942491 19328.7090 ## 1261 Reunion Africa 1952 52.72400 257700 2718.8853 ## 1262 Reunion Africa 1957 55.09000 308700 2769.4518 ## 1263 Reunion Africa 1962 57.66600 358900 3173.7233 ## 1264 Reunion Africa 1967 60.54200 414024 4021.1757 ## 1265 Reunion Africa 1972 64.27400 461633 5047.6586 ## 1266 Reunion Africa 1977 67.06400 492095 4319.8041 ## 1267 Reunion Africa 1982 69.88500 517810 5267.2194 ## 1268 Reunion Africa 1987 71.91300 562035 5303.3775 ## 1269 Reunion Africa 1992 73.61500 622191 6101.2558 ## 1270 Reunion Africa 1997 74.77200 684810 6071.9414 ## 1271 Reunion Africa 2002 75.74400 743981 6316.1652 ## 1272 Reunion Africa 2007 76.44200 798094 7670.1226 ## 1273 Romania Europe 1952 61.05000 16630000 3144.6132 ## 1274 Romania Europe 1957 64.10000 17829327 3943.3702 ## 1275 Romania Europe 1962 66.80000 18680721 4734.9976 ## 1276 Romania Europe 1967 66.80000 19284814 6470.8665 ## 1277 Romania Europe 1972 69.21000 20662648 8011.4144 ## 1278 Romania Europe 1977 69.46000 21658597 9356.3972 ## 1279 Romania Europe 1982 69.66000 22356726 9605.3141 ## 1280 Romania Europe 1987 69.53000 22686371 9696.2733 ## 1281 Romania Europe 1992 69.36000 22797027 6598.4099 ## 1282 Romania Europe 1997 69.72000 22562458 7346.5476 ## 1283 Romania Europe 2002 71.32200 22404337 7885.3601 ## 1284 Romania Europe 2007 72.47600 22276056 10808.4756 ## 1285 Rwanda Africa 1952 40.00000 2534927 493.3239 ## 1286 Rwanda Africa 1957 41.50000 2822082 540.2894 ## 1287 Rwanda Africa 1962 43.00000 3051242 597.4731 ## 1288 Rwanda Africa 1967 44.10000 3451079 510.9637 ## 1289 Rwanda Africa 1972 44.60000 3992121 590.5807 ## 1290 Rwanda Africa 1977 45.00000 4657072 670.0806 ## 1291 Rwanda Africa 1982 46.21800 5507565 881.5706 ## 1292 Rwanda Africa 1987 44.02000 6349365 847.9912 ## 1293 Rwanda Africa 1992 23.59900 7290203 737.0686 ## 1294 Rwanda Africa 1997 36.08700 7212583 589.9445 ## 1295 Rwanda Africa 2002 43.41300 7852401 785.6538 ## 1296 Rwanda Africa 2007 46.24200 8860588 863.0885 ## 1297 Sao Tome and Principe Africa 1952 46.47100 60011 879.5836 ## 1298 Sao Tome and Principe Africa 1957 48.94500 61325 860.7369 ## 1299 Sao Tome and Principe Africa 1962 51.89300 65345 1071.5511 ## 1300 Sao Tome and Principe Africa 1967 54.42500 70787 1384.8406 ## 1301 Sao Tome and Principe Africa 1972 56.48000 76595 1532.9853 ## 1302 Sao Tome and Principe Africa 1977 58.55000 86796 1737.5617 ## 1303 Sao Tome and Principe Africa 1982 60.35100 98593 1890.2181 ## 1304 Sao Tome and Principe Africa 1987 61.72800 110812 1516.5255 ## 1305 Sao Tome and Principe Africa 1992 62.74200 125911 1428.7778 ## 1306 Sao Tome and Principe Africa 1997 63.30600 145608 1339.0760 ## 1307 Sao Tome and Principe Africa 2002 64.33700 170372 1353.0924 ## 1308 Sao Tome and Principe Africa 2007 65.52800 199579 1598.4351 ## 1309 Saudi Arabia Asia 1952 39.87500 4005677 6459.5548 ## 1310 Saudi Arabia Asia 1957 42.86800 4419650 8157.5912 ## 1311 Saudi Arabia Asia 1962 45.91400 4943029 11626.4197 ## 1312 Saudi Arabia Asia 1967 49.90100 5618198 16903.0489 ## 1313 Saudi Arabia Asia 1972 53.88600 6472756 24837.4287 ## 1314 Saudi Arabia Asia 1977 58.69000 8128505 34167.7626 ## 1315 Saudi Arabia Asia 1982 63.01200 11254672 33693.1753 ## 1316 Saudi Arabia Asia 1987 66.29500 14619745 21198.2614 ## 1317 Saudi Arabia Asia 1992 68.76800 16945857 24841.6178 ## 1318 Saudi Arabia Asia 1997 70.53300 21229759 20586.6902 ## 1319 Saudi Arabia Asia 2002 71.62600 24501530 19014.5412 ## 1320 Saudi Arabia Asia 2007 72.77700 27601038 21654.8319 ## 1321 Senegal Africa 1952 37.27800 2755589 1450.3570 ## 1322 Senegal Africa 1957 39.32900 3054547 1567.6530 ## 1323 Senegal Africa 1962 41.45400 3430243 1654.9887 ## 1324 Senegal Africa 1967 43.56300 3965841 1612.4046 ## 1325 Senegal Africa 1972 45.81500 4588696 1597.7121 ## 1326 Senegal Africa 1977 48.87900 5260855 1561.7691 ## 1327 Senegal Africa 1982 52.37900 6147783 1518.4800 ## 1328 Senegal Africa 1987 55.76900 7171347 1441.7207 ## 1329 Senegal Africa 1992 58.19600 8307920 1367.8994 ## 1330 Senegal Africa 1997 60.18700 9535314 1392.3683 ## 1331 Senegal