diff --git a/prereise/gather/solardata/nsrdb/demo/nsrdb_sam_demo.ipynb b/prereise/gather/solardata/nsrdb/demo/nsrdb_sam_demo.ipynb
index b092fddc3..e224a3b55 100644
--- a/prereise/gather/solardata/nsrdb/demo/nsrdb_sam_demo.ipynb
+++ b/prereise/gather/solardata/nsrdb/demo/nsrdb_sam_demo.ipynb
@@ -154,7 +154,7 @@
        "      <td>12.00</td>\n",
        "      <td>1</td>\n",
        "      <td>10.0</td>\n",
-       "      <td>3.00</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>...</td>\n",
        "      <td>solar</td>\n",
        "      <td>Texas</td>\n",
@@ -178,7 +178,7 @@
        "      <td>1.80</td>\n",
        "      <td>0</td>\n",
        "      <td>1.5</td>\n",
-       "      <td>0.45</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>...</td>\n",
        "      <td>solar</td>\n",
        "      <td>Texas</td>\n",
@@ -202,7 +202,7 @@
        "      <td>276.00</td>\n",
        "      <td>0</td>\n",
        "      <td>230.0</td>\n",
-       "      <td>69.00</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>...</td>\n",
        "      <td>solar</td>\n",
        "      <td>Texas</td>\n",
@@ -226,7 +226,7 @@
        "      <td>47.52</td>\n",
        "      <td>1</td>\n",
        "      <td>39.6</td>\n",
-       "      <td>11.88</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>...</td>\n",
        "      <td>solar</td>\n",
        "      <td>Texas</td>\n",
@@ -250,7 +250,7 @@
        "      <td>1.68</td>\n",
        "      <td>1</td>\n",
        "      <td>1.4</td>\n",
-       "      <td>0.42</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>...</td>\n",
        "      <td>solar</td>\n",
        "      <td>Texas</td>\n",
@@ -269,13 +269,13 @@
        "</div>"
       ],
       "text/plain": [
-       "           bus_id     Pg   Qg  Qmax  Qmin    Vg   mBase  status   Pmax   Pmin  \\\n",
-       "plant_id                                                                        \n",
-       "12878     3001011   9.99  0.0   0.0   0.0  1.00   12.00       1   10.0   3.00   \n",
-       "12896     3001062   0.00  0.0   0.0   0.0  1.01    1.80       0    1.5   0.45   \n",
-       "12897     3001063   0.00  0.0   0.0   0.0  1.01  276.00       0  230.0  69.00   \n",
-       "12984     3003120  29.70  0.0   0.0   0.0  1.00   47.52       1   39.6  11.88   \n",
-       "13161     3006085   1.05  0.0   0.0   0.0  1.04    1.68       1    1.4   0.42   \n",
+       "           bus_id     Pg   Qg  Qmax  Qmin    Vg   mBase  status   Pmax  Pmin  \\\n",
+       "plant_id                                                                       \n",
+       "12878     3001011   9.99  0.0   0.0   0.0  1.00   12.00       1   10.0   0.0   \n",
+       "12896     3001062   0.00  0.0   0.0   0.0  1.01    1.80       0    1.5   0.0   \n",
+       "12897     3001063   0.00  0.0   0.0   0.0  1.01  276.00       0  230.0   0.0   \n",
+       "12984     3003120  29.70  0.0   0.0   0.0  1.00   47.52       1   39.6   0.0   \n",
+       "13161     3006085   1.05  0.0   0.0   0.0  1.04    1.68       1    1.4   0.0   \n",
        "\n",
        "          ...   type  interconnect  GenFuelCost  GenIOB  GenIOC  GenIOD  \\\n",
        "plant_id  ...                                                             \n",
@@ -314,12 +314,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "There are 36 solar plants in the Eastern interconnection.\n"
+      "There are 36 solar plants in the Texas interconnection.\n"
      ]
     }
    ],
    "source": [
-    "print(\"There are %d solar plants in the Eastern interconnection.\" % len(solar_plant))"
+    "print(\"There are %d solar plants in the Texas interconnection.\" % len(solar_plant))"
    ]
   },
   {
@@ -339,7 +339,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "email=brdo@intven.com\n",
+      "email=daniel@breakthroughenergy.org\n",
       "api_key=········\n"
      ]
     }
@@ -358,12 +358,12 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 17/17 [00:44<00:00,  2.42s/it]\n"
+      "100%|██████████████████████████████████████████| 17/17 [00:51<00:00,  3.14s/it]\n"
      ]
     }
    ],
    "source": [
-    "data = sam.retrieve_data(solar_plant, email, key)"
+    "data = sam.retrieve_data_blended(email, key, grid=grid)"
    ]
   },
   {
@@ -392,179 +392,605 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>Pout</th>\n",
-       "      <th>plant_id</th>\n",
-       "      <th>ts</th>\n",
-       "      <th>ts_id</th>\n",
+       "      <th>12878</th>\n",
+       "      <th>12896</th>\n",
+       "      <th>12897</th>\n",
+       "      <th>12984</th>\n",
+       "      <th>13161</th>\n",
+       "      <th>13162</th>\n",
+       "      <th>13163</th>\n",
