Create a bar chart without aggregation for any metric

This function creates a bar chart directly from the aggregated / summarised data. Unlike create_bar() which performs a person-level aggregation, there is no calculation for create_bar_asis() and the values are rendered as they are passed into the function.

create_bar_asis(
  data,
  group_var,
  bar_var,
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  ylab = group_var,
  xlab = bar_var,
  percent = FALSE,
  bar_colour = "default",
  rounding = 1
)

Arguments

data

Plotting data as a data frame.

group_var

String containing name of variable for the group.

bar_var

String containing name of variable representing the value of the bars.

title

Title of the plot.

subtitle

Subtitle of the plot.

caption

Caption of the plot.

ylab

Y-axis label for the plot (group axis)

xlab

X-axis label of the plot (bar axis).

percent

Logical value to determine whether to show labels as percentage signs. Defaults to FALSE.

bar_colour

String to specify colour to use for bars. In-built accepted values include "default" (default), "alert" (red), and "darkblue". Otherwise, hex codes are also accepted. You can also supply RGB values via rgb2hex().

rounding

Numeric value to specify number of digits to show in data labels

Value

'ggplot' object. A horizontal bar plot.

See also

Other Visualization: afterhours_dist(), afterhours_fizz(), afterhours_line(), afterhours_rank(), afterhours_summary(), afterhours_trend(), collaboration_area(), collaboration_dist(), collaboration_fizz(), collaboration_line(), collaboration_rank(), collaboration_sum(), collaboration_trend(), create_bar(), create_boxplot(), create_bubble(), create_dist(), create_fizz(), create_inc(), create_line_asis(), create_line(), create_period_scatter(), create_rank(), create_sankey(), create_scatter(), create_stacked(), create_tracking(), create_trend(), email_dist(), email_fizz(), email_line(), email_rank(), email_summary(), email_trend(), external_dist(), external_fizz(), external_line(), external_network_plot(), external_rank(), external_sum(), hr_trend(), hrvar_count(), hrvar_trend(), internal_network_plot(), keymetrics_scan(), meeting_dist(), meeting_fizz(), meeting_line(), meeting_quality(), meeting_rank(), meeting_summary(), meeting_trend(), meetingtype_dist_ca(), meetingtype_dist_mt(), meetingtype_dist(), meetingtype_summary(), mgrcoatt_dist(), mgrrel_matrix(), one2one_dist(), one2one_fizz(), one2one_freq(), one2one_line(), one2one_rank(), one2one_sum(), one2one_trend(), period_change(), workloads_dist(), workloads_fizz(), workloads_line(), workloads_rank(), workloads_summary(), workloads_trend(), workpatterns_area(), workpatterns_rank()

Other Flexible: create_bar(), create_boxplot(), create_bubble(), create_density(), create_dist(), create_fizz(), create_hist(), create_inc(), create_line_asis(), create_line(), create_period_scatter(), create_rank(), create_sankey(), create_scatter(), create_stacked(), create_tracking(), create_trend(), period_change()

Examples

# Creating a custom bar plot without mean aggregation
library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union

sq_data %>%
  group_by(Organization) %>%
  summarise(across(.cols = Meeting_hours,
                   .fns = ~sum(., na.rm = TRUE))) %>%
  create_bar_asis(group_var = "Organization",
                  bar_var = "Meeting_hours",
                  title = "Total Meeting Hours over period",
                  subtitle = "By Organization",
                  caption = extract_date_range(sq_data, return = "text"),
                  bar_colour = "darkblue",
                  rounding = 0)


library(dplyr)

# Summarise Non-person-average median `Emails_sent`
med_df <-
  sq_data %>%
  group_by(Organization) %>%
  summarise(Emails_sent_median = median(Emails_sent))

med_df %>%
  create_bar_asis(
    group_var = "Organization",
    bar_var = "Emails_sent_median",
    title = "Median Emails Sent by Organization",
    subtitle = "Person Averaging Not Applied",
    bar_colour = "darkblue",
    caption = extract_date_range(sq_data, return = "text")
  )