diff --git a/AI-and-Analytics/End-to-end-Workloads/Census/census_modin.ipynb b/AI-and-Analytics/End-to-end-Workloads/Census/census_modin.ipynb index 95d79349fe..746d53a8d4 100644 --- a/AI-and-Analytics/End-to-end-Workloads/Census/census_modin.ipynb +++ b/AI-and-Analytics/End-to-end-Workloads/Census/census_modin.ipynb @@ -56,7 +56,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Import basic python modules" + "Import basic python modules and disable warnings to avoid output cluttering" ] }, { @@ -66,7 +66,10 @@ "outputs": [], "source": [ "import os\n", - "import numpy as np" + "import numpy as np\n", + "import warnings\n", + "\n", + "warnings.filterwarnings(\"ignore\")" ] }, { @@ -90,11 +93,20 @@ }, "outputs": [], "source": [ - "#import modin.pandas as pd\n", - "os.environ[\"MODIN_ENGINE\"] = \"native\"\n", - "os.environ[\"MODIN_BACKEND\"] = \"omnisci\"\n", - "os.environ[\"MODIN_EXPERIMENTAL\"] = \"True\"\n", - "import modin.pandas as pd" + "#import pandas as pd\n", + "import modin.pandas as pd\n", + "\n", + "import modin.config as cfg\n", + "from packaging import version\n", + "import modin\n", + "\n", + "cfg.IsExperimental.put(\"True\")\n", + "cfg.Engine.put('native')\n", + "# Since modin 0.12.0 OmniSci engine activation process slightly changed\n", + "if version.parse(modin.__version__) <= version.parse('0.11.3'):\n", + " cfg.Backend.put('omnisci')\n", + "else:\n", + " cfg.StorageFormat.put('omnisci')\n" ] }, { @@ -148,7 +160,7 @@ }, "outputs": [], "source": [ - "df = pd.read_csv('ipums_education2income_1970-2010.csv.gz', compression=\"gzip\", nrows=10000)" + "df = pd.read_csv('ipums_education2income_1970-2010.csv.gz')" ] }, { @@ -183,9 +195,9 @@ "df = df[keep_cols]\n", "\n", "# clean up samples with invalid income, education, etc.\n", - "df = df.query(\"INCTOT != 9999999\")\n", - "df = df.query(\"EDUC != -1\")\n", - "df = df.query(\"EDUCD != -1\")\n", + "df = df[df[\"INCTOT\"] != 9999999]\n", + "df = df[df[\"EDUC\"] != -1]\n", + "df = df[df[\"EDUCD\"] != -1]\n", "\n", "# normalize income for inflation\n", "df[\"INCTOT\"] = df[\"INCTOT\"] * df[\"CPI99\"]\n", diff --git a/AI-and-Analytics/End-to-end-Workloads/Census/sample.json b/AI-and-Analytics/End-to-end-Workloads/Census/sample.json index 49f3a324a7..995ed5217e 100755 --- a/AI-and-Analytics/End-to-end-Workloads/Census/sample.json +++ b/AI-and-Analytics/End-to-end-Workloads/Census/sample.json @@ -10,16 +10,19 @@ "targetDevice": ["CPU"], "ciTests": { "linux": [ - { - "env": ["source activate base"], - "steps": [ - "conda create -y -n intel-aikit-modin intel-aikit-modin -c intel", - "conda activate intel-aikit-modin", - "conda install -y runipy", - "pip install opencensus", - "runipy census_modin.ipynb" - ] - } + { + "env": [], + "id": "Intel_Modin_E2E_py", + "steps": [ + "set -e # Terminate the script on first error", + "source $(conda info --base)/etc/profile.d/conda.sh # Bypassing conda's disability to activate environments inside a bash script: https://github.com/conda/conda/issues/7980", + "conda create -y -n intel-aikit-modin intel-aikit-modin -c intel", + "conda activate intel-aikit-modin", + "conda install -y jupyter # Installing 'jupyter' for extended abilities to execute the notebook", + "pip install opencensus # Installing 'runipy' for extended abilities to execute the notebook", + "jupyter nbconvert --to notebook --execute census_modin.ipynb" + ] + } ] } } diff --git a/AI-and-Analytics/Getting-Started-Samples/IntelModin_GettingStarted/README.md b/AI-and-Analytics/Getting-Started-Samples/IntelModin_GettingStarted/README.md index fc30994458..849d51d04a 100644 --- a/AI-and-Analytics/Getting-Started-Samples/IntelModin_GettingStarted/README.md +++ b/AI-and-Analytics/Getting-Started-Samples/IntelModin_GettingStarted/README.md @@ -68,17 +68,17 @@ source activate intel-aikit-modin ### Activate conda environment Without Root Access (Optional) -By default, the Intel® oneAPI AI Analytics toolkit is installed in the `oneapi` folder, which requires root privileges to manage it. If you would like to bypass using root access to manage your conda environment, then you can clone your desired conda environment using the following command: +By default, the Intel® oneAPI AI Analytics toolkit is installed in the `oneapi` folder, which requires root privileges to manage it. If you would like to bypass using root access to manage your conda environment, then you can install the Intel® Distribution of Modin* python environment with the following command: #### Linux + ``` -conda create --name user-intel-aikit-modin --clone intel-aikit-modin +conda create -y -n modin-conda-forge -c conda-forge modin-all +conda install -y -n modin-conda-forge -c conda-forge matplotlib ``` - Then activate your conda environment with the following command: - ``` -source activate user-intel-aikit-modin +conda activate modin-conda-forge ``` @@ -87,7 +87,7 @@ source activate user-intel-aikit-modin Launch Jupyter Notebook in the directory housing the code example: ``` -conda install jupyter nb_conda_kernels +conda install jupyter nb_conda_kernels -c conda-forge -y ``` #### View in Jupyter Notebook