Pycoder's Weekly VS Pandas
Compare Pycoder's Weekly VS Pandas and see what are their differences
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Pycoder's Weekly
One Month Python
Glitch Instant Database Starters
Learn Python The Hard Way
Mode Python Notebooks
Exaptive
utile
Micro Python
Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
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Based on our record, Pandas seems to be a lot more popular than Pycoder's Weekly. While we know about 196 links to Pandas, we've tracked only 6 mentions of Pycoder's Weekly. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
PyCoder's Weekly[https://pycoders.com/] is a good newsletter for learning more about Python. - Source: Hacker News / about 1 year ago
Coincidentally, I just saw the article How to Evaluate the Quality of Python Packages on the latest PyCoder's Weekly. Source: about 1 year ago
There are many podcasts that will keep you in touch. And also https://pycoders.com/ weekly newsletter. Source: over 1 year ago
You can go to the home page of PYPI and have a look at the list of trending packages, but I'd suggest following a good podcast like Talk Python to Me or Pycoders Weekly. They often feature interesting new packages. Source: over 1 year ago
Recommend reading PyCoders weekly newsletter every Thursday. Source: almost 2 years ago
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / about 2 months ago
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts. - Source: dev.to / 4 months ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 4 months ago
Pandas, a powerful data manipulation library in Python, has become an essential tool for data scientists and analysts. One of its key functions is read_csv(), which allows users to read data from CSV (Comma-Separated Values) files into a Pandas DataFrame. In this tutorial, brought to you by CodesWithPankaj.com, we will explore the intricacies of read_csv() with clear examples to help you harness its full potential. - Source: dev.to / 5 months ago
So, what I'd like to do is write a documentation package in Python to recreate what I've lost. I plan to build upon the fantastic python-docx and docxtpl packages, and I'll probably rely on pandas from much of the tabular stuff. Here are the features I intend to include:. Source: 5 months ago
One Month Python - Learn to build Django apps in just one month.
NumPy - NumPy is the fundamental package for scientific computing with Python
Glitch Instant Database Starters - Build a database-backed full-stack app in under a minute.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Learn Python The Hard Way - One of the best guides to learn Python & coding in general
OpenCV - OpenCV is the world's biggest computer vision library