Africa 2002 61.60000 10870037 1519.6353 ## 1332 Senegal Africa 2007 63.06200 12267493 1712.4721 ## 1333 Serbia Europe 1952 57.99600 6860147 3581.4594 ## 1334 Serbia Europe 1957 61.68500 7271135 4981.0909 ## 1335 Serbia Europe 1962 64.53100 7616060 6289.6292 ## 1336 Serbia Europe 1967 66.91400 7971222 7991.7071 ## 1337 Serbia Europe 1972 68.70000 8313288 10522.0675 ## 1338 Serbia Europe 1977 70.30000 8686367 12980.6696 ## 1339 Serbia Europe 1982 70.16200 9032824 15181.0927 ## 1340 Serbia Europe 1987 71.21800 9230783 15870.8785 ## 1341 Serbia Europe 1992 71.65900 9826397 9325.0682 ## 1342 Serbia Europe 1997 72.23200 10336594 7914.3203 ## 1343 Serbia Europe 2002 73.21300 10111559 7236.0753 ## 1344 Serbia Europe 2007 74.00200 10150265 9786.5347 ## 1345 Sierra Leone Africa 1952 30.33100 2143249 879.7877 ## 1346 Sierra Leone Africa 1957 31.57000 2295678 1004.4844 ## 1347 Sierra Leone Africa 1962 32.76700 2467895 1116.6399 ## 1348 Sierra Leone Africa 1967 34.11300 2662190 1206.0435 ## 1349 Sierra Leone Africa 1972 35.40000 2879013 1353.7598 ## 1350 Sierra Leone Africa 1977 36.78800 3140897 1348.2852 ## 1351 Sierra Leone Africa 1982 38.44500 3464522 1465.0108 ## 1352 Sierra Leone Africa 1987 40.00600 3868905 1294.4478 ## 1353 Sierra Leone Africa 1992 38.33300 4260884 1068.6963 ## 1354 Sierra Leone Africa 1997 39.89700 4578212 574.6482 ## 1355 Sierra Leone Africa 2002 41.01200 5359092 699.4897 ## 1356 Sierra Leone Africa 2007 42.56800 6144562 862.5408 ## 1357 Singapore Asia 1952 60.39600 1127000 2315.1382 ## 1358 Singapore Asia 1957 63.17900 1445929 2843.1044 ## 1359 Singapore Asia 1962 65.79800 1750200 3674.7356 ## 1360 Singapore Asia 1967 67.94600 1977600 4977.4185 ## 1361 Singapore Asia 1972 69.52100 2152400 8597.7562 ## 1362 Singapore Asia 1977 70.79500 2325300 11210.0895 ## 1363 Singapore Asia 1982 71.76000 2651869 15169.1611 ## 1364 Singapore Asia 1987 73.56000 2794552 18861.5308 ## 1365 Singapore Asia 1992 75.78800 3235865 24769.8912 ## 1366 Singapore Asia 1997 77.15800 3802309 33519.4766 ## 1367 Singapore Asia 2002 78.77000 4197776 36023.1054 ## 1368 Singapore Asia 2007 79.97200 4553009 47143.1796 ## 1369 Slovak Republic Europe 1952 64.36000 3558137 5074.6591 ## 1370 Slovak Republic Europe 1957 67.45000 3844277 6093.2630 ## 1371 Slovak Republic Europe 1962 70.33000 4237384 7481.1076 ## 1372 Slovak Republic Europe 1967 70.98000 4442238 8412.9024 ## 1373 Slovak Republic Europe 1972 70.35000 4593433 9674.1676 ## 1374 Slovak Republic Europe 1977 70.45000 4827803 10922.6640 ## 1375 Slovak Republic Europe 1982 70.80000 5048043 11348.5459 ## 1376 Slovak Republic Europe 1987 71.08000 5199318 12037.2676 ## 1377 Slovak Republic Europe 1992 71.38000 5302888 9498.4677 ## 1378 Slovak Republic Europe 1997 72.71000 5383010 12126.2306 ## 1379 Slovak Republic Europe 2002 73.80000 5410052 13638.7784 ## 1380 Slovak Republic Europe 2007 74.66300 5447502 18678.3144 ## 1381 Slovenia Europe 1952 65.57000 1489518 4215.0417 ## 1382 Slovenia Europe 1957 67.85000 1533070 5862.2766 ## 1383 Slovenia Europe 1962 69.15000 1582962 7402.3034 ## 1384 Slovenia Europe 1967 69.18000 1646912 9405.4894 ## 1385 Slovenia Europe 1972 69.82000 1694510 12383.4862 ## 1386 Slovenia Europe 1977 70.97000 1746919 15277.0302 ## 1387 Slovenia Europe 1982 71.06300 1861252 17866.7218 ## 1388 Slovenia Europe 1987 72.25000 1945870 18678.5349 ## 1389 Slovenia Europe 1992 73.64000 1999210 14214.7168 ## 1390 Slovenia Europe 1997 75.13000 2011612 17161.1073 ## 1391 Slovenia Europe 2002 76.66000 2011497 20660.0194 ## 1392 Slovenia Europe 2007 77.92600 2009245 25768.2576 ## 1393 Somalia Africa 1952 32.97800 2526994 1135.7498 ## 1394 Somalia Africa 1957 34.97700 2780415 1258.1474 ## 1395 Somalia Africa 1962 36.98100 3080153 1369.4883 ## 1396 Somalia Africa 1967 38.97700 3428839 1284.7332 ## 1397 Somalia Africa 1972 40.97300 3840161 1254.5761 ## 1398 Somalia Africa 1977 41.97400 4353666 1450.9925 ## 1399 Somalia Africa 1982 42.95500 5828892 1176.8070 ## 1400 Somalia Africa 1987 44.50100 6921858 1093.2450 ## 1401 Somalia Africa 1992 39.65800 6099799 