Package: explore 1.3.3

explore: Simplifies Exploratory Data Analysis

Interactive data exploration with one line of code, automated reporting or use an easy to remember set of tidy functions for low code exploratory data analysis.

Authors:Roland Krasser [aut, cre]

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explore.pdf |explore.html✨
explore/json (API)
NEWS

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

Bug tracker:https://github.com/rolkra/explore/issues

Pkgdown site:https://rolkra.github.io

On CRAN:

data-explorationdata-visualisationdecision-treesedarmarkdownshinytidy

11.31 score 220 stars 1 packages 221 scripts 1.7k downloads 3 mentions 83 exports 82 dependencies

Last updated 3 months agofrom:088c0d16f2. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 04 2025
R-4.5-winOKFeb 04 2025
R-4.5-macOKFeb 04 2025
R-4.5-linuxOKFeb 04 2025
R-4.4-winOKFeb 04 2025
R-4.4-macOKFeb 04 2025
R-4.3-winOKFeb 04 2025
R-4.3-macOKFeb 04 2025

Exports:abtestadd_var_idadd_var_random_01add_var_random_catadd_var_random_dbladd_var_random_intadd_var_random_moonadd_var_random_starsignbalance_targetclean_varcount_pctcreate_data_abtestcreate_data_appcreate_data_buycreate_data_churncreate_data_emptycreate_data_esotericcreate_data_newslettercreate_data_personcreate_data_randomcreate_data_unfaircreate_notebook_exploredata_dict_mddecryptdescribedescribe_alldescribe_catdescribe_numdescribe_tbldrop_obs_ifdrop_obs_with_nadrop_var_by_namesdrop_var_low_variancedrop_var_no_variancedrop_var_not_numericdrop_var_with_naencryptexplain_forestexplain_logregexplain_treeexplain_xgboostexploreexplore_allexplore_barexplore_colexplore_corexplore_countexplore_densityexplore_shinyexplore_targetpctexplore_tblformat_num_autoformat_num_kMBformat_num_spaceformat_targetformat_typeget_colorget_nrowget_typeget_var_bucketsguess_cat_numinteractmix_colorplot_legend_targetpctplot_textpredict_targetreplace_na_withreportrescale01show_colorsimplify_texttotal_fig_heightuse_data_beeruse_data_diamondsuse_data_irisuse_data_mpguse_data_mtcarsuse_data_penguinsuse_data_starwarsuse_data_titanicuse_data_wordleweight_targetyyyymm_calc

Dependencies:askpassbase64encbslibcachemclicolorspacecommonmarkcpp11crayoncrosstalkcurldata.tabledigestdplyrDTevaluatefansifarverfastmapfontawesomeforcatsfsgenericsggplot2gluegridExtragtablehighrhtmltoolshtmlwidgetshttpuvhttrisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmeopensslpalmerpenguinspillarpkgconfigplotlypromisespurrrR6rappdirsRColorBrewerRcpprlangrmarkdownrpartrpart.plotsassscalesshinysourcetoolsstringistringrsystibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunxtableyaml

A/B test

Roland Krasser

Rendered fromabtest.Rmdusingknitr::rmarkdownon Feb 04 2025.

Last update: 2024-10-11
Started: 2023-10-04

Clean / Drop

Roland Krasser

Rendered fromclean-drop.Rmdusingknitr::rmarkdownon Feb 04 2025.

Last update: 2024-02-24
Started: 2024-02-24

Data

Roland Krasser

Rendered fromdata.Rmdusingknitr::rmarkdownon Feb 04 2025.

Last update: 2024-03-23
Started: 2023-10-04

Describe

Roland Krasser

Rendered fromdescribe.Rmdusingknitr::rmarkdownon Feb 04 2025.

Last update: 2023-10-04
Started: 2023-10-04

Explain

Roland Krasser

Rendered fromexplain.Rmdusingknitr::rmarkdownon Feb 04 2025.

Last update: 2024-02-24
Started: 2023-10-04

explore

Roland Krasser

Rendered fromexplore.Rmdusingknitr::rmarkdownon Feb 04 2025.

Last update: 2024-11-10
Started: 2019-05-13

Explore mtcars

Roland Krasser

Rendered fromexplore-mtcars.Rmdusingknitr::rmarkdownon Feb 04 2025.

Last update: 2024-04-15
Started: 2024-04-15

Explore penguins

Roland Krasser

Rendered fromexplore-penguins.Rmdusingknitr::rmarkdownon Feb 04 2025.

Last update: 2024-04-15
Started: 2024-04-15

Explore titanic

Roland Krasser

Rendered fromexplore-titanic.Rmdusingknitr::rmarkdownon Feb 04 2025.

Last update: 2024-04-15
Started: 2024-04-15

Predict

Roland Krasser

Rendered frompredict.Rmdusingknitr::rmarkdownon Feb 04 2025.

