nas_are_false
.reverse_code
.t_test
to allow a t-test between two different vectors from the same data.comparison_table
to use a t-test on numeric data when the grouping variable only has two unique values.breakdown
is calculated.chisq_test
to allow a chi-square test between two different vectors.comparison_table
to use a correct chi-square test.comparison_table
to print out the filter names in cases of numeric data.drop_na_cols
, which drops columns from a dataframe that are entirely NA.gather
.ctab
to properly create variables when analyzing continuous data.ctab
to count the number of cells when analyzing continuous data.comparison_table_
as a NSE-safe companion to comparison_table
.tab
and ctab
to allow filter()
as an alias for filters()
.tab
and ctab
when using filters()
with a length > 1 vector.tab
and ctab
to take an argument filters()
containing filters for the data. This will filter the dataframe and print out the list of filters. For example, try tab(iris, filters(Species %not_in% "virginica", Petal.Width > 0.2), Species)
to look at the Species when excluding virginia and all Petal.Length
below 0.2.nas_are_zeros
to convert NAs to zeros.Major
drop_values
to drop individual values from a variable.apply_over_vars
to apply a function over variables in a dataframe by specifying the names of the variables.cut3
to split a vector into roughly even-sized bins.Minor
response_rate
from working.na.rm = FALSE
.swap_by_value
to swap for multiple variables.num_over_zero
to have a na.rm
parameter.breakdown
to handle passing in the variable as a string.comparison_table
for some logical operator comparisons involving continuous data, introduced by v0.4.16.tab
and comparison_table
to have a parameter top
that can constrain the number of levels outputted, putting all minor levels in a single bin called "Other".na.rm = TRUE
in comparison_table
.var_summary
to report the number of NAs and the number of values > 0 for numeric variables when called with verbose = TRUE
.var_summary
to report the number of NAs for non-numeric variables when called with verbose = TRUE
.var_summary
to no longer track the class
of the object.var_summary
returns as a named vector if possible.var_summary
to no longer display a table of numeric variables (as originally intended).var_summary
to no longer supports serialize
.swap_by_value
to enforce a correct swap_list.swap_by_value
to no longer use direct substitution.swap_by_value
to swap based on a grep-pattern.get_vars
to support multiple patterns passed as a vector.fish_for_correlations
that analyzes a dataframe for correlations.get_vars
to streamline finding all names in a dataframe that match a pattern.%not_in%
, the opposite of %in%
.data_summary
to extend var_summary
to an entire dataframe.var_summary
, restore them by using verbose = TRUE
..10
minor versioning for this release was a mistake.)swap_by_value
when the dataframe has NAs.replace
to now take column name via NSE.replace
implementation.replace
to swap values within a dataframe.breakdown
and num_answers
to use NSE by default.breakdown_
and num_answers_
for non-NSE.ctab
and tab
to announce in printed table if NAs were removed.var_summary
and summary_csv
from the (now defunct) summarizeR package.tab
and ctab
to now take a (functional) na.rm
parameter.num_respondants
to num_respondents
.ctab
as an alias for comparison_table
.dplyr_table
to tab
.ctab
and ctable
as aliases for comparison_table
.tab
to print more cleanly.tab
and ctab
to take expressions (e.g., tab(iris, Species == "setosa")
)comparison_table
to support NSE for variable names and can infer the comparison type.comparison_table
to print out the median for continuous data too.comparison_table
to allow "discrete" as a synonym for "continuous" when specifying a type.comparison_table
to no longer take in vectors directly.Add the following code to your website.
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