Pandas
pyexcel
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Pandas | pyexcel | |
---|---|---|
393 | 1 | |
41,863 | 1,173 | |
1.3% | 0.7% | |
10.0 | 0.0 | |
4 days ago | 4 months ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Pandas
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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]
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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:
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How do people know when to use what programming language?
Weirdly most of my time spent with data analysis was in the C layers in pandas.
- Read files from s3 using Pandas/s3fs or AWS Data Wrangler?
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10 Github repositories to achieve Python mastery
Explore here.
pyexcel
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Advice on ETL and Data Sharing work process
You could try and write some simple python using the pyexcel and pandas libraries. I created a tool as a consultant with these packages that parsed spreadsheets with data from factories from all around the world. They did not lock down the Excel files used to submit data and it made it so much harder. If you go this route, I would recommend starting by putting your data into a SQLite database. Once you have your data in a database, you unlock the power of SQL for pulling reports. Also, you can port the data into a proper database if you ever need to. ChatGPT can probably get you a good chunk of the way there.
What are some alternatives?
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
openpyxl
tensorflow - An Open Source Machine Learning Framework for Everyone
XlsxWriter - A Python module for creating Excel XLSX files.
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
xlwings - xlwings is a Python library that makes it easy to call Python from Excel and vice versa. It works with Excel on Windows and macOS as well as with Google Sheets and Excel on the web.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
xlwt
Keras - Deep Learning for humans
docxtpl - Use a docx as a jinja2 template
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
unoconv - Universal Office Converter - Convert between any document format supported by LibreOffice/OpenOffice.