926.9603 ## 1402 Somalia Africa 1997 43.79500 6633514 930.5964 ## 1403 Somalia Africa 2002 45.93600 7753310 882.0818 ## 1404 Somalia Africa 2007 48.15900 9118773 926.1411 ## 1405 South Africa Africa 1952 45.00900 14264935 4725.2955 ## 1406 South Africa Africa 1957 47.98500 16151549 5487.1042 ## 1407 South Africa Africa 1962 49.95100 18356657 5768.7297 ## 1408 South Africa Africa 1967 51.92700 20997321 7114.4780 ## 1409 South Africa Africa 1972 53.69600 23935810 7765.9626 ## 1410 South Africa Africa 1977 55.52700 27129932 8028.6514 ## 1411 South Africa Africa 1982 58.16100 31140029 8568.2662 ## 1412 South Africa Africa 1987 60.83400 35933379 7825.8234 ## 1413 South Africa Africa 1992 61.88800 39964159 7225.0693 ## 1414 South Africa Africa 1997 60.23600 42835005 7479.1882 ## 1415 South Africa Africa 2002 53.36500 44433622 7710.9464 ## 1416 South Africa Africa 2007 49.33900 43997828 9269.6578 ## 1417 Spain Europe 1952 64.94000 28549870 3834.0347 ## 1418 Spain Europe 1957 66.66000 29841614 4564.8024 ## 1419 Spain Europe 1962 69.69000 31158061 5693.8439 ## 1420 Spain Europe 1967 71.44000 32850275 7993.5123 ## 1421 Spain Europe 1972 73.06000 34513161 10638.7513 ## 1422 Spain Europe 1977 74.39000 36439000 13236.9212 ## 1423 Spain Europe 1982 76.30000 37983310 13926.1700 ## 1424 Spain Europe 1987 76.90000 38880702 15764.9831 ## 1425 Spain Europe 1992 77.57000 39549438 18603.0645 ## 1426 Spain Europe 1997 78.77000 39855442 20445.2990 ## 1427 Spain Europe 2002 79.78000 40152517 24835.4717 ## 1428 Spain Europe 2007 80.94100 40448191 28821.0637 ## 1429 Sri Lanka Asia 1952 57.59300 7982342 1083.5320 ## 1430 Sri Lanka Asia 1957 61.45600 9128546 1072.5466 ## 1431 Sri Lanka Asia 1962 62.19200 10421936 1074.4720 ## 1432 Sri Lanka Asia 1967 64.26600 11737396 1135.5143 ## 1433 Sri Lanka Asia 1972 65.04200 13016733 1213.3955 ## 1434 Sri Lanka Asia 1977 65.94900 14116836 1348.7757 ## 1435 Sri Lanka Asia 1982 68.75700 15410151 1648.0798 ## 1436 Sri Lanka Asia 1987 69.01100 16495304 1876.7668 ## 1437 Sri Lanka Asia 1992 70.37900 17587060 2153.7392 ## 1438 Sri Lanka Asia 1997 70.45700 18698655 2664.4773 ## 1439 Sri Lanka Asia 2002 70.81500 19576783 3015.3788 ## 1440 Sri Lanka Asia 2007 72.39600 20378239 3970.0954 ## 1441 Sudan Africa 1952 38.63500 8504667 1615.9911 ## 1442 Sudan Africa 1957 39.62400 9753392 1770.3371 ## 1443 Sudan Africa 1962 40.87000 11183227 1959.5938 ## 1444 Sudan Africa 1967 42.85800 12716129 1687.9976 ## 1445 Sudan Africa 1972 45.08300 14597019 1659.6528 ## 1446 Sudan Africa 1977 47.80000 17104986 2202.9884 ## 1447 Sudan Africa 1982 50.33800 20367053 1895.5441 ## 1448 Sudan Africa 1987 51.74400 24725960 1507.8192 ## 1449 Sudan Africa 1992 53.55600 28227588 1492.1970 ## 1450 Sudan Africa 1997 55.37300 32160729 1632.2108 ## 1451 Sudan Africa 2002 56.36900 37090298 1993.3983 ## 1452 Sudan Africa 2007 58.55600 42292929 2602.3950 ## 1453 Swaziland Africa 1952 41.40700 290243 1148.3766 ## 1454 Swaziland Africa 1957 43.42400 326741 1244.7084 ## 1455 Swaziland Africa 1962 44.99200 370006 1856.1821 ## 1456 Swaziland Africa 1967 46.63300 420690 2613.1017 ## 1457 Swaziland Africa 1972 49.55200 480105 3364.8366 ## 1458 Swaziland Africa 1977 52.53700 551425 3781.4106 ## 1459 Swaziland Africa 1982 55.56100 649901 3895.3840 ## 1460 Swaziland Africa 1987 57.67800 779348 3984.8398 ## 1461 Swaziland Africa 1992 58.47400 962344 3553.0224 ## 1462 Swaziland Africa 1997 54.28900 1054486 3876.7685 ## 1463 Swaziland Africa 2002 43.86900 1130269 4128.1169 ## 1464 Swaziland Africa 2007 39.61300 1133066 4513.4806 ## 1465 Sweden Europe 1952 71.86000 7124673 8527.8447 ## 1466 Sweden Europe 1957 72.49000 7363802 9911.8782 ## 1467 Sweden Europe 1962 73.37000 7561588 12329.4419 ## 1468 Sweden Europe 1967 74.16000 7867931 15258.2970 ## 1469 Sweden Europe 1972 74.72000 8122293 17832.0246 ## 1470 Sweden Europe 1977 75.44000 8251648 18855.7252 ## 1471 Sweden Europe 1982 76.42000 8325260 20667.3812 ## 1472 Sweden Europe 1987 77.19000 8421403 23586.9293 ## 1473 Sweden Europe 1992 78.16000 8718867 23880.0168 ## 1474 Sweden Europe 