Create a BigQuery DataFrame from a CSV file in GCS
Stay organized with collections
Save and categorize content based on your preferences.
Use the BigQuery DataFrames API to turn a CSV file in Google Cloud Storage into a BigQuery DataFrame.
Explore further
For detailed documentation that includes this code sample, see the following:
Code sample
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],[],[[["The BigQuery DataFrames API can be used to transform a CSV file stored in Google Cloud Storage into a BigQuery DataFrame."],["The `bpd.read_csv()` function is used to read the CSV file from Google Cloud Storage, with the file path specified as a parameter."],["Authentication to BigQuery can be achieved by setting up Application Default Credentials, following the provided guide for client libraries."],["The code example uses the `bigframes.pandas` library and displays the first few rows of the created DataFrame with `df_from_gcs.head()`."]]],[]]
