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    "# The Euro on Forex\n",
    "## Exploring Twenty Years of Volatility\n",
    "### History\n",
    "The currency exchange market has been around since coins were first used. At the end of the 1800s the development of the gold standard fixed currency values to a certain amount of gold, allowing for an internationally stable monetary system (1). Eventually the amount of gold was not enough to keep up with the demand for currency. After World War II the Bretton Woods Accord set the US Dollar as the global fixed currency. This was an adjustable rate, but still determined by central banks and state actors (2). The US dollar was pegged to gold at the time, but during the 1970s the same problem (i.e. amount of gold vs currency in circulation) occurred with the dollar. In August of 1971 President Richard Nixon unilaterally canceled direct international convertability of the US dollar to gold, inadvertently beginning a regime of free-floating currencies (3).\n",
    "\n",
    "### Today\n",
    "The modern foreign exchange market (Forex, FX, or currency market) is a direct broker to dealer global marketplace that determines the market value and exchange rate of currencies all over the world. It is open 24 hours a day, 5 days a week. Currencies are always traded in pairs, and the value expressed is of one currency relative to another. For example, at the end of the day on 11/19/21 the Euro to US dollar rate was 1.13, or $1.13 equals €1. All of the twenty most traded currencies are free-floating, their value is determined by political conditions, economic factors and market psychology.\n",
    "\n",
    "Forex is by far the largest financial market in the world, in 2019 having a daily volume of over $6.6 trillion (4). The Euro to US dollar (EURUSD) is the most traded currency pair, taking about 30% of the multi-billion dollar Forex turnover (5).\n",
    "\n",
    "### Methodology\n",
    "This study examines the volatility of the value of the Euro to eight other currencies. It uses the 2019 Triennial Central Bank Survey by the Bank for International Settlements to determine four currencies that represent large portions of the market and four currencies that represent small portions of the market. The highly traded currencies are the US dollar, Japanese yen, UK pound, and Australian dollar. The Israeli shekel, Phillipine peso, Malaysian ringgit, and Romanian leu comprise the group of least traded currencies.\n",
    "\n",
    "The data set used is based on daily closing values provided by the European Central Bank and compiled by Daria Chemkaeva. It is updated weekly, the version used for this study was downloaded from Kaggle in November 2021.\n",
    "\n",
    "### Summary\n",
    "Text with conclusion.\n",
    "<br><br>\n",
    "\n",
    "## Initial Look\n",
    "The first steps are to import the basic libraries, open the file, and take an initial look at the dataset.\n",
    "\n"
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       "      <th>[Philippine peso ]</th>\n",
       "      <th>[Polish zloty ]</th>\n",
       "      <th>[Romanian leu ]</th>\n",
       "      <th>[Russian rouble ]</th>\n",
       "      <th>[Swedish krona ]</th>\n",
       "      <th>[Singapore dollar ]</th>\n",
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       "      <th>[Slovak koruna ]</th>\n",
       "      <th>[Thai baht ]</th>\n",
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       "      <th>0</th>\n",
       "      <td>2021-01-08</td>\n",
       "      <td>1.5758</td>\n",
       "      <td>1.9558</td>\n",
       "      <td>6.5748</td>\n",
       "      <td>1.5543</td>\n",
       "      <td>1.0827</td>\n",
       "      <td>7.9184</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.163</td>\n",
       "      <td>7.4369</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.90128</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.4982</td>\n",
       "      <td>7.5690</td>\n",
       "      <td>359.62</td>\n",
       "      <td>17247.33</td>\n",
       "      <td>3.8981</td>\n",
       "      <td>89.7975</td>\n",
       "      <td>155.5000</td>\n",
       "      <td>127.26</td>\n",
       "      <td>1337.90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.4718</td>\n",
       "      <td>4.9359</td>\n",
       "      <td>10.2863</td>\n",
       "      <td>1.6883</td>\n",
       "      <td>58.947</td>\n",
       "      <td>4.5113</td>\n",
       "      <td>4.8708</td>\n",
       "      <td>90.8000</td>\n",
       "      <td>10.0510</td>\n",
       "      <td>1.6228</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.8480</td>\n",
       "      <td>9.0146</td>\n",
       "      <td>1.2250</td>\n",
       "      <td>18.7212</td>\n",
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       "      <th>1</th>\n",
       "      <td>2021-01-07</td>\n",
       "      <td>1.5836</td>\n",
       "      <td>1.9558</td>\n",
       "      <td>6.5172</td>\n",
       "      <td>1.5601</td>\n",
       "      <td>1.0833</td>\n",
       "      <td>7.9392</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.147</td>\n",
       "      <td>7.4392</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.90190</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.5176</td>\n",
       "      <td>7.5660</td>\n",
       "      <td>357.79</td>\n",
       "      <td>17259.99</td>\n",
       "      <td>3.9027</td>\n",
       "      <td>90.0455</td>\n",
       "      <td>155.3000</td>\n",
       "      <td>127.13</td>\n",
       "      <td>1342.29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.2552</td>\n",
       "      <td>4.9570</td>\n",
       "      <td>10.3435</td>\n",
       "      <td>1.6907</td>\n",
       "      <td>59.043</td>\n",
       "      <td>4.4998</td>\n",
       "      <td>4.8712</td>\n",
       "      <td>91.2000</td>\n",
       "      <td>10.0575</td>\n",
       "      <td>1.6253</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.8590</td>\n",
       "      <td>8.9987</td>\n",
       "      <td>1.2276</td>\n",
       "      <td>18.7919</td>\n",
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       "      <th>2</th>\n",
       "      <td>2021-01-06</td>\n",
       "      <td>1.5824</td>\n",
       "      <td>1.9558</td>\n",
       "      <td>6.5119</td>\n",
       "      <td>1.5640</td>\n",
       "      <td>1.0821</td>\n",
       "      <td>7.9653</td>\n",
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       "      <td>26.145</td>\n",
       "      <td>7.4393</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.90635</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.5659</td>\n",
       "      <td>7.5595</td>\n",
       "      <td>357.86</td>\n",
       "      <td>17168.20</td>\n",
       "      <td>3.9289</td>\n",
       "      <td>90.2040</td>\n",
       "      <td>156.3000</td>\n",
       "      <td>127.03</td>\n",
       "      <td>1339.30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.3543</td>\n",
       "      <td>4.9482</td>\n",
       "      <td>10.3810</td>\n",
       "      <td>1.6916</td>\n",
       "      <td>59.296</td>\n",
       "      <td>4.5160</td>\n",
       "      <td>4.8720</td>\n",
       "      <td>90.8175</td>\n",
       "      <td>10.0653</td>\n",
       "      <td>1.6246</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.9210</td>\n",
       "      <td>9.0554</td>\n",
       "      <td>1.2338</td>\n",
       "      <td>18.5123</td>\n",
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       "      <th>3</th>\n",
       "      <td>2021-01-05</td>\n",
       "      <td>1.5927</td>\n",
       "      <td>1.9558</td>\n",
       "      <td>6.5517</td>\n",
       "      <td>1.5651</td>\n",
       "      <td>1.0803</td>\n",
       "      <td>7.9315</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.227</td>\n",
       "      <td>7.4387</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.90333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.5136</td>\n",
       "      <td>7.5588</td>\n",
       "      <td>360.27</td>\n",
       "      <td>17075.10</td>\n",
       "      <td>3.9277</td>\n",
       "      <td>89.8670</td>\n",
       "      <td>156.1000</td>\n",
       "      <td>126.25</td>\n",
       "      <td>1335.85</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.5860</td>\n",
       "      <td>4.9293</td>\n",
       "      <td>10.4713</td>\n",
       "      <td>1.7036</td>\n",
       "      <td>59.020</td>\n",
       "      <td>4.5473</td>\n",
       "      <td>4.8721</td>\n",
       "      <td>91.6715</td>\n",
       "      <td>10.0570</td>\n",
       "      <td>1.6180</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.7760</td>\n",
       "      <td>9.0694</td>\n",
       "      <td>1.2271</td>\n",
       "      <td>18.4194</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-01-04</td>\n",
       "      <td>1.5928</td>\n",
       "      <td>1.9558</td>\n",
       "      <td>6.3241</td>\n",
       "      <td>1.5621</td>\n",
       "      <td>1.0811</td>\n",
       "      <td>7.9484</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.141</td>\n",
       "      <td>7.4379</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.90160</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.5330</td>\n",
       "      <td>7.5565</td>\n",
       "      <td>361.32</td>\n",
       "      <td>17062.67</td>\n",
       "      <td>3.9430</td>\n",
       "      <td>89.7890</td>\n",
       "      <td>156.1000</td>\n",
       "      <td>126.62</td>\n",
       "      <td>1332.03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.3031</td>\n",
       "      <td>4.9264</td>\n",
       "      <td>10.4440</td>\n",
       "      <td>1.7065</td>\n",
       "      <td>59.058</td>\n",
       "      <td>4.5475</td>\n",
       "      <td>4.8713</td>\n",
       "      <td>90.3420</td>\n",
       "      <td>10.0895</td>\n",
       "      <td>1.6198</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.7280</td>\n",
       "      <td>9.0579</td>\n",
       "      <td>1.2296</td>\n",
       "      <td>17.9214</td>\n",
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       "  Period\\Unit: [Australian dollar ] [Bulgarian lev ] [Brazilian real ] [Canadian dollar ] [Swiss franc ] [Chinese yuan renminbi ] [Cypriot pound ] [Czech koruna ] [Danish krone ] [Estonian kroon ] [UK pound sterling ] [Greek drachma ] [Hong Kong dollar ] [Croatian kuna ] [Hungarian forint ] [Indonesian rupiah ] [Israeli shekel ] [Indian rupee ]   [Iceland krona ]   [Japanese yen ] [Korean won ] [Lithuanian litas ] [Latvian lats ] [Maltese lira ] [Mexican peso ] [Malaysian ringgit ] [Norwegian krone ] [New Zealand dollar ] [Philippine peso ] [Polish zloty ]    [Romanian leu ]   [Russian rouble ] [Swedish krona ] [Singapore dollar ] [Slovenian tolar ] [Slovak koruna ] [Thai baht ]    [Turkish lira ]   [US dollar ] [South African rand ]\n",
       "0  2021-01-08         1.5758             1.9558            6.5748            1.5543           1.0827              7.9184                 NaN            26.163          7.4369             NaN              0.90128              NaN              9.4982            7.5690             359.62             17247.33             3.8981           89.7975                155.5000      127.26         1337.90            NaN               NaN             NaN           24.4718           4.9359              10.2863              1.6883              58.947            4.5113                   4.8708       90.8000          10.0510            1.6228               NaN               NaN          36.8480                 9.0146    1.2250            18.7212      \n",
       "1  2021-01-07         1.5836             1.9558            6.5172            1.5601           1.0833              7.9392                 NaN            26.147          7.4392             NaN              0.90190              NaN              9.5176            7.5660             357.79             17259.99             3.9027           90.0455                155.3000      127.13         1342.29            NaN               NaN             NaN           24.2552           4.9570              10.3435              1.6907              59.043            4.4998                   4.8712       91.2000          10.0575            1.6253               NaN               NaN          36.8590                 8.9987    1.2276            18.7919      \n",
       "2  2021-01-06         1.5824             1.9558            6.5119            1.5640           1.0821              7.9653                 NaN            26.145          7.4393             NaN              0.90635              NaN              9.5659            7.5595             357.86             17168.20             3.9289           90.2040                156.3000      127.03         1339.30            NaN               NaN             NaN           24.3543           4.9482              10.3810              1.6916              59.296            4.5160                   4.8720       90.8175          10.0653            1.6246               NaN               NaN          36.9210                 9.0554    1.2338            18.5123      \n",
       "3  2021-01-05         1.5927             1.9558            6.5517            1.5651           1.0803              7.9315                 NaN            26.227          7.4387             NaN              0.90333              NaN              9.5136            7.5588             360.27             17075.10             3.9277           89.8670                156.1000      126.25         1335.85            NaN               NaN             NaN           24.5860           4.9293              10.4713              1.7036              59.020            4.5473                   4.8721       91.6715          10.0570            1.6180               NaN               NaN          36.7760                 9.0694    1.2271            18.4194      \n",
       "4  2021-01-04         1.5928             1.9558            6.3241            1.5621           1.0811              7.9484                 NaN            26.141          7.4379             NaN              0.90160              NaN              9.5330            7.5565             361.32             17062.67             3.9430           89.7890                156.1000      126.62         1332.03            NaN               NaN             NaN           24.3031           4.9264              10.4440              1.7065              59.058            4.5475                   4.8713       90.3420          10.0895            1.6198               NaN               NaN          36.7280                 9.0579    1.2296            17.9214      "
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       "      <td>1.7643</td>\n",
       "      <td>1.6138</td>\n",
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       "      <td>80.9900</td>\n",
       "      <td>130.09</td>\n",
       "      <td>1366.73</td>\n",
       "      <td>4.66430</td>\n",
       "      <td>0.6654</td>\n",
       "      <td>0.4419</td>\n",
       "      <td>11.4414</td>\n",
       "      <td>4.4295</td>\n",
       "      <td>8.5900</td>\n",
       "      <td>2.1557</td>\n",
       "      <td>44.295</td>\n",
       "      <td>4.0363</td>\n",
       "      <td>1.3143</td>\n",
       "      <td>27.2075</td>\n",
       "      <td>9.1650</td>\n",
       "      <td>1.9537</td>\n",
       "      <td>188.8400</td>\n",
       "      <td>42.560</td>\n",
       "      <td>42.5590</td>\n",
       "      <td>0.3718</td>\n",
       "      <td>1.1659</td>\n",
       "      <td>6.7855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5695</th>\n",
       "      <td>1999-01-07</td>\n",
       "      <td>1.8474</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.7602</td>\n",
       "      <td>1.6165</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.58187</td>\n",
       "      <td>34.886</td>\n",
       "      <td>7.4431</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.70585</td>\n",
       "      <td>324.40</td>\n",
       "      <td>9.0131</td>\n",
       "      <td>NaN</td>\n",
       "      <td>250.09</td>\n",
       "      <td>9218.77</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81.0600</td>\n",
       "      <td>129.43</td>\n",
       "      <td>1337.16</td>\n",
       "      <td>4.65480</td>\n",
       "      <td>0.6627</td>\n",
       "      <td>0.4413</td>\n",
       "      <td>11.5511</td>\n",
       "      <td>4.4203</td>\n",
       "      <td>8.6295</td>\n",
       "      <td>2.1531</td>\n",
