Ponder

Run pandas at scale directly in your data warehouse—be it Snowflake, BigQuery or DuckDB—all from the comfort of your favorite IDE or notebook.

[Ponder @ponderdata]

📣 As of TODAY, Ponder is in Public Beta. 🚀 Now ANYONE can start running Python data workflows (pandas, NumPy) directly in their data warehouse in less than five minutes. Just pip install ponder.

Learn more below! 🧵[1/N]

https://t.co/ydnF0SMuje

#python #pandas #datascience

[Ponder @ponderdata]

We’re excited to announce Snowflake's intent to acquire Ponder to bring Ponder's Python data science innovations to all its customers.

Thank you to all of the Ponder and Modin supporters who brought us to this point -- We're excited for what's to come!

https://t.co/yeJPXcNmGg

[Snowflake @Snowflake]

Snowflake announced its intent to acquire @ponderdata to further enable Python data scientists in the Data Cloud. We look forward to welcoming the Ponder team and the Modin community to Snowflake. Learn more: https://t.co/eY8W9g5dPc

[Ponder @ponderdata]

Great coverage in the @realpython podcast of @maheshvash's article: "Why Are There So Many Python Dataframes?"

Here's the link to jump straight to that 7-minute portion:
https://t.co/5z31iaE54Y

Link to article: https://t.co/hGIo78pYlA

[Real Python @realpython]

🐍🎧 Episode #176 of the Real Python Podcast is live: “Building Python Best Practices and Fundamental Skills” #python #podcast https://t.co/dJYRQ8SenB

[Ponder @ponderdata]

You can run NumPy 🔢 at scale in your database with Ponder 💥

Through @modin_project, Ponder supports:
- Element-wise matrix ops (addition, subtraction, division, power)
- Axis-collapsing or reducing ops (min, max, sum, product, mean)
& more: https://t.co/xvWEhR3gzy

#NumPy #SQL

[Ponder @ponderdata]

If you're backed into a dark alley, facing a pack of ravenous NaN dogs, you'll want a sidekick like pandas dropna.

Drop rows with n missing values using thresh=n.

Drop entirely empty rows with how='all'.

Learn more from @__mharrison__: https://t.co/cUxVKDc6ec

#pandas #Python

[Ponder @ponderdata]

A 2-hour pandas workflow (150 million rows) can take 2 minutes with Ponder on Snowflake.

Read more: https://t.co/jqzbhvWfdr

Or watch the demo here: https://t.co/FvghhdRyFu

#pandas #SQL #Snowflake

[Ponder @ponderdata]

How do you use database connections & cursors in Python?

It can be hard to figure out because database concepts & Python objects don't map 1:1.

To learn more (with an emphasis on the Snowflake-Python connector) check out: https://t.co/WAtP2OGwUa

#python #database #snowflake

[Ponder @ponderdata]

If you want to automatically parallelize your pandas code, you should check out open-source Modin: https://t.co/uN0uRLwUWv

@modin_project uses the pandas API, so all you need to do is change "import pandas as pd" to "import modin.pandas as pd"

#pandas #Python #opensource

[Python Hub @PythonHub]

How the Python Dataframe Interchange Protocol Makes Life Better

In this article, we answer three questions about the Python Dataframe Interchange Protocol: What it is + what problems it solves; how it works; and how extensively it's been adopted.

https://t.co/s3H8C4VZtc

[pandas @pandas_dev]

We're happy to announce the release of #pandas 2.1.1. You can install it with `pip install pandas` or `mamba install -c conda-forge pandas`. You can find what's new in this version in the release notes. Thanks to all contributors and sponsors who made this release possible!

[Ponder @ponderdata]

Ever had hourly data, but wished it were monthly? Daily, but wished it were weekly? 😢

pandas resample will dry your tears.

It makes upsampling + downsampling really slick, & now it's possible to run it directly in your database: https://t.co/zXJ2ROYa9z

#pandas #database

[Ponder @ponderdata]

Congratulations to @MotherDuck 🦆 on your Series B 📈

We're excited to have Ponder be part of the Modern Duck Stack!

https://t.co/Cu4nPyNS6v

#pandas #Python #duckdb

[Ponder @ponderdata]

@maheshvash Comments, questions, things to add -- Feel free to share thoughts here

[Ponder @ponderdata]

pandas. Modin. Polars. RAPIDS cuDF. Ibis. Vaex. Dask. PySpark. Daft. Snowpark dfs. BigQuery dfs.

Why are there so many #Python #dataframe libraries?

Open-source dataframe contributor + Ponder Founding Engineer @maheshvash shares 3 conclusions: https://t.co/Rf9RgLOWoE

[Ponder @ponderdata]

Pulling data from @SnowflakeDB to work w/ scikit-learn, LightGBM, XGBoost?

💥Snowpark ML lets you stay in Snowflake but use important ML classes: LGBMClassifier, Lasso, PCA, XGBClassifier, etc.

💥Ponder lets you do your pandas preprocessing in Snowflake
https://t.co/O144dIcwOw

[Ponder @ponderdata]

Ponder typically runs pandas code in your database by translating it to SQL. But pandas apply is different.

For apply, we create a temporary Python user-defined table function (UDTF).

Read more about apply + how Ponder handles it: https://t.co/Uvhuserj5C

#Python #pandas #SQL

[Ponder @ponderdata]

.@IntelDevTools saw a workload speedup of 4X with @modin_project (the scalable drop-in replacement for pandas) compared to pandas!

Read more from Intel here: https://t.co/Evk4qmqls8

#python #pandas #datascience

[Ponder @ponderdata]

@__mharrison__ @ralfgommers 💯

[Ponder @ponderdata]

The Python Dataframe Interchange Protocol is a quiet hero 🦸‍♀️.

It makes it easy for libraries to accept many dataframes (Modin, Polars, Ibis, cuDF, Dask).

Read our encomium: https://t.co/LWOnZBI5IL

Thanks to Marco Gorelli & @ralfgommers for your work!

#python #dataframes

[Ponder @ponderdata]

@__mharrison__ Thanks, @__mharrison__ !

[Ponder @ponderdata]

Ponder, explained in 90 seconds ⏱️:

https://t.co/7atG9Id7Pp

#python #pandas #datascience #sql #database