ibnummuhammad
commited on
Commit
•
8458717
1
Parent(s):
3ff19ec
Fix IDI_1 vs newcastle
Browse files- coal-price-forecast.ipynb +15 -34
coal-price-forecast.ipynb
CHANGED
@@ -167,43 +167,12 @@
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},
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{
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"cell_type": "code",
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"execution_count":
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"metadata": {},
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"outputs": [],
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"source": [
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"y = df.ICI_1\n",
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"x = df.newcastle"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {},
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"outputs": [],
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"source": [
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"slope, intercept, r, p, std_err = stats.linregress(x, y)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"metadata": {},
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"outputs": [],
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"source": [
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"def myfunc(x):\n",
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" return slope * x + intercept\n",
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"\n",
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"mymodel = list(map(myfunc, x))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"metadata": {},
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"outputs": [
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{
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"data": {
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-
"image/png": 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",
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"text/plain": [
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"<Figure size 640x480 with 1 Axes>"
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]
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}
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],
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"source": [
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"plt.scatter(x, y)\n",
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-
"plt.plot(x, mymodel)\n",
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"plt.show()"
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]
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},
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},
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{
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"cell_type": "code",
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+
"execution_count": 35,
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"metadata": {},
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"outputs": [
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{
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"data": {
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+
"image/png": 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UyNHK1PdeBCKVNbLhzrR4b27EqrSNXl0l6+2zlStXwmQyYfz48dDr9baf999/HwAQFhaGnTt3YtKkSRg4cCCefPJJZGVlYevWrbbXCAkJwbZt2xASEgKDwYA5c+bgwQcfxMsvvyxXt4iIyF8IAeyaIA1EPWcADwjFBSIgOKbFy0n222et6dmzJ/Lz89t8nd69e2P79u2eahYREQUChRdTOxIM0+Ll5BeF1kRERB6l8GJqZ6zT4p1V76jQOAtNydPi5cRQREREgaP+GrBOBXzz303Hhr0J3F8NhNjvcKA01mnxAOyCUaBMi5cTQxEREQWG0s/sZ5fde1FRs8tcEejT4uXkN4s3EhERtYujlal7zgDG/kO+NnlZIE+LlxNDERERKVcAFlO7ytm0eF9v/xFIGIqIiEiZTvxWWjvUqTOQVREQtUPtJcf2H4GENUVERKQsDoup3wJ+eiXoA5Fc238ECoYiIiJSDqfF1AvkaY+faGv7D6Bx+48GS+vrAwY7hiIiIvJ/tpWp05uO9cxS7MrUnubO9h/kHGuKiIjIvwVxMbWruP2HZzAUERGR/yr8DXDs+abHLKZ2iNt/eAZDERER+Z/6a/a1Q8PeCvraIWes238YTTUO64pUaFzckdt/tI41RURE5F9YTO02bv/hGQxFRETkH1hM3SHc/qPjePuMiIjkx2Jqj+D2Hx3DUERERPKyK6buAmRdZjF1Oznb/oPaxlBERETyYDE1+RmGIiIi8r3Sz6S1Q0BjMTVrh0hGDEVEROQ7QgC704Cy3U3Het4HjN0oX5uIfsRQREREvnGlGPioj/TYxH1A3Bh52kPUAkMREdGPGiyCs3a8hcXUpAAMRUREAPIKS7Fsa5FkU029NgJLM5O5vktHsJiaFISLNxJR0MsrLEX22iN2u4wbTTXIXnsEeYWlMrVM4bgyNSkMQxERBbUGi8CyrUUO94uyHlu2tQgNFkdXkENCADvvbLEy9X1cmZr8Hm+fEVFQO1hcYTdC1JwAUGqqwcHiCi6I5woWU5OCMRQRUVArr3IeiNpzXVBjMTUpHEMREQW1+OiIti9y47qgxGJqChAMRUQU1EYmxUKvjYDRVOOwrkiFxl3GRybF+rppysCVqSmAsNCaiIJaiFqFpZnJABoDUHPWx0szk7leUUuOiql7/YTF1KRoDEVEFPQyUvRYOWcodFrpLTKdNgIr5wzlOkUtXSkG1quB8j1NxybuA27/u2xNIvIE3j4jIkJjMJqYrOOK1m0p/DVw7IWmx526APdVAOpQ+dpE5CEMRUREPwpRqzjt3hlHxdTD/wjclCNPe4i8gKGIiIhad/FTYE+G9BiLqSkAMRQREZFjQgC77pLWDvX6CWuHKGAxFBERkT2uTE1BiKGIiIikWExNQYqhiIiIGrGYmoIcQxERETkppi4FInXytIdIBgxFRETBjMXURDYMRUREwcphMfUXQNxt8rSHSGYMRUREwahlMXWoBsj6D4upKagxFBERBZP6q8DfO0uPDX8buOmX8rSHyI8wFBERBQsWUxO1iqGIiCjQCQHsuhMoz2861uunwO3vy9cmIj/EUEREFMhYTE3kMoYiIqJAdfwV4PiLTY9ZTE3UKoYiIqJAw2JqonZhKCIiCiQspiZqN4YiIvILDRaBg8UVKK+qQXx0BEYmxSJErZK7WcrBYmqiDmMoIiLZ5RWWYtnWIpSaamzH9NoILM1MRkaKXsaWKQSLqYk8Qi13A4gouOUVliJ77RFJIAIAo6kG2WuPIK+wVKaWKcTxV6SBKFQDzLzOQETUDgxFRCSbBovAsq1FEA7OWY8t21qEBoujK4Jc/VVgnUo6u2z428BPTJxdRtRODEVEJJuDxRV2I0TNCQClphocLK7wXaOU4GKe/eyye0s5u4yog1hTRESyKa9yHojac13AEwLYNR4o39t0jMXURB7DUEREsomPjvDodQHtyr+Bj/pKj7GYmsijePuMiGQzMikWem0EnE28V6FxFtrIpFhfNsv/HH9FGohYTE3kFQxFRCSbELUKSzOTAcAuGFkfL81MDt71ilhMTeRTDEVEJKuMFD1WzhkKnVZ6i0ynjcDKOUODd50iFlMT+ZysoSg3NxcjRoxAdHQ04uPjMX36dJw8eVJyTU1NDXJyctCtWzd06dIFWVlZKCsrk1xTUlKCqVOnIioqCvHx8Xj66adRX1/vy64QUQdkpOixb/FdWP/IaLw5cwjWPzIa+xbfFZyBSAhg5x3AnslNx3r9FHhAcKsOIi+TtdA6Pz8fOTk5GDFiBOrr6/Hcc89h0qRJKCoqQufOjf+HtGjRInz88cfYuHEjtFotFixYgBkzZuCLL74AADQ0NGDq1KnQ6XTYv38/SktL8eCDDyI0NBS//e1v5eweEbkhRK2CoW83uZshL4fF1PuBOIM87SEKMiohhN+sinbp0iXEx8cjPz8f48aNg8lkQlxcHNatW4f77rsPAPDdd99h0KBBKCgowOjRo/HJJ5/g7rvvxsWLF5GQkAAAWLVqFRYvXoxLly4hLCyszfc1m83QarUwmUzQaDRe7SMRkUPHX5HWDoVqgaxLrB0iaoWnv7/9qqbIZDIBAGJjG2eaHD58GHV1dUhLS7NdM3DgQPTq1QsFBQUAgIKCAgwePNgWiAAgPT0dZrMZJ06ccPg+tbW1MJvNkh+iYNNgESg4cxlbjl5AwZnLXDVaLo6KqUe8A/ykkoGIyMf8Zp0ii8WChQsXYsyYMUhJSQEAGI1GhIWFISYmRnJtQkICjEaj7Zrmgch63nrOkdzcXCxbtszDPSBSDm7A6icu5klrh4DGYmrWDhHJwm9GinJyclBYWIgNGzZ4/b2WLFkCk8lk+zl37pzX35PIX3ADVj/gsJj6fhZTE8nML0aKFixYgG3btmHv3r3o0aOH7bhOp8P169dRWVkpGS0qKyuDTqezXXPw4EHJ61lnp1mvaSk8PBzh4eEe7gWR/2trA1YVGjdgnZisC961gbyNxdREfkvWkSIhBBYsWIBNmzZh9+7dSEpKkpwfNmwYQkNDsWvXLtuxkydPoqSkBAZD4z8gBoMBx48fR3l5ue2aHTt2QKPRIDk52TcdIVIIbsAqs+Mvt1iZWvvjytQMRET+QNaRopycHKxbtw5btmxBdHS0rQZIq9UiMjISWq0W8+bNwxNPPIHY2FhoNBo89thjMBgMGD16NABg0qRJSE5Oxs9+9jO89tprMBqNeP7555GTk8PRIKIWuAGrTOqv2i/EOOIdoH+2PO0hIodkDUUrV64EAIwfP15yfPXq1XjooYcAAG+88QbUajWysrJQW1uL9PR0vPPOO7ZrQ0JCsG3bNmRnZ8NgMKBz586YO3cuXn75ZV91g0gxuAGrDC5+AuyZIj3GYmoiv+RX6xTJhesUUbBosAjc/upuGE01DuuKVGjcXmPf4rtYU9RR1mLqS/9sOtbrfuB2708mIQoWAb1OERF5Fzdg9ZEr/wbWq6WBaOJ+BiIiP8dQRBRkuAGrl9kVU8ewmJpIIfxiSj4R+VZGih4Tk3U4WFyB8qoaxEdHYGRSLEeIOoLF1ESKx1BEFKS4AasHsZiaKCAwFBERtZcQwM5xwKV9TcdYTE2kWAxFRETtwZWpiQIOQxERkbuOvwwcX9r0ODQGyCrnrvZECsdQRETkKhZTEwU0hiIiIlewmJoo4DEUERG1xlExde+ZwJj18rWJiLyCoYhIYRosgusL+QqLqYmCCkMRkYLkFZZi2dYilJqadrHXayOwNDOZK1F7GoupiYIOt/kgUoi8wlJkrz0iCUQAYDTVIHvtEeQVlsrUsgBTfxVYp5IGohHvAD/5gYGIKMAxFBEpQINFYNnWIoc721uPLdtahAaLoyvIZRc/sZ9ddq+Rs8uIggRDEZECHCyusBshak4AKDXV4GBxhe8aFUiEAHaMlc4u6z0LeEAAkQnytYuIfIo1RUQKUF7lPBC15zpqhsXURPQjjhQRKUB8dIRHr6MfHV8mDURhXYGZ1xmIiIKUx0LRmTNncNddd3nq5YiomZFJsdBrI+Bs4r0KjbPQRibF+rJZymUrpn6p6diId4D7KlhMTRTEPBaKrly5gvz8fE+9HBE1E6JWYWlmMgDYBSPr46WZyVyvyBUXtrOYmogccrmmaMWKFa2ev3DhQocbQ0TOZaTosXLOULt1inRcp8g1DlemngWMWSdfm4jIr6iEEC7N4VWr1dDr9QgLC3N4/vr16zAajWhoaPBoA33BbDZDq9XCZDJBo9HI3RyiVnFF63aoOgNs7Sc9xmJqIsXz9Pe3yyNFvXv3xquvvoqf/vSnDs8fPXoUw4YN63CDiKh1IWoVDH27yd0M5Ti+TFo7FBYLzDCydoiI7LhcUzRs2DAcPnzY6XmVSgUXB52IiLzPYTH1SuC+ywxEROSQyyNFL7/8Mq5ever0fHJyMoqLiz3SKCKiDrmwHcifKj12r5ELMRJRq1wORcnJya2eDw0NRe/evTvcICKidnNYTP0AMOY9+dpERIrBFa2JgkTAF2g7KqaeVAB0Hy1Pe9oQ8J8HkQIxFBEFgbzCUrup/PpAmsp/7CWgcFnTYz8vpg74z4NIobjNB1GAyyssRfbaI3YbyhpNNcheewR5haUytcwD6qsbi6mbByI/L6YO6M+DSOEYiogCWINFYNnWIjiaF2o9tmxrERosCpw5emE78Pcu0mP3GoH+8+VpjwsC+vMgCgAMRUQB7GBxhd2IRHMCQKmpBgeLK3zXqI4SAthxu3R2We8HgAeE388uC8jPgyiAeGybD6vHH3+83Y0hIs8qr3L+Bdye62SnsGLqlgLu8yAKMC6HojfeeKPNa1QqFUMRkR+Jj47w6HWyOvaSooqpHQmoz4MoALkcirgwI5HyjEyKhV4bAaOpxmEdiwqNG8qOTIr1ddNcV19tXzs0YhXQ/xfytKcDAuLzIApgrCkiCmAhahWWZjYuvNpyBRzr46WZyf67Po7TYmrlBSIgAD4PogDncijavXs3kpOTYTab7c6ZTCbcfPPN2Lt3r0cbR0Qdl5Gix8o5Q6HTSm/J6LQRWDlnqH+ui6PgYuq2KPLzIAoSKuHiLq733HMP7rzzTixatMjh+RUrVuDzzz/Hpk2bPNpAXzCbzdBqtTCZTNBoNHI3h8grFLOCssKLqV2lmM+DyI95+vvb5VDUu3dv5OXlYdCgQQ7Pf/fdd5g0aRJKSko63ChfYygi8hPHXlJ8MTUR+Y6nv79dLrQuKytDaKjzf5g6deqES5cudbhBRBSEAqiYmoiUy+WaohtuuAGFhYVOzx87dgx6Pe+FE5GbLnwcUMXURKRcLoeiKVOm4IUXXkBNjf2iYteuXcPSpUtx9913e7RxRBTAhAA+GwPkN/t3I0CKqYlImVyuKSorK8PQoUMREhKCBQsWYMCAAQAaa4nefvttNDQ04MiRI0hIUN4/ZqwpIvKxICmmJiLvkq2mKCEhAfv370d2djaWLFkCa5ZSqVRIT0/H22+/rchAREQ+dmwpUPhy02MWUxORn3A5FAGNM9C2b9+OH374AadPn4YQAv3790fXrl291T4iChSOiqlH/g/Q71F52kNE1IJbociqa9euGDFihKfbQkSB6sLH0tohAJhRBkTEy9MeIiIHXA5FM2bMcOm6Dz/8sN2NIaIAY12Z+j/7m471fgAY8558bSIicsLlUKTVar3ZDiIKNA6Lqb8Euo+Spz1ERG1wORStXr3am+0gokDSspg6vBtwb6nTYmpueUFE/qBdNUVESsQvXh9oRzF1XmEplm0tQqmpaQ00vTYCSzOTuTkqEfkUQxEFBW988TJktdCOYuq8wlJkrz2CloulGU01yF57hLvGE5FPMRRRwPPGFy9HN5oRAtgxBvhPQdOxG2cDt61t9WkNFoFlW4vsPhcAEABUAJZtLcLEZF1wh00i8hmXt/kgUqK2vniBxi/eBotLC7sDaApZzQMR0BSy8gpL299gpak6DaxXSwPRpC/bDEQAcLC4wu7vsDkBoNRUg4PFFR5oKBFR2xiKKKB5+ovXGyFLsY69CGzt3/Q4vBsw87rLs8vKq5x/Lu25joioo3j7jAKap7943QlZhr7dXHpNxfHQytTx0REevY6IqKMYiiigefqLN+hHNzy4MvXIpFjotREwmmocjrypAOi0jQXsRES+wNtnFNCsX7zOynRVaCyQdvWLN2hHN4QAPjVIA9GNs4EHRLu36ghRq7A0MxkA7D4f6+OlmckssiYin2EoooDm6S9eT4csRbAWU1/+sumYi8XUbclI0WPlnKHQaaUhUqeN4HR8IvI5lRAiCCpCW2c2m6HVamEymaDRaORuDnmBJ6fQW2efAZDc9rEGpY58mfvd2kfHXgQKX2l6HN79x5WpPXvn3e/6TUSK4Onvb4YiMBQFC09+8XpjnSK/WvvIQ8XURETexFDkBQxF1B6eDlmOFpj0xOiT2zxYTE1E5E2e/v6WtaZo7969yMzMRGJiIlQqFTZv3iw5/9BDD0GlUkl+MjIyJNdUVFRg9uzZ0Gg0iImJwbx583DlyhUf9oKCVYhaBUPfbpg25AYY+nZrdyDym7WPvFBMTUSkJLKGourqatxyyy14++23nV6TkZGB0tJS28/69esl52fPno0TJ05gx44d2LZtG/bu3YtHH+UQPymHX6zs7LCY+oBHiqmJiJRC1nWKJk+ejMmTJ7d6TXh4OHQ6ncNz3377LfLy8nDo0CEMHz4cAPDWW29hypQpeP3115GYmOjxNhN5muxrH/momJqIyN/5/ZT8PXv2ID4+HgMGDEB2djYuX75sO1dQUICYmBhbIAKAtLQ0qNVqHDhwwOlr1tbWwmw2S36I5CLb2kf11cA6lTQQjfwfIOsSAxERBSW/DkUZGRn461//il27duHVV19Ffn4+Jk+ejIaGBgCA0WhEfLy01qFTp06IjY2F0Wh0+rq5ubnQarW2n549e3q1H0StkWXtowvb7GeXzSjz+uyyBotAwZnL2HL0AgrOXA6OPeKISDH8+n8HZ86cafvz4MGDkZqair59+2LPnj2YMGFCu193yZIleOKJJ2yPzWYzgxHJxrrAZPbaI1DB8dpHHlvZWQjgs9uktUM3zgFu+1vHX7sNfrXkABGRA349UtRSnz590L17d5w+fRoAoNPpUF5eLrmmvr4eFRUVTuuQgMY6JY1GI/khkpNPVnZ2Wkztm0CUvfaIXUG50VSD7LVHkFdY6vU2EBG1xa9Hilo6f/48Ll++DL2+8QvCYDCgsrIShw8fxrBhwwAAu3fvhsViwahRo+RsKpHbMlL0mJis887KznbF1HHAvRd9UjvU1pIDKjQuOTAxWcdVrIlIVrKGoitXrthGfQCguLgYR48eRWxsLGJjY7Fs2TJkZWVBp9PhzJkzeOaZZ9CvXz+kp6cDAAYNGoSMjAw88sgjWLVqFerq6rBgwQLMnDmTM89IkaxrH3mMw5Wp/wT0e8Rz79EGd5Yc8GjfiYjcJGso+uqrr3DnnXfaHlvrfObOnYuVK1fi2LFjePfdd1FZWYnExERMmjQJr7zyCsLDw23Pee+997BgwQJMmDABarUaWVlZWLFihc/7QuR3LmwD8jOlx2RYmVr2JQeIiFwkaygaP348Wttl5NNPP23zNWJjY7Fu3TpPNotI2RwWU/8MuO2vsjRHtiUHiIjcpKiaIiJqQ9VpYGt/6bFJB4DuI+VpD5qWHDCaahzWFanQWFDu0SUHiIjaQVGzz4ioFd+8IA1E4XHAzDpZAxHQtOQAALu1mDy+5AARUQcwFBEpnXVl6hO/bjo28k9AVrnfrEztkyUHiIg6yD/+xSSi9vGTYmpXeHXJASIiD2AoIlIiPyumdpXHlxwgIvIghiIipTGfArbdJD0mczE1EVEgYCgiUpJvXpDWDkXEA9Mv+E3tEBGRkvFfUiIl8IOVqYmIAh1DEZG/O78V2HuP9JifFlMTESkZQxGRv3JUTJ30IGB4V742EREFMIYiIn/kqJg6/SDQbYQ87SEiCgJcvJHI33zzgjQQRcQ3rkzNQERE5FUcKSLyF3VXgI3R0mMj/xfo91/ytIeIKMgwFBH5AxZTExHJjqGISE5CAJ8ZgMsHmo6xmJqISBYMRURyYTE1EZFfYaE1kRy+eZ7F1EREfoYjRRQwGizC/3dgZzE1EZHfYiiigJBXWIplW4tQaqqxHdNrI7A0MxkZKXoZW9ZMO4upFRH2iIgCAEMRKV5eYSmy1x6BaHHcaKpB9tojWDlnqLzBSAjgs9HA5YNNx1wsplZE2CMiChCsKSJFa7AILNtaZBeIANiOLdtahAaLoyt8wHwKWK+WBqL0gy4Houy1RySBCGgKe3mFpZ5uLRFRUGMoIkU7WFxhFxqaEwBKTTU4WFzhu0ZZdaCY2u/DHhFRAOLtM1K08irngag913mEB4qp3Ql7hr7d2tlQIiJqjqGIFC0+OsKj13XY+Y+AvdOkx2aUAxFxbr2MX4Y9IqIAx9tnpGgjk2Kh10bA2VwsFRoLk0cmxXq3IUIAn46SBqKkB4EHhNuBCPDDsEdEFAQYikjRQtQqLM1MBgC7YGR9vDQz2btT2DtQTO2M34Q9IqIgwlBEipeRosfKOUOh00pHTXTaCO9Px/fSytR+EfaIiIKMSggR9NNXzGYztFotTCYTNBqN3M0hJ9paxNCnixw6KqYe9Weg7zyPvg3XKSIics7T398MRWAoUgK/CgceKqZ2FVe0JiJyjKHICxiK/JuzFautscBnK1Z3YGVqIiLyPE9/f3NKPvm1thYxVKFxEcOJyTq3Rk/cHn0x/wvYNkB6LP0Q0G24y+9JRET+jaGI/FpHFzF0FH52FBnduxX3qQG4/GXT44gEYPp5QM3/fIiIAgn/VSe/1pFFDB3VIcVEhaLyap3dtQ43j62tAP4hDVqWEf8LdX/XV6YmIiLl4JR88mvtXcTQ2WaqjgIR4GA/sW9ftwtEY779P4z5IIkbsRIRBSiOFJGs2qrtsS5iaDTVOKwrUqFxPaLmixi2VofUmsZbcdcQskH6/wqm+s64pej9Hx/UYP7aI5g35kakJevarEXizDEiIuVgKCLZuDLN3rqIYfbaI1ABkqDjbBHDtuqQnLk16jts6veU5Nh/nX0BO82j7K79yxdn8ZcvzrZai+RXywgQEVGbePuMZOHs9pa1tievsBQNFoGCM5dRW2/BwrT+SNCES651tmJ1ezZJ/bDvk3aBqN+xzQ4DkbP2NudK/4iIyL9wpIh8zpVp9s9+eBwvfVQEo7kpVOg0EViUdhNu7B7V6q0odzZJ1YZU4ZubZ0mOnYmZiwl7f+LS81suCwAAX/77Mp79x3GPLyNARETexZEi8jlXptlXXq2TBCIAKDPX4A87/4XwTmoY+nZzGija2kzV6tG4f9gFoj0DD6J8wP9zpRuS9paaavDH3adw+6u7MfvPB1B5zXFBd/PrDxZXuPU+RETkXQxF5HPtub0FOJgh5kTbm6kKnE29G8/pV9uOmxu6IC/1IsYPHeFyqGrpjZ2n3Kplau/fAxEReQdDEfmcO7e3WnJ1lCUjRY+Vc4ZCp5W+V1rcv3E2NVNy7Lub/obOs812xd2AfajypI78PRARkeexpoh8zjoS054ZYlaujLJkpOgxMVlnmxJ/1/fTEF19WHrRzOsYqA51+NyVc4bazR7zBEfLCBARkfwYisgnWq7X89+TB2HBhq/b/XqujrKEqFUw9FAB/+ghPdE/Bxjxx1af2zxU7Sgy4v++OOtwWQB31kNytowAERHJj6GIvM7Rej2xne1HZ1zh9ihL0WvA0cXSY9POAp17u/T0ELUKhr7dYOjbDSOTYu36odNGYOaIXnhj579cej0d1ykiIvJbDEXkVdb1elqOplRUO5+d5YxboyxCAOtblMyFxgA/+cHt97VqeTvOuiwAAGw4VOJ01W2gcc+1t2cNxehWZs0REZG8WGhNXtPe7TaccbZYo51LBfaBaNyWDgUiK+vI0bQhN9iWBWhrtpsKwPIZgzGmf3cGIiIiP8aRIvKa9m63ATTdJnv9vlvwn+pa1/cN+3Q0cPmA9NjM64CDYmpPclaYzdtlRETKwVBEXtPedXia3yYb07+7a0+qrbDb1R43LQCGv9WuNrSHs9trHB0iIlIGhiLyGldniMV2DkNF9XXbY7dHVxwWU38PdO7lalM9xnp7jYiIlIehiDym5bT7Yb27Qq+NcFqAbL1Flv/0nTj8/Q/uj644KqYO6wrcx+0ziIjIfQxF5BGOpt3rtRG45xY9/rS32OH6PkDjLbKwH/cyc8ulAmDHbdJj47YAPe5x+pSWoY23toiIqDmGIuowZ9PujaYa/GlvMR4dl4SPvil1uwDZaYhpRzG1s9DGImgiIrJiKCKb9oyktDbtXqBxROijb0rdvkXmKMQM6Hodn/acIb3wpseA4StabWNroS177RHXpvkTEVHAYygiAO0fSWlr2r11A9e/FZzFQ2OSXLpd5SjE/CLuAyzRr5Fe6EIxtSuhbdnWIkxM1vFWGhFRkOPijWQLIS3DjXUkJa+w1OlzXZ12/8rH3+L2V3e3+lqAoxAjcDb1bkkgMjdEo2GmxaXZZa6GtoPFLM4mIgp2DEVBrq2RFKBxJKXB4nhdalen3QNth6wGi8CaL4ptIWZo1Lc4m5opuWZe8QtIPbHe5RDjamhr75pKREQUOHj7LMi5M5LiaIbYyKTYVqfdt3wtZ7erWt6+29xvEYZEnZI8v9+xzaj/8VfW1RDjamhzJ9wREVFg4khRkOvoSEpr+3454uh2VfPbd9qQKpxNvVsSiFb/JxM3HttmC0SA6yHGGtqctU2Fxtop68auREQUvBiKgpwnRlKs+37ptK6PtlhDVvPbd7+I+wDf3DxLct1t3/4fll38heRY16hQl0NMW5u1Ao1rJbHImoiIZA1Fe/fuRWZmJhITE6FSqbB582bJeSEEXnzxRej1ekRGRiItLQ2nTklvqVRUVGD27NnQaDSIiYnBvHnzcOXKFR/2QtnaGkkBgNjOoTCaa1Bw5rLT2qKMFD32Lb4LL0wd5NL7WkNW4+27a3bF1JX1XXDjsW24WBdv99y2btM5apuj0KbTRnA6PhER2cgaiqqrq3HLLbfg7bffdnj+tddew4oVK7Bq1SocOHAAnTt3Rnp6Ompqmm7lzJ49GydOnMCOHTuwbds27N27F48++qivuqB4rtz+qqiuw6L3j2LW/37Z6gyyELUKD41JQkxU6zvSxzQb6an+T5HDYuohRRucPr/yap3bs8WsoW39I6Px5swhWP/IaOxbfBcDERER2aiEEO7+j7dXqFQqbNq0CdOnTwfQOEqUmJiIJ598Ek899RQAwGQyISEhAWvWrMHMmTPx7bffIjk5GYcOHcLw4cMBAHl5eZgyZQrOnz+PxMREh+9VW1uL2tpa22Oz2YyePXvCZDJBo9F4t6N+ytE6RY5Yg9PbDwyFNjIUBf/+DwQAbXgoKmuuQwUV1hScRXVtg9PX6BwegmNL0xFy7DmgaLnkXPNi6ta8OXMIpg25oc3riIgocJnNZmi1Wo99f/vt7LPi4mIYjUakpaXZjmm1WowaNQoFBQWYOXMmCgoKEBMTYwtEAJCWlga1Wo0DBw7g3nvvdfjaubm5WLZsmdf7oCQZKXpMTNbhYHEFjKZreOXjbyU711tZE3TOOvsVol1WV4WQDdJByv9nnI23ymc5eYI9zhYjIiJP89tCa6PRCABISEiQHE9ISLCdMxqNiI+X1px06tQJsbGxtmscWbJkCUwmk+3n3LlzHm69MoWoVTD07QadNtJhIGquvYFokqYAJ1J+Kjl264n3XA5EnC1GRETe4rcjRd4UHh6O8PBwuZvht7yzkKHA1n4LMTjqjO3I3yvS8Mz5hW6/EmeLERGRN/htKNLpdACAsrIy6PVNxbBlZWUYMmSI7Zry8nLJ8+rr61FRUWF7PrnP07em+oSfx+4B8yXH7j71BxRe6+f2a2nbKOImIiJqL7+9fZaUlASdToddu3bZjpnNZhw4cAAGgwEAYDAYUFlZicOHD9uu2b17NywWC0aNGuXzNgcKV6bpu+oZ3RpJIDLWxaLPsS3tCkQAYLpa1+Z+bERERO0h60jRlStXcPr0advj4uJiHD16FLGxsejVqxcWLlyIX//61+jfvz+SkpLwwgsvIDEx0TZDbdCgQcjIyMAjjzyCVatWoa6uDgsWLMDMmTOdzjyjtlmn6WevPdLu1+isvmpXO/T0uV9h4w8TO9Q27mxPRETeImso+uqrr3DnnXfaHj/xxBMAgLlz52LNmjV45plnUF1djUcffRSVlZW4/fbbkZeXh4iIpts77733HhYsWIAJEyZArVYjKysLK1as8HlfApE2MhSV1+rcft4kTQH+dONvJMduPfEefmjQeqRdbe3HRkRE1B5+s06RnDy9zoHSWfcic/8Xw76Y+v2KiVh8/le2x2oV4GRRbLdxrSIiouDm6e9vv60pInk034vMHX3Cz+NsaqYkEN196g+SQAQAcw29oYLzfch+PuZGt7cKISIi8gS/nX1G8mjci8y9KfnP6Nbgl/Ef2B4b62Jx27erYUGI3bWTbtZjVJ9udqtn67QRWJqZjIwUPRosAn/eVwyjqcZhOFP9eD3XKiIiIk9iKCKbBovAF6f/4/L17hZT6zThGJkUixC1yrZ6dnlVDeKjI2zHAWmhtwrShSK5sz0REXkLQ1GQabAI21Ye/7lyHZXXrkMFoJNajQ2HzsFodm2UqD3F1C/dc7Mk+LRWJG3d2b61ESUiIiJPYigKIq5u+tq6toupW4qJCsXyGYPdDjLN92NzNKJERETkSQxFQaL9M8qatGdl6pzxffHEpAHtDjJtjSgRERF5CkNREGjvjLLmWhZTX7zeHbd/9xeHxdTN3d4/jiM7RESkCAxFQaA9M8