── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr 1.1.4 ✔ readr 2.1.5
✔ forcats 1.0.0 ✔ stringr 1.5.1
✔ ggplot2 3.5.1 ✔ tibble 3.2.1
✔ lubridate 1.9.3 ✔ tidyr 1.3.1
✔ purrr 1.0.2
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(plotly)
Warning: package 'plotly' was built under R version 4.4.3
Attaching package: 'plotly'
The following object is masked from 'package:ggplot2':
last_plot
The following object is masked from 'package:stats':
filter
The following object is masked from 'package:graphics':
layout
Rows: 5275 Columns: 10
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (5): iso2c, iso3c, country, region, income
dbl (5): year, gdp_percap, population, birth_rate, neonat_mortal_rate
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
head(nations)
# A tibble: 6 × 10
iso2c iso3c country year gdp_percap population birth_rate neonat_mortal_rate
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 AD AND Andorra 1996 NA 64291 10.9 2.8
2 AD AND Andorra 1994 NA 62707 10.9 3.2
3 AD AND Andorra 2003 NA 74783 10.3 2
4 AD AND Andorra 1990 NA 54511 11.9 4.3
5 AD AND Andorra 2009 NA 85474 9.9 1.7
6 AD AND Andorra 2011 NA 82326 NA 1.6
# ℹ 2 more variables: region <chr>, income <chr>
summary(nations)
iso2c iso3c country year
Length:5275 Length:5275 Length:5275 Min. :1990
Class :character Class :character Class :character 1st Qu.:1996
Mode :character Mode :character Mode :character Median :2002
Mean :2002
3rd Qu.:2008
Max. :2014
gdp_percap population birth_rate neonat_mortal_rate
Min. : 239.7 Min. :9.004e+03 Min. : 6.90 Min. : 0.70
1st Qu.: 2263.6 1st Qu.:7.175e+05 1st Qu.:13.40 1st Qu.: 6.70
Median : 6563.2 Median :5.303e+06 Median :21.60 Median :15.00
Mean : 12788.8 Mean :2.958e+07 Mean :24.16 Mean :19.40
3rd Qu.: 17195.0 3rd Qu.:1.757e+07 3rd Qu.:33.88 3rd Qu.:29.48
Max. :141968.1 Max. :1.364e+09 Max. :55.12 Max. :73.10
NA's :766 NA's :14 NA's :295 NA's :525
region income
Length:5275 Length:5275
Class :character Class :character
Mode :character Mode :character
nations_gdp <- nations |>mutate( gdp = gdp_percap*population/10^12)head(nations_gdp)
# A tibble: 6 × 11
iso2c iso3c country year gdp_percap population birth_rate neonat_mortal_rate
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 AD AND Andorra 1996 NA 64291 10.9 2.8
2 AD AND Andorra 1994 NA 62707 10.9 3.2
3 AD AND Andorra 2003 NA 74783 10.3 2
4 AD AND Andorra 1990 NA 54511 11.9 4.3
5 AD AND Andorra 2009 NA 85474 9.9 1.7
6 AD AND Andorra 2011 NA 82326 NA 1.6
# ℹ 3 more variables: region <chr>, income <chr>, gdp <dbl>
# A tibble: 6 × 11
iso2c iso3c country year gdp_percap population birth_rate neonat_mortal_rate
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 BR BRA Brazil 2002 9468. 181045592 20.0 13.9
2 BR BRA Brazil 1995 8029. 162755054 22.0 20
3 BR BRA Brazil 1996 8227. 165303155 21.8 19.3
4 BR BRA Brazil 1993 7221. 157812220 22.6 21.5
5 BR BRA Brazil 1994 7649. 160260508 22.2 20.7
6 BR BRA Brazil 2001 9182. 178419396 20.5 14.9
# ℹ 3 more variables: region <chr>, income <chr>, gdp <dbl>
p1 <-ggplot(nations_p1, aes(x = year, y = gdp, color = country)) +labs(title ="GDP of Top Oil Producing Countries in Latin America, 1990-2014",x ="Year", y ="GDP ($ trillion)") +theme_minimal(base_size =12) +geom_line() +geom_point() +scale_color_brewer(palette ="Set1")
# A tibble: 6 × 11
# Groups: region, year [6]
iso2c iso3c country year gdp_percap population birth_rate neonat_mortal_rate
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 AD AND Andorra 1996 NA 64291 10.9 2.8
2 AD AND Andorra 1994 NA 62707 10.9 3.2
3 AD AND Andorra 2003 NA 74783 10.3 2
4 AD AND Andorra 1990 NA 54511 11.9 4.3
5 AD AND Andorra 2009 NA 85474 9.9 1.7
6 AD AND Andorra 2011 NA 82326 NA 1.6
# ℹ 3 more variables: region <chr>, income <chr>, gdp <dbl>
`summarise()` has grouped output by 'region'. You can override using the
`.groups` argument.
head(nations_p2GDP)
# A tibble: 6 × 3
# Groups: region [1]
region year sum_GDP
<chr> <dbl> <dbl>
1 East Asia & Pacific 1990 5.52
2 East Asia & Pacific 1991 6.03
3 East Asia & Pacific 1992 6.50
4 East Asia & Pacific 1993 7.04
5 East Asia & Pacific 1994 7.64
6 East Asia & Pacific 1995 8.29
p2 <-ggplot(nations_p2GDP, aes(x = year, y = sum_GDP, fill = region, color = region)) +labs(title ="GDP by World Bank Regions, 1990-2014",x ="Year", y ="GDP ($ trillion)") +theme_minimal(base_size =12) +geom_area(alpha=0.6 , size=0.5, color="white") +scale_fill_brewer(palette ="Set2")
Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.
