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kutils (version 1.0)

Project Management Tools

Description

Tools for data importation, recoding, and inspection that are used at the University of Kansas Center for Research Methods and Data Analysis. There are functions to create new project folders, R code templates, create uniquely named output directories, and to quickly obtain a visual summary for each variable in a data frame. The main feature here is the systematic implementation of the "variable key" framework for data importation and recoding. We are eager to have community feedback about the variable key and the vignette about it.

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Version

Install

install.packages('kutils')

Monthly Downloads

13,877

Version

1.0

License

GPL-2

Maintainer

Paul Johnson

Last Published

May 19th, 2017

Functions in kutils (1.0)

Keep only alpha-numeric symbols

Set missing values

Check and Clean data.frame for usage with variable key functions

colnamesReplace

Replace column names with new names from a named vector

deleteBogusRows

Remove rows in which the proportion of missing data exceeds a threshold.

Discern nesting pattern of SEM coefficients

deleteBogusColumns

Remove columns in which the proportion of missing data exceeds a threshold.

A variable is transformed in an indicated way

Compare observed values with the values listed (presumably from a variable key).

Convert nothing to R missing(NA).

Smoking, Happiness, and other survey responses

Delete multiple slashes, replace with one

Delete trailing slash

Convert the variable key into a keylist structure for use in keyApply

Reverse the levels in a factor

If a numeric variable has only integer values, then make it an integer.

Cuts a string at a specified linewidth, trying to align cut with a separator

Update packages, spot new dependencies, and install them

Create a graphics device

dir.create.unique

Create a uniquely named directory. Appends number & optionally date to directory name.

Creates Structural Equation Modeling Tables

apply a vector of replacements, one after the other.

Reduce each in a vector of strings to a given length

Text that is to be included as content in documents is cleaned (escaped) to prevent errors

Create project directories, initialize a git repo, create README.md ChangeLog, and R template file in R directory

Percentage tables for Likert Scale variables

convert a key object from long to wide format

read file after deducing file type from suffix.

Checks a variable key for possible errors.

Diagnose accuracy of result from applying variable key to data

Create variable key template

Update a key in light of a new data frame (add variables and values)

print.keyDiagnostic

Print the "changes" component of a keyDiagnostic object

is.data.frame.simple

Check if a data frame is a simple collection of columns (no lists or matrices within)

Apply variable key to data frame (generate recoded data frame)

Compares a key provided to keyUpdate with the return of keyUpdate

Import a file and clean up for use as variable key

Remove elements if they are in a target vector, possibly replacing with NA

Insert 0's in the front of existing digits or characters so that all elements of a vector have the same number of characters.

Show variables, one column at a time.

How many stars would we need for this p value?

Insert "\n" after the k'th character in a string. This IS vectorized, so can receive just one or many character strings in a vector.

save file after deducing type from suffix

Convert a key object from wide to long format

Convert leading or trailing white space and tab characters to nothing.