Package: conjurer 1.7.0

conjurer: A Parametric Method for Generating Synthetic Data

Generates synthetic data distributions to enable testing various modelling techniques in ways that real data does not allow. Noise can be added in a controlled manner such that the data seems real. This methodology is generic and therefore benefits both the academic and industrial research.

Authors:Sidharth Macherla [aut, cre]

conjurer_1.7.0.tar.gz
conjurer_1.7.0.zip(r-4.7-any)conjurer_1.7.0.zip(r-4.6-any)conjurer_1.7.0.zip(r-4.5-any)
conjurer_1.7.0.tgz(r-4.6-any)conjurer_1.7.0.tgz(r-4.5-any)
conjurer_1.7.0.tar.gz(r-4.7-any)conjurer_1.7.0.tar.gz(r-4.6-any)
conjurer_1.7.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
conjurer/json (API)

# Install 'conjurer' in R:
install.packages('conjurer', repos = c('https://sidharthmacherla.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/sidharthmacherla/conjurer/issues

On CRAN:

Conda:

dummy-data-generatorsynthetic-datasynthetic-data-generationsynthetic-dataset-generationsynthetic-tabular-data

4.95 score 9 stars 4 scripts 393 downloads 11 exports 8 dependencies

Last updated from:7aabe3eb09. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develNOTE101
source / vignettesOK174
linux-releaseNOTE104
macos-releaseNOTE177
macos-oldrelNOTE171
windows-develNOTE55
windows-releaseNOTE74
windows-oldrelNOTE62
wasm-releaseOK80

Exports:buildCustbuildHierarchybuildIdbuildModelDatabuildNamesbuildNumbuildParetobuildPatternbuildProdextractDfgenTrans

Dependencies:askpasscurlhttrjsonlitemimeopensslR6sys

Introduction to conjurer
Summary | Continuous data | Description | Usage | String data | Alpha Numeric data | Sequencial data | Graph data | Relationship data
Rendered fromintroduction_to_conjurer.Rmdusingknitr::rmarkdown

Last update: 2023-04-22
Started: 2020-01-07

Industry Example
Overview | Steps to build synthetic data | Installation | Build customers | Build customer names | Assign customer name to customer ID | Build customer age | Assign customer age to customer ID | Build customer phone number | Assign customer phone number to customer ID | Build products | Build product hierarchy | Build transactions | Build final data | Allocate customers to transactions | Allocate products to product hierarchy | Allocate products to transactions | Combine customers and transactions data | Final data | Interpret the results
Rendered fromindustry_example.Rmdusingknitr::rmarkdown

Last update: 2023-04-22
Started: 2023-04-22