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