This PR updates the superseded dplyr scoped verbs to use the current recommended approach with across(). It focuses on updating the most critical and commonly used functions in the package to ensure compatibility with the latest dplyr releases and improve code maintainability.

This PR also increments the package to v1.10.0 and improves overall test coverage of the package.

Key Changes:

Updated functions that use superseded dplyr syntax:

• Replace summarise_if(), summarise_at(), summarise_all() with summarise(across()) syntax
• Replace mutate_at(), mutate_if(), mutate_all() with mutate(across()) syntax
• Replace select_if() with select(where())
• Add all_of() around string variables in select()

Main files updated:

• period_change.R: Updated summarise_if() and mutate_at()
• meeting_skim.R: Updated summarise_at() and mutate_at()
• meetingtype_summary.R: Updated summarise_at() with vars() to use across(all_of())
• create_line.R: Updated summarise_at() with vars(all_of()) to use across(all_of())
• identify_outlier.R: Updated summarise_at() to use across()
• create_scatter.R: Updated summarise_at() to use across()
• create_bubble.R: Updated summarise_at() to use across()
• meetingtype_dist_ca.R: Updated summarise_at() to use across()
• create_IV.R: Updated direct variable selection with all_of() and select_if() with select(where())
• create_dt.R: Updated select_if() to select(where())
• hrvar_count_all.R: Updated summarise_at() to use across()

Syntax improvements for dplyr compatibility:

• Added .groups = "drop" parameter to grouped summarise() calls to ensure consistent behavior across dplyr versions
• Fixed across() syntax to use all_of(c(var1, var2)) instead of c(!!sym(var1), !!sym(var2))
• Updated comprehensive test coverage for all modified functions with simplified, robust assertions

Example of changes:

Before:

data %>%
  group_by(Period, PersonId) %>%
  summarise_if(is.numeric, mean, na.rm = TRUE)

# or
data %>%
  mutate_at("Employee_perc", ~round(. * 100, 1))

After:

data %>%
  group_by(Period, PersonId) %>%
  summarise(across(where(is.numeric), ~mean(., na.rm = TRUE)), .groups = "drop")

# or
data %>%
  mutate(across("Employee_perc", ~round(. * 100, 1)))

These changes ensure compatibility with the latest dplyr releases and follow current best practices for data manipulation while maintaining identical functionality.

Fixes #243.