exchange-rates-in-argentina.ipynb

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    "# Exchange rates in Argentina\n",
    "\n",
    "Argentinian economy has two exchange rates to USD. An official and an unofficial (called blue). \n",
    "\n",
    "The goals of this notebook are: \n",
    "\n",
    "1.\tRead a dataset with the official exchange rates.\n",
    "2.\tRead a dataset with the unofficial (blue) exchange rates.\n",
    "3.\tMerge those datasets.\n",
    "4.\tCalculate the mean between buy and sell for both exchange rates. \n",
    "5.\tAnalyze the correlation along time for these exchange rates. \n",
    "\n",
    "\n",
    "**Metadata for official and unofficial (blue) exchange rates**\n",
    "\n",
    "Field | Detail | Type \n",
    "------|--------|-----\n",
    "date (index) | Quote date | Date \n",
    "buy | purchase price per dollar | float\n",
    "sell | sales price per dollar | float\n",
    "\n",
    "**Metada for interest rates**\n",
    "\n",
    "\n",
    "Field | Detail | Type \n",
    "------|--------|-----\n",
    "indice_tiempo | Time index | Date: dd/MM/yyyy\n",
    "tasas_interes_call | Interest rates Call | float number\n",
    "tasas_interes_badlar | Interest rates Badlar | float number\n",
    "tasas_interes_pm | Interest rates PM (Monetary policies) | float number"
   ]
  },
  {
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   "metadata": {},
   "source": [
    "## Imports"
   ]
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       "'3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0]'"
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   "source": [
    "\n",
    "import urllib.request, json\n",
    "import sys\n",
    "from datetime import datetime, timedelta\n",
    "import numpy as np  # linear algebra\n",
    "import pandas as pd  # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "import matplotlib.pyplot as plt  # Matplotlib to data visualization\n",
    "import seaborn as sns  # Seaborn to data visualization\n",
    "\n",
    "sys.version"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c14b37e0",
   "metadata": {},
   "source": [
    "## Configs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "56010349",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Constants with types of currency in Argentina\n",
    "OFFCIAL = 'oficial'\n",
    "BLUE = 'informal'\n",
    "\n",
    "# Date format to build API request\n",
    "date_format = '%Y-%m-%d'\n",
    "\n",
    "# Returns initial and end date for request API\n",
    "def get_dates(_range = 60):\n",
    "    end_date = datetime.today() - timedelta(days=1) # D-1\n",
    "    initial_date = end_date - timedelta(days=_range) # (D-1) - _range\n",
    "    return initial_date.strftime(date_format), end_date.strftime(date_format)\n",
    "\n",
    "# Returns json with currency data\n",
    "def get_data(_url):\n",
    "    with urllib.request.urlopen(_url) as url:\n",
    "        result = json.loads(url.read())\n",
    "    \n",
    "    return result\n",
    "\n",
    "# Clean data from API result and returns an Pandas DataFrame \n",
    "def get_dataframe(_currency_list):\n",
    "    df = pd.DataFrame(data=_currency_list[1:], columns=['date', 'buy', 'sell']).set_index('date')\n",
    "\n",
    "    df.index = pd.to_datetime(df.index, dayfirst=True)\n",
    "    df.buy = df.buy.str.replace(',', '.').astype(float)\n",
    "    df.sell = df.sell.str.replace(',', '.').astype(float)\n",
    "    return df \n"
   ]
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   "source": [
    "# Setting initial and end dates\n",
    "initial_date, end_date = get_dates()\n",
    "\n",
    "# Settings API urls\n",
    "af_blue_url = \"https://mercados.ambito.com/dolar/informal/historico-general/{}/{}\".format(initial_date, end_date)\n",
    "af_official_url = \"https://mercados.ambito.com//dolar/oficial/historico-general/{}/{}\".format(initial_date, end_date)\n",
    "\n",
    "# Getting data from API\n",
    "list_blue, list_official = get_data(af_blue_url), get_data(af_official_url)\n",
    "\n",
    "# Getting DataFrames from API data\n",
    "df_official = get_dataframe(list_official)\n",
    "df_blue = get_dataframe(list_blue)\n",
    "\n",
    "# Merge those datasets\n",
    "exchange_rates = df_blue.merge(df_official, how='inner', left_index=True, right_index=True, suffixes=('_blue', '_oficial'))"
   ]
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>buy_blue</th>\n",
       "      <th>sell_blue</th>\n",
       "      <th>buy_oficial</th>\n",
       "      <th>sell_oficial</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-07-19</th>\n",
       "      <td>520.0</td>\n",
       "      <td>525.0</td>\n",
       "      <td>271.35</td>\n",
       "      <td>281.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-07-20</th>\n",
       "      <td>520.0</td>\n",
       "      <td>525.0</td>\n",
       "      <td>271.66</td>\n",
       "      <td>281.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-07-21</th>\n",
