zhaoy provides functions for 5 data tasks: transfer, tidy, transform, summarize, and check.

Some advantages of zhaoy functions:

• Data-transfer functions convert relative file-paths to absolute file-paths, so there's no need to set working directories.

• First arguments are data, so functions are compatible with the tidyverse pipe.

• Within data tasks, function names and arguments are consistent.

Microsoft Excel: import_excel (deprecates i_excel) and export_excel

feather: import_feather (deprecates i_feather) and export_feather

R-specific binary files: import_rds and export_rds

path: convert relative file-paths to absolute

tidy_activity: Provide Enterprise (PE) "Activity Summary By Provider by Client by Date" report

tidy_adap: Provide Enterprise (PE) "Clients - View ADAP Clients by Recertification Date" report

tidy_lab_pe: Provide Enterprise (PE) "Test Results by Client With ID" report

tidy_provider_relationship: Provide Enterprise (PE) "Test Results by Client With ID" report

lc_df (deprecates i_df): convert upper-case English characters to lower-case, in data-frames

lz_id: include or exclude leading zeros in medical record numbers (MRNs)

s_cross_n: cross-tabulate counts of unique values, including missing-data, in 2 or 3 variables

s_cross_p: cross-tabulate percents of unique values, including missing-data, in 2 or 3 variables

s_cross_np: cross-tabulate counts and percents of unique values, including missing-data, in 2 or 3 variables

s_mode: statistical mode

s_s: tabulate summary statistics

s_unique: tabulate counts and percents of unique values, including missing-data, in vectors

c_assert: check assertions about data