       "      <td>44.436</td>\n",
       "      <td>4.0165</td>\n",
       "      <td>1.3092</td>\n",
       "      <td>26.9876</td>\n",
       "      <td>9.1800</td>\n",
       "      <td>1.9436</td>\n",
       "      <td>188.8000</td>\n",
       "      <td>42.765</td>\n",
       "      <td>42.1678</td>\n",
       "      <td>0.3701</td>\n",
       "      <td>1.1632</td>\n",
       "      <td>6.8283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5696</th>\n",
       "      <td>1999-01-06</td>\n",
       "      <td>1.8820</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.7711</td>\n",
       "      <td>1.6116</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.58200</td>\n",
       "      <td>34.850</td>\n",
       "      <td>7.4452</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.70760</td>\n",
       "      <td>324.72</td>\n",
       "      <td>9.1010</td>\n",
       "      <td>NaN</td>\n",
       "      <td>250.67</td>\n",
       "      <td>9337.68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81.5400</td>\n",
       "      <td>131.42</td>\n",
       "      <td>1359.54</td>\n",
       "      <td>4.69940</td>\n",
       "      <td>0.6649</td>\n",
       "      <td>0.4420</td>\n",
       "      <td>11.4705</td>\n",
       "      <td>4.4637</td>\n",
       "      <td>8.7335</td>\n",
       "      <td>2.1890</td>\n",
       "      <td>44.872</td>\n",
       "      <td>4.0065</td>\n",
       "      <td>1.3168</td>\n",
       "      <td>27.4315</td>\n",
       "      <td>9.3050</td>\n",
       "      <td>1.9699</td>\n",
       "      <td>188.7000</td>\n",
       "      <td>42.778</td>\n",
       "      <td>42.6949</td>\n",
       "      <td>0.3722</td>\n",
       "      <td>1.1743</td>\n",
       "      <td>6.7307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5697</th>\n",
       "      <td>1999-01-05</td>\n",
       "      <td>1.8944</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.7965</td>\n",
       "      <td>1.6123</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.58230</td>\n",
       "      <td>34.917</td>\n",
       "      <td>7.4495</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.71220</td>\n",
       "      <td>324.70</td>\n",
       "      <td>9.1341</td>\n",
       "      <td>NaN</td>\n",
       "      <td>250.80</td>\n",
       "      <td>9314.51</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81.5300</td>\n",
       "      <td>130.96</td>\n",
       "      <td>1373.01</td>\n",
       "      <td>4.71740</td>\n",
       "      <td>0.6657</td>\n",
       "      <td>0.4432</td>\n",
       "      <td>11.5960</td>\n",
       "      <td>4.4805</td>\n",
       "      <td>8.7745</td>\n",
       "      <td>2.2011</td>\n",
       "      <td>44.745</td>\n",
       "      <td>4.0245</td>\n",
       "      <td>1.3168</td>\n",
       "      <td>26.5876</td>\n",
       "      <td>9.4025</td>\n",
       "      <td>1.9655</td>\n",
       "      <td>188.7750</td>\n",
       "      <td>42.848</td>\n",
       "      <td>42.5048</td>\n",
       "      <td>0.3728</td>\n",
       "      <td>1.1790</td>\n",
       "      <td>6.7975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5698</th>\n",
       "      <td>1999-01-04</td>\n",
       "      <td>1.9100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.8004</td>\n",
       "      <td>1.6168</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.58231</td>\n",
       "      <td>35.107</td>\n",
       "      <td>7.4501</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.71110</td>\n",
       "      <td>327.15</td>\n",
       "      <td>9.1332</td>\n",
       "      <td>NaN</td>\n",
       "      <td>251.48</td>\n",
       "      <td>9433.61</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81.4800</td>\n",
       "      <td>133.73</td>\n",
       "      <td>1398.59</td>\n",
       "      <td>4.71700</td>\n",
       "      <td>0.6668</td>\n",
       "      <td>0.4432</td>\n",
       "      <td>11.6446</td>\n",
       "      <td>4.4798</td>\n",
       "      <td>8.8550</td>\n",
       "      <td>2.2229</td>\n",
       "      <td>45.510</td>\n",
       "      <td>4.0712</td>\n",
       "      <td>1.3111</td>\n",
       "      <td>25.2875</td>\n",
       "      <td>9.4696</td>\n",
       "      <td>1.9554</td>\n",
       "      <td>189.0450</td>\n",
       "      <td>42.991</td>\n",
       "      <td>42.6799</td>\n",
       "      <td>0.3723</td>\n",
       "      <td>1.1789</td>\n",
       "      <td>6.9358</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Period\\Unit: [Australian dollar ] [Bulgarian lev ] [Brazilian real ] [Canadian dollar ] [Swiss franc ] [Chinese yuan renminbi ] [Cypriot pound ] [Czech koruna ] [Danish krone ] [Estonian kroon ] [UK pound sterling ] [Greek drachma ] [Hong Kong dollar ] [Croatian kuna ] [Hungarian forint ] [Indonesian rupiah ] [Israeli shekel ] [Indian rupee ]   [Iceland krona ]   [Japanese yen ] [Korean won ] [Lithuanian litas ] [Latvian lats ] [Maltese lira ] [Mexican peso ] [Malaysian ringgit ] [Norwegian krone ] [New Zealand dollar ] [Philippine peso ] [Polish zloty ]    [Romanian leu ]   [Russian rouble ] [Swedish krona ] [Singapore dollar ] [Slovenian tolar ] [Slovak koruna ] [Thai baht ]    [Turkish lira ]   [US dollar ] [South African rand ]\n",
       "5694  1999-01-08         1.8406               NaN               NaN             1.7643           1.6138                NaN                0.58187          34.938          7.4433           15.6466            0.70940            324.00             9.0302              NaN              250.15              9321.63               NaN              NaN                   80.9900      130.09         1366.73          4.66430           0.6654          0.4419          11.4414           4.4295              8.5900               2.1557              44.295            4.0363                   1.3143       27.2075          9.1650             1.9537            188.8400           42.560         42.5590                 0.3718    1.1659            6.7855       \n",
       "5695  1999-01-07         1.8474               NaN               NaN             1.7602           1.6165                NaN                0.58187          34.886          7.4431           15.6466            0.70585            324.40             9.0131              NaN              250.09              9218.77               NaN              NaN                   81.0600      129.43         1337.16          4.65480           0.6627          0.4413          11.5511           4.4203              8.6295               2.1531              44.436            4.0165                   1.3092       26.9876          9.1800             1.9436            188.8000           42.765         42.1678                 0.3701    1.1632            6.8283       \n",
       "5696  1999-01-06         1.8820               NaN               NaN             1.7711           1.6116                NaN                0.58200          34.850          7.4452           15.6466            0.70760            324.72             9.1010              NaN              250.67              9337.68               NaN              NaN                   81.5400      131.42         1359.54          4.69940           0.6649          0.4420          11.4705           4.4637              8.7335               2.1890              44.872            4.0065                   1.3168       27.4315          9.3050             1.9699            188.7000           42.778         42.6949                 0.3722    1.1743            6.7307       \n",
       "5697  1999-01-05         1.8944               NaN               NaN             1.7965           1.6123                NaN                0.58230          34.917          7.4495           15.6466            0.71220            324.70             9.1341              NaN              250.80              9314.51               NaN              NaN                   81.5300      130.96         1373.01          4.71740           0.6657          0.4432          11.5960           4.4805              8.7745               2.2011              44.745            4.0245                   1.3168       26.5876          9.4025             1.9655            188.7750           42.848         42.5048                 0.3728    1.1790            6.7975       \n",
       "5698  1999-01-04         1.9100               NaN               NaN             1.8004           1.6168                NaN                0.58231          35.107          7.4501           15.6466            0.71110            327.15             9.1332              NaN              251.48              9433.61               NaN              NaN                   81.4800      133.73         1398.59          4.71700           0.6668          0.4432          11.6446           4.4798              8.8550               2.2229              45.510            4.0712                   1.3111       25.2875          9.4696             1.9554            189.0450           42.991         42.6799                 0.3723    1.1789            6.9358       "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 5699 entries, 0 to 5698\n",
      "Data columns (total 41 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   Period\\Unit:              5699 non-null   object \n",
      " 1   [Australian dollar ]      5699 non-null   object \n",
      " 2   [Bulgarian lev ]          5297 non-null   object \n",
      " 3   [Brazilian real ]         5431 non-null   object \n",
      " 4   [Canadian dollar ]        5699 non-null   object \n",
      " 5   [Swiss franc ]            5699 non-null   object \n",
      " 6   [Chinese yuan renminbi ]  5431 non-null   object \n",
      " 7   [Cypriot pound ]          2346 non-null   object \n",
      " 8   [Czech koruna ]           5699 non-null   object \n",
      " 9   [Danish krone ]           5699 non-null   object \n",
      " 10  [Estonian kroon ]         3130 non-null   object \n",
      " 11  [UK pound sterling ]      5699 non-null   object \n",
      " 12  [Greek drachma ]          520 non-null    object \n",
      " 13  [Hong Kong dollar ]       5699 non-null   object \n",
      " 14  [Croatian kuna ]          5431 non-null   object \n",
      " 15  [Hungarian forint ]       5699 non-null   object \n",
      " 16  [Indonesian rupiah ]      5699 non-null   object \n",
      " 17  [Israeli shekel ]         5431 non-null   object \n",
      " 18  [Indian rupee ]           5431 non-null   object \n",
      " 19  [Iceland krona ]          3292 non-null   float64\n",
      " 20  [Japanese yen ]           5699 non-null   object \n",
      " 21  [Korean won ]             5699 non-null   object \n",
      " 22  [Lithuanian litas ]       4159 non-null   object \n",
      " 23  [Latvian lats ]           3904 non-null   object \n",
      " 24  [Maltese lira ]           2346 non-null   object \n",
      " 25  [Mexican peso ]           5699 non-null   object \n",
      " 26  [Malaysian ringgit ]      5699 non-null   object \n",
      " 27  [Norwegian krone ]        5699 non-null   object \n",
      " 28  [New Zealand dollar ]     5699 non-null   object \n",
      " 29  [Philippine peso ]        5699 non-null   object \n",
      " 30  [Polish zloty ]           5699 non-null   object \n",
      " 31  [Romanian leu ]           5637 non-null   float64\n",
      " 32  [Russian rouble ]         5699 non-null   object \n",
      " 33  [Swedish krona ]          5699 non-null   object \n",
      " 34  [Singapore dollar ]       5699 non-null   object \n",
      " 35  [Slovenian tolar ]        2085 non-null   object \n",
      " 36  [Slovak koruna ]          2608 non-null   object \n",
      " 37  [Thai baht ]              5699 non-null   object \n",
      " 38  [Turkish lira ]           5637 non-null   float64\n",
      " 39  [US dollar ]              5699 non-null   object \n",
      " 40  [South African rand ]     5699 non-null   object \n",
      "dtypes: float64(3), object(38)\n",
      "memory usage: 1.8+ MB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "None"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# import libraries and set display options\n",
    "import pandas as pd\n",
    "import pprint\n",
    "\n",
    "pd.options.display.float_format = '{:20,.4f}'.format\n",
    "pd.set_option('display.max_rows', None)\n",
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.width', 3000)\n",
    "pd.set_option('display.colheader_justify', 'center')\n",
    "pd.set_option('display.precision', 3)\n",
    "\n",
    "# open file\n",
    "x_rates = pd.read_csv(\"euro-daily-hist_1999_2020.csv\")\n",
    "\n",
    "# head, tail, and basic info\n",
    "display(x_rates.head())\n",
    "display(x_rates.tail())\n",
    "display(x_rates.info())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initial Look Continued\n",
    "The dataset covers the time period from January 1999 to January 2021. It has 5699 rows and 41 columns. Some of these columns have less than half the number of entries as other columns. In the original data set, cells with missing entries have a hyphen (-). This causes problems with a lot of the functions that will be used. For the time being the hyphens will be converted to the value ```NaN```, which preserves the row of information.\n",
    "## Data Cleaning\n",
    "The first steps will be:\n",
    "* Clean and modify column names\n",
    "* Convert to `datetime` data type\n",
    "* Sort the values with oldest first and reset the index\n",
    "* Clean currency columns\n",
    "* Convert exchange rates to floats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/bz/5cj1tzbj5xn319rpqrw6gpmh0000gn/T/ipykernel_4881/1330394742.py:4: FutureWarning: The default value of regex will change from True to False in a future version. In addition, single character regular expressions will *not* be treated as literal strings when regex=True.\n",
      "  x_rates.columns = x_rates.columns.str.replace(\"[\",\"\").str.replace(\"]\",\"\")\n"
     ]
    },
    {
     "data": {
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: center;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>australian_dollar</th>\n",
       "      <th>bulgarian_lev</th>\n",
       "      <th>brazilian_real</th>\n",
       "      <th>canadian_dollar</th>\n",
       "      <th>swiss_franc</th>\n",
       "      <th>chinese_yuan</th>\n",
       "      <th>cypriot_pound</th>\n",
       "      <th>czech_koruna</th>\n",
       "      <th>danish_krone</th>\n",
       "      <th>estonian_kroon</th>\n",
       "      <th>uk_pound</th>\n",
       "      <th>greek_drachma</th>\n",
       "      <th>hong_kong_dollar</th>\n",
       "      <th>croatian_kuna</th>\n",
       "      <th>hungarian_forint</th>\n",
       "      <th>indonesian_rupiah</th>\n",
       "      <th>israeli_shekel</th>\n",
       "      <th>indian_rupee</th>\n",
       "      <th>iceland_krona</th>\n",
       "      <th>japanese_yen</th>\n",
       "      <th>korean_won</th>\n",
       "      <th>lithuanian_litas</th>\n",
       "      <th>latvian_lats</th>\n",
       "      <th>maltese_lira</th>\n",
       "      <th>mexican_peso</th>\n",
       "      <th>malaysian_ringgit</th>\n",
       "      <th>norwegian_krone</th>\n",
       "      <th>new_zealand_dollar</th>\n",
       "      <th>philippine_peso</th>\n",
       "      <th>polish_zloty</th>\n",
       "      <th>romanian_leu</th>\n",
       "      <th>russian_rouble</th>\n",
       "      <th>swedish_krona</th>\n",
       "      <th>singapore_dollar</th>\n",
       "      <th>slovenian_tolar</th>\n",
       "      <th>slovak_koruna</th>\n",
       "      <th>thai_baht</th>\n",
       "      <th>turkish_lira</th>\n",
       "      <th>us_dollar</th>\n",
       "      <th>south_african_rand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1999-01-04</td>\n",
       "      <td>1.9100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.8004</td>\n",
       "      <td>1.6168</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.5823</td>\n",
       "      <td>35.1070</td>\n",
       "      <td>7.4501</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.7111</td>\n",
       "      <td>327.1500</td>\n",
       "      <td>9.1332</td>\n",
       "      <td>NaN</td>\n",
       "      <td>251.4800</td>\n",
       "      <td>9,433.6100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81.4800</td>\n",
       "      <td>133.7300</td>\n",
       "      <td>1,398.5900</td>\n",
       "      <td>4.7170</td>\n",
       "      <td>0.6668</td>\n",
       "      <td>0.4432</td>\n",
