Levenshtein
Pandas
Levenshtein | Pandas | |
---|---|---|
2 | 395 | |
1,239 | 41,983 | |
- | 0.6% | |
0.0 | 10.0 | |
over 2 years ago | 5 days ago | |
C | Python | |
GNU General Public License v2.0 or later | BSD 3-clause "New" or "Revised" License |
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Levenshtein
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Is it possible on Python?
Yeah my hunch is that a combination of nltk, python-Levenshtein, numpy for language processing, pandas for gathering results and scrapy for web scraping should make it possible. Sadly such a project probably requires at least a month or two worth of training in Python to prototype. Good luck OP.
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Four Useful Python Libraries You Don't Know About
I've used fuzzy-wuzzy and it is pretty slow if you can't install python-Levenshtein (which I couldn't, though I don't remember why). I ended up uninstalling it and using a custom matching algorithm for search in my app.
Pandas
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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:
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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.
What are some alternatives?
fuzzywuzzy - Fuzzy String Matching in Python
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
jellyfish - 🪼 a python library for doing approximate and phonetic matching of strings.
tensorflow - An Open Source Machine Learning Framework for Everyone
TextDistance - 📐 Compute distance between sequences. 30+ algorithms, pure python implementation, common interface, optional external libs usage.
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
chardet - Python character encoding detector
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Charset Normalizer - Truly universal encoding detector in pure Python
Keras - Deep Learning for humans
shortuuid - A generator library for concise, unambiguous and URL-safe UUIDs.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration