diff --git a/time_series/prophet_pymc3.ipynb b/time_series/prophet_pymc3.ipynb
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+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "import pymc3 as pm\n",
+ "import matplotlib.pyplot as plt\n",
+ "from scipy import stats\n",
+ "import pandas as pd\n",
+ "import theano\n",
+ "import theano.tensor as tt\n",
+ "from fbprophet import Prophet"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 319,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "df = pd.read_csv('caracteristics.csv', encoding='latin1' )\n",
+ "a = pd.DataFrame(df[['jour', 'mois', 'an']].values, columns=['day', 'month', 'year'])\n",
+ "a['year'] += 2000\n",
+ "a = pd.to_datetime(a, dayfirst=True)\n",
+ "df['date'] = a\n",
+ "del a"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 337,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "df = df.groupby('date')['Num_Acc'].count()\n",
+ "df = df.reset_index(-1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 363,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
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+ " \n",
+ " \n",
+ " | \n",
+ " y | \n",
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\n",
+ " \n",
+ " \n",
+ " \n",
+ " | count | \n",
+ " 4.383000e+03 | \n",
+ "
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+ " \n",
+ " | mean | \n",
+ " -4.150101e-16 | \n",
+ "
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+ " \n",
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+ " \n",
+ " | 50% | \n",
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+ " \n",
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+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "df = df.rename({'date': 'ds', \"Num_Acc\": 'y'}, axis=1)\n",
+ "df['y'] = (df.y - df.y.mean()) / df.y.std()\n",
+ "df.plot(x='ds', figsize=(16, 6))\n",
+ "df.describe()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 90,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
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+ " \n",
+ " \n",
+ " | \n",
+ " y | \n",
+ "
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+ " \n",
+ " \n",
+ " \n",
+ " | count | \n",
+ " 2.905000e+03 | \n",
+ "
\n",
+ " \n",
+ " | mean | \n",
+ " -1.134912e-15 | \n",
+ "
\n",
+ " \n",
+ " | std | \n",
+ " 1.000000e+00 | \n",
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+ " \n",
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+ " | 75% | \n",
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