06-Sharing-all-your-analysis.Rmd

---
title: "06-Share all your analysis"
output:
  dcTemplate::dc_lesson_template:
    fig_width: 6
    fig_height: 6
    highlight: pygments
---

Now that we have learned how to work with a dockerfile, we can send all our analysis to a collaborator. 
We will share an image that contains all the dependencies that we need to run our analysis, the data and the analysis.

We will build this image via a dockerfile. Let's start with the basic verse rocker image we used before. 
This time we want to have a specific R version (3.3.2), which the developers make possible by tagging the images with the version.
See all available tags for the `rocker/verse` image [here](https://hub.docker.com/r/rocker/verse/tags/). The version tag is very
useful when you want your analysis to be reproducible.

```
FROM rocker/verse:3.3.2
```

As part of our analysis, we will use the gapminder data. We will need to install this package into our docker image.
Let's modify our dockerfile to install this package. 

```
RUN R -e "install.packages('gapminder', repos = 'http://cran.us.r-project.org')"
```

Now we just need to write our analysis and add it to our dockerfile.

For this analysis, we will create a plot of life expectancy vs. gdp per capita. 

On a new R script let's write the following analysis. 

```{r}
library(ggplot2)
library(gapminder)

life_expentancy_plot <- ggplot(data = gapminder) +
  geom_point(aes(x = lifeExp, y = gdpPercap, colour = continent))
```

We will save this r script as analysis.R and add it to our dockerfile.

```
ADD analysis.R /home/rstudio/
```

Now we can build the image and check that we have everything we want to share with our collaborator. 

```
docker build -t my-analysis .
```

Our analysis will appear on the list of images. 

```
docker images
```

Launch your new image and check you have everything you want to include:

```
docker run -dp 8787:8787 my-analysis
```

Great! our analysis script is there and gapminder is installed. 

Now we can push our analysis to dockerhub.

On dockerhub click on *Create Repository*.
Choose a name (e.g. gapminder_my_analysis) and a description for your repository and click *Create*.

Log into the Docker Hub from the command line
```{}
docker login --username=yourhubusername
```
just with your own user name that you used for the account.
Enter your password when prompted. 

Check the image ID using

```{}
docker images
```
and what you will see will be similar to
```{}
REPOSITORY                         TAG                 IMAGE ID            CREATED             SIZE
my-analysis                      latest              dc63d4790eaa        2 minutes ago       3.164 GB
```

and tag your image
```{}
docker tag dc63d4790eaa yourhubusername/gapminder_my_analysis:firsttry
```

Push your image to the repository you created
```{}
docker push yourhubusername/gapminder_my_analysis
```

Your image is now available for everyone to use.

Now your collaborator can download your image. 

Your collaborator should write on their command line:

```
docker pull yourhubusername/gapminder_my_analysis:firsttry
```

They now have the image of your analysis.


Click to go back to the [main page](http://jsta.github.io/r-docker-tutorial/).