Last Updated on October 21, 2021 by Admin
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You create an Azure Machine Learning service datastore in a workspace. The datastore contains the following files:
All files store data in the following format:
You run the following code:
You need to create a dataset named training_data and load the data from all files into a single data frame by using the following code:
Solution: Run the following code:
Does the solution meet the goal?
Use two file paths.
Use Dataset.Tabular_from_delimeted as the data isn’t cleansed.
A TabularDataset represents data in a tabular format by parsing the provided file or list of files. This provides you with the ability to materialize the data into a pandas or Spark DataFrame so you can work with familiar data preparation and training libraries without having to leave your notebook. You can create a TabularDataset object from .csv, .tsv, .parquet, .jsonl files, and from SQL query results.