preprocess: Standardize Variables, Handle Dates, and Remove Bad Columns
In jesse-smith/coviData: COVID-19 Data Munging Tools for the Shelby County Health Department
preprocess R Documentation
Standardize Variables, Handle Dates, and Remove Bad Columns
Description
preprocess standardizes column names, converts variables to the
appropriate data types (including oddly formatted dates/datetimes), and
removes empty or constant columns.
Usage
preprocess(data, na_constant = TRUE)
Arguments
data
A dataframe(-like) object
na_constant
Should NA values be considered when deciding
whether a column is constant? The default is TRUE, which will
keep columns that only have 1 unique non-missing value.
Value
A processed tibble
jesse-smith/coviData documentation built on Jan. 14, 2023, 11:08 a.m.
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| preprocess | R Documentation |
Standardize Variables, Handle Dates, and Remove Bad Columns
Description
preprocess standardizes column names, converts variables to the
appropriate data types (including oddly formatted dates/datetimes), and
removes empty or constant columns.
Usage
preprocess(data, na_constant = TRUE)
Arguments
data |
A dataframe(-like) object |
na_constant |
Should |
Value
A processed tibble
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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