View output: Select the eye icon, and follow the instruction to browse the Results_dataset folder, and download the data.csv file. You can find the dataset as a component in the component tree under the My Datasets section. Register dataset: Select the icon and save the CSV file back to the Azure Machine Learning workspace as a separate dataset. Select the Outputs tab in the right panel of Convert to CSV, and select on one of these icons under the Port outputs. You can find this component in the Data Transformation group in the designer.Ĭonnect it to any component that outputs a dataset.

How to configure Convert to CSVĪdd the Convert to CSV component to your pipeline. You can download the CSV from the Results folder to a local directory. You can also access the CSV in the designer by selecting the Convert to CSV component, then select the histogram icon under the Outputs tab in the right panel to view the output. You can use an Azure storage utility to open and use the file directly. When you convert a dataset to CSV, the csv is saved in your Azure Machine Learning workspace. Use the CSV format to prepare data for use in R and Python.Save the CSV file to cloud storage and connect to it from Power BI to create visualizations.Download the CSV file to open it with Excel, or import it into a relational database.CSV is a common interchange format when working with open-source languages such as R or Python.Įven if you do most of your work in Azure Machine Learning, there are times when you might find it handy to convert your dataset to CSV to use in external tools. The CSV format, which stands for 'comma-separated values', is a file format used by many external machine learning tools. Use this component to convert a dataset into a CSV format that can be downloaded, exported, or shared with R or Python script components. This article describes a component in Azure Machine Learning designer.

Convert text file to csv python