Modin* Cheat Sheet

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