Get started with Intel® Distribution of Modin* using the following commands.
For additional installation and tuning methods, see the Getting Started Guide and Performance and Tuning Guide.
For more information, see Intel Distribution of Modin.
Recommended Installation Using Anaconda* (All Back Ends) |
conda install -c conda-forge modin-all |
Recommended Installation Using Anaconda (Ray Framework Back End) |
conda install -c conda-forge modin-ray |
Recommended Installation Using Anaconda (Dask* Back End) |
conda install -c conda-forge modin-dask |
Recommended Installation Using Anaconda (OmniSci* Back End) |
conda install -c conda-forge modin-omnisci |
Installation Using PyPI* (All Back Ends) |
pip install modin[all] |
Installation Using PyPI (Ray Framework Back End) |
pip install modin[ray] |
Installation Using PyPI (Dask Back End) |
pip install modin[dask] |
Switch to a Ray Framework Back End with a Command Prompt (If Not Enabled): For Versions After 0.12 |
export MODIN_STORAGE_FORMAT=ray |
Switch to a Ray Framework Back End in the Code (If Not Enabled): For Versions After 0.12 |
import modin.config as cfg cfg.StorageFormat.put(‘ray’) import modin.pandas as pd |
Switch to a Dask Back End with a Command Prompt (If Not Enabled): For Versions After 0.12 |
export MODIN_STORAGE_FORMAT=dask |
Switch to a Dask Back End In the Code (If Not Enabled): For Versions After 0.12 |
import modin.config as cfg cfg.StorageFormat.put(‘dask’) import modin.pandas as pd |
Switch to an OmniSci* Back End with a Command Prompt (If Not Enabled): For Versions After 0.12 |
export MODIN_STORAGE_FORMAT=omnisci |
Switch to an OmniSci Back End In the Code (If Not Enabled): For Versions After 0.12 |
import modin.config as cfg cfg.StorageFormat.put(‘omnisci’) import modin.pandas as pd |
Convert a Modin Object to a Pandas Object (Example in Bold) |
import modin.pandas as pd df_log=pd.concat([self.df_log])
import pandas as pd occ_dict = dict(df_log['EventTemplate']._to_pandas().value_counts()) df_event = pd.DataFrame() df_event['EventTemplate'] = df_log['EventTemplate'].unique() |
Set Number of Cores Modin Uses (Modin Uses All Available Resources by Default) |
# set to Modin to only utilize 4 cores export MODIN_CPUS=4 |
For more information and support, or to report any issues, see:
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