1997 79.39000 8897619 25266.5950 ## 1475 Sweden Europe 2002 80.04000 8954175 29341.6309 ## 1476 Sweden Europe 2007 80.88400 9031088 33859.7484 ## 1477 Switzerland Europe 1952 69.62000 4815000 14734.2327 ## 1478 Switzerland Europe 1957 70.56000 5126000 17909.4897 ## 1479 Switzerland Europe 1962 71.32000 5666000 20431.0927 ## 1480 Switzerland Europe 1967 72.77000 6063000 22966.1443 ## 1481 Switzerland Europe 1972 73.78000 6401400 27195.1130 ## 1482 Switzerland Europe 1977 75.39000 6316424 26982.2905 ## 1483 Switzerland Europe 1982 76.21000 6468126 28397.7151 ## 1484 Switzerland Europe 1987 77.41000 6649942 30281.7046 ## 1485 Switzerland Europe 1992 78.03000 6995447 31871.5303 ## 1486 Switzerland Europe 1997 79.37000 7193761 32135.3230 ## 1487 Switzerland Europe 2002 80.62000 7361757 34480.9577 ## 1488 Switzerland Europe 2007 81.70100 7554661 37506.4191 ## 1489 Syria Asia 1952 45.88300 3661549 1643.4854 ## 1490 Syria Asia 1957 48.28400 4149908 2117.2349 ## 1491 Syria Asia 1962 50.30500 4834621 2193.0371 ## 1492 Syria Asia 1967 53.65500 5680812 1881.9236 ## 1493 Syria Asia 1972 57.29600 6701172 2571.4230 ## 1494 Syria Asia 1977 61.19500 7932503 3195.4846 ## 1495 Syria Asia 1982 64.59000 9410494 3761.8377 ## 1496 Syria Asia 1987 66.97400 11242847 3116.7743 ## 1497 Syria Asia 1992 69.24900 13219062 3340.5428 ## 1498 Syria Asia 1997 71.52700 15081016 4014.2390 ## 1499 Syria Asia 2002 73.05300 17155814 4090.9253 ## 1500 Syria Asia 2007 74.14300 19314747 4184.5481 ## 1501 Taiwan Asia 1952 58.50000 8550362 1206.9479 ## 1502 Taiwan Asia 1957 62.40000 10164215 1507.8613 ## 1503 Taiwan Asia 1962 65.20000 11918938 1822.8790 ## 1504 Taiwan Asia 1967 67.50000 13648692 2643.8587 ## 1505 Taiwan Asia 1972 69.39000 15226039 4062.5239 ## 1506 Taiwan Asia 1977 70.59000 16785196 5596.5198 ## 1507 Taiwan Asia 1982 72.16000 18501390 7426.3548 ## 1508 Taiwan Asia 1987 73.40000 19757799 11054.5618 ## 1509 Taiwan Asia 1992 74.26000 20686918 15215.6579 ## 1510 Taiwan Asia 1997 75.25000 21628605 20206.8210 ## 1511 Taiwan Asia 2002 76.99000 22454239 23235.4233 ## 1512 Taiwan Asia 2007 78.40000 23174294 28718.2768 ## 1513 Tanzania Africa 1952 41.21500 8322925 716.6501 ## 1514 Tanzania Africa 1957 42.97400 9452826 698.5356 ## 1515 Tanzania Africa 1962 44.24600 10863958 722.0038 ## 1516 Tanzania Africa 1967 45.75700 12607312 848.2187 ## 1517 Tanzania Africa 1972 47.62000 14706593 915.9851 ## 1518 Tanzania Africa 1977 49.91900 17129565 962.4923 ## 1519 Tanzania Africa 1982 50.60800 19844382 874.2426 ## 1520 Tanzania Africa 1987 51.53500 23040630 831.8221 ## 1521 Tanzania Africa 1992 50.44000 26605473 825.6825 ## 1522 Tanzania Africa 1997 48.46600 30686889 789.1862 ## 1523 Tanzania Africa 2002 49.65100 34593779 899.0742 ## 1524 Tanzania Africa 2007 52.51700 38139640 1107.4822 ## 1525 Thailand Asia 1952 50.84800 21289402 757.7974 ## 1526 Thailand Asia 1957 53.63000 25041917 793.5774 ## 1527 Thailand Asia 1962 56.06100 29263397 1002.1992 ## 1528 Thailand Asia 1967 58.28500 34024249 1295.4607 ## 1529 Thailand Asia 1972 60.40500 39276153 1524.3589 ## 1530 Thailand Asia 1977 62.49400 44148285 1961.2246 ## 1531 Thailand Asia 1982 64.59700 48827160 2393.2198 ## 1532 Thailand Asia 1987 66.08400 52910342 2982.6538 ## 1533 Thailand Asia 1992 67.29800 56667095 4616.8965 ## 1534 Thailand Asia 1997 67.52100 60216677 5852.6255 ## 1535 Thailand Asia 2002 68.56400 62806748 5913.1875 ## 1536 Thailand Asia 2007 70.61600 65068149 7458.3963 ## 1537 Togo Africa 1952 38.59600 1219113 859.8087 ## 1538 Togo Africa 1957 41.20800 1357445 925.9083 ## 1539 Togo Africa 1962 43.92200 1528098 1067.5348 ## 1540 Togo Africa 1967 46.76900 1735550 1477.5968 ## 1541 Togo Africa 1972 49.75900 2056351 1649.6602 ## 1542 Togo Africa 1977 52.88700 2308582 1532.7770 ## 1543 Togo Africa 1982 55.47100 2644765 1344.5780 ## 1544 Togo Africa 1987 56.94100 3154264 1202.2014 ## 1545 Togo Africa 1992 58.06100 3747553 1034.2989 ## 1546 Togo Africa 1997 58.39000 4320890 982.2869 ## 1547 Togo Africa 2002 57.56100 4977378 886.2206 ## 1548 Togo Africa 2007 58.42000 5701579 