finance-courses
Notes and examples about Portfolio Construction and Analysis with Python (Jupyter notebooks) (by z4ir3)
COVID19_mobility
COVID-19 Mobility Data Aggregator. Scraper of Google, Apple, Waze and TomTom COVID-19 Mobility Reports🚶🚘🚉 (by ActiveConclusion)
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| finance-courses | COVID19_mobility | |
|---|---|---|
| 9 | 5 | |
| 157 | 263 | |
| - | - | |
| 2.7 | 4.0 | |
| 5 months ago | 6 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
finance-courses
Posts with mentions or reviews of finance-courses.
We have used some of these posts to build our list of alternatives
and similar projects.
COVID19_mobility
Posts with mentions or reviews of COVID19_mobility.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-12-08.
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How did everyone here learn how to webscrape? and have any of you made any cool projects with it?
Specifically for learning Scrapy, I recommend this book, which helped me at the starting point. https://www.amazon.com/Learning-Scrapy-Dimitrios-Kouzis-Loukas/dp/1784399787 But this, of course, is not enough, only practice and studying the experience of experienced colleagues on a real project have seriously improved my mastery. I also have a pet project, which I am not super proud of, but anyway, that has given me invaluable experience in maintaining open-source repo. https://github.com/ActiveConclusion/COVID19_mobility Despite some poor architectural decisions, I see that it's cited in some papers and used in university course labs works because sometimes students still ask me something about it. I absolutely didn't expect that, it looks sort of funny and nice to me.
- Archive of Apple Mobility Data (COVID)
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Coronavirus Datsets
COVID-19 Mobility Data Aggregator [source comment]
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Any Practical Python Book for a Beginner starting his Machine Learning Journey?
Download some real data https://github.com/ActiveConclusion/COVID19_mobility and play with it.
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A national mask mandate in the US early in the COVID-19 pandemic could have led to as much as 47% less deaths nationally by the end of May, which roughly translates to up to 47,000 saved lives.
I haven't stayed up with it, but did some early tinkering with Google Mobility data and found that every county in the US was trending similarly across all categories in the Google Mobility data (e.g. down in workplace and recreation, up in residential).
What are some alternatives?
When comparing finance-courses and COVID19_mobility you can also consider the following projects:
covid19za - Coronavirus COVID-19 (2019-nCoV) Data Repository and Dashboard for South Africa
airscraper - Airtable backup script package
music-downloader - This program will first get the metadata of various songs from metadata providers like musicbrainz, and then search for download links on pages like bandcamp. Then it will download the song and edit the metadata accordingly.
covid-19-data - A repository of data on coronavirus cases and deaths in the U.S.
ncov - Nextstrain build for novel coronavirus SARS-CoV-2
Respiratory-Disease-Coughing-Dataset-CNN - A collection of coughing audio files from Coswara, Coughvid, and Virufy as well as generated spectrograms for the use of machine learning