       "      <td>11.6446</td>\n",
       "      <td>4.4798</td>\n",
       "      <td>8.8550</td>\n",
       "      <td>2.2229</td>\n",
       "      <td>45.5100</td>\n",
       "      <td>4.0712</td>\n",
       "      <td>1.3111</td>\n",
       "      <td>25.2875</td>\n",
       "      <td>9.4696</td>\n",
       "      <td>1.9554</td>\n",
       "      <td>189.0450</td>\n",
       "      <td>42.9910</td>\n",
       "      <td>42.6799</td>\n",
       "      <td>0.3723</td>\n",
       "      <td>1.1789</td>\n",
       "      <td>6.9358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1999-01-05</td>\n",
       "      <td>1.8944</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.7965</td>\n",
       "      <td>1.6123</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.5823</td>\n",
       "      <td>34.9170</td>\n",
       "      <td>7.4495</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.7122</td>\n",
       "      <td>324.7000</td>\n",
       "      <td>9.1341</td>\n",
       "      <td>NaN</td>\n",
       "      <td>250.8000</td>\n",
       "      <td>9,314.5100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81.5300</td>\n",
       "      <td>130.9600</td>\n",
       "      <td>1,373.0100</td>\n",
       "      <td>4.7174</td>\n",
       "      <td>0.6657</td>\n",
       "      <td>0.4432</td>\n",
       "      <td>11.5960</td>\n",
       "      <td>4.4805</td>\n",
       "      <td>8.7745</td>\n",
       "      <td>2.2011</td>\n",
       "      <td>44.7450</td>\n",
       "      <td>4.0245</td>\n",
       "      <td>1.3168</td>\n",
       "      <td>26.5876</td>\n",
       "      <td>9.4025</td>\n",
       "      <td>1.9655</td>\n",
       "      <td>188.7750</td>\n",
       "      <td>42.8480</td>\n",
       "      <td>42.5048</td>\n",
       "      <td>0.3728</td>\n",
       "      <td>1.1790</td>\n",
       "      <td>6.7975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1999-01-06</td>\n",
       "      <td>1.8820</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.7711</td>\n",
       "      <td>1.6116</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.5820</td>\n",
       "      <td>34.8500</td>\n",
       "      <td>7.4452</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.7076</td>\n",
       "      <td>324.7200</td>\n",
       "      <td>9.1010</td>\n",
       "      <td>NaN</td>\n",
       "      <td>250.6700</td>\n",
       "      <td>9,337.6800</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81.5400</td>\n",
       "      <td>131.4200</td>\n",
       "      <td>1,359.5400</td>\n",
       "      <td>4.6994</td>\n",
       "      <td>0.6649</td>\n",
       "      <td>0.4420</td>\n",
       "      <td>11.4705</td>\n",
       "      <td>4.4637</td>\n",
       "      <td>8.7335</td>\n",
       "      <td>2.1890</td>\n",
       "      <td>44.8720</td>\n",
       "      <td>4.0065</td>\n",
       "      <td>1.3168</td>\n",
       "      <td>27.4315</td>\n",
       "      <td>9.3050</td>\n",
       "      <td>1.9699</td>\n",
       "      <td>188.7000</td>\n",
       "      <td>42.7780</td>\n",
       "      <td>42.6949</td>\n",
       "      <td>0.3722</td>\n",
       "      <td>1.1743</td>\n",
       "      <td>6.7307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1999-01-07</td>\n",
       "      <td>1.8474</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.7602</td>\n",
       "      <td>1.6165</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.5819</td>\n",
       "      <td>34.8860</td>\n",
       "      <td>7.4431</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.7058</td>\n",
       "      <td>324.4000</td>\n",
       "      <td>9.0131</td>\n",
       "      <td>NaN</td>\n",
       "      <td>250.0900</td>\n",
       "      <td>9,218.7700</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81.0600</td>\n",
       "      <td>129.4300</td>\n",
       "      <td>1,337.1600</td>\n",
       "      <td>4.6548</td>\n",
       "      <td>0.6627</td>\n",
       "      <td>0.4413</td>\n",
       "      <td>11.5511</td>\n",
       "      <td>4.4203</td>\n",
       "      <td>8.6295</td>\n",
       "      <td>2.1531</td>\n",
       "      <td>44.4360</td>\n",
       "      <td>4.0165</td>\n",
       "      <td>1.3092</td>\n",
       "      <td>26.9876</td>\n",
       "      <td>9.1800</td>\n",
       "      <td>1.9436</td>\n",
       "      <td>188.8000</td>\n",
       "      <td>42.7650</td>\n",
       "      <td>42.1678</td>\n",
       "      <td>0.3701</td>\n",
       "      <td>1.1632</td>\n",
       "      <td>6.8283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1999-01-08</td>\n",
       "      <td>1.8406</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.7643</td>\n",
       "      <td>1.6138</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.5819</td>\n",
       "      <td>34.9380</td>\n",
       "      <td>7.4433</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.7094</td>\n",
       "      <td>324.0000</td>\n",
       "      <td>9.0302</td>\n",
       "      <td>NaN</td>\n",
       "      <td>250.1500</td>\n",
       "      <td>9,321.6300</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80.9900</td>\n",
       "      <td>130.0900</td>\n",
       "      <td>1,366.7300</td>\n",
       "      <td>4.6643</td>\n",
       "      <td>0.6654</td>\n",
       "      <td>0.4419</td>\n",
       "      <td>11.4414</td>\n",
       "      <td>4.4295</td>\n",
       "      <td>8.5900</td>\n",
       "      <td>2.1557</td>\n",
       "      <td>44.2950</td>\n",
       "      <td>4.0363</td>\n",
       "      <td>1.3143</td>\n",
       "      <td>27.2075</td>\n",
       "      <td>9.1650</td>\n",
       "      <td>1.9537</td>\n",
       "      <td>188.8400</td>\n",
       "      <td>42.5600</td>\n",
       "      <td>42.5590</td>\n",
       "      <td>0.3718</td>\n",
       "      <td>1.1659</td>\n",
       "      <td>6.7855</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     date      australian_dollar   bulgarian_lev  brazilian_real    canadian_dollar        swiss_franc      chinese_yuan     cypriot_pound        czech_koruna         danish_krone        estonian_kroon          uk_pound           greek_drachma      hong_kong_dollar    croatian_kuna   hungarian_forint     indonesian_rupiah   israeli_shekel  indian_rupee     iceland_krona        japanese_yen          korean_won        lithuanian_litas       latvian_lats         maltese_lira         mexican_peso       malaysian_ringgit     norwegian_krone    new_zealand_dollar     philippine_peso       polish_zloty         romanian_leu        russian_rouble        swedish_krona      singapore_dollar      slovenian_tolar       slovak_koruna          thai_baht          turkish_lira           us_dollar       south_african_rand \n",
       "0 1999-01-04               1.9100      NaN             NaN                     1.8004               1.6168      NaN                    0.5823              35.1070               7.4501              15.6466               0.7111             327.1500               9.1332      NaN                   251.4800           9,433.6100       NaN            NaN                   81.4800             133.7300           1,398.5900               4.7170               0.6668               0.4432              11.6446               4.4798               8.8550               2.2229              45.5100               4.0712               1.3111              25.2875               9.4696               1.9554             189.0450              42.9910              42.6799               0.3723               1.1789               6.9358\n",
       "1 1999-01-05               1.8944      NaN             NaN                     1.7965               1.6123      NaN                    0.5823              34.9170               7.4495              15.6466               0.7122             324.7000               9.1341      NaN                   250.8000           9,314.5100       NaN            NaN                   81.5300             130.9600           1,373.0100               4.7174               0.6657               0.4432              11.5960               4.4805               8.7745               2.2011              44.7450               4.0245               1.3168              26.5876               9.4025               1.9655             188.7750              42.8480              42.5048               0.3728               1.1790               6.7975\n",
       "2 1999-01-06               1.8820      NaN             NaN                     1.7711               1.6116      NaN                    0.5820              34.8500               7.4452              15.6466               0.7076             324.7200               9.1010      NaN                   250.6700           9,337.6800       NaN            NaN                   81.5400             131.4200           1,359.5400               4.6994               0.6649               0.4420              11.4705               4.4637               8.7335               2.1890              44.8720               4.0065               1.3168              27.4315               9.3050               1.9699             188.7000              42.7780              42.6949               0.3722               1.1743               6.7307\n",
       "3 1999-01-07               1.8474      NaN             NaN                     1.7602               1.6165      NaN                    0.5819              34.8860               7.4431              15.6466               0.7058             324.4000               9.0131      NaN                   250.0900           9,218.7700       NaN            NaN                   81.0600             129.4300           1,337.1600               4.6548               0.6627               0.4413              11.5511               4.4203               8.6295               2.1531              44.4360               4.0165               1.3092              26.9876               9.1800               1.9436             188.8000              42.7650              42.1678               0.3701               1.1632               6.8283\n",
       "4 1999-01-08               1.8406      NaN             NaN                     1.7643               1.6138      NaN                    0.5819              34.9380               7.4433              15.6466               0.7094             324.0000               9.0302      NaN                   250.1500           9,321.6300       NaN            NaN                   80.9900             130.0900           1,366.7300               4.6643               0.6654               0.4419              11.4414               4.4295               8.5900               2.1557              44.2950               4.0363               1.3143              27.2075               9.1650               1.9537             188.8400              42.5600              42.5590               0.3718               1.1659               6.7855"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# strip brackets and trailing space from country names\n",
    "# replace remaining space with underscore\n",
    "# lower case all column names\n",
    "x_rates.columns = x_rates.columns.str.replace(\"[\",\"\").str.replace(\"]\",\"\")\n",
    "x_rates.columns = x_rates.columns.str.rstrip()\n",
    "x_rates.columns = x_rates.columns.str.replace(\" \",\"_\")\n",
    "x_rates.columns = x_rates.columns.str.lower()\n",
    "\n",
    "# rename columns\n",
    "x_rates.rename(columns={\"period\\\\unit:\":\"date\",\n",
    "                        \"chinese_yuan_renminbi\":\"chinese_yuan\",\n",
    "                        \"uk_pound_sterling\":\"uk_pound\"}, inplace=True)\n",
    "\n",
    "# convert datetime\n",
    "x_rates[\"date\"] = pd.to_datetime(x_rates[\"date\"])\n",
    "\n",
    "# resort and reindex\n",
    "x_rates.sort_values(\"date\", inplace=True)\n",
    "x_rates.reset_index(drop=True, inplace=True)\n",
    "\n",
    "# convert hyphens in currency columns to NaN\n",
    "import numpy as np\n",
    "x_rates = x_rates.replace(\"-\", np.nan)\n",
    "\n",
    "# convert exchange rate values to float\n",
    "x_rates.iloc[:,1:] = x_rates.iloc[:,1:].astype(float)\n",
    "\n",
    "# set style for cells with centered output\n",
    "from IPython.core.display import HTML\n",
    "HTML(\"\"\"\n",
    "<style>\n",
    ".output_png {\n",
    "    display: table-cell;\n",
    "    text-align: center;\n",
    "    vertical-align: middle;\n",
    "}\n",
    "</style>\n",
    "\"\"\")\n",
    "\n",
    "# x_rates head\n",
    "display(x_rates.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dollar to Euro\n",
    "The change over time in Euro exchange rate can be visualized in a line graph. The US dollar is the first currency to be examined."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x270 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create a us dollar to euro dataframe and add 30 day rolling mean column\n",
    "us_dollar = x_rates[[\"date\",\"us_dollar\"]].copy()\n",
    "us_dollar[\"rolling_mean_30\"] = us_dollar[\"us_dollar\"].rolling(30).mean()\n",
    "\n",
    "# line graph for dollar to euro exchange rate\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "%matplotlib inline\n",
    "fig, ax = plt.subplots(figsize=(10,3.75))\n",
    "ax.plot(us_dollar[\"date\"], us_dollar[\"rolling_mean_30\"])\n",
    "ax.set(xlabel=\"Year\",\n",
    "       ylabel=\"US dollar\",\n",
    "       title=\"US Dollar to Euro Exhcange Rates\")\n",
    "ax.set_xticks([\"2000-01-04 00:00:00\", \"2005-01-04 00:00:00\", \"2010-01-04 00:00:00\",\n",
    "               \"2015-01-04 00:00:00\", \"2020-01-04 00:00:00\"])\n",
    "ax.set_xticklabels([2000,2005,2010,2015,2020])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Euro to Dollar Continued\n",
    "The line graph shows that the exchange rate between the Euro and US dollar is pretty variable. There are also a lot of gaps in the graph. These represent points in the data frame where information for a particular day is missing. This is the most accurate representation of the data, but it's not very easy to look at. A quick visual check can illustrate this overlap and then compare the original data frame with one where the missing dates are removed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x540 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x540 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create nan group and get dates\n",
    "nan_dollar_group = us_dollar[us_dollar[\"us_dollar\"].isnull()]\n",
    "nan_days = nan_dollar_group[\"date\"]\n",
    "\n",
    "# line graph showing dollar to euro showing NaN values with and without highlight\n",
    "fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(10,7.5))\n",
    "ax1.plot(us_dollar[\"date\"], us_dollar[\"rolling_mean_30\"])\n",
    "ax1.set(title=\"dataset w/ NaN values\")\n",
    "ax2.plot(us_dollar[\"date\"], us_dollar[\"rolling_mean_30\"])\n",
    "ax2.set(title=\"dataset w/ corresponding dates in light blue\")\n",
    "for ax in ax1, ax2:\n",
    "    ax.set_xticks([\"2000-01-04 00:00:00\", \"2005-01-04 00:00:00\", \"2010-01-04 00:00:00\",\n",
    "               \"2015-01-04 00:00:00\", \"2020-01-04 00:00:00\"])\n",
    "    ax.set_xticklabels([2000,2005,2010,2015,2020])\n",
    "for xc in nan_days:\n",
    "    plt.axvline(x=xc, color=\"lightcyan\")\n",
    "fig.suptitle(\"US dollar to Euro exchange rates\", fontsize=20)\n",
    "fig.tight_layout(pad=3.0)\n",
    "plt.show()\n",
    "\n",
    "# create a dollar to euro dataframe with NaN dates removed\n",
    "US_dollar_nonull = x_rates[x_rates[\"us_dollar\"].notna()].copy()\n",
    "US_dollar_nonull[\"rolling_mean_30\"] = US_dollar_nonull[\"us_dollar\"].rolling(30).mean()\n",
    "\n",
    "# line graph showing 30 day rolling mean with and without NaN rows\n",
    "fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(10,7.5))\n",
    "ax1.plot(us_dollar[\"date\"], us_dollar[\"rolling_mean_30\"])\n",
    "ax1.set(title=\"NaN rows included\")\n",
    "ax2.plot(US_dollar_nonull[\"date\"], US_dollar_nonull[\"rolling_mean_30\"])\n",
    "ax2.set(title=\"NaN rows removed\")\n",
    "for ax in ax1, ax2:\n",
    "    ax.set_xticks([\"2000-01-04 00:00:00\", \"2005-01-04 00:00:00\", \"2010-01-04 00:00:00\",\n",
    "               \"2015-01-04 00:00:00\", \"2020-01-04 00:00:00\"])\n",
    "    ax.set_xticklabels([2000,2005,2010,2015,2020])\n",
    "fig.suptitle(\"US dollar to Euro exchange rates\", fontsize=20)\n",
    "fig.tight_layout(pad=3.0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Euro to Dollar Conclusion\n",