qsHBVTP3VuIT74Ia3V53GGGBERKQ1DURBo76737V2ZmjPEiIhIiRiKgoD7ixy6X0zdHGeIERGREjEUBQHrrveu3ELrG34OuwZkS461VUzdXGznUOQ/fSfCOnGxdCIiUhZ+cwUB62KIbd3IWqxbIwlEF693R59jW1wORABQUV2Hw9//0M6WEhERyYehKEhkpOjx9gO3OgxGndVXcTb1bmQ3m1321LmFuO27NW3OLnOkvTVMREREcuLtsyDStXO43bT89hZTt4YbtRIRkRIxFAUR6RYeHSumdoTT8ImISMkYigKcda+z8qoaHPm+AoDjYuqpp/6AE27UDrXk6jT85u3hth1ERORPGIoCSMvAcbmqFi9uLURFdZ3tmsW6NZLaIVdXpm6LK9PwHe29puf0fSIi8hMMRQGirc1e27syNQB0jQpFeCc1jOZa2zG9NgIzR/TCjd2jXBrxcbb3mtFUg+y1R7ByzlAGIyIikhVDUQBoa7PXjhRTqwDkzhjcod3qW9t7Tfz4Hsu2FmFiso630oiISDYMRQrX+mavAtv6L0RKZFMx9frLk7DkwuMuvbY2shNezUq1jeC0d7f6tvZeEwBKTTU4WFzR7vcgIiLqKIYihfvyzGWHgcMTxdTvzB6GMf26d7iNrq5bxPWNiIhITgxFCpZXWIrF/zhud/xZ3WrMj/+H7XF7iqn12giM7uOZURtX1y3i+kZERCQnhiKF2n6sFL9cd0RyrCPF1Fbe2OHeuvea0VTj8DYf1zciIiJ/wG0+FGj7sYvIWS8NROma/XaB6NYT77kViIDGcOLpmWDWvdcA2G0z4o0QRkRE1B4cKVKYvMJS/HLd182OCHzc/1e4OfLftiPuFFMDQFSYGr+5NxU6jfcWU8xI0WPlnKF2ywa4sr4RERGRLzAUKUiDReDZD5tqiDy1MvXV6xboNBFen/mVkaLv0NR+IiIib2IoUpAv/30ZlVcbV6f2RDF1c76a+RWiVnHaPRER+SWGIgXZf/o/Doupnzy3CP/4YUKHXpszv4iIKNgxFClItx+24UTK05JjQ06sQ2WDxulztJGdoFKpYLpax5lfRERErWAoUoCGBgtqtg7Bz0VTPVFbxdRTUhIwe9SNGN23G3YUGZG99ghUgCQYceYXERFRE4YiP5d/aC/uOHUHOjc71lYx9cIJ/bFw4k22x5z5RURE1DaGIj/25T9+jjtqV9seu1JM3TUqFI9N6G93nDO/iIiIWsdQJLMGi7APKg1VwEYtRje7ztVi6t9MH+w06HDmFxERkXMMRTLKKyy1u6U1U3cIy+OXSa5rq5i6uac++Aanyq9gwV39OApERETkBpUQwtGkpKBiNpuh1WphMpmg0bgWPjoqr7AU2WuPNCt87vjK1M3FRIVi+YzBrBciIqKA5envb+59JoMGi8CyrUW2QNQ3/BzOpmZKAtHUU39odyACgMqrdZi/9gjyCks72FoiIqLgwFAkg4PFFbZbZs/q/k+yVceF63Hoc2yL21t1OLNsaxEaLEE/GEhERNQm1hTJoLyqBl3UV1HohZWpWyo11eBgcQULrImIiNrAUOQjzWeZdS77CIUpv5Scd6eY2l2+2teMiIhIyRiKfKBpltk1bO//OJIji23nOlJM7Srua0ZERNQ2hiIvs84y6xN+DmdTsyXn2lqZuqO4rxkREZHrGIq8yDrLbLHu/zA//kPb8QvX4zD2uz/DghCoVYC7ddARnVSoqW/9SdzXjIiIyD0MRV50+NT3KOidJjnWspjaIoDoiE6oqql3+XXbCkQA9zUjIiJyF0ORF/UrmiF57KyY2p1A1JaYqFC8PWsoRvftxhEiIiIiN3CdIi+6FjMOQGMx9Y3HtnltdllzlVfroFarGIiIiIjcxJEiL9Ld8QZGL78bRnOtT993Z5GR6xIRERG5iSNFXtJgEfjj7tMwX6vz2GuOvLGrS9dtOnqBq1gTERG5iSNFXpBXWIpnPzyOyqueC0QAMLpPN5y+VI2K6uutXldRXcdVrImIiNzEkSIPyyssxfy1RzweiADg71+dwz23uDabjKtYExERuYehyIOs6xJ5i9Fci55do1y6lqtYExERuYehyIMOFleg1OTdEZrYLuHQa50HHhUAPVexJiIichtDkQf54paVTtO4KKMKTatWW3EVayIiovZjKPIgb96yaj4ClJGix8o5Q6FrMWKk00Zg5ZyhXMWaiIioHTj7zINGJsVCr43w+C00RyNAGSl6TEzW4WBxBcqrahAf3RiYOEJERETUPgxFHhSiVmFpZjLmrz3i0dd1to9ZiFrFafdEREQewttnHpaRosc7DwyFykMDNovS+mPf4rt4S4yIiMjLGIq8YEqqHm/PurXDr6MCsOHQuY43iIiIiNrEUOQlU1ITkX5zQodeQwAoNdXgYHGFZxpFRERETvl1KHrppZegUqkkPwMHDrSdr6mpQU5ODrp164YuXbogKysLZWVlMrZYqn98F4+8DlenJiIi8j6/DkUAcPPNN6O0tNT2s2/fPtu5RYsWYevWrdi4cSPy8/Nx8eJFzJgxQ8bWShn6dPfI63B1aiIiIu/z+9lnnTp1gk6nsztuMpnwl7/8BevWrcNdd90FAFi9ejUGDRqEL7/8EqNHj/Z1U+2M7tsNMVGhre6DpkLjbTJn53RcnZqIiMgn/H6k6NSpU0hMTESfPn0we/ZslJSUAAAOHz6Muro6pKWl2a4dOHAgevXqhYKCglZfs7a2FmazWfLjDSFqFZbPGNzqNY+OS+Lq1ERERH7Ar0PRqFGjsGbNGuTl5WHlypUoLi7G2LFjUVVVBaPRiLCwMMTExEiek5CQAKPR2Orr5ubmQqvV2n569uzptT5kpOixas5Q6DThkuM6TThWzRmKJVOSuTo1ERGRH1AJIZzdvfE7lZWV6N27N37/+98jMjISDz/8MGprayXXjBw5EnfeeSdeffVVp69TW1sreZ7ZbEbPnj1hMpmg0Wi80vYGi2h19em2zhMREZGU2WyGVqv12Pe339cUNRcTE4ObbroJp0+fxsSJE3H9+nVUVlZKRovKysoc1iA1Fx4ejvDw8Fav8bS2Vp/m6tRERETy8uvbZy1duXIFZ86cgV6vx7BhwxAaGopdu3bZzp88eRIlJSUwGAwytpKIiIiUyK9Hip566ilkZmaid+/euHjxIpYuXYqQkBDMmjULWq0W8+bNwxNPPIHY2FhoNBo89thjMBgMfjHzjIiIiJTFr0PR+fPnMWvWLFy+fBlxcXG4/fbb8eWXXyIuLg4A8MYbb0CtViMrKwu1tbVIT0/HO++8I3OriYiISIkUVWjtLZ4u1CIiIiLv8/T3t6JqioiIiIi8haGIiIiICAxFRERERAAYioiIiIgAMBQRERERAfDzKfm+Yp2A562NYYmIiMjzrN/bnppIz1AEoKqqCgC8ujEsEREReUdVVRW0Wm2HX4frFAGwWCy4ePEioqOjoVJ5fhNW64az586dC+h1kIKln0Dw9DVY+gkET1+DpZ8A+xqIWvZTCIGqqiokJiZCre54RRBHigCo1Wr06NHD6++j0WgC+pfVKlj6CQRPX4Oln0Dw9DVY+gmwr4GoeT89MUJkxUJrIiIiIjAUEREREQFgKPKJ8PBwLF26FOHh4XI3xauCpZ9A8PQ1WPoJBE9fg6WfAPsaiLzdTxZaExEREYEjRUREREQAGIqIiIiIADAUEREREQFgKCIiIiICwFDkMS+99BJUKpXkZ+DAgbbzNTU1yMnJQbdu3dClSxdkZWWhrKxMxha7bu/evcjMzERiYiJUKhU2b94sOS+EwIsvvgi9Xo/IyEikpaXh1KlTkmsqKiowe/ZsaDQaxMTEYN68ebhy5YoPe9G2tvr50EMP2X3GGRkZkmuU0M/c3FyMGDEC0dHRiI+Px/Tp03Hy5EnJNa78vpaUlGDq1KmIiopCfHw8nn76adTX1/uyK21ypa/jx4+3+1znz58vucbf+7py5UqkpqbaFrQzGAz45JNPbOcD5fME2u5rIHyejixfvhwqlQoLFy60HQukz7U5R3312ecqyCOWLl0qbr75ZlFaWmr7uXTpku38/PnzRc+ePcWuXbvEV199JUaPHi1uu+02GVvsuu3bt4v//u//Fh9++KEAIDZt2iQ5v3z5cqHVasXmzZvFN998I+655x6RlJQkrl27ZrsmIyND3HLLLeLLL78U//znP0W/fv3ErFmzfNyT1rXVz7lz54qMjAzJZ1xRUSG5Rgn9TE9PF6tXrxaFhYXi6NGjYsqUKaJXr17iypUrtmva+n2tr68XKSkpIi0tTXz99ddi+/btonv37mLJkiVydMkpV/p6xx13iEceeUTyuZpMJtt5JfT1o48+Eh9//LH417/+JU6ePCmee+45ERoaKgoLC4UQgfN5CtF2XwPh82zp4MGD4sYbbxSpqaniV7/6le14IH2uVs766qvPlaHIQ5YuXSpuueUWh+cqKytFaGio2Lhxo+3Yt99+KwCIgoICH7XQM1qGBYvFInQ6nfjd735nO1ZZWSnCw8PF+vXrhRBCFBUVCQDi0KFDtms++eQToVKpxIULF3zWdnc4C0XTpk1z+hwl9lMIIcrLywUAkZ+fL4Rw7fd1+/btQq1WC6PRaLtm5cqVQqPRiNraWt92wA0t+ypE4z+2zf/xbUmpfe3atav485//HNCfp5W1r0IE3udZVVUl+vfvL3bs2CHpWyB+rs76KoTvPlfePvOgU6dOITExEX369MHs2bNRUlICADh8+DDq6uqQlpZmu3bgwIHo1asXCgoK5GquRxQXF8NoNEr6ptVqMWrUKFvfCgoKEBMTg+HDh9uuSUtLg1qtxoEDB3ze5o7Ys2cP4uPjMWDAAGRnZ+Py5cu2c0rtp8lkAgDExsYCcO33taCgAIMHD0ZCQoLtmvT0dJjNZpw4ccKHrXdPy75avffee+jevTtSUlKwZMkSXL161XZOaX1taGjAhg0bUF1dDYPBENCfZ8u+WgXS55mTk4OpU6dKPj8gMP87ddZXK198rtwQ1kNGjRqFNWvWYMCAASgtLcWyZcswduxYFBYWwmg0IiwsDDExMZLnJCQkwGg0ytNgD7G2v/kvovWx9ZzRaER8fLzkfKdOnRAbG6uo/mdkZGDGjBlISkrCmTNn8Nxzz2Hy5MkoKChASEiIIvtpsViwcOFCjBkzBikpKQDg0u+r0Wh0+Jlbz/kjR30FgAceeAC9e/dGYmIijh07hsWLF+PkyZP48MMPASinr8ePH4fBYEBNTQ26dOmCTZs2ITk5GUePHg24z9NZX4HA+TwBYMOGDThy5AgOHTpkdy7Q/jttra+A7z5XhiIPmTx5su3PqampGDVqFHr37o2///3viIyMlLFl5CkzZ860/Xnw4MFITU1F3759sWfPHkyYMEHGlrVfTk4OCgsLsW/fPrmb4nXO+vroo4/a/jx48GDo9XpMmDABZ86cQd++fX3dzHYbMGAAjh49CpPJhA8++ABz585Ffn6+3M3yCmd9TU5ODpjP89y5c/jVr36FHTt2ICIiQu7meJUrffXV58rbZ14SExODm266CadPn4ZOp8P169dRWVkpuaasrAw6nU6eBnqItf0tZzw075tOp0N5ebnkfH19PSoqKhTd/z59+qB79+44ffo0AOX1c8GCBdi2bRs+//xz9OjRw3bcld9XnU7n8DO3nvM3zvrqyKhRowBA8rkqoa9hYWHo168fhg0bhtzcXNxyyy148803A/LzdNZXR5T6eR4+fBjl5eUYOnQoOnXqhE6dOiE/Px8rVqxAp06dkJCQEDCfa1t9bWhosHuOtz5XhiIvuXLlCs6cOQO9Xo9hw4YhNDQUu3btsp0/efIkSkpKJPfBlSgpKQk6nU7SN7PZjAMHDtj6ZjAYUFlZicOHD9uu2b17NywWi+0XW4nOnz+Py5cvQ6/XA1BOP4UQWLBgATZt2oTdu3cjKSlJct6V31eDwYDjx49LQuCOHTug0WhstzH8QVt9deTo0aMAIPlcldDXliwWC2prawPq83TG2ldHlPp5TpgwAcePH8fRo0dtP8OHD8fs2bNtfw6Uz7WtvoaEhNg9x2ufq/v14eTIk08+Kfbs2SOKi4vFF198IdLS0kT37t1FeXm5EKJx6mSvXr3E7t27xVdffSUMBoMwGAwyt9o1VVVV4uuvvxZff/21ACB+//vfi6+//lp8//33QojGKfkxMTFiy5Yt4tixY2LatGkOp+Tfeuut4sCBA2Lfvn2if//+fjdVvbV+VlVViaeeekoUFBSI4uJisXPnTjF06FDRv39/UVNTY3sNJfQzOztbaLVasWfPHsn01qtXr9quaev31Tr9ddKkSeLo0aMiLy9PxMXF+d1U37b6evr0afHyyy+Lr776ShQXF4stW7aIPn36iHHjxtleQwl9ffbZZ0V+fr4oLi4Wx44dE88++6xQqVTis88+E0IEzucpROt9DZTP05mWM7AC6XNtqXlfffm5MhR5yP333y/0er0ICwsTN9xwg7j//vvF6dOnbeevXbsmfvnLX4quXbuKqKgoce+994rS0lIZW+y6zz//XACw+5k7d64QonFa/gsvvCASEhJEeHi4mDBhgjh58qTkNS5fvixmzZolunTpIjQajXj44YdFVVWVDL1xrrV+Xr16VUyaNEnExcWJ0NBQ0bt3b/HII49Ipn8KoYx+OuojALF69WrbNa78vp49e1ZMnjxZREZGiu7du4snn3xS1NXV+bg3rWurryUlJWLcuHEiNjZWhIeHi379+omnn35asv6JEP7f15///Oeid+/eIiwsTMTFxYkJEybYApEQgfN5CtF6XwPl83SmZSgKpM+1peZ99eXnqhJCCNfHlYiIiIgCE2uKiIiIiMBQRERERASAoYiIiIgIAEMREREREQCGIiIiIiIADEVEREREABiKiIiIiAAwFBEREREBYCgiIuqQhx56CNOnT5e7GUTkAQxFROQVDz30EFQqFZYvXy45vnnzZqhUKpla1X5nz56FSqWybURJRIGHoYiIvCYiIgKvvvoqfvjhB7mbQkTUJoYiIvKatLQ06HQ65ObmOr1m3759GDt2LCIjI9GzZ088/vjjqK6uBgD88Y9/REpKiu1a6yjTqlWrJO/x/PPP2x5v3boVI0aMQEREBLp37457773Xdu5vf/sbhg8fjujoaOh0OjzwwAMoLy+3nf/hhx8we/ZsxMXFITIyEv3798fq1asBAElJSQCAW2+9FSqVCuPHj3fYH4vFgtzcXCQlJSEyMhK33HILPvjgAzf+1ohILgxFROQ1ISEh+O1vf4u33noL58+ftzt/5swZZGRkICsrC8eOHcP777+Pffv2YcGCBQCAO+64A0VFRbh06RIAID8/H927d8eePXsAAHV1dSgoKLAFlI8//hj33nsvpkyZgq+//hq7du3CyJEjbe9XV1eHV155Bd988w02b96Ms2fP4qGHHrKdf+GFF1BUVIRPPvkE3377LVauXInu3bsDAA4ePAgA2LlzJ0pLS/Hhhx867HNubi7++te/YtWqVThx4gQWLVqEOXPmID8/v0N/l0TkA4KIyAvmzp0rpk2bJoQQYvTo0eLnP/+5EEKITZs2Ces/PfPmzROPPvqo5Hn//Oc/hVqtFteuXRMWi0V069ZNbNy4UQghxJAhQ0Rubq7Q6XRCCCH27dsnQkNDRXV1tRBCCIPBIGbPnu1yGw8dOiQAiKqqKiGEEJmZmeLhhx92eG1xcbEAIL7++mun/aypqRFRUVFi//79kmvmzZsnZs2a5XK7iEgeHCkiIq979dVX8e677+Lbb7+VHP/mm2+wZs0adOnSxfaTnp4Oi8WC4uJiqFQqjBs3Dnv27EFlZSWKiorwy1/+ErW1tfjuu++Qn5+PESNGICoqCgBw9OhRTJgwwWk7Dh8+jMzMTPTq1QvR0dG44447AAAlJSUAgOzsbGzYsAFDhgzBM888g/3797vVz9OnT+Pq1auYOHGipE9//etfcebMGbdei4h8r5PcDSCiwDdu3Dikp6djyZIlkttVV65cwS9+8Qs8/vjjds/p1asXAGD8+PH405/+hH/+85+49dZbodFobEEpPz/fFmwAIDIy0mkbqqurkZ6ejvT0dLz33nuIi4tDSUkJ0tPTcf36dQDA5MmT8f3332P79u3YsWMHJkyYgJycHLz++usu9fPKlSsAGm/j3XDDDZJz4eHhLr0GEcmHoYiIfGL58uUYMmQIBgwYYDs2dOhQFBUVoV+/fk6fd8cdd2DhwoXYuHGjrXZo/Pjx2LlzJ7744gs8+eSTtmtTU1Oxa9cuPPzww3av89133+Hy5ctYvnw5evbsCQD46quv7K6Li4vD3LlzMXfuXIwdOxZPP/00Xn/9dYSFhQEAGhoanLY1OTkZ4eHhKCkpkYQ1IlIGhiIi8onBgwdj9uzZWLFihe3Y4sWLMXr0aCxYsAD/9V//hc6dO6OoqAg7duzAH//4RwCNQadr165Yt24dtm3bBqAxFD311FNQqVQYM2aM7fWWLl2KCRMmoG/fvpg5cybq6+uxfft2LF68GL169UJYWBjeeustzJ8/H4WFhXjllVckbXzxxRcxbNgw3HzzzaitrcW2bdswaNAgAEB8fDwiIyORl5eHHj16ICIiAlqtVvL86OhoPPXUU1i0aBEsFgtuv/12mEwmfPHFF9BoNJg7d65X/m6JyDNYU0REPvPyyy/DYrHYHqempiI/Px//+te/MHbsWNx666148cUXkZiYaLtGpVJh7NixUKlUuP32223P02g0GD58ODp37my7dvz48di4cSM++ugjDBkyBHfddZdt1lhcXBzWrFmDjRs3Ijk5GcuXL7e7LRYWFoYlS5YgNTUV48aNQ0hICDZs2AAA6NSpE1asWIH/+Z//QWJiIqZNm+awj6+88gpeeOEF5ObmYtCgQcjIyMDHH39sm9JPRP5LJYQQcjeCiIiISG4cKSIiIiICQxERERERAIYiIiIiIgAMRUREREQAGIqIiIiIADAUEREREQFgKCIiIiICwFBEREREBIChiIiIiAgAQxERERERAIYiIiIiIgDA/wfaBA6fb5vNOwAAAABJRU5ErkJggg==",
|
176 |
"text/plain": [
|
177 |
"<Figure size 640x480 with 1 Axes>"
|
178 |
]
|
|
|
182 |
}
|
183 |
],
|
184 |
"source": [
|
185 |
+
"x = df.newcastle\n",
|
186 |
+
"y = df.ICI_1\n",
|
187 |
+
"\n",
|
188 |
+
"slope, intercept, r, p, std_err = stats.linregress(x, y)\n",
|
189 |
+
"\n",
|
190 |
+
"def myfunc(x):\n",
|
191 |
+
" return slope * x + intercept\n",
|
192 |
+
"\n",
|
193 |
+
"mymodel = list(map(myfunc, x))\n",
|
194 |
+
"\n",
|
195 |
"plt.scatter(x, y)\n",
|
196 |
+
"plt.plot(x, mymodel, color='orange')\n",
|
197 |
+
"plt.xlabel(\"Newcastle\")\n",
|
198 |
+
"plt.ylabel(\"ICI 1\")\n",
|
199 |
"plt.show()"
|
200 |
]
|
201 |
},
|