data.table (>= 1.11), reshape2 (>= 1.4), scales (>= 1.0),
ggplot2 (>= 2.2), gridExtra (>= 2.3), rmarkdown (>= 1.10),
networkD3 (>= 0.4), stats, utils, tools, parallel

Automated data exploration process for analytic tasks and predictive modeling, so
that users could focus on understanding data and extracting insights. The package scans and
analyzes each variable, and visualizes them with typical graphical techniques. Common
data processing methods are also available to treat and format data.

data.table (>= 1.12.8), reshape2 (>= 1.4.3), scales (>=
1.1.0), ggplot2, gridExtra, rmarkdown (>= 2.0), networkD3 (>=
0.4), stats, utils, tools, parallel

data.table (>= 1.13.4), reshape2 (>= 1.4.3), scales (>=
1.1.0), ggplot2, gridExtra, rmarkdown (>= 2.5), networkD3 (>=
0.4), stats, utils, tools, parallel

Generate Fake Data for Relational Databases
c(
person(
given = "Krystian", family = "Igras",
email = "krystian8207@gmail.com",
role = c("aut", "cre")
),
person(
given = "Kamil", family = "Wais",
email = "kamil.wais@gmail.com",
role = c("ctb")
),
person(
given = "Adam", family = "Foryś",
email = "adam.forys@gmail.com",
role = c("ctb")
),
person(
given = "Adam", family = "Leśniewski",
email = "alesniewski123@gmail.com",
role = c("ctb")
),
person(
given = "Paweł", family = "Kawski",
email = "pawel.kawski@gmail.com",
role = c("ctb")
)
)
Based on provided database description and/or database connection
generate data sample preserving source structure.
yaml, purrr, tidygraph, dplyr (>= 1.0.0), tibble, magrittr,
glue, R6
DBI, charlatan, stringr, stringi, rmarkdown, knitr, covr,
lintr, httr, mockery, testthat (>= 3.0.0), rcmdcheck
'DataFaker-package.R' 'simulate_char_col.R'
'simulate_num_col.R' 'simulate_int_col.R' 'simulate_lgl_col.R'
'simulate_dat_col.R' 'simulate_cols.R' 'simulate_tables.R'
'schema_utils.R' 'schema_deps.R' 'schema_conf.R'
'schema_source.R' 'schema_from_db.R' 'schema_from_list.R'
Krystian Igras [aut, cre],
Kamil Wais [ctb],
Adam Foryś [ctb],
Adam Leśniewski [ctb],
Paweł Kawski [ctb]