882.9699 ## 1549 Trinidad and Tobago Americas 1952 59.10000 662850 3023.2719 ## 1550 Trinidad and Tobago Americas 1957 61.80000 764900 4100.3934 ## 1551 Trinidad and Tobago Americas 1962 64.90000 887498 4997.5240 ## 1552 Trinidad and Tobago Americas 1967 65.40000 960155 5621.3685 ## 1553 Trinidad and Tobago Americas 1972 65.90000 975199 6619.5514 ## 1554 Trinidad and Tobago Americas 1977 68.30000 1039009 7899.5542 ## 1555 Trinidad and Tobago Americas 1982 68.83200 1116479 9119.5286 ## 1556 Trinidad and Tobago Americas 1987 69.58200 1191336 7388.5978 ## 1557 Trinidad and Tobago Americas 1992 69.86200 1183669 7370.9909 ## 1558 Trinidad and Tobago Americas 1997 69.46500 1138101 8792.5731 ## 1559 Trinidad and Tobago Americas 2002 68.97600 1101832 11460.6002 ## 1560 Trinidad and Tobago Americas 2007 69.81900 1056608 18008.5092 ## 1561 Tunisia Africa 1952 44.60000 3647735 1468.4756 ## 1562 Tunisia Africa 1957 47.10000 3950849 1395.2325 ## 1563 Tunisia Africa 1962 49.57900 4286552 1660.3032 ## 1564 Tunisia Africa 1967 52.05300 4786986 1932.3602 ## 1565 Tunisia Africa 1972 55.60200 5303507 2753.2860 ## 1566 Tunisia Africa 1977 59.83700 6005061 3120.8768 ## 1567 Tunisia Africa 1982 64.04800 6734098 3560.2332 ## 1568 Tunisia Africa 1987 66.89400 7724976 3810.4193 ## 1569 Tunisia Africa 1992 70.00100 8523077 4332.7202 ## 1570 Tunisia Africa 1997 71.97300 9231669 4876.7986 ## 1571 Tunisia Africa 2002 73.04200 9770575 5722.8957 ## 1572 Tunisia Africa 2007 73.92300 10276158 7092.9230 ## 1573 Turkey Europe 1952 43.58500 22235677 1969.1010 ## 1574 Turkey Europe 1957 48.07900 25670939 2218.7543 ## 1575 Turkey Europe 1962 52.09800 29788695 2322.8699 ## 1576 Turkey Europe 1967 54.33600 33411317 2826.3564 ## 1577 Turkey Europe 1972 57.00500 37492953 3450.6964 ## 1578 Turkey Europe 1977 59.50700 42404033 4269.1223 ## 1579 Turkey Europe 1982 61.03600 47328791 4241.3563 ## 1580 Turkey Europe 1987 63.10800 52881328 5089.0437 ## 1581 Turkey Europe 1992 66.14600 58179144 5678.3483 ## 1582 Turkey Europe 1997 68.83500 63047647 6601.4299 ## 1583 Turkey Europe 2002 70.84500 67308928 6508.0857 ## 1584 Turkey Europe 2007 71.77700 71158647 8458.2764 ## 1585 Uganda Africa 1952 39.97800 5824797 734.7535 ## 1586 Uganda Africa 1957 42.57100 6675501 774.3711 ## 1587 Uganda Africa 1962 45.34400 7688797 767.2717 ## 1588 Uganda Africa 1967 48.05100 8900294 908.9185 ## 1589 Uganda Africa 1972 51.01600 10190285 950.7359 ## 1590 Uganda Africa 1977 50.35000 11457758 843.7331 ## 1591 Uganda Africa 1982 49.84900 12939400 682.2662 ## 1592 Uganda Africa 1987 51.50900 15283050 617.7244 ## 1593 Uganda Africa 1992 48.82500 18252190 644.1708 ## 1594 Uganda Africa 1997 44.57800 21210254 816.5591 ## 1595 Uganda Africa 2002 47.81300 24739869 927.7210 ## 1596 Uganda Africa 2007 51.54200 29170398 1056.3801 ## 1597 United Kingdom Europe 1952 69.18000 50430000 9979.5085 ## 1598 United Kingdom Europe 1957 70.42000 51430000 11283.1779 ## 1599 United Kingdom Europe 1962 70.76000 53292000 12477.1771 ## 1600 United Kingdom Europe 1967 71.36000 54959000 14142.8509 ## 1601 United Kingdom Europe 1972 72.01000 56079000 15895.1164 ## 1602 United Kingdom Europe 1977 72.76000 56179000 17428.7485 ## 1603 United Kingdom Europe 1982 74.04000 56339704 18232.4245 ## 1604 United Kingdom Europe 1987 75.00700 56981620 21664.7877 ## 1605 United Kingdom Europe 1992 76.42000 57866349 22705.0925 ## 1606 United Kingdom Europe 1997 77.21800 58808266 26074.5314 ## 1607 United Kingdom Europe 2002 78.47100 59912431 29478.9992 ## 1608 United Kingdom Europe 2007 79.42500 60776238 33203.2613 ## 1609 United States Americas 1952 68.44000 157553000 13990.4821 ## 1610 United States Americas 1957 69.49000 171984000 14847.1271 ## 1611 United States Americas 1962 70.21000 186538000 16173.1459 ## 1612 United States Americas 1967 70.76000 198712000 19530.3656 ## 1613 United States Americas 1972 71.34000 209896000 21806.0359 ## 1614 United States Americas 1977 73.38000 220239000 24072.6321 ## 1615 United States Americas 1982 74.65000 232187835 25009.5591 ## 1616 United States Americas 1987 