+       "      <th>13164</th>\n",
+       "      <th>13165</th>\n",
+       "      <th>13166</th>\n",
+       "      <th>...</th>\n",
+       "      <th>13997</th>\n",
+       "      <th>13998</th>\n",
+       "      <th>13999</th>\n",
+       "      <th>14000</th>\n",
+       "      <th>14001</th>\n",
+       "      <th>14002</th>\n",
+       "      <th>14003</th>\n",
+       "      <th>14004</th>\n",
+       "      <th>14005</th>\n",
+       "      <th>14006</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>12878</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>12896</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>12897</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>12984</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13161</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13162</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
+       "      <th>2016-01-01 00:00:00</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13163</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
+       "      <th>2016-01-01 01:00:00</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13164</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
+       "      <th>2016-01-01 02:00:00</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13165</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
+       "      <th>2016-01-01 03:00:00</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13166</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
+       "      <th>2016-01-01 04:00:00</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13237</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
+       "      <th>2016-01-01 05:00:00</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>11</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13238</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
+       "      <th>2016-01-01 06:00:00</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13239</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
+       "      <th>2016-01-01 07:00:00</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>13</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13240</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
+       "      <th>2016-01-01 08:00:00</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>14</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13308</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
+       "      <th>2016-01-01 09:00:00</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13309</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
+       "      <th>2016-01-01 10:00:00</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>16</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13310</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
+       "      <th>2016-01-01 11:00:00</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>17</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13311</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
+       "      <th>2016-01-01 12:00:00</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>18</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13312</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
+       "      <th>2016-01-01 13:00:00</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>19</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13313</td>\n",
-       "      <td>2016-01-01</td>\n",
-       "      <td>1</td>\n",
+       "      <th>2016-01-01 14:00:00</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.059885</td>\n",
+       "      <td>0.042145</td>\n",
+       "      <td>0.042145</td>\n",
+       "      <td>0.042145</td>\n",
+       "      <td>0.042145</td>\n",
+       "      <td>0.042145</td>\n",
+       "      <td>0.042145</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2016-01-01 15:00:00</th>\n",
+       "      <td>0.050717</td>\n",
+       "      <td>0.054200</td>\n",
+       "      <td>0.054200</td>\n",
+       "      <td>0.113199</td>\n",
+       "      <td>0.076352</td>\n",
+       "      <td>0.076352</td>\n",
+       "      <td>0.076352</td>\n",
+       "      <td>0.076352</td>\n",
+       "      <td>0.076352</td>\n",
+       "      <td>0.076352</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.213463</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.041453</td>\n",
+       "      <td>0.016044</td>\n",
+       "      <td>0.036233</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.236540</td>\n",
+       "      <td>0.041453</td>\n",
+       "      <td>0.042298</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2016-01-01 16:00:00</th>\n",
+       "      <td>0.110172</td>\n",
+       "      <td>0.390702</td>\n",
+       "      <td>0.390702</td>\n",
+       "      <td>0.285293</td>\n",
+       "      <td>0.399805</td>\n",
+       "      <td>0.399805</td>\n",
+       "      <td>0.399805</td>\n",
+       "      <td>0.399805</td>\n",
+       "      <td>0.399805</td>\n",
+       "      <td>0.399805</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.408348</td>\n",
+       "      <td>0.184071</td>\n",
+       "      <td>0.184071</td>\n",
+       "      <td>0.065924</td>\n",
+       "      <td>0.233065</td>\n",
+       "      <td>0.081087</td>\n",
+       "      <td>0.184071</td>\n",
+       "      <td>0.007065</td>\n",
+       "      <td>0.065924</td>\n",
+       "      <td>0.249503</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2016-01-01 17:00:00</th>\n",
+       "      <td>0.206698</td>\n",
+       "      <td>0.338267</td>\n",
+       "      <td>0.338267</td>\n",
+       "      <td>0.242969</td>\n",
+       "      <td>0.631615</td>\n",
+       "      <td>0.631615</td>\n",
+       "      <td>0.631615</td>\n",
+       "      <td>0.631615</td>\n",
+       "      <td>0.631615</td>\n",
+       "      <td>0.631615</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.031129</td>\n",
+       "      <td>0.064183</td>\n",
+       "      <td>0.064183</td>\n",
+       "      <td>0.214012</td>\n",
+       "      <td>0.171571</td>\n",
+       "      <td>0.119463</td>\n",
+       "      <td>0.064183</td>\n",
+       "      <td>0.097522</td>\n",
+       "      <td>0.214012</td>\n",
+       "      <td>0.163943</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2016-01-01 18:00:00</th>\n",
+       "      <td>0.129504</td>\n",
+       "      <td>0.401456</td>\n",
+       "      <td>0.401456</td>\n",
+       "      <td>0.141671</td>\n",
+       "      <td>0.142196</td>\n",
+       "      <td>0.142196</td>\n",
+       "      <td>0.142196</td>\n",
+       "      <td>0.142196</td>\n",
+       "      <td>0.142196</td>\n",
+       "      <td>0.142196</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.095960</td>\n",
+       "      <td>0.296626</td>\n",
+       "      <td>0.296626</td>\n",
+       "      <td>0.192276</td>\n",
+       "      <td>0.067980</td>\n",
+       "      <td>0.151283</td>\n",
+       "      <td>0.296626</td>\n",
+       "      <td>0.245919</td>\n",
+       "      <td>0.192276</td>\n",
+       "      <td>0.209212</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2016-01-01 19:00:00</th>\n",
+       "      <td>0.076174</td>\n",
+       "      <td>0.384640</td>\n",
+       "      <td>0.384640</td>\n",
+       "      <td>0.213146</td>\n",
+       "      <td>0.126637</td>\n",
+       "      <td>0.126637</td>\n",
+       "      <td>0.126637</td>\n",
+       "      <td>0.126637</td>\n",
+       "      <td>0.126637</td>\n",
+       "      <td>0.126637</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.040535</td>\n",
+       "      <td>0.188210</td>\n",
+       "      <td>0.188210</td>\n",
+       "      <td>0.286320</td>\n",
+       "      <td>0.101564</td>\n",
+       "      <td>0.234526</td>\n",
+       "      <td>0.188210</td>\n",
+       "      <td>0.162571</td>\n",
+       "      <td>0.286320</td>\n",
+       "      <td>0.343501</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
+       "<p>20 rows × 36 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "    Pout  plant_id         ts  ts_id\n",
-       "0    0.0     12878 2016-01-01      1\n",
-       "1    0.0     12896 2016-01-01      1\n",
-       "2    0.0     12897 2016-01-01      1\n",
-       "3    0.0     12984 2016-01-01      1\n",
-       "4    0.0     13161 2016-01-01      1\n",
-       "5    0.0     13162 2016-01-01      1\n",
-       "6    0.0     13163 2016-01-01      1\n",
-       "7    0.0     13164 2016-01-01      1\n",
-       "8    0.0     13165 2016-01-01      1\n",
-       "9    0.0     13166 2016-01-01      1\n",
-       "10   0.0     13237 2016-01-01      1\n",
-       "11   0.0     13238 2016-01-01      1\n",
-       "12   0.0     13239 2016-01-01      1\n",
-       "13   0.0     13240 2016-01-01      1\n",
-       "14   0.0     13308 2016-01-01      1\n",
-       "15   0.0     13309 2016-01-01      1\n",
-       "16   0.0     13310 2016-01-01      1\n",
-       "17   0.0     13311 2016-01-01      1\n",
-       "18   0.0     13312 2016-01-01      1\n",
-       "19   0.0     13313 2016-01-01      1"
+       "                        12878     12896     12897     12984     13161  \\\n",
+       "2016-01-01 00:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 01:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 02:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 03:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 04:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 05:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 06:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 07:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 08:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 09:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 10:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 11:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 12:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 13:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 14:00:00  0.000000  0.000000  0.000000  0.059885  0.042145   \n",
+       "2016-01-01 15:00:00  0.050717  0.054200  0.054200  0.113199  0.076352   \n",
+       "2016-01-01 16:00:00  0.110172  0.390702  0.390702  0.285293  0.399805   \n",
+       "2016-01-01 17:00:00  0.206698  0.338267  0.338267  0.242969  0.631615   \n",
+       "2016-01-01 18:00:00  0.129504  0.401456  0.401456  0.141671  0.142196   \n",
+       "2016-01-01 19:00:00  0.076174  0.384640  0.384640  0.213146  0.126637   \n",
+       "\n",
+       "                        13162     13163     13164     13165     13166  ...  \\\n",
+       "2016-01-01 00:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  ...   \n",
+       "2016-01-01 01:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  ...   \n",
+       "2016-01-01 02:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  ...   \n",
+       "2016-01-01 03:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  ...   \n",
+       "2016-01-01 04:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  ...   \n",
+       "2016-01-01 05:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  ...   \n",
+       "2016-01-01 06:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  ...   \n",
+       "2016-01-01 07:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  ...   \n",
+       "2016-01-01 08:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  ...   \n",
+       "2016-01-01 09:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  ...   \n",
+       "2016-01-01 10:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  ...   \n",
+       "2016-01-01 11:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  ...   \n",
+       "2016-01-01 12:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  ...   \n",
+       "2016-01-01 13:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  ...   \n",
+       "2016-01-01 14:00:00  0.042145  0.042145  0.042145  0.042145  0.042145  ...   \n",
+       "2016-01-01 15:00:00  0.076352  0.076352  0.076352  0.076352  0.076352  ...   \n",
+       "2016-01-01 16:00:00  0.399805  0.399805  0.399805  0.399805  0.399805  ...   \n",
+       "2016-01-01 17:00:00  0.631615  0.631615  0.631615  0.631615  0.631615  ...   \n",
+       "2016-01-01 18:00:00  0.142196  0.142196  0.142196  0.142196  0.142196  ...   \n",
+       "2016-01-01 19:00:00  0.126637  0.126637  0.126637  0.126637  0.126637  ...   \n",
+       "\n",
+       "                        13997     13998     13999     14000     14001  \\\n",
+       "2016-01-01 00:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 01:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 02:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 03:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 04:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 05:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 06:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 07:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 08:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 09:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 10:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 11:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 12:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 13:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 14:00:00  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "2016-01-01 15:00:00  0.213463  0.000000  0.000000  0.041453  0.016044   \n",
+       "2016-01-01 16:00:00  0.408348  0.184071  0.184071  0.065924  0.233065   \n",
+       "2016-01-01 17:00:00  0.031129  0.064183  0.064183  0.214012  0.171571   \n",
+       "2016-01-01 18:00:00  0.095960  0.296626  0.296626  0.192276  0.067980   \n",
+       "2016-01-01 19:00:00  0.040535  0.188210  0.188210  0.286320  0.101564   \n",
+       "\n",
+       "                        14002     14003     14004     14005     14006  \n",
+       "2016-01-01 00:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  \n",
+       "2016-01-01 01:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  \n",
+       "2016-01-01 02:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  \n",
+       "2016-01-01 03:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  \n",
+       "2016-01-01 04:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  \n",
+       "2016-01-01 05:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  \n",
+       "2016-01-01 06:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  \n",
+       "2016-01-01 07:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  \n",
+       "2016-01-01 08:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  \n",
+       "2016-01-01 09:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  \n",
+       "2016-01-01 10:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  \n",
+       "2016-01-01 11:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  \n",
+       "2016-01-01 12:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  \n",
+       "2016-01-01 13:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  \n",
+       "2016-01-01 14:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  \n",
+       "2016-01-01 15:00:00  0.036233  0.000000  0.236540  0.041453  0.042298  \n",
+       "2016-01-01 16:00:00  0.081087  0.184071  0.007065  0.065924  0.249503  \n",
+       "2016-01-01 17:00:00  0.119463  0.064183  0.097522  0.214012  0.163943  \n",
+       "2016-01-01 18:00:00  0.151283  0.296626  0.245919  0.192276  0.209212  \n",
+       "2016-01-01 19:00:00  0.234526  0.188210  0.162571  0.286320  0.343501  \n",
+       "\n",
+       "[20 rows x 36 columns]"
       ]
      },
      "execution_count": 7,
@@ -602,74 +1028,269 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>Pout</th>\n",
-       "      <th>plant_id</th>\n",
-       "      <th>ts_id</th>\n",
+       "      <th>12878</th>\n",
+       "      <th>12896</th>\n",
+       "      <th>12897</th>\n",
+       "      <th>12984</th>\n",
+       "      <th>13161</th>\n",
+       "      <th>13162</th>\n",
+       "      <th>13163</th>\n",
+       "      <th>13164</th>\n",
+       "      <th>13165</th>\n",
+       "      <th>13166</th>\n",
+       "      <th>...</th>\n",
+       "      <th>13997</th>\n",
+       "      <th>13998</th>\n",
+       "      <th>13999</th>\n",
+       "      <th>14000</th>\n",
+       "      <th>14001</th>\n",
+       "      <th>14002</th>\n",
+       "      <th>14003</th>\n",
+       "      <th>14004</th>\n",
+       "      <th>14005</th>\n",
+       "      <th>14006</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>count</th>\n",
-       "      <td>316224.000000</td>\n",
-       "      <td>316224.000000</td>\n",
-       "      <td>316224.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
+       "      <td>8784.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>mean</th>\n",
-       "      <td>0.287262</td>\n",
-       "      <td>13506.527778</td>\n",
-       "      <td>4392.500000</td>\n",
+       "      <td>0.319473</td>\n",
+       "      <td>0.305552</td>\n",
+       "      <td>0.305552</td>\n",
+       "      <td>0.280769</td>\n",
+       "      <td>0.275564</td>\n",
+       "      <td>0.275564</td>\n",
+       "      <td>0.275564</td>\n",
+       "      <td>0.275564</td>\n",
+       "      <td>0.275564</td>\n",
+       "      <td>0.275564</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.310299</td>\n",
+       "      <td>0.302906</td>\n",
+       "      <td>0.302906</td>\n",
+       "      <td>0.313706</td>\n",
+       "      <td>0.313175</td>\n",
+       "      <td>0.315599</td>\n",
+       "      <td>0.302906</td>\n",
+       "      <td>0.317617</td>\n",
+       "      <td>0.313706</td>\n",
+       "      <td>0.297031</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>std</th>\n",
-       "      <td>0.370628</td>\n",
-       "      <td>410.426139</td>\n",
-       "      <td>2535.726375</td>\n",
+       "      <td>0.392525</td>\n",
+       "      <td>0.384133</td>\n",
+       "      <td>0.384133</td>\n",
+       "      <td>0.365295</td>\n",
+       "      <td>0.363075</td>\n",
+       "      <td>0.363075</td>\n",
+       "      <td>0.363075</td>\n",
+       "      <td>0.363075</td>\n",
+       "      <td>0.363075</td>\n",
+       "      <td>0.363075</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.389951</td>\n",
+       "      <td>0.385331</td>\n",
+       "      <td>0.385331</td>\n",
+       "      <td>0.391299</td>\n",
+       "      <td>0.390747</td>\n",
+       "      <td>0.393994</td>\n",
+       "      <td>0.385331</td>\n",
+       "      <td>0.395716</td>\n",
+       "      <td>0.391299</td>\n",
+       "      <td>0.379438</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>min</th>\n",
        "      <td>0.000000</td>\n",
-       "      <td>12878.000000</td>\n",
-       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25%</th>\n",
        "      <td>0.000000</td>\n",
-       "      <td>13165.750000</td>\n",
-       "      <td>2196.750000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>50%</th>\n",
        "      <td>0.000000</td>\n",
-       "      <td>13311.500000</td>\n",
-       "      <td>4392.500000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>75%</th>\n",
-       "      <td>0.671450</td>\n",
-       "      <td>13997.250000</td>\n",
-       "      <td>6588.250000</td>\n",
+       "      <td>0.770420</td>\n",
+       "      <td>0.726192</td>\n",
+       "      <td>0.726192</td>\n",
+       "      <td>0.660864</td>\n",
+       "      <td>0.628115</td>\n",
+       "      <td>0.628115</td>\n",
+       "      <td>0.628115</td>\n",
+       "      <td>0.628115</td>\n",
+       "      <td>0.628115</td>\n",
+       "      <td>0.628115</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.748457</td>\n",
+       "      <td>0.728051</td>\n",
+       "      <td>0.728051</td>\n",
+       "      <td>0.745061</td>\n",
+       "      <td>0.763090</td>\n",
+       "      <td>0.766505</td>\n",
+       "      <td>0.728051</td>\n",
+       "      <td>0.763064</td>\n",
+       "      <td>0.745061</td>\n",
+       "      <td>0.705764</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>max</th>\n",
        "      <td>1.000000</td>\n",
-       "      <td>14006.000000</td>\n",
-       "      <td>8784.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
+       "<p>8 rows × 36 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "                Pout       plant_id          ts_id\n",
-       "count  316224.000000  316224.000000  316224.000000\n",
-       "mean        0.287262   13506.527778    4392.500000\n",
-       "std         0.370628     410.426139    2535.726375\n",
-       "min         0.000000   12878.000000       1.000000\n",
-       "25%         0.000000   13165.750000    2196.750000\n",
-       "50%         0.000000   13311.500000    4392.500000\n",
-       "75%         0.671450   13997.250000    6588.250000\n",
-       "max         1.000000   14006.000000    8784.000000"
+       "             12878        12896        12897        12984        13161  \\\n",
+       "count  8784.000000  8784.000000  8784.000000  8784.000000  8784.000000   \n",
+       "mean      0.319473     0.305552     0.305552     0.280769     0.275564   \n",
+       "std       0.392525     0.384133     0.384133     0.365295     0.363075   \n",
+       "min       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
+       "25%       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
+       "50%       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
+       "75%       0.770420     0.726192     0.726192     0.660864     0.628115   \n",
+       "max       1.000000     1.000000     1.000000     1.000000     1.000000   \n",
+       "\n",
+       "             13162        13163        13164        13165        13166  ...  \\\n",
+       "count  8784.000000  8784.000000  8784.000000  8784.000000  8784.000000  ...   \n",
+       "mean      0.275564     0.275564     0.275564     0.275564     0.275564  ...   \n",
+       "std       0.363075     0.363075     0.363075     0.363075     0.363075  ...   \n",
+       "min       0.000000     0.000000     0.000000     0.000000     0.000000  ...   \n",
+       "25%       0.000000     0.000000     0.000000     0.000000     0.000000  ...   \n",
+       "50%       0.000000     0.000000     0.000000     0.000000     0.000000  ...   \n",
+       "75%       0.628115     0.628115     0.628115     0.628115     0.628115  ...   \n",
+       "max       1.000000     1.000000     1.000000     1.000000     1.000000  ...   \n",
+       "\n",
+       "             13997        13998        13999        14000        14001  \\\n",
+       "count  8784.000000  8784.000000  8784.000000  8784.000000  8784.000000   \n",
+       "mean      0.310299     0.302906     0.302906     0.313706     0.313175   \n",
+       "std       0.389951     0.385331     0.385331     0.391299     0.390747   \n",
+       "min       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
+       "25%       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
+       "50%       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
+       "75%       0.748457     0.728051     0.728051     0.745061     0.763090   \n",
+       "max       1.000000     1.000000     1.000000     1.000000     1.000000   \n",
+       "\n",
+       "             14002        14003        14004        14005        14006  \n",
+       "count  8784.000000  8784.000000  8784.000000  8784.000000  8784.000000  \n",
+       "mean      0.315599     0.302906     0.317617     0.313706     0.297031  \n",
+       "std       0.393994     0.385331     0.395716     0.391299     0.379438  \n",
+       "min       0.000000     0.000000     0.000000     0.000000     0.000000  \n",
+       "25%       0.000000     0.000000     0.000000     0.000000     0.000000  \n",
+       "50%       0.000000     0.000000     0.000000     0.000000     0.000000  \n",
+       "75%       0.766505     0.728051     0.763064     0.745061     0.705764  \n",
+       "max       1.000000     1.000000     1.000000     1.000000     1.000000  \n",
+       "\n",
+       "[8 rows x 36 columns]"
       ]
      },
      "execution_count": 8,
@@ -713,8 +1334,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "data_oneplant = data[data.plant_id == plant_id].set_index(\"ts\", drop=True).drop(\n",
-    "    [\"plant_id\", \"ts_id\"], axis=1) * solar_plant.loc[plant_id, \"Pmax\"]"
+    "data_oneplant = data[plant_id] * solar_plant.loc[plant_id, \"Pmax\"]"
    ]
   },
   {
@@ -724,7 +1344,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1152x576 with 1 Axes>"
       ]
@@ -751,7 +1371,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1152x576 with 1 Axes>"
       ]
@@ -785,274 +1405,20 @@
     }
    ],
    "source": [
-    "print(\"Capacity Factor: %.3f\" % (data_oneplant['Pout'].sum() / (366 * 24 * solar_plant.loc[plant_id].Pmax)))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 4. Format Data\n",
-    "Data are formated for REISE"
+    "print(\"Capacity Factor: %.3f\" % (data_oneplant.sum() / (366 * 24 * solar_plant.loc[plant_id].Pmax)))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "data_reise = to_reise(data)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>12878</th>\n",
-       "      <th>12896</th>\n",
-       "      <th>12897</th>\n",
-       "      <th>12984</th>\n",
-       "      <th>13161</th>\n",
-       "      <th>13162</th>\n",
-       "      <th>13163</th>\n",
-       "      <th>13164</th>\n",
-       "      <th>13165</th>\n",
-       "      <th>13166</th>\n",
-       "      <th>...</th>\n",
-       "      <th>13997</th>\n",
-       "      <th>13998</th>\n",
-       "      <th>13999</th>\n",
-       "      <th>14000</th>\n",
-       "      <th>14001</th>\n",
-       "      <th>14002</th>\n",
-       "      <th>14003</th>\n",
-       "      <th>14004</th>\n",
-       "      <th>14005</th>\n",
-       "      <th>14006</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>UTC</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>2016-12-31 19:00:00</th>\n",
-       "      <td>0.396333</td>\n",
-       "      <td>0.896270</td>\n",
-       "      <td>0.896270</td>\n",
-       "      <td>0.039165</td>\n",
-       "      <td>0.225599</td>\n",
-       "      <td>0.225599</td>\n",
-       "      <td>0.225599</td>\n",
-       "      <td>0.225599</td>\n",
-       "      <td>0.225599</td>\n",
-       "      <td>0.225599</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.100340</td>\n",
-       "      <td>0.173883</td>\n",
-       "      <td>0.173883</td>\n",
-       "      <td>0.858580</td>\n",
-       "      <td>0.679116</td>\n",
-       "      <td>0.152976</td>\n",
-       "      <td>0.173883</td>\n",
-       "      <td>0.700871</td>\n",
-       "      <td>0.858580</td>\n",
-       "      <td>0.257330</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2016-12-31 20:00:00</th>\n",
-       "      <td>0.361778</td>\n",
-       "      <td>0.867004</td>\n",
-       "      <td>0.867004</td>\n",
-       "      <td>0.032010</td>\n",
-       "      <td>0.187044</td>\n",
-       "      <td>0.187044</td>\n",
-       "      <td>0.187044</td>\n",
-       "      <td>0.187044</td>\n",
-       "      <td>0.187044</td>\n",
-       "      <td>0.187044</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.084908</td>\n",
-       "      <td>0.148601</td>\n",
-       "      <td>0.148601</td>\n",
-       "      <td>0.824070</td>\n",
-       "      <td>0.646151</td>\n",
-       "      <td>0.128386</td>\n",
-       "      <td>0.148601</td>\n",
-       "      <td>0.671406</td>\n",
-       "      <td>0.824070</td>\n",
-       "      <td>0.221522</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2016-12-31 21:00:00</th>\n",
-       "      <td>0.320027</td>\n",
-       "      <td>0.806385</td>\n",
-       "      <td>0.806385</td>\n",
-       "      <td>0.020413</td>\n",
-       "      <td>0.124775</td>\n",
-       "      <td>0.124775</td>\n",
-       "      <td>0.124775</td>\n",
-       "      <td>0.124775</td>\n",
-       "      <td>0.124775</td>\n",
-       "      <td>0.124775</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.057858</td>\n",
-       "      <td>0.103123</td>\n",
-       "      <td>0.103123</td>\n",
-       "      <td>0.763334</td>\n",
-       "      <td>0.589665</td>\n",
-       "      <td>0.089725</td>\n",
-       "      <td>0.103123</td>\n",
-       "      <td>0.612961</td>\n",
-       "      <td>0.763334</td>\n",
-       "      <td>0.162948</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2016-12-31 22:00:00</th>\n",
-       "      <td>0.228057</td>\n",
-       "      <td>0.676944</td>\n",
-       "      <td>0.676944</td>\n",
-       "      <td>0.007701</td>\n",
-       "      <td>0.047807</td>\n",
-       "      <td>0.047807</td>\n",
-       "      <td>0.047807</td>\n",
-       "      <td>0.047807</td>\n",
-       "      <td>0.047807</td>\n",
-       "      <td>0.047807</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.028175</td>\n",
-       "      <td>0.050069</td>\n",
-       "      <td>0.050069</td>\n",
-       "      <td>0.639724</td>\n",
-       "      <td>0.488693</td>\n",
-       "      <td>0.042283</td>\n",
-       "      <td>0.050069</td>\n",
-       "      <td>0.512841</td>\n",
-       "      <td>0.639724</td>\n",
-       "      <td>0.067953</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2016-12-31 23:00:00</th>\n",
-       "      <td>0.092564</td>\n",
-       "      <td>0.309558</td>\n",
-       "      <td>0.309558</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>...</td>\n",
-       "      <td>0.000728</td>\n",
-       "      <td>0.004824</td>\n",
-       "      <td>0.004824</td>\n",
-       "      <td>0.306920</td>\n",
-       "      <td>0.261957</td>\n",
-       "      <td>0.003524</td>\n",
-       "      <td>0.004824</td>\n",
-       "      <td>0.292800</td>\n",
-       "      <td>0.306920</td>\n",
-       "      <td>0.002723</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 36 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                        12878     12896     12897     12984     13161  \\\n",
-       "UTC                                                                     \n",
-       "2016-12-31 19:00:00  0.396333  0.896270  0.896270  0.039165  0.225599   \n",
-       "2016-12-31 20:00:00  0.361778  0.867004  0.867004  0.032010  0.187044   \n",
-       "2016-12-31 21:00:00  0.320027  0.806385  0.806385  0.020413  0.124775   \n",
-       "2016-12-31 22:00:00  0.228057  0.676944  0.676944  0.007701  0.047807   \n",
-       "2016-12-31 23:00:00  0.092564  0.309558  0.309558  0.000000  0.000000   \n",
-       "\n",
-       "                        13162     13163     13164     13165     13166  ...  \\\n",
-       "UTC                                                                    ...   \n",
-       "2016-12-31 19:00:00  0.225599  0.225599  0.225599  0.225599  0.225599  ...   \n",
-       "2016-12-31 20:00:00  0.187044  0.187044  0.187044  0.187044  0.187044  ...   \n",
-       "2016-12-31 21:00:00  0.124775  0.124775  0.124775  0.124775  0.124775  ...   \n",
-       "2016-12-31 22:00:00  0.047807  0.047807  0.047807  0.047807  0.047807  ...   \n",
-       "2016-12-31 23:00:00  0.000000  0.000000  0.000000  0.000000  0.000000  ...   \n",
-       "\n",
-       "                        13997     13998     13999     14000     14001  \\\n",
-       "UTC                                                                     \n",
-       "2016-12-31 19:00:00  0.100340  0.173883  0.173883  0.858580  0.679116   \n",
-       "2016-12-31 20:00:00  0.084908  0.148601  0.148601  0.824070  0.646151   \n",
-       "2016-12-31 21:00:00  0.057858  0.103123  0.103123  0.763334  0.589665   \n",
-       "2016-12-31 22:00:00  0.028175  0.050069  0.050069  0.639724  0.488693   \n",
-       "2016-12-31 23:00:00  0.000728  0.004824  0.004824  0.306920  0.261957   \n",
-       "\n",
-       "                        14002     14003     14004     14005     14006  \n",
-       "UTC                                                                    \n",
-       "2016-12-31 19:00:00  0.152976  0.173883  0.700871  0.858580  0.257330  \n",
-       "2016-12-31 20:00:00  0.128386  0.148601  0.671406  0.824070  0.221522  \n",
-       "2016-12-31 21:00:00  0.089725  0.103123  0.612961  0.763334  0.162948  \n",
-       "2016-12-31 22:00:00  0.042283  0.050069  0.512841  0.639724  0.067953  \n",
-       "2016-12-31 23:00:00  0.003524  0.004824  0.292800  0.306920  0.002723  \n",
-       "\n",
-       "[5 rows x 36 columns]"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_reise.tail()"
-   ]
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },