Aug 8, 2023

HuggingFace Transformers with Ponder

In this article we show how the HuggingFace Transformers library works with Ponder, a tool that uses your data warehouse (Snowflake, BigQuery, DuckDB) as an engine to run your pandas and NumPy code...


Aug 3, 2023

Ponder 0.2.0 Release: BigQuery in Public Beta!

We are thrilled to announce Ponder's public beta of BigQuery support. You can now harness the capabilities of BigQuery directly within your pandas workflows, eliminating the need for data movement, so that you can enjoy the scalability and governance provided by an enterprise-grade data warehouse. B...


Jul 20, 2023

pandas apply in your database

Learn how you can use pandas's apply to perform custom functions on your DataFrame directly on your database!...


Jul 14, 2023

Pandas in Production with VertexAI and BigQuery

With Ponder, you can use lightweight Vertex AI Notebooks to run pandas on large datasets, all by letting BigQuery do the heavy lifting....


Jun 23, 2023

Ponder at Snowflake Summit

Come meet with our experts at the Snowflake Summit for a free 1:1 consulting, personalized demo, and some awesome Ponder swag!...


Jun 9, 2023

The New DuckDB Pivot Operator

DuckDB recently introduced support for a DuckDB PIVOT operator. In this post, we compare the syntax for DuckDB Pivot, Snowflake Pivot, and Ponder Pivot (using the pandas API)....


Jun 8, 2023

Top 5 Things to Know When Using the Snowflake Module in Python

We describe five key things to know when using the Snowflake module in Python, also known as the “snowflake-connector-python,” to interact with data in Snowflake from a Python interface....


Jun 5, 2023

An API-First Approach to Data

We explore why it is important to adopt an infrastructure-agnostic approach when picking data tools and how Ponder gives you the flexibility you need by letting you use your favorite data APIs, like pandas and NumPy, no matter what database your data is stored in...


May 31, 2023

Python for Finance: Pandas Resample, Groupby, and Rolling

With an end-to-end example, we explore how you can leverage pandas to understand trends in times series data quickly, with a particular focus on time series methods like pandas resample, grouping by dates, and performing rolling operations to smooth out the results....

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