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{
"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
}