Function reference • PKPDmisc

Data Ingestion Ingest Data.
`read_nonmem()`	read nonmem files easily
`read_phx()`	to more easily read data with a 2nd row with units common to phx data
`write_nonmem()`	easily write a csv file compatible with nonmem
Data Manipulation
`as_numeric()`	Convert to numeric passing through character for safety
`fill_backward()`	given NA values fill them with the next non-na value
`fill_forward()`	given NA values fill them with the final non-na value
`ids_per_plot()` `chunk()` `chunk_grp()` `chunk_list()` `chunk_grp_list()`	split IDs into groups to use for subsequent plotting
`max_through()`	give the max value up to that point
`min_through()`	give the min value up to that point
`set_bins()`	given a set of bin ranges, assign each value to a bin
`unique_non_numerics()`	Find all unique non-numeric values
Summaries
`s_pauc_()` `s_pauc()`	summarize paucs
`s_quantiles_()` `s_quantiles()`	summarize quantiles for a column
Formatting
`capitalize_names()`	capitalize all names for a dataframe
`lowercase_names()`	lowercase all names for a dataframe
`char_to_numeric()`	convert all columns to numeric
`cols_to_numeric()`	convert column to type numeric
`ordinal_to_binary_()`	convert a column of categorical covariates into a number of columns with a binary flag for each category
`replace_dots()`	Convert '.' values into missing values.
`pad_left()`	add left padding to a vector of values
Pharmacometrics-specific
`auc_inf()`	Calculate AUCt-inf
`auc_partial()`	Calculate partial AUC
`resample_df()`	resampling
`strip_curves()`	basic curve stripping to get initial estimates
`wam()`	wam function
misc
`jprint()`	print multiple values joined together
`view_creator()`	create view commands that save rds files to where a shiny app is listening for them
`peek()`	peek at the results in a dplyr pipeline
`pad_left()`	add left padding to a vector of values

Reference

Data Ingestion

Data Manipulation

Summaries

Formatting

Pharmacometrics-specific

misc