Stata in DXJupyterLab

Using Stata via DXJupyterlab, working with project files, and creating datasets with Spark.

Stata is a powerful statistics package for data science. Stata commands and functionality can be accessed on the DNAnexus Platform via stata_kernel, in Jupyter notebooks.

Before You Begin

Project License Requirement

On the DNAnexus Platform, use the DXJupyterLab app to create and edit Jupyter notebooks.

Note that you can only run this app within a project that’s billed to an account with a license that allows the use of both DXJupyterLab and HTTPS apps. Contact DNAnexus Sales if you need to upgrade your license.

Note also that DXJupyterLab is accessible to all users of the UK Biobank Research Analysis Platform and the Our Future Health Trusted Research Environment. A license is required to access DXJupyterLab on the DNAnexus Platform. Contact DNAnexus Sales for more information.

Stata License Requirement

To use Stata on the DNAnexus Platform, you need a valid Stata license. Before launching Stata in a project, you must save your license details according to the instructions below in a plain text file with the extension .json, then upload this file to the project’s root directory. You only need to do this once per project.

Creating a Stata License Details File

Start by creating the file in a text editor, including all the fields shown here, where <user> is your DNAnexus username, and<organization>is the org of which you're a member:

{
  "license": {
    "serialNumber": "<Serial number from Stata>",
    "code": "<Code from Stata>",
    "authorization": "<Authorization from Stata>",
    "user": "<Registered user line 1>",
    "organization": "<Registered user line 2>"
  }
}

Save the file according to the following format, where <username> is your DNAnexus username: .stataSettings.user-<username>.json

Some operating systems may not support the naming of files with a "." as the first character. If this is the case, you can rename the .json file after uploading it to your project by hovering over the name of your file and clicking the pencil icon that appears.

Uploading the Stata License Details File

Open the project in which you want to use Stata. Upload the Stata license details file to the project’s root directory by going to your project's Manage tab, clicking on the Add button on the upper right, and then selecting the Upload data option.

Secure Indirect Format Option for Shared Projects

When working in a shared project, you can take an additional step to avoid exposing your Stata license details to project collaborators.

Create a private project. Then create and save a Stata license details file in that project’s root directory, as per the instructions above.

Within the shared project, create and save a Stata license details file in this format, where project-yyyy is the name of the private project, and file-xxxx is the license details file ID, in that private project:

{ 
      "licenseFile": {
            "$dnanexus_link": {
                  "id": "file-xxxx",
                  "project": "project-yyyy"
            }
      }
}

Note that when working on the Research Analysis Platform, you can only create a private credentials project from the Research Analysis Platform Projects page.

Launching DXJupyterLab

1. Open the project in which you want to use Stata. From within the project's Manage tab, click the Start Analysis button.

2. Select the app DXJupyterLab with Python, R, Stata, ML.

3. Click the Run Selected button. Note that if you haven't run this app before, you'll be prompted to install it. Next, you’ll be taken to the Run Analysis screen.

4. On the Run Analysis screen, open the Analysis Inputs tab and click the Stata settings file button.

5. Add your Stata settings file as an input. This is the .json file you created, containing your Stata license details.

6. In the Common section at the bottom of the Analysis Inputs pane, open the Feature dropdown menu and select Stata.

7. Click the Start Analysis button at the top right corner of the screen. This will launch the DXJupyterLab app, and take you to the project's Monitor tab, where you can monitor the app's status as it loads.

Note: The app can take some time to load and start running.

Once the analysis starts, you’ll see the notification "Running" appear under the name of the app.

Opening JupyterLab

Click the Monitor tab heading. This will open a list of running and past jobs. Jobs are shown in reverse chronological order, with the most recently launched at the top. The topmost row should show the job you’ve just launched. To open the job and enter the JupyterLab interface, click on the URL shown under Worker URL.

If you do not see the worker URL, click on the name of the job in the Monitor page.

Using Stata Within JupyterLab

Within the JupyterLab interface, open the DNAnexus tab shown at the left edge of the screen.

The location of the DNAnexus tab within the JupyterLab interface.

Open a new Stata notebook by clicking the Stata tile in the Notebooks section.

Working with Project Files

You can download DNAnexus data files to DXJupyterLab container from Stata notebook with:

!dx download project-xxxx:file-yyy

Data files in the current project can also be accessed using a /mnt/project folder from a Stata notebook as follows: To load a DTA file:

use /mnt/project/<path>/data_in.dta

To load a CSV file:

import delimited /mnt/project/<path>/data_in.csv

To write a DTA file to the DXJupyterLab container:

save data_out

To write a CSV file to the DXJupyterLab container:

export delimited data_out.csv

To upload a data file from the DXJupyterLab container to the project, use the following command in a Stata notebook:

!dx upload <file> --destination=<destination>

Alternatively, open a new Launcher tab, open Terminal, and run:

dx upload <file> --destination=<destination>

Note that /mnt/project directory is read-only, so trying to write to it results in an error.

Creating a Stata Dataset with Spark

DXJupyterLab spark cluster app can be used to query and filter DNAnexus datasets returning a PySpark DataFrame. PySpark Dataframe can be converted to a pandas DataFrame with:

pandas_df = spark_df.toPandas()

Pandas dataframe can be exported to CSV or Stata DTA files in the JupyterLab container with:

pandas_df.to_stata("data_out.dta")
pandas_df.to_csv("data_out.csv")

To upload a data file from the JupyterLab container to the DNAnexus project in the DXJupyterLab spark cluster app, use

%%bash
dx upload <file>

Once saved to the project, data files can be used in a DXJupyterLab Stata session using the instructions above.