Hands-On_Ex05

pacman::p_load(igraph, tidygraph, ggraph, 
               visNetwork, lubridate, clock,
               tidyverse, graphlayouts)
GAStech_nodes <- read_csv("data/GAStech_email_node.csv")
Rows: 54 Columns: 4
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (3): label, Department, Title
dbl (1): id

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.
GAStech_edges <- read_csv("data/GAStech_email_edge-v2.csv")
Rows: 9063 Columns: 8
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr  (5): SentDate, Subject, MainSubject, sourceLabel, targetLabel
dbl  (2): source, target
time (1): SentTime

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.
glimpse(GAStech_edges)
Rows: 9,063
Columns: 8
$ source      <dbl> 43, 43, 44, 44, 44, 44, 44, 44, 44, 44, 44, 44, 26, 26, 26…
$ target      <dbl> 41, 40, 51, 52, 53, 45, 44, 46, 48, 49, 47, 54, 27, 28, 29…
$ SentDate    <chr> "6/1/2014", "6/1/2014", "6/1/2014", "6/1/2014", "6/1/2014"…
$ SentTime    <time> 08:39:00, 08:39:00, 08:58:00, 08:58:00, 08:58:00, 08:58:0…
$ Subject     <chr> "GT-SeismicProcessorPro Bug Report", "GT-SeismicProcessorP…
$ MainSubject <chr> "Work related", "Work related", "Work related", "Work rela…
$ sourceLabel <chr> "Sven.Flecha", "Sven.Flecha", "Kanon.Herrero", "Kanon.Herr…
$ targetLabel <chr> "Isak.Baza", "Lucas.Alcazar", "Felix.Resumir", "Hideki.Coc…
GAStech_edges <- GAStech_edges %>%
  mutate(SendDate = dmy(SentDate)) %>%
  mutate(Weekday = wday(SentDate,
                        label = TRUE,
                        abbr = FALSE))
GAStech_edges_aggregated <- GAStech_edges %>%
  filter(MainSubject == "Work related") %>%
  group_by(source, target, Weekday) %>%
    summarise(Weight = n()) %>%
  filter(source!=target) %>%
  filter(Weight > 1) %>%
  ungroup()
`summarise()` has grouped output by 'source', 'target'. You can override using
the `.groups` argument.
GAStech_edges_aggregated
# A tibble: 1,372 × 4
   source target Weekday   Weight
    <dbl>  <dbl> <ord>      <int>
 1      1      2 Sunday         5
 2      1      2 Monday         2
 3      1      2 Tuesday        3
 4      1      2 Wednesday      4
 5      1      2 Friday         6
 6      1      3 Sunday         5
 7      1      3 Monday         2
 8      1      3 Tuesday        3
 9      1      3 Wednesday      4
10      1      3 Friday         6
# ℹ 1,362 more rows
glimpse(GAStech_edges_aggregated)
Rows: 1,372
Columns: 4
$ source  <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
$ target  <dbl> 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 6,…
$ Weekday <ord> Sunday, Monday, Tuesday, Wednesday, Friday, Sunday, Monday, Tu…
$ Weight  <int> 5, 2, 3, 4, 6, 5, 2, 3, 4, 6, 5, 2, 3, 4, 6, 5, 2, 3, 4, 6, 5,…
GAStech_graph <- tbl_graph(nodes = GAStech_nodes,
                           edges = GAStech_edges_aggregated, 
                           directed = TRUE)
GAStech_graph
# A tbl_graph: 54 nodes and 1372 edges
#
# A directed multigraph with 1 component
#
# A tibble: 54 × 4
     id label               Department     Title                                
  <dbl> <chr>               <chr>          <chr>                                
1     1 Mat.Bramar          Administration Assistant to CEO                     
2     2 Anda.Ribera         Administration Assistant to CFO                     
3     3 Rachel.Pantanal     Administration Assistant to CIO                     
4     4 Linda.Lagos         Administration Assistant to COO                     
5     5 Ruscella.Mies.Haber Administration Assistant to Engineering Group Manag…
6     6 Carla.Forluniau     Administration Assistant to IT Group Manager        
# ℹ 48 more rows
#
# A tibble: 1,372 × 4
   from    to Weekday Weight
  <int> <int> <ord>    <int>
1     1     2 Sunday       5
2     1     2 Monday       2
3     1     2 Tuesday      3
# ℹ 1,369 more rows
ggraph(GAStech_graph) + #used to initialize the network plot
  geom_edge_link() +  #to visualize the edges as lines
  geom_node_point() + #represent the nodes as points
  theme_void() #remove any background elements from the plot and create a clean, minimalistic appearance.
Using "stress" as default layout
Warning: Using the `size` aesthetic in this geom was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` in the `default_aes` field and elsewhere instead.

g <- ggraph(GAStech_graph) + 
  geom_edge_link(aes(colour = 'grey50')) +
  geom_node_point(aes(colour = 'grey40'))
Using "stress" as default layout
g + theme_graph(background = 'grey10',
                text_colour = 'white')

g <- ggraph(GAStech_graph, 
            layout = "fr") +
  geom_edge_link(aes()) +
  geom_node_point(aes())

g + theme_graph()

g <- ggraph(GAStech_graph, 
            layout = "nicely") + 
  geom_edge_link(aes()) +
  geom_node_point(aes(colour = Department, 
                      size = 3))

g + theme_graph()

GAStech_edges_aggregated <- GAStech_edges %>%
  left_join(GAStech_nodes, by = c("sourceLabel" = "label")) %>%
  rename(from = id) %>%
  left_join(GAStech_nodes, by = c("targetLabel" = "label")) %>%
  rename(to = id) %>%
  filter(MainSubject == "Work related") %>%
  group_by(from, to) %>%
    summarise(weight = n()) %>%
  filter(from!=to) %>%
  filter(weight > 1) %>%
  ungroup()
`summarise()` has grouped output by 'from'. You can override using the
`.groups` argument.
visNetwork(GAStech_nodes, 
           GAStech_edges_aggregated)
visNetwork(GAStech_nodes,
           GAStech_edges_aggregated) %>%
  visIgraphLayout(layout = "layout_with_fr") 
GAStech_nodes <- GAStech_nodes %>%
  rename(group = Department) 
visNetwork(GAStech_nodes,
           GAStech_edges_aggregated) %>%
  visIgraphLayout(layout = "layout_with_fr") %>%
  visEdges(arrows = "to", 
           smooth = list(enabled = TRUE, 
                         type = "curvedCW")) %>%
  visOptions(highlightNearest = TRUE,
             nodesIdSelection = TRUE) %>%
  visLegend() %>%
  visLayout(randomSeed = 123)