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https://github.com/rolkra/explore
R package that makes basic data exploration radically simple (interactive data exploration, reproducible data science)
https://github.com/rolkra/explore
data-exploration data-visualisation decision-trees eda r rmarkdown shiny tidy
Last synced: about 1 month ago
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R package that makes basic data exploration radically simple (interactive data exploration, reproducible data science)
- Host: GitHub
- URL: https://github.com/rolkra/explore
- Owner: rolkra
- License: other
- Created: 2018-04-06T20:54:05.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2024-04-09T13:09:26.000Z (7 months ago)
- Last Synced: 2024-04-09T20:19:32.938Z (7 months ago)
- Topics: data-exploration, data-visualisation, decision-trees, eda, r, rmarkdown, shiny, tidy
- Language: R
- Homepage: https://rolkra.github.io/explore/
- Size: 29.4 MB
- Stars: 201
- Watchers: 11
- Forks: 24
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- jimsghstars - rolkra/explore - R package that makes basic data exploration radically simple (interactive data exploration, reproducible data science) (R)
README
# explore 
[](https://github.com/rolkra/explore/actions/workflows/R-CMD-check.yaml)
[](https://CRAN.r-project.org/package=explore)
[](https://CRAN.r-project.org/package=explore)
Simplifies Exploratory Data Analysis:
- **Interactive data exploration** using `explore()`
- Generate an **automated report** of your data (or patterns in your data) using `report()`
- **Manual exploration** using `explore()`, `describe()`, `explain_*()`, `abtest()`, ...
``` r
# install from CRAN
install.packages("explore")
```
## Examples
``` r
# interactive data exploration
library(explore)
beer <- use_data_beer()
beer |> explore()
```
``` r
# describe data
beer |> describe()
```
```
# A tibble: 11 × 8
variable type na na_pct unique min mean max
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
```
``` r
# 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)
```
``` r
# explore manually with color and interactive
beer |>
explore(sugar_g_100ml, color = "gold") |>
interact()
```
## Get started
* [Get started with {explore}](https://rolkra.github.io/explore/articles/explore.html)
* [Explore penguins (tidy-data)](https://rolkra.github.io/explore/articles/explore_penguins.html)
* [Explore titanic (count-data)](https://rolkra.github.io/explore/articles/explore_titanic.html)
* [Explain a target using machine learning](https://rolkra.github.io/explore/articles/explain.html)
* [Generate a report of all variables in the data](https://rolkra.github.io/explore/articles/report.html)
* [Generate a report of all patterns in the data](https://rolkra.github.io/explore/articles/report-target.html)
* [Datasets in {explore}](https://rolkra.github.io/explore/articles/data.html)
* [A/B testing](https://rolkra.github.io/explore/articles/abtest.html)
* and more ...