    "The third graph shows vertical blue stripes for all dates with missing information. These correspond perfectly with the gaps in the original chart. The final chart, with these rows removed, appears to be good match and is easier to look at. This also demonstrates how the rolling mean handles NaN values within a data frame. In either case the shape of the line is identical where the information exists, therefor both are similarly accurate represenations of the availalble data. All further currency data frames will be handled the same.\n",
    "\n",
    "## Euro & Traded Pairs\n",
    "### Euro to Highly Traded Currencies\n",
    "The line graphs represent the exchange rates for the Euro to the US dollar, Japanese yen, UK pound, and Australian dollar. These four currencies, in addition to the Euro, are the top five currenceis in the Forex market. All five together comprise over 75% of daily trades (4).\n",
    "### Euro to Least Traded Currencies\n",
    "The line graphs represent the exchange rates for the Euro to the Israeli shekel, Philippine peso, Malaysian ringgit, and Romanian leu. These four currencies have low trade volumes, they comprise less than 0.4% of daily trades (4)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "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: center;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>australian_dollar</th>\n",
       "      <th>australian_dollar_rolling_30</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1999-02-12</td>\n",
       "      <td>1.7459</td>\n",
       "      <td>1.8102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>1999-02-15</td>\n",
       "      <td>1.7353</td>\n",
       "      <td>1.8043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>1999-02-16</td>\n",
       "      <td>1.7467</td>\n",
       "      <td>1.7994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>1999-02-17</td>\n",
       "      <td>1.7751</td>\n",
       "      <td>1.7958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>1999-02-18</td>\n",
       "      <td>1.7687</td>\n",
       "      <td>1.7932</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      date      australian_dollar   australian_dollar_rolling_30\n",
       "29 1999-02-12               1.7459                    1.8102    \n",
       "30 1999-02-15               1.7353                    1.8043    \n",
       "31 1999-02-16               1.7467                    1.7994    \n",
       "32 1999-02-17               1.7751                    1.7958    \n",
       "33 1999-02-18               1.7687                    1.7932    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['australian_dollar']\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# building the rolling 30 mean into the data frame\n",
    "mean_rates = x_rates.rolling(30).mean()\n",
    "mean_rates = mean_rates.add_suffix(\"_rolling_30\")\n",
    "new_frame = pd.concat([x_rates, mean_rates], axis=1)\n",
    "new_frame = new_frame[[item for items in zip(x_rates.columns, mean_rates.columns) for item in items]]\n",
    "# display(new_frame.head())\n",
    "# # how do I get the currency columns before the rolling mean column\n",
    "\n",
    "# function to build data frame for Euro to other half of trading pair\n",
    "# this one uses new_frame, which has the 30 day rolling mean incorporated, and then removes the NaN dates\n",
    "framer_list = []\n",
    "\n",
    "def framer(col):\n",
    "    framer_list.append(col)\n",
    "    col_names = [\"date\", (str(col)), (str(col)+\"_rolling_30\")]\n",
    "    df = pd.DataFrame(columns=col_names)\n",
    "    df.iloc[:,0] = new_frame[\"date\"]\n",
    "    df.iloc[:,1] = new_frame[col]\n",
    "    df.iloc[:,2] = new_frame[(str(col)+\"_rolling_30\")]\n",
    "    df = df[df.iloc[:,2].notna()]\n",
    "    return df\n",
    "\n",
    "australian_dollar = framer(\"australian_dollar\")\n",
    "display(australian_dollar.head())\n",
    "print(framer_list)\n",
    "plt.plot(australian_dollar[\"date\"], australian_dollar[\"australian_dollar_rolling_30\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# function to build data frame for Euro to other half of trading pair\n",
    "# this one uses x_rates, removes the NaN values, and then adds a rolling 30 mean\n",
    "xchange_list = []\n",
    "\n",
    "def xchange(col):\n",
    "    xchange_list.append(col)\n",
    "    df = x_rates[[\"date\",col]].copy()\n",
    "    df = df[df[col].notna()]\n",
    "    df[\"rolling_mean_30\"] = df[col].rolling(30).mean()\n",
    "    return df\n",
    "\n",
    "# canadian_dollar = xchange(\"canadian_dollar\")\n",
    "# display(canadian_dollar.head())\n",
    "# print(xchange_list)\n",
    "# plt.plot(canadian_dollar[\"date\"], canadian_dollar[\"rolling_mean_30\"])\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# is there a way to apply either function to all the columns in x_rates?\n",
    "# one drawback could be having 42 data frames\n",
    "    \n",
    "# calling xchange function on four highly traded currencies\n",
    "us_dollar = xchange(\"us_dollar\")\n",
    "japanese_yen = xchange(\"japanese_yen\")\n",
    "uk_pound = xchange(\"uk_pound\")\n",
    "australian_dollar = xchange(\"australian_dollar\")\n",
    "\n",
    "# calling xchange function on four least traded currencies\n",
    "israeli_shekel = xchange(\"israeli_shekel\")\n",
    "philippine_peso = xchange(\"philippine_peso\")\n",
    "malaysian_ringgit = xchange(\"malaysian_ringgit\")\n",
    "romanian_leu = xchange(\"romanian_leu\")\n",
    "\n",
    "# it would be cool to convert or use xchange_list for this but I can't get the string off\n",
    "c_list = [us_dollar, japanese_yen, uk_pound, australian_dollar,\n",
    "          israeli_shekel, philippine_peso, malaysian_ringgit, romanian_leu]\n",
    "\n",
    "# line graph showing Euro to each high frequency trading pairs\n",
    "fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows=2, ncols=2, figsize=(12,8))\n",
    "fig.tight_layout(pad=3)\n",
    "years = mdates.YearLocator() # every year\n",
    "years_fmt = mdates.DateFormatter('%Y')\n",
    "for ax in ax1, ax2, ax3, ax4:\n",
    "    ax.xaxis.set_major_locator(years) # format the x ticks\n",
    "    ax.xaxis.set_major_formatter(years_fmt)\n",
    "    fmt_three_years = mdates.MonthLocator(interval = 36) # Major ticks every 3 years\n",
    "    ax.xaxis.set_major_locator(fmt_three_years)\n",
    "    ax.set(yticks=[],\n",
    "           xlabel=\"Year\")\n",
    "for ax, currency in zip((ax1, ax2, ax3, ax4), c_list[:5]):\n",
    "    ax.plot(currency[\"date\"], currency[\"rolling_mean_30\"])\n",
    "#   ax.set_ylabel(str(currency)) # why not, i can get it to change to a string \"currency\", but not a variable\n",
    "ax1.set(ylabel=\"US dollar\")\n",
    "ax2.set(ylabel=\"Japanese yen\")\n",
    "ax3.set(ylabel=\"UK pound\")\n",
    "ax4.set(ylabel=\"Australian dollar\")\n",
    "fig.suptitle(\"Euro to High Frequency Pairs\", fontsize=20)\n",
    "plt.show()\n",
    "\n",
    "# line graph showing Euro to each low frequency trading pairs\n",
    "fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows=2, ncols=2, figsize=(12,8))\n",
    "fig.tight_layout(pad=3)\n",
    "for ax in ax1, ax2, ax3, ax4:\n",
    "    ax.xaxis.set_major_locator(years) # format the x ticks\n",
    "    ax.xaxis.set_major_formatter(years_fmt)\n",
    "    fmt_three_years = mdates.MonthLocator(interval = 36) # Major ticks every 3 years\n",
    "    ax.xaxis.set_major_locator(fmt_three_years)\n",
    "    ax.set(yticks=[],\n",
    "           xlabel=\"Year\")\n",
    "for ax, currency in zip((ax1, ax2, ax3, ax4), c_list[4:]):\n",
    "    ax.plot(currency[\"date\"], currency[\"rolling_mean_30\"])\n",
    "#   ax.set_ylabel(str(currency)) # why not, i can get it to change to a string \"currency\", but not a variable\n",
    "ax1.set(ylabel=\"Israeli shekel\")\n",
    "ax2.set(ylabel=\"Philippine peso\")\n",
    "ax3.set(ylabel=\"Malaysian ringgit\")\n",
    "ax4.set(ylabel=\"Romanian leu\")\n",
    "fig.suptitle(\"Euro to Low Frequency Pairs\", fontsize=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Euro to Traded Pairs Conclusion**\n",
    "\n",
    "### High Frequency Pairs\n",
    "* The US dollar, Japanese yen, and UK pound all show a tight ratio with the Euro in the early 2000s.\n",
    "* Both the Japanese yen and Australian dollar show similar trade ratios in late 2011.\n",
    "### Low Frequency Pairs\n",
    "* The Israeli shekel appears to have increased in value and the Romanian leu is definitely loosing value.\n",
    "* The shekel and leu appear to be fairly stable, or have low volatility.\n",
    "* The Israeli shekel and Malaysian ringgit also show the tight ratio of the early 2000s. This is seen to a lesser extent in the Phillipine pese\n",
    "\n",
    "## **The early struggle**\n",
    "An overlay of all currencies focused on the first decade of the Euro shows it's initial struggle and eventual success."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_values1 = us_dollar[\"date\"]\n",
    "y_values1 = us_dollar[\"rolling_mean_30\"]\n",
    "\n",
    "x_values2 = japanese_yen[\"date\"]\n",
    "y_values2 = japanese_yen[\"rolling_mean_30\"]\n",
    "\n",
    "x_values3 = uk_pound[\"date\"]\n",
    "y_values3 = uk_pound[\"rolling_mean_30\"]\n",
    "\n",
    "# x_values4 = uk_pound[\"date\"]\n",
    "# y_values4 = uk_pound[\"rolling_mean_30\"]\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, label = \"1\")\n",
    "ax2 = fig.add_subplot(111, label = \"2\", frame_on = False)\n",
    "ax3 = fig.add_subplot(111, label = \"3\", frame_on = False)\n",
    "for ax in ax, ax2, ax3:\n",
    "    ax.xaxis.set_major_locator(years) # format the x ticks\n",
    "    ax.xaxis.set_major_formatter(years_fmt)\n",
    "    fmt_three_years = mdates.MonthLocator(interval = 36) # Major ticks every 3 years\n",
    "    ax.xaxis.set_major_locator(fmt_three_years)\n",
    "    ax.set(yticks=[],\n",
    "           xlabel=\"Year\")\n",
    "#     ax.set_xlim(right=2009)\n",
    "\n",
    "ax.plot(x_values1, y_values1, color = \"blue\")\n",
    "\n",
    "ax.set_yticks([])\n",
    "# ax.set_xlabel(\"x label 1\", color = \"C0\")\n",
    "# ax.set_ylabel(\"y label 1\", color = \"C0\")\n",
    "# ax.tick_params(axis = 'x', colors = \"C0\")\n",
    "# ax.tick_params(axis = 'y', colors = \"C0\")\n",
    "\n",
    "ax2.plot(x_values2, y_values2, color = \"green\")\n",
    "\n",
    "ax2.set_yticks([])\n",
    "# ax2.xaxis.tick_top()\n",
    "# ax2.yaxis.tick_right()\n",
    "# ax2.set_xlabel('x label 2', color = \"C1\")\n",
    "# ax2.set_ylabel('y label 2', color = \"C1\")\n",
    "# ax2.xaxis.set_label_position('top')\n",
    "# ax2.yaxis.set_label_position('right')\n",
    "# ax2.tick_params(axis = 'x', colors = \"C1\")\n",
    "# ax2.tick_params(axis = 'y', colors = \"C1\")\n",
    "\n",
    "ax3.plot(x_values3, y_values3, color = \"yellow\")\n",
    "ax3.set_yticks([])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# [us_dollar, japanese_yen, uk_pound, australian_dollar,\n",
    "#  israeli_shekel, philippine_peso, malaysian_ringgit, romanian_leu]\n",
    "\n",
    "for country in c_list:\n",
    "    plt.plot(country[\"date\"],country[\"rolling_mean_30\"])\n",
    "\n",
    "# plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": false
   },
   "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: center;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>australian_dollar</th>\n",
       "      <th>bulgarian_lev</th>\n",
       "      <th>brazilian_real</th>\n",
       "      <th>canadian_dollar</th>\n",
       "      <th>swiss_franc</th>\n",
       "      <th>chinese_yuan</th>\n",
       "      <th>cypriot_pound</th>\n",
       "      <th>czech_koruna</th>\n",
       "      <th>danish_krone</th>\n",
       "      <th>estonian_kroon</th>\n",
       "      <th>uk_pound</th>\n",
       "      <th>greek_drachma</th>\n",
       "      <th>hong_kong_dollar</th>\n",
       "      <th>croatian_kuna</th>\n",
       "      <th>hungarian_forint</th>\n",
       "      <th>indonesian_rupiah</th>\n",
       "      <th>israeli_shekel</th>\n",
       "      <th>indian_rupee</th>\n",
       "      <th>iceland_krona</th>\n",
       "      <th>japanese_yen</th>\n",
       "      <th>korean_won</th>\n",
       "      <th>lithuanian_litas</th>\n",
       "      <th>latvian_lats</th>\n",
       "      <th>maltese_lira</th>\n",
       "      <th>mexican_peso</th>\n",
       "      <th>malaysian_ringgit</th>\n",
       "      <th>norwegian_krone</th>\n",
       "      <th>new_zealand_dollar</th>\n",
       "      <th>philippine_peso</th>\n",
       "      <th>polish_zloty</th>\n",
       "      <th>romanian_leu</th>\n",
       "      <th>russian_rouble</th>\n",
       "      <th>swedish_krona</th>\n",
       "      <th>singapore_dollar</th>\n",
       "      <th>slovenian_tolar</th>\n",
       "      <th>slovak_koruna</th>\n",
       "      <th>thai_baht</th>\n",
       "      <th>turkish_lira</th>\n",
       "      <th>us_dollar</th>\n",
       "      <th>south_african_rand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1999-01-04</td>\n",
       "      <td>1.9100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.8004</td>\n",
       "      <td>1.6168</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.5823</td>\n",
       "      <td>35.1070</td>\n",
       "      <td>7.4501</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.7111</td>\n",
       "      <td>327.1500</td>\n",
       "      <td>9.1332</td>\n",
       "      <td>NaN</td>\n",
       "      <td>251.4800</td>\n",
       "      <td>9,433.6100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81.4800</td>\n",
       "      <td>133.7300</td>\n",
       "      <td>1,398.5900</td>\n",
       "      <td>4.7170</td>\n",
       "      <td>0.6668</td>\n",
       "      <td>0.4432</td>\n",
       "      <td>11.6446</td>\n",
       "      <td>4.4798</td>\n",
       "      <td>8.8550</td>\n",
       "      <td>2.2229</td>\n",
       "      <td>45.5100</td>\n",
       "      <td>4.0712</td>\n",
       "      <td>1.3111</td>\n",
       "      <td>25.2875</td>\n",
       "      <td>9.4696</td>\n",
       "      <td>1.9554</td>\n",
       "      <td>189.0450</td>\n",
       "      <td>42.9910</td>\n",
       "      <td>42.6799</td>\n",
       "      <td>0.3723</td>\n",
       "      <td>1.1789</td>\n",
       "      <td>6.9358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1999-01-05</td>\n",
       "      <td>1.8944</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.7965</td>\n",
       "      <td>1.6123</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.5823</td>\n",
       "      <td>34.9170</td>\n",
       "      <td>7.4495</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.7122</td>\n",
       "      <td>324.7000</td>\n",
       "      <td>9.1341</td>\n",
       "      <td>NaN</td>\n",
       "      <td>250.8000</td>\n",
       "      <td>9,314.5100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81.5300</td>\n",
       "      <td>130.9600</td>\n",
       "      <td>1,373.0100</td>\n",
       "      <td>4.7174</td>\n",
       "      <td>0.6657</td>\n",
       "      <td>0.4432</td>\n",
       "      <td>11.5960</td>\n",
       "      <td>4.4805</td>\n",
       "      <td>8.7745</td>\n",
       "      <td>2.2011</td>\n",
       "      <td>44.7450</td>\n",
       "      <td>4.0245</td>\n",
       "      <td>1.3168</td>\n",
       "      <td>26.5876</td>\n",
       "      <td>9.4025</td>\n",
       "      <td>1.9655</td>\n",
       "      <td>188.7750</td>\n",
       "      <td>42.8480</td>\n",
       "      <td>42.5048</td>\n",
       "      <td>0.3728</td>\n",
       "      <td>1.1790</td>\n",
       "      <td>6.7975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1999-01-06</td>\n",
       "      <td>1.8820</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.7711</td>\n",
       "      <td>1.6116</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.5820</td>\n",
       "      <td>34.8500</td>\n",
       "      <td>7.4452</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.7076</td>\n",
       "      <td>324.7200</td>\n",
       "      <td>9.1010</td>\n",
       "      <td>NaN</td>\n",
       "      <td>250.6700</td>\n",
       "      <td>9,337.6800</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81.5400</td>\n",
       "      <td>131.4200</td>\n",
       "      <td>1,359.5400</td>\n",
       "      <td>4.6994</td>\n",
       "      <td>0.6649</td>\n",
       "      <td>0.4420</td>\n",
       "      <td>11.4705</td>\n",
       "      <td>4.4637</td>\n",
       "      <td>8.7335</td>\n",
       "      <td>2.1890</td>\n",
       "      <td>44.8720</td>\n",
       "      <td>4.0065</td>\n",
       "      <td>1.3168</td>\n",
       "      <td>27.4315</td>\n",
       "      <td>9.3050</td>\n",
       "      <td>1.9699</td>\n",
       "      <td>188.7000</td>\n",
       "      <td>42.7780</td>\n",
       "      <td>42.6949</td>\n",
       "      <td>0.3722</td>\n",
       "      <td>1.1743</td>\n",
       "      <td>6.7307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1999-01-07</td>\n",
       "      <td>1.8474</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.7602</td>\n",
       "      <td>1.6165</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.5819</td>\n",
       "      <td>34.8860</td>\n",
       "      <td>7.4431</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.7058</td>\n",
       "      <td>324.4000</td>\n",
       "      <td>9.0131</td>\n",
       "      <td>NaN</td>\n",
       "      <td>250.0900</td>\n",
       "      <td>9,218.7700</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81.0600</td>\n",
       "      <td>129.4300</td>\n",
       "      <td>1,337.1600</td>\n",
       "      <td>4.6548</td>\n",
       "      <td>0.6627</td>\n",
       "      <td>0.4413</td>\n",
       "      <td>11.5511</td>\n",
       "      <td>4.4203</td>\n",
       "      <td>8.6295</td>\n",
       "      <td>2.1531</td>\n",
       "      <td>44.4360</td>\n",
       "      <td>4.0165</td>\n",
       "      <td>1.3092</td>\n",
       "      <td>26.9876</td>\n",
       "      <td>9.1800</td>\n",
       "      <td>1.9436</td>\n",
       "      <td>188.8000</td>\n",
       "      <td>42.7650</td>\n",
       "      <td>42.1678</td>\n",
       "      <td>0.3701</td>\n",
       "      <td>1.1632</td>\n",
       "      <td>6.8283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1999-01-08</td>\n",
       "      <td>1.8406</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.7643</td>\n",
       "      <td>1.6138</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.5819</td>\n",
       "      <td>34.9380</td>\n",
       "      <td>7.4433</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.7094</td>\n",
       "      <td>324.0000</td>\n",
       "      <td>9.0302</td>\n",
       "      <td>NaN</td>\n",
       "      <td>250.1500</td>\n",
       "      <td>9,321.6300</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80.9900</td>\n",
       "      <td>130.0900</td>\n",
       "      <td>1,366.7300</td>\n",
       "      <td>4.6643</td>\n",
       "      <td>0.6654</td>\n",
       "      <td>0.4419</td>\n",
       "      <td>11.4414</td>\n",
       "      <td>4.4295</td>\n",
       "      <td>8.5900</td>\n",
       "      <td>2.1557</td>\n",
       "      <td>44.2950</td>\n",
       "      <td>4.0363</td>\n",
       "      <td>1.3143</td>\n",
       "      <td>27.2075</td>\n",
       "      <td>9.1650</td>\n",
       "      <td>1.9537</td>\n",
       "      <td>188.8400</td>\n",
       "      <td>42.5600</td>\n",
       "      <td>42.5590</td>\n",
       "      <td>0.3718</td>\n",
       "      <td>1.1659</td>\n",
       "      <td>6.7855</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     date      australian_dollar   bulgarian_lev  brazilian_real    canadian_dollar        swiss_franc      chinese_yuan     cypriot_pound        czech_koruna         danish_krone        estonian_kroon          uk_pound           greek_drachma      hong_kong_dollar    croatian_kuna   hungarian_forint     indonesian_rupiah   israeli_shekel  indian_rupee     iceland_krona        japanese_yen          korean_won        lithuanian_litas       latvian_lats         maltese_lira         mexican_peso       malaysian_ringgit     norwegian_krone    new_zealand_dollar     philippine_peso       polish_zloty         romanian_leu        russian_rouble        swedish_krona      singapore_dollar      slovenian_tolar       slovak_koruna          thai_baht          turkish_lira           us_dollar       south_african_rand \n",
       "0 1999-01-04               1.9100      NaN             NaN                     1.8004               1.6168      NaN                    0.5823              35.1070               7.4501              15.6466               0.7111             327.1500               9.1332      NaN                   251.4800           9,433.6100       NaN            NaN                   81.4800             133.7300           1,398.5900               4.7170               0.6668               0.4432              11.6446               4.4798               8.8550               2.2229              45.5100               4.0712               1.3111              25.2875               9.4696               1.9554             189.0450              42.9910              42.6799               0.3723               1.1789               6.9358\n",
       "1 1999-01-05               1.8944      NaN             NaN                     1.7965               1.6123      NaN                    0.5823              34.9170               7.4495              15.6466               0.7122             324.7000               9.1341      NaN                   250.8000           9,314.5100       NaN            NaN                   81.5300             130.9600           1,373.0100               4.7174               0.6657               0.4432              11.5960               4.4805               8.7745               2.2011              44.7450               4.0245               1.3168              26.5876               9.4025               1.9655             188.7750              42.8480              42.5048               0.3728               1.1790               6.7975\n",
       "2 1999-01-06               1.8820      NaN             NaN                     1.7711               1.6116      NaN                    0.5820              34.8500               7.4452              15.6466               0.7076             324.7200               9.1010      NaN                   250.6700           9,337.6800       NaN            NaN                   81.5400             131.4200           1,359.5400               4.6994               0.6649               0.4420              11.4705               4.4637               8.7335               2.1890              44.8720               4.0065               1.3168              27.4315               9.3050               1.9699             188.7000              42.7780              42.6949               0.3722               1.1743               6.7307\n",
       "3 1999-01-07               1.8474      NaN             NaN                     1.7602               1.6165      NaN                    0.5819              34.8860               7.4431              15.6466               0.7058             324.4000               9.0131      NaN                   250.0900           9,218.7700       NaN            NaN                   81.0600             129.4300           1,337.1600               4.6548               0.6627               0.4413              11.5511               4.4203               8.6295               2.1531              44.4360               4.0165               1.3092              26.9876               9.1800               1.9436             188.8000              42.7650              42.1678               0.3701               1.1632               6.8283\n",
       "4 1999-01-08               1.8406      NaN             NaN                     1.7643               1.6138      NaN                    0.5819              34.9380               7.4433              15.6466               0.7094             324.0000               9.0302      NaN                   250.1500           9,321.6300       NaN            NaN                   80.9900             130.0900           1,366.7300               4.6643               0.6654               0.4419              11.4414               4.4295               8.5900               2.1557              44.2950               4.0363               1.3143              27.2075               9.1650               1.9537             188.8400              42.5600              42.5590               0.3718               1.1659               6.7855"
      ]
     },
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    },
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: center;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>australian_dollar</th>\n",
       "      <th>bulgarian_lev</th>\n",
       "      <th>brazilian_real</th>\n",
       "      <th>canadian_dollar</th>\n",
       "      <th>swiss_franc</th>\n",
       "      <th>chinese_yuan</th>\n",
       "      <th>cypriot_pound</th>\n",
       "      <th>czech_koruna</th>\n",
       "      <th>danish_krone</th>\n",
       "      <th>estonian_kroon</th>\n",
       "      <th>uk_pound</th>\n",
       "      <th>greek_drachma</th>\n",
       "      <th>hong_kong_dollar</th>\n",
       "      <th>croatian_kuna</th>\n",
       "      <th>hungarian_forint</th>\n",
       "      <th>indonesian_rupiah</th>\n",
       "      <th>israeli_shekel</th>\n",
       "      <th>indian_rupee</th>\n",
       "      <th>iceland_krona</th>\n",
       "      <th>japanese_yen</th>\n",
       "      <th>korean_won</th>\n",
       "      <th>lithuanian_litas</th>\n",
       "      <th>latvian_lats</th>\n",
       "      <th>maltese_lira</th>\n",
       "      <th>mexican_peso</th>\n",
       "      <th>malaysian_ringgit</th>\n",
       "      <th>norwegian_krone</th>\n",
       "      <th>new_zealand_dollar</th>\n",
       "      <th>philippine_peso</th>\n",
       "      <th>polish_zloty</th>\n",
       "      <th>romanian_leu</th>\n",
       "      <th>russian_rouble</th>\n",
       "      <th>swedish_krona</th>\n",
       "      <th>singapore_dollar</th>\n",
       "      <th>slovenian_tolar</th>\n",
       "      <th>slovak_koruna</th>\n",
       "      <th>thai_baht</th>\n",
       "      <th>turkish_lira</th>\n",
       "      <th>us_dollar</th>\n",
       "      <th>south_african_rand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2603</th>\n",
       "      <td>2008-12-25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2604</th>\n",
       "      <td>2008-12-26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2605</th>\n",
       "      <td>2008-12-29</td>\n",
       "      <td>2.0595</td>\n",
       "      <td>1.9558</td>\n",
       "      <td>3.3777</td>\n",
       "      <td>1.7408</td>\n",
       "      <td>1.4931</td>\n",
       "      <td>9.7788</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.4550</td>\n",
       "      <td>7.4503</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.9786</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.0599</td>\n",
       "      <td>7.3438</td>\n",
       "      <td>266.6400</td>\n",
       "      <td>15,839.7000</td>\n",
       "      <td>5.4998</td>\n",
       "      <td>68.6360</td>\n",
       "      <td>NaN</td>\n",
       "      <td>128.9800</td>\n",
       "      <td>1,828.4900</td>\n",
       "      <td>3.4528</td>\n",
       "      <td>0.7061</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.1860</td>\n",
       "      <td>4.9660</td>\n",
       "      <td>9.9450</td>\n",
       "      <td>2.4559</td>\n",
       "      <td>67.7400</td>\n",
       "      <td>4.1400</td>\n",
       "      <td>4.0649</td>\n",
       "      <td>41.6925</td>\n",
       "      <td>10.9795</td>\n",
       "      <td>2.0532</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30.1700</td>\n",
       "      <td>49.9380</td>\n",
       "      <td>2.1628</td>\n",
       "      <td>1.4270</td>\n",
       "      <td>13.6136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2606</th>\n",
       "      <td>2008-12-30</td>\n",
       "      <td>2.0435</td>\n",
       "      <td>1.9558</td>\n",
       "      <td>3.3127</td>\n",
       "      <td>1.7331</td>\n",
       "      <td>1.4963</td>\n",
       "      <td>9.6364</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.6300</td>\n",
       "      <td>7.4506</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.9742</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.9261</td>\n",
       "      <td>7.3348</td>\n",
       "      <td>266.3300</td>\n",
       "      <td>15,507.8000</td>\n",
       "      <td>5.3021</td>\n",
       "      <td>67.8530</td>\n",
       "      <td>NaN</td>\n",
       "      <td>127.4000</td>\n",
       "      <td>1,902.4300</td>\n",
       "      <td>3.4528</td>\n",
       "      <td>0.7079</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.3143</td>\n",
       "      <td>4.9040</td>\n",
       "      <td>9.8400</td>\n",
       "      <td>2.4448</td>\n",
       "      <td>67.0400</td>\n",
       "      <td>4.1465</td>\n",
       "      <td>4.0202</td>\n",
       "      <td>41.4035</td>\n",
       "      <td>10.9500</td>\n",
       "      <td>2.0325</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30.1450</td>\n",
       "      <td>48.9980</td>\n",
       "      <td>2.1606</td>\n",
       "      <td>1.4098</td>\n",
       "      <td>13.3931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2607</th>\n",
       "      <td>2008-12-31</td>\n",
       "      <td>2.0274</td>\n",
       "      <td>1.9558</td>\n",
       "      <td>3.2436</td>\n",
       "      <td>1.6998</td>\n",
       "      <td>1.4850</td>\n",
       "      <td>9.4956</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.8750</td>\n",
       "      <td>7.4506</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.9525</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.7858</td>\n",
       "      <td>7.3555</td>\n",
       "      <td>266.7000</td>\n",
       "      <td>15,239.1200</td>\n",
       "      <td>5.2919</td>\n",
       "      <td>67.4370</td>\n",
       "      <td>NaN</td>\n",
       "      <td>126.1400</td>\n",
       "      <td>1,839.1300</td>\n",
       "      <td>3.4528</td>\n",
       "      <td>0.7083</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.2333</td>\n",
       "      <td>4.8048</td>\n",
       "      <td>9.7500</td>\n",
       "      <td>2.4191</td>\n",
       "      <td>65.9300</td>\n",
       "      <td>4.1535</td>\n",
       "      <td>4.0225</td>\n",
       "      <td>41.2830</td>\n",
       "      <td>10.8700</td>\n",
       "      <td>2.0040</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30.1260</td>\n",
       "      <td>48.2850</td>\n",
       "      <td>2.1488</td>\n",
       "      <td>1.3917</td>\n",
       "      <td>13.0667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date      australian_dollar      bulgarian_lev       brazilian_real       canadian_dollar        swiss_franc         chinese_yuan      cypriot_pound     czech_koruna         danish_krone        estonian_kroon          uk_pound        greek_drachma   hong_kong_dollar       croatian_kuna      hungarian_forint     indonesian_rupiah     israeli_shekel        indian_rupee      iceland_krona     japanese_yen          korean_won        lithuanian_litas       latvian_lats      maltese_lira     mexican_peso       malaysian_ringgit     norwegian_krone    new_zealand_dollar     philippine_peso       polish_zloty         romanian_leu        russian_rouble        swedish_krona      singapore_dollar    slovenian_tolar     slovak_koruna          thai_baht          turkish_lira           us_dollar       south_african_rand \n",
       "2603 2008-12-25                  NaN                  NaN                  NaN                  NaN                  NaN                  NaN      NaN                        NaN                  NaN                  NaN                  NaN      NaN                        NaN                  NaN                  NaN                  NaN                  NaN                  NaN      NaN                        NaN                  NaN                  NaN                  NaN      NaN                       NaN                  NaN                  NaN                  NaN                  NaN                  NaN                  NaN                  NaN                  NaN                  NaN       NaN                         NaN                  NaN                  NaN                  NaN                  NaN\n",
