- This allows you to calculate row means
- This produces a nested data frame
-
Previously
get_corr()
had some bugs that have been fixed. -
Also added the ability to group by multiple variables
- This allows you to flip the valence of a variable
- Simplified the vignette and added information about
flip_val()
- Allows you to set the question preface and update the variable label
- Added two new arguments, show_means, and show_pct_change.
- Added a return value for most functions
- This function calculates the difference in means.
- I added a new argument that allows you to specify the levels. This is not fully implemented yet, however.
- This is an experimental function that will hopefully become the basis for get_freqs as it is three times as fast.
- Adding an argument that sorts the data
- This function makes it easy to get the correlations for all variables in a data set.
- Added new functionality so that data can be grouped before performing
dunnet()
and improved the group argument to include functionality for grouping by multiple variables.
- Flatten a labelled vector. or example if a vector has values 1 and 0 where 1 is "Yes" and 0 is "No", it will output a string that reads:
1 = "Yes", 0 = "No"
.
- These three functions make it easy to remove bots and duplicates, remove all non-bots and duplicates, and export all bots and duplicates.
- Calculate weighted correlations among each level of a group
- Perform Dunnett's multiple comparisons test
- Get variable label for vectors and dataframes
- Get value labels for vectors and dataframes
- Get factor levels for vectors and dataframes
- Get note attribute for vectors and dataframes
- Get survey_flow attribute for vectors and dataframes
- Get question_preface attribute for vectors and dataframes
- get transformation attribute for vectors and dataframes
- Added new argument that enables wrapping facet labels.
- Did not work with factor or character vectors so updated
- With factor vectors now just returns the factor vector
- With character vectors converts it to a factor
- Fixed a bug that returned the variable name instead of variable labels
- This function takes a labelled vector and uses the value labels to turn it into a factor
- contains two arguments:
x
andordered
- Added a new argument that enables you to add a variable label to the variable that contains the names (names_to)
- Using internal functions to reduce external dependencies
- Updated the internal code so that it only gives you the attribute under "label"
- Previously if "label" was NULL, it would give you the values in "labels"
- This function allows you to create a new data.frame object where each column is a different attribute and each row is a different variable
- Contains one argument:
df
- Add this function after using
get_freqs()
to make a pretty gt table - Contains one argument:
x
- Hoping to continue building this out for means, coefficients, and possibly more
- This allows you to reorder the levels of a factor variable
- Contains one argument:
x
- Create a density plot with quantile lines
- Has a bunch of arguments:
mapping
,data
,geom
,position
,...
,bw
,adjust
,kernel
,n
,na.rm
,bounds
,show.legend
,inherit.aes
,quantile_lines
,calc_ecdf
,quantiles
- This may still be buggy and I still need to create the accompanying geom
This update includes a bunch of new features and bug fixes. Some of the underlying code has also been updated to be more modular by replacing repetitive code with internal helper functions.
- This function makes it easy to calculate means with confidence intervals.
- It contains four arguments:
df
,x
,group
, andwt
- The most important argument is
group
as it allows you to calculate means by a grouping variable. It operates similar to the.by
argument in somedplyr
functions.
- This makes it easy to calculate weighted frequencies.
- It contains the same first four arguments as
get_means
but also contains a fifth argument,cross_tab
. By settingcross_tab = TRUE
you pivot the table so that it appears like most cross tabs.
- Add the % symbol to a numeric vector and as a result convert to a character vector
- Contains three arguments: x, digits, and scale
- Digits specifies how many decimal places the percentage should be rounded to
- Scale determines by what scale the numeric vector values should be multiplied
- This is a simple function that makes it easier to create documentation for data sets by leveraging the underlying variable labels in the dataset
- Now all arguments accept either strings or symbols, making it easier to use with functional programming
- It also contains a new argument
show_genpop
which enables you to determine whether you want a column showing the frequencies for the general population or not.
- Fixed a bug where mean plots didn't work in a dodged vertical charts.