75.02000 242803533 29884.3504 ## 1617 United States Americas 1992 76.09000 256894189 32003.9322 ## 1618 United States Americas 1997 76.81000 272911760 35767.4330 ## 1619 United States Americas 2002 77.31000 287675526 39097.0995 ## 1620 United States Americas 2007 78.24200 301139947 42951.6531 ## 1621 Uruguay Americas 1952 66.07100 2252965 5716.7667 ## 1622 Uruguay Americas 1957 67.04400 2424959 6150.7730 ## 1623 Uruguay Americas 1962 68.25300 2598466 5603.3577 ## 1624 Uruguay Americas 1967 68.46800 2748579 5444.6196 ## 1625 Uruguay Americas 1972 68.67300 2829526 5703.4089 ## 1626 Uruguay Americas 1977 69.48100 2873520 6504.3397 ## 1627 Uruguay Americas 1982 70.80500 2953997 6920.2231 ## 1628 Uruguay Americas 1987 71.91800 3045153 7452.3990 ## 1629 Uruguay Americas 1992 72.75200 3149262 8137.0048 ## 1630 Uruguay Americas 1997 74.22300 3262838 9230.2407 ## 1631 Uruguay Americas 2002 75.30700 3363085 7727.0020 ## 1632 Uruguay Americas 2007 76.38400 3447496 10611.4630 ## 1633 Venezuela Americas 1952 55.08800 5439568 7689.7998 ## 1634 Venezuela Americas 1957 57.90700 6702668 9802.4665 ## 1635 Venezuela Americas 1962 60.77000 8143375 8422.9742 ## 1636 Venezuela Americas 1967 63.47900 9709552 9541.4742 ## 1637 Venezuela Americas 1972 65.71200 11515649 10505.2597 ## 1638 Venezuela Americas 1977 67.45600 13503563 13143.9510 ## 1639 Venezuela Americas 1982 68.55700 15620766 11152.4101 ## 1640 Venezuela Americas 1987 70.19000 17910182 9883.5846 ## 1641 Venezuela Americas 1992 71.15000 20265563 10733.9263 ## 1642 Venezuela Americas 1997 72.14600 22374398 10165.4952 ## 1643 Venezuela Americas 2002 72.76600 24287670 8605.0478 ## 1644 Venezuela Americas 2007 73.74700 26084662 11415.8057 ## 1645 Vietnam Asia 1952 40.41200 26246839 605.0665 ## 1646 Vietnam Asia 1957 42.88700 28998543 676.2854 ## 1647 Vietnam Asia 1962 45.36300 33796140 772.0492 ## 1648 Vietnam Asia 1967 47.83800 39463910 637.1233 ## 1649 Vietnam Asia 1972 50.25400 44655014 699.5016 ## 1650 Vietnam Asia 1977 55.76400 50533506 713.5371 ## 1651 Vietnam Asia 1982 58.81600 56142181 707.2358 ## 1652 Vietnam Asia 1987 62.82000 62826491 820.7994 ## 1653 Vietnam Asia 1992 67.66200 69940728 989.0231 ## 1654 Vietnam Asia 1997 70.67200 76048996 1385.8968 ## 1655 Vietnam Asia 2002 73.01700 80908147 1764.4567 ## 1656 Vietnam Asia 2007 74.24900 85262356 2441.5764 ## 1657 West Bank and Gaza Asia 1952 43.16000 1030585 1515.5923 ## 1658 West Bank and Gaza Asia 1957 45.67100 1070439 1827.0677 ## 1659 West Bank and Gaza Asia 1962 48.12700 1133134 2198.9563 ## 1660 West Bank and Gaza Asia 1967 51.63100 1142636 2649.7150 ## 1661 West Bank and Gaza Asia 1972 56.53200 1089572 3133.4093 ## 1662 West Bank and Gaza Asia 1977 60.76500 1261091 3682.8315 ## 1663 West Bank and Gaza Asia 1982 64.40600 1425876 4336.0321 ## 1664 West Bank and Gaza Asia 1987 67.04600 1691210 5107.1974 ## 1665 West Bank and Gaza Asia 1992 69.71800 2104779 6017.6548 ## 1666 West Bank and Gaza Asia 1997 71.09600 2826046 7110.6676 ## 1667 West Bank and Gaza Asia 2002 72.37000 3389578 4515.4876 ## 1668 West Bank and Gaza Asia 2007 73.42200 4018332 3025.3498 ## 1669 Yemen, Rep. Asia 1952 32.54800 4963829 781.7176 ## 1670 Yemen, Rep. Asia 1957 33.97000 5498090 804.8305 ## 1671 Yemen, Rep. Asia 1962 35.18000 6120081 825.6232 ## 1672 Yemen, Rep. Asia 1967 36.98400 6740785 862.4421 ## 1673 Yemen, Rep. Asia 1972 39.84800 7407075 1265.0470 ## 1674 Yemen, Rep. Asia 1977 44.17500 8403990 1829.7652 ## 1675 Yemen, Rep. Asia 1982 49.11300 9657618 1977.5570 ## 1676 Yemen, Rep. Asia 1987 52.92200 11219340 1971.7415 ## 1677 Yemen, Rep. Asia 1992 55.59900 13367997 1879.4967 ## 1678 Yemen, Rep. Asia 1997 58.02000 15826497 2117.4845 ## 1679 Yemen, Rep. Asia 2002 60.30800 18701257 2234.8208 ## 1680 Yemen, Rep. Asia 2007 62.69800 22211743 2280.7699 ## 1681 Zambia Africa 1952 42.03800 2672000 1147.3888 ## 1682 Zambia Africa 1957 44.07700 3016000 1311.9568 ## 1683 Zambia Africa 1962 46.02300 3421000 1452.7258 ## 1684 Zambia Africa 1967 47.76800 3900000 1777.0773 ## 1685 Zambia Africa 1972 50.10700 4506497 1773.4983 ## 1686 Zambia Africa 1977 51.38600 5216550 1588.6883 ## 1687 Zambia Africa 1982 51.82100 6100407 1408.6786 ## 1688 Zambia Africa 1987 50.82100 7272406 1213.3151 ## 1689 Zambia Africa 1992 46.10000 8381163 1210.8846 ## 1690 Zambia Africa 1997 40.23800 9417789 1071.3538 ## 1691 Zambia Africa 2002 39.19300 10595811 1071.6139 ## 1692 Zambia Africa 2007 42.38400 11746035 1271.2116 ## 1693 Zimbabwe Africa 1952 48.45100 3080907 406.8841 ## 1694 Zimbabwe Africa 1957 50.46900 3646340 518.7643 ## 1695 Zimbabwe Africa 1962 52.35800 4277736 527.2722 ## 1696 Zimbabwe Africa 1967 53.99500 4995432 569.7951 ## 1697 Zimbabwe Africa 1972 55.63500 5861135 799.3622 ## 1698 Zimbabwe Africa 1977 57.67400 6642107 685.5877 ## 1699 Zimbabwe Africa 1982 60.36300 7636524 788.8550 ## 1700 Zimbabwe Africa 1987 62.35100 9216418 706.1573 ## 1701 Zimbabwe Africa 1992 60.37700 10704340 693.4208 ## 1702 Zimbabwe Africa 1997 46.80900 11404948 792.4500 ## 1703 Zimbabwe Africa 2002 39.98900 11926563 672.0386 ## 1704 Zimbabwe Africa 2007 43.48700 12311143 469.7093 ``` ] --- ## Dataframes: imprimir tibble .codefont[ ```r data_gapminder <- as_tibble(data_gapminder) # Pasamos nuevamente a tibble class(data_gapminder) ``` ``` ## [1] "tbl_df" "tbl" "data.frame" ``` ```r print(data_gapminder) ``` ``` ## # A tibble: 1,704 x 6 ## country continent year lifeExp pop gdpPercap ## <fct> <fct> <int> <dbl> <int> <dbl> ## 1 Afghanistan Asia 1952 28.8 8425333 779. ## 2 Afghanistan Asia 1957 30.3 9240934 821. ## 3 Afghanistan Asia 1962 32.0 10267083 853. ## 4 Afghanistan Asia 1967 34.0 11537966 836. ## 5 Afghanistan Asia 1972 36.1 13079460 740. ## 6 Afghanistan Asia 1977 38.4 14880372 786. ## 7 Afghanistan Asia 1982 39.9 12881816 978. ## 8 Afghanistan Asia 1987 40.8 13867957 852. ## 9 Afghanistan Asia 1992 41.7 16317921 649. ## 10 Afghanistan Asia 1997 41.8 22227415 635. ## # ... with 1,694 more rows ``` ] --- ## Tidy dataset - Hay muchas formas de estructurar un conjunto de datos. El enfoque tidy sugiere que cada variable sea una columna y cada observación sea una fila, por lo que cada valor tiene su propia celda: .center[ <img src="ima/tidy_data.png" width="1000px" /> ] .right[[Wichkham & Grolemund (2018)](https://r4ds.had.co.nz/tidy-data.html)] --- ## Nombres de variables Muchas veces los usamos datos que no están documentados de manera uniforme o apropiada, por ejemplo, con nombres dispares y propensos a errores en las columnas. [Janitor](https://garthtarr.github.io/meatR/janitor.html#catalog_of_janitor_functions) es un paquete orientado al estilo Tidyverse (aunque no pertenece) que facilita algunas funciones para limpiar y explorar datos. .codefont[ ```r ejemplo ``` ``` ## COLORES NombresCompletos edad_NUMERICA ## 1 Verde María S. 32 ## 2 Rojo Juan F. 23 ## 3 Azul Pedro A. 24 ``` ```r janitor::clean_names(ejemplo) ``` ``` ## colores nombres_completos edad_numerica ## 1 Verde María S. 32 ## 2 Rojo Juan F. 23 ## 3 Azul Pedro A. 24 ``` ] --- class: inverse, center, middle # Explorar datos --- ## Resumen de un dataframe .codefont[ ] .codefont[ ```r dim(data_gapminder) # Número de filas y columnas ``` ``` ## [1] 1704 6 ``` ```r names(data_gapminder) # Nombre de variables ``` ``` ## [1] "country" "continent" "year" "lifeExp" "pop" "gdpPercap" ``` ```r head(data_gapminder, 3) # Imprime primeras filas (3 en este caso) ``` ``` ## # A tibble: 3 x 6 ## country continent year lifeExp pop gdpPercap ## <fct> <fct> <int> <dbl> <int> <dbl> ## 1 Afghanistan Asia 1952 28.8 8425333 779. ## 2 Afghanistan Asia 1957 30.3 9240934 821. ## 3 Afghanistan Asia 1962 32.0 10267083 853. ``` ] --- ## Resumen de un dataframe .codefont[ ```r # Estructura del dataframe str(data_gapminder) ``` ``` ## tibble [1,704 x 6] (S3: tbl_df/tbl/data.frame) ## $ country : Factor w/ 142 levels "Afghanistan",..: 1 1 1 1 1 1 1 1 1 1 ... ## $ continent: Factor w/ 5 levels "Africa","Americas",..: 3 3 3 3 3 3 3 3 3 3 ... ## $ year : int [1:1704] 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 ... ## $ lifeExp : num [1:1704] 28.8 30.3 32 34 36.1 ... ## $ pop : int [1:1704] 8425333 