All functions

IV_by_period()

Identify the WPA metrics that have the biggest change between two periods.

IV_report()

Generate a Information Value HTML Report

afterhours_dist()

Distribution of After-hours Collaboration Hours as a 100% stacked bar

afterhours_fizz()

Distribution of After-hours Collaboration Hours (Fizzy Drink plot)

afterhours_line()

After-hours Collaboration Time Trend - Line Chart

afterhours_rank()

Rank groups with high After-Hours Collaboration Hours

afterhours_summary() afterhours_sum()

Summary of After-Hours Collaboration Hours

afterhours_trend()

After-Hours Time Trend

calculate_IV()

Calculate Weight of Evidence (WOE) and Information Value (IV) between a single predictor and a single outcome variable.

camel_clean()

Convert "CamelCase" to "Camel Case"

capacity_report()

Generate a Capacity report in HTML

check_inputs()

Check whether a data frame contains all the required variable

check_query()

Check a query to ensure that it is suitable for analysis

coaching_report()

Generate a Coaching report in HTML

collaboration_area() collab_area()

Collaboration - Stacked Area Plot

collaboration_dist() collab_dist()

Distribution of Collaboration Hours as a 100% stacked bar

collaboration_fizz() collab_fizz()

Distribution of Collaboration Hours (Fizzy Drink plot)

collaboration_line() collab_line()

Collaboration Time Trend - Line Chart

collaboration_rank() collab_rank()

Collaboration Ranking

collaboration_report()

Generate a Collaboration Report in HTML

collaboration_sum() collab_sum() collaboration_summary() collab_summary()

Collaboration Summary

collaboration_trend()

Collaboration Time Trend

combine_signals()

Combine signals from the Hourly Collaboration query

comma()

Add comma separator for thousands

connectivity_report()

Generate a Connectivity report in HTML

copy_df()

Copy a data frame to clipboard for pasting in Excel

create_ITSA()

Estimate an effect of intervention on every WPA metric in input file by applying single-group Interrupted Time-Series Analysis (ITSA)

create_IV()

Calculate Information Value for a selected outcome variable

create_bar()

Mean Bar Plot for any metric

create_bar_asis()

Create a bar chart without aggregation for any metric

create_boxplot()

Box Plot for any metric

create_bubble()

Create a bubble plot with two selected Workplace Analytics metrics (General Purpose), with size representing the number of employees in the group.

create_dist()

Horizontal 100 percent stacked bar plot for any metric

create_dt()

Create interactive tables in HTML with 'download' buttons.

create_fizz()

Fizzy Drink / Jittered Scatter Plot for any metric

create_hist()

Create a histogram plot for any metric

create_line()

Time Trend - Line Chart for any metric

create_line_asis()

Create a line chart without aggregation for any metric

create_period_scatter()

Period comparison scatter plot for any two metrics

create_rank()

Rank all groups across HR attributes on a selected Workplace Analytics metric

create_rank_combine()

Create combination pairs of HR variables and run 'create_rank()'

create_sankey()

Create a sankey chart from a two-column count table

create_scatter()

Create a Scatter plot with two selected Workplace Analytics metrics (General Purpose)

create_stacked()

Horizontal stacked bar plot for any metric

create_trend()

Heat mapped horizontal bar plot over time for any metric

cut_hour()

Convert a numeric variable for hours into categorical

dv_data

Sample Standard Person Query dataset for Data Validation

em_data

Sample Hourly Collaboration data with Email and IMs

email_dist()

Distribution of Email Hours as a 100% stacked bar

email_fizz()

Distribution of Email Hours (Fizzy Drink plot)

email_line()

Email Time Trend - Line Chart

email_rank()

Email Hours Ranking

email_summary() email_sum()

Email Summary

email_trend()

Email Hours Time Trend

export()

Export 'wpa' outputs to CSV, clipboard, or save as images

external_network_plot()

Plot External Network Breadth and Size as a scatter plot

extract_date_range()

Extract date period

extract_hr()

Extract HR attribute variables

flag_ch_ratio()

Flag unusual high collaboration hours to after-hours collaboration hours ratio

flag_em_ratio()

Flag Persons with unusually high Email Hours to Emails Sent ratio

flag_extreme()

Warn if a certain metric exceeds an arbitrary threshold

flag_outlooktime()

Flag unusual outlook time settings for work day start and end time

flex_index()

Compute a Flexibility Index based on the Hourly Collaboration Query

g2g_data

Sample Group-to-Group dataset

generate_report()

Generate HTML report with list inputs

heat_colours() heat_colors()

Generate a vector of n contiguous colours, as a red-yellow-green palette.

hr_trend()

Employee count over time

hrvar_count() analysis_scope()

Create a count of distinct people in a specified HR variable

hrvar_count_all()

Create count of distinct fields and percentage of employees with missing values for all HR variables

hrvar_trend()

Track count of distinct people over time in a specified HR variable

identify_churn()

Identify employees who have churned from the dataset

identify_holidayweeks()

Identify Holiday Weeks based on outliers

identify_inactiveweeks()

Identify Inactive Weeks

identify_nkw()

Identify Non-Knowledge workers in a Person Query using Collaboration Hours

identify_outlier()

Identify metric outliers over a date interval

identify_privacythreshold()

Identify groups under privacy threshold

identify_query()

Identify the query type of the passed data frame

identify_shifts()

Identify shifts based on outlook time settings for work day start and end time

identify_shifts_wp()

Identify shifts based on binary activity

identify_tenure()

