A C D E F G H I J K L M N O P R S T U V W
| 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_sum | Summary of After-Hours Collaboration Hours |
| afterhours_summary | Summary of After-Hours Collaboration Hours |
| afterhours_trend | After-Hours Time Trend |
| analysis_scope | Create a count of distinct people in a specified HR variable |
| anonymise | Anonymise a categorical variable by replacing values |
| anonymize | Anonymise a categorical variable by replacing values |
| 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 | Collaboration - Stacked Area Plot |
| collaboration_dist | Distribution of Collaboration Hours as a 100% stacked bar |
| collaboration_fizz | Distribution of Collaboration Hours (Fizzy Drink plot) |
| collaboration_line | Collaboration Time Trend - Line Chart |
| collaboration_rank | Collaboration Ranking |
| collaboration_report | Generate a Collaboration Report in HTML |
| collaboration_sum | Collaboration Summary |
| collaboration_summary | Collaboration Summary |
| collaboration_trend | Collaboration Time Trend |
| collab_area | Collaboration - Stacked Area Plot |
| collab_dist | Distribution of Collaboration Hours as a 100% stacked bar |
| collab_fizz | Distribution of Collaboration Hours (Fizzy Drink plot) |
| collab_line | Collaboration Time Trend - Line Chart |
| collab_rank | Collaboration Ranking |
| collab_sum | Collaboration Summary |
| collab_summary | Collaboration Summary |
| 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_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 Viva Insights metrics (General Purpose), with size representing the number of employees in the group. |
| create_density | Create a density plot for any metric |
| 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_inc | Create an incidence analysis reflecting proportion of population scoring above or below a threshold for a metric |
| create_incidence | Create an incidence analysis reflecting proportion of population scoring above or below a threshold for a metric |
| create_ITSA | Estimate an effect of intervention on every Viva Insights metric in input file by applying single-group Interrupted Time-Series Analysis (ITSA) |
| create_IV | Calculate Information Value for a selected outcome variable |
| 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 Viva Insights 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 Viva Insights metrics (General Purpose) |
| create_stacked | Horizontal stacked bar plot for any metric |
| create_tracking | Create a line chart that tracks metrics over time with a 4-week rolling average |
| 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 |
| 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_sum | Email Summary |
| email_summary | Email Summary |
| email_trend | Email Hours Time Trend |
| em_data | Sample Hourly Collaboration data |
| export | Export 'wpa' outputs to CSV, clipboard, or save as images |
| external_dist | Distribution of External Collaboration Hours as a 100% stacked bar |
| external_fizz | Distribution of External Collaboration Hours (Fizzy Drink plot) |
| external_line | External Collaboration Hours Time Trend - Line Chart |
| external_network_plot | Plot External Network Breadth and Size as a scatter plot |
| external_rank | Rank groups with high External Collaboration Hours |
| external_sum | External Collaboration Summary |
| external_summary | External Collaboration Summary |
| 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 for extreme values by checking against a 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 |
| g2g_network | Create a network plot with the group-to-group query |
| generate_report | Generate HTML report with list inputs |
| generate_report2 | Generate HTML report based on existing RMarkdown documents |
| GetResiduals | Extract Residuals from ARIMA, VAR, or any Simulated Fitted Time Series Model |
| heat_colors | Generate a vector of 'n' contiguous colours, as a red-yellow-green palette. |
| heat_colours | Generate a vector of 'n' contiguous colours, as a red-yellow-green palette. |
| hrvar_count | 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 |
| hr_trend | Employee count over time |
| identify_churn | Identify employees who have churned from the dataset |
| identify_datefreq | Identify date frequency based on a series of dates |
| 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 |
| IV_by_period | Identify the WPA metrics that have the biggest change between two periods. |
| IV_report | Generate a Information Value HTML Report |
| jitter_metrics | Jitter metrics in a data frame |
| keymetrics_scan | Run a summary of Key Metrics from the Standard Person Query data |
| keymetrics_scan_asis | Run a summary of Key Metrics without aggregation |
| LjungBox | Ljung and Box Portmanteau Test |
| 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 |
| 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_sum | Create a summary bar chart of the proportion of Meeting Hours spent in Long or Large Meetings |
| meetingtype_summary | Create a summary bar chart of the proportion of Meeting Hours spent in Long or Large Meetings |
| 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_sum | Meeting Summary |
| meeting_summary | Meeting Summary |
| meeting_tm_report | Generate a Meeting Text Mining report in HTML |
| meeting_trend | Meeting Hours Time Trend |
| 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 | Create a network plot with the group-to-group query |
| network_p2p | Perform network analysis with the person-to-person query |
| network_summary | Summarise node centrality statistics with an igraph object |
| 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 | Manager 1:1 Time Summary |
| 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 |
| pad2 | Create the two-digit zero-padded format |
| pairwise_count | Perform a pairwise count of words by id |
| period_change | Plot the distribution of percentage change between periods of a Viva Insights metric by the number of employees. |
| personas_hclust | Create hierarchical clusters of selected metrics using a Person query |
| plot_flex_index | Plot a Sample of Working Patterns using Flexibility Index output |
| plot_hourly_pat | Internal function for plotting the hourly activity patterns. |
| plot_WOE | Plot WOE graphs with an IV object |
| p_test | Calculate the p-value of the null hypothesis that two outcomes are from the same dataset |
| 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 | Standardise variable names to a Standard Person Query |
| standardize_pq | Standardise variable names to a Standard Person Query |
| subject_classify | Create a new logical variable that classifies meetings by patterns in subject lines |
| subject_scan | Count top words in subject lines grouped by a custom attribute |
| 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_scan | Count top words in subject lines grouped by a custom attribute |
| 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 |
| wellbeing_report | Generate a Wellbeing 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_sum | Work Week Span Summary |
| workloads_summary | 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 |
| wrap_text | Wrap text based on character threshold |