R: Create a bar chart without aggregation for any metric

create_bar_asis {wpa}

R Documentation

Create a bar chart without aggregation for any metric

Description

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.

Usage

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.

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(), create_line_asis(), 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(), meetingtype_dist_ca(), meetingtype_dist_mt(), 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(), create_line_asis(), 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)

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")
  )