       "2604 2008-12-26                  NaN                  NaN                  NaN                  NaN                  NaN                  NaN      NaN                        NaN                  NaN                  NaN                  NaN      NaN                        NaN                  NaN                  NaN                  NaN                  NaN                  NaN      NaN                        NaN                  NaN                  NaN                  NaN      NaN                       NaN                  NaN                  NaN                  NaN                  NaN                  NaN                  NaN                  NaN                  NaN                  NaN       NaN                         NaN                  NaN                  NaN                  NaN                  NaN\n",
       "2605 2008-12-29               2.0595               1.9558               3.3777               1.7408               1.4931               9.7788      NaN                    26.4550               7.4503              15.6466               0.9786      NaN                    11.0599               7.3438             266.6400          15,839.7000               5.4998              68.6360      NaN                   128.9800           1,828.4900               3.4528               0.7061      NaN                   19.1860               4.9660               9.9450               2.4559              67.7400               4.1400               4.0649              41.6925              10.9795               2.0532       NaN                     30.1700              49.9380               2.1628               1.4270              13.6136\n",
       "2606 2008-12-30               2.0435               1.9558               3.3127               1.7331               1.4963               9.6364      NaN                    26.6300               7.4506              15.6466               0.9742      NaN                    10.9261               7.3348             266.3300          15,507.8000               5.3021              67.8530      NaN                   127.4000           1,902.4300               3.4528               0.7079      NaN                   19.3143               4.9040               9.8400               2.4448              67.0400               4.1465               4.0202              41.4035              10.9500               2.0325       NaN                     30.1450              48.9980               2.1606               1.4098              13.3931\n",
       "2607 2008-12-31               2.0274               1.9558               3.2436               1.6998               1.4850               9.4956      NaN                    26.8750               7.4506              15.6466               0.9525      NaN                    10.7858               7.3555             266.7000          15,239.1200               5.2919              67.4370      NaN                   126.1400           1,839.1300               3.4528               0.7083      NaN                   19.2333               4.8048               9.7500               2.4191              65.9300               4.1535               4.0225              41.2830              10.8700               2.0040       NaN                     30.1260              48.2850               2.1488               1.3917              13.0667"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "first_decade = x_rates[x_rates[\"date\"].dt.year < 2009]\n",
    "display(first_decade.head())\n",
    "display(first_decade.tail())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Late 2011\n",
    "An overlay of the Japanese yen and Australian dollar will show if the changes in 2011 are concurrent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x396 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# line graph showing Euro to yen and aus dollar\n",
    "fig, ax = plt.subplots(figsize=(9,5.5))\n",
    "ax.plot(japanese_yen[\"date\"], japanese_yen[\"rolling_mean_30\"], color=\"green\")\n",
    "ax.set_ylabel('Japanese yen', color=\"green\")\n",
    "ax.set(yticks=[])\n",
    "ax2 = ax.twinx()\n",
    "ax2.plot(australian_dollar[\"date\"], australian_dollar[\"rolling_mean_30\"], color=\"blue\")\n",
    "ax2.set_ylabel('Australian dollar', color=\"blue\")\n",
    "ax2.set(yticks=[])\n",
    "ax.set(xlabel='Year')\n",
    "ax.xaxis.set_major_locator(years) # format the x ticks\n",
    "ax.xaxis.set_major_formatter(years_fmt)\n",
    "fmt_three_years = mdates.MonthLocator(interval = 36) # Major ticks every 3 years\n",
    "ax.xaxis.set_major_locator(fmt_three_years)\n",
    "fig.suptitle(\"Euro to Two Traded Currencies\", fontsize=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "days = new_frame\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "ax.plot(new_frame[\"date\"],new_frame[\"chinese_yuan_rolling_30\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# big_list = []\n",
    "# for col in x_rates.columns:\n",
    "#     big_list.append(col)\n",
    "    \n",
    "# big_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: center;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>australian_dollar</th>\n",
       "      <th>bulgarian_lev</th>\n",
       "      <th>brazilian_real</th>\n",
       "      <th>canadian_dollar</th>\n",
       "      <th>swiss_franc</th>\n",
       "      <th>chinese_yuan</th>\n",
       "      <th>cypriot_pound</th>\n",
       "      <th>czech_koruna</th>\n",
       "      <th>danish_krone</th>\n",
       "      <th>estonian_kroon</th>\n",
       "      <th>uk_pound</th>\n",
       "      <th>greek_drachma</th>\n",
       "      <th>hong_kong_dollar</th>\n",
       "      <th>croatian_kuna</th>\n",
       "      <th>hungarian_forint</th>\n",
       "      <th>indonesian_rupiah</th>\n",
       "      <th>israeli_shekel</th>\n",
       "      <th>indian_rupee</th>\n",
       "      <th>iceland_krona</th>\n",
       "      <th>japanese_yen</th>\n",
       "      <th>korean_won</th>\n",
       "      <th>lithuanian_litas</th>\n",
       "      <th>latvian_lats</th>\n",
       "      <th>maltese_lira</th>\n",
       "      <th>mexican_peso</th>\n",
       "      <th>malaysian_ringgit</th>\n",
       "      <th>norwegian_krone</th>\n",
       "      <th>new_zealand_dollar</th>\n",
       "      <th>philippine_peso</th>\n",
       "      <th>polish_zloty</th>\n",
       "      <th>romanian_leu</th>\n",
       "      <th>russian_rouble</th>\n",
       "      <th>swedish_krona</th>\n",
       "      <th>singapore_dollar</th>\n",
       "      <th>slovenian_tolar</th>\n",
       "      <th>slovak_koruna</th>\n",
       "      <th>thai_baht</th>\n",
       "      <th>turkish_lira</th>\n",
       "      <th>us_dollar</th>\n",
       "      <th>south_african_rand</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2608</th>\n",
       "      <td>2009-01-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2609</th>\n",
       "      <td>2009-01-02</td>\n",
       "      <td>1.9884</td>\n",
       "      <td>1.9558</td>\n",
       "      <td>3.2456</td>\n",
       "      <td>1.6942</td>\n",
       "      <td>1.4874</td>\n",
       "      <td>9.4608</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.8250</td>\n",
       "      <td>7.4499</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.9610</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.7472</td>\n",
       "      <td>7.3346</td>\n",
       "      <td>265.4800</td>\n",
       "      <td>15,391.2600</td>\n",
       "      <td>5.2522</td>\n",
       "      <td>67.1250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>126.6400</td>\n",
       "      <td>1,833.0900</td>\n",
       "      <td>3.4528</td>\n",
       "      <td>0.7083</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.1718</td>\n",
       "      <td>4.8080</td>\n",
       "      <td>9.6950</td>\n",
       "      <td>2.3969</td>\n",
       "      <td>65.3100</td>\n",
       "      <td>4.1638</td>\n",
       "      <td>4.0350</td>\n",
       "      <td>40.7819</td>\n",
       "      <td>10.8425</td>\n",
       "      <td>2.0265</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48.2120</td>\n",
       "      <td>2.1380</td>\n",
       "      <td>1.3866</td>\n",
       "      <td>13.0618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2610</th>\n",
       "      <td>2009-01-05</td>\n",
       "      <td>1.9189</td>\n",
       "      <td>1.9558</td>\n",
       "      <td>3.1619</td>\n",
       "      <td>1.6475</td>\n",
       "      <td>1.5060</td>\n",
       "      <td>9.2781</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.7600</td>\n",
       "      <td>7.4488</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.9358</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.5303</td>\n",
       "      <td>7.3026</td>\n",
       "      <td>267.1300</td>\n",
       "      <td>15,076.0200</td>\n",
       "      <td>5.2355</td>\n",
       "      <td>65.8930</td>\n",
       "      <td>NaN</td>\n",
       "      <td>126.8100</td>\n",
       "      <td>1,799.5200</td>\n",
       "      <td>3.4528</td>\n",
       "      <td>0.7070</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.5292</td>\n",
       "      <td>4.7503</td>\n",
       "      <td>9.3950</td>\n",
       "      <td>2.3301</td>\n",
       "      <td>64.0800</td>\n",
       "      <td>4.1360</td>\n",
       "      <td>4.0490</td>\n",
       "      <td>39.5915</td>\n",
       "      <td>10.7075</td>\n",
       "      <td>1.9987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47.4620</td>\n",
       "      <td>2.0897</td>\n",
       "      <td>1.3582</td>\n",
       "      <td>12.8655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2611</th>\n",
       "      <td>2009-01-06</td>\n",
       "      <td>1.8727</td>\n",
       "      <td>1.9558</td>\n",
       "      <td>2.9517</td>\n",
       "      <td>1.5850</td>\n",
       "      <td>1.5018</td>\n",
       "      <td>9.1138</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.4100</td>\n",
       "      <td>7.4530</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.9176</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.3369</td>\n",
       "      <td>7.2835</td>\n",
       "      <td>266.6700</td>\n",
       "      <td>14,665.2000</td>\n",
       "      <td>5.1477</td>\n",
       "      <td>64.8270</td>\n",
       "      <td>NaN</td>\n",
       "      <td>125.8400</td>\n",
       "      <td>1,753.5800</td>\n",
       "      <td>3.4528</td>\n",
       "      <td>0.7070</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.7949</td>\n",
       "      <td>4.6789</td>\n",
       "      <td>9.3850</td>\n",
       "      <td>2.2700</td>\n",
       "      <td>62.5700</td>\n",
       "      <td>4.0200</td>\n",
       "      <td>4.0675</td>\n",
       "      <td>38.8859</td>\n",
       "      <td>10.5675</td>\n",
       "      <td>1.9719</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46.7550</td>\n",
       "      <td>2.0256</td>\n",
       "      <td>1.3332</td>\n",
       "      <td>12.4521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2612</th>\n",
       "      <td>2009-01-07</td>\n",
       "      <td>1.8831</td>\n",
       "      <td>1.9558</td>\n",
       "      <td>2.9977</td>\n",
       "      <td>1.6061</td>\n",
       "      <td>1.5006</td>\n",
       "      <td>9.2908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.1170</td>\n",
       "      <td>7.4522</td>\n",
       "      <td>15.6466</td>\n",
       "      <td>0.9043</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.5398</td>\n",
       "      <td>7.3019</td>\n",
       "      <td>266.1400</td>\n",
       "      <td>14,750.5800</td>\n",
       "      <td>5.2685</td>\n",
       "      <td>66.3640</td>\n",
       "      <td>NaN</td>\n",
       "      <td>126.7700</td>\n",
       "      <td>1,780.1300</td>\n",
       "      <td>3.4528</td>\n",
       "      <td>0.7069</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.2717</td>\n",
       "      <td>4.7589</td>\n",
       "      <td>9.3915</td>\n",
       "      <td>2.2717</td>\n",
       "      <td>63.1500</td>\n",
       "      <td>3.9747</td>\n",
       "      <td>4.0995</td>\n",
       "      <td>39.9068</td>\n",
       "      <td>10.5763</td>\n",
       "      <td>1.9990</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47.3510</td>\n",
       "      <td>2.0672</td>\n",
       "      <td>1.3595</td>\n",
       "      <td>12.7150</td>\n",
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      ],
      "text/plain": [
       "        date      australian_dollar      bulgarian_lev       brazilian_real       canadian_dollar        swiss_franc         chinese_yuan      cypriot_pound     czech_koruna         danish_krone        estonian_kroon          uk_pound        greek_drachma   hong_kong_dollar       croatian_kuna      hungarian_forint     indonesian_rupiah     israeli_shekel        indian_rupee      iceland_krona     japanese_yen          korean_won        lithuanian_litas       latvian_lats      maltese_lira     mexican_peso       malaysian_ringgit     norwegian_krone    new_zealand_dollar     philippine_peso       polish_zloty         romanian_leu        russian_rouble        swedish_krona      singapore_dollar    slovenian_tolar  slovak_koruna       thai_baht          turkish_lira           us_dollar       south_african_rand \n",
       "2608 2009-01-01                  NaN                  NaN                  NaN                  NaN                  NaN                  NaN      NaN                        NaN                  NaN                  NaN                  NaN      NaN                        NaN                  NaN                  NaN                  NaN                  NaN                  NaN      NaN                        NaN                  NaN                  NaN                  NaN      NaN                       NaN                  NaN                  NaN                  NaN                  NaN                  NaN                  NaN                  NaN                  NaN                  NaN       NaN             NaN                        NaN                  NaN                  NaN                  NaN\n",
       "2609 2009-01-02               1.9884               1.9558               3.2456               1.6942               1.4874               9.4608      NaN                    26.8250               7.4499              15.6466               0.9610      NaN                    10.7472               7.3346             265.4800          15,391.2600               5.2522              67.1250      NaN                   126.6400           1,833.0900               3.4528               0.7083      NaN                   19.1718               4.8080               9.6950               2.3969              65.3100               4.1638               4.0350              40.7819              10.8425               2.0265       NaN             NaN                    48.2120               2.1380               1.3866              13.0618\n",
       "2610 2009-01-05               1.9189               1.9558               3.1619               1.6475               1.5060               9.2781      NaN                    26.7600               7.4488              15.6466               0.9358      NaN                    10.5303               7.3026             267.1300          15,076.0200               5.2355              65.8930      NaN                   126.8100           1,799.5200               3.4528               0.7070      NaN                   18.5292               4.7503               9.3950               2.3301              64.0800               4.1360               4.0490              39.5915              10.7075               1.9987       NaN             NaN                    47.4620               2.0897               1.3582              12.8655\n",
       "2611 2009-01-06               1.8727               1.9558               2.9517               1.5850               1.5018               9.1138      NaN                    26.4100               7.4530              15.6466               0.9176      NaN                    10.3369               7.2835             266.6700          14,665.2000               5.1477              64.8270      NaN                   125.8400           1,753.5800               3.4528               0.7070      NaN                   17.7949               4.6789               9.3850               2.2700              62.5700               4.0200               4.0675              38.8859              10.5675               1.9719       NaN             NaN                    46.7550               2.0256               1.3332              12.4521\n",
