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#pandas
Finally got a fully working #python #pandas sidecar in @TauriApps 
...though I should probably rewrite it in @pola.rs 
But for now, here's how I did it!
https://mclare.blog/posts/writing-a-pandas-sidecar-for-tauri/
Pandas là gì? Lợi ích & Ứng dụng thư viện Pandas trong Python
Pandas là một thư viện mã nguồn mở trong Python, được thiết kế đặc biệt để xử lý và phân tích dữ liệu. Với cấu trúc dữ liệu mạnh mẽ và các công cụ tiện ích, Pandas giúp làm sạch và trực quan hóa dữ liệu một cách dễ dàng và nhanh chóng. Bài viết này sẽ giới thiệu các tính năng và ứng dụng thực tế của Pandas trong các dự án phân tích dữ liệu.
Đọc bài viết ngay tại: https://interdata.vn/blog/pandas-la-gi/
I am really looking forward to a time when scientific data analysis is less of a constant fuckaround and fight with technical bullshit. I'd *really* like
- #netCDF natively supporting complex numbers
- #Python #xarray and #pandas to natively support physical units (#pint is great on its own but the integrations leave a LOT to be desired)
- #Jupyter notebooks to suck less (crashes, glitches, widget plots not saved statically, an effing BUILTIN formatter, etc.)
- proper data pipeline systems
...
Every Wednesday, Bamboo Weekly (https://BambooWeekly.com) poses data-analysis questions based on current events.
But what if you want to practice a particular #Pandas skill, such as multi-indexes, regular expressions, PyArrow, or pivot tables?
Good news: Our new "tags" page, at https://BambooWeekly.com/tags/ , lists dozens of topics you might want to learn or practice -- with links to all relevant articles.
Check it out, and level up your Pandas skills today!
OPEN SOURCE 
The Problem
There have been many instances where I needed to compare two dataframes and analyze their differences. To address this need, I created a fast Python library called "data_fingerprint" that does exactly that.
Check it out and let me know what you think! 
https://github.com/SimpleSimpler/data_fingerprint
Los pandas tienen que ser los animales más felices... se entretienen muy fácilmente.
#Nature #Naturaleza #Pandas
Parsing CSV with units in the header · Issue #166 · hgrecco/pint-pandas
https://github.com/hgrecco/pint-pandas/issues/166
Now we can read a #csv file with a header like `time / s,mass / g` into #pandas and call `.pint.quantify()` to get a #dataframe in which the columns have #units as in #Pints !
Handy for CSV restricted to single-row headers, as in Confluence Databases and Microsoft Lists.
This week's achievement unlocked reporting a bug for a widely used tool that was both simple and unknown before...
Now the even more useful part - actually submitting fix? #Pandas 
:flower: @pythonhub
@pandas_dev
#pandas
Hello, I am looking for a way to identify a commune/city from a geolocation point (lat. - long.)
Does a library exist?
How to do that?
This request is not to find a commune/city from an address.
For instance, my search is from points in the middle of fields and in a forest...
And when I don't have an address :).
Thank you for your time.
----
Je cherche un moyen de retourner le nom d'une commune à partir de la géolocalisation d'in point.
Merci.
Thank you to #Kone & Mai and Tor Nessling Foundations for supporting this work. A quantitative work like this would not be possible without a robust suite of FOSS tools. My thanks to the maintainers of #QGIS, #pandas, #geopandas, #duckdb, #dask, #statsmodels, #jupyter and many more!
Evaluating Past Range Shifts and Niche Dynamics of Giant Pandas Since the Last Interglacial
Transform your tedious data cleaning tasks with automated pipelines in Python using pandas! Reduce time spent on repetitive processes and enhance data quality by leveraging structured workflows, validation, and monitoring. Build reusable functions and pipelines to create a more efficient data cleaning system. #DataCleaning #Python #Pandas #Automation #DataScience https://www.kdnuggets.com/creating-automated-data-cleaning-pipelines-using-python-and-pandas
Polars vs. pandas – Python のデータフレームライブラリを徹底比較
#Python #Pycharm #Datascience #Pandas #Polars
Working on core array computing libraries that power #scientificPython? #EuroSciPy2025 wants your proposals on optimized array operations, vectorization techniques, and numerical foundations. Submit your groundbreaking work!
At last night’s @mug meeting we looked at a lot of different solutions to #adventofcode day 1 in many different languages. Two that were very interesting to me were #Zig and #haskell. The way these two languages worked was really quite fascinating. After seeing real code in these two languages, I can tell they are not for me; but they were interesting and illuminating nonetheless.
There was a solution entirely in #SQL. Another in #vim9script. Another in #swiftlang #swift (I don’t think that one’s in the repo yet). I wrote several implementations myself. The one I felt most proud of is #Python with the core written in #rustlang #rust tied together with #PyO3. The one I felt was maybe the best tool for the job was entirely based on #pandas. As I said in a previous post, I tried to solve it in #polars, but the API exposed by Polars at least as far as I could tell, made it no better than simple lists in Python. I need to get deeper knowledge here.
The repo lives here: https://github.com/MichiganUnixUserGroup/MUG-2025-03-11-Advent-of-Code.
#python #pandas #regex
Ein großer Fallstrick für mich, sind die unterschiedlichen Rückgabewerte.
pandas lässt recht einfach auf den gesuchten Regex als Rückgabewert zugreifen, bei python zusammen mit re braucht es eine extra Schleife, wenn man den Regex als Rückgabewert will.
Der Kleinkram macht immer den Unerschied!
