Dask
Pandas
Apache Airflow
NumPy
Apache Spark
Burla
Celery
SciPy
Apple Watch
Fitbit Blaze
Fitbit Charge
Apple Watch Series 3
Moto 360
WHOOP Strap
Blocks
Galaxy Watch Active
Apple WatchBased on our record, Dask seems to be more popular. It has been mentiond 16 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
We're using a lot of Python. In addition to these, gridMET, Dask, HoloViz, and kerchunk. Source: about 2 years ago
I wrote this for speeding up the RPC messaging in dask, but figured it might be useful for others as well. The source is available on github here: https://github.com/jcrist/msgspec. Source: about 2 years ago
Dask: Distributed data frames, machine learning and more. - Source: dev.to / over 2 years ago
To do that, we are efficiently using Dask, simply creating on-demand local (or remote) clusters on task run() method:. - Source: dev.to / over 2 years ago
I’m quite sure dask helps and has a pandas like api though will use disk and not just RAM. Source: over 2 years ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Fitbit Blaze - Fitbit Blaze is a smartwatch that includes both a heart rate monitor and a fitness activity tracker. It comes with a color touchscreen, and you can change both the watch's strap and frame. Read more about Fitbit Blaze.
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
Fitbit Charge - Activity and sleep tracking wristband
NumPy - NumPy is the fundamental package for scientific computing with Python
Apple Watch Series 3 - Apple's newest internet-connected smartwatch