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AI-and-Analytics/Getting-Started-Samples/IntelModin_GettingStarted/README.md

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# `Intel® Modin* Get Started` Sample
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# Modin Get Started Sample
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The `Intel® Modin Getting Started` sample demonstrates how to use distributed Pandas using the Intel® Distribution of Modin* package. It demonstrates how to use software products that can be found in the [Intel® AI Tools](https://software.intel.com/content/www/us/en/develop/tools/oneapi/ai-analytics-toolkit.html).
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The `Modin Getting Started` sample demonstrates how to use distributed Pandas using the Modin package.
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| Area | Description
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| :--- | :---
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| What you will learn | Basic Intel® Distribution of Modin* programming model for Intel processors
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| Time to complete | 5 to 8 minutes
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| Category | Getting Started
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| What you will learn | Basic Modin programming model for Intel processors
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| Time to complete | 5 to 8 minutes
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## Purpose
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Intel® Distribution of Modin* uses Ray or Dask to provide a method to speed up your Pandas notebooks, scripts, and libraries. Unlike other distributed DataFrame libraries, Intel® Distribution of Modin* provides integration and compatibility with existing Pandas code.
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Modin uses Ray or Dask to provide a method to speed up your Pandas notebooks, scripts, and libraries. Unlike other distributed DataFrame libraries, Modin provides integration and compatibility with existing Pandas code.
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In this sample, you will run Intel® Distribution of Modin*-accelerated Pandas functions and note the performance gain when compared to "stock" (or standard) Pandas functions.
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In this sample, you will run Modin-accelerated Pandas functions and note the performance gain when compared to "stock" (or standard) Pandas functions.
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## Prerequisites
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| Optimized for | Description
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| :--- | :---
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| OS | Ubuntu* 18.04 (or newer)
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| Hardware | Intel® Atom® processors <br> Intel® Core™ processor family <br> Intel® Xeon® processor family <br> Intel® Xeon® Scalable Performance processor family
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| Software | Intel® Distribution of Modin*
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| Software | Modin
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## Key Implementation Details
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This get started sample code is implemented for CPU using the Python language. The example assumes you have Pandas and Modin installed inside a conda environment.
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## Configure Environment
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## Environment Setup
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1. Install Intel® Distribution of Modin* in a new conda environment.
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1. Install Modin in a new conda environment.
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>**Note:** replace python=3.x with your own Python version
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```
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conda create -n aikit-modin python=3.x -y
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conda activate aikit-modin
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conda install modin-all -c intel -y
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conda create -n modin python=3.x -y
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conda activate modin
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conda install modin-all -c conda-forge -y
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```
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2. Install Matplotlib.
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```
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conda install -c intel matplotlib -y
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conda install -c conda-forge matplotlib -y
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```
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3. Install Jupyter Notebook.
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conda install ipykernel
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python -m ipykernel install --user --name usr_modin
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```
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## Run the `Intel® Modin* Get Started` Sample
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## Run the `Modin Get Started` Sample
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You can run the Jupyter notebook with the sample code on your local server or download the sample code from the notebook as a Python file and run it locally. Visit [Intel® Distribution of Modin Getting Started Guide](https://www.intel.com/content/www/us/en/developer/articles/technical/intel-distribution-of-modin-getting-started-guide.html) for more information.
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You can run the Jupyter notebook with the sample code on your local server or download the sample code from the notebook as a Python file and run it locally.
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### Run the Sample in Visual Studio Code* (Optional)
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3. Locate and open the Notebook.
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```
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IntelModin_GettingStarted.ipynb
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Modin_GettingStarted.ipynb
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```
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4. Click the **Run** button to move through the cells in sequence.
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### Run the Python Script Locally
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1. Convert ``IntelModin_GettingStarted.ipynb`` to a Python file. There are two options.
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1. Convert ``Modin_GettingStarted.ipynb`` to a Python file. There are two options.
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1. Open the notebook and download the script as Python file: **File > Download as > Python (py)**.
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2. Convert the notebook file to a Python script using commands similar to the following.
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```
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jupyter nbconvert --to python IntelModin_GettingStarted.ipynb
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jupyter nbconvert --to python Modin_GettingStarted.ipynb
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```
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2. Run the Python script.
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```
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ipython IntelModin_GettingStarted.py
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ipython Modin_GettingStarted.py
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```
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### Expected Output
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The expected cell output is shown in the `IntelModin_GettingStarted.ipynb` Notebook.
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The expected cell output is shown in the `Modin_GettingStarted.ipynb` Notebook.
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## Related Samples
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* [Modin Vs. Pandas Performance](https://github.com/oneapi-src/oneAPI-samples/tree/master/AI-and-Analytics/Getting-Started-Samples/Modin_Vs_Pandas)
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## License
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Code samples are licensed under the MIT license. See
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[License.txt](https://github.com/oneapi-src/oneAPI-samples/blob/master/License.txt) for details.
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Third party program Licenses can be found here: [third-party-programs.txt](https://github.com/oneapi-src/oneAPI-samples/blob/master/third-party-programs.txt).
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*Other names and brands may be claimed as the property of others. [Trademarks](https://www.intel.com/content/www/us/en/legal/trademarks.html)

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