{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## PyMC3 example"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import pymc3 as pm\n",
"\n",
"%config InlineBackend.figure_format = 'retina'\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"sns.set()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Python version: 3.7.7 (default, Mar 23 2020, 23:19:08) [MSC v.1916 64 bit (AMD64)]\n",
"Numpy version: 1.18.1\n",
"PyMC3 version: 3.8\n"
]
}
],
"source": [
"import sys\n",
"print(\"Python version:\", sys.version)\n",
"print(\"Numpy version:\", np.__version__)\n",
"print(\"PyMC3 version:\", pm.__version__)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_csv(\"intervals.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
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