Перейти к файлу
Giorgi 5cbf4b6fa4 added .js suffixes. #158 2022-03-30 18:29:33 +04:00
.github Python port of the salary data example (#120) 2021-12-01 16:35:07 -05:00
R added vignettes, fixes to summarize that allow parameterized summary expressions 2022-03-27 22:17:34 -05:00
data Added binary data, example visualizations 2022-02-15 20:01:34 -06:00
data-raw Added binary data, example visualizations 2022-02-15 20:01:34 -06:00
datamations made datamations as npm package, wrote tests and made the whole code a single bundle. #158 2022-03-30 18:12:22 +04:00
dist made datamations as npm package, wrote tests and made the whole code a single bundle. #158 2022-03-30 18:12:22 +04:00
inst added .js suffixes. #158 2022-03-30 18:29:33 +04:00
man readme updates 2022-03-28 22:04:02 -05:00
notebooks Groupby two columns (#127) 2021-12-09 20:53:00 -05:00
renv will added 2022-03-16 12:34:50 +04:00
sandbox updated quantile specs 2022-03-23 20:57:42 -05:00
tests Styler 2021-12-13 12:16:53 -05:00
vignettes moving new vignettes to the correct branch for proper PR 2022-03-28 22:08:08 -05:00
.Rbuildignore Ignore python file in pkg build 2021-12-13 12:16:08 -05:00
.Rprofile Set up renv 2021-04-06 09:50:10 -04:00
.gitignore made datamations as npm package, wrote tests and made the whole code a single bundle. #158 2022-03-30 18:12:22 +04:00
DESCRIPTION will added 2022-03-16 12:34:50 +04:00
LICENSE Add MIT license 2021-07-15 10:29:03 -04:00
LICENSE.md Add MIT license 2021-07-15 10:29:03 -04:00
NAMESPACE R cmd check fixes 2021-06-15 16:18:13 -04:00
PythonSettings.json Groupby two columns (#127) 2021-12-09 20:53:00 -05:00
README.Rmd readme updates 2022-03-28 22:04:02 -05:00
README.md readme new md file 2022-03-28 22:20:48 -05:00
_pkgdown.yml data reference added in pkgdown yaml 2022-02-15 21:06:33 -06:00
app.R Add shiny app for datamation stages 2021-05-11 10:19:48 -04:00
azure-pipelines.yml Update azure-pipelines.yml for Azure Pipelines 2021-04-30 22:28:10 -04:00
datamations.Rproj Rename package and rproj file for consistency 2021-04-05 18:11:07 -04:00
package-lock.json will added 2022-03-16 12:34:50 +04:00
renv.lock Update renv 2021-12-08 13:43:23 -05:00
setup.py Python port of the salary data example (#120) 2021-12-01 16:35:07 -05:00

README.md

datamations

R-CMD-check

datamations is a framework for the automatic generation of explanation of the steps of an analysis pipeline. It automatically turns code into animations, showing the state of the data at each step of an analysis.

For more information, please visit the package website, which includes additional examples, defaults and conventions, and more.

Installation

You can install datamations from GitHub with:

# install.packages("devtools")
devtools::install_github("microsoft/datamations")

Usage

To get started, load datamations and dplyr:

A datamation shows a plot of what the data looks like at each step of a tidyverse pipeline, animated by the transitions that lead to each state. The following shows an example taking the built-in small_salary data set, grouping by Degree, and calculating the mean Salary.

First, define the code for the pipeline, then generate the datamation with datamation_sanddance():

library(datamations)
library(dplyr)

"small_salary %>% 
  group_by(Degree) %>%
  summarize(mean = mean(Salary))" %>%
  datamation_sanddance()

datamations supports the following dplyr functions:

  • group_by() (up to three grouping variables)
  • summarize()/summarise() (limited to summarizing one variable)
  • filter()
  • count()/tally