       "      <td>524.0</td>\n",
       "      <td>529.0</td>\n",
       "      <td>272.54</td>\n",
       "      <td>282.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-07-24</th>\n",
       "      <td>547.0</td>\n",
       "      <td>552.0</td>\n",
       "      <td>274.37</td>\n",
       "      <td>284.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-07-25</th>\n",
       "      <td>531.0</td>\n",
       "      <td>536.0</td>\n",
       "      <td>274.65</td>\n",
       "      <td>284.65</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "            buy_blue  sell_blue  buy_oficial  sell_oficial\n",
       "date                                                      \n",
       "2023-07-19     520.0      525.0       271.35        281.35\n",
       "2023-07-20     520.0      525.0       271.66        281.66\n",
       "2023-07-21     524.0      529.0       272.54        282.54\n",
       "2023-07-24     547.0      552.0       274.37        284.37\n",
       "2023-07-25     531.0      536.0       274.65        284.65"
      ]
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     "execution_count": 4,
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   "source": [
    "exchange_rates.head()"
   ]
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   "source": [
    "## Analyze data (Currency)"
   ]
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   "source": [
    "### Calculate the mean between buy and sell for both exchange rates. "
   ]
  },
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   "id": "990b9e5b",
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   "source": [
    "exchange_rates = exchange_rates.assign(mean_blue = lambda x : (x['buy_blue'] + x['sell_blue'])/2 ).copy()\n",
    "exchange_rates = exchange_rates.assign(mean_oficial = lambda x : (x['buy_oficial'] + x['sell_oficial'])/2 ).copy()"
   ]
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>buy_blue</th>\n",
       "      <th>sell_blue</th>\n",
       "      <th>buy_oficial</th>\n",
       "      <th>sell_oficial</th>\n",
       "      <th>mean_blue</th>\n",
       "      <th>mean_oficial</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-07-19</th>\n",
       "      <td>520.0</td>\n",
       "      <td>525.0</td>\n",
       "      <td>271.35</td>\n",
       "      <td>281.35</td>\n",
       "      <td>522.5</td>\n",
       "      <td>276.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-07-20</th>\n",
       "      <td>520.0</td>\n",
       "      <td>525.0</td>\n",
       "      <td>271.66</td>\n",
       "      <td>281.66</td>\n",
       "      <td>522.5</td>\n",
       "      <td>276.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-07-21</th>\n",
       "      <td>524.0</td>\n",
       "      <td>529.0</td>\n",
       "      <td>272.54</td>\n",
       "      <td>282.54</td>\n",
       "      <td>526.5</td>\n",
       "      <td>277.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-07-24</th>\n",
       "      <td>547.0</td>\n",
       "      <td>552.0</td>\n",
       "      <td>274.37</td>\n",
       "      <td>284.37</td>\n",
       "      <td>549.5</td>\n",
       "      <td>279.37</td>\n",
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       "    <tr>\n",
       "      <th>2023-07-25</th>\n",
       "      <td>531.0</td>\n",
       "      <td>536.0</td>\n",
       "      <td>274.65</td>\n",
       "      <td>284.65</td>\n",
       "      <td>533.5</td>\n",
       "      <td>279.65</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "            buy_blue  sell_blue  buy_oficial  sell_oficial  mean_blue  \\\n",
       "date                                                                    \n",
       "2023-07-19     520.0      525.0       271.35        281.35      522.5   \n",
       "2023-07-20     520.0      525.0       271.66        281.66      522.5   \n",
       "2023-07-21     524.0      529.0       272.54        282.54      526.5   \n",
       "2023-07-24     547.0      552.0       274.37        284.37      549.5   \n",
       "2023-07-25     531.0      536.0       274.65        284.65      533.5   \n",
       "\n",
       "            mean_oficial  \n",
       "date                      \n",
       "2023-07-19        276.35  \n",
       "2023-07-20        276.66  \n",
       "2023-07-21        277.54  \n",
       "2023-07-24        279.37  \n",
       "2023-07-25        279.65  "
      ]
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   "source": [
    "\n",
    "exchange_rates.head()\n"
   ]
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   "source": [
    "### Analyze the correlation along time for these exchange rates. "
   ]
  },
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      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"darkgrid\")\n",
    "plt.figure(figsize=(12,10))\n",
    "plt.title(\"Correlation of average prices of the official and 'blue' dollar quotation in Argentina, between {} and {}\".format(initial_date, end_date))\n",
    "sns.scatterplot(data=exchange_rates[['mean_oficial', 'mean_blue']], x='mean_blue', y='mean_oficial')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e28eb351",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-20T18:01:05.309007Z",
     "iopub.status.busy": "2023-03-20T18:01:05.308621Z",
     "iopub.status.idle": "2023-03-20T18:01:05.320138Z",
     "shell.execute_reply": "2023-03-20T18:01:05.319280Z"
    },
    "papermill": {
     "duration": 0.018706,
     "end_time": "2023-03-20T18:01:05.322013",
     "exception": false,
     "start_time": "2023-03-20T18:01:05.303307",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean_oficial</th>\n",
       "      <th>mean_blue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mean_oficial</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.980991</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              mean_oficial  mean_blue\n",
       "mean_oficial           1.0   0.980991"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(exchange_rates[['mean_oficial', 'mean_blue']].corr()[0:1])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "5d80fa53",
   "metadata": {},
   "source": [
    "### Evolution of the official and 'blue' exchange rates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f9d3717c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "exchange_rates[['mean_oficial', 'mean_blue']].plot(kind='line', \\\n",
    "    title=\"Evolution of the official and 'blue' exchange rates\", figsize=(12,10))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "83baf1f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "exchange_rates[['mean_oficial', 'mean_blue']].pct_change().plot(kind='line', \\\n",
    "    title=\"Evolution of the official and 'blue' exchange rates (PCT)\", figsize=(12,10))\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "8827401f",
   "metadata": {},
   "source": [
    "### Analyzing evolution of currencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b9551c85",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>diff</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>type</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Official</th>\n",
       "      <td>276.35</td>\n",
       "      <td>357.0</td>\n",
       "      <td>29.184006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Unofficial</th>\n",
       "      <td>522.50</td>\n",
       "      <td>725.0</td>\n",
       "      <td>38.755981</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             start    end       diff\n",
       "type                                \n",
       "Official    276.35  357.0  29.184006\n",
       "Unofficial  522.50  725.0  38.755981"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "start = exchange_rates[exchange_rates.index == exchange_rates.index.min()]\\\n",
    "    [['mean_blue', 'mean_oficial']]\n",
    "end = exchange_rates[exchange_rates.index == exchange_rates.index.max()]\\\n",
    "    [['mean_blue', 'mean_oficial']]\n",
    "\n",
    "res = [['Official', start['mean_oficial'].values[0], end['mean_oficial'].values[0], \\\n",
    "        (end['mean_oficial'].values[0]/start['mean_oficial'].values[0]-1)*100],\n",
    "       ['Unofficial', start['mean_blue'].values[0], end['mean_blue'].values[0], \\\n",
    "        (end['mean_blue'].values[0]/start['mean_blue'].values[0]-1)*100]]\n",
    "\n",
    "pd.DataFrame(res, columns=['type', 'start', 'end', 'diff']).set_index('type')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3731d845",
   "metadata": {},
   "source": [
    "### Calculate and plot growth PCT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c8cb8999",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "diff_official = (exchange_rates['mean_oficial'].max() / exchange_rates['mean_oficial'].min() - 1) * 100\n",
    "diff_blue = (exchange_rates['mean_blue'].max() / exchange_rates['mean_blue'].min() - 1) * 100\n",
    "\n",
    "# Show plot\n",
    "plt.figure(figsize=(10,10))\n",
    "\n",
    "currencies = {\"currencies\": [\"Official\", \"Unofficial\"], \"values\": [diff_official, diff_blue]}\n",
    "ax = sns.barplot(x='currencies', y='values', data=currencies)\n",
    "\n",
    "ax.bar_label(ax.containers[0])\n",
    "plt.xlabel('Exchange Rate Type')\n",
    "plt.ylabel('Growth (%)')\n",
    "plt.title(\"Evolution of exchange rates by type of exchange\")\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "7265190a",
   "metadata": {},
   "source": [
    "## Analyze Data (interest rates)\n",
    "[Source](https://datos.gob.ar/dataset/sspm-principales-tasas-interes/archivo/sspm_89.2)\n",
    "\n",
    "The interest rates (PM - Monetary Policies) have positive correlation with Oficial Exchange Rates "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "863b3d2d",
   "metadata": {},
   "source": [
    "### (Down)load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e5534e94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Shape: (7547, 3)'"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "\"Fields: Index(['tasas_interes_call', 'tasas_interes_badlar', 'tasas_interes_pm'], dtype='object')\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tasas_interes_call</th>\n",
       "      <th>tasas_interes_badlar</th>\n",
       "      <th>tasas_interes_pm</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>indice_tiempo</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-08-27</th>\n",
       "      <td>103.50</td>\n",
       "      <td>113.0625</td>\n",
       "      <td>118.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-28</th>\n",
       "      <td>100.73</td>\n",
       "      <td>114.0625</td>\n",
       "      <td>118.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-29</th>\n",
       "      <td>99.81</td>\n",
       "      <td>112.5000</td>\n",
       "      <td>118.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-30</th>\n",
       "      <td>99.07</td>\n",
       "      <td>113.5625</td>\n",
       "      <td>118.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-31</th>\n",
       "      <td>110.19</td>\n",
       "      <td>113.4375</td>\n",
       "      <td>118.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               tasas_interes_call  tasas_interes_badlar  tasas_interes_pm\n",
       "indice_tiempo                                                            \n",
       "2023-08-27                 103.50              113.0625             118.0\n",
       "2023-08-28                 100.73              114.0625             118.0\n",
       "2023-08-29                  99.81              112.5000             118.0\n",
       "2023-08-30                  99.07              113.5625             118.0\n",
       "2023-08-31                 110.19              113.4375             118.0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daily_interest_rates = 'https://infra.datos.gob.ar/catalog/sspm/dataset/89/distribution/89.2/download/principales-tasas-interes-diarias.csv'\n",
    "inter = pd.read_csv(daily_interest_rates, parse_dates=['indice_tiempo'], index_col=['indice_tiempo'])\n",
    "\n",
    "display(\"Shape: \" + str(inter.shape))\n",
    "display(\"Fields: \" + str(inter.columns))\n",
    "\n",
    "inter.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a115cf8f",
   "metadata": {},
   "source": [
    "### Merging, renaming, and filtering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ac6e4cdb",
   "metadata": {},
   "outputs": [],
   "source": [
    "_all = inter.merge(exchange_rates, how='inner', left_index=True, right_index=True)\n",
    "_all.rename(columns={'tasas_interes_call': 'ti_call', 'tasas_interes_badlar': 'ti_badlar', 'tasas_interes_pm': 'ti_pm'}, inplace=True)\n",
    "\n",
    "# Excluding 'ti_pm because have't data change\n",
    "ftr = ['ti_badlar', 'ti_call', 'mean_oficial', 'mean_blue']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "323a9b0c",
   "metadata": {},
   "source": [
    "### Plot correlation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7b940e4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ti_badlar</th>\n",
       "      <th>ti_call</th>\n",
       "      <th>mean_oficial</th>\n",
       "      <th>mean_blue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ti_badlar</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.902488</td>\n",
       "      <td>0.950989</td>\n",
       "      <td>0.944211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ti_call</th>\n",
       "      <td>0.902488</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.957189</td>\n",
       "      <td>0.928418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean_oficial</th>\n",
       "      <td>0.950989</td>\n",
       "      <td>0.957189</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.974354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean_blue</th>\n",
       "      <td>0.944211</td>\n",
       "      <td>0.928418</td>\n",
       "      <td>0.974354</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              ti_badlar   ti_call  mean_oficial  mean_blue\n",
       "ti_badlar      1.000000  0.902488      0.950989   0.944211\n",
       "ti_call        0.902488  1.000000      0.957189   0.928418\n",
       "mean_oficial   0.950989  0.957189      1.000000   0.974354\n",
       "mean_blue      0.944211  0.928418      0.974354   1.000000"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "interest_rates_currency_correlation = _all[ftr].corr()\n",
    "\n",
    "# Printing heatmap with data above\n",
    "plt.figure(figsize=(10,10))\n",
    "sns.heatmap(interest_rates_currency_correlation, cmap='YlGnBu')\n",
    "plt.title('Correlation between rates and currencies')\n",
    "plt.show()\n",
    "\n",
    "display(interest_rates_currency_correlation)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 11.365254,
   "end_time": "2023-03-20T18:01:06.048333",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2023-03-20T18:00:54.683079",
   "version": "2.4.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}