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dataPreparation  

Automated Data Preparation
View on CRAN: Click here


Download and install dataPreparation package within the R console
Install from CRAN:
install.packages("dataPreparation")

Install from Github:
library("remotes")
install_github("cran/dataPreparation")

Install by package version:
library("remotes")
install_version("dataPreparation", "1.1.2")



Attach the package and use:
library("dataPreparation")
Maintained by
Emmanuel-Lin Toulemonde
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-07-07
Latest Update: 2025-09-03
Description:
Do most of the painful data preparation for a data science project with a minimum amount of code; Take advantages of 'data.table' efficiency and use some algorithmic trick in order to perform data preparation in a time and RAM efficient way.
How to cite:
Emmanuel-Lin Toulemonde (2017). dataPreparation: Automated Data Preparation. R package version 1.1.2, https://cran.r-project.org/web/packages/dataPreparation. Accessed 07 Jun. 2026.
Previous versions and publish date:
0.1 (2017-07-07 12:14), 0.2 (2017-08-18 10:05), 0.3.2 (2017-10-25 20:59), 0.3.4 (2017-12-20 11:37), 0.3.5 (2018-02-16 16:29), 0.3.6 (2018-05-11 16:35), 0.3.7 (2018-08-20 18:40), 0.3.8 (2018-10-17 17:30), 0.3.9 (2019-01-02 12:20), 0.4.0 (2019-03-25 16:43), 0.4.1 (2019-07-19 15:30), 0.4.2 (2019-11-14 18:00), 0.4.3 (2020-02-12 15:20), 1.0.0 (2020-11-13 12:50), 1.0.1 (2020-12-16 01:00), 1.0.2 (2021-09-20 11:30), 1.0.3 (2021-11-19 21:00), 1.0.4 (2021-12-21 09:30), 1.0.5 (2022-07-15 12:10), 1.1.1 (2023-07-04 15:13)
Other packages that cited dataPreparation R package
View dataPreparation citation profile
Other R packages that dataPreparation depends, imports, suggests or enhances
Complete documentation for dataPreparation
Functions, R codes and Examples using the dataPreparation R package
Some associated functions: adult . aggregate_by_key . as.POSIXct_fast . build_bins . build_date_factor . build_encoding . build_scales . build_target_encoding . compute_probability_ratio . compute_weight_of_evidence . data_preparation_news . date_format_unifier . description . fast_discretization . fast_filter_variables . fast_handle_na . fast_is_equal . fast_round . fast_scale . find_and_transform_dates . find_and_transform_numerics . generate_date_diffs . generate_factor_from_date . generate_from_character . generate_from_factor . get_most_frequent_element . identify_dates . messy_adult . one_hot_encoder . prepare_set . remove_percentile_outlier . remove_rare_categorical . remove_sd_outlier . same_shape . set_as_numeric_matrix . set_col_as_character . set_col_as_date . set_col_as_factor . set_col_as_numeric . shape_set . target_encode . tiny_messy_adult . un_factor . which_are_bijection . which_are_constant . which_are_in_double . which_are_included . 
Some associated R codes: aggregate.R . data_set.R . dates_manipulations.R . description.R . discretization.R . factor_manipulation.R . fast_posixct.R . generate_from_character.R . generate_from_date.R . generate_from_factor.R . generic_functions.R . numeric_manipulations.R . on_load.R . prepare_set.R . row_filtering.R . same_shape.R . scale.R . set_col_as.R . shape_set.R . which_functions.R .  Full dataPreparation package functions and examples
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