62 строки
1.8 KiB
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62 строки
1.8 KiB
Markdown
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<!-- README.md is generated from README.Rmd. Please edit that file -->
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# datamations
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<!-- badges: start -->
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[](https://github.com/microsoft/datamations/actions)
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<!-- badges: end -->
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datamations is a framework for the automatic generation of explanation
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of the steps of an analysis pipeline. It automatically turns code into
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animations, showing the state of the data at each step of an analysis.
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For more information, please visit the [package
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website](https://microsoft.github.io/datamations/), which includes
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[additional
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examples](https://microsoft.github.io/datamations/articles/Examples.html),
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[defaults and
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conventions](https://microsoft.github.io/datamations/articles/details.html),
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and more.
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## Installation
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You can install datamations from GitHub with:
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``` r
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# install.packages("devtools")
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devtools::install_github("microsoft/datamations")
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```
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## Usage
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To get started, load datamations and dplyr:
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A datamation shows a plot of what the data looks like at each step of a
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tidyverse pipeline, animated by the transitions that lead to each state.
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The following shows an example taking the built-in `small_salary` data
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set, grouping by `Degree`, and calculating the mean `Salary`.
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First, define the code for the pipeline, then generate the datamation
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with `datamation_sanddance()`:
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``` r
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library(datamations)
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library(dplyr)
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"small_salary %>%
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group_by(Degree) %>%
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summarize(mean = mean(Salary))" %>%
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datamation_sanddance()
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```
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<img src="man/figures/README-mean_salary_grouped_degree.gif" width="80%" />
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datamations supports the following `dplyr` functions:
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- `group_by()` (up to three grouping variables)
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- `summarize()`/`summarise()` (limited to summarizing one variable)
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- `filter()`
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- `count()`/`tally`
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