
Dask
Pandas
NumPy
Apache Airflow
SciPy
Anaconda
PySpark
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Based 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: over 4 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: over 4 years ago
Dask: Distributed data frames, machine learning and more. - Source: dev.to / over 4 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 4 years ago
Iโm quite sure dask helps and has a pandas like api though will use disk and not just RAM. Source: over 4 years ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
NumPy - NumPy is the fundamental package for scientific computing with Python
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
SciPy - SciPy is a Python-based ecosystem of open-source software for mathematics, science, and engineering.ย
Anaconda - Anaconda is the leading open data science platform powered by Python.
PySpark - PySpark Tutorial - Apache Spark is written in Scala programming language. To support Python with Spark, Apache Spark community released a tool, PySpark. Using PySpark, you can wor