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"cell_type": "code",
"execution_count": 1,
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"outputs": [
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"name": "stdout",
"output_type": "stream",
"text": [
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"Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from plotly) (1.14.0)\n",
"Requirement already satisfied: retrying>=1.3.3 in /usr/local/lib/python3.6/dist-packages (from plotly) (1.3.3)\n"
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"source": [
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"metadata": {},
"outputs": [],
"source": [
"import re\n",
"from pathlib import Path\n",
"from typing import Union, List\n",
"from plotly import express as px\n",
"from plotly import graph_objects as go"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# Ensure that we have a `data` directory we use to store downloaded data\n",
"!mkdir -p data\n",
"data_dir: Path = Path('data')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"File ‘data/AutoInsurSweden.txt’ already there; not retrieving.\n",
"\n"
]
}
],
"source": [
"# Downloading the \"Auto Insurance in Sweden\" data set\n",
"!wget -nc -P data https://www.math.muni.cz/~kolacek/docs/frvs/M7222/data/AutoInsurSweden.txt"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Auto Insurance in Sweden\n",
"\n",
"In the following data\n",
"X = number of claims\n",
"Y = total payment for all the claims in thousands of Swedish Kronor\n",
"for geographical zones in Sweden\n",
"Reference: Swedish Committee on Analysis of Risk Premium in Motor Insurance\n",
"http://college.hmco.com/mathematics/brase/understandable_statistics/7e/students/datasets/\n",
" slr/frames/frame.html\n",
"\n",
"X\tY\n",
"108\t392,5\n",
"19\t46,2\n",
"13\t15,7\n",
"124\t422,2\n",
"40\t119,4\n",
"57\t170,9\n",
"23\t56,9\n",
"14\t77,5\n",
"45\t214\n"
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}
],
"source": [
"!head -n 20 data/AutoInsurSweden.txt"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"# Create the Python path pointing to the `AutoInsurSweden.txt` file\n",
"insurance_data_path: Path = data_dir / 'AutoInsurSweden.txt'"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"# Read the `AutoInsurSweden.txt` file, extract the `x` and `y` values via regex and store them into vectors\n",
"xs: List[float] = []\n",
"ys: List[float] = []\n",
"\n",
"with open(insurance_data_path) as file:\n",
" content: str = file.read()\n",
" for x, y in re.findall(r'([\\d,]+)\\t([\\d,]+)', content):\n",
" xs.append(float(x.replace(',', '.')))\n",
" ys.append(float(y.replace(',', '.')))"
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},
{
"cell_type": "code",
"execution_count": 8,
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"source": [
"# A convenience function which creates a scatter plot with an optional line\n",
"def plot(xs: List[float], ys: List[float], ys_pred: Union[List[float], None] = None) -> None:\n",
" fig = px.scatter(x=xs, y=ys, labels={'x': 'Number of claims', 'y': 'Total payment'})\n",
" # If present, add the line\n",
" if ys_pred:\n",
" fig.add_trace(\n",
" go.Scatter(\n",
" x=xs, y=ys_pred, name='Guess'\n",
" )\n",
" )\n",
" fig.show()"
]
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