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Copy file name to clipboardExpand all lines: AI-and-Analytics/Getting-Started-Samples/IntelModin_GettingStarted/README.md
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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" (aka standard) Pandas functions.
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## Key Implementation Details
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This Getting Started sample code is implemented for CPU using the Python language. The example assumes you have Pandas and MoIntel Distribution of Modin* installed inside a conda environment, similar to what is directed by the [Intel® oneAPI AI Analytics Toolkit](https://www.intel.com/content/www/us/en/develop/documentation/installation-guide-for-intel-oneapi-toolkits-linux/top/installation/install-using-package-managers/conda/install-intel-ai-analytics-toolkit-via-conda.html).
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This Getting Started sample code is implemented for CPU using the Python language. The example assumes you have Pandas and Modin installed inside a conda environment, similar to what is directed by the [Intel® oneAPI AI Analytics Toolkit](https://www.intel.com/content/www/us/en/develop/documentation/installation-guide-for-intel-oneapi-toolkits-linux/top/installation/install-using-package-managers/conda/install-intel-ai-analytics-toolkit-via-conda.html).
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## License
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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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## Building Intel Distribution of Modin* for CPU
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## Running Samples on the Intel® DevCloud
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If you are running this sample on the DevCloud, see [Running Samples on the Intel® DevCloud](#run-samples-on-devcloud)
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## Building Modin for CPU
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Intel Distribution of Modin* is ready for use once you finish the Intel Distribution of Modin installation and have run the post installation script.
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jupyter notebook
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```
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## Running the Sample
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## Running the Sample<aname="running-the-sample"></a>
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### Run as Jupyter Notebook
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### Run as Jupyter Notebook<aname="run-as-jupyter-notebook"></a>
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Open .ipynb file and run cells in Jupyter Notebook using the "Run" button (see the image using "daal4py Hello World" sample):
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`python IntelModin_GettingStarted.py`
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##### Expected Printed Output:
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Expected Cell Output is shown in IntelModin_GettingStarted.ipynb.
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Expected Cell Output is shown in IntelModin_GettingStarted.ipynb
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### Running Samples on the Intel® DevCloud (Optional)<aname="run-samples-on-devcloud"></a>
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<!---Include the next paragraph ONLY if the sample runs in batch mode-->
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### Run in Batch Mode
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This sample runs in batch mode, so you must have a script for batch processing. Once you have a script set up, refer to [Running the Sample](#running-the-sample).
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<!---Include the next paragraph ONLY if the sample DOES NOT RUN in batch mode-->
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### Run in Interactive Mode
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This sample runs in interactive mode. For more information, see [Run as Juypter Notebook](#run-as-jupyter-notebook).
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### Request a Compute Node
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In order to run on the DevCloud, you need to request a compute node using node properties such as: `gpu`, `xeon`, `fpga_compile`, `fpga_runtime` and others. For more information about the node properties, execute the `pbsnodes` command.
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This node information must be provided when submitting a job to run your sample in batch mode using the qsub command. When you see the qsub command in the Run section of the [Hello World instructions](https://devcloud.intel.com/oneapi/get_started/aiAnalyticsToolkitSamples/), change the command to fit the node you are using. Nodes which are in bold indicate they are compatible with this sample:
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### Build and run additional samples
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Several sample programs are available for you to try, many of which can be compiled and run in a similar fashion. Experiment with running the various samples on different kinds of compute nodes or adjust their source code to experiment with different workloads.
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