       "2612 2009-01-07               1.8831               1.9558               2.9977               1.6061               1.5006               9.2908      NaN                    26.1170               7.4522              15.6466               0.9043      NaN                    10.5398               7.3019             266.1400          14,750.5800               5.2685              66.3640      NaN                   126.7700           1,780.1300               3.4528               0.7069      NaN                   18.2717               4.7589               9.3915               2.2717              63.1500               3.9747               4.0995              39.9068              10.5763               1.9990       NaN             NaN                    47.3510               2.0672               1.3595              12.7150"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "late_2000s = x_rates[x_rates[\"date\"].dt.year.between(2009,2013)]\n",
    "late_2000s.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Volatility\n",
    "Determining volatility of the eight currencies for the past two decades illustrates part of the story of the twenty-first century."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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XN3JJs6jLa9aeB/wccGOSG5q21zMo0nYkuQi4E3gpQFXdnGQHcAuDb7UXV9XDHcYnteY1IKvXpK+5TbIZ2Aywfv36jqLWcvELqJZDZ8VaVf0Vo69DAzhzgX0uBS7tKiZJWoz519wOThiM3nRE2wHX3MLgUg5gG8CmTZtGbiNJw5zBQJJG6OKaW0laCos1SZqnxTW3cOA1txckeUySk/GaW0kTtCzjrEnSCuM1t5J6w2JNkubxmltJfeJpUEmSpB6zWJMkSeoxizVJkqQes1iTJEnqMW8wkCSpBWcr0LR4ZE2SJKnHPLKmzvgtVJKmb1Qudn7jlcUja5IkST1msSZJktRjFmuSJEk95jVr0hJ4DYgkabl4ZE2SJKnHLNYkSZJ6zNOgkiStMvMv5fAyjn7zyJokSVKPeWRNkqR5HNRbfWKxpokwsXmHqCSpG54GlSRJ6jGLNUmSpB6zWJMkSeoxr1mTJK16XnerPrNYkyRplfMGqX6zWJM65MCTUv94FK0dC7j+sFjTkpjsJElaHhZrOiQLM0mSpqd3xVqSs4C3A2uA91TV1imHtOpYnHWnze/W0wwrl/mrn8xpk+OlHdPRq2ItyRrg94EXAnuBLyXZWVW3TDcyafl4ncjKZP5afv6taLXoVbEGnAbsrqqvAyS5HDgPMNlNgN8uVy7/U1oRzF8TtNR8ZZ5bXkv9fZu/FqdvxdoJwF1Dr/cC/3J4gySbgc3Ny39KctsyxTbfscDfTulnT9os9QVWSX/y5ilEMr5JfDY/MolAOnDI/AUTy2F9/zdufOOZ+fg6zl99/v0tKX/1rVjLiLZ6xIuqbcC25QlnYUl2VdWmaccxCbPUF7A/fTZLfRnhkPkLJpPD+v57NL7xGN94+h7fUvRtuqm9wElDr08E7p5SLJK0GOYvSZ3oW7H2JWBjkpOTPBq4ANg55ZgkqQ3zl6RO9Oo0aFU9lOSXgc8xuPX9fVV185TDWsjUT8VO0Cz1BexPn81SXx5hmfNX33+Pxjce4xtP3+NbtFQdcEmFJEmSeqJvp0ElSZI0xGJNkiSpxyzWDiLJMUmuSHJ783z0AtudleS2JLuTbBmx/teTVJJju496tHH7kuR3knwtyVeTfDzJUcsW/CFiG1qfJO9o1n81yalt952GpfYnyUlJ/jzJrUluTvKa5Y/+QON8Ps36NUm+nORTyxd1P00i9yT5lWbdzUl+u2/xNes7yY19zXd9z2F9z0mrOsdUlY8FHsBvA1ua5S3Am0dsswb4a+BJwKOBrwCnDK0/icEFx98Ajl2pfQF+CjisWX7zqP07jv+gv+dmm7OBzzIY7+p04Jq2+07h8xinP+uAU5vlJwD/ZyX3Z2j9rwIfAj41zb704TGBv9fnA1cCj2leH9en+Jr1neXGPua7vuewvuek1Z5jPLJ2cOcB25vl7cD5I7b5/hQzVfUgMDfFzJy3Ar/BiMExl9lYfamqz1fVQ812VzMYQ2o5Her3TPP6shq4GjgqybqW+y63JfenqvZV1fUAVXU/cCuD0fOnaZzPhyQnAucA71nOoHts3NzzKmBrVT0AUFX39iw+6DY39jHf9T2H9T0nreocY7F2cMdX1T6A5vm4EduMmmLmBIAk5wLfrKqvdB1oC2P1ZZ6fZ/DtZTm1iW2hbdr2azmN05/vS7IBeDZwzeRDXJRx+/M2Bv9xf6+j+Faacf9enwL8myTXJPmLJM/tU3zLkBv7mO/6nsP6npNWdY7p1Thr05DkSuCHR6x6Q9u3GNFWSY5o3uOnlhrbYnXVl3k/4w3AQ8AHFxfd2NpM5bPQNq2mAVpm4/RnsDJ5PPBR4LVVdd8EY1uKJfcnyYuBe6vquiRnTDqwvur47/Uw4GgGp4KeC+xI8qRqzgVNM75J5cYVmO/6nsP6npNWdY5Z9cVaVf3kQuuS3DN3iLc5lDrqVMJCU8w8GTgZ+EqSufbrk5xWVX8zsQ4M6bAvc+9xIfBi4MzFJP0JaTOVz0LbPLrFvsttnP6Q5FEMkuIHq+pjHcbZ1jj9+Y/AuUnOBh4LHJnkA1X1sg7jnbqO/173Ah9r/k6vTfI9BpNb7+9BfBPJjSsw3/U9h/U9J63uHDPpi+Bm6QH8Do+8SPW3R2xzGPB1Bsln7qLHp4/Ybg/TvcFgrL4AZwG3AGunFP8hf88MrkcYvrj02sV8RiuoPwEuA942zT5Mqj/ztjmDFXjxbwe/z3H/Xl8J/Pdm+SkMTg2lL/HN227iubGP+a7vOazvOWm155ipB9DnB/AvgKuA25vnY5r2JwKfGdrubAZ3v/w18IYF3mviCWk5+wLsbhL+Dc3jD6bQhwNiY/Cf0iub5QC/36y/Edi0mM9opfQH+HEGh/+/OvR5nL1S+zPvPVZkIu3gdznu3+ujgQ8ANwHXAy/oU3zz3mviubGv+a7vOazvOWk15xinm5IkSeox7waVJEnqMYs1SZKkHrNYkyRJ6jGLNUmSpB6zWJMkSeoxizVJkqQes1iTJEnqMYs1SZKkHrNYkyRJ6jGLNUmSpB6zWJMkSeoxizVJkqQes1iTJEnqMYs1SZKkHrNYkyRJ6jGLNUmSpB47bNoBjOPYY4+tDRs2TDsMScvouuuu+9uqWjvtOCbBHCatLkvNXyu6WNuwYQO7du2adhiSllGSb0w7hkkxh0mry1Lzl6dBJUmSesxiTZIkqccs1iRJknrMYk2SJKnHLNYkSZJ6zGJNkiSpx1b00B1aHhu2fPqAtj1bz5lCJJK08phDNS6PrEmSJPWYxZokSVKPWaxJkiT1mMWaJElSj1msSZIk9ZjFmiRJUo9ZrEmSJPWY46xJkrTM5o+95rhrOhiPrEmSJPWYxZokSVKPWaxJkiT1mMWapFUryfuS3JvkpqG2Y5JckeT25vnooXWXJNmd5LYkLxpqf06SG5t170iS5e6LpNllsSZpNftj4Kx5bVuAq6pqI3BV85okpwAXAE9v9nlnkjXNPu8CNgMbm8f895SkJfNuUC2JdzJpFlTVXybZMK/5POCMZnk78AXgdU375VX1AHBHkt3AaUn2AEdW1RcBklwGnA98tuPwJa0SHlmTpEc6vqr2ATTPxzXtJwB3DW23t2k7oVme3z5Sks1JdiXZtX///okGLmk2WaxJUjujrkOrg7SPVFXbqmpTVW1au3btxIKTNLss1iTpke5Jsg6geb63ad8LnDS03YnA3U37iSPaJWkiLNYk6ZF2Ahc2yxcCnxxqvyDJY5KczOBGgmubU6X3Jzm9uQv05UP7SNLYvMFA0qqV5E8Y3ExwbJK9wBuBrcCOJBcBdwIvBaiqm5PsAG4BHgIurqqHm7d6FYM7Sw9ncGOBNxdImphOi7Uk/xX4BQbXb9wIvAI4AvhTYAOwB/iZqvr7ZvtLgIuAh4FXV9XnuoxP0upWVT+7wKozF9j+UuDSEe27gGdMMDRJ+r7OToMmOQF4NbCpqp4BrGEwRtFSxjCSJElalbq+Zu0w4PAkhzE4onY3g7GKtjfrtzMYjwiGxjCqqjuA3cBpHccnSZLUa50Va1X1TeB3GVzzsQ/4x6r6PIsfw0iSJGnV6vI06NEMjpadDDwReFySlx1slxFtB4xV5ICSkiRpNenyNOhPAndU1f6q+i7wMeBfs/gxjB7BASUlSdJq0mWxdidwepIjmrGHzgRuZZFjGHUYnyRJUu91NnRHVV2T5CPA9QzGJPoysA14PIsfw0iSJGlV6nSctap6I4NBJoc9wCLHMJIkSVqtnG5KkiSpxyzWJEmSesy5QXWADVs+Pe0QJElSwyNrkiRJPWaxJkmS1GMWa5IkST1msSZJktRjFmuSJEk9ZrEmSZLUYxZrkiRJPWaxJkmS1GMOiitJIyT5r8AvAAXcCLwCOAL4U2ADsAf4mar6+2b7S4CLgIeBV1fV55Y/ak2bg4qrCx5Zk6R5kpwAvBrYVFXPANYAFwBbgKuqaiNwVfOaJKc0658OnAW8M8maacQuafZYrEnSaIcBhyc5jMERtbuB84DtzfrtwPnN8nnA5VX1QFXdAewGTlvecCXNKos1SZqnqr4J/C5wJ7AP+Meq+jxwfFXta7bZBxzX7HICcNfQW+xt2iRpbBZrkjRPkqMZHC07GXgi8LgkLzvYLiPaaoH33pxkV5Jd+/fvHz9YSTPPYk2SDvSTwB1Vtb+qvgt8DPjXwD1J1gE0z/c22+8FThra/0QGp00PUFXbqmpTVW1au3ZtZx2QNDss1iTpQHcCpyc5IkmAM4FbgZ3Ahc02FwKfbJZ3AhckeUySk4GNwLXLHLOkGeXQHZI0T1Vdk+QjwPXAQ8CXgW3A44EdSS5iUNC9tNn+5iQ7gFua7S+uqoenErykmWOxJkkjVNUbgTfOa36AwVG2UdtfClzadVySVh+LNU3EqIEg92w9ZwqRSJI0W7xmTZIkqcdaFWtJntF1IJI0DvOUpFnV9sjaHyS5Nsl/SXJUlwFJ0hKZpyTNpFbFWlX9OPCfGYwjtCvJh5K8sNPIJGkRzFOSZlXrGwyq6vYkvwnsAt4BPLsZf+j1VfWxUfs0327fAzyDwWjePw/cBvwpsAHYA/xMVf19s/0lwEXAw8Crq+pzS+qVpFVpKXlK6gNv0tLBtL1m7ceSvJXBoJAvAH66qn60WX7rQXZ9O/BnVfU04JnN/luAq6pqI3BV85okpwAXAE8HzgLemWTNknoladUZI09JUq+1vWbtfzIYHPKZVXVxVV0PUFV3A785aockRwI/Aby32fbBqvoHBvPtbW822w6c3yyfB1xeVQ9U1R3AbuC0xXZI0qq16DwlSStB29OgZwPfmRuRO8kPAY+tqn+uqvcvsM+TgP3AHyV5JnAd8Brg+KraB1BV+5Ic12x/AnD10P57m7ZHSLIZ2Aywfv36luFLWgWWkqckqffaHlm7Ejh86PURTdvBHAacCryrqp4NfJvmlOcCMqKtDmhwEmRJoy0lT0lS77Ut1h5bVf8096JZPuIQ++wF9lbVNc3rjzAo3u5Jsg6geb53aPuThvY/Ebi7ZXyStJQ8JUm917ZY+3aSU+deJHkO8J2D7VBVfwPcleSpTdOZDCY53glc2LRdCHyyWd4JXJDkMUlOBjYC17aMT5IWnackaSVoe83aa4EPJ5k70rUO+E8t9vsV4INJHg18HXgFgwJxR5KLgDuBlwJU1c1JdjAo6B4CLp679kSSWngtS8tTktRrrYq1qvpSkqcBT2VwbdnXquq7Lfa7Adg0YtWZC2x/KXBpm5gkadhS85Qk9V3rQXGB5zIYyPYwBgNNUlWXdRKVJC2NeUrSzGlVrCV5P/Bk4AYGswvA4E5Nk6CkXjBPSZpVbY+sbQJOqaoDhtKQpJ4wT0maSW3vBr0J+OEuA5GkMZmnJM2ktkfWjgVuSXIt8MBcY1Wd20lUkrR45ilJM6ltsfamLoOQpAl407QDkKQutDoNWlV/AewBHtUsf4nBhMmS1AuTzlNJjkrykSRfS3Jrkn+V5JgkVyS5vXk+emj7S5LsTnJbkheN3SFJarQq1pL8IoPpov6waToB+ERHMUnSonWQp94O/FlVPQ14JnArg/mNr6qqjcBVzWuSnAJcADwdOAt4Z5I1Y/xsSfq+tjcYXAw8D7gPoKpuB47rKihJWoKJ5akkRwI/Aby3ea8Hq+ofgPOA7c1m24Hzm+XzgMur6oGqugPYDZy2pF5I0jxti7UHqurBuRdJDmMwfpEk9cUk89STgP3AHyX5cpL3JHkccHxV7QNonueKwROAu4b239u0HSDJ5iS7kuzav3//EsOTtJq0Ldb+IsnrgcOTvBD4MPC/ugtLkhZtknnqMOBU4F1V9Wzg2zSnPBeQEW0jC8Wq2lZVm6pq09q1a5cYnqTVpO3doFuAi4AbgV8CPgO8p6ugNBs2bPn0AW17tp4zhUi0SkwyT+0F9lbVNc3rjzTvf0+SdVW1L8k64N6h7U8a2v9E4G4kaQLaTuT+PeDdzUOSemeSeaqq/ibJXUmeWlW3AWcCtzSPC4GtzfMnm112Ah9K8hbgicBG4Npx45AkaD836B2MOKRfVU+aeESStAQd5KlfAT6Y5NHA14FXMLh0ZEeSi4A7gZc2P+PmJDsYFHMPARdX1cOj31aSFmcxc4POeSyDBHXM5MORpCWbaJ6qqhvmveecMxfY/lLg0qX+PElaSNtBcb819PhmVb0NeEG3oUlSe+YpSbOq7WnQU4de/hCDb5tP6CQiLatRNwFIK5F5StKsansa9PeGlh9iMKXLz0w8GklaOvOUpJnU9m7Q53cdiCSNwzwlaVa1PQ36qwdbX1VvmUw4krQ05ilJs2oxd4M+l8FYQgA/Dfwlj5xeRZKmyTwlaSa1LdaOBU6tqvsBkrwJ+HBV/UJXgUnSIpmnJM2ktnODrgceHHr9ILBh4tFI0tKZpyTNpLZH1t4PXJvk4wxGCH8JcFlnUUnS4pmnJM2ktoPiXspgqpW/B/4BeEVV/Y82+yZZk+TLST7VvD4myRVJbm+ejx7a9pIku5PcluRFi+6NpFVrnDwlSX3W9jQowBHAfVX1dmBvkpNb7vca4Nah11uAq6pqI3BV85okpwAXAE8HzgLemWTNIuKTpKXmKUnqrbZDd7yRwZ1WTwX+CHgU8AHgeYfY70TgHAbz5c3dVn8ecEazvB34AvC6pv3yqnoAuCPJbuA04IuteyNp1VpqnpLG4SwwWg5tj6y9BDgX+DZAVd1Nu2lc3gb8BvC9obbjq2pf8z77gOOa9hN45C32e5s2SWpjqXlKknqtbbH2YFUVg4t2SfK4Q+2Q5MXAvVV1XcufkRFtNeJ9NyfZlWTX/v37W761pFVg0XlKklaCtsXajiR/CByV5BeBK4F3H2Kf5wHnJtkDXA68IMkHgHuSrANonu9ttt8LnDS0/4nA3fPftKq2VdWmqtq0du3aluFLWgWWkqckqfcOWawlCfCnwEeAjzK4HuS/VdX/e7D9quqSqjqxqjYwuHHgf1fVyxiMLn5hs9mFwCeb5Z3ABUke01wUvBG4dvFdkrTaLDVPSdJKcMgbDKqqknyiqp4DXDGBn7mVwTfgi4A7gZc2P+fmJDuAW4CHgIur6uEJ/DxJM66DPCVJvdF2UNyrkzy3qr60lB9SVV9gcNcnVfUt4MwFtruUwZ2jkrRYY+UpSeqrtsXa84FXNteffZvBzQBVVT/WVWCStEjmKc2U+cOC7Nl6zpQi0bQdtFhLsr6q7gT+3TLFI0mL0mWeagbm3gV8s6penOQYBtfGbQD2AD9TVX/fbHsJcBHwMPDqqvrcpOORtDod6gaDTwBU1TeAt1TVN4YfnUcnSYf2CegsTzkDi6SpO1SxNjz22ZO6DESSlqiTPDU0A8t7hprPYzDzCs3z+UPtl1fVA1V1BzA3A4skje1QxVotsCxJfdFVnnobzsAiqQcOdYPBM5Pcx+Cb6+HNMvzgwt0jO41Okg5t4nlqeAaWJGe02WVE28jCMclmYDPA+vXrFxuapFXooMVaVXnNhaRe6yhPzc3AcjbwWODI4RlYqmrfUmZgaeLdBmwD2LRpk2csJB1S2+mmJGnVcAYWSX3Sdpw1SZIzsEiaAos1SToIZ2CRNG0Wa6vI/NGwJUlS/1msaVk5fYokSYvjDQaSJEk9ZrEmSZLUYxZrkiRJPWaxJkmS1GMWa5IkST1msSZJktRjFmuSJEk9ZrEmSZLUYxZrkiRJPWaxJkmS1GMWa5IkST1msSZJktRjFmuSJEk91lmxluSkJH+e5NYkNyd5TdN+TJIrktzePB89tM8lSXYnuS3Ji7qKTZIkaaXo8sjaQ8CvVdWPAqcDFyc5BdgCXFVVG4Grmtc06y4Ang6cBbwzyZoO45MkSeq9w7p646raB+xrlu9PcitwAnAecEaz2XbgC8DrmvbLq+oB4I4ku4HTgC92FaMkSW1t2PLpaYegVWpZrllLsgF4NnANcHxTyM0VdMc1m50A3DW0296mbf57bU6yK8mu/fv3dxq3JEnStHVerCV5PPBR4LVVdd/BNh3RVgc0VG2rqk1VtWnt2rWTClOSJKmXOi3WkjyKQaH2war6WNN8T5J1zfp1wL1N+17gpKHdTwTu7jI+SRrFG6Qk9Uln16wlCfBe4NaqesvQqp3AhcDW5vmTQ+0fSvIW4InARuDaruJbDby+QlqyuRukrk/yBOC6JFcA/zeDG6S2JtnC4Aap1827QeqJwJVJnlJVD08pfkkzpMsja88Dfg54QZIbmsfZDIq0Fya5HXhh85qquhnYAdwC/BlwsYlO0jRU1b6qur5Zvh8YvkFqe7PZduD8Zvn7N0hV1R3A3A1SkjS2Lu8G/StGX4cGcOYC+1wKXNpVTOqfUUf/9mw9ZwqRSKMd7AapJMM3SF09tNvIG6Sa99sMbAZYv359R1FrFpkvVy9nMJCkBUz6BinwJilJi2exJkkjeIOUpL6wWJOkeVrcIAUH3iB1QZLHJDkZb5CSNEGdXbMmSSvY3A1SNya5oWl7PYMbonYkuQi4E3gpDG6QSjJ3g9RDeIOUpAmyWJOkebxBSlKfeBpUkiSpxyzWJEmSesxiTZIkqce8Zk2SpHmcrk99YrEmSdIK5awGq4PFmnrH5CNJ0g9YrM0ID9lLkjSbvMFAkiSpxyzWJEmSesxiTZIkqccs1iRJknrMYk2SJKnHLNYkSZJ6zKE7tCLMH5rEcdckTdIsDX9kvpw9HlmTJEnqMY+srVCz9C1QkiQtzGJtBbAwO5BTUklSO+bLlc/ToJIkST1msSZJktRjvTsNmuQs4O3AGuA9VbV1yiEtK095SivXas9fK4V51jtGV5peFWtJ1gC/D7wQ2At8KcnOqrplupFpJTD5aJrMX/1lcaaVrlfFGnAasLuqvg6Q5HLgPGAmkp0XeS6vtgnaz0ATMtP5q4/MqZNjvuy3vhVrJwB3Db3eC/zLKcWyoEl+S/Mb3/R1+RnMT2z+5zLTVkT+WimW+ndpTu3WpH6/5r3F6VuxlhFt9YgNks3A5ublPyW5rfOoluZY4G+nHUSH7F8LefNktunASv78fmTaASzgkPkLOsthffs8jefg+hYPLHNMLfJe335Hk4pnSfmrb8XaXuCkodcnAncPb1BV24BtyxnUUiTZVVWbph1HV+zfyjbr/ZuSQ+Yv6CaH9e3zNJ6D61s80L+YjOeR+jZ0x5eAjUlOTvJo4AJg55RjkqQ2zF+SOtGrI2tV9VCSXwY+x+DW9/dV1c1TDkuSDsn8JakrvSrWAKrqM8Bnph3HBPT+VO2Y7N/KNuv9m4op5q++fZ7Gc3B9iwf6F5PxDEnVAde/SpIkqSf6ds2aJEmShlisjSHJMUmuSHJ783z0AtudleS2JLuTbBlq/50kX0vy1SQfT3LUsgW/gIViHVqfJO9o1n81yalt9+2DpfYvyUlJ/jzJrUluTvKa5Y/+0Mb5/Jr1a5J8Ocmnli9qtTFuvmnW/Uqz7uYkvz3teJr1v56kkhw7zXgmlY/7lkP7lvP6lqPG/LyOSvKR5t/NrUn+1SRiGqmqfCzxAfw2sKVZ3gK8ecQ2a4C/Bp4EPBr4CnBKs+6ngMOa5TeP2n+Z+7NgrEPbnA18lsGYUqcD17Tdd9qPMfu3Dji1WX4C8H9mqX9D638V+BDwqWn3x8cBn++4+eb5wJXAY5rXx00znmb9SQxuyPgGcOyUfz9j5+O+5dC+5by+5ahx4wG2A7/QLD8aOGrcmBZ6eGRtPOcx+LBons8fsc33p6CpqgeBuSloqKrPV9VDzXZXMxiXaZoWjHXIecBlNXA1cFSSdS33nbYl96+q9lXV9QBVdT9wK4MR6/tknM+PJCcC5wDvWc6g1dpY+QZ4FbC1qh4AqKp7pxwPwFuB32DE4MHLHc+E8nHfcmjfcl7fctSS40lyJPATwHsBqurBqvqHCcV1AIu18RxfVfsAmufjRmwzagqaUf/gf55B9T5NbWJdaJu2/Zymcfr3fUk2AM8Grpl8iGMZt39vY/Af5/c6ik/jGTffPAX4N0muSfIXSZ47zXiSnAt8s6q+MmYcE4lnnqXm477l0L7lvL7lqHHieRKwH/ij5rTse5I8bkJxHaB3Q3f0TZIrgR8eseoNbd9iRNv8KbTeADwEfHBx0U1cm+lyFtqm1VQ7UzZO/wYrk8cDHwVeW1X3TTC2SVhy/5K8GLi3qq5LcsakA1M7Heebw4CjGZzKeS6wI8mTqjmHs5zxJDmieY+favk+ncYz72eMk4/7lkP7lvP6lqPG+f0cBpwK/EpVXZPk7QxOv/8/E4rtESzWDqGqfnKhdUnumTtc3BymHXVa4aBT0CS5EHgxcObBkuYyaTNdzkLbPLrFvtM2Tv9I8igGSeuDVfWxDuNcqnH69x+Bc5OcDTwWODLJB6rqZR3Gq3k6zjd7gY81eebaJN9jMN/h/inE82TgZOArSebar09yWlX9zRTimXuPcfNx33Jo33Je33LUOPEUsLeq5o42foRBsdaNSVz4tlofwO/wyAtaf3vENocBX2eQmOYuYHx6s+4s4BZg7bT7cqhYh7Y5h0debHlt232n/RizfwEuA9427X500b9525yBNxj07jGBfPNK4L83y09hcGon04pn3nZ7GP8Gg6nn477l0L7lvL7lqHHjAf4/4KnN8puA35nU7+qAWLt649XwAP4FcBVwe/N8TNP+ROAzQ9udzeBOmr8G3jDUvrtJmDc0jz/oQZ8OiJVBkn9lsxzg95v1NwKbDtXPPj2W2j/gxxl8k/rq0Od19rT7M8nPb+g9JpIIfUz8sx033zwa+ABwE3A98IJpxjPvvfYwfrHWi3zctxzat5zXtxw15uf1LGBX8zv6BHD0JGIa9XAGA0mSpB7zblBJkqQes1iTJEnqMYs1SZKkHrNYkyRJ6jGLNUmSpB6zWJMkSeoxizVJkqQes1iTJEnqMYs1SZKkHrNYkyRJ6jGLNUmSpB6zWJMkSeoxizVJkqQes1iTJEnqMYs1SZKkHrNYkyRJ6jGLNUmSpB47bNoBjOPYY4+tDRs2TDsMScvouuuu+9uqWjvtOCbBHCatLkvNXyu6WNuwYQO7du2adhiSllGSb0w7hkkxh0mry1Lzl6dBJUmSesxiTZIkqccs1iRJknrMYk2SJKnHLNYkSZJ6zGJNkiSpx1b00B1avTZs+fQBbXu2njOFSCRJB2O+Hp9H1iStWknel+TeJDcNtb0pyTeT3NA8zh5ad0mS3UluS/KiofbnJLmxWfeOJFnuvkiaXRZrklazPwbOGtH+1qp6VvP4DECSU4ALgKc3+7wzyZpm+3cBm4GNzWPUe0rSknRarCX5r0luTnJTkj9J8tgkxyS5IsntzfPRQ9uP/NYqSV2oqr8E/q7l5ucBl1fVA1V1B7AbOC3JOuDIqvpiVRVwGXB+JwFLWpU6K9aSnAC8GthUVc8A1jD4VroFuKqqNgJXNa8P9a1VkpbTLyf5anOadO4L5QnAXUPb7G3aTmiW57dL0kR0fRr0MODwJIcBRwB3M/h2ur1Zv50ffAMd+a214/gkab53AU8GngXsA36vaR91HVodpH2kJJuT7Eqya//+/WOGKmk16KxYq6pvAr8L3Mkg4f1jVX0eOL6q9jXb7AOOa3ZZ6FvrI5joJHWpqu6pqoer6nvAu/nBl8a9wElDm57I4Avo3mZ5fvtC77+tqjZV1aa1a9dONnhJM6nL06BHMzhadjLwROBxSV52sF1GtB3w7dREJ6lLzTVoc14CzN0puhO4IMljkpzM4EaCa5svnfcnOb25C/TlwCeXNWhJM63LcdZ+ErijqvYDJPkY8K+Be5Ksq6p9TVK8t9l+oW+t0shxeqRxJfkT4Azg2CR7gTcCZyR5FoMvi3uAXwKoqpuT7ABuAR4CLq6qh5u3ehWDO0sPBz7bPCRpIros1u4ETk9yBPAd4ExgF/Bt4EJga/M89w10J/ChJG9hcCRuI3Bth/FJWuWq6mdHNL/3INtfClw6on0X8IwJhiZJ39dZsVZV1yT5CHA9g2+hXwa2AY8HdiS5iEFB99Jm+4N9a5UkSVqVOp1uqqreyOC0wrAHGBxlG7X9yG+tkiRJq5Vzg0qSpInxGuPJc7opSZKkHrNYkyRJ6jGLNUmSpB6zWJMkSeoxizVJkqQes1iTJEnqMYs1SZKkHrNYkyRJ6jGLNUmSpB6zWJMkSeoxizVJkqQes1iTJEnqMYs1SZKkHrNYkyRJ6jGLNUmrVpL3Jbk3yU1Dbb+T5GtJvprk40mOato3JPlOkhuaxx8M7fOcJDcm2Z3kHUkyhe5ImlEWa5JWsz8GzprXdgXwjKr6MeD/AJcMrfvrqnpW83jlUPu7gM3AxuYx/z0lackOm3YA0nwbtnx62iFolaiqv0yyYV7b54deXg38x4O9R5J1wJFV9cXm9WXA+cBnJxqspFXLI2uStLCf55FF18lJvpzkL5L8m6btBGDv0DZ7m7aRkmxOsivJrv37908+Ykkzx2JNkkZI8gbgIeCDTdM+YH1VPRv4VeBDSY4ERl2fVgu9b1Vtq6pNVbVp7dq1kw5b0gzyNKgkzZPkQuDFwJlVVQBV9QDwQLN8XZK/Bp7C4EjaiUO7nwjcvbwRS5plHlmTpCFJzgJeB5xbVf881L42yZpm+UkMbiT4elXtA+5PcnpzF+jLgU9OIXRJM8oja5JWrSR/ApwBHJtkL/BGBnd/Pga4ohmB4+rmzs+fAP57koeAh4FXVtXfNW/1KgZ3lh7O4Bo3by6QNDEWa5JWrar62RHN711g248CH11g3S7gGRMMTZK+z9OgkiRJPWaxJkmS1GMWa5IkST1msSZJktRjnRZrSY5K8pFmUuRbk/yrJMckuSLJ7c3z0UPbX9JMhHxbkhd1GZskSdJK0PWRtbcDf1ZVTwOeCdwKbAGuqqqNwFXNa5KcAlwAPJ3BJMjvnBvTSJIkabXqrFhrpmH5CZrb4Kvqwar6B+A8YHuz2XYGEx7TtF9eVQ9U1R3AbuC0ruKTJElaCbo8svYkYD/wR83Ex+9J8jjg+GbEb5rn45rtTwDuGtr/oJMhS5IkrQZdFmuHAacC72omPv42zSnPBbSaDDnJ5iS7kuzav3//ZCKVJEnqqS5nMNgL7K2qa5rXH2FQrN2TZF1V7UuyDrh3aPuThvYfORlyVW0DtgFs2rTpgGJOq9eGLZ9+xOs9W8+ZUiSSJE1OZ0fWqupvgLuSPLVpOhO4BdgJXNi0XcgPJjzeCVyQ5DFJTmYwSfK1XcUnSZK0EnQ9N+ivAB9M8mjg68ArGBSIO5JcBNwJvBSgqm5OsoNBQfcQcHFVPdxxfJIkSb3WabFWVTcAm0asOnOB7S8FLu0yJkmSpJXEGQwkSZJ6zGJNkiSpx1oVa0me0XUgkjQO85SkWdX2yNofJLk2yX9JclSXAUnSEi06TyV5X5J7k9w01Lbo+YuTPCfJjc26dyQZNW6kJC1Jq2Ktqn4c+M8MxkHbleRDSV7YaWSStAhLzFN/zGAu4mFLmb/4XcBmBkMObRzxnpK0ZK2vWauq24HfBF4H/FvgHUm+luTfdxWcJC3GYvNUVf0l8Hfzmhc1f3EzuPeRVfXFqirgsqF9JGlsba9Z+7EkbwVuBV4A/HRV/Wiz/NYO45OkViaYpxY7f/EJzfL8dkmaiLbjrP1P4N3A66vqO3ONVXV3kt/sJDJJWpyu89RC8xe3mtf4+2+SbGZwypT169dPICxJs65tsXY28J25GQWS/BDw2Kr656p6f2fRSVJ7k8pTi52/eG+zPL99JOc3lrRYba9ZuxI4fOj1EU2bJPXFpPLUouYvbk6V3p/k9OYu0JcP7SNJY2t7ZO2xVfVPcy+q6p+SHNFRTJK0FIvOU0n+BDgDODbJXuCNwFYWP3/xqxjcWXo48NnmIUkT0bZY+3aSU6vqehiMKQR85xD7SNJyWnSeqqqfXWDVouYvrqpdgIPySupE22LttcCHk8xdh7EO+E+dRCRJS/NazFOSZlCrYq2qvpTkacBTGdz59LWq+m6nkUnSIpinJM2qtkfWAJ4LbGj2eXYSquqyTqKSpKUxT0maOa2KtSTvB54M3ADMXVA7N1K3JE2deUrSrGp7ZG0TcEozlYok9ZF5StJMajvO2k3AD3cZiCSNyTwlaSa1PbJ2LHBLkmuBB+Yaq+rcTqKSpMUzT0maSW2LtTd1GYQkTcCbph2AJHWh7dAdf5HkR4CNVXVlMyr4mm5Dk6T2zFPSyrFhy6cPaNuz9ZwpRLIytLpmLckvAh8B/rBpOgH4REcxSdKimackzaq2NxhcDDwPuA+gqm4HjusqKElaAvOUpJnUtlh7oKoenHuR5DAG4xdJUl+YpyTNpLbF2l8keT1weJIXAh8G/ld3YUnSopmnJM2ktneDbgEuAm4Efgn4DPCeroLS6jHqIlNpicxTkmZS27tBvwe8u3lIUu+YpyTNqrZzg97BiGs/qupJE49ImhBvDV9dzFOSZtVi5gad81jgpcAxkw9HkpbMPCVpJrW6waCqvjX0+GZVvQ14QZt9k6xJ8uUkn2peH5PkiiS3N89HD217SZLdSW5L8qKldEjS6jROnpovyVOT3DD0uC/Ja5O8Kck3h9rPHtrH/CWpE21Pg5469PKHGHyDfULLn/Ea4FbgyOb1FuCqqtqaZEvz+nVJTgEuAJ4OPBG4MslTqurhlj9H0io2Zp56hKq6DXhW875rgG8CHwdeAby1qn533s82f0nqTNvToL83tPwQsAf4mUPtlORE4BzgUuBXm+bzgDOa5e3AF4DXNe2XV9UDwB1JdgOnAV9sGaOk1W1JeaqFM4G/rqpvJFloG/OXpM60vRv0+Ut8/7cBv8Ejv90eX1X7mvfdl2RuhPETgKuHttvbtEnSIY2Rpw7lAuBPhl7/cpKXA7uAX6uqv2cR+SvJZmAzwPr16zsJWNJsaXsa9FcPtr6q3jJinxcD91bVdUnOaPNjRr31iPc10Uk6wFLyVIv3fDRwLnBJ0/Qu4LcY5KbfYnA07+dpmb+aOLYB2wA2bdrkDAuSDmkxd4M+F9jZvP5p4C+Buw6yz/OAc5sLcB8LHJnkA8A9SdY1R9XWAfc22+8FThra/0Tg7vlvaqKTtICl5KlD+XfA9VV1D8DcM0CSdwOfal62yl+StBRti7VjgVOr6n6AJG8CPlxVv7DQDlV1Cc230ebI2q9X1cuS/A5wIbC1ef5ks8tO4ENJ3sLgAt2NwLWL7I+k1WvReaqFn2XoFOjcF83m5UuAm5pl85ekzrQt1tYDDw69fhDYsMSfuRXYkeQi4E4GYyFRVTcn2QHcwuDi4Iu9k0rSIkwyT5HkCOCFDKaumvPbSZ7F4BTnnrl15i9JXWpbrL0fuDbJxxkkqZcAl7X9IVX1BQZ3fVJV32Jwd9Wo7S5lcOeoJC3WWHlqvqr6Z+BfzGv7uYNsb/6S1Im2d4NemuSzwL9pml5RVV/uLixJWhzzlKRZ1fbIGsARwH1V9UdJ1iY5uaru6CowSVoC85S0jEbNwazJazXdVJI3Mhi4du729UcBH+gqKElaLPOUpFnVqlhjcO3HucC3AarqbpY4jYskdcQ8JWkmtS3WHqyqohnkMcnjugtJkpbEPCVpJrUt1nYk+UPgqCS/CFwJvLu7sCRp0cxTkmbSIW8wyGDm4j8FngbcBzwV+G9VdUXHsUlSK+YpSbPskMVaVVWST1TVcwATn6TeMU9JmmVtT4NeneS5nUYiSeMxT0maSW3HWXs+8MokexjcaRUGX2Z/rKvAJGmRzFOSZtJBi7Uk66vqTuDfLVM8krQo5ilJs+5QR9Y+AZxaVd9I8tGq+g/LEJMkLcYnME9JmmGHumYtQ8tP6jIQSVoi85SkmXaoYq0WWJakvjBPSZpphzoN+swk9zH45np4sww/uHD3yE6j08xx0l91wDwlaaYdtFirqjXLFYgkLYV5StKsazvOmiStKkn2JLkxyQ1JdjVtxyS5IsntzfPRQ9tfkmR3ktuSvGh6kUuaNW3HWZNmwqjTsHu2njOFSLRCPL+q/nbo9RbgqqrammRL8/p1SU4BLgCeDjwRuDLJU6rq4eUPWdKs8ciaJLV3HrC9Wd4OnD/UfnlVPVBVdwC7gdOWPzxJs8hiTZJGK+DzSa5LsrlpO76q9gE0z8c17ScAdw3tu7dpO0CSzUl2Jdm1f//+jkKXNEs8DSpJoz2vqu5OchxwRZKvHWTbjGgbOYxIVW0DtgFs2rTJoUYkHZJH1iRphKq6u3m+F/g4g9Oa9yRZB9A839tsvhc4aWj3E4G7ly9aSbPMYk2S5knyuCRPmFsGfgq4CdgJXNhsdiHwyWZ5J3BBksckORnYCFy7vFFLmlWeBpWkAx0PfDwJDPLkh6rqz5J8CdiR5CLgTuClAFV1c5IdwC3AQ8DF3gkqaVIs1iRpnqr6OvDMEe3fAs5cYJ9LgUs7Dk3SKuRpUEmSpB6zWJMkSeoxizVJkqQes1iTJEnqsc6KtSQnJfnzJLcmuTnJa5p2J0KWJElqqcsjaw8Bv1ZVPwqcDlzcTHY8NxHyRuCq5jXzJkI+C3hnkjUdxidJktR7nQ3d0cybNzeH3v1JbmUwV955wBnNZtuBLwCvY2giZOCOJHMTIX+xqxglSVI/bNjy6Ue83rP1nClF0j/Lcs1akg3As4FrGHMiZCdBliRJq0nnxVqSxwMfBV5bVfcdbNMRbQdMclxV26pqU1VtWrt27aTClCRJ6qVOZzBI8igGhdoHq+pjTfM9SdZV1T4nQlYfeOhdktRnXd4NGuC9wK1V9ZahVU6ELEmS1FKXR9aeB/wccGOSG5q21wNbcSLkVWH+EStJkrR4Xd4N+leMvg4NnAhZkiSpFWcwkCRJ6jGLNUmSpB7r9G5QSZI0O7wWeTo8siZJ8xxkbuM3Jflmkhuax9lD+zi3saROeGRNkg40N7fx9UmeAFyX5Ipm3Vur6neHN543t/ETgSuTPMU72iVNgkfWJGmeqtpXVdc3y/cDc3MbL+T7cxtX1R3A3NzGkjQ2izVJOoh5cxsD/HKSryZ5X5Kjm7ZWcxtL0lJYrEnSAkbMbfwu4MnAs4B9wO/NbTpi9wPmNm7ec3OSXUl27d+/f/JBS5o5FmuSNMKouY2r6p6qeriqvge8mx+c6mw9t3FVbauqTVW1ae3atd11QNLM8AYDaZ5Rt6Y7ufvqstDcxknWVdW+5uVLgJua5Z3Ah5K8hcENBs5tLGliLNYk6UALzW38s0mexeAU5x7gl8C5jSV1y2JNE+FAiZolB5nb+DMH2ce5jSV1wmvWJEmSesxiTZIkqccs1iRJknrMYk2SJKnHLNYkSZJ6zLtBJUlS7zjm5Q9YrEktzE8aqzVhSJKWn8WalsRx1SRJWh5esyZJktRjFmuSJEk9ZrEmSZLUY16zJkmSDuC1yf1hsaZD8g9WkqTpsViTlsDxfyRJy8Vr1iRJknrMI2s6gKc9l8ajbZJWqpWS91drnrVYW+VWyh/oSuXMB5KkcfWuWEtyFvB2YA3wnqraOuWQpIlZrd8KVwvzl6Qu9KpYS7IG+H3ghcBe4EtJdlbVLdONbDZ4FK2fPPo2G8xfWklm6f+D1ZBDe1WsAacBu6vq6wBJLgfOA0x2SzBLf4yriUffVizzl6RO9K1YOwG4a+j1XuBfDm+QZDOwuXn5T0luW4a4jgX+dhl+znKYlb7MSj+gRV/y5mWKZHzL8bn8SMfvv1SHzF8wMod9i9n5t7wYs/Q3vBj2u2M9y5fz+72k/NW3Yi0j2uoRL6q2AduWJ5yBJLuqatNy/syuzEpfZqUfYF9myCHzFxyYw1br78x+ry72ezx9G2dtL3DS0OsTgbunFIskLYb5S1In+lasfQnYmOTkJI8GLgB2TjkmSWrD/CWpE706DVpVDyX5ZeBzDG59f19V3TzlsGCZT7t2bFb6Miv9APsyE8bIX6v1d2a/Vxf7PYZUHXBJhSRJknqib6dBJUmSNMRiTZIkqccs1hpJjklyRZLbm+ejF9jurCS3JdmdZMuI9b+epJIc233UI+Mbqx9JfifJ15J8NcnHkxy1bMEfIrah9Unyjmb9V5Oc2nbf5bbUviQ5KcmfJ7k1yc1JXrP80T8iziV/Js36NUm+nORTyxd1fyzi7/J9Se5NctO89jcl+WaSG5rH2csT+Xgm0O9W+/fNBPLwivq8ZylntzVmn/ckubH5bHe1+oFV5WNw3d5vA1ua5S3Am0dsswb4a+BJwKOBrwCnDK0/icHFxd8Ajl2J/QB+CjisWX7zqP07jv+gv+Nmm7OBzzIY1+p04Jq2+66gvqwDTm2WnwD8n2n1ZZx+DK3/VeBDwKem9XlM89Hm77JZ9xPAqcBN89rfBPz6tPsxhX632r9vjwnk4RXzec9Szl6OPjfr9rDIGsEjaz9wHrC9Wd4OnD9im+9PJ1NVDwJz08nMeSvwG4wYCHMZjdWPqvp8VT3UbHc1g7GiltOhfsc0ry+rgauBo5Ksa7nvclpyX6pqX1VdD1BV9wO3MhghfxrG+UxIciJwDvCe5Qy6Z9r8XVJVfwn83TLFtBzG7Xer/XtoEv+frBSzlLPbGisnLoXF2g8cX1X7AJrn40ZsM2o6mRMAkpwLfLOqvtJ1oIcwVj/m+XkG3wyWU5vYFtqmbb+Wyzh9+b4kG4BnA9dMPsRWxu3H2xh8ifleR/GtBG3+Lg/ll5vTKe9bKacDGb/fk/i9TcMk8vBK+bxnKWe3NW5OLODzSa7LYPq5Q+rVOGtdS3Il8MMjVr2h7VuMaKskRzTv8VNLjW0xuurHvJ/xBuAh4IOLi25sbabsWWibVtP9LKNx+jJYmTwe+Cjw2qq6b4KxLcaS+5HkxcC9VXVdkjMmHVifTODv8mDeBfwWg9/7bwG/x+DL1NR13O/e6jgP9/bzHmGWcnZb4+b251XV3UmOA65I8rXm6PKCVlWxVlU/udC6JPfMnX5qDlXeO2KzhaaTeTJwMvCVJHPt1yc5rar+ZmIdaHTYj7n3uBB4MXBmNSfYl1GbKXsW2ubRLfZdTuP0hSSPYlCofbCqPtZhnIcyTj/+I3Buc4H0Y4Ejk3ygql7WYbxTMYG/y4O99z1D7/VuoDc3anTZb2Dc/TvTZR7u8+c9wizl7LbGyu1VNfd8b5KPMzitetBizdOgP7ATuLBZvhD45IhtRk4nU1U3VtVxVbWhqjYw+JBO7aJQa2HJ/YDBHS7A64Bzq+qflyHe1rEN2Qm8vLnb5nTgH5tTDX2b7mfJfcmg6n8vcGtVvWV5wz7AkvtRVZdU1YnN38UFwP+exUKthTZ/lwuad63LS4CbFtq2Z8bq9wT2n5Zx8/BK+rxnKWe3NU5uf1ySJwAkeRyDM3KH/nwXczfCLD+AfwFcBdzePB/TtD8R+MzQdmczuDPvr4E3LPBee5je3aBj9QPYzeA8+w3N4w+m0IcDYgNeCbyyWQ7w+836G4FNi/l8VkJfgB9ncMj8q0OfxdkrrR/z3uMMVu/doG3/Lv8E2Ad8l8GXvoua9vc3v9evMvhPYN20+7RM/R65f98fE8jDK+rznqWc3XWfGdxB+pXmcXPbPjvdlCRJUo95GlSSJKnHLNYkSZJ6zGJNkiSpxyzWJEmSesxiTZIkqccs1iRJknrMYk2SJKnHLNYkSZJ6zGJNkiSpxyzWJEmSesxiTZIkqccs1iRJknrMYk2SJKnHLNYkSZJ6zGJNkiSpxyzWJEmSeuywaQcwjmOPPbY2bNgw7TAkLaPrrrvub6tq7bTjmARzmLS6LDV/rehibcOGDezatWvaYUhaRkm+Me0YJsUcJq0uS81fngaVJEnqMYs1SZKkHrNYkyRJ6jGLNUmSpB6zWJMkSeoxizVJkqQeW9FDd2j12rDl0we07dl6zhQikaQfMDepCx5ZkyRJ6jGLNUmSpB6zWJMkSeoxizVJkqQes1iTJEnqMYs1SZKkHut06I4k/xX4BaCAG4FXAEcAfwpsAPYAP1NVf99sfwlwEfAw8Oqq+lyX8WnlGHU7vCRJq0FnR9aSnAC8GthUVc8A1gAXAFuAq6pqI3BV85okpzTrnw6cBbwzyZqu4pMkSVoJuj4NehhweJLDGBxRuxs4D9jerN8OnN8snwdcXlUPVNUdwG7gtI7jkyRJ6rXOirWq+ibwu8CdwD7gH6vq88DxVbWv2WYfcFyzywnAXUNvsbdpkyRJWrW6PA16NIOjZScDTwQel+RlB9tlRFuNeN/NSXYl2bV///7JBCtpVUry2CTXJvlKkpuT/P+a9mOSXJHk9ub56KF9LkmyO8ltSV401P6cJDc2696RZFROk6RF6/I06E8Cd1TV/qr6LvAx4F8D9yRZB9A839tsvxc4aWj/ExmcNn2EqtpWVZuqatPatWs7DF/SKvAA8IKqeibwLOCsJKeztGtr3wVsBjY2j7OWsR+SZliXxdqdwOlJjmi+YZ4J3ArsBC5strkQ+GSzvBO4IMljkpzMINld22F8kla5Gvin5uWjmkexyGtrmy+eR1bVF6uqgMuG9pGksXQ2dEdVXZPkI8D1wEPAl4FtwOOBHUkuYlDQvbTZ/uYkO4Bbmu0vrqqHu4pPkgCaI2PXAf8X8PtN7nrEtbVJhq+tvXpo97lra7/bLM9vl6SxdTrOWlW9EXjjvOYHGBxlG7X9pcClXcYkScOaL4XPSnIU8PEkzzjI5gtdW9vqmlsYXHfL4HQp69evX1ywklYlZzCQJKCq/gH4AoNrzRZ7be3eZnl++6if43W3khbFYk3SqpVkbXNEjSSHM7gx6mss8tra5pTp/UlOb67RffnQPpI0lk5Pg0pSz60DtjfXrf0QsKOqPpXkiyz+2tpXAX8MHA58tnlI0tgs1iStWlX1VeDZI9q/xSKvra2qXcDBrneTpCXxNKgkSVKPWaxJkiT1mMWaJElSj1msSZIk9ZjFmiRJUo9ZrEmSJPWYxZokSVKPWaxJkiT1mMWaJElSj1msSZIk9ZjFmiRJUo9ZrEmSJPWYxZokSVKPHTbtAKRJ2bDl0494vWfrOVOKRJKkyfHImiRJUo95ZE29M/8ImdSVJCcBlwE/DHwP2FZVb0/yJuAXgf3Npq+vqs80+1wCXAQ8DLy6qj7XtD8H+GPgcOAzwGuqqpavN5JmlcWapNXsIeDXqur6JE8ArktyRbPurVX1u8MbJzkFuAB4OvBE4MokT6mqh4F3AZuBqxkUa2cBn12mfkiaYZ4GlbRqVdW+qrq+Wb4fuBU44SC7nAdcXlUPVNUdwG7gtCTrgCOr6ovN0bTLgPO7jV7SamGxJklAkg3As4FrmqZfTvLVJO9LcnTTdgJw19Bue5u2E5rl+e2SNDaLNUmrXpLHAx8FXltV9zE4pflk4FnAPuD35jYdsXsdpH3Uz9qcZFeSXfv37x+1iSQ9gsWapFUtyaMYFGofrKqPAVTVPVX1cFV9D3g3cFqz+V7gpKHdTwTubtpPHNF+gKraVlWbqmrT2rVrJ9sZSTPJYk3SqpUkwHuBW6vqLUPt64Y2ewlwU7O8E7ggyWOSnAxsBK6tqn3A/UlOb97z5cAnl6UTkmaed4NKWs2eB/wccGOSG5q21wM/m+RZDE5l7gF+CaCqbk6yA7iFwZ2kFzd3ggK8ih8M3fFZvBNU0oRYrElatarqrxh9vdlnDrLPpcClI9p3Ac+YXHSSNNDpadAkRyX5SJKvJbk1yb9KckySK5Lc3jwfPbT9JUl2J7ktyYu6jE2SJGkl6PqatbcDf1ZVTwOeyWAMoy3AVVW1EbiqeT1/sMmzgHcmWdNxfJIkSb3WWbGW5EjgJxhcvEtVPVhV/8BgUMntzWbb+cHAkSMHm+wqPkmSpJWgyyNrT2Iwr94fJflykvckeRxwfHPnFM3zcc32Cw02+QiOUSRJklaTLou1w4BTgXdV1bOBb9Oc8lxAq0ElHaNIkiStJl0Wa3uBvVU1N3XLRxgUb/fMjWHUPN87tP2owSYlSZJWrc6Ktar6G+CuJE9tms5kMDbRTuDCpu1CfjBw5MjBJruKT5IkaSVoNc5akmdU1U2H3vIAvwJ8MMmjga8Dr2BQIO5IchFwJ/BSOORgk5J0UGPkKUnqtbaD4v5BU3D9MfCh5q7OQ6qqG4BNI1aducD2IweblKQWlpSnJKnvWp0GraofB/4zg2vKdiX5UJIXdhqZJC2CeUrSrGp9zVpV3Q78JvA64N8C72hmJvj3XQUnSYthnpI0i1oVa0l+LMlbGcxA8ALgp6vqR5vlt3YYnyS1Yp6SNKvaXrP2P4F3A6+vqu/MNVbV3Ul+s5PIJGlxzFOSZlLbYu1s4Dtzd2cm+SHgsVX1z1X1/s6ik6T2zFOSZlLba9auBA4fen1E0yZJfWGekjST2hZrj62qf5p70Swf0U1IkrQki85TSU5K8udJbk1yc5LXNO3HJLkiye3N89FD+1ySZHeS25K8aKj9OUlubNa9I8moKfQkadHaFmvfTnLq3IskzwG+c5DtJWm5LSVPPQT8WnMjwunAxUlOYTCP8VVVtRG4qnlNs+4C4OnAWcA7k6xp3utdwGYGs69sbNZL0tjaXrP2WuDDSebm6lwH/KdOIpKkpXkti8xTVbUP2Ncs35/kVuAE4DzgjGaz7cAXGAwHch5weVU9ANyRZDdwWpI9wJFV9UWAJJcB5wOfnUzXJK1mrYq1qvpSkqcBTwUCfK2qvttpZJK0COPmqSQbgGcD1wDHN4UcVbUvyXHNZicAVw/ttrdp+26zPL991M/ZzOAIHOvXr28bnqRVrO2RNYDnAhuafZ6dhKq6rJOoJGlplpSnkjwe+Cjw2qq67yCXm41aUQdpP7CxahuwDWDTpk0jt5GkYW0ncn8/8GTgBmBucvUCLNYk9cJS81SSRzEo1D5YVR9rmu9Jsq45qrYOuLdp38tgOqs5JwJ3N+0njmiXpLG1PbK2CTilqvwWKKmvFp2nmjs23wvcWlVvGVq1E7gQ2No8f3Ko/UNJ3gI8kcGNBNdW1cNJ7k9yOoPTqC8H/t9xOyRJ0L5Yuwn4YZoLcSWph5aSp54H/BxwY5IbmrbXMyjSdiS5CLgTeClAVd2cZAdwC4M7SS+eG4QXeBXwxwzGevss3lwgaULaFmvHArckuRZ4YK6xqs7tJCpJWrxF56mq+itGX28GcOYC+1wKXDqifRfwjMUELElttC3W3tRlEJI0AW+adgCS1IW2Q3f8RZIfATZW1ZVJjgDWHGo/aZo2bPn0AW17tp4zhUi0HMxTkmZVqxkMkvwi8BHgD5umE4BPdBSTJC2aeUrSrGo73dTFDC7EvQ+gqm4HjjvoHpK0vMxTkmZS22Ltgap6cO5FksNYYMBHSZoS85SkmdS2WPuLJK8HDk/yQuDDwP/qLixJWjTzlKSZ1LZY2wLsB24Efgn4DPCbXQUlSUtgnpI0k9reDfo94N3NQ5qYUXdsSkthnpI0q9rODXoHI679qKonTTwiSVoC85SkWbWYuUHnPJbB1CvHTD4cSVoy85SkmdTqmrWq+tbQ45tV9TbgBd2GJkntmackzaq2p0FPHXr5Qwy+wT6hk4gkaQnMU5JmVdvToL83tPwQsAf4mYlHI0lLZ56SNJPa3g36/KX+gCRrgF3AN6vqxUmOAf4U2ECTTKvq75ttLwEuAh4GXl1Vn1vqz5W0uoyTpySpz9qeBv3Vg62vqrccZPVrgFuBI5vXW4Crqmprki3N69clOQW4AHg68ETgyiRPqaqH28QoaXUbM09JUm+1HRR3E/AqBhMjnwC8EjiFwfUgC14TkuRE4BzgPUPN5wHbm+XtwPlD7ZdX1QNVdQewGzitZXyStOg8leR9Se5NctNQ25uSfDPJDc3j7KF1lyTZneS2JC8aan9Okhubde9Iko76KGkVanvN2rHAqVV1PwySGfDhqvqFQ+z3NuA3eGSiPL6q9gFU1b4kcxMtnwBcPbTd3qbtEZJsBjYDrF+/vmX4klaBpeSpPwb+J3DZvPa3VtXvDjcc4uj/uxjkpasZzJxwFvDZcTskSdD+yNp64MGh1w8yuOZsQUleDNxbVde1/BmjvomOGuByW1VtqqpNa9eubfnWklaBReepqvpL4O9avv/Io/9J1gFHVtUXq6oYFH7nLzJ2SVpQ2yNr7weuTfJxBgXUSzjwm+h8zwPObU4hPBY4MskHgHuSrGuOqq0D7m223wucNLT/icDdLeOTpKXkqYX8cpKXM7g56team6AWOvr/3WZ5fvtInh2QtFhtB8W9FHgF8PfAPwCvqKr/cYh9LqmqE6tqA4NTB/+7ql4G7AQubDa7EPhks7wTuCDJY5KcDGwErl1cdyStVkvJUwt4F/Bk4FnAPn4wJMhCR/9bnRUYitOzA5IWpe2RNYAjgPuq6o+SrE1ycnMqYLG2AjuSXATcyWBKGKrq5iQ7gFsYjJF0sXeCSlqksfNUVd0zt5zk3cCnmpcLHf3f2yzPb5ekiWh1ZC3JG4HXAZc0TY8CPtD2h1TVF6rqxc3yt6rqzKra2Dz/3dB2l1bVk6vqqVXlxbmSWhs3Tw29z7qhly8B5u4UHXn0v7lh6v4kpzd3gb6cH5wxkKSxtT2y9hLg2cD1AFV1dxKncZHUJ4vOU0n+BDgDODbJXuCNwBlJnsXgVOYe4Jea9zvY0f9XMbiz9HAGd4H6ZVPSxLQt1h6sqkpSAEke12FMkrQUi85TVfWzI5rfe5DtLwUuHdG+C3jGImKVpNbaDt2xI8kfAkcl+UXgSuDd3YUlSYtmnpI0kw55ZK25BuNPgacB9wFPBf5bVV3RcWyS1Ip5StIsO2Sx1pxW+ERVPQcw8UnqHfOUpFnW9jTo1Ume22kkkjQe85SkmdT2BoPnA69Msgf4NoNBIKuqfqyrwCRpkcxTkmbSQYu1JOur6k7g3y1TPJK0KOYpSbPuUEfWPgGcWlXfSPLRqvoPyxCTJC3GJzBPSZphh7pmbXjOuyd1GYgkLZF5StJMO9SRtVpgWVqRNmz59AFte7aeM4VINEHmKUkz7VDF2jOT3Mfgm+vhzTL84MLdIzuNTpIOzTwlaaYdtFirqjXLFYhWh1FHtqRxmKckzbq246xJkiRpCizWJEmSesxiTZIkqccs1iRJknrMYk3SqpXkfUnuTXLTUNsxSa5IcnvzfPTQukuS7E5yW5IXDbU/J8mNzbp3JMn8nyVJS2WxJmk1+2PgrHltW4CrqmojcFXzmiSnABcAT2/2eWeSuTtR3wVsBjY2j/nvKUlLZrEmadWqqr8E/m5e83nA9mZ5O3D+UPvlVfVAVd0B7AZOS7IOOLKqvlhVBVw2tI8kje1Qg+JK0mpzfFXtA6iqfUmOa9pPAK4e2m5v0/bdZnl++0hJNjM4Csf69esnGLamwbEjtRw8siZJ7Yy6Dq0O0j5SVW2rqk1VtWnt2rUTC07S7LJYk6RHuqc5tUnzfG/Tvhc4aWi7E4G7m/YTR7RL0kRYrEnSI+0ELmyWLwQ+OdR+QZLHJDmZwY0E1zanTO9PcnpzF+jLh/aRpLF5zZqkVSvJnwBnAMcm2Qu8EdgK7EhyEXAn8FKAqro5yQ7gFuAh4OKqerh5q1cxuLP0cOCzzUOSJsJiTdKqVVU/u8CqMxfY/lLg0hHtu4BnTDA0Sfo+T4NKkiT1WGfFWpKTkvx5kluT3JzkNU37okcHlyRJWq26PA36EPBrVXV9kicA1yW5Avi/GYwOvjXJFgajg79u3ujgTwSuTPKUoWtCpE7MHydpz9ZzphSJJEkH6uzIWlXtq6rrm+X7gVsZDBS5qNHBu4pPkiRpJViWa9aSbACeDVzDvNHBgeHRwe8a2u2go4BLkiStBp0Xa0keD3wUeG1V3XewTUe0HTAKeJLNSXYl2bV///5JhSlJktRLnRZrSR7FoFD7YFV9rGle7Ojgj+BULZIkaTXp7AaDZiTv9wK3VtVbhlbNjQ6+lQNHB/9QkrcwuMFgI3BtV/Gpe05wLEnS+Lq8G/R5wM8BNya5oWl7PUsbHVySJGlV6qxYq6q/YvR1aLDI0cElSZJWK2cwkCRJ6jHnBpUkqUOjrt918G0thkfWJEmSesxiTZIkqccs1iRphCR7ktyY5IYku5q2Y5JckeT25vnooe0vSbI7yW1JXjS9yCXNGq9Zk+bx+hINeX5V/e3Q6y3AVVW1NcmW5vXrkpwCXAA8ncE4kVcmeYrDD0maBI+sSVJ75wHbm+XtwPlD7ZdX1QNVdQewGzht+cOTNIs8sqaJcLYCzaACPp+kgD+sqm3A8VW1D6Cq9iU5rtn2BODqoX33Nm2SNDaLNUka7XlVdXdTkF2R5GsH2XbUAOA1csNkM7AZYP369eNHKWnmeRpUkkaoqrub53uBjzM4rXlPknUAzfO9zeZ7gZOGdj8RuHuB991WVZuqatPatWu7Cl/SDLFYk6R5kjwuyRPmloGfAm4CdgIXNptdCHyyWd4JXJDkMUlOBjYC1y5v1JJmladBJelAxwMfTwKDPPmhqvqzJF8CdiS5CLgTeClAVd2cZAdwC/AQcLF3gkqaFIs1SZqnqr4OPHNE+7eAMxfY51Lg0o5Dk7QKeRpUkiSpxyzWJEmSesxiTZIkqccs1iRJknrMGwy0JM5YIEnS8vDImiRJUo9ZrEmSJPWYp0GlFuaf9t2z9ZwpRSJJWm0s1iRJasFrdTUtFmuSJC0zj9ZrMSzWpCUY9Q3bZCtJ6oI3GEiSJPWYR9Z0SF6nIUnS9Fis6QAWZ0vjqVFJUhc8DSpJktRjvTuyluQs4O3AGuA9VbV1yiFJUivmr9mx3GcYPDKvg+lVsZZkDfD7wAuBvcCXkuysqlumG9ns8pTn8jIhzy7zl6Su9KpYA04DdlfV1wGSXA6cB5jslsBCbPrafAaOtzQzzF+aKHOD5vStWDsBuGvo9V7gX04plrG1+Y96Un98Fmazo+3Rt5WayFdq3C3MVP6aZSs1X3pkfvXqW7GWEW31iA2SzcDm5uU/Jbmt45iOBf62qzfPm7t655E67csym6W+wCH60+bfyTL/WzqYRX02S4j7Rxa9x/I4ZP6CJeewWfv3PmdW+wXL1Lcp/d3P6ue2HP1aUv7qW7G2Fzhp6PWJwN3DG1TVNmDbcgWUZFdVbVqun9cl+9Jfs9SfWerLIh0yf8HSctis/k5ntV9g31aiPverb0N3fAnYmOTkJI8GLgB2TjkmSWrD/CWpE706slZVDyX5ZeBzDG59f19V3TzlsCTpkMxfkrrSq2INoKo+A3xm2nEMWbZTrsvAvvTXLPVnlvqyKB3mr1n9nc5qv8C+rUS97VeqDrj+VZIkST3Rt2vWJEmSNMRiDUhyTJIrktzePB+9wHZnJbktye4kW0as//UkleTY7qMebdy+JPmdJF9L8tUkH09y1LIFf4jYhtYnyTua9V9NcmrbfZfbUvuS5KQkf57k1iQ3J3nN8kd/oHE+m2b9miRfTvKp5Yt6ZVjE3+77ktyb5Kal7L/cJpCT3pTkm0luaB5nL1/0o81Sjho2Zr/2JLmx+Yx2LW/kh9aib09L8sUkDyT59cXsuyyqatU/gN8GtjTLW4A3j9hmDfDXwJOARwNfAU4ZWn8SgwuLvwEcu1L7AvwUcFiz/OZR+3cc/0F/z802ZwOfZTCu1enANW33XUF9WQec2iw/Afg/0+zLuP0ZWv+rwIeAT02zL318tPnbbdb9BHAqcNNS9u9jvw6Rk94E/Pq0+9Em1qFtVkSOmlS/mnV7mOL/fRPo23HAc4FLh/+99eUz88jawHnA9mZ5O3D+iG2+P5VMVT0IzE0lM+etwG8wYhDMZTZWX6rq81X1ULPd1QzGilpOh/o907y+rAauBo5Ksq7lvstpyX2pqn1VdT1AVd0P3MpghPxpGuezIcmJwDnAe5Yz6BWkzd8uVfWXwN8tdf8pmER+7ZNZylHDxvr77rlD9q2q7q2qLwHfXey+y8FibeD4qtoH0DwfN2KbUVPJnACQ5Fzgm1X1la4DbWGsvszz8wy+RS2nNrEttE3bfi2XcfryfUk2AM8Grpl8iIsybn/exuALzfc6im+la/O32+X+XZlETvrl5rTb+3pweneWctSwcf++C/h8kusymKWjT8b5vffiM+vd0B1dSXIl8MMjVr2h7VuMaKskRzTv8VNLjW2xuurLvJ/xBuAh4IOLi25sbabsWWibVtP9LKNx+jJYmTwe+Cjw2qq6b4KxLcWS+5PkxcC9VXVdkjMmHdhKMYG/3V7qOCe9C/it5vVvAb/H4IvktMxSjho2br56XlXdneQ44IokX2uOAvfBOL/3Xnxmq6ZYq6qfXGhdknvmTj01h3TvHbHZQlPJPBk4GfhKkrn265OcVlV/M7EODOmwL3PvcSHwYuDMak7aL6M2U/YstM2jW+y7nMbpC0kexaBQ+2BVfazDONsapz//ETi3uTj8scCRST5QVS/rMN7emcDf7sGMu/+SdZmTquqeofd6NzDtm1NmKUcNGytfVdXc871JPs7g9GFfirVWU8F1sO/EeBp0YCdwYbN8IfDJEduMnEqmqm6squOqakNVbWDwwZ7aVaHWwpL7AoO7XoDXAedW1T8vQ7ytYxuyE3h5c2fS6cA/NqdX+jbdz5L7kkHl/17g1qp6y/KGvaAl96eqLqmqE5u/kQuA/73aCrUW2vztdrl/V8bNScPXRL0EuGnE/stplnLUsHHy1eOSPAEgyeMYnGma9uc0bJzfez8+sy7vXlgpD+BfAFcBtzfPxzTtTwQ+M7Td2Qzuyvtr4A0LvNcepns36Fh9AXYzOD9/Q/P4gyn04YDYgFcCr2yWA/x+s/5GYNNiPqOV0Bfgxxkcav/q0Gdx9krtz7z3OAPvBh31u237t/snwD4GF0LvBS462P7TfkwgJ72/+bf0VQb/Sa7rQZ9mJkdNol8M7pT8SvO4uW/9atm3H27+nu4D/qFZPrIvn5kzGEiSJPWYp0ElSZJ6zGJNkiSpxyzWJEmSesxiTZIkqccs1iRJknrMYk2SJKnHLNYkSZJ6zGJNkiSpx/7/f6ErYfNKyZkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x1008 with 8 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# function to get log of daily rate\n",
    "def logarizer(dataset):\n",
    "    dataset[\"log_rate\"] = np.log(dataset.iloc[:,1]/dataset.iloc[:,1].shift()) # getting the log of the exchange rate\n",
    "    return dataset[\"log_rate\"]\n",
    "\n",
    "# function to get overall volatility\n",
    "volatility_dict = {}\n",
    "def volatizer(dataset):\n",
    "    column_headers = list(dataset.columns.values)\n",
    "    currency_name = column_headers[1]\n",
    "    volatility = dataset[\"log_rate\"].std()*253**.5 # volatility measured by standard deviation * 253 trading days per year\n",
    "    volatility = round(volatility, 4)*100\n",
    "    volatility_dict[currency_name] = volatility\n",
    "\n",
    "# calling logarizer on all eight currencies\n",
    "for currency in c_list:\n",
    "    logarizer(currency)\n",
    "    \n",
    "# calling volatizer on all eight currencies\n",
    "for currency in c_list:\n",
    "    volatizer(currency)\n",
    "\n",
    "# line graph showing log exchange rates of each currency\n",
    "plt.figure(figsize=(10,14))\n",
    "for i, currency in zip(range(1,9), c_list):\n",
    "    plt.subplot(4,2,i)\n",
    "    currency[\"log_rate\"].plot.hist(bins=50)\n",
    "#     plt.title(currency) # will get ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().\n",
    "plt.show()\n",
    "\n",
    "# plt.title(\"Romanian volatility: \" + str(romanian_leu[\"volatility\"]) + \"%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'us_dollar': 9.66,\n",
       " 'japanese_yen': 11.74,\n",
       " 'uk_pound': 8.110000000000001,\n",
       " 'australian_dollar': 10.56,\n",
       " 'israeli_shekel': 9.83,\n",
       " 'philippine_peso': 10.57,\n",
       " 'malaysian_ringgit': 9.47,\n",
       " 'romanian_leu': 8.16}"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "volatility_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# import geopandas and other libraries\n",
    "# import geopandas as gpd\n",
    "# import seaborn as sns\n",
    "# import os\n",
    "# map_data = gpd.read_file(\"World_Countries__Generalized_.shp\")\n",
    "# map_data[\"Volatility\"] = None\n",
    "# map_data.head()\n",
    "\n",
    "# map_data.shape\n",
    "# map_data.plot(figsize=(15,13))\n",
    "# map_data[map_data[\"COUNTRY\"] == \"United States\"].plot(color = \"green\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Volatility Continued\n",
    "stuff\n",
    "## Mapping\n",
    "stuff"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Citations\n",
    "1.  Eichengreen, Barry (2019). Globalizing Capital: A History of the International Monetary System (3rd ed.). Princeton University Press. pp. 7, 79. ISBN 978-0-691-19390-8. JSTOR j.ctvd58rxg.\n",
    "2. https://en.wikipedia.org/wiki/Bretton_Woods_system\n",
    "3. Lowenstein, Roger (August 5, 2011). \"The Nixon Shock\". www.bloomberg.com. Bloomberg. Retrieved March 25, 2019.\n",
    "4. Bank for International Settlements. \"Foreign Exchange Turnover in April 2019.\" Accessed Oct. 3, 2020.\n",
    "5. https://fxssi.com/the-most-traded-currency-pairs"
   ]
  }
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