Week-11-VA

Week-11 VA Dhriti 2023-03-29 library (gapminder) ## Warning: package 'gapminder' was built under R version 4.2.2 library (dplyr) ## Warning: package 'dplyr' was built under R version 4.2.2 ## ## 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 gap77 <- gapminder %>% filter (year == 1977 ) fit <- lm (lifeExp ~ log (gdpPercap), data = gap77) summary (fit) ## ## Call: ## lm(formula = lifeExp ~ log(gdpPercap), data = gap77) ## ## Residuals: ## Min 1Q Median 3Q Max ## -19.8647 -3.7210 0.9703 4.1957 16.8197 ## ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) ## (Intercept) -2.7389 3.8043 -0.72 0.473 ## log(gdpPercap) 7.5490 0.4561 16.55 <2e-16 *** ## --- ## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 ## ## Residual standard error: 6.552 on 140 degrees of freedom ## Multiple R-squared: 0.6618, Adjusted R-squared: 0.6594 ## F-statistic: 274 on 1 and 140 DF, p-value: < 2.2e-16 library (tidyr) ## Warning: package 'tidyr' was built under R version 4.2.2

out_le <- gapminder %>% group_by (continent, year) %>% nest () out_le ## # A tibble: 60 × 3 ## # Groups: continent, year [60] ## continent year data ## <fct> <int> <list> ## 1 Asia 1952 <tibble [33 × 4]> ## 2 Asia 1957 <tibble [33 × 4]> ## 3 Asia 1962 <tibble [33 × 4]> ## 4 Asia 1967 <tibble [33 × 4]> ## 5 Asia 1972 <tibble [33 × 4]> ## 6 Asia 1977 <tibble [33 × 4]> ## 7 Asia 1982 <tibble [33 × 4]> ## 8 Asia 1987 <tibble [33 × 4]> ## 9 Asia 1992 <tibble [33 × 4]> ## 10 Asia 1997 <tibble [33 × 4]> ## # ... with 50 more rows out_le %>% filter (continent == "Europe" & year == 1977 ) %>% unnest () ## Warning: `cols` is now required when using unnest(). ## Please use `cols = c(data)` ## # A tibble: 30 × 6 ## # Groups: continent, year [1] ## continent year country lifeExp pop gdpPercap ## <fct> <int> <fct> <dbl> <int> <dbl> ## 1 Europe 1977 Albania 68.9 2509048 3533. ## 2 Europe 1977 Austria 72.2 7568430 19749. ## 3 Europe 1977 Belgium 72.8 9821800 19118. ## 4 Europe 1977 Bosnia and Herzegovina 69.9 4086000 3528. ## 5 Europe 1977 Bulgaria 70.8 8797022 7612. ## 6 Europe 1977 Croatia 70.6 4318673 11305. ## 7 Europe 1977 Czech Republic 70.7 10161915 14800. ## 8 Europe 1977 Denmark 74.7 5088419 20423. ## 9 Europe 1977 Finland 72.5 4738902 15605.

## 10 Europe 1977 France 73.8 53165019 18293. ## # ... with 20 more rows fit_ols <- function (df) { lm (lifeExp ~ log (gdpPercap), data = df) } library (ggplot2) ## Warning: package 'ggplot2' was built under R version 4.2.2 library (purrr) ## Warning: package 'purrr' was built under R version 4.2.2 library (socviz) library (gapminder) out_le <- gapminder %>% group_by (continent, year) %>% nest () %>% mutate ( model = map (data, fit_ols)) out_le ## # A tibble: 60 × 4 ## # Groups: continent, year [60] ## continent year data model ## <fct> <int> <list> <list> ## 1 Asia 1952 <tibble [33 × 4]> <lm> ## 2 Asia 1957 <tibble [33 × 4]> <lm> ## 3 Asia 1962 <tibble [33 × 4]> <lm> ## 4 Asia 1967 <tibble [33 × 4]> <lm> ## 5 Asia 1972 <tibble [33 × 4]> <lm> ## 6 Asia 1977 <tibble [33 × 4]> <lm> ## 7 Asia 1982 <tibble [33 × 4]> <lm> ## 8 Asia 1987 <tibble [33 × 4]> <lm> ## 9 Asia 1992 <tibble [33 × 4]> <lm> ## 10 Asia 1997 <tibble [33 × 4]> <lm> ## # ... with 50 more rows fit_ols <- function (df) { lm (lifeExp ~ log (gdpPercap), data = df) } fit_ols ## function(df) { ## lm(lifeExp ~ log(gdpPercap), data = df) ## } fit_ols ( df = gapminder)

