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testing.json
{
"cells": [
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import datetime"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"values = pd.read_sql(con="postgresql://postgres:@localhost/ass-dev", sql="value")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"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>state</th>\n",
" <th>en</th>\n",
" <th>ma</th>\n",
" <th>sv</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>value_int</th>\n",
" <td>12.560006</td>\n",
" <td>12.470872</td>\n",
" <td>12.496125</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
"state en ma sv\n",
"value_int 12.560006 12.470872 12.496125"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"values.pivot_table(columns="state", values="value_int", aggfunc="mean")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"15.0"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"values["value_int"].median()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"values.pivot_table?"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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" 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>id</th>\n",
" <th>attribute_codename</th>\n",
" <th>datetime</th>\n",
" <th>state</th>\n",
" <th>value_int</th>\n",
" <th>value_str</th>\n",
" <th>time_created</th>\n",
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" <td>sv</td>\n",
" <td>17.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>81afc712-6ef6-44ef-b9b6-ba0cffb4f2f6</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>b8bd638b-e1fc-4d83-ad49-37083482c9e4</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>17.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>4617a5af-f828-4b3e-bf4f-df7dc46e26b2</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>10.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>af892ce3-21c7-4a6f-901d-d75dbfec9150</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>0.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>eee6f78b-91c3-4358-bf19-d38a3870b41d</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>17.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>036336a4-fafd-4052-823d-c7e07ade911b</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>17.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>4bb592dc-96ad-4fe6-889c-5a16b30ed3c8</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>17.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>81ceb6c9-47db-4891-918b-0d50216433ea</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>17.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>11c76f09-830d-4960-ac27-a7c8a48abe60</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>10.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" id attribute_codename datetime \\\n",
"entity \n",
"1 8a884092-6ffa-4f5f-bf34-00e902e4419d grade.points 2019-01-01 \n",
"2 81afc712-6ef6-44ef-b9b6-ba0cffb4f2f6 grade.points 2019-01-01 \n",
"3 b8bd638b-e1fc-4d83-ad49-37083482c9e4 grade.points 2019-01-01 \n",
"4 4617a5af-f828-4b3e-bf4f-df7dc46e26b2 grade.points 2019-01-01 \n",
"5 af892ce3-21c7-4a6f-901d-d75dbfec9150 grade.points 2019-01-01 \n",
"6 eee6f78b-91c3-4358-bf19-d38a3870b41d grade.points 2019-01-01 \n",
"7 036336a4-fafd-4052-823d-c7e07ade911b grade.points 2019-01-01 \n",
"8 4bb592dc-96ad-4fe6-889c-5a16b30ed3c8 grade.points 2019-01-01 \n",
"9 81ceb6c9-47db-4891-918b-0d50216433ea grade.points 2019-01-01 \n",
"10 11c76f09-830d-4960-ac27-a7c8a48abe60 grade.points 2019-01-01 \n",
"\n",
" state value_int value_str time_created time_updated \n",
"entity \n",
"1 sv 17.5 None 2019-06-05 16:46:51.266049 NaT \n",
"2 sv 15.0 None 2019-06-05 16:46:51.266049 NaT \n",
"3 sv 17.5 None 2019-06-05 16:46:51.266049 NaT \n",
"4 sv 10.0 None 2019-06-05 16:46:51.266049 NaT \n",
"5 sv 0.0 None 2019-06-05 16:46:51.266049 NaT \n",
"6 sv 17.5 None 2019-06-05 16:46:51.266049 NaT \n",
"7 sv 17.5 None 2019-06-05 16:46:51.266049 NaT \n",
"8 sv 17.5 None 2019-06-05 16:46:51.266049 NaT \n",
"9 sv 17.5 None 2019-06-05 16:46:51.266049 NaT \n",
"10 sv 10.0 None 2019-06-05 16:46:51.266049 NaT "
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"values.head(10)"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
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" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
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" <td>15.0</td>\n",
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" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
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" <td>20.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>7edc6156-67ed-4d3f-8678-d6de376636ae</td>\n",
