notebook
Pandas
notebook | Pandas | |
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10 | 396 | |
11,172 | 41,983 | |
0.8% | 0.6% | |
9.2 | 10.0 | |
1 day ago | 6 days ago | |
Jupyter Notebook | Python | |
BSD 3-clause "New" or "Revised" License | BSD 3-clause "New" or "Revised" License |
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notebook
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Jupyter Notebook 7
For folks asking what the Notebook UX offers that the Lab does not, this github thread may be enlightening: https://github.com/jupyter/notebook/issues/6210
(TLDR: some novice users in educational settings find the lab environment overwhelming.)
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The Best Python IDE For Mac Users - Part 1
For further info refer to the official GitHub Repo.
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I've been writing Python for years but wanted to get into open source dev, but, what can a person do?
https://github.com/jupyter/notebook has over 2000 open issues
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as simple as it is here, whats the error?
DisabledFunctionError: cv2.imshow() is disabled in Colab, because it causes Jupyter sessions to crash; see https://github.com/jupyter/notebook/issues/3935. As a substitution, consider using from google.colab.patches import cv2_imshow
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How to use Jupyter notebooks in a conda environment?
As it seems, this is not quite straight forward and manyusers have similar troubles.
- How do I disable .ipynb_checkpoints forever!
- The future of the classic notebook interface · Issue #6210 · Jupyter/notebook
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The end is near
cough-cough-cough
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Cannot open Jupyter Notebook due to some Traceback error
Take a look here: https://github.com/jupyter/notebook/issues/3435
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Hacktoberfest: 69 Beginner-Friendly Projects You Can Contribute To
https://github.com/jupyter/notebook Jupyter Interactive Notebook
Pandas
- PHP Doesn't Suck Anymore
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AWS Serverless Diversity: Multi-Language Strategies for Optimal Solutions
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience.
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Pandas reset_index(): How To Reset Indexes in Pandas
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method.
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Deploying a Serverless Dash App with AWS SAM and Lambda
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. Instead, we'll focus on what's necessary to make it run serverless.
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Help Us Build Our Roadmap – Pydantic
there is pull request to integrate in both pydantic extra types and into pandas cose [1]
[1]: https://github.com/pandas-dev/pandas/issues/53999
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Stuff I Learned during Hanukkah of Data 2023
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.
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Introducing Flama for Robust Machine Learning APIs
pandas: A library for data analysis in Python
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
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.
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Mastering Pandas read_csv() with Examples - A Tutorial by Codes With Pankaj
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.
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What Would Go in Your Dream Documentation Solution?
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:
What are some alternatives?
jupyter - Jupyter metapackage for installation, docs and chat
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
matplotlib - matplotlib: plotting with Python
tensorflow - An Open Source Machine Learning Framework for Everyone
graph-notebook - Library extending Jupyter notebooks to integrate with Apache TinkerPop, openCypher, and RDF SPARQL.
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
moment - Parse, validate, manipulate, and display dates in javascript.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Vue.js - This is the repo for Vue 2. For Vue 3, go to https://github.com/vuejs/core
Keras - Deep Learning for humans
Sinatra - Classy web-development dressed in a DSL (official / canonical repo)
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration