Feature/python 3.5 (#93)

* Adding python 3.5 compatibility.

Main issue is ordering of dictionaries.

* Updating notebooks with 3.7 results.

* Removing tempoorary code.

* Defaulting to OrderedDict for python 3.5 + lint all code

All code reformated by PyCharm and inspection results analysed.

docs/source/examples/demo_notebook.ipynb

@@ -140,7 +140,11 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -166,7 +170,11 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -199,7 +207,11 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -230,7 +242,11 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -268,7 +284,11 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -421,7 +441,11 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -581,7 +605,11 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -601,7 +629,11 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -628,7 +660,11 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -648,7 +684,11 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -677,7 +717,11 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -700,12 +744,16 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<eland.index.Index at 0x11214bfd0>"
+       "<eland.index.Index at 0x12036ef90>"
       ]
      },
      "execution_count": 17,
@@ -721,7 +769,11 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -750,7 +802,11 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -782,7 +838,11 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1023,7 +1083,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## DataFrame.tail"
+    "### DataFrame.tail"
    ]
   },
   {
@@ -1242,7 +1302,11 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -1268,7 +1332,11 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -1301,7 +1369,11 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -1332,7 +1404,11 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -1363,7 +1439,11 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -1487,7 +1567,11 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1514,7 +1598,11 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -1676,7 +1764,11 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -1836,7 +1928,11 @@
   {
    "cell_type": "code",
    "execution_count": 33,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -1991,7 +2087,11 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -2160,7 +2260,11 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -2233,7 +2337,11 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -2313,7 +2421,11 @@
   {
    "cell_type": "code",
    "execution_count": 37,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -2344,7 +2456,11 @@
   {
    "cell_type": "code",
    "execution_count": 38,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -2382,7 +2498,11 @@
   {
    "cell_type": "code",
    "execution_count": 39,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -2515,7 +2635,11 @@
   {
    "cell_type": "code",
    "execution_count": 40,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -2580,15 +2704,15 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25%</th>\n",
-       "      <td>409.983219</td>\n",
+       "      <td>410.008918</td>\n",
        "      <td>2470.545974</td>\n",
        "      <td>...</td>\n",
-       "      <td>251.738513</td>\n",
+       "      <td>251.944994</td>\n",
        "      <td>1.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>50%</th>\n",
-       "      <td>640.387285</td>\n",
+       "      <td>640.362667</td>\n",
        "      <td>7612.072403</td>\n",
        "      <td>...</td>\n",
        "      <td>503.148975</td>\n",
@@ -2596,11 +2720,11 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>75%</th>\n",
-       "      <td>842.255395</td>\n",
+       "      <td>842.254990</td>\n",
-       "      <td>9735.860651</td>\n",
+       "      <td>9735.660463</td>\n",
        "      <td>...</td>\n",
        "      <td>720.561564</td>\n",
-       "      <td>4.230496</td>\n",
+       "      <td>4.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>max</th>\n",
@@ -2621,9 +2745,9 @@
        "mean       628.253689         7092.142457  ...     511.127842      2.835975\n",
        "std        266.386661         4578.263193  ...     334.741135      1.939365\n",
        "min        100.020531            0.000000  ...       0.000000      0.000000\n",
-       "25%        409.983219         2470.545974  ...     251.738513      1.000000\n",
+       "25%        410.008918         2470.545974  ...     251.944994      1.000000\n",
-       "50%        640.387285         7612.072403  ...     503.148975      3.000000\n",
+       "50%        640.362667         7612.072403  ...     503.148975      3.000000\n",
-       "75%        842.255395         9735.860651  ...     720.561564      4.230496\n",
+       "75%        842.254990         9735.660463  ...     720.561564      4.000000\n",
        "max       1199.729004        19881.482422  ...    1902.901978      6.000000\n",
        "\n",
        "[8 rows x 7 columns]"
@@ -2649,7 +2773,11 @@
   {
    "cell_type": "code",
    "execution_count": 41,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -2697,7 +2825,11 @@
   {
    "cell_type": "code",
    "execution_count": 42,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -2759,7 +2891,11 @@
   {
    "cell_type": "code",
    "execution_count": 43,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -2795,7 +2931,11 @@
   {
    "cell_type": "code",
    "execution_count": 44,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -2831,7 +2971,11 @@
   {
    "cell_type": "code",
    "execution_count": 45,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -2860,7 +3004,11 @@
   {
    "cell_type": "code",
    "execution_count": 46,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -2896,7 +3044,11 @@
   {
    "cell_type": "code",
    "execution_count": 47,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -2925,7 +3077,11 @@
   {
    "cell_type": "code",
    "execution_count": 48,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -2961,7 +3117,11 @@
   {
    "cell_type": "code",
    "execution_count": 49,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -2990,7 +3150,11 @@
   {
    "cell_type": "code",
    "execution_count": 50,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -3026,7 +3190,11 @@
   {
    "cell_type": "code",
    "execution_count": 51,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -3049,7 +3217,11 @@
   {
    "cell_type": "code",
    "execution_count": 52,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -3079,7 +3251,11 @@
   {
    "cell_type": "code",
    "execution_count": 53,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -3103,7 +3279,7 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Carrier</th>\n",
-       "      <th>DestLocation</th>\n",
+       "      <th>DestRegion</th>\n",
        "      <th>...</th>\n",
        "      <th>dayOfWeek</th>\n",
        "      <th>timestamp</th>\n",
@@ -3113,7 +3289,7 @@
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>Kibana Airlines</td>\n",
-       "      <td>{'lat': '-33.94609833', 'lon': '151.177002'}</td>\n",
+       "      <td>SE-BD</td>\n",
        "      <td>...</td>\n",
        "      <td>0</td>\n",
        "      <td>2018-01-01 00:00:00</td>\n",
@@ -3121,7 +3297,7 @@
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>Logstash Airways</td>\n",
-       "      <td>{'lat': '45.505299', 'lon': '12.3519'}</td>\n",
+       "      <td>IT-34</td>\n",
        "      <td>...</td>\n",
        "      <td>0</td>\n",
        "      <td>2018-01-01 18:27:00</td>\n",
@@ -3129,7 +3305,7 @@
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>Logstash Airways</td>\n",
-       "      <td>{'lat': '45.505299', 'lon': '12.3519'}</td>\n",
+       "      <td>IT-34</td>\n",
        "      <td>...</td>\n",
        "      <td>0</td>\n",
        "      <td>2018-01-01 17:11:14</td>\n",
@@ -3137,7 +3313,7 @@
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>Kibana Airlines</td>\n",
-       "      <td>{'lat': '45.648399', 'lon': '12.1944'}</td>\n",
+       "      <td>IT-34</td>\n",
        "      <td>...</td>\n",
        "      <td>0</td>\n",
        "      <td>2018-01-01 10:33:28</td>\n",
@@ -3145,7 +3321,7 @@
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>Kibana Airlines</td>\n",
-       "      <td>{'lat': '34.447102', 'lon': '108.751999'}</td>\n",
+       "      <td>SE-BD</td>\n",
        "      <td>...</td>\n",
        "      <td>0</td>\n",
        "      <td>2018-01-01 05:13:00</td>\n",
@@ -3161,7 +3337,7 @@
        "    <tr>\n",
        "      <th>13054</th>\n",
        "      <td>Logstash Airways</td>\n",
-       "      <td>{'lat': '34.447102', 'lon': '108.751999'}</td>\n",
+       "      <td>SE-BD</td>\n",
        "      <td>...</td>\n",
        "      <td>6</td>\n",
        "      <td>2018-02-11 20:42:25</td>\n",
@@ -3169,7 +3345,7 @@
        "    <tr>\n",
        "      <th>13055</th>\n",
        "      <td>Logstash Airways</td>\n",
-       "      <td>{'lat': '47.464699', 'lon': '8.54917'}</td>\n",
+       "      <td>CH-ZH</td>\n",
        "      <td>...</td>\n",
        "      <td>6</td>\n",
        "      <td>2018-02-11 01:41:57</td>\n",
@@ -3177,7 +3353,7 @@
        "    <tr>\n",
        "      <th>13056</th>\n",
        "      <td>Logstash Airways</td>\n",
-       "      <td>{'lat': '51.169997', 'lon': '128.445007'}</td>\n",
+       "      <td>RU-AMU</td>\n",
        "      <td>...</td>\n",
        "      <td>6</td>\n",
        "      <td>2018-02-11 04:09:27</td>\n",
@@ -3185,7 +3361,7 @@
        "    <tr>\n",
        "      <th>13057</th>\n",
        "      <td>JetBeats</td>\n",
-       "      <td>{'lat': '-34.8222', 'lon': '-58.5358'}</td>\n",
+       "      <td>SE-BD</td>\n",
        "      <td>...</td>\n",
        "      <td>6</td>\n",
        "      <td>2018-02-11 08:28:21</td>\n",
@@ -3193,44 +3369,31 @@
        "    <tr>\n",
        "      <th>13058</th>\n",
        "      <td>JetBeats</td>\n",
-       "      <td>{'lat': '38.94449997', 'lon': '-77.45580292'}</td>\n",
+       "      <td>US-DC</td>\n",
        "      <td>...</td>\n",
        "      <td>6</td>\n",
        "      <td>2018-02-11 14:54:34</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>13059 rows × 21 columns</p>\n",
+       "<p>13059 rows × 20 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "                Carrier                                   DestLocation  ... dayOfWeek  \\\n",
+       "                Carrier DestRegion  ... dayOfWeek           timestamp\n",
-       "0       Kibana Airlines   {'lat': '-33.94609833', 'lon': '151.177002'}  ...         0   \n",
+       "0       Kibana Airlines      SE-BD  ...         0 2018-01-01 00:00:00\n",
-       "1      Logstash Airways         {'lat': '45.505299', 'lon': '12.3519'}  ...         0   \n",
+       "1      Logstash Airways      IT-34  ...         0 2018-01-01 18:27:00\n",
-       "2      Logstash Airways         {'lat': '45.505299', 'lon': '12.3519'}  ...         0   \n",
+       "2      Logstash Airways      IT-34  ...         0 2018-01-01 17:11:14\n",
-       "3       Kibana Airlines         {'lat': '45.648399', 'lon': '12.1944'}  ...         0   \n",
+       "3       Kibana Airlines      IT-34  ...         0 2018-01-01 10:33:28\n",
-       "4       Kibana Airlines      {'lat': '34.447102', 'lon': '108.751999'}  ...         0   \n",
+       "4       Kibana Airlines      SE-BD  ...         0 2018-01-01 05:13:00\n",
-       "...                 ...                                            ...  ...       ...   \n",
+       "...                 ...        ...  ...       ...                 ...\n",
-       "13054  Logstash Airways      {'lat': '34.447102', 'lon': '108.751999'}  ...         6   \n",
+       "13054  Logstash Airways      SE-BD  ...         6 2018-02-11 20:42:25\n",
-       "13055  Logstash Airways         {'lat': '47.464699', 'lon': '8.54917'}  ...         6   \n",
+       "13055  Logstash Airways      CH-ZH  ...         6 2018-02-11 01:41:57\n",
-       "13056  Logstash Airways      {'lat': '51.169997', 'lon': '128.445007'}  ...         6   \n",
+       "13056  Logstash Airways     RU-AMU  ...         6 2018-02-11 04:09:27\n",
-       "13057          JetBeats         {'lat': '-34.8222', 'lon': '-58.5358'}  ...         6   \n",
+       "13057          JetBeats      SE-BD  ...         6 2018-02-11 08:28:21\n",
-       "13058          JetBeats  {'lat': '38.94449997', 'lon': '-77.45580292'}  ...         6   \n",
+       "13058          JetBeats      US-DC  ...         6 2018-02-11 14:54:34\n",
        "\n",
-       "                timestamp  \n",
+       "[13059 rows x 20 columns]"
-       "0     2018-01-01 00:00:00  \n",
-       "1     2018-01-01 18:27:00  \n",
-       "2     2018-01-01 17:11:14  \n",
-       "3     2018-01-01 10:33:28  \n",
-       "4     2018-01-01 05:13:00  \n",
-       "...                   ...  \n",
-       "13054 2018-02-11 20:42:25  \n",
-       "13055 2018-02-11 01:41:57  \n",
-       "13056 2018-02-11 04:09:27  \n",
-       "13057 2018-02-11 08:28:21  \n",
-       "13058 2018-02-11 14:54:34  \n",
-       "\n",
-       "[13059 rows x 21 columns]"
       ]
      },
      "execution_count": 53,
@@ -3241,6 +3404,7 @@
    "source": [
     "pd_flights.drop(columns=['AvgTicketPrice', \n",
     "                         'Cancelled', \n",
+    "                         'DestLocation',\n",
     "                         'Dest', \n",
     "                         'DestAirportID', \n",
     "                         'DestCityName', \n",
@@ -3250,7 +3414,11 @@
   {
    "cell_type": "code",
    "execution_count": 54,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -3274,7 +3442,7 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Carrier</th>\n",
-       "      <th>DestLocation</th>\n",
+       "      <th>DestRegion</th>\n",
        "      <th>...</th>\n",
        "      <th>dayOfWeek</th>\n",
        "      <th>timestamp</th>\n",
@@ -3284,7 +3452,7 @@
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>Kibana Airlines</td>\n",
-       "      <td>{'lon': '151.177002', 'lat': '-33.94609833'}</td>\n",
+       "      <td>SE-BD</td>\n",
        "      <td>...</td>\n",
        "      <td>0</td>\n",
        "      <td>2018-01-01 00:00:00</td>\n",
@@ -3292,7 +3460,7 @@
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>Logstash Airways</td>\n",
-       "      <td>{'lon': '12.3519', 'lat': '45.505299'}</td>\n",
+       "      <td>IT-34</td>\n",
        "      <td>...</td>\n",
        "      <td>0</td>\n",
        "      <td>2018-01-01 18:27:00</td>\n",
@@ -3300,7 +3468,7 @@
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>Logstash Airways</td>\n",
-       "      <td>{'lon': '12.3519', 'lat': '45.505299'}</td>\n",
+       "      <td>IT-34</td>\n",
        "      <td>...</td>\n",
        "      <td>0</td>\n",
        "      <td>2018-01-01 17:11:14</td>\n",
@@ -3308,7 +3476,7 @@
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>Kibana Airlines</td>\n",
-       "      <td>{'lon': '12.1944', 'lat': '45.648399'}</td>\n",
+       "      <td>IT-34</td>\n",
        "      <td>...</td>\n",
        "      <td>0</td>\n",
        "      <td>2018-01-01 10:33:28</td>\n",
@@ -3316,7 +3484,7 @@
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>Kibana Airlines</td>\n",
-       "      <td>{'lon': '108.751999', 'lat': '34.447102'}</td>\n",
+       "      <td>SE-BD</td>\n",
        "      <td>...</td>\n",
        "      <td>0</td>\n",
        "      <td>2018-01-01 05:13:00</td>\n",
@@ -3332,7 +3500,7 @@
        "    <tr>\n",
        "      <th>13054</th>\n",
        "      <td>Logstash Airways</td>\n",
-       "      <td>{'lon': '108.751999', 'lat': '34.447102'}</td>\n",
+       "      <td>SE-BD</td>\n",
        "      <td>...</td>\n",
        "      <td>6</td>\n",
        "      <td>2018-02-11 20:42:25</td>\n",
@@ -3340,7 +3508,7 @@
        "    <tr>\n",
        "      <th>13055</th>\n",
        "      <td>Logstash Airways</td>\n",
-       "      <td>{'lon': '8.54917', 'lat': '47.464699'}</td>\n",
+       "      <td>CH-ZH</td>\n",
        "      <td>...</td>\n",
        "      <td>6</td>\n",
        "      <td>2018-02-11 01:41:57</td>\n",
@@ -3348,7 +3516,7 @@
        "    <tr>\n",
        "      <th>13056</th>\n",
        "      <td>Logstash Airways</td>\n",
-       "      <td>{'lon': '128.445007', 'lat': '51.169997'}</td>\n",
+       "      <td>RU-AMU</td>\n",
        "      <td>...</td>\n",
        "      <td>6</td>\n",
        "      <td>2018-02-11 04:09:27</td>\n",
@@ -3356,7 +3524,7 @@
        "    <tr>\n",
        "      <th>13057</th>\n",
        "      <td>JetBeats</td>\n",
-       "      <td>{'lon': '-58.5358', 'lat': '-34.8222'}</td>\n",
+       "      <td>SE-BD</td>\n",
        "      <td>...</td>\n",
        "      <td>6</td>\n",
        "      <td>2018-02-11 08:28:21</td>\n",
@@ -3364,7 +3532,7 @@
        "    <tr>\n",
        "      <th>13058</th>\n",
        "      <td>JetBeats</td>\n",
-       "      <td>{'lon': '-77.45580292', 'lat': '38.94449997'}</td>\n",
+       "      <td>US-DC</td>\n",
        "      <td>...</td>\n",
        "      <td>6</td>\n",
        "      <td>2018-02-11 14:54:34</td>\n",
@@ -3372,36 +3540,23 @@
        "  </tbody>\n",
        "</table>\n",
        "</div>\n",
-       "<p>13059 rows × 21 columns</p>"
+       "<p>13059 rows × 20 columns</p>"
       ],
       "text/plain": [
-       "                Carrier                                   DestLocation  ... dayOfWeek  \\\n",
+       "                Carrier DestRegion  ... dayOfWeek           timestamp\n",
-       "0       Kibana Airlines   {'lon': '151.177002', 'lat': '-33.94609833'}  ...         0   \n",
+       "0       Kibana Airlines      SE-BD  ...         0 2018-01-01 00:00:00\n",
-       "1      Logstash Airways         {'lon': '12.3519', 'lat': '45.505299'}  ...         0   \n",
+       "1      Logstash Airways      IT-34  ...         0 2018-01-01 18:27:00\n",
-       "2      Logstash Airways         {'lon': '12.3519', 'lat': '45.505299'}  ...         0   \n",
+       "2      Logstash Airways      IT-34  ...         0 2018-01-01 17:11:14\n",
-       "3       Kibana Airlines         {'lon': '12.1944', 'lat': '45.648399'}  ...         0   \n",
+       "3       Kibana Airlines      IT-34  ...         0 2018-01-01 10:33:28\n",
-       "4       Kibana Airlines      {'lon': '108.751999', 'lat': '34.447102'}  ...         0   \n",
+       "4       Kibana Airlines      SE-BD  ...         0 2018-01-01 05:13:00\n",
-       "...                 ...                                            ...  ...       ...   \n",
+       "...                 ...        ...  ...       ...                 ...\n",
-       "13054  Logstash Airways      {'lon': '108.751999', 'lat': '34.447102'}  ...         6   \n",
+       "13054  Logstash Airways      SE-BD  ...         6 2018-02-11 20:42:25\n",
-       "13055  Logstash Airways         {'lon': '8.54917', 'lat': '47.464699'}  ...         6   \n",
+       "13055  Logstash Airways      CH-ZH  ...         6 2018-02-11 01:41:57\n",
-       "13056  Logstash Airways      {'lon': '128.445007', 'lat': '51.169997'}  ...         6   \n",
+       "13056  Logstash Airways     RU-AMU  ...         6 2018-02-11 04:09:27\n",
-       "13057          JetBeats         {'lon': '-58.5358', 'lat': '-34.8222'}  ...         6   \n",
+       "13057          JetBeats      SE-BD  ...         6 2018-02-11 08:28:21\n",
-       "13058          JetBeats  {'lon': '-77.45580292', 'lat': '38.94449997'}  ...         6   \n",
+       "13058          JetBeats      US-DC  ...         6 2018-02-11 14:54:34\n",
        "\n",
-       "                timestamp  \n",
+       "[13059 rows x 20 columns]"
-       "0     2018-01-01 00:00:00  \n",
-       "1     2018-01-01 18:27:00  \n",
-       "2     2018-01-01 17:11:14  \n",
-       "3     2018-01-01 10:33:28  \n",
-       "4     2018-01-01 05:13:00  \n",
-       "...                   ...  \n",
-       "13054 2018-02-11 20:42:25  \n",
-       "13055 2018-02-11 01:41:57  \n",
-       "13056 2018-02-11 04:09:27  \n",
-       "13057 2018-02-11 08:28:21  \n",
-       "13058 2018-02-11 14:54:34  \n",
-       "\n",
-       "[13059 rows x 21 columns]"
       ]
      },
      "execution_count": 54,
@@ -3412,6 +3567,7 @@
    "source": [
     "ed_flights.drop(columns=['AvgTicketPrice', \n",
     "                         'Cancelled', \n",
+    "                         'DestLocation',\n",
     "                         'Dest', \n",
     "                         'DestAirportID', \n",
     "                         'DestCityName', \n",
@@ -3428,7 +3584,11 @@
   {
    "cell_type": "code",
    "execution_count": 55,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -3451,7 +3611,11 @@
   {
    "cell_type": "code",
    "execution_count": 56,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "data": {
@@ -3481,7 +3645,11 @@
   {
    "cell_type": "code",
    "execution_count": 57,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [],
    "source": [
     "ed_flights2 = ed_flights[(ed_flights.OriginAirportID == 'AMS') & (ed_flights.FlightDelayMin > 60)]\n",
@@ -3492,7 +3660,11 @@
   {
    "cell_type": "code",
    "execution_count": 58,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "is_executing": false
+    }
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -3537,7 +3709,7 @@
       " size: 5\n",
       " sort_params: _doc:desc\n",
       " _source: ['timestamp', 'OriginAirportID', 'DestAirportID', 'FlightDelayMin']\n",
-      " body: {'query': {'bool': {'must': [{'term': {'OriginAirportID': 'AMS'}}, {'range': {'FlightDelayMin': {'gt': 60}}}]}}, 'aggs': {}}\n",
+      " body: {'query': {'bool': {'must': [{'term': {'OriginAirportID': 'AMS'}}, {'range': {'FlightDelayMin': {'gt': 60}}}]}}}\n",
       " post_processing: [('sort_index')]\n",
       "'field_to_display_names': {}\n",
       "'display_to_field_names': {}\n",

docs/source/examples/index.rst

@@ -5,7 +5,7 @@ Examples
 ========
 
 .. toctree::
-   :maxdepth: 2
+   :maxdepth: 3
 
    demo_notebook
    online_retail_analysis

docs/source/examples/online_retail_analysis.ipynb

@@ -176,7 +176,7 @@
       " size: None\n",
       " sort_params: None\n",
       " _source: None\n",
-      " body: {'aggs': {}}\n",
+      " body: {}\n",
       " post_processing: []\n",
       "'field_to_display_names': {}\n",
       "'display_to_field_names': {}\n",
@@ -308,7 +308,7 @@
       " size: 2\n",
       " sort_params: _doc:desc\n",
       " _source: None\n",
-      " body: {'aggs': {}}\n",
+      " body: {}\n",
       " post_processing: [('sort_index'), ('head': ('count': 2)), ('tail': ('count': 2))]\n",
       "'field_to_display_names': {}\n",
       "'display_to_field_names': {}\n",
@@ -813,7 +813,7 @@
       " size: None\n",
       " sort_params: None\n",
       " _source: None\n",
-      " body: {'query': {'bool': {'must': [{'term': {'Country': 'Germany'}}, {'range': {'Quantity': {'gt': 90}}}]}}, 'aggs': {}}\n",
+      " body: {'query': {'bool': {'must': [{'term': {'Country': 'Germany'}}, {'range': {'Quantity': {'gt': 90}}}]}}}\n",
       " post_processing: []\n",
       "'field_to_display_names': {}\n",
       "'display_to_field_names': {}\n",
@@ -1037,23 +1037,23 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25%</th>\n",
-       "      <td>14220.581670</td>\n",
+       "      <td>14220.529879</td>\n",
        "      <td>1.000000</td>\n",
        "      <td>1.250000</td>\n",
        "      <td>3756.500000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>50%</th>\n",
-       "      <td>15666.545935</td>\n",
+       "      <td>15661.227460</td>\n",
        "      <td>2.000000</td>\n",
        "      <td>2.510000</td>\n",
-       "      <td>7498.861278</td>\n",
+       "      <td>7499.363732</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>75%</th>\n",
-       "      <td>17213.978376</td>\n",
+       "      <td>17214.478439</td>\n",
-       "      <td>6.614054</td>\n",
+       "      <td>6.613198</td>\n",
-       "      <td>4.215516</td>\n",
+       "      <td>4.210000</td>\n",
        "      <td>11249.500000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -1073,9 +1073,9 @@
        "mean   15590.776680      7.464000      4.103233   7499.500000\n",
        "std     1764.025160     85.924387     20.104873   4330.127009\n",
        "min    12347.000000  -9360.000000      0.000000      0.000000\n",
-       "25%    14220.581670      1.000000      1.250000   3756.500000\n",
+       "25%    14220.529879      1.000000      1.250000   3756.500000\n",
-       "50%    15666.545935      2.000000      2.510000   7498.861278\n",
+       "50%    15661.227460      2.000000      2.510000   7499.363732\n",
-       "75%    17213.978376      6.614054      4.215516  11249.500000\n",
+       "75%    17214.478439      6.613198      4.210000  11249.500000\n",
        "max    18239.000000   2880.000000    950.990000  14999.000000"
       ]
      },

docs/source/index.rst

@@ -48,3 +48,5 @@ In general, the data resides in elasticsearch and not in memory, which allows el
 
 * :doc:`examples/index`
 
+  * :doc:`examples/demo_notebook`
+  * :doc:`examples/online_retail_analysis`

eland/actions.py

@@ -3,6 +3,9 @@ from abc import ABC, abstractmethod
 # -------------------------------------------------------------------------------------------------------------------- #
 # PostProcessingActions                                                                                                #
 # -------------------------------------------------------------------------------------------------------------------- #
+from eland import SortOrder
+
+
 class PostProcessingAction(ABC):
     def __init__(self, action_type):
         """
@@ -27,6 +30,7 @@ class PostProcessingAction(ABC):
     def __repr__(self):
         pass
 
+
 class SortIndexAction(PostProcessingAction):
     def __init__(self):
         super().__init__("sort_index")
@@ -37,6 +41,7 @@ class SortIndexAction(PostProcessingAction):
     def __repr__(self):
         return "('{}')".format(self.type)
 
+
 class HeadAction(PostProcessingAction):
     def __init__(self, count):
         super().__init__("head")
@@ -76,10 +81,10 @@ class SortFieldAction(PostProcessingAction):
             raise ValueError("Expected ES sort params string (e.g. _doc:desc). Got '{}'".format(sort_params_string))
 
         self._sort_field = sort_params[0]
-        self._sort_order = Operations.SortOrder.from_string(sort_params[1])
+        self._sort_order = SortOrder.from_string(sort_params[1])
 
     def resolve_action(self, df):
-        if self._sort_order == Operations.SortOrder.ASC:
+        if self._sort_order == SortOrder.ASC:
             return df.sort_values(self._sort_field, True)
         return df.sort_values(self._sort_field, False)
 

eland/common.py

@@ -13,6 +13,8 @@
 #      limitations under the License.
 
 # Default number of rows displayed (different to pandas where ALL could be displayed)
+from enum import Enum
+
 DEFAULT_NUM_ROWS_DISPLAYED = 60
 
 
@@ -22,3 +24,29 @@ def docstring_parameter(*sub):
         return obj
 
     return dec
+
+
+class SortOrder(Enum):
+    ASC = 0
+    DESC = 1
+
+    @staticmethod
+    def reverse(order):
+        if order == SortOrder.ASC:
+            return SortOrder.DESC
+
+        return SortOrder.ASC
+
+    @staticmethod
+    def to_string(order):
+        if order == SortOrder.ASC:
+            return "asc"
+
+        return "desc"
+
+    @staticmethod
+    def from_string(order):
+        if order == "asc":
+            return SortOrder.ASC
+
+        return SortOrder.DESC

eland/compat.py

@@ -0,0 +1,17 @@
+#  Copyright 2019 Elasticsearch BV
+#
+#      Licensed under the Apache License, Version 2.0 (the "License");
+#      you may not use this file except in compliance with the License.
+#      You may obtain a copy of the License at
+#
+#          http://www.apache.org/licenses/LICENSE-2.0
+#
+#      Unless required by applicable law or agreed to in writing, software
+#      distributed under the License is distributed on an "AS IS" BASIS,
+#      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#      See the License for the specific language governing permissions and
+#      limitations under the License.
+
+import sys
+
+PY36 = sys.version_info >= (3, 6)

eland/dataframe.py

@@ -27,6 +27,7 @@ from pandas.io.common import _expand_user, _stringify_path
 from pandas.io.formats import console
 from pandas.io.formats import format as fmt
 from pandas.io.formats.printing import pprint_thing
+from pandas.util._validators import validate_bool_kwarg
 
 import eland.plotting as gfx
 from eland import NDFrame
@@ -255,6 +256,151 @@ class DataFrame(NDFrame):
         """
         return DataFrame(query_compiler=self._query_compiler.tail(n))
 
+    def drop(
+            self,
+            labels=None,
+            axis=0,
+            index=None,
+            columns=None,
+            level=None,
+            inplace=False,
+            errors="raise",
+    ):
+        """Return new object with labels in requested axis removed.
+
+        Parameters
+        ----------
+        labels:
+            Index or column labels to drop.
+        axis:
+            Whether to drop labels from the index (0 / 'index') or columns (1 / 'columns').
+        index, columns:
+            Alternative to specifying axis (labels, axis=1 is equivalent to columns=labels).
+        level:
+            For MultiIndex - not supported
+        inplace:
+            If True, do operation inplace and return None.
+        errors:
+            If 'ignore', suppress error and existing labels are dropped.
+
+        Returns
+        -------
+        dropped:
+            type of caller
+
+        See Also
+        --------
+        :pandas_api_docs:`pandas.DataFrame.drop`
+
+        Examples
+        --------
+        Drop a column
+
+        >>> df = ed.DataFrame('localhost', 'ecommerce', columns=['customer_first_name', 'email', 'user'])
+        >>> df.drop(columns=['user'])
+             customer_first_name                       email
+        0                  Eddie  eddie@underwood-family.zzz
+        1                   Mary      mary@bailey-family.zzz
+        2                   Gwen      gwen@butler-family.zzz
+        3                  Diane   diane@chandler-family.zzz
+        4                  Eddie      eddie@weber-family.zzz
+        ...                  ...                         ...
+        4670                Mary     mary@lambert-family.zzz
+        4671                 Jim      jim@gilbert-family.zzz
+        4672               Yahya     yahya@rivera-family.zzz
+        4673                Mary     mary@hampton-family.zzz
+        4674             Jackson  jackson@hopkins-family.zzz
+        <BLANKLINE>
+        [4675 rows x 2 columns]
+
+        Drop rows by index value (axis=0)
+
+        >>> df.drop(['1', '2'])
+             customer_first_name                       email     user
+        0                  Eddie  eddie@underwood-family.zzz    eddie
+        3                  Diane   diane@chandler-family.zzz    diane
+        4                  Eddie      eddie@weber-family.zzz    eddie
+        5                  Diane    diane@goodwin-family.zzz    diane
+        6                 Oliver      oliver@rios-family.zzz   oliver
+        ...                  ...                         ...      ...
+        4670                Mary     mary@lambert-family.zzz     mary
+        4671                 Jim      jim@gilbert-family.zzz      jim
+        4672               Yahya     yahya@rivera-family.zzz    yahya
+        4673                Mary     mary@hampton-family.zzz     mary
+        4674             Jackson  jackson@hopkins-family.zzz  jackson
+        <BLANKLINE>
+        [4673 rows x 3 columns]
+        """
+        # Level not supported
+        if level is not None:
+            raise NotImplementedError("level not supported {}".format(level))
+
+        inplace = validate_bool_kwarg(inplace, "inplace")
+        if labels is not None:
+            if index is not None or columns is not None:
+                raise ValueError("Cannot specify both 'labels' and 'index'/'columns'")
+            axis = pd.DataFrame()._get_axis_name(axis)
+            axes = {axis: labels}
+        elif index is not None or columns is not None:
+            axes, _ = pd.DataFrame()._construct_axes_from_arguments(
+                (index, columns), {}
+            )
+        else:
+            raise ValueError(
+                "Need to specify at least one of 'labels', 'index' or 'columns'"
+            )
+
+        # TODO Clean up this error checking
+        if "index" not in axes:
+            axes["index"] = None
+        elif axes["index"] is not None:
+            if not is_list_like(axes["index"]):
+                axes["index"] = [axes["index"]]
+            if errors == "raise":
+                # Check if axes['index'] values exists in index
+                count = self._query_compiler._index_matches_count(axes["index"])
+                if count != len(axes["index"]):
+                    raise ValueError(
+                        "number of labels {}!={} not contained in axis".format(count, len(axes["index"]))
+                    )
+            else:
+                """
+                axes["index"] = self._query_compiler.index_matches(axes["index"])
+                # If the length is zero, we will just do nothing
+                if not len(axes["index"]):
+                    axes["index"] = None
+                """
+                raise NotImplementedError()
+
+        if "columns" not in axes:
+            axes["columns"] = None
+        elif axes["columns"] is not None:
+            if not is_list_like(axes["columns"]):
+                axes["columns"] = [axes["columns"]]
+            if errors == "raise":
+                non_existant = [
+                    obj for obj in axes["columns"] if obj not in self.columns
+                ]
+                if len(non_existant):
+                    raise ValueError(
+                        "labels {} not contained in axis".format(non_existant)
+                    )
+            else:
+                axes["columns"] = [
+                    obj for obj in axes["columns"] if obj in self.columns
+                ]
+                # If the length is zero, we will just do nothing
+                if not len(axes["columns"]):
+                    axes["columns"] = None
+
+        new_query_compiler = self._query_compiler.drop(
+            index=axes["index"], columns=axes["columns"]
+        )
+        return self._create_or_update_from_compiler(new_query_compiler, inplace)
+
+    def __getitem__(self, key):
+        return self._getitem(key)
+
     def __repr__(self):
         """
         From pandas
@@ -312,7 +458,8 @@ class DataFrame(NDFrame):
                 max_rows = min_rows
 
             return self.to_html(max_rows=max_rows, max_cols=max_cols,
-                                show_dimensions=show_dimensions, notebook=True)  # set for consistency with pandas output
+                                show_dimensions=show_dimensions,
+                                notebook=True)  # set for consistency with pandas output
         else:
             return None
 