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" <td>2019-01-01</td>\n",
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" <td>20.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1c11ecb3-a10e-4d40-ab05-2aca092c8ae9</td>\n",
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" </tr>\n",
" <tr>\n",
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" <td>10.0</td>\n",
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" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>17.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>ae8e6469-fcac-4cc1-a8ec-196df760fe8a</td>\n",
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" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
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" <td>3a89f5f7-dd43-4fb4-a75b-382486e5b512</td>\n",
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" <td>0.0</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>e9068e69-25ae-4686-8e87-6307ecc47037</td>\n",
" <td>np.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>en</td>\n",
" <td>0.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>92c9fcc8-4c10-4908-955f-31fede65a62e</td>\n",
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" <td>2019-01-01</td>\n",
" <td>ma</td>\n",
" <td>0.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>4617a5af-f828-4b3e-bf4f-df7dc46e26b2</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>10.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>aa76be24-78a8-477e-8202-f1ddc9d6c44c</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>en</td>\n",
" <td>17.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>726a7dc5-7ad0-454d-8bf2-e6cf46871f7a</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>ma</td>\n",
" <td>12.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>a3394e9c-72ef-48e5-b0d9-dad595b1d527</td>\n",
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" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2b1dbbd3-7dbd-4f31-9c10-cbda0a74ea72</td>\n",
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" <td>2019-01-01</td>\n",
" <td>en</td>\n",
" <td>0.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>32900b22-d168-49a2-9f6d-865fc23e3cc1</td>\n",
" <td>np.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>ma</td>\n",
" <td>10.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
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],
"text/plain": [
" id attribute_codename datetime \\\n",
"entity \n",
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"\n",
" state value_int value_str time_created time_updated \n",
"entity \n",
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"3 ma 15.0 None 2019-06-05 16:46:51.266049 NaT \n",
"3 sv 0.0 None 2019-06-05 16:46:51.266049 NaT \n",
"3 en 0.0 None 2019-06-05 16:46:51.266049 NaT \n",
"3 ma 0.0 None 2019-06-05 16:46:51.266049 NaT \n",
"4 sv 10.0 None 2019-06-05 16:46:51.266049 NaT \n",
"4 en 17.5 None 2019-06-05 16:46:51.266049 NaT \n",
"4 ma 12.5 None 2019-06-05 16:46:51.266049 NaT \n",
"4 sv 0.0 None 2019-06-05 16:46:51.266049 NaT \n",
"4 en 0.0 None 2019-06-05 16:46:51.266049 NaT \n",
"4 ma 10.0 None 2019-06-05 16:46:51.266049 NaT "
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"values.loc[[1,2,3,4]]"
]
},
{
"cell_type": "code",
"execution_count": 81,
"metadata": {},
"outputs": [
{
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" <td>2019-06-05 16:46:51.266049</td>\n",
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" <td>2019-06-05 16:46:51.266049</td>\n",
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" <th>14</th>\n",
" <td>1d547fb0-4c31-4518-bcd5-beaee80becf9</td>\n",
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" <td>0.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
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" <td>2019-06-05 16:46:51.266049</td>\n",
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" <td>sv</td>\n",
" <td>0.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
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" <th>17</th>\n",
" <td>28860870-ae72-44a6-8a79-1237ad2cab0e</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>10.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>94f83c7f-279c-4794-ae92-7f2ff3f62d98</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>17.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
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" <th>19</th>\n",
" <td>fa52245a-6106-4509-bf81-6da14479264c</td>\n",
" <td>grade.points</td>\n",
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" <th>20</th>\n",
" <td>8f554594-6c1c-4000-830c-6915844892c5</td>\n",
" <td>grade.points</td>\n",
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" <td>sv</td>\n",
" <td>15.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>f33a3b44-5459-4287-bcb2-2783df8066b3</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>10.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>56f3c737-69d7-49e0-9fba-af4b1b7a975b</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>17.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>2125b1bf-b228-428c-8c09-6fa13703bb8b</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>15.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>5302d07c-4e7c-440c-a521-25239c1c8758</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>20.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>e82da7a7-6962-433b-916a-c87558e9cb64</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>12.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>a287702f-51cc-4c7b-a18d-7a66ae770ab4</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>12.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>96daaa02-5aee-42cb-aa30-ea44db59937e</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>17.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>fe6d0816-aad3-4650-aa00-eac0550a8db6</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>12.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>f6e5528a-50d1-411f-9a65-fd7099efae6b</td>\n",
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" <td>12.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
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" <th>30</th>\n",
" <td>ed34ab38-4f71-4772-9efe-48378b4f2f1a</td>\n",
" <td>grade.points</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>15.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
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"</table>\n",
"<p>29997 rows × 8 columns</p>\n",
"</div>"
],
"text/plain": [
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"... ... ... ... ... ... \n",
"9970 ma 20.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9971 ma 15.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9972 ma 17.5 None 2019-06-05 16:46:51.266049 NaT \n",
"9973 ma 10.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9974 ma 0.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9975 ma 15.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9976 ma 12.5 None 2019-06-05 16:46:51.266049 NaT \n",
"9977 ma 0.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9978 ma 0.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9979 ma 0.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9980 ma 12.5 None 2019-06-05 16:46:51.266049 NaT \n",
"9981 ma 12.5 None 2019-06-05 16:46:51.266049 NaT \n",
"9982 ma 20.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9983 ma 12.5 None 2019-06-05 16:46:51.266049 NaT \n",
"9984 ma 12.5 None 2019-06-05 16:46:51.266049 NaT \n",
"9985 ma 20.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9986 ma 12.5 None 2019-06-05 16:46:51.266049 NaT \n",
"9987 ma 10.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9988 ma 20.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9989 ma 17.5 None 2019-06-05 16:46:51.266049 NaT \n",
"9990 ma 20.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9991 ma 0.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9992 ma 10.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9993 ma 15.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9994 ma 12.5 None 2019-06-05 16:46:51.266049 NaT \n",
"9995 ma 20.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9996 ma 20.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9997 ma 10.0 None 2019-06-05 16:46:51.266049 NaT \n",
"9998 ma 17.5 None 2019-06-05 16:46:51.266049 NaT \n",
"9999 ma 15.0 None 2019-06-05 16:46:51.266049 NaT \n",
"\n",
"[29997 rows x 8 columns]"
]
},
"execution_count": 81,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"values[values["attribute_codename"] == "grade.points"]"
]
},
{
"cell_type": "code",
"execution_count": 70,
"metadata": {},
"outputs": [],
"source": [
"tmp = values.loc[[1,2,3,5]].groupby(by=["attribute_codename", "state"]).mean()"
]
},
{
"cell_type": "code",
"execution_count": 82,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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" }\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></th>\n",
" <th>value_int</th>\n",
" </tr>\n",
" <tr>\n",
" <th>attribute_codename</th>\n",
" <th>state</th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th rowspan=\"3\" valign=\"top\">grade.points</th>\n",
" <th>en</th>\n",
" <td>12.500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ma</th>\n",
" <td>17.500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>sv</th>\n",
" <td>12.500</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"3\" valign=\"top\">np.points</th>\n",
" <th>en</th>\n",
" <td>12.500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ma</th>\n",
" <td>8.125</td>\n",
" </tr>\n",
" <tr>\n",
" <th>sv</th>\n",
" <td>14.375</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" value_int\n",
"attribute_codename state \n",
"grade.points en 12.500\n",
" ma 17.500\n",
" sv 12.500\n",
"np.points en 12.500\n",
" ma 8.125\n",
" sv 14.375"
]
},
"execution_count": 82,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tmp"
]
},
{
"cell_type": "code",
"execution_count": 78,
"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></th>\n",
" <th>value_int</th>\n",
" </tr>\n",
" <tr>\n",
" <th>attribute_codename</th>\n",
" <th>state</th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th rowspan=\"3\" valign=\"top\">grade.points</th>\n",
" <th>en</th>\n",
" <td>12.500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ma</th>\n",
" <td>17.500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>sv</th>\n",
" <td>12.500</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"3\" valign=\"top\">np.points</th>\n",
" <th>en</th>\n",
" <td>12.500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ma</th>\n",
" <td>8.125</td>\n",
" </tr>\n",
" <tr>\n",
" <th>sv</th>\n",
" <td>14.375</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" value_int\n",
"attribute_codename state \n",
"grade.points en 12.500\n",
" ma 17.500\n",
" sv 12.500\n",
"np.points en 12.500\n",
" ma 8.125\n",
" sv 14.375"
]
},
"execution_count": 78,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tmp.loc[["grade.points", "np.points"]]"
]
},
{
"cell_type": "code",
"execution_count": 79,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""{\"value_int\":{\"[\"grade.points\",\"en\"]\":12.5,\"[\"grade.points\",\"ma\"]\":17.5,\"[\"grade.points\",\"sv\"]\":12.5,\"[\"np.points\",\"en\"]\":12.5,\"[\"np.points\",\"ma\"]\":8.125,\"[\"np.points\",\"sv\"]\":14.375}}""
]
},
"execution_count": 79,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tmp.loc[["grade.points", "np.points"]].to_json()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Number of values in a singular state"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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"\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>id</th>\n",
" <th>attribute_codename</th>\n",
" <th>entity</th>\n",
" <th>datetime</th>\n",
" <th>state</th>\n",
" <th>value_int</th>\n",
" <th>value_str</th>\n",
" <th>time_created</th>\n",
" <th>time_updated</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>8a884092-6ffa-4f5f-bf34-00e902e4419d</td>\n",
" <td>grade.points</td>\n",
" <td>1</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>17.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>81afc712-6ef6-44ef-b9b6-ba0cffb4f2f6</td>\n",
" <td>grade.points</td>\n",
" <td>2</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>15.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>b8bd638b-e1fc-4d83-ad49-37083482c9e4</td>\n",
" <td>grade.points</td>\n",
" <td>3</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>17.5</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4617a5af-f828-4b3e-bf4f-df7dc46e26b2</td>\n",
" <td>grade.points</td>\n",
" <td>4</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>10.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>af892ce3-21c7-4a6f-901d-d75dbfec9150</td>\n",
" <td>grade.points</td>\n",
" <td>5</td>\n",
" <td>2019-01-01</td>\n",
" <td>sv</td>\n",
" <td>0.0</td>\n",
" <td>None</td>\n",
" <td>2019-06-05 16:46:51.266049</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" id attribute_codename entity datetime \\\n",
"0 8a884092-6ffa-4f5f-bf34-00e902e4419d grade.points 1 2019-01-01 \n",
"1 81afc712-6ef6-44ef-b9b6-ba0cffb4f2f6 grade.points 2 2019-01-01 \n",
"2 b8bd638b-e1fc-4d83-ad49-37083482c9e4 grade.points 3 2019-01-01 \n",
"3 4617a5af-f828-4b3e-bf4f-df7dc46e26b2 grade.points 4 2019-01-01 \n",
"4 af892ce3-21c7-4a6f-901d-d75dbfec9150 grade.points 5 2019-01-01 \n",
"\n",
" state value_int value_str time_created time_updated \n",
"0 sv 17.5 None 2019-06-05 16:46:51.266049 NaT \n",
"1 sv 15.0 None 2019-06-05 16:46:51.266049 NaT \n",
"2 sv 17.5 None 2019-06-05 16:46:51.266049 NaT \n",
"3 sv 10.0 None 2019-06-05 16:46:51.266049 NaT \n",
"4 sv 0.0 None 2019-06-05 16:46:51.266049 NaT "
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"values.head(5)"
