python-docx
Pandas
| python-docx | Pandas | |
|---|---|---|
| 6 | 398 | |
| 4,203 | 42,039 | |
| 1.7% | 0.7% | |
| 8.0 | 10.0 | |
| 7 days ago | 3 days ago | |
| Python | Python | |
| MIT License | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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python-docx
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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:
- Can someone please help why I'm getting this error?
- See unknow person with a problem in Stackoverflow: writes a library for her
- \begin{mess}
- Generating Report with Python
Pandas
- The Birth of Parquet
- PDEP-13: The Pandas Logical Type System
- 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.
What are some alternatives?
docxtpl - Use a docx as a jinja2 template
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
openpyxl
tensorflow - An Open Source Machine Learning Framework for Everyone
python-pptx - Create Open XML PowerPoint documents in Python
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
XlsxWriter - A Python module for creating Excel XLSX files.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
unoconv - Universal Office Converter - Convert between any document format supported by LibreOffice/OpenOffice.
Keras - Deep Learning for humans
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.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration