Had a great time on @posit.co 's Test Set pod w/ @mchow.com @hadley.nz @wesmckinney.com!
We talk about moving between R, SQL, python and the strengths of different analytical tools for diff data tasks. You won't believe what proprietary language gets a shout-out (Stata!)
posit.co/thetestset/e...
Excited to be talking about dbt with @mchow.com at @posit.co's Data Science Lab tomorrow (1/6) at noon Eastern!
If you're a data scientist or analyst curious about dbt/analytics engineering, this will be an accessible introduction
Register:
pos.it/dslab
Last 2025 post, on @python.org & @carpentries.carpentries.org values, a great @posit.co conf session feat @mchow.com @richmeister.bsky.social @davisvaughan.bsky.social, the magic of #rstats #python dev cultures sharing best practices, and random #rstats history
www.emilyriederer.com/post/py-rgo-...
It was such a pleasure to join @hadley.nz, @wesmckinney.com, and @mchow.com on THE TEST SET! You can check out the two parts of our conversation here:
🍕 posit.co/thetestset/e...
🤖 posit.co/thetestset/e...
Hadley Wickham in a white t-shirt and jeans sits on a light-colored couch across from Michael Chow, wearing a dark green shirt and pants, who is seated on an orange pouf. Between them is a white coffee table with books. In the background, there's a dark bar with shelves displaying numerous bottles, a wood-paneled wall, and a black, modern fireplace. Text overlay reads "Hadley Wickham CHIEF SCIENTIST, POSIT".
Ever wonder how the #tidyverse came to be? 🤔
#TheTestSet's first episode features @hadley.nz on his accidental empire of #RStats packages, bear encounters, and more!
Stream it at thetestset.co, Spotify, or Apple Podcasts.
#DataAnalytics #PodcastLaunch
Data science junkies, get ready! 🚀 "The Test Set" #podcast trailer is here for your viewing pleasure.
Tune in July 1st and every Tuesday after for new episodes with hosts @mchow.com, @hadley.nz, and @wesmckinney.com as they welcome thought leaders in #DataScience.
Subscribe now: pos.it/thetestset
Great Tables logo with arrows pointing up above the logo
Great Tables is the #Python library for creating display-ready tables from your #Polars DataFrames and more.
In their 3-part video series, @mchow.com & @richmeister.bsky.social show how to add structure, formatting, & styling to go beyond the default.
Explore the details: posit.co/blog/level-u...
![Python code using Polars and great_tables libraries to create a DataFrame with two columns and apply a blue background style to rows where column 'a' contains null values. The code is followed by an image showing the resulting styled table.
Here is the Python code:
```
import polars as pl
from great_tables import loc, style
(
pl.DataFrame({"a": [1, None], "b": [3, 4]})
.style
.tab_style(
style.fill("aliceblue"),
loc.body(rows=pl.col("a").is_null())
)
)
```](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:7gygvhegj2i2q2ebjqozbkkd/bafkreidkx6xs4gktbtsjp4djso7ztqsgjtrskdugmgxxmwl7qsk6sgh4zm)
Python code using Polars and great_tables libraries to create a DataFrame with two columns and apply a blue background style to rows where column 'a' contains null values. The code is followed by an image showing the resulting styled table. Here is the Python code: ``` import polars as pl from great_tables import loc, style ( pl.DataFrame({"a": [1, None], "b": [3, 4]}) .style .tab_style( style.fill("aliceblue"), loc.body(rows=pl.col("a").is_null()) ) ) ```
New post! Great Tables: Becoming the Polars .style property
When you use Polars `DataFrame.style` it returns a Great Tables object. This is a bit cheesy, but I look back on all the pieces the open source community chipped in to make this happen 🥲.
posit-dev.github.io/great-tables...
Ahh I never wrote the follow-up post 😓, but this Great Tables post does one better, and shows how we used singledispatch with another tool (databackend), to support multiple dataframes without a hard dependency on Pandas or Polars:
posit-dev.github.io/great-tables...
Thanks for this deep dive! partridge is a bit hard for me to grok, since I'm noticing a lot of for loops, but more used to data wrangling looking a bit more like SQL transformations / tidyverse pipes.
(I wonder if Polars would help with this, since it makes easier to keep things table-y, SQL-y)
I think it's good when a system has a real story, but that most good systems are totally inscrutable 😭.
verraes.net/2013/08/john...
It seems similar to how memory champions use spatial locations to memorize large lists of numbers.
A system explained in the abstract is a list of arbitrary facts and rules to learn. A story might be the same system with all kinds of juicy extra context / structure as a mnemonic aid?!
omg this is incredible
A table made by Great Tables, showing names of Paris Metro stations. There is a column called lines, which shows each line number at that station. And a column called passengers, with the number of passengers with the total number of station entries in 2021.
I'm looking to contribute to tools for analyzing public transit data in 2025--and would love to hear from folks!
posit-dev.github.io/great-tables...
Have you ever wondered how to render images seamlessly in Great Tables?
Check out our latest blog post, where we dive into the most common use cases and practical examples!
🔗 Rendering Images Anywhere in Great Tables: posit-dev.github.io/great-tables...
#python #dataviz
pins-python uses fsspec under the hood. afaict since fsspec has both iceberg and duckdb support, this wouldn't be too hard to test out!
