8000 Version 0.0.1 accepted to CRAN by hanneoberman · Pull Request #30 · amices/ggmice · GitHub
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Version 0.0.1 accepted to CRAN #30

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Merged
merged 2 commits into from
Mar 17, 2022
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Version 0.0.1 accepted to CRAN #30

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d65d548
Update readme after CRAN acceptance
hanneoberman Mar 17, 2022
d5ecc75
Merge branch 'main' of https://github.com/hanneoberman/ggmice into main
hanneoberman Mar 17, 2022
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4 changes: 2 additions & 2 deletions CRAN-SUBMISSION
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@@ -1,3 +1,3 @@
Version: 0.0.1
Date: 2022-03-15 16:49:59 UTC
SHA: dcfcfa5a0bc6f945790ed2b5d3051eba7ff08161
Date: 2022-03-16 18:36:30 UTC
SHA: f3e7e2fcbf1516bda983f82159b30806c739d48f
14 changes: 10 additions & 4 deletions README.Rmd
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Expand Up @@ -24,13 +24,19 @@ set.seed(1)
[![Codecov test coverage](https://codecov.io/gh/amices/ggmice/branch/main/graph/badge.svg)](https://app.codecov.io/gh/amices/ggmice?branch=main)
<!-- badges: end -->

## Plotting package for incomplete and imputed data
## Visualizations for `mice` with `ggplot2`

The `ggmice` package enhances imputation package `mice` with `ggplot2` visualizations. See the [vignette](https://amices.org/ggmice/articles/ggmice.html) for an overview of `ggmice`'s functionalities.
Enhance a `mice` imputation workflow with visualizations for incomplete and/or imputed data. The plotting functions produce `ggplot` objects which may be easily manipulated or extended. Use `ggmice` to inspect missing data, develop imputation models, evaluate algorithmic convergence, or compare observed versus imputed data.

## Installation

You can install the development version of `ggmice` from [GitHub](https://github.com/amices) with:
You can install the latest `ggmice` release from [CRAN](https://cran.r-project.org/) with:

``` r
install.packages("ggmice")
```

Alternatively, you could install the development version of `ggmice` from [GitHub](https://github.com/amices) with:

``` r
# install.packages("devtools")
Expand All @@ -39,7 +45,7 @@ devtools::install_github("amices/ggmice")

## Example

Visualize missing data in an incomplete dataset, or evaluate imputed data against the observed data.
Visualize missing data in an incomplete dataset, or evaluate imputed data against the observed data.See the [`ggmice` vignette](https://amices.org/ggmice/articles/ggmice.html) for an overview of all functionalities.

```{r example}
# load the package and some data
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26 changes: 18 additions & 8 deletions README.md
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Expand Up @@ -15,17 +15,25 @@ experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](h
coverage](https://codecov.io/gh/amices/ggmice/branch/main/graph/badge.svg)](https://app.codecov.io/gh/amices/ggmice?branch=main)
<!-- badges: end -->

## Plotting package for incomplete and imputed data
## Visualizations for `mice` with `ggplot2`

The `ggmice` package enhances imputation package `mice` with `ggplot2`
visualizations. See the
[vignette](https://amices.org/ggmice/articles/ggmice.html) for an
overview of `ggmice`’s functionalities.
Enhance a `mice` imputation workflow with visualizations for incomplete
and/or imputed data. The plotting functions produce `ggplot` objects
which may be easily manipulated or extended. Use `ggmice` to inspect
missing data, develop imputation models, evaluate algorithmic
convergence, or compare observed versus imputed data.

## Installation

You can install the development version of `ggmice` from
[GitHub](https://github.com/amices) with:
You can install the latest `ggmice` release from
[CRAN](https://cran.r-project.org/) with:

``` r
install.packages("ggmice")
```

Alternatively, you could install the development version of `ggmice`
from [GitHub](https://github.com/amices) with:

``` r
# install.packages("devtools")
Expand All @@ -35,7 +43,9 @@ devtools::install_github("amices/ggmice")
## Example

Visualize missing data in an incomplete dataset, or evaluate imputed
data against the observed data.
data against the observed data.See the [`ggmice`
vignette](https://amices.org/ggmice/articles/ggmice.html) for an
overview of all functionalities.

``` r
# load the package and some data
Expand Down
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