library(tidyverse)
## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --
## v ggplot2 3.3.5 v purrr 0.3.4
## v tibble 3.1.4 v dplyr 1.0.7
## v tidyr 1.1.3 v stringr 1.4.0
## v readr 2.0.1 v forcats 0.5.1
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
library(gapminder)
## Warning: package 'gapminder' was built under R version 4.1.2
data(gapminder)
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
#population VS time of germany
gapminder_ger<-filter(gapminder, country == 'Germany')
ggplot(gapminder_ger) + geom_point(mapping = aes(x = pop, y = year))
ggplot(gapminder_ger) + geom_line(mapping = aes(x = pop, y = year))
#Create same plots for your own country.
gapminder_Ind<-filter(gapminder, country == 'India')
ggplot(gapminder_Ind) + geom_point(mapping = aes(x = pop, y = year))
ggplot(gapminder_Ind) + geom_line(mapping = aes(x = pop, y = year))
#Make a histogram of for life expectancy values for year 2007. Do not forget that you need to subset your dataset
gapminder_2007 <- gapminder %>%
filter(year == 2007)
p = ggplot(gapminder_2007, aes(x=lifeExp, fill=year)) +
geom_histogram(position="identity", colour="grey40", alpha=0.2, bins = 10)
p
#Create a facets of histograms life expectancy values by year
p = ggplot(gapminder, aes(x=lifeExp, fill=country)) +
geom_histogram(position="identity", colour="grey40", alpha=0.2, bins = 10)+
facet_grid(. ~year )
p
#Create a line plot of life expectancy values for the countries. In the aesthetics, you need to set x,y and by
ggplot(gapminder) +
geom_line(aes(x = lifeExp, y = country)) +
scale_x_log10()
#Create a line plot of life expectancy values for the countries. Set the color for the continent values In the aesthetics, you need to set x,y, by and color.
ggplot(data = gapminder) +
geom_line(mapping = aes(x =lifeExp , y = country, color = continent, size = pop)) +
scale_x_log10()
#Create a line plot of life expectancy values for the countries. create the facets for the continent values
ggplot(gapminder_2007) +
geom_line(aes(x = lifeExp, y = country, color = year, size = pop)) +
scale_x_log10() +
facet_wrap(~ continent)
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
