upload_dataframe

nominal.thirdparty.pandas.upload_dataframe(client: NominalClient, df: DataFrame, name: str, timestamp_column: str, timestamp_type: Iso8601 | Epoch | Relative | Custom | Literal['iso_8601', 'epoch_picoseconds', 'epoch_nanoseconds', 'epoch_microseconds', 'epoch_milliseconds', 'epoch_seconds', 'epoch_minutes', 'epoch_hours', 'epoch_days'], description: str | None = None, channel_name_delimiter: str | None = None, *, wait_until_complete: bool = True, labels: Sequence[str] = (), properties: Mapping[str, str | float] | None = None, tag_columns: Mapping[str, str] | None = None, tags: Mapping[str, str] | None = None) → Dataset

Create a dataset in the Nominal platform from a pandas.DataFrame.

Parameters:

• client – Client instance to use for creating the dataset

• df – Dataframe to create a dataset from

• name – Name of the dataset to create, as well as filename for the uploaded “file”.

• timestamp_column – Name of the column containing timestamp information for the dataframe

• timestamp_type – Type of the timestamp column, e.g. epoch_seconds, iso8601, etc.

• description – Description of the dataset to create

• channel_name_delimiter – Delimiter to use for folding channel view to a tree view.

• wait_until_complete – If true, wait until all data has been ingested successfully before returning

• labels – String labels to apply to the created dataset

• properties – String or numeric properties for the created dataset. Integers are stored as floats.

• tag_columns – Mapping of column name => tag key to apply to the respective rows of data

• tags – Mapping of key-value pairs to apply uniformly as tags to all data within the dataframe.

Returns:

Created dataset

Raises:

TypeError – If a property value is a boolean or is not a string, integer, or float.