## ## Call: ## lm(formula = lifeExp ~ log(gdpPercap), data = df) ## ## Coefficients: ## (Intercept) log(gdpPercap) ## -9.101 8.405 library (tidyverse) ## Warning: package 'tidyverse' was built under R version 4.2.2 ## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ── ## ✔ tibble 3.1.8 ✔ stringr 1.4.1 ## ✔ readr 2.1.3 ✔ forcats 0.5.2 ## Warning: package 'tibble' was built under R version 4.2.2 ## Warning: package 'readr' was built under R version 4.2.2 ## Warning: package 'stringr' was built under R version 4.2.2 ## Warning: package 'forcats' was built under R version 4.2.2 ## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ── ## ✖ dplyr::filter() masks stats::filter() ## ✖ dplyr::lag() masks stats::lag() library (dplyr) library (broom) ## Warning: package 'broom' was built under R version 4.2.2 out_tidy <- gapminder %>% group_by (continent, year) %>% nest () %>% mutate ( model = map (data, fit_ols), tidied = map (model, tidy)) %>% unnest (tidied, .drop = TRUE ) %>% filter (term %nin% "(Intercept)" & continent %nin% "Oceania" ) ## Warning: The `.drop` argument of `unnest()` is deprecated as of tidyr 1.0.0. ## All list-columns are now preserved. ℹ out_tidy ## # A tibble: 48 × 9 ## # Groups: continent, year [48] ## continent year data model term estim...¹

std.e...² stati...³ p.value ## <fct> <int> <list> <lis> <chr> <dbl> <dbl> <dbl> <dbl> ## 1 Asia 1952 <tibble [33 × 4]> <lm> log(... 4.16 1.25 3.33 2.28e-3 ## 2 Asia 1957 <tibble [33 × 4]> <lm> log(... 4.17 1.28 3.26 2.71e-3 ## 3 Asia 1962 <tibble [33 × 4]> <lm> log(... 4.59 1.24 3.72 7.94e-4 ## 4 Asia 1967 <tibble [33 × 4]> <lm> log(... 4.50 1.15 3.90 4.77e-4 ## 5 Asia 1972 <tibble [33 × 4]> <lm> log(... 4.44 1.01 4.41 1.16e-4 ## 6 Asia 1977 <tibble [33 × 4]> <lm> log(... 4.87 1.03 4.75 4.42e-5 ## 7 Asia 1982 <tibble [33 × 4]> <lm> log(... 4.78 0.852 5.61 3.77e-6 ## 8 Asia 1987 <tibble [33 × 4]> <lm> log(... 5.17 0.727 7.12 5.31e-8 ## 9 Asia 1992 <tibble [33 × 4]> <lm> log(... 5.09 0.649 7.84 7.60e-9 ## 10 Asia 1997 <tibble [33 × 4]> <lm> log(... 5.11 0.628 8.15 3.35e-9 ## # ... with 38 more rows, and abbreviated variable names ¹ estimate, ²std.error, ## # ³statistic p <- ggplot ( data = out_tidy, mapping = aes ( x = year, y = estimate, ymin = estimate - 2 * std.error, ymax = estimate + 2 * std.error, group = continent, color = continent)) p + geom_pointrange ( position = position_dodge ( width = 1 )) + scale_x_continuous ( breaks = unique (gapminder $ year)) + theme ( legend.position = "top" ) + labs ( x = "Year" , y = "Estimate" , color = "Continent" )