Gender at the Work Place

Setting up R Packages

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

Plot Theme and Fonts

```{r}
#| code-fold: true
#| message: false
#| warning: false

knitr::opts_chunk$set(
  fig.width = 7,
  fig.asp = 0.618, # Golden Ratio
  # out.width = "80%",
  fig.align = "center"
)
##
## https://stackoverflow.com/questions/36476751/associate-a-color-palette-with-ggplot2-theme
##
my_colours <- c("#fd7f6f", "#7eb0d5", "#b2e061", "#bd7ebe", "#ffb55a", "#ffee65", "#beb9db", "#fdcce5", "#8bd3c7")
my_pastels <- c("#66C5CC", "#F6CF71", "#F89C74", "#DCB0F2", "#87C55F", "#9EB9F3", "#FE88B1", "#C9DB74", "#8BE0A4", "#B497E7", "#D3B484", "#B3B3B3")
my_greys <- c("#000000", "#333333", "#666666", "#999999", "#cccccc")
my_vivids <- c("#E58606", "#5D69B1", "#52BCA3", "#99C945", "#CC61B0", "#24796C", "#DAA51B", "#2F8AC4", "#764E9F", "#ED645A", "#CC3A8E", "#A5AA99")

my_bolds <- c("#7F3C8D", "#11A579", "#3969AC", "#F2B701", "#E73F74", "#80BA5A", "#E68310", "#008695", "#CF1C90", "#f97b72", "#4b4b8f", "#A5AA99")

library(systemfonts)
library(showtext)
## Clean the slate
systemfonts::clear_local_fonts()
systemfonts::clear_registry()
##
showtext_opts(dpi = 96) # set DPI for showtext
sysfonts::font_add(
  family = "Alegreya",
  regular = "../../../../../../fonts/Alegreya-Regular.ttf",
  bold = "../../../../../../fonts/Alegreya-Bold.ttf",
  italic = "../../../../../../fonts/Alegreya-Italic.ttf",
  bolditalic = "../../../../../../fonts/Alegreya-BoldItalic.ttf"
)

sysfonts::font_add(
  family = "Roboto Condensed",
  regular = "../../../../../../fonts/RobotoCondensed-Regular.ttf",
  bold = "../../../../../../fonts/RobotoCondensed-Bold.ttf",
  italic = "../../../../../../fonts/RobotoCondensed-Italic.ttf",
  bolditalic = "../../../../../../fonts/RobotoCondensed-BoldItalic.ttf"
)
showtext_auto(enable = TRUE) # enable showtext
##
theme_custom <- function() {
  font <- "Alegreya" # assign font family up front

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

    theme(
      text = element_text(family = font), # set base font family

      # text elements
      plot.title = element_text( # title
        family = font, # set font family
        size = 24, # set font size
        face = "bold", # bold typeface
        hjust = 0, # left align
        margin = margin(t = 5, r = 0, b = 5, l = 0)
      ), # margin
      plot.title.position = "plot",
      plot.subtitle = element_text( # subtitle
        family = font, # font family
        size = 14, # font size
        hjust = 0, # left align
        margin = margin(t = 5, r = 0, b = 10, l = 0)
      ), # margin

      plot.caption = element_text( # caption
        family = font, # font family
        size = 9, # font size
        hjust = 1
      ), # right align

      plot.caption.position = "plot", # right align

      plot.background = element_rect(fill = "navajowhite"),
      axis.title = element_text( # axis titles
        family = "Roboto Condensed", # font family
        size = 12
      ), # font size

      axis.text = element_text( # axis text
        family = "Roboto Condensed", # font family
        size = 9
      ), # font size

      axis.text.x = element_text( # margin for axis text
        margin = margin(5, b = 10)
      )

      # since the legend often requires manual tweaking
      # based on plot content, don't define it here
    )
}

## Use available fonts in ggplot text geoms too!
update_geom_defaults(geom = "text", new = list(
  family = "Roboto Condensed",
  face = "plain",
  size = 3.5,
  color = "#2b2b2b"
))

## Set the theme
theme_set(new = theme_custom())
```

Introduction

This is a dataset pertaining to gender and compensation at the workplace, modified for ease of analysis and plotting.

Data

[1] 2088   12

ABCDEFGHIJ0123456789

year <dbl>	occupation <chr>	major_category <chr>
2013	Chief executives	Management, Business, and Financial
2013	General and operations managers	Management, Business, and Financial
2013	Legislators	Management, Business, and Financial
2013	Advertising and promotions managers	Management, Business, and Financial
2013	Marketing and sales managers	Management, Business, and Financial
2013	Public relations and fundraising managers	Management, Business, and Financial
2013	Administrative services managers	Management, Business, and Financial
2013	Computer and information systems managers	Management, Business, and Financial
2013	Financial managers	Management, Business, and Financial
2013	Compensation and benefits managers	Management, Business, and Financial

Next

123456

...

209

Previous

1-10 of 2,088 rows | 1-3 of 12 columns

ABCDEFGHIJ0123456789

major_category <chr>	n <int>
Computer, Engineering, and Science	236
Education, Legal, Community Service, Arts, and Media	168
Healthcare Practitioners and Technical	128
Management, Business, and Financial	232
Natural Resources, Construction, and Maintenance	328
Production, Transportation, and Material Moving	444
Sales and Office	280
Service	272

8 rows

ABCDEFGHIJ0123456789

minor_category <chr>	n <int>
Architecture and Engineering	84
Arts, Design, Entertainment, Sports, and Media	72
Building and Grounds Cleaning and Maintenance	24
Business and Financial Operations	112
Community and Social Service	32
Computer and mathematical	64
Construction and Extraction	152
Education, Training, and Library	44
Farming, Fishing, and Forestry	32
Food Preparation and Serving Related	52

Next

123

Previous

1-10 of 23 rows

ABCDEFGHIJ0123456789

occupation <chr>	n <int>
Accountants and auditors	4
Actors	4
Actuaries	4
Adhesive bonding machine operators and tenders	4
Administrative services managers	4
Advertising and promotions managers	4
Advertising sales agents	4
Aerospace engineers	4
Agents and business managers of artists, performers, and athletes	4
Agricultural and food science technicians	4

Next

123456

...

53

Previous

1-10 of 522 rows

Download the Modified data

Data Dictionary

Quantitative Variables

Write in.

Qualitative Variables

Write in.

Observations

Write in.

Plot the Data

Task and Discussion

Complete the Data Dictionary. Create the graph shown and discuss the following questions:

• What kind of chart is used in the figure?
• What geometries have been used and to which variables have these geometries been mapped?
• Based on this graph, do you think gender plays a role in salaries? What is the trend you see?
• If SALARY, NO_OF_WORKERS, GENDER, OCCUPATION were available in the original dataset, what pre-processing would have been necessary to obtain this plot?