Women Live Longer?

Setting up R Packages

library(tidyverse)
library(mosaic)
library(skimr)
library(ggformula)

Plot Theme

Show the Code

# https://stackoverflow.com/questions/74491138/ggplot-custom-fonts-not-working-in-quarto

# Chunk options
knitr::opts_chunk$set(
  fig.width = 7,
  fig.asp = 0.618, # Golden Ratio
  # out.width = "80%",
  fig.align = "center"
)
### Ggplot Theme
### https://rpubs.com/mclaire19/ggplot2-custom-themes

theme_custom <- function() {
  font <- "Roboto Condensed" # assign font family up front

  theme_classic(base_size = 14) %+replace% # replace elements we want to change

    theme(
      panel.grid.minor = element_blank(), # strip minor gridlines
      text = element_text(family = font),
      # text elements
      plot.title = element_text( # title
        family = font, # set font family
        size = 16, # set font size
        face = "bold", # bold typeface
        hjust = 0, # left align
        # vjust = 2                #raise slightly
        margin = margin(0, 0, 10, 0)
      ),
      plot.subtitle = element_text( # subtitle
        family = font, # font family
        size = 14, # font size
        hjust = 0,
        margin = margin(2, 0, 5, 0)
      ),
      plot.caption = element_text( # caption
        family = font, # font family
        size = 8, # font size
        hjust = 1
      ), # right align

      axis.title = element_text( # axis titles
        family = font, # font family
        size = 10 # font size
      ),
      axis.text = element_text( # axis text
        family = font, # axis family
        size = 8
      ) # font size
    )
}

# Set graph theme
theme_set(new = theme_custom())
#

Introduction

This dataset pertains to survival ages in different countries across the world. Women survival ages are compared to those of men.

Read the Data

Rows: 18,408
Columns: 7
$ Entity                                                               <chr> "…
$ Code                                                                 <chr> "…
$ Year                                                                 <dbl> 2…
$ `Life expectancy - Sex: female - Age: at birth - Variant: estimates` <dbl> N…
$ `Life expectancy - Sex: male - Age: at birth - Variant: estimates`   <dbl> N…
$ `Population - Sex: all - Age: all - Variant: estimates`              <dbl> N…
$ Continent                                                            <chr> "…

ABCDEFGHIJ0123456789

Entity <chr>	Code <chr>	Year <dbl>	Life expectancy - Sex: female - Age: at birth - Variant: estimates <dbl>
Abkhazia	OWID_ABK	2015	NA
Afghanistan	AFG	1950	28.4
Afghanistan	AFG	1951	28.6
Afghanistan	AFG	1952	29.1
Afghanistan	AFG	1953	29.6
Afghanistan	AFG	1954	29.9

Data Dictionary

Quantitative Variables

Write in.

Qualitative Variables

Write in.

Observations

Write in.

Analyse/Transform the Data

```{r}
#| label: data-preprocessing
#
# Write in your code here
# to prepare this data as shown below
# to generate the plot that follows
# Rename Variables if needed
# Change data to factors etc.
# Set up Counts, histograms etc
```

ABCDEFGHIJ0123456789

Entity <chr>	Code <chr>	Year <dbl>	LifeExpFemale <dbl>	LifeExpMale <dbl>	Population <dbl>	Continent <chr>
Afghanistan	AFG	2015	64.6	60.8	33753500	Asia
Albania	ALB	2015	81.2	76.4	2882482	Europe
Algeria	DZA	2015	76.8	74.5	39543148	Africa
American Samoa	ASM	2015	74.8	70.3	51391	Oceania
Andorra	AND	2015	85.4	80.6	71766	Europe
Angola	AGO	2015	63.1	58.2	28127724	Africa
Anguilla	AIA	2015	80.8	73.7	14554	North America
Antigua and Barbuda	ATG	2015	80.4	75.1	89958	North America
Argentina	ARG	2015	80.2	73.3	43257064	South America
Armenia	ARM	2015	78.8	69.6	2878598	Asia

Research Question

Note

Write in!! Look at the Chart!

Plot the Data

Task and Discussion

Complete the Data Dictionary.
Select and Transform the variables as shown.
Create the graphs shown and discuss the following questions:
- Identify the type of charts
- Identify the variables used for various geometrical aspects (x, y, fill…). Name the variables appropriately.
- What research activity might have been carried out to obtain the data graphed here? Provide some details.
- What pre-processing of the data was required to create the chart?
- What might be the Hypothesis / Research Question, based on the Chart?
- What does the dashed line in the chart represent?
- Write a 2-line story based on the chart, describing your inference/surprise.

Reference

In order to obtain that floating text note slope = 1 in the chart, you need to use gf_refine(annotate(....)). Look at the vignette/help here. https://ggplot2.tidyverse.org/reference/annotate.html