Dataframe

tamr_client.dataframe.upsert(session, dataset, df, *, primary_key_name=None)

Upserts a record for each row of df with attributes for each column in df.

Parameters

• dataset (Dataset) – Dataset to receive record updates

• df (pd.DataFrame) – The DataFrame containing records to be upserted

• primary_key_name (Optional[str]) – The primary key of the dataset. Must be a column of df. By default the key_attribute_name of dataset

Return type

Dict[str, Any]

Returns

JSON response body from the server

Raises

• requests.HTTPError – If an HTTP error is encountered

• primary_key.NotFound – If primary_key_name is not a column in df or the index of df

• ValueError – If primary_key_name matches both a column in df and the index of df

tamr_client.dataframe.create(session, instance, df, *, name, primary_key_name=None, description=None, external_id=None)

Create a dataset in Tamr from the DataFrame df and creates a record from each row

All attributes other than the primary key are created as the default type array(string)

Parameters

• instance (Instance) – Tamr instance

• df (pd.DataFrame) – The DataFrame containing records to be upserted

• name (str) – Dataset name

• primary_key_name (Optional[str]) – The primary key of the dataset. Must be a column of df. By default the name of the index of df

• description (Optional[str]) – Dataset description

• external_id (Optional[str]) – External ID of the dataset

Return type

Dataset

Returns

Dataset created in Tamr

Raises

• dataset.AlreadyExists – If a dataset with these specifications already exists.

• requests.HTTPError – If any other HTTP error is encountered.

• primary_key.NotFound – If primary_key_name is not a column in df or the index of df

• ValueError – If primary_key_name matches both a column in df and the index of df