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This is data of gapminder for teaching

library(gapminder)
gapminder

## # A tibble: 1,704 × 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.
## # ℹ 1,694 more rows

Selecting data

In this section selecting data of year 1980 onwards

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

gapminder%>%
filter (year > 1980)

## # A tibble: 852 × 6
##    country     continent  year lifeExp      pop gdpPercap
##    <fct>       <fct>     <int>   <dbl>    <int>     <dbl>
##  1 Afghanistan Asia       1982    39.9 12881816      978.
##  2 Afghanistan Asia       1987    40.8 13867957      852.
##  3 Afghanistan Asia       1992    41.7 16317921      649.
##  4 Afghanistan Asia       1997    41.8 22227415      635.
##  5 Afghanistan Asia       2002    42.1 25268405      727.
##  6 Afghanistan Asia       2007    43.8 31889923      975.
##  7 Albania     Europe     1982    70.4  2780097     3631.
##  8 Albania     Europe     1987    72    3075321     3739.
##  9 Albania     Europe     1992    71.6  3326498     2497.
## 10 Albania     Europe     1997    73.0  3428038     3193.
## # ℹ 842 more rows