9240934 10267083 11537966 13079460 14880372 12881816 13867957 16317921 22227415 ... ## $ gdpPercap: num [1:1704] 779 821 853 836 740 ... ``` ```r ncol(data_gapminder) # Numero de columnas ``` ``` ## [1] 6 ``` ```r nrow(data_gapminder) # Numero de filas ``` ``` ## [1] 1704 ``` ] --- ## Resumen de un dataframe ```r # Pequeño resumen de las variables: summary(data_gapminder) ``` ``` ## country continent year lifeExp ## Afghanistan: 12 Africa :624 Min. :1952 Min. :23.60 ## Albania : 12 Americas:300 1st Qu.:1966 1st Qu.:48.20 ## Algeria : 12 Asia :396 Median :1980 Median :60.71 ## Angola : 12 Europe :360 Mean :1980 Mean :59.47 ## Argentina : 12 Oceania : 24 3rd Qu.:1993 3rd Qu.:70.85 ## Australia : 12 Max. :2007 Max. :82.60 ## (Other) :1632 ## pop gdpPercap ## Min. :6.001e+04 Min. : 241.2 ## 1st Qu.:2.794e+06 1st Qu.: 1202.1 ## Median :7.024e+06 Median : 3531.8 ## Mean :2.960e+07 Mean : 7215.3 ## 3rd Qu.:1.959e+07 3rd Qu.: 9325.5 ## Max. :1.319e+09 Max. :113523.1 ## ``` --- ## Resumen de un dataframe Una de las funciones más utiles para resumir un dataframe es `glimpse()` del paquete dplyr o tidyverse. Es particularmente util debido a que permite un vistazo al nombre, tipo y primeros valores de .bold[todos] las variables de un dataframe. ```r # Resumen más completo: glimpse(gapminder) ``` ``` ## Rows: 1,704 ## Columns: 6 ## $ country <fct> "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", ~ ## $ continent <fct> Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, ~ ## $ year <int> 1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, ~ ## $ lifeExp <dbl> 28.801, 30.332, 31.997, 34.020, 36.088, 38.438, 39.854, 40.8~ ## $ pop <int> 8425333, 9240934, 10267083, 11537966, 13079460, 14880372, 12~ ## $ gdpPercap <dbl> 779.4453, 820.8530, 853.1007, 836.1971, 739.9811, 786.1134, ~ ``` --- ## Tablas En R Base la función para obtener frecuencias es `table()` junto con `prop.table()` y `addmargins()` .codefontchico[ ```r # Para obtener una tabla de frecuencias de una variable usamos la función # table() de R Base tabla_1 <- table(data_gapminder$continent) # Frecuencia simple tabla_1 ``` ``` ## ## Africa Americas Asia Europe Oceania ## 624 300 396 360 24 ``` ```r prop.table(tabla_1) # Proporciones ``` ``` ## ## Africa Americas Asia Europe Oceania ## 0.36619718 0.17605634 0.23239437 0.21126761 0.01408451 ``` ```r addmargins(tabla_1) # Totales ``` ``` ## ## Africa Americas Asia Europe Oceania Sum ## 624 300 396 360 24 1704 ``` ```r addmargins(prop.table(tabla_1)) # Proporciones y totales ``` ``` ## ## Africa Americas Asia Europe Oceania Sum ## 0.36619718 0.17605634 0.23239437 0.21126761 0.01408451 1.00000000 ``` ] --- ## Tablas Para obtener tablas que cruzen dos variables podemos nuevamente usar `table()` especificando dos variables. .codefont[ ```r tabla_2 <- table(data_gapminder$continent, data_gapminder$mercosur) tabla_2 ``` ``` ## ## 0 1 ## Africa 624 0 ## Americas 252 48 ## Asia 396 0 ## Europe 360 0 ## Oceania 24 0 ``` ```r prop.table(tabla_2) ``` ``` ## ## 0 1 ## Africa 0.36619718 0.00000000 ## Americas 0.14788732 0.02816901 ## Asia 0.23239437 0.00000000 ## Europe 0.21126761 0.00000000 ## Oceania 0.01408451 0.00000000 ``` ] --- ## Tablas .codefont[ ```r # Totales por columna o fila tabla_2 <- table(data_gapminder$continent, data_gapminder$mercosur) addmargins(tabla_2, 1) # Total por columna ``` ``` ## ## 0 1 ## Africa 624 0 ## Americas 252 48 ## Asia 396 0 ## Europe 360 0 ## Oceania 24 0 ## Sum 1656 48 ``` ```r addmargins(tabla_2, 2) # Total por fila ``` ``` ## ## 0 1 Sum ## Africa 624 0 624 ## Americas 252 48 300 ## Asia 396 0 396 ## Europe 360 0 360 ## Oceania 24 0 24 ``` ] --- ## Tablas .codefont[ ```r # Editar nombres de columnas tabla_2 <- table(data_gapminder$continent, data_gapminder$mercosur) tabla_2 ``` ``` ## ## 0 1 ## Africa 624 0 ## Americas 252 48 ## Asia 396 0 ## Europe 360 0 ## Oceania 24 0 ``` ```r colnames(tabla_2) <- c("No mercosur", "Mercosur") tabla_2 ``` ``` ## ## No mercosur Mercosur ## Africa 624 0 ## Americas 252 48 ## Asia 396 0 ## Europe 360 0 ## Oceania 24 0 ``` ]