usaddress
DataProfiler
usaddress | DataProfiler | |
---|---|---|
5 | 61 | |
1,552 | 1,456 | |
0.6% | 0.5% | |
4.7 | 3.5 | |
12 days ago | 5 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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.
usaddress
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Which of your favorite Python 3.11 packages lack Python 3.11 support?
Usaddress https://github.com/datamade/usaddress
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Script to split addresses in Google Sheets?
Assuming you’re working with addresses in the US, here’s a Python package that should help: https://github.com/datamade/usaddress
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PyWhat: Identify Anything
Some great probabilistic python libraries:
https://github.com/datamade/usaddress - "usaddress is a Python library for parsing unstructured address strings into address components, using advanced NLP methods."
https://github.com/datamade/probablepeople - "probablepeople is a python library for parsing unstructured romanized name or company strings into components, using advanced NLP methods."
- Turning unstructured address data into a structure Salesforce Address Field
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Fuzzy Name Matching in Postgres
For address parsing, I've had good luck with this package: https://github.com/datamade/usaddress
DataProfiler
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LongRoPE: Extending LLM Context Window Beyond 2M Tokens
It's been possible to skip tokenization for a long time, my team and I did it here - https://github.com/capitalone/DataProfiler
For what it's worth, we actually were working with LSTMs with nearly a billion params back in 2016-2017 area. Transformers made it far more effective to train and execute, but ultimately LSTMs are able to achieve similar results, though slow & require more training data.
- Data Profiler – What's in your data?
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Data Profiler 0.9.0 -- offering a massive improvement to memory usage during profiling of large datasets
Great call out -- would you be willing to write up an issue for that on the repo? Thank you! https://github.com/capitalone/DataProfiler/issues/new/choose
- FLiPN-FLaNK Stack Weekly for 20 March 2023
- Release 0.8.3 · capitalone/DataProfiler
What are some alternatives?
libpostal - A C library for parsing/normalizing street addresses around the world. Powered by statistical NLP and open geo data.
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
pyWhat - 🐸 Identify anything. pyWhat easily lets you identify emails, IP addresses, and more. Feed it a .pcap file or some text and it'll tell you what it is! 🧙♀️
lightly - A python library for self-supervised learning on images.
addok - Search engine for address. Only address.
lightdash - Self-serve BI to 10x your data team ⚡️
probablepeople - :family: a python library for parsing unstructured western names into name components.
SymSpell - SymSpell: 1 million times faster spelling correction & fuzzy search through Symmetric Delete spelling correction algorithm
vtuber-livechat-dataset - 📊 VTuber 1B: Billion-scale Live Chat and Moderation Event Dataset
ctparse - Parse natural language time expressions in python
sheet2dict - Simple XLSX and CSV to dictionary converter