Bon après midi à tous. 📖📚

#mastolecture #mardilecture #polars #bibliotheque #LectureEnCours #mastolivres

#VendrediLecture
M.J. Arlidge, 2 #polars : Am stram gram et Il court, il court, le furet.
Pour les 2, j'ai failli laisser tomber.
L'intrigue et l'enquête sont bien fichues. Alors : L'écriture pas terrible ? pas seulement.
La flique principale porte une épaisse carapace. Cette carapace englobe les livres, j'ai eu du mal à y entrer.
L'enquête oui, mais aucun plaisir à suivre les personnages, abstraits, sans profondeur. Même Southampton, lieu des 2 romans, pourrait être n'importe où.
OK sans plus.

Can someone explain why I am so confused about #polars? The pitch is "it's like #pandas but lightning fast!". But I don't think I have ever given pandas' performance a single thought before. Am I just not doing "hardcore" enough work to warrant consideration of polars?

I've written a blog post diving deep into the differences between #Polars and #pandas, and what are the best use cases for each of these dataframe libraries (spoiler alert: the answer is not always Polars 😅).

https://blog.jetbrains.com/dataspell/2023/08/polars-vs-pandas-what-s-the-difference/

Polars 0.19 is out 🐻‍❄️ https://github.com/pola-rs/polars/releases/tag/py-0.19.0

Highlights:

- `sink_csv` for `LazyFrame`
- "massive expansion" of database support
- Rename `groupby` to `group_by` and some other methods (the old ones are deprecated ❗)
- Read/write support for Arrow IPC streams in DataFrames
- Lots of deprecated functionalities got removed

Get it now while it's hot!

#python #pydata #polars #datascience

@samharrison7
Something that you can easily avoid by using your local #Python with #pandas or #polars and other available today packages. I don't see any benefit on this announcement...

Optimization #polars #EuroSciPy

Example of #polars #EuroSciPy

Here's another web app built aiming towards non-coding lab chemists (my two cents towards this) - https://jhylin.github.io/Data_in_life_blog/posts/15_Molviz/Molviz.html

Quick features of the app:
- viewing and highlighting substructures in 2D compound images (for deployed version)
- viewing, saving and highlighting 2D images (for localhost version)

For interactive data table part: https://jhylin.github.io/Data_in_life_blog/posts/15_Molviz/itables.html

Big thanks to #rdkit, #datamol, #pyshiny, #itables, #pandas, #polars & #python.

Polars is a lightning fast DataFrame library/in-memory query engine with parallel execution and cache efficiency. And now you can use is with the tidyverse syntax: https://www.tidypolars.etiennebacher.com/ #rstats #polars #optimisation

For #metasynth (:python: pkg for generating synthetic tables from sensitive data) we're using #polars (https://pola.rs) as our data frame library.

I had to get used to it (it's not #tidyverse ) but I'm really liking how consistent (and fast!) it is. Also good thought went into data types. For this, I like it much better than #pandas!

The only minor problem is that it is not yet easy to find answers to some basic questions, because there are not that many users.

Use polars everyone!

5 Latest Tools You Should Be Using With Python for Data Science.
🗂️ The article provides insightful details on tools like ConnectorX, DuckDB, Optimus, Polars, and Snakemake which could enhance data wrangling, querying, manipulation, and workflow automation capabilities.

1. 🧰 ConnectorX: Simplifying the Loading of Data
2. 🧰 DuckDB: Empowering Analytical Query Workloads
3. 🧰 Optimus: Streamlining Data Manipulation
4. 🧰 Polars: Accelerating DataFrames
5. 🧰 Snakemake: Automating Data Science Workflows

https://www.makeuseof.com/latest-python-data-science-tools/

#Python #DataScience #ConnectorX #DuckDB #Optimus #Polars #Snakemake #Programming #DataAnalysis #Productivity

📝 "Pills dataset - Part 2"

👤 Jennifer HY Lin (@jhylin)

🔗 https://jhylin.github.io/Data_in_life_blog/posts/09_Pills/Rust_polars_pills_df.html

#pyladies #python #dataanalyticsprojects #pillsdatasetseries #polars #plotly #jupyter

#VendrediLecture
'Kabukicho' de Dominique Sylvain.
Le Kawaguchi était une courte pause dans ma (qqf re)lecture des #polars de D. Sylvain.
J'ai attaqué Kabukicho, que je n'avais pas encore lu.
Un polar plus noir que ses autres, qui se déroule à Tokyo, dans le quartier chaud qui donne son nom au titre. Des personnages fouillés et complexes, une histoire prenante, les codes du Japon.
Je me régale.

📝 "Working with scaffolds in small molecules"

👤 Jennifer HY Lin (@jhylin)

🔗 https://jhylin.github.io/Data_in_life_blog/posts/14_Scaffolds_in_small_molecules/chembl_anti-inf_data_prep_current.html

#pyladies #python #rdkit #datamol #pandas #polars #cheminformatics

Team "abonnés en novembre 2022, ils reviennent".
J'en profite pour faire mon #intro.
Julie, aime la #lecture ( #polars et #thrillers principalement), mon #chien la #randonnee et la #montagne en général. Je cours un peu aussi #running et je bois de la #biere

(Re)bonjour !

I was wondering what can I do to keep practicing #rustlang (because I don't have much time nowadays).

For me it should be a tiny side-project, something that I could finish in a weekend (otherwise maybe I wouldn't even start it)... and I remembered that I work with #python #pandas in a daily basis and I could try #polars to see the differences in syntax and performance.

Maybe tinkering around with some data is my next #rustlang task 🤔

📝 "Shinylive app in Python"

👤 Jennifer HY Lin (@jhylin)

🔗 https://jhylin.github.io/Data_in_life_blog/posts/13_Shiny_app_python/ShinyAppPy_PC_Cov19_data_prep.html

#pyladies #python #shiny #polars #plotly #pubchem #cheminformatics

Check out Patrick Hoefler's new blog about his experience #benchmarking #pandas and #Polars:

https://levelup.gitconnected.com/benchmarking-pandas-against-polars-from-a-pandas-pov-554416a863db

It has some nice details about how to optimize pandas code ✨

TIL In #Python #polars is a faster alternative to #pandas. Sadly, it has a different API: https://towardsdatascience.com/pandas-vs-polars-a-syntax-and-speed-comparison-5aa54e27497e