In ukgovdatascience/orgsurveyr: Visualising and Analysing Organisation Data As Tidy Networks

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width=5.5,
  fig.height=4
)
library(tidygraph, quietly = TRUE)
library(ggraph, quietly = TRUE)
library(tibble, quietly = TRUE)
library(purrr, quietly = TRUE)
library(dplyr, quietly = TRUE)
library(orgsurveyr, quietly = TRUE)

Introduction

This vignette introduces the general functionality of the orgsurveyr package and how it can be used to analyse and visualise organisational data. For a more detailed explanation of the ggraph and tidygraph packages are being used 'under the hood' please see the Organisations With ggraph vignette.

Example

Simulating and plotting an organisation

A realistic organisation can be simulated and plotted:

set.seed(1236)
tg2 <- create_realistic_org(n_children = 4, max_depth = 3, prob=0.3)
plot_org(tg2)

Organisation data structure

The orgsurveyr package uses the tidygraph and ggraph packages under the hood to provide functionality for HR analysts to easily analyse organisational data. The organisation simulated above is a tbl_graph object:

tg2

This is made up of two data frames, one for the nodes (organisational units) and another for the edges (the connections between the units). Importantly, note that the from/to columns in the edge data relate to the row number of the node and NOT the value of the unit_id column.

Although the convenience plot_org function is provided, users are advised to explore the full functionality of the ggraph package for their plots.

Simulating individuals within an organisation

Individual level data also be simulated first by simulating the number of individuals in unit:

tg3 <- simulate_unit_size(tg2)
tg3

Followed by simulating the individuals and any additional variables. The commands can be piped as per tidyverse convention:

tg3_individuals_df <- tg3 %>% 
  simulate_individuals_df() %>%
  mutate(test_var2 = purrr::map_dbl(individual_id, ~rnorm(1, 20,3)))
tg3_individuals_df

Summarising individual level data

The individual data can be aggregated at the unit level. This can be either be just those individuals associated with an organisational unit or (more usefully) a cumulative aggregation involving all individuals that are part of that unit and any units below it in the organisation:

summary_df <- calc_summary_df(tg=tg3, df=tg3_individuals_df, 
                              selected_vars=c('test_var', 'test_var2'), is_cumulative=TRUE)
summary_df

If the is_cumulative flag is set to FALSE then the raw individual to unit mappings are used from the individual data:

tg3_individuals_df %>%
  select(unit_id, individual_id) %>%
  count(unit_id)

If the is_cumulative flag is set to TRUE then the raw individual to unit mappings are generated from the generate_cumulative_mapping function leading to much higher group sizes:

generate_cumulative_mapping(tg3, tg3_individuals_df) %>%
  count(parent_id)

Plotting aggregated data

Finally the aggregated data can be plotted as a dendrogram:

plot_org(tg3, fill_var = 'test_var', df = summary_df)

Or some other representation, such as a starburst plot, using generic tidygraph and ggraph functionality:

plot_data <- tg3_individuals_df %>% 
  inner_join(generate_cumulative_mapping(tg3, tg3_individuals_df), by='individual_id') %>%
  group_by(parent_id) %>%
  summarise(test_var = mean(test_var), 
            cumulative_group_size = n()) 

plot_tg <- tg3 %>%
  activate(nodes) %>%
  inner_join(plot_data, by=c('unit_id'='parent_id'))

ggraph(plot_tg, 'partition', circular = TRUE) + 
  geom_node_arc_bar(aes(fill = test_var), size = 0.25) +
  geom_node_text(aes(label = cumulative_group_size), color = 'white', size = 3) + 
  theme_bw()

Interactive visualisations

The following shiny apps are included in the orgsurveyr package:

• test_viz - simulates an organisation with different characteristics
• orgviz - permits visualisation of either simulated or real data as long as the data formats described in orgsurveyr-data-formats as used.

Further information on using these is available in the Package Setup Vignette but to visualise the examples above we can just type the following command:

orgviz(tg=tg3, df=summary_df)

Further reading/viewing

• Organisations With ggraph vignette
• Package Setup Vignette
• Data Imaginist - Thomas Lin Pedersen's blog
• 'Tidying up your network analysis with tidygraph and ggraph': RStudio::conf presentation from Thomas Lin Pedersen
• useR 2018 Interview with Thomas Lin Pedersen

ukgovdatascience/orgsurveyr documentation built on May 4, 2019, 7:41 p.m.