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explore

Simplifies Exploratory Data Analysis:

• Interactive data exploration using explore()
• Use AI to unveil hidden patterns in your data (xgboost, RF, logreg, DT)
• Generate an automated report of your data (or patterns in your data) using report()
• Manual exploration using explore(), describe(), explain_*(), abtest(), …
• 18 ready to use datasets for teaching & testing

# install from CRAN
install.packages("explore")

Examples

# interactive data exploration
library(explore)
beer <- use_data_beer()
beer |> explore()

# describe data
beer |> describe()

# A tibble: 11 × 8
   variable          type     na na_pct unique    min    mean    max
   <chr>             <chr> <int>  <dbl>  <int>  <dbl>   <dbl>  <dbl>
 1 name              chr       0    0      161   NA     NA      NA  
 2 brand             chr       0    0       29   NA     NA      NA  
 3 country           chr       0    0        3   NA     NA      NA  
 4 year              dbl       0    0        1 2023   2023    2023  
 5 type              chr       0    0        3   NA     NA      NA  
 6 color_dark        dbl       0    0        2    0      0.09    1  
 7 alcohol_vol_pct   dbl       2    1.2     35    0      4.32    8.4
 8 original_wort     dbl       5    3.1     54    5.1   11.3    18.3
 9 energy_kcal_100ml dbl      11    6.8     34   20     39.9    62  
10 carb_g_100ml      dbl      16    9.9     44    1.5    3.53    6.7
11 sugar_g_100ml     dbl      16    9.9     26    0      0.72    4.6

# explore data manually
beer |> explore(type)
beer |> explore(energy_kcal_100ml)
beer |> explore(energy_kcal_100ml, target = type)
beer |> explore(alcohol_vol_pct, energy_kcal_100ml, target = type)

# explore manually with color and interactive
beer |> 
  explore(sugar_g_100ml, color = "gold") |> 
  interact()

Get started

• Get started with {explore}
• Explore penguins (tidy-data)
• Explore titanic (count-data)
• Explain a target using machine learning
• Generate a report of all variables in the data
• Generate a report of all patterns in the data
• Datasets in {explore}
• A/B testing
• and more …

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.
Health stats visible at Monitor.