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uawardata
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| data | uawardata | |
|---|---|---|
| 116 | 3 | |
| 16,631 | 113 | |
| 0.4% | - | |
| 8.5 | 0.0 | |
| about 2 months ago | over 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Creative Commons Attribution 4.0 | - |
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.
data
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[USMNT] It only took 20 caps for Jesus Ferreira to get double-digit goals. The fastest in #USMNT history.
You of course already know this answer, but just to put it into more perspective. Here are the SPI ranking equivalents to what he did with these 11 goals in Scotland and Switzerland.
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[Effortpost] Advanced stats on which players are contributing the most to the Heat's playoff run.
To answer these questions I decided to look at 538’s RAPTOR ratings. RAPTOR uses player tracking data to estimate how much each player contributes on the offensive and defensive ends. The total RAPTOR score should be something like the “number of points a player contributes to his team’s offense and defense per 100 possessions, relative to a league-average player.” Higher is better, best during the regular season has been Nikola Jokic at +14. You can read more about it here or play with an interactive tool on their website here. I don’t really care about the details of why it’s a good statistic, but it seems pretty helpful and most importantly for my purposes you can download the data here for free.
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Consanguineous marriage percentage per country
EDIT: I came to this data from this repository which has a nice csv collection for machine training.
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USMNT is a European club. How did they do this season?
Looks like we may actually be collectively underrating our guys now. That's an interesting change. Based on SPI (rating = 72.4) we would be:
- Derrick White's WAR over the past season has been ~6.7 according to a composite of various metrics. Derrick White's WAR in the playoffs has been ~0.1 according to RAPTOR. The worst among the main Boston roster
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Nate Silver: Some personal news
Before Disney/ABC get any -ideas-, might be a good chance to get our hands on at least their data[0]!
[0]: https://data.fivethirtyeight.com/
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In honor of Sexual Assault Awareness Month, make sure neither you nor friends harbor any misconceptions about consent
Most young women expect words to be involved when their partner seeks their consent. 43% of young men actually ask for verbal confirmation of consent. Overall, verbal indicators of consent or nonconsent are more common than nonverbal indicators. More open communication also increases the likelihood of orgasm for women.
- CMV: When selecting a movie to watch, the audience's rating is the only thing that matters and the critic's rating is entirely irrelevant.
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Slight majority of people in WA want to leave state, poll finds
DHM does not use an equity sample. Of all polling operations they rank 250 out of 517. Id like to see another pollster https://github.com/fivethirtyeight/data/blob/master/pollster-ratings/pollster-ratings.csv
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Optimism is bad for your health. So lets just do some maths! How can Liverpool FC get top 4? part 2
LOL My github’s pretty sparse but I’m pulling data from this API; 538 also provides the data they use for their club predictions here if that interests you
uawardata
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I found an intteractive map locating all Russian military forces. Can anyone verify how up-to-date it is?
They provide dates with their data, but the data only goes up to September. The raw data is also available on Github, if you need that as well: https://github.com/simonhuwiler/uawardata
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Need a website for monitoring Russian attacks and movement
The data is also hosted on Github: https://github.com/simonhuwiler/uawardata
- According to preliminary information Russian invasion troops are in the pocket near Kherson. They were allowed to give up in 2 days or they will be destroyed.
What are some alternatives?
tidytuesday - Official repo for the #tidytuesday project
datasets - 🎁 5,400,000+ Unsplash images made available for research and machine learning
ydata-quality - Data Quality assessment with one line of code
kuwala - Kuwala is the no-code data platform for BI analysts and engineers enabling you to build powerful analytics workflows. We are set out to bring state-of-the-art data engineering tools you love, such as Airbyte, dbt, or Great Expectations together in one intuitive interface built with React Flow. In addition we provide third-party data into data science models and products with a focus on geospatial data. Currently, the following data connectors are available worldwide: a) High-resolution demographics data b) Point of Interests from Open Street Map c) Google Popular Times
quilt - Quilt is a data mesh for connecting people with actionable data
images - Public domain photos of Members of the United States Congress
CodeSearchNet - Datasets, tools, and benchmarks for representation learning of code.
fraud-detection-handbook - Reproducible Machine Learning for Credit Card Fraud Detection - Practical Handbook
Video-Swin-Transformer - This is an official implementation for "Video Swin Transformers".
PyCBC-Tutorials - Learn how to use PyCBC to analyze gravitational-wave data and do parameter inference.
datagen - Generates customer, sales reps, sales mgrs, products, manufacturer, and transaction data and creates and populates MySQL database with it. Also, can generate single tables of random data.