Package index
Graph Wrappers
These are wrapper functions around common ggplot2 functions. They’re designed to make it easier to make graphs.
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adl_bar_plots() - Create bar plots in ADL's style
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adl_coef_plots() - Create coefficient plots in ADL's style
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adl_lollipop_plots() - Lollipop plots with optional dodging and auto label offsets
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stat_density_quant() - Stat for density ridgeline plots
Themes
Full blown ggplot2 themes that affect almost all visual aspects of a graph. These are similar to ggplot2 themes like ggplot2::theme_minimal() or ggplot2::theme_gray().
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theme_default() - Default theme
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theme_v_bar() - Theme for vertical non-stacked bar plots
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theme_h_bar() - Theme for non-stacked horizontal bar plots
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theme_h_stack() - Theme for horizontal stacked bar plots
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theme_coef() - Theme for coefficient plots
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hc_theme_default() - The default theme for hc charts
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scale_adl() - ADL color scale
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adl_palettes - Complete list of available adl official color palettes
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case_match_fct() case_matchwith factor levels-
case_when_fct() case_whenwith factor levels-
flip_val() - Flip the valence of a vector
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make_factor() - Convert a labelled vector into a factor
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make_quarts() - Create quartiles
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make_dicho() - Make dichotomous factors
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make_binary() - Make binary variables
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make_nested() - Create a nested data frame
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num_rev() - Reverse a numeric function
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refactor() - Assign or reorder factor levels manually
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pct_conv() - Make proper percent labels
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make_percent() - Convert a numeric vector to a percent
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pivot_longer_values() - Pivot data from wide to long with value labels
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dunnett() - Run Dunnett's multiple comparisons test with one control.
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get_coefficients() - Create a tidied tibble of regression results
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get_means() - Calculate means with confidence intervals
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get_diffs() - Calculate difference in means
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get_freqs() - Compute weighted frequencies, optionally grouped and/or across multiple variables
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get_freq_table() - Get the frequencies as a GT table
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get_all_freqs() - Export frequencies for a set of variables to a word doc.
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export_freqs_excel() - Export Frequency Tables to Excel with Professional Formatting
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get_corr() - Calculate weighted correlations
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get_all_corr() - Get correlations for a combination of variables
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get_loadings() - Calculate the loadings in factor analysis
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prettytable() - Make pretty HTML tables
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row_means() - Calculate row means
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row_sums() - Calculate row sums
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wtd_corr() - Calculate individual weighted correlations
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attr_var_label() - Get variable label
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attr_val_labels() - Get value labels
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attr_levels() - Get variable label
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attr_note() - Get the note attribute
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attr_question_preface() - Get the question_preface attribute
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attr_survey_flow() - Get the survey_flow attribute
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attr_transformation() - Get the transformation attribute
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flatten_labelled_vec() - Flatten a labelled vector
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set_question_preface() - Set a new attribute called
question_preface
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clean_demos() - Clean up demographic variables
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remove_bogus() - Remove bots, duplicates, and/or speedsters from a data frame
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get_bogus() - Get bogus data from a data frame
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export_bogus() - Export data frame with only bots and duplicates
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get_col_names() - Get the column names
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codebook() - Create a data codebook
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dunnett_helper() - Perform Dunnett's test (mostly internal function)
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funky_freqs()experimental - Calculate weighted frequencies
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stars_pval() - Add stars based on the p-value
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write_word_table() - This mainly an internal package but can be used externally
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wtd_sd() - Calculate weighted standard deviation
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test_data - dataset_title,
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remove_bot_dupe()deprecated - Remove bots and/or duplicates from a data frame
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get_bot_dupe()deprecated - Get the bots or duplicates from a data frame
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export_bot_dupe()superseded - Export data frame with only bots and duplicates