Google launches BigQuery Data Frames

Google just announced BigQuery DataFrames — the feature is now in preview. BigQuery DataFrames is a Python API that you can use to analyze data and perform machine learning tasks in BigQuery[1]. BigQuery DataFrames combines Data Analysis and Data Science capabilities by giving you the following options[1]: <ul> <li><code>bigframes.pandas</code> implements a DataFrame API (with partial Pandas compatibility) on top of BigQuery.</li> <li><code>bigframes.ml</code> implements a Python API for BigQuery ML (with partial scikit-learn compatibility).</li> </ul> DataFrames is an open-source package that you can run <code>pip install --upgrade bigframes</code> to install the latest version — here a small blue print on how to use it[2]: <pre> import bigframes.pandas as bpd bpd.options.bigquery.project = your_gcp_project_id df1 = bpd.read_gbq("project.dataset.table") df2 = bpd.read_gbq("SELECT a, b, c, FROM `project.dataset.table`")</pre> So this is again quite good news if you are working with Google Cloud and BigQuery in the enterprise but also want to do more with Python and run Data Science and Machine Learning task without any more unnecessary interfaces. Alternatively, Google also offers BigQuery ML, an alternative for ML via SQL. If you want to get started with BigQuery DataFrames Google also provides a BigQuery DataFrames quickstart. <a href="https://medium.com/codex/google-launches-bigquery-data-frames-762ae20ff1d0">Visit Now</a>