Create a dataset from pandas dataframe

# azureml-core of version 1.0.72 or higher is required
# azureml-dataprep[pandas] of version 1.1.34 or higher is required

from azureml.core import Workspace, Dataset
local_path = 'data/prepared.csv'
dataframe.to_csv(local_path)

# upload the local file to a datastore on the cloud

subscription_id = 'xxxxxxxxxxxxxxxxxxxxx'
resource_group = 'xxxxxx'
workspace_name = 'xxxxxxxxxxxxxxxx'

workspace = Workspace(subscription_id, resource_group, workspace_name)

# get the datastore to upload prepared data
datastore = workspace.get_default_datastore()

# upload the local file from src_dir to the target_path in datastore
datastore.upload(src_dir='data', target_path='data')

# create a dataset referencing the cloud location
dataset = Dataset.Tabular.from_delimited_files(path = [(datastore, ('data/prepared.csv'))])