May 24, 2022 · However, passing a meta attribute to read_sql_query and setting head_rows=0 is completely ok as long as there's an efficient way to retrieve/create while dask-sql might work …

Sep 6, 2019 · 36 dask delayed 10.288054704666138s my cpu has 6 physical cores Question Why does Dask perform so slower while multiprocessing perform so much faster? Am I using …

Jun 20, 2017 · The documentation for Dask talks about repartioning to reduce overhead here. They however seem to indicate you need some knowledge of what your dataframe will look …

As of August 2017, Pandas DataFame.apply() is unfortunately still limited to working with a single core, meaning that a multi-core machine will waste the majority of its compute-time when you …

May 15, 2018 · How should I get the shape of a dask dataframe? Asked 7 years, 6 months ago Modified 1 year, 6 months ago Viewed 26k times

Dask dataframes: reading multiple files & storing filename in column Asked 7 years, 9 months ago Modified 6 years, 8 months ago Viewed 11k times

Find the dask package suitable for your python version from the release history page of the pypi dask page. Go back to colab and remove dask completely !pip uninstall dask

Jul 2, 2021 · I am importing a very large csv file ~680GB using Dask, however, the output is not what I expect. My aim is to select only some columns (6/50), and perhaps filter them (this I am …

Jun 8, 2017 · This is required because apply() is flexible enough that it can produce just about anything from a dataframe. As you can see, if you don't provide a meta, then dask actually …

Jul 15, 2022 · TypeError: Cannot interpret 'string[python]' as a data type string[python] is just an example, whatever is your dd["series1"] datatype will be inputed here. So my question is: What …