Visualizing recruiting data

HR Analytics: Exploring Employee Data in R

Ben Teusch

HR Analytics Consultant

Small number of groups

call_center_a %>% 
  group_by(team) %>% 
  summarize(avg_calls = mean(calls_made)) %>% 
  arrange(desc(avg_calls))

   team avg_calls
  <chr>     <dbl>
1     D  84.21283
2     B  79.65947
3     A  73.80612
4     C  61.73712

Large number of groups

call_center_b %>% 
  group_by(team) %>% 
  summarize(avg_calls = mean(calls_made)) %>% 
  arrange(desc(avg_calls))

     team avg_calls
   <fctr>     <dbl>
1       J  98.16318
2       U  89.64824
3       M  84.90123
4       L  82.90802
5       D  82.62958
6       E  82.08344
7       C  80.46505
8       K  79.91899
# ... with 18 more rows

A simple bar chart

call_center_b_summary

     team avg_calls
   <fctr>     <dbl>
1       J  98.16318
2       U  89.64824
3       M  84.90123
4       L  82.90802
5       D  82.62958
6       E  82.08344
7       C  80.46505
8       K  79.91899
# ... with 18 more rows

ggplot(call_center_b_summary, aes(x = team, y = avg_calls)) +
  geom_col()

A simple bar chart

A polished bar chart

Let's practice!

HR Analytics: Exploring Employee Data in R