{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Analytics Module\n", "The Analytics module provides descriptive statistics on content data, evidence data and model evaluations " ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# reloads modules automatically before entering the execution of code\n", "%load_ext autoreload\n", "%autoreload 2\n", "\n", "# third parties imports\n", "import numpy as np \n", "import pandas as pd\n", "# -- add new imports here --\n", "\n", "# local imports\n", "from constants import Constant as C\n", "from loaders import load_ratings\n", "from loaders import load_items" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 1 - Content analytics\n", "Explore and perform descriptive statistics on content data" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "# -- load the items and display the Dataframe" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "# -- display relevant informations that can be extracted from the dataset" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 2 - Evidence analytics\n", "Explore and perform descriptive statistics on evidence data" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "# -- load the items and display the Dataframe" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "# -- display relevant informations that can be extracted from the dataset" ] } ], "metadata": { "kernelspec": { "display_name": "mlsmm2156", "language": "python", "name": "mlsmm2156" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.9" } }, "nbformat": 4, "nbformat_minor": 4 }