The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

dataprep: Efficient and Flexible Data Preprocessing Tools

Efficiently and flexibly preprocess data using a set of data filtering, deletion, and interpolation tools. These data preprocessing methods are developed based on the principles of completeness, accuracy, threshold method, and linear interpolation and through the setting of constraint conditions, time completion & recovery, and fast & efficient calculation and grouping. Key preprocessing steps include deletions of variables and observations, outlier removal, and missing values (NA) interpolation, which are dependent on the incomplete and dispersed degrees of raw data. They clean data more accurately, keep more samples, and add no outliers after interpolation, compared with ordinary methods. Auto-identification of consecutive NA via run-length based grouping is used in observation deletion, outlier removal, and NA interpolation; thus, new outliers are not generated in interpolation. Conditional extremum is proposed to realize point-by-point weighed outlier removal that saves non-outliers from being removed. Plus, time series interpolation with values to refer to within short periods further ensures reliable interpolation. These methods are based on and improved from the reference: Liang, C.-S., Wu, H., Li, H.-Y., Zhang, Q., Li, Z. & He, K.-B. (2020) <doi:10.1016/j.scitotenv.2020.140923>.

Version: 0.1.5
Depends: R (≥ 3.5.0)
Imports: ggplot2, scales, foreach, doParallel, dplyr, reshape2, data.table, zoo
Suggests: knitr, rmarkdown
Published: 2022-01-15
DOI: 10.32614/CRAN.package.dataprep
Author: Chun-Sheng Liang, Hao Wu, Hai-Yan Li, Qiang Zhang, Zhanqing Li, Ke-Bin He, Lanzhou University, Tsinghua University
Maintainer: Chun-Sheng Liang <liangchunsheng at lzu.edu.cn>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: dataprep results

Documentation:

Reference manual: dataprep.pdf
Vignettes: dataprep: data preprocessing and plots

Downloads:

Package source: dataprep_0.1.5.tar.gz
Windows binaries: r-devel: dataprep_0.1.5.zip, r-release: dataprep_0.1.5.zip, r-oldrel: dataprep_0.1.5.zip
macOS binaries: r-release (arm64): dataprep_0.1.5.tgz, r-oldrel (arm64): dataprep_0.1.5.tgz, r-release (x86_64): dataprep_0.1.5.tgz, r-oldrel (x86_64): dataprep_0.1.5.tgz
Old sources: dataprep archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=dataprep to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.