]
},
{
"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 tr th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe thead tr:last-of-type th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th colspan=\"2\" halign=\"left\">value_int</th>\n",
" </tr>\n",
" <tr>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th>mean</th>\n",
" <th>median</th>\n",
" </tr>\n",
" <tr>\n",
" <th>datetime</th>\n",
" <th>state</th>\n",
" <th>attribute_codename</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th rowspan=\"6\" valign=\"top\">2019-01-01</th>\n",
" <th rowspan=\"2\" valign=\"top\">en</th>\n",
" <th>grade.points</th>\n",
" <td>12.549255</td>\n",
" <td>15.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>np.points</th>\n",
" <td>12.570757</td>\n",
" <td>15.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">ma</th>\n",
" <th>grade.points</th>\n",
" <td>12.510751</td>\n",
" <td>15.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>np.points</th>\n",
" <td>12.430993</td>\n",
" <td>12.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">sv</th>\n",
" <th>grade.points</th>\n",
" <td>12.488499</td>\n",
" <td>12.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>np.points</th>\n",
" <td>12.503750</td>\n",
" <td>15.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" value_int \n",
" mean median\n",
"datetime state attribute_codename \n",
"2019-01-01 en grade.points 12.549255 15.0\n",
" np.points 12.570757 15.0\n",
" ma grade.points 12.510751 15.0\n",
" np.points 12.430993 12.5\n",
" sv grade.points 12.488499 12.5\n",
" np.points 12.503750 15.0"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"values.pivot_table(values=["value_int"], index=["datetime", "state", "attribute_codename"], aggfunc={"value_int": ["mean", "median"]})"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"sv_grades = values[(values["attribute_codename"] == "grade.points") & (values["state"] == "sv")]"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"10.0 1714\n",
"15.0 1693\n",
"17.5 1681\n",
"12.5 1664\n",
"0.0 1641\n",
"20.0 1606\n",
"Name: value_int, dtype: int64"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sv_grades.value_int.value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[{"2019-05-03": []}]"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"[\n",
" {"2019-05-03": [\n",
" {\n",
" "group": "9a__girls",\n",
" "attribute": "grade.points",\n",
" # "state": "sv",\n",
" "results": [{\n",
" "count_datapoints": 1231231,\n",
" "median": 12.4\n",
" "mean": 11.3,\n",
" "operation": \n",
"\n",
" }, {\n",
" # ... \n",
" }, {\n",
" "group": "9a__girls",\n",
" "attribute": "grade.points",\n",
" "state": "en",\n",
" # ...\n",
" }],\n",
" \n",
"]"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"input_data = {\n",
" \"operations\": [\"mean\", \"median\", \"sum\"],\n",
" \"attributes\": [\"grade.points\", \"np.points\"],\n",
" \"interval\": [datetime.datetime(2019, 1, 1), datetime.datetime(2019, 1, 1)],\n",
" \"entities\": {\n",
" \"1\": [1, 10, 11, 100, 101, 110, 111, 1001, 1010, 1011, 1100, 1101, 1110, 1111],\n",
" \"2\": [2, 20, 22, 200, 202, 220, 222, 2002, 2020, 2022, 2200, 2202, 2220, 2222],\n",
" \"3\": [3, 30, 33, 300, 303, 330, 333, 3003, 3030, 3033, 3300, 3303, 3330, 3333],\n",
" \"4\": [4, 40, 44, 400, 404, 440, 444, 4004, 4040, 4044, 4400, 4404, 4440, 4444],\n",
" \"5\": [5, 50, 55, 500, 505, 550, 555, 5005, 5050, 5055, 5500, 5505, 5550, 5555],\n",
" \"6\": [6, 60, 66, 600, 606, 660, 666, 6006, 6060, 6066, 6600, 6606, 6660, 6666],\n",
" \"7\": [7, 70, 77, 700, 707, 770, 777, 7007, 7070, 7077, 7700, 7707, 7770, 7777],\n",
" \"8\": [8, 80, 88, 800, 808, 880, 888, 8008, 8080, 8088, 8800, 8808, 8880, 8888],\n",
" \"9\": [9, 90, 99, 900, 909, 990, 999, 9009, 9090, 9099, 9900, 9909, 9990, 9999],\n",
" \"11\": [11, 110, 111, 1101, 1110, 1111],\n",
" \"22\": [22, 220, 222, 2201, 2220, 2222],\n",
" \"33\": [33, 330, 333, 3303, 3330, 3333],\n",
" \"44\": [44, 440, 444, 4404, 4440, 4444],\n",
" \"55\": [55, 550, 555, 5505, 5550, 5555],\n",
" \"66\": [66, 660, 666, 6606, 6660, 6666],\n",
" \"77\": [77, 770, 777, 7707, 7770, 7777],\n",
" \"88\": [88, 880, 888, 8808, 8880, 8888],\n",
" \"99\": [99, 990, 999, 9909, 9990, 9999],\n",
" },\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1\n",
"2\n",
"3\n",
"4\n",
"5\n",
"6\n",
"7\n",
"8\n",
"9\n",
"11\n",
"22\n",
"33\n",
"44\n",
"55\n",
"66\n",
"77\n",
"88\n",
"99\n"
]
}
],
"source": [
"for key, val in input_data[\"entities\"].items():\n",
" print(key)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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