upload_dataframe#
- nominal.thirdparty.pandas.upload_dataframe(client, df, name, timestamp_column, timestamp_type, description=None, channel_name_delimiter=None, *, wait_until_complete=True, labels=(), properties=None, tag_columns=None, tags=None)#
Create a dataset in the Nominal platform from a pandas.DataFrame.
- Parameters:
client (NominalClient)
Client instance to use for creating the dataset
df (DataFrame)
Dataframe to create a dataset from
name (str)
Name of the dataset to create, as well as filename for the uploaded “file”.
timestamp_column (str)
Name of the column containing timestamp information for the dataframe
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'])
Type of the timestamp column, e.g. epoch_seconds, iso8601, etc.
description (str | None)
Description of the dataset to create
channel_name_delimiter (str | None)
Delimiter to use for folding channel view to a tree view.
wait_until_complete (bool)
If true, wait until all data has been ingested successfully before returning
-
String labels to apply to the created dataset
properties (Mapping[str, str | float] | None)
String or numeric properties for the created dataset. Integers are stored as floats.
tag_columns (Mapping[str, str] | None)
Mapping of column name => tag key to apply to the respective rows of data
tags (Mapping[str, str] | None)
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.
- Return type: