EVDS - Central Bank of Turkey.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0453305d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\user\\anaconda3\\lib\\site-packages\\evds\\__init__.py:42: FutureWarning: Could not cast to int32, falling back to object. This behavior is deprecated. In a future version, when a dtype is passed to 'DataFrame', either all columns will be cast to that dtype, or a TypeError will be raised.\n",
      "  main_categories_df = pd.DataFrame(main_categories_raw, dtype=\"int\")[[\"CATEGORY_ID\",\"TOPIC_TITLE_\" + self.lang]]\n"
     ]
    },
    {
     "data": {
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CATEGORY_ID</th>\n",
       "      <th>TOPIC_TITLE_TR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>PİYASA VERİLERİ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>KURLAR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>FAİZ İSTATİSTİKLERİ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>PARA VE BANKA İSTATİSTİKLERİ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>MENKUL KIYMET İSTATİSTİKLERİ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>12</td>\n",
       "      <td>FİNANSAL İSTATİSTİKLER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>13</td>\n",
       "      <td>TCMB BİLANÇO VERİLERİ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>14</td>\n",
       "      <td>FİYAT ENDEKSLERİ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>15</td>\n",
       "      <td>ANKETLER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>18</td>\n",
       "      <td>ÖDEMELER DENGESİ, ULUSLARARASI YATIRIM POZİSYONU</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>19</td>\n",
       "      <td>DIŞ TİCARET İSTATİSTİKLERİ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>20</td>\n",
       "      <td>KAMU MALİYESİ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>21</td>\n",
       "      <td>ÜRETİM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>22</td>\n",
       "      <td>ÖDEME SİSTEMLERİ VE EMİSYON</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>23</td>\n",
       "      <td>İSTİHDAM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>6</td>\n",
       "      <td>DIŞ BORÇLAR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>7</td>\n",
       "      <td>ZORUNLU KARŞILIĞA TABİ MEVDUAT VE KATILIM FONLARI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>24</td>\n",
       "      <td>BIS KARŞILAŞTIRMALI ÜLKE İSTATİSTİKLERİ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>25</td>\n",
       "      <td>ALTIN VERİLERİ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>26</td>\n",
       "      <td>KONUT VE İNŞAAT İSTATİSTİKLERİ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>27</td>\n",
       "      <td>FİNANSAL HESAPLAR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>28</td>\n",
       "      <td>TURİZM İSTATİSTİKLERİ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>95</td>\n",
       "      <td>EVDS KULLANIM İSTATİSTİKLERİ</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    CATEGORY_ID                                     TOPIC_TITLE_TR\n",
       "0             1                                    PİYASA VERİLERİ\n",
       "1             2                                             KURLAR\n",
       "2             3                                FAİZ İSTATİSTİKLERİ\n",
       "3             4                       PARA VE BANKA İSTATİSTİKLERİ\n",
       "4             5                       MENKUL KIYMET İSTATİSTİKLERİ\n",
       "5            12                             FİNANSAL İSTATİSTİKLER\n",
       "6            13                              TCMB BİLANÇO VERİLERİ\n",
       "7            14                                   FİYAT ENDEKSLERİ\n",
       "8            15                                           ANKETLER\n",
       "9            18   ÖDEMELER DENGESİ, ULUSLARARASI YATIRIM POZİSYONU\n",
       "10           19                         DIŞ TİCARET İSTATİSTİKLERİ\n",
       "11           20                                      KAMU MALİYESİ\n",
       "12           21                                             ÜRETİM\n",
       "13           22                        ÖDEME SİSTEMLERİ VE EMİSYON\n",
       "14           23                                           İSTİHDAM\n",
       "15            6                                        DIŞ BORÇLAR\n",
       "16            7  ZORUNLU KARŞILIĞA TABİ MEVDUAT VE KATILIM FONLARI\n",
       "17           24            BIS KARŞILAŞTIRMALI ÜLKE İSTATİSTİKLERİ\n",
       "18           25                                     ALTIN VERİLERİ\n",
       "19           26                     KONUT VE İNŞAAT İSTATİSTİKLERİ\n",
       "20           27                                  FİNANSAL HESAPLAR\n",
       "21           28                              TURİZM İSTATİSTİKLERİ\n",
       "22           95                       EVDS KULLANIM İSTATİSTİKLERİ"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from evds import evdsAPI\n",
    "evds= evdsAPI('YourAPIKey')\n",
    "evds.main_categories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "69666012",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CATEGORY_ID</th>\n",
       "      <th>DATAGROUP_CODE</th>\n",
       "      <th>DATAGROUP_NAME</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13</td>\n",
       "      <td>bie_abanlbil</td>\n",
       "      <td>Merkez Bankası Analitik Bilanço(Bin TL)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13</td>\n",
       "      <td>bie_mbblnch</td>\n",
       "      <td>Merkez Bankası Haftalık Vaziyeti (Yeni)(Bin TL)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13</td>\n",
       "      <td>bie_mbblnca</td>\n",
       "      <td>Merkez Bankası Bilançosu (Yeni)(Bin TL)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>13</td>\n",
       "      <td>bie_abstc2</td>\n",
       "      <td>Merkez Bankası Bilançosu-Stand By-18.01.2002 T...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13</td>\n",
       "      <td>bie_abres2</td>\n",
       "      <td>Merkez Bankası Rezervleri (Milyon ABD Doları)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>13</td>\n",
       "      <td>bie_rkdrk</td>\n",
       "      <td>Reeskont Kredilerinin Döviz Rezervlerine Katki...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   CATEGORY_ID DATAGROUP_CODE  \\\n",
       "0           13   bie_abanlbil   \n",
       "1           13    bie_mbblnch   \n",
       "2           13    bie_mbblnca   \n",
       "3           13     bie_abstc2   \n",
       "4           13     bie_abres2   \n",
       "5           13      bie_rkdrk   \n",
       "\n",
       "                                      DATAGROUP_NAME  \n",
       "0            Merkez Bankası Analitik Bilanço(Bin TL)  \n",
       "1    Merkez Bankası Haftalık Vaziyeti (Yeni)(Bin TL)  \n",
       "2            Merkez Bankası Bilançosu (Yeni)(Bin TL)  \n",
       "3  Merkez Bankası Bilançosu-Stand By-18.01.2002 T...  \n",
       "4      Merkez Bankası Rezervleri (Milyon ABD Doları)  \n",
       "5  Reeskont Kredilerinin Döviz Rezervlerine Katki...  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "evds.get_sub_categories(13)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "29a63e78",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SERIE_CODE</th>\n",
       "      <th>SERIE_NAME</th>\n",
       "      <th>START_DATE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>TP.AB.A01</td>\n",
       "      <td>A.AKTİF(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TP.AB.A02</td>\n",
       "      <td>A.1-DIŞ VARLIKLAR(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TP.AB.A03</td>\n",
       "      <td>A.2-İÇ VARLIKLAR(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>TP.AB.A04</td>\n",
       "      <td>A.2A-Nakit İşlemler(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TP.AB.A05</td>\n",
       "      <td>A.2Aa-Hazine Borçları(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>TP.AB.A051</td>\n",
       "      <td>A.2Aa1-Menkul Kıymetler(Bin TL)</td>\n",
       "      <td>24-11-2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>TP.AB.A052</td>\n",
       "      <td>A.2Aa1a-5 Kasım 2001 Öncesi DİBS(Bin TL)</td>\n",
       "      <td>24-11-2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>TP.AB.A053</td>\n",
       "      <td>A.2Aa1b-İkincil Piyasadan Alınan DİBS(Bin TL)</td>\n",
       "      <td>24-11-2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>TP.AB.A054</td>\n",
       "      <td>A.2Aa2-Diğer(Bin TL)</td>\n",
       "      <td>24-11-2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>TP.AB.A06</td>\n",
       "      <td>A.2Ab-Bankacılık Sektörüne Açılan Nakit Kredil...</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>TP.AB.A061</td>\n",
       "      <td>A.2Ac-TMSF'ye Kullandırılan Krediler(Bin TL)</td>\n",
       "      <td>24-11-2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>TP.AB.A07</td>\n",
       "      <td>A.2Ad-Diğer Kalemler(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>TP.AB.A08</td>\n",
       "      <td>A.3-DEĞERLEME HESABI(BİN TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>TP.AB.A081</td>\n",
       "      <td>A.2B-IMF Acil Yardım Takip Hesabı(Hazine)(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>TP.AB.A09</td>\n",
       "      <td>P.PASİF(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>TP.AB.A10</td>\n",
       "      <td>P.1-TOPLAM DÖVİZ YÜKÜMLÜLÜKLERİ(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>TP.AB.A11</td>\n",
       "      <td>P.1a-Dış Yükümlülükler(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>TP.AB.A12</td>\n",
       "      <td>P.1b-İç Yükümlülükler(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>TP.AB.A13</td>\n",
       "      <td>P.1ba-Kamu ve Diğer Döviz Mevduatı(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>TP.AB.A14</td>\n",
       "      <td>P.1bb-Bankalar Döviz Mevduatı(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>TP.AB.A15</td>\n",
       "      <td>P.2-MERKEZ BANKASI PARASI(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>TP.AB.A16</td>\n",
       "      <td>P.2A-Rezerv Para(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>TP.AB.A17</td>\n",
       "      <td>P.2Aa-Emisyon(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>TP.AB.A18</td>\n",
       "      <td>P.2Ab-Bankalar Mevduatı(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>TP.AB.A19</td>\n",
       "      <td>P.2Aba-Zorunlu Karşılıklar Bloke Hesabı(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>TP.AB.A20</td>\n",
       "      <td>P.2Abb-Serbest Mevduat(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>TP.AB.A21</td>\n",
       "      <td>P.2Ac-Fon hesapları(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>TP.AB.A22</td>\n",
       "      <td>P.2Ad-Banka Dışı Kesim Mevduatı(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>TP.AB.A23</td>\n",
       "      <td>P.2B-Diğer Merkez Bankası Parası(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>TP.AB.A24</td>\n",
       "      <td>P.2Ba-Açık Piyasa İşlemleri(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>TP.AB.A25</td>\n",
       "      <td>P.2Bb-Kamu Mevduatı(Bin TL)</td>\n",
       "      <td>26-12-1980</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    SERIE_CODE                                         SERIE_NAME  START_DATE\n",
       "0    TP.AB.A01                                    A.AKTİF(Bin TL)  26-12-1980\n",
       "1    TP.AB.A02                          A.1-DIŞ VARLIKLAR(Bin TL)  26-12-1980\n",
       "2    TP.AB.A03                           A.2-İÇ VARLIKLAR(Bin TL)  26-12-1980\n",
       "3    TP.AB.A04                        A.2A-Nakit İşlemler(Bin TL)  26-12-1980\n",
       "4    TP.AB.A05                      A.2Aa-Hazine Borçları(Bin TL)  26-12-1980\n",
       "5   TP.AB.A051                    A.2Aa1-Menkul Kıymetler(Bin TL)  24-11-2000\n",
       "6   TP.AB.A052           A.2Aa1a-5 Kasım 2001 Öncesi DİBS(Bin TL)  24-11-2000\n",
       "7   TP.AB.A053      A.2Aa1b-İkincil Piyasadan Alınan DİBS(Bin TL)  24-11-2000\n",
       "8   TP.AB.A054                               A.2Aa2-Diğer(Bin TL)  24-11-2000\n",
       "9    TP.AB.A06  A.2Ab-Bankacılık Sektörüne Açılan Nakit Kredil...  26-12-1980\n",
       "10  TP.AB.A061       A.2Ac-TMSF'ye Kullandırılan Krediler(Bin TL)  24-11-2000\n",
       "11   TP.AB.A07                       A.2Ad-Diğer Kalemler(Bin TL)  26-12-1980\n",
       "12   TP.AB.A08                       A.3-DEĞERLEME HESABI(BİN TL)  26-12-1980\n",
       "13  TP.AB.A081  A.2B-IMF Acil Yardım Takip Hesabı(Hazine)(Bin TL)  26-12-1980\n",
       "14   TP.AB.A09                                    P.PASİF(Bin TL)  26-12-1980\n",
       "15   TP.AB.A10            P.1-TOPLAM DÖVİZ YÜKÜMLÜLÜKLERİ(Bin TL)  26-12-1980\n",
       "16   TP.AB.A11                     P.1a-Dış Yükümlülükler(Bin TL)  26-12-1980\n",
       "17   TP.AB.A12                      P.1b-İç Yükümlülükler(Bin TL)  26-12-1980\n",
       "18   TP.AB.A13         P.1ba-Kamu ve Diğer Döviz Mevduatı(Bin TL)  26-12-1980\n",
       "19   TP.AB.A14              P.1bb-Bankalar Döviz Mevduatı(Bin TL)  26-12-1980\n",
       "20   TP.AB.A15                  P.2-MERKEZ BANKASI PARASI(Bin TL)  26-12-1980\n",
       "21   TP.AB.A16                           P.2A-Rezerv Para(Bin TL)  26-12-1980\n",
       "22   TP.AB.A17                              P.2Aa-Emisyon(Bin TL)  26-12-1980\n",
       "23   TP.AB.A18                    P.2Ab-Bankalar Mevduatı(Bin TL)  26-12-1980\n",
       "24   TP.AB.A19    P.2Aba-Zorunlu Karşılıklar Bloke Hesabı(Bin TL)  26-12-1980\n",
       "25   TP.AB.A20                     P.2Abb-Serbest Mevduat(Bin TL)  26-12-1980\n",
       "26   TP.AB.A21                        P.2Ac-Fon hesapları(Bin TL)  26-12-1980\n",
       "27   TP.AB.A22            P.2Ad-Banka Dışı Kesim Mevduatı(Bin TL)  26-12-1980\n",
       "28   TP.AB.A23           P.2B-Diğer Merkez Bankası Parası(Bin TL)  26-12-1980\n",
       "29   TP.AB.A24                P.2Ba-Açık Piyasa İşlemleri(Bin TL)  26-12-1980\n",
       "30   TP.AB.A25                        P.2Bb-Kamu Mevduatı(Bin TL)  26-12-1980"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "evds.get_series('bie_abanlbil')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fb1e71af",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\user\\anaconda3\\lib\\site-packages\\evds\\__init__.py:180: FutureWarning: Could not cast to float64, falling back to object. This behavior is deprecated. In a future version, when a dtype is passed to 'DataFrame', either all columns will be cast to that dtype, or a TypeError will be raised.\n",
      "  df = pd.DataFrame(data, dtype=\"float\")\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "#fxab = USD/TRY rate and analytical balance sheet data frame\n",
    "\n",
    "# TP_AB_A02 = Foreign Assets\n",
    "# TP.DK.USD.A.YTL = USD/TRY Rate\n",
    "\n",
    "#Load data and format the date column\n",
    "\n",
    "fxab = evds.get_data(['TP.DK.USD.A.YTL','TP.AB.A02'], startdate=\"01-10-2019\", enddate=\"20-01-2023\")\n",
    "fxab['Tarih'] = pd.to_datetime(fxab['Tarih'], dayfirst=True)\n",
    "fxab['TP_AB_A02'] = fxab['TP_AB_A02'].ffill()\n",
    "fxab['TP_DK_USD_A_YTL'] = fxab['TP_DK_USD_A_YTL'].ffill()\n",
    "\n",
    "# Calculate the y-axis data\n",
    "y = ((fxab[\"TP_AB_A02\"]/fxab[\"TP_DK_USD_A_YTL\"])/1000000)\n",
    "\n",
    "# Create the plot\n",
    "sns.lineplot(x=\"Tarih\", y=y, data=fxab)\n",
    "\n",
    "# Customize the plot\n",
    "sns.set_style(\"whitegrid\")\n",
    "sns.set_context(\"notebook\", font_scale=1.5)\n",
    "\n",
    "# Rotate x-axis labels for readability\n",
    "plt.xticks(rotation=45, ha='right')\n",
    "\n",
    "# Add a title and labels\n",
    "plt.title(\"Foreign Assets by USD\", fontsize=20)\n",
    "plt.xlabel(\"Date\", fontsize=15)\n",
    "plt.ylabel(\"Billion USD\", fontsize=15)\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1712275a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}