c(person(c("Jason", "P."), "Becker", role = c("ctb"),
email = "jason+sitemail@jbecker.co"),
person(c("Jared", "E."), "Knowles", role=c("aut", "cre"),
email="jknowles@gmail.com"))
Collection of convenience functions to make working with
administrative records easier and more consistent. Includes functions to
clean strings, identify cutpoints, and quickly combine shapefiles and
dataframes for plotting. Includes four alternative themes for ggplot2 as
well as a wrapper for exporting graphics for inclusion in MS Office
products. Also includes three example datasets of administrative education
records for learning how to process records with errors.
stringr, maptools, grid, arm, data.table, memisc
'age_calc.R' 'autoplot.lm.R' 'cleanTex.R' 'cutoff.R'
'decomma.R' 'defac.R' 'destring.R' 'dropbox_source.R'
'eeptools.R' 'lags.R' 'mapfunctions.R' 'max_mis.R' 'modsims.R'
'moves_calc.R' 'plotForWord.R' 'remove_char.R' 'statamode.R'
'theme_dpi.R' 'theme_dpi_map.R' 'theme_dpi_map2.R'
'theme_dpi_mapPNG.R' 'thresh.R'
Jason P. Becker [ctb],
Jared E. Knowles [aut, cre]

Convenience Functions for Education Data
Collection of convenience functions to make working with
administrative records easier and more consistent. Includes functions to
clean strings, identify cutpoints, and quickly combine shapefiles and
dataframes for plotting. Includes four alternative themes for ggplot2. Also
includes three example datasets of administrative education records for
learning how to process records with errors.
maptools, grid, arm, data.table, vcd, memisc, rgeos
reshape, sp, plyr, mapproj, testthat, maps, stringr, knitr,
rmarkdown, MASS

Collection of convenience functions to make working with
administrative records easier and more consistent. Includes functions to
clean strings, identify cut points, and quickly combine shapefiles and
data frames for plotting. Also includes three example data sets of
administrative education records for learning how to process records with
errors.

Collection of convenience functions to make working with
administrative records easier and more consistent. Includes functions to
clean strings, and identify cut points. Also includes three example data
sets of administrative education records for learning how to process records
with errors.
reshape, plyr, testthat, stringr, knitr, rmarkdown, MASS