transform_missing: Identifies 'missingness' in a data frame by examining the...
In BigelowLab/flowcamr: flowcamr - R tools for FlowCam
Description
Identifies 'missingness' in a data frame by examining the value of the
test_col. If a given row's (test_col <= 0) & (test_col != NaN) the row
values are changed to NA.
Usage
1
2
transform_missing(x, test_col = "Count", replace = NA,
keep_col = c("Label", "Blob", "Count", "UserLabel"))
Arguments
x
a data.frame
test_col
the name of the column to test (!=0 and !=NaN)
replace
the value to use for the replacement
keep_col
the names of the columns to *not* change
the
transformed data frame
BigelowLab/flowcamr documentation built on May 5, 2019, 2:42 p.m.
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Description
Identifies 'missingness' in a data frame by examining the value of the test_col. If a given row's (test_col <= 0) & (test_col != NaN) the row values are changed to NA.
Usage
1 2 | transform_missing(x, test_col = "Count", replace = NA,
keep_col = c("Label", "Blob", "Count", "UserLabel"))
|
Arguments
x |
a data.frame |
test_col |
the name of the column to test (!=0 and !=NaN) |
replace |
the value to use for the replacement |
keep_col |
the names of the columns to *not* change |
the |
transformed data frame |
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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