{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "737ff348-7e92-4a56-bb19-9c5ccb038383",
   "metadata": {},
   "source": [
    "# GDP growth rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3b025d0c-56e5-47ff-a7fc-f4821e8b6343",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Subscribe to api.insee.fr and get your credentials!\n",
    "# Save your credentials with init_conn function :\n",
    "# from pynsee.utils import init_conn\n",
    "# init_conn(insee_key=\"my_insee_key\", insee_secret=\"my_insee_secret\")\n",
    "\n",
    "# Beware : any change to the keys should be tested after having cleared the cache\n",
    "# Please do : from pynsee.utils import clear_all_cache; clear_all_cache()\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "45d8f81f-83b4-4d5a-8736-5018f5fed017",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pynsee.macrodata import get_dataset_list, get_series_list, get_series\n",
    "\n",
    "import pandas as pd\n",
    "import matplotlib.ticker as ticker\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "26a6a286-8aa0-4832-83c6-0061e475cd37",
   "metadata": {},
   "outputs": [],
   "source": [
    "import logging\n",
    "import sys\n",
    "logging.basicConfig(stream=sys.stdout,\n",
    "                    level=logging.INFO, \n",
    "                    format=\"%(message)s\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "18dcbf6f-82d3-425f-b761-7ab761b76420",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Existing environment variables used, instead of locally saved credentials\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Getting datasets list: 100%|██████████| 201/201 [00:00<00:00, 1730.69it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Locally saved data has been used\n",
      "Set update=True to trigger an update\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "1/1 - Getting series: 100%|██████████| 1/1 [00:00<00:00,  3.46it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# get macroeconomic datasets list\n",
    "insee_dataset = get_dataset_list()\n",
    "insee_dataset.head()\n",
    "\n",
    "# get series key (idbank), for Gross domestic product balance\n",
    "id = get_series_list(\"CNT-2014-PIB-EQB-RF\")\n",
    "\n",
    "id = id.loc[(id.FREQ == \"T\") &\n",
    "            (id.OPERATION == \"PIB\") &\n",
    "            (id.NATURE == \"TAUX\") &\n",
    "            (id.CORRECTION == \"CVS-CJO\")]\n",
    "\n",
    "data = get_series(id.IDBANK)\n",
    "#data = split_title(df = data, n_split=2)\n",
    "\n",
    "# define plot\n",
    "ax = data.plot(kind='bar', x=\"TIME_PERIOD\", stacked=True, y=\"OBS_VALUE\", figsize=(15,5))\n",
    "#add title\n",
    "plt.title(\"French GDP growth rate, quarter-on-quarter, sa-wda\")\n",
    "# customize x-axis tickers\n",
    "ticklabels = ['']*len(data.TIME_PERIOD)\n",
    "ticklabels[::12] = [item for item in data.TIME_PERIOD[::12]]\n",
    "ax.xaxis.set_major_formatter(ticker.FixedFormatter(ticklabels))\n",
    "plt.gcf().autofmt_xdate()\n",
    "#remove legend\n",
    "ax.get_legend().remove()\n",
    "#remove x-axistitle\n",
    "ax.xaxis.label.set_visible(False)\n",
    "plt.show()"
   ]
  }
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