CPython VS Pandas

Hi eesmith, thanks for your insight! I've applied a lot of the improvements you mentioned, the collections.Counter one didn't even cross my mind- very neat:)

The lines are processed independently as they are separate sentences. One line may be from one source, and the next from a completely different source. The problem with simply concatenating them is that the target words on the boundaries between sentences can end up with context words from unrelated sentences.

>I liked seeing the 'η' - I haven't yet used non-ASCII in my code!

Then you may enjoy this april fool's python issue I made https://github.com/python/cpython/issues/103172

Yeah, I like using utf-8 chars for mathematical symbols, it makes my brain hurt a little less when mapping between the two! I also like using ŷ for predictions in ML contexts as that's the canonical symbol used in the literature.

So I wanted to test this out with Python, as I want to embed Python to allow support for scripting in my app. However, as you can see in the Readme here, the build process for Windows and MacOS is a bit different (Mac involves running Make, while Windows just runs a bat file). Neither are complicated, but I originally assumed that the process would be basically the same, and I could use a CMakeLists that wasn't platform specific.

We'll also end up using Python, Docker and Git.

Anything using inspect.getargspec due to this change.

There’s not a single best route but I’d suggest spending an evening with Scratch, then learn a bit of Python via Codecademy. After that, I recommend either Godot, Java, or C++.

It can be useful in some uncommon use cases to make some, let's say, "magic" classes. For example, the enum module in the stdlib makes use of __new__ to create enum classes.

There’s not a single best route but I’d suggest spending an evening with Scratch, then learn a bit of Python via Codecademy. After that, I recommend either Godot, Java, or C++.

Python

Here are links to things that I talked about in this comment. Python (High Level Programming language) https://www.python.org/, Visual Studio Code (A Code Editor) https://code.visualstudio.com/, Stack Overflow (Programming Questions) https://stackoverflow.com/, W3 Schools (Learning Programming Languages) https://www.w3schools.com/.

Hello there folks! I decided to create a data analysis library modeled after pandas, as all things are, this library isn't perfect. It currently only supports a simple CSV, and serializes it into a 2D matrix. Here is currently how it looks

I think that the model should be able to understand to use a tool like [pandas](https://pandas.pydata.org/) and not to analyze the data with it's capabilities.

pandas: you mention employability, and this is one of the most powerful ways you can wrangle with data in Python, say as a data analyst. I have used it for some of my research projects because it allows you to collect elements from a data table easily based on shared characteristics or a custom function and plot/perform statistical analysis on them.

Traditionally Kedro has favoured pandas as a dataframe library because of its ubiquity and popularity. This means that, for example, to read a CSV file, you would add a corresponding entry to the catalog:

I asked GPT-4 this

can you visit https://pandas.pydata.org/about/governance.html and tell me if I am allowed to use the term 'pandas' in the name of another unaffiliated project, for example 'pandas-ai'

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Based on the BSD 3-Clause License under which pandas is released, neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission[ 1] . This means that to use the term 'pandas' in the name of another unaffiliated project such as 'pandas-ai', you would likely need to get written permission from the pandas project's copyright holders.

However, please note that this is not legal advice, and it would be a good idea to consult with a lawyer who specializes in open-source software or intellectual property law to ensure that you're in compliance with all legal requirements.

[1] https://github.com/pandas-dev/pandas/blob/main/LICENSE

I have updated this issue https://github.com/pola-rs/polars/issues/8533, please kindly help to solve it. I have also sent similar issues to Pandas https://github.com/pandas-dev/pandas/issues/53249

Before diving into advanced machine learning algorithms or statistical models, we need to start with the basics: collecting and organizing data. Fortunately, both Python and R offer a wealth of libraries that make it easy to collect data from a variety of sources, including web scraping, APIs, and reading from files. Key libraries in Python include requests, BeautifulSoup, and pandas, while R has httr, rvest, and dplyr.

Analysis was done in Jupyter Notebook with Python 3.10, Pandas, Matplotlib, wordcloud and Mercury framework.

Analysis was done in Jupyter Notebook with Python 3.10 kernel, Pandas, Matplotlib, wordcloud and Mercury framework to share notebook as a web application with widgets and code hidden. Gif created in Canva.

Speaking of pandas: groupby used to treat x and [x] the same way. Now it treats them differently, but still is forced to make the decision whether a value is scalar or iterable. Maybe in 10 years we will get another flavor of the idea ? Which one is best ? That sort of "design roaming" is quite symptomatic of that sort of API, for a good reason: there is no winning solution, it will always be broken by design: https://github.com/pandas-dev/pandas/pull/47761