Tenure calculation based on different input dates, returns data summary table or histogram

import_to_fst()

Read a Workplace Analytics query in '.csv' using and create a '.fst' file in the same directory for faster reading

import_wpa()

Import a Workplace Analytics Query

internal_network_plot()

Plot Internal Network Breadth and Size as a scatter plot

is_date_format()

Identify whether string is a date format

keymetrics_scan()

Run a summary of Key Metrics from the Standard Person Query data

map_IV()

Calculate Weight of Evidence (WOE) and Information Value (IV) between multiple predictors and a single outcome variable, returning a list of statistics.

maxmin()

Max-Min Scaling Function

meeting_dist()

Distribution of Meeting Hours as a 100% stacked bar

meeting_extract()

Extract top low-engagement meetings from the Meeting Query

meeting_fizz()

Distribution of Meeting Hours (Fizzy Drink plot)

meeting_line()

Meeting Time Trend - Line Chart

meeting_quality()

Run a meeting habits / meeting quality analysis

meeting_rank()

Meeting Hours Ranking

meeting_skim()

Produce a skim summary of meeting hours

meeting_summary() meeting_sum()

Meeting Summary

meeting_tm_report()

Generate a Meeting Text Mining report in HTML

meeting_trend()

Meeting Hours Time Trend

meetingtype_dist()

Distribution of Meeting Types by number of Attendees and Duration

meetingtype_dist_ca()

Meeting Type Distribution (Ways of Working Assessment Query)

meetingtype_dist_mt()

Meeting Type Distribution (Meeting Query)

meetingtype_summary() meetingtype_sum()

Create a summary bar chart of the proportion of Meeting Hours spent in Long or Large Meetings

mgrcoatt_dist()

Manager meeting coattendance distribution

mgrrel_matrix()

Manager Relationship 2x2 Matrix

mt_data

Sample Meeting Query dataset

network_describe()

Uncover HR attributes which best represent a population for a Person to Person query

network_g2g() g2g_network()

Create a network plot with the group-to-group query

network_leiden()

Implement the Leiden community detection on a Person to Person network query

network_louvain()

Implement the Louvain community detection on a Person to Person network query

network_p2p()

Create a network plot with the person-to-person query

one2one_dist()

Distribution of Manager 1:1 Time as a 100% stacked bar

one2one_fizz()

Distribution of Manager 1:1 Time (Fizzy Drink plot)

one2one_freq()

Frequency of Manager 1:1 Meetings as bar or 100% stacked bar chart

one2one_line()

Manager 1:1 Time Trend - Line Chart

one2one_rank()

Manager 1:1 Time Ranking

one2one_sum() one2one_summary()

Manager 1:1 Time Summary

one2one_trend()

Manager 1:1 Time Trend

p2p_data_sim()

Simulate a person-to-person query using a Watts-Strogatz model

p_test()

Calculate the p-value of the null hypothesis that two outcomes are from the same dataset

pairwise_count()

Perform a pairwise count of words by id

period_change()

Plot the distribution of percentage change between periods of a WpA metric by the number of employees.

personas_hclust()

Create hierarchical clusters of selected metrics using a Person query

plot_WOE()

Plot WOE graphs with an IV object

plot_flex_index()

Plot a Sample of Working Patterns using Flexibility Index output

read_preamble()

Read preamble

remove_outliers()

Remove outliers from a person query across time

rgb2hex()

Convert rgb to HEX code

sq_data

Sample Standard Person Query dataset

standardise_pq() standardize_pq()

Standardise variable names to a Standard Person Query

subject_validate()

Scan meeting subject and highlight items for review

subject_validate_report()

Generate Meeting Text Mining report in HTML for Common Exclusion Terms

theme_wpa()

Main theme for 'wpa' visualisations

theme_wpa_basic()

Basic theme for 'wpa' visualisations

tm_clean()

Clean subject line text prior to analysis

tm_cooc()

Analyse word co-occurrence in subject lines and return a network plot

tm_freq()

Perform a Word or Ngram Frequency Analysis and return a Circular Bar Plot

tm_wordcloud()

Generate a wordcloud with meeting subject lines

totals_bind()

Row-bind an identical data frame for computing grouped totals

totals_col()

Fabricate a 'Total' HR variable

totals_reorder()

Reorder a value to the top of the summary table

track_HR_change()

Sankey chart of organizational movement between HR attributes and missing values (outside company move) (Data Overview)

tstamp()

Generate a time stamp

us_to_space()

Replace underscore with space

validation_report()

Generate a Data Validation report in HTML

workloads_dist()

Distribution of Work Week Span as a 100% stacked bar

workloads_fizz()

Distribution of Work Week Span (Fizzy Drink plot)

workloads_line()

Workloads Time Trend - Line Chart

workloads_rank()

Rank all groups across HR attributes for Work Week Span

workloads_summary() workloads_sum()

Work Week Span Summary

workloads_trend()

Work Week Span Time Trend

workpatterns_area()

Create an area plot of emails and IMs by hour of the day

workpatterns_classify()

Classify working pattern personas using a rule based algorithm

workpatterns_classify_bw()

Classify working pattern week archetypes using a rule-based algorithm, using the binary week-based ('bw') method.

workpatterns_classify_pav()

Classify working pattern personas using a rule based algorithm, using the person-average volume-based ('pav') method.

workpatterns_hclust()

Create a hierarchical clustering of email or IMs by hour of day

workpatterns_rank()

Create a rank table of working patterns

workpatterns_report()

Generate a report on working patterns in HTML

wrap()

Add a character at the start and end of a character string