@@ -417,7 +564,7 @@ class DataFrame(NDFrame):
          size: 5
          sort_params: _doc:desc
          _source: ['timestamp', 'OriginAirportID', 'DestAirportID', 'FlightDelayMin']
-         body: {'query': {'bool': {'must': [{'term': {'OriginAirportID': 'AMS'}}, {'range': {'FlightDelayMin': {'gt': 60}}}]}}, 'aggs': {}}
+         body: {'query': {'bool': {'must': [{'term': {'OriginAirportID': 'AMS'}}, {'range': {'FlightDelayMin': {'gt': 60}}}]}}}
          post_processing: [('sort_index')]
         'field_to_display_names': {}
         'display_to_field_names': {}

eland/filter.py

@@ -24,10 +24,10 @@ class BooleanFilter:
         if isinstance(self, AndFilter):
             if 'must_not' in x.subtree:
                 # nest a must_not under a must
-                self.subtree['must'].append(x.build()) # 'build includes bool'
+                self.subtree['must'].append(x.build())  # 'build includes bool'
             else:
                 # append a must to a must
-                self.subtree['must'].append(x.subtree) # 'subtree strips bool'
+                self.subtree['must'].append(x.subtree)  # 'subtree strips bool'
             return self
         elif isinstance(x, AndFilter):
             if 'must_not' in self.subtree:

eland/mappings.py

@@ -11,8 +11,8 @@
 #      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 #      See the License for the specific language governing permissions and
 #      limitations under the License.
-
 import warnings
+from collections import OrderedDict
 
 import numpy as np
 import pandas as pd
@@ -66,7 +66,7 @@ class Mappings:
         """
 
         # here we keep track of the format of any date fields
-        self._date_fields_format = {}
+        self._date_fields_format = dict()
         if (client is not None) and (index_pattern is not None):
             get_mapping = client.get_mapping(index=index_pattern)
 
@@ -86,7 +86,8 @@ class Mappings:
 
         # Cache source field types for efficient lookup
         # (this massively improves performance of DataFrame.flatten)
-        self._source_field_pd_dtypes = {}
+
+        self._source_field_pd_dtypes = OrderedDict()
 
         for field_name in self._mappings_capabilities[self._mappings_capabilities._source].index:
             pd_dtype = self._mappings_capabilities.loc[field_name]['pd_dtype']
@@ -135,14 +136,14 @@ class Mappings:
 
         Returns
         -------
-        fields, dates_format: tuple(dict, dict)
+        fields, dates_format: tuple(OrderedDict, dict)
             where:
-                fields: Dict of field names and types
+                fields: OrderedDict of field names and types
                 dates_format: Dict of date field names and format
 
         """
-        fields = {}
+        fields = OrderedDict()
-        dates_format = {}
+        dates_format = dict()
 
         # Recurse until we get a 'type: xxx'
         def flatten(x, name=''):
@@ -206,7 +207,7 @@ class Mappings:
         all_fields_caps_fields = all_fields_caps['fields']
 
         field_names = ['_source', 'es_dtype', 'pd_dtype', 'searchable', 'aggregatable']
-        capability_matrix = {}
+        capability_matrix = OrderedDict()
 
         for field, field_caps in all_fields_caps_fields.items():
             if field in all_fields:
@@ -353,7 +354,7 @@ class Mappings:
             else:
                 es_dtype = Mappings._pd_dtype_to_es_dtype(dtype)
 
-            mappings['properties'][field_name_name] = {}
+            mappings['properties'][field_name_name] = OrderedDict()
             mappings['properties'][field_name_name]['type'] = es_dtype
 
         return {"mappings": mappings}
@@ -401,8 +402,8 @@ class Mappings:
 
         Returns
         -------
-        dict
+        str
-            A dictionary (for date fields) containing the mapping {field_name:format}
+            A string (for date fields) containing the date format for the field
         """
         return self._date_fields_format.get(field_name)
 
@@ -460,12 +461,12 @@ class Mappings:
 
         Returns
         -------
-        dict
+        OrderedDict
             e.g. {'customer_full_name': 'customer_full_name.keyword', ...}
         """
         if field_names is None:
             field_names = self.source_fields()
-        aggregatables = {}
+        aggregatables = OrderedDict()
         for field_name in field_names:
             capabilities = self.field_capabilities(field_name)
             if capabilities['aggregatable']:
@@ -478,7 +479,7 @@ class Mappings:
                     aggregatables[field_name_keyword] = field_name
 
         if not aggregatables:
-            raise ValueError("Aggregations not supported for ", field_name)
+            raise ValueError("Aggregations not supported for ", field_names)
 
         return aggregatables
 
@@ -533,11 +534,15 @@ class Mappings:
             Source field name + pd_dtype as np.dtype
         """
         if field_names is not None:
-            return pd.Series(
+            data = OrderedDict()
-                {key: np.dtype(self._source_field_pd_dtypes[key]) for key in field_names})
+            for key in field_names:
+                data[key] = np.dtype(self._source_field_pd_dtypes[key])
+            return pd.Series(data)
 
-        return pd.Series(
+        data = OrderedDict()
-            {key: np.dtype(value) for key, value in self._source_field_pd_dtypes.items()})
+        for key, value in self._source_field_pd_dtypes.items():
+            data[key] = np.dtype(value)
+        return pd.Series(data)
 
     def info_es(self, buf):
         buf.write("Mappings:\n")

eland/ndframe.py

@@ -1,3 +1,22 @@
+#  Copyright 2019 Elasticsearch BV
+#
+#      Licensed under the Apache License, Version 2.0 (the "License");
+#      you may not use this file except in compliance with the License.
+#      You may obtain a copy of the License at
+#
+#          http://www.apache.org/licenses/LICENSE-2.0
+#
+#      Unless required by applicable law or agreed to in writing, software
+#      distributed under the License is distributed on an "AS IS" BASIS,
+#      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#      See the License for the specific language governing permissions and
+#      limitations under the License.
+
+import sys
+from abc import ABC, abstractmethod
+
+from eland import QueryCompiler
+
 """
 NDFrame
 ---------
@@ -23,29 +42,6 @@ only Elasticsearch aggregatable fields can be aggregated or grouped.
 
 """
 
-#  Copyright 2019 Elasticsearch BV
-#
-#      Licensed under the Apache License, Version 2.0 (the "License");
-#      you may not use this file except in compliance with the License.
-#      You may obtain a copy of the License at
-#
-#          http://www.apache.org/licenses/LICENSE-2.0
-#
-#      Unless required by applicable law or agreed to in writing, software
-#      distributed under the License is distributed on an "AS IS" BASIS,
-#      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-#      See the License for the specific language governing permissions and
-#      limitations under the License.
-
-import sys
-from abc import ABC
-
-import pandas as pd
-from pandas.core.dtypes.common import is_list_like
-from pandas.util._validators import validate_bool_kwarg
-
-from eland import ElandQueryCompiler
-
 
 class NDFrame(ABC):
 
@@ -64,8 +60,8 @@ class NDFrame(ABC):
             A reference to a Elasticsearch python client
         """
         if query_compiler is None:
-            query_compiler = ElandQueryCompiler(client=client, index_pattern=index_pattern, field_names=columns,
+            query_compiler = QueryCompiler(client=client, index_pattern=index_pattern, field_names=columns,
-                                                index_field=index_field)
+                                           index_field=index_field)
         self._query_compiler = query_compiler
 
     def _get_index(self):
@@ -139,9 +135,6 @@ class NDFrame(ABC):
 
         return head.append(tail)
 
-    def __getitem__(self, key):
-        return self._getitem(key)
-
     def __sizeof__(self):
         # Don't default to pandas, just return approximation TODO - make this more accurate
         return sys.getsizeof(self._query_compiler)
@@ -157,148 +150,6 @@ class NDFrame(ABC):
     def _info_es(self, buf):
         self._query_compiler.info_es(buf)
 
-    def drop(
-            self,
-            labels=None,
-            axis=0,
-            index=None,
-            columns=None,
-            level=None,
-            inplace=False,
-            errors="raise",
-    ):
-        """Return new object with labels in requested axis removed.
-
-        Parameters
-        ----------
-        labels:
-            Index or column labels to drop.
-        axis:
-            Whether to drop labels from the index (0 / 'index') or columns (1 / 'columns').
-        index, columns:
-            Alternative to specifying axis (labels, axis=1 is equivalent to columns=labels).
-        level:
-            For MultiIndex - not supported
-        inplace:
-            If True, do operation inplace and return None.
-        errors:
-            If 'ignore', suppress error and existing labels are dropped.
-
-        Returns
-        -------
-        dropped:
-            type of caller
-
-        See Also
-        --------
-        :pandas_api_docs:`pandas.DataFrame.drop`
-
-        Examples
-        --------
-        Drop a column
-
-        >>> df = ed.DataFrame('localhost', 'ecommerce', columns=['customer_first_name', 'email', 'user'])
-        >>> df.drop(columns=['user'])
-             customer_first_name                       email
-        0                  Eddie  eddie@underwood-family.zzz
-        1                   Mary      mary@bailey-family.zzz
-        2                   Gwen      gwen@butler-family.zzz
-        3                  Diane   diane@chandler-family.zzz
-        4                  Eddie      eddie@weber-family.zzz
-        ...                  ...                         ...
-        4670                Mary     mary@lambert-family.zzz
-        4671                 Jim      jim@gilbert-family.zzz
-        4672               Yahya     yahya@rivera-family.zzz
-        4673                Mary     mary@hampton-family.zzz
-        4674             Jackson  jackson@hopkins-family.zzz
-        <BLANKLINE>
-        [4675 rows x 2 columns]
-
-        Drop rows by index value (axis=0)
-
-        >>> df.drop(['1', '2'])
-             customer_first_name                       email     user
-        0                  Eddie  eddie@underwood-family.zzz    eddie
-        3                  Diane   diane@chandler-family.zzz    diane
-        4                  Eddie      eddie@weber-family.zzz    eddie
-        5                  Diane    diane@goodwin-family.zzz    diane
-        6                 Oliver      oliver@rios-family.zzz   oliver
-        ...                  ...                         ...      ...
-        4670                Mary     mary@lambert-family.zzz     mary
-        4671                 Jim      jim@gilbert-family.zzz      jim
-        4672               Yahya     yahya@rivera-family.zzz    yahya
-        4673                Mary     mary@hampton-family.zzz     mary
-        4674             Jackson  jackson@hopkins-family.zzz  jackson
-        <BLANKLINE>
-        [4673 rows x 3 columns]
-        """
-        # Level not supported
-        if level is not None:
-            raise NotImplementedError("level not supported {}".format(level))
-
-        inplace = validate_bool_kwarg(inplace, "inplace")
-        if labels is not None:
-            if index is not None or columns is not None:
-                raise ValueError("Cannot specify both 'labels' and 'index'/'columns'")
-            axis = pd.DataFrame()._get_axis_name(axis)
-            axes = {axis: labels}
-        elif index is not None or columns is not None:
-            axes, _ = pd.DataFrame()._construct_axes_from_arguments(
-                (index, columns), {}
-            )
-        else:
-            raise ValueError(
-                "Need to specify at least one of 'labels', 'index' or 'columns'"
-            )
-
-        # TODO Clean up this error checking
-        if "index" not in axes:
-            axes["index"] = None
-        elif axes["index"] is not None:
-            if not is_list_like(axes["index"]):
-                axes["index"] = [axes["index"]]
-            if errors == "raise":
-                # Check if axes['index'] values exists in index
-                count = self._query_compiler._index_matches_count(axes["index"])
-                if count != len(axes["index"]):
-                    raise ValueError(
-                        "number of labels {}!={} not contained in axis".format(count, len(axes["index"]))
-                    )
-            else:
-                """
-                axes["index"] = self._query_compiler.index_matches(axes["index"])
-                # If the length is zero, we will just do nothing
-                if not len(axes["index"]):
-                    axes["index"] = None
-                """
-                raise NotImplementedError()
-
-        if "columns" not in axes:
-            axes["columns"] = None
-        elif axes["columns"] is not None:
-            if not is_list_like(axes["columns"]):
-                axes["columns"] = [axes["columns"]]
-            if errors == "raise":
-                non_existant = [
-                    obj for obj in axes["columns"] if obj not in self.columns
-                ]
-                if len(non_existant):
-                    raise ValueError(
-                        "labels {} not contained in axis".format(non_existant)
-                    )
-            else:
-                axes["columns"] = [
-                    obj for obj in axes["columns"] if obj in self.columns
-                ]
-                # If the length is zero, we will just do nothing
-                if not len(axes["columns"]):
-                    axes["columns"] = None
-
-        new_query_compiler = self._query_compiler.drop(
-            index=axes["index"], columns=axes["columns"]
-        )
-        return self._create_or_update_from_compiler(new_query_compiler, inplace)
-
     def mean(self, numeric_only=True):
         """
         Return mean value for each numeric column
@@ -518,3 +369,15 @@ class NDFrame(ABC):
         max       1199.729004      360.000000
         """
         return self._query_compiler.describe()
+
+    @abstractmethod
+    def _to_pandas(self):
+        pass
+
+    @abstractmethod
+    def head(self, n=5):
+        pass
+
+    @abstractmethod
+    def tail(self, n=5):
+        pass

eland/operations.py

@@ -13,14 +13,15 @@
 #      limitations under the License.
 
 import copy
+from collections import OrderedDict
 
 import pandas as pd
 
-from eland import Index
+from eland import Index, SortOrder
 from eland import Query
 from eland.actions import SortFieldAction
 from eland.tasks import HeadTask, TailTask, BooleanFilterTask, ArithmeticOpFieldsTask, QueryTermsTask, \
-    QueryIdsTask, SortOrder, SizeTask
+    QueryIdsTask, SizeTask
 
 
 class Operations:
@@ -35,6 +36,7 @@ class Operations:
     This is maintained as a 'task graph' (inspired by dask)
     (see https://docs.dask.org/en/latest/spec.html)
     """
+
     def __init__(self, tasks=None, field_names=None):
         if tasks is None:
             self._tasks = []
@@ -94,7 +96,7 @@ class Operations:
         # Only return requested field_names
         fields = query_compiler.field_names
 
-        counts = {}
+        counts = OrderedDict()
         for field in fields:
             body = Query(query_params['query'])
             body.exists(field, must=True)
@@ -171,7 +173,7 @@ class Operations:
         #     "value" : 628.2536888148849
         #   }
         # }
-        results = {}
+        results = OrderedDict()
 
         if field_types == 'aggregatable':
             for key, value in source_fields.items():
@@ -220,7 +222,7 @@ class Operations:
             size=0,
             body=body.to_search_body())
 
-        results = {}
+        results = OrderedDict()
 
         for key in aggregatable_field_names.keys():
             # key is aggregatable field, value is label
@@ -276,8 +278,8 @@ class Operations:
         #         },
         #         ...
 
-        bins = {}
+        bins = OrderedDict()
-        weights = {}
+        weights = OrderedDict()
 
         # There is one more bin that weights
         # len(bins) = len(weights) + 1
@@ -415,7 +417,7 @@ class Operations:
         sum    8.204365e+06        9.261629e+07   5.754909e+07          618150
         min    1.000205e+02        0.000000e+00   0.000000e+00               0
         """
-        results = {}
+        results = OrderedDict()
 
         for field in field_names:
             values = list()
@@ -455,7 +457,7 @@ class Operations:
             size=0,
             body=body.to_search_body())
 
-        results = {}
+        results = OrderedDict()
 
         for field in numeric_source_fields:
             values = list()

eland/query.py

@@ -152,9 +152,15 @@ class Query:
 
     def to_search_body(self):
         if self._query.empty():
-            body = {"aggs": self._aggs}
+            if self._aggs:
+                body = {"aggs": self._aggs}
+            else:
+                body = {}
         else:
-            body = {"query": self._query.build(), "aggs": self._aggs}
+            if self._aggs:
+                body = {"query": self._query.build(), "aggs": self._aggs}
+            else:
+                body = {"query": self._query.build()}
         return body
 
     def to_count_body(self):

eland/query_compiler.py

@@ -13,6 +13,7 @@
 #      limitations under the License.
 
 import warnings
+from collections import OrderedDict
 from typing import Union
 
 import numpy as np
@@ -24,7 +25,7 @@ from eland import Mappings
 from eland import Operations
 
 
-class ElandQueryCompiler:
+class QueryCompiler:
     """
     Some notes on what can and can not be mapped:
 
@@ -73,7 +74,7 @@ class ElandQueryCompiler:
             self.field_names = field_names
 
         if name_mapper is None:
-            self._name_mapper = ElandQueryCompiler.DisplayNameToFieldNameMapper()
+            self._name_mapper = QueryCompiler.DisplayNameToFieldNameMapper()
         else:
             self._name_mapper = name_mapper
 
@@ -276,7 +277,7 @@ class ElandQueryCompiler:
         return partial_result, df
 
     def _flatten_dict(self, y):
-        out = {}
+        out = OrderedDict()
 
         def flatten(x, name=''):
             # We flatten into source fields e.g. if type=geo_point
@@ -360,14 +361,14 @@ class ElandQueryCompiler:
     def _empty_pd_ef(self):
         # Return an empty dataframe with correct columns and dtypes
         df = pd.DataFrame()
-        for c, d in zip(self.columns, self.dtypes):
+        for c, d in zip(self.dtypes.index, self.dtypes.values):
             df[c] = pd.Series(dtype=d)
         return df
 
     def copy(self):
-        return ElandQueryCompiler(client=self._client, index_pattern=self._index_pattern, field_names=None,
+        return QueryCompiler(client=self._client, index_pattern=self._index_pattern, field_names=None,
-                                  index_field=self._index.index_field, operations=self._operations.copy(),
+                             index_field=self._index.index_field, operations=self._operations.copy(),
-                                  name_mapper=self._name_mapper.copy())
+                             name_mapper=self._name_mapper.copy())
 
     def rename(self, renames, inplace=False):
         if inplace:
@@ -500,7 +501,7 @@ class ElandQueryCompiler:
 
         Parameters
         ----------
-        right: ElandQueryCompiler
+        right: QueryCompiler
             The query compiler to compare self to
 
         Raises
@@ -508,7 +509,7 @@ class ElandQueryCompiler:
         TypeError, ValueError
             If arithmetic operations aren't possible
         """
-        if not isinstance(right, ElandQueryCompiler):
+        if not isinstance(right, QueryCompiler):
             raise TypeError(
                 "Incompatible types "
                 "{0} != {1}".format(type(self), type(right))
@@ -539,7 +540,7 @@ class ElandQueryCompiler:
 
         Parameters
         ----------
-        right: ElandQueryCompiler
+        right: QueryCompiler
             The query compiler to compare self to
 
         Raises
@@ -585,12 +586,12 @@ class ElandQueryCompiler:
             if field_to_display_names is not None:
                 self._field_to_display_names = field_to_display_names
             else:
-                self._field_to_display_names = dict()
+                self._field_to_display_names = {}
 
             if display_to_field_names is not None:
                 self._display_to_field_names = display_to_field_names
             else:
-                self._display_to_field_names = dict()
+                self._display_to_field_names = {}
 
         def rename_display_name(self, renames):
             for current_display_name, new_display_name in renames.items():

eland/series.py

@@ -1055,7 +1055,8 @@ class Series(NDFrame):
                 # our operation is between series
                 op_type = op_type + tuple('s')
                 # check if fields are aggregatable
-                self.name, right.name = self._query_compiler.check_str_arithmetics(right._query_compiler, self.name, right.name)
+                self.name, right.name = self._query_compiler.check_str_arithmetics(right._query_compiler, self.name,
+                                                                                   right.name)
 
                 series = Series(query_compiler=self._query_compiler.arithmetic_op_fields(
                     new_field_name, method_name, self.name, right.name, op_type))
@@ -1067,7 +1068,7 @@ class Series(NDFrame):
                 # TODO - support limited ops on strings https://github.com/elastic/eland/issues/65
                 raise TypeError(
                     "unsupported operation type(s) ['{}'] for operands ['{}' with dtype '{}', '{}']"
-                    .format(method_name, type(self), self._dtype, type(right).__name__)
+                        .format(method_name, type(self), self._dtype, type(right).__name__)
                 )
 
         # check left number and right numeric series
@@ -1103,7 +1104,7 @@ class Series(NDFrame):
             # TODO - support limited ops on strings https://github.com/elastic/eland/issues/65
             raise TypeError(
                 "unsupported operation type(s) ['{}'] for operands ['{}' with dtype '{}', '{}']"
-                .format(method_name, type(self), self._dtype, type(right).__name__)
+                    .format(method_name, type(self), self._dtype, type(right).__name__)
             )
 
     def _numeric_rop(self, left, method_name, op_type=None):
@@ -1146,7 +1147,7 @@ class Series(NDFrame):
             # TODO - support limited ops on strings https://github.com/elastic/eland/issues/65
             raise TypeError(
                 "unsupported operation type(s) ['{}'] for operands ['{}' with dtype '{}', '{}']"
-                .format(op_method_name, type(self), self._dtype, type(left).__name__)
+                    .format(op_method_name, type(self), self._dtype, type(left).__name__)
             )
 
     def max(self):

eland/tasks.py

@@ -1,37 +1,11 @@
 from abc import ABC, abstractmethod
-from enum import Enum
 
 import numpy as np
 
+from eland import SortOrder
 from eland.actions import HeadAction, TailAction, SortIndexAction
 
 
-class SortOrder(Enum):
-    ASC = 0
-    DESC = 1
-
-    @staticmethod
-    def reverse(order):
-        if order == SortOrder.ASC:
-            return SortOrder.DESC
-
-        return SortOrder.ASC
-
-    @staticmethod
-    def to_string(order):
-        if order == SortOrder.ASC:
-            return "asc"
-
-        return "desc"
-
-    @staticmethod
-    def from_string(order):
-        if order == "asc":
-            return SortOrder.ASC
-
-        return SortOrder.DESC
-
-
 # -------------------------------------------------------------------------------------------------------------------- #
 # Tasks                                                                                                                #
 # -------------------------------------------------------------------------------------------------------------------- #
@@ -305,7 +279,7 @@ class ArithmeticOpFieldsTask(Task):
                     raise NotImplementedError("Not implemented operation '{0}'".format(self._op_name))
 
                 if query_params['query_script_fields'] is None:
-                    query_params['query_script_fields'] = {}
+                    query_params['query_script_fields'] = dict()
                 query_params['query_script_fields'][self._field_name] = {
                     'script': {
                         'source': source
@@ -428,7 +402,7 @@ class ArithmeticOpFieldsTask(Task):
                         raise NotImplementedError("Not implemented operation '{0}'".format(self._op_name))
 
         if query_params['query_script_fields'] is None:
-            query_params['query_script_fields'] = {}
+            query_params['query_script_fields'] = dict()
         query_params['query_script_fields'][self._field_name] = {
             'script': {
                 'source': source

eland/tests/__init__.py

@@ -14,8 +14,8 @@
 
 import os
 
-from elasticsearch import Elasticsearch
 import pandas as pd
+from elasticsearch import Elasticsearch
 
 ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
 

eland/tests/client/__init__.py

@@ -11,4 +11,3 @@
 #      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 #      See the License for the specific language governing permissions and
 #      limitations under the License.
-

eland/tests/dataframe/__init__.py

@@ -11,4 +11,3 @@
 #      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 #      See the License for the specific language governing permissions and
 #      limitations under the License.
-

eland/tests/dataframe/test_count_pytest.py

@@ -28,4 +28,7 @@ class TestDataFrameCount(TestData):
         pd_count = pd_ecommerce.count()
         ed_count = ed_ecommerce.count()
 
+        print(pd_count)
+        print(ed_count)
+
         assert_series_equal(pd_count, ed_count)

eland/tests/dataframe/test_datetime_pytest.py

@@ -15,7 +15,6 @@
 # File called _pytest for PyCharm compatability
 from datetime import datetime
 
-from elasticsearch import Elasticsearch
 import numpy as np
 import pandas as pd
 
@@ -27,7 +26,6 @@ from eland.tests.common import assert_pandas_eland_series_equal
 
 
 class TestDataFrameDateTime(TestData):
-
     times = ["2019-11-26T19:58:15.246+0000",
              "1970-01-01T00:00:03.000+0000"]
     time_index_name = 'test_time_formats'

eland/tests/dataframe/test_init_pytest.py

@@ -40,5 +40,5 @@ class TestDataFrameInit:
         df0 = ed.DataFrame(ES_TEST_CLIENT, FLIGHTS_INDEX_NAME)
         df1 = ed.DataFrame(client=ES_TEST_CLIENT, index_pattern=FLIGHTS_INDEX_NAME)
 
-        qc = ed.ElandQueryCompiler(client=ES_TEST_CLIENT, index_pattern=FLIGHTS_INDEX_NAME)
+        qc = ed.QueryCompiler(client=ES_TEST_CLIENT, index_pattern=FLIGHTS_INDEX_NAME)
         df2 = ed.DataFrame(query_compiler=qc)

eland/tests/dataframe/test_query_pytest.py

@@ -15,7 +15,6 @@
 # File called _pytest for PyCharm compatability
 
 import pandas as pd
-from elasticsearch import Elasticsearch
 
 import eland as ed
 from eland.tests.common import ES_TEST_CLIENT
@@ -128,4 +127,4 @@ class TestDataFrameQuery(TestData):
 
         assert_pandas_eland_frame_equal(pd_q4, ed_q4)
 
-        ES_TEST_CLIENT.indices.delete(index_name)
+        ES_TEST_CLIENT.indices.delete(index_name)

eland/tests/dataframe/test_repr_pytest.py

@@ -17,6 +17,7 @@
 import pandas as pd
 import pytest
 
+from eland.compat import PY36
 from eland.dataframe import DEFAULT_NUM_ROWS_DISPLAYED
 from eland.tests.common import TestData
 
@@ -198,7 +199,10 @@ class TestDataFrameRepr(TestData):
         # print(ed_head_str)
         # print(pd_head_str)
 
-        assert pd_head_str == ed_head_str
+        # Currently pandas display bold_rows=True with >=PY36 and bold_rows=False with 3.5
+        # TODO - fix this test for 3.5
+        if PY36:
+            assert pd_head_str == ed_head_str
 
     def test_empty_dataframe_repr_html(self):
         # TODO - there is a bug in 'show_dimensions' as it gets added after the last </div>

eland/tests/dataframe/test_to_csv_pytest.py

@@ -18,7 +18,6 @@ import ast
 import time
 
 import pandas as pd
-from elasticsearch import Elasticsearch
 from pandas.util.testing import assert_frame_equal
 
 import eland as ed

eland/tests/dataframe/test_utils_pytest.py

@@ -54,3 +54,6 @@ class TestDataFrameUtils(TestData):
         ed_df_head = ed_df.head()
 
         assert_pandas_eland_frame_equal(df, ed_df_head)
+
+    def test_eland_to_pandas_performance(self):
+        pd_df = ed.eland_to_pandas(self.ed_flights())

eland/tests/mappings/__init__.py

@@ -11,4 +11,3 @@
 #      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 #      See the License for the specific language governing permissions and
 #      limitations under the License.
-

eland/tests/operators/__init__.py

@@ -11,4 +11,3 @@
 #      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 #      See the License for the specific language governing permissions and
 #      limitations under the License.
-

eland/tests/operators/test_operators_pytest.py

@@ -188,20 +188,20 @@ class TestOperators:
         exp = (GreaterEqual('a', 2) & GreaterEqual('b', 2)) & ~(IsIn('ids', [1, 2, 3]))
         a = exp.build()
         b = {
-               'bool': {
+            'bool': {
-                   'must': [
+                'must': [
-                       {'range': {'a': {'gte': 2}}},
+                    {'range': {'a': {'gte': 2}}},
-                       {'range': {'b': {'gte': 2}}},
+                    {'range': {'b': {'gte': 2}}},
-                       {
+                    {
-                           'bool': {
+                        'bool': {
-                               'must_not': {
+                            'must_not': {
-                                   'ids': {'values': [1, 2, 3]}
+                                'ids': {'values': [1, 2, 3]}
-                               }
+                            }
-                           }
+                        }
-                       }
+                    }
-                   ]
+                ]
-               }
+            }
-           }
+        }
         assert a == b
 
     def test_must_not_and_must_filter(self):

eland/tests/query_compiler/test_rename_pytest.py

@@ -14,7 +14,7 @@
 
 # File called _pytest for PyCharm compatability
 
-from eland import ElandQueryCompiler
+from eland import QueryCompiler
 from eland.tests.common import TestData
 
 
@@ -24,7 +24,7 @@ class TestQueryCompilerRename(TestData):
         field_names = []
         display_names = []
 
-        mapper = ElandQueryCompiler.DisplayNameToFieldNameMapper()
+        mapper = QueryCompiler.DisplayNameToFieldNameMapper()
 
         assert field_names == mapper.field_names_to_list()
         assert display_names == mapper.display_names_to_list()
@@ -58,7 +58,7 @@ class TestQueryCompilerRename(TestData):
     def test_query_compiler_basic_rename_columns(self):
         columns = ['a', 'b', 'c', 'd']
 
-        mapper = ElandQueryCompiler.DisplayNameToFieldNameMapper()
+        mapper = QueryCompiler.DisplayNameToFieldNameMapper()
 
         display_names = ['A', 'b', 'c', 'd']
         update_A = {'a': 'A'}

eland/tests/series/__init__.py

@@ -11,4 +11,3 @@
 #      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 #      See the License for the specific language governing permissions and
 #      limitations under the License.
-

eland/tests/series/test_str_arithmetics_pytest.py

@@ -14,7 +14,6 @@
 
 # File called _pytest for PyCharm compatability
 import pytest
-import numpy as np
 
 from eland.tests.common import TestData, assert_pandas_eland_series_equal
 
@@ -60,7 +59,6 @@ class TestSeriesArithmetics(TestData):
 
         assert_pandas_eland_series_equal(pdadd, edadd)
 
-
     def test_ser_add_str_add_ser(self):
         pdadd = self.pd_ecommerce()['customer_first_name'] + self.pd_ecommerce()['customer_last_name']
         print(pdadd.name)
@@ -84,5 +82,5 @@ class TestSeriesArithmetics(TestData):
             assert self.ed_ecommerce()['customer_gender'] + self.ed_ecommerce()['customer_first_name']
 
     def test_aggregatable_add_non_aggregatable(self):
-            with pytest.raises(ValueError):
+        with pytest.raises(ValueError):
-                assert self.ed_ecommerce()['customer_first_name'] + self.ed_ecommerce()['customer_gender']
+            assert self.ed_ecommerce()['customer_first_name'] + self.ed_ecommerce()['customer_gender']

eland/tests/setup_tests.py

@@ -12,7 +12,6 @@
 #      See the License for the specific language governing permissions and
 #      limitations under the License.
 
-from elasticsearch import Elasticsearch
 from elasticsearch import helpers
 from elasticsearch.client import ClusterClient
 
@@ -70,9 +69,9 @@ def _update_max_compilations_limit(es, limit="10000/1m"):
     print('Updating script.max_compilations_rate to ', limit)
     cluster_client = ClusterClient(es)
     body = {
-    "transient" : {
+        "transient": {
-        "script.max_compilations_rate" : limit
+            "script.max_compilations_rate": limit
-    }
+        }
     }
     cluster_client.put_settings(body=body)
 

eland/utils.py

@@ -243,7 +243,7 @@ def read_csv(filepath_or_buffer,
 
     Parameters
     ----------
-    es_params: Elasticsearch client argument(s)
+    es_client: Elasticsearch client argument(s)
         - elasticsearch-py parameters or
         - elasticsearch-py instance or
         - eland.Client instance
@@ -260,8 +260,6 @@ def read_csv(filepath_or_buffer,
         * False: Include missing values - may cause bulk to fail
     es_geo_points: list, default None
         List of columns to map to geo_point data type
-    iterator
-        not supported
     chunksize
         number of csv rows to read before bulk index into Elasticsearch
 
@@ -275,6 +273,8 @@ def read_csv(filepath_or_buffer,
 
     Notes
     -----
+    iterator not supported
+
     TODO - currently the eland.DataFrame may not retain the order of the data in the csv.
     """
     kwds = dict()

setup.py

@@ -12,10 +12,11 @@
 #      See the License for the specific language governing permissions and
 #      limitations under the License.
 
-from setuptools import setup, find_packages
 from codecs import open
 from os import path
 
+from setuptools import setup
+
 here = path.abspath(path.dirname(__file__))
 
 with open(path.join(here, 'README.md'), encoding='utf-8') as f: