sig_test_y2
can now take a grouped freqs() object of multi-select variables; filters out rows across multi-select variable "stems" that are all NAsig_test_y2
can now take a grouped freqs() object with multiple variables; function iterates through pairwise group-level testing in each variable and displays results together.freqs
- When show_missing_levels = TRUE, now has freqs table ordered by value, slotting in the missing levels where they should have gone if not missing, instead of at the end of the table.verbatims_y2
now has an additional column of output: base_ns.cross_freqs
- New argument include_overall Boolean, whether to include the overall frequency levels for variables (default = FALSE)multi_freqs
- New argument show_missing_levels Boolean, whether to keep response levels with no data (default: TRUE). This argument functions the same way it does with freqs()freqs
did not always capture all missing levels with the argument show_missing_levels when the data was grouped. This has been fixed, and the hotfix also applies to the new argument in multi_freqsstat_test_y2
- Akin to crosstabs, run significance testing on a grouped frequenciesmulti_freqs
- Resolved bug for multi-select questions with 10+ options.freqs
- Bug fix for grouped frequencies with prompt = TRUEfreqs
- 'prompt = TRUE' now properly working with the new 'show_missing_levels' argumentverbatims_y2
- internal update to work more in-line with the y2municipal topline() functionfreqs
- When freqs was run on a factor variable in the past, the "value" column would pull the character labels even when the factor had underlying numbers. This version of y2clerk updates freqs to be more consistent with other types of haven labelled variables and pulls the underlying numbers of factor variables for use in the value column. freqs
- show_missing_levels: whether to keep response levels with no data (default: TRUE). For example, set to TRUE if you know no one answered "very dissatisfied" on a scale, but you still want that empty level of the scale present in the output of freqs.to_haven_y2
- Convert a factor variable or a character variable to a haven labelled variablemulti_freqs
Finally the new freqs function everyone has been waiting for. Run a frequencies table on a multiple answer question. Under the hood, the function looks for any respondents who answered none of the multiple selects for that series of questions with the same stem and filters them out before running freqs. Essentially, multi_freqs
automates all that by-hand filtering that had to be done manually on any multiple answer questions. Conveniently allows you to input only one question in a multiple answer block. For example, the user only has to give it m_race_1, instead of m_race_1, m_race_2, m_race_3, etc..append_ns
- Uses the output from the y2clerk freqs() function and adds (N = ...) to the end of each label, based off the column "n". Useful for charts that require ns for all levelspivot_freqs
The last bug fix was a temporary solution for the list columns, but this one should be more legit (using values_fill argument from pivot_wider)pivot_freqs
bug fixed where pivot_freqs was making columns into lists instead of numericsfreqs
& cross_freqs
: argument pr changed to percentile. Change was done to better align with tidyverse practice that no arguments are the beginnings of another argument (existing argument "prompt" matched to "pr", which we now want to avoid by changing "pr" to "percentile")freqs
bug fixed so now grouped freqs with stat = 'mean' runs properly pivot_freqs
- columns_var: DEFAULT = label; Used to pivot so only "label" could be the new columns in the wide df. Now you can set group_var to be the new columns, instead of rows. freqs()
has a new argument: unweighted_ns
. Use this argument in combination with the wt
argument to have weighted results but unweighted ns. This is particularly useful in toplines.pivot_freqs
- for pivoting wide a grouped freqs. Makes it easier for quick comparisonscross_freqs
- more succinct way of running functioncross_freqs
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