Oct 23, 2023
🐼 ❤️ ❄️
We are excited to announce Snowflake’s intent to acquire Ponder to bring Ponder’s Python data science innovations to its customers and to accelerate the growth of the Modin community.
Oct 23, 2023 Snowflake has announced its intent to acquire Ponder.
Read more from Ponder hereWe're proud to announce that Ponder will join Snowflake to supercharge data science and AI in the Snowflake Data Cloud.
Ponder brings the best of both worlds: a fully pandas-native experience that is familiar and fast to prototype, plus the scalability and reliability of operating in a data warehouse.
Iterate on your Pandas workflows quickly, from prototype to deployment, all running securely within your cloud-native data warehouse. Turbocharge your productivity and speed up development cycles with lightning-fast, interactive results.
Get StartedRun your Pandas workflows at all scales, from megabytes to terabytes, without changing a single line of code. No more painful out-of-memory errors or slow single-threaded execution.
Get Starteddf.merge()
df.pivot()
df.fillna()
df.describe()
df.explode()
df.merge()
df.pivot()
df.fillna()
df.describe()
df.explode()
Don’t let your warehouse investments go to waste. Leverage your existing data warehouse as compute. No additional infrastructure setup required.
Get StartedPonder was founded by the creators of the popular open-source library Modin, which enables data scientists to run pandas at scale on distributed computing backends, such as Ray or Dask. Modin is embraced by the community and has seen adoption across sectors, including by the world's leading AI companies.
Ponder is founded by a professor and PhDs from the UC Berkeley RISE Lab. Ponder's underlying technology is based on decades of deep academic research and is built by the team that developed open-source scalable data science library Modin.
Learn moreOct 23, 2023
We are excited to announce Snowflake’s intent to acquire Ponder to bring Ponder’s Python data science innovations to its customers and to accelerate the growth of the Modin community.
Oct 3, 2023
This is the fifth in a series of blog posts that teach how to write professional-quality pandas code. We start by discussing pandas dropna generally and going over a simple example. Then we talk about identifying missing values, when to drop data, and how to drop entire rows that are missing.
Sep 19, 2023
In this article, we describe pandas resample + provide some examples, and then show how you can use it at scale in your database.
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