Last update: 2024-02-22
Started: 2023-10-06

Report target

Roland Krasser

Rendered fromreport-target.Rmdusingknitr::rmarkdownon Feb 04 2025.

Last update: 2023-10-06
Started: 2023-10-06

Report targetpct

Roland Krasser

Rendered fromreport-targetpct.Rmdusingknitr::rmarkdownon Feb 04 2025.

Last update: 2023-10-06
Started: 2023-10-06

Report variables

Roland Krasser

Rendered fromreport.Rmdusingknitr::rmarkdownon Feb 04 2025.

Last update: 2023-10-07
Started: 2023-10-06

Tips & tricks

Roland Krasser

Rendered fromtips-tricks.Rmdusingknitr::rmarkdownon Feb 04 2025.

Last update: 2024-09-15
Started: 2023-10-07

Readme and manuals

Help Manual

Help pageTopics
A/B testingabtest
A/B testing interactiveabtest_shiny
A/B testing comparing two meanabtest_targetnum
A/B testing comparing percent per groupabtest_targetpct
Add a variable id at first column in datasetadd_var_id
Add a random 0/1 variable to datasetadd_var_random_01
Add a random categorical variable to datasetadd_var_random_cat
Add a random double variable to datasetadd_var_random_dbl
Add a random integer variable to datasetadd_var_random_int
Add a random moon variable to datasetadd_var_random_moon
Add a random starsign variable to datasetadd_var_random_starsign
Balance target variablebalance_target
Check vector for low variancecheck_vec_low_variance
Clean variableclean_var
Adds percentage to dplyr::count()count_pct
Create data of A/B testingcreate_data_abtest
Create data appcreate_data_app
Create data buycreate_data_buy
Create data churncreate_data_churn
Create an empty datasetcreate_data_empty
Create data esotericcreate_data_esoteric
Create data newslettercreate_data_newsletter
Create data personcreate_data_person
Create data randomcreate_data_random
Create data unfaircreate_data_unfair
Generate a notebookcreate_notebook_explore
Cut a variablecut_vec_num_avg
Create a data dictionary Markdown filedata_dict_md
decrypt textdecrypt
Describe a dataset or variabledescribe
Describe all variables of a datasetdescribe_all
Describe categorical variabledescribe_cat
Describe numerical variabledescribe_num
Describe tabledescribe_tbl
Drop all observations where expression is truedrop_obs_if
Drop all observations with NA-valuesdrop_obs_with_na
Drop variables by namedrop_var_by_names
Drop all variables with low variancedrop_var_low_variance
Drop all variables with no variancedrop_var_no_variance
Drop all not numeric variablesdrop_var_not_numeric
Drop all variables with NA-valuesdrop_var_with_na
encrypt textencrypt
Explain a target using Random Forest.explain_forest
Explain a binary target using a logistic regression (glm). Model chosen by AIC in a Stepwise Algorithm ('MASS::stepAIC()').explain_logreg
Explain a target using a simple decision tree (classification or regression)explain_tree
Explain a binary target using xgboostexplain_xgboost
Explore a dataset or variableexplore
Explore all variablesexplore_all
Explore categorical variable using bar chartsexplore_bar
Explore data without aggregation (label + value)explore_col
Explore the correlation between two variablesexplore_cor
Explore count data (categories + frequency)explore_count
Explore density of variableexplore_density
Explore dataset interactiveexplore_shiny
Explore variable + binary target (values 0/1)explore_targetpct
Explore tableexplore_tbl
Format number as character string (auto)format_num_auto
Format number as character string (kMB)format_num_kMB
Format number as character string (space as big.mark)format_num_space
Format targetformat_target
Format type descriptionformat_type
Get predefined colorsget_color
Return type of variableget_type
Put variables into "buckets" to create a set of plots instead one large plotget_var_buckets
Return if variable is categorical or numericalguess_cat_num
Make a explore-plot interactiveinteract
Log conditionallog_info_if
Mix colorsmix_color
Plots a legend that can be used for explore_all with a binary targetplot_legend_targetpct
Plot a textplot_text
Plot a variable infoplot_var_info
Predict target using a trained model.predict_target
Replace NAreplace_na_with
Generate a report of all variablesreport
Rescales a numeric variable into values between 0 and 1rescale01
Show color vector as ggplotshow_color
Simplifies a text stringsimplify_text
Explore categorical variable + targettarget_explore_cat
Explore Nuberical variable + targettarget_explore_num
Get fig.height for RMarkdown-junk using explore_all()total_fig_height
Use the beer data setuse_data_beer
Use the diamonds data setuse_data_diamonds
Use the iris flower data setuse_data_iris
Use the mpg data setuse_data_mpg
Use the mtcars data setuse_data_mtcars
Use the penguins data setuse_data_penguins
Use the starwars data setuse_data_starwars
Use the titanic data setuse_data_titanic
Use the wordle data setuse_data_wordle
Weight target variableweight_target
Calculate with periods (format yyyymm)yyyymm_calc