CSV (Comma Separated Values) is a widely used format for logging flight, sensor, and machine data. It is human-readable, editable with spreadsheets, and compatible with practically any data analysis tool.

Nominal is the leading platform for operationalizing test data.

This guide describes an automatable pipeline for uploading CSV files to Nominal.

Connect to Nominal

There are two primary ways of authenticating the Nominal Client. The first is to use a profile stored on disk, and the second is to use a token directly.

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$ nom config profile add default
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# Alternatively, if `nom` is missing from the path:
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$ python -m nominal config profile add default

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from nominal.core import NominalClient
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client = NominalClient.from_profile("default")
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# Get details about the currently logged-in user to validate authentication
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# Will display an object like: `User(display_name='your_email@your_company.com', ...)`
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print(client.get_user())

$
nom config migrate
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# Or, if `nom` is missing from your path:
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python -m nominal config migrate

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from nominal.core import NominalClient
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# Get an instance of the client using provided credentials
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client = NominalClient.from_token("<insert api key>")
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# Get details about the currently logged-in user to validate authentication
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# Will display an object like: `User(display_name='your_email@your_company.com', ...)`
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print(client.get_user())

Download sample data

For convenience and educational purposes, Nominal hosts test sample data on the Nominal Hugging Face account.

Let’s download a 1000 rows of data generated in the X-Plane flight simulator.

We’ll use the popular Polars library to download and inspect the data. Polars is installed automatically as part of the nominal Python library.

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import polars as pl
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df = pl.read_csv('hf://datasets/nominal-io/frosty-flight/frosty_flight_1k_rows.csv')
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df.write_csv('frosty_flight_1k_rows.csv')
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df.head().select(df.columns[:6])

Upload your data to Nominal

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from nominal.core import NominalClient
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client = NominalClient.from_profile("default")  # replace with your profile name
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dataset = client.create_dataset('Frosty Flight')
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dataset.add_tabular_data(
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    'frosty_flight_1k_rows.csv',
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    timestamp_column = 'source_time',
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    timestamp_type = 'iso_8601',
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)
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print('Uploaded dataset:', dataset.rid)

Equivalently, since your CSV is already loaded in the Polars dataframe df, you can upload it with the upload_dataframe() method:

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from nominal.thirdparty.pandas import upload_dataframe
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dataset = upload_dataframe(
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    client,
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    df.to_pandas(),
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    "name",
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    timestamp_column='source_time',
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    timestamp_type='iso_8601'
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)
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print('Uploaded dataset:', dataset.rid)

After upload, navigate to Nominal’s Datasets page (login required). You’ll see your CSV at the top!