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1 change: 0 additions & 1 deletion .vscode/settings.json
Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,6 @@
"files.autoSave": "afterDelay",
"screencastMode.onlyKeyboardShortcuts": true,
"terminal.integrated.fontSize": 18,
"workbench.activityBar.visible": true,
"workbench.colorTheme": "Visual Studio Dark",
"workbench.fontAliasing": "antialiased",
"workbench.statusBar.visible": true
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Binary file modified data/nyc_parking_violations.db
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Binary file modified data/prod_nyc_parking_violations.db
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3 changes: 2 additions & 1 deletion nyc_parking_violations/profiles.yml
Original file line number Diff line number Diff line change
Expand Up @@ -9,4 +9,5 @@ nyc_parking_violations:
# start in the root directory and not in the
# nyc_parking_violations directory
path: './data/prod_nyc_parking_violations.db'
target: dev
target: dev

264 changes: 260 additions & 4 deletions run_sql_queries_here.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
"execution_count": null,
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -12,17 +12,273 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 2,
"metadata": {},
"outputs": [],
"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>registration_state</th>\n",
" <th>ticket_count</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>NJ</td>\n",
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" <td>1787</td>\n",
" </tr>\n",
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" <td>840</td>\n",
" </tr>\n",
" <tr>\n",
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" <th>59</th>\n",
" <td>NB</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>60</th>\n",
" <td>PE</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>61</th>\n",
" <td>SK</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
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"</div>"
],
"text/plain": [
" registration_state ticket_count\n",
"0 NJ 9258\n",
"1 PA 3514\n",
"2 FL 2414\n",
"3 CT 1787\n",
"4 GA 840\n",
".. ... ...\n",
"57 AB 1\n",
"58 BC 1\n",
"59 NB 1\n",
"60 PE 1\n",
"61 SK 1\n",
"\n",
"[62 rows x 2 columns]"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sql_query = '''\n",
"show tables\n",
"SELECT * FROM gold_vehicles_metrics\n",
"'''\n",
"\n",
"with duckdb.connect('data/nyc_parking_violations.db') as con:\n",
" display(con.sql(sql_query).df())"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"sql_query_import_1 ='''\n",
"CREATE OR REPLACE TABLE parking_violations_codes AS\n",
"SELECT *\n",
"FROM read_csv_auto(\n",
"'data/dof_parking_violation_codes.csv',\n",
"normalize_names=True\n",
")\n",
"'''\n",
"\n",
"sql_query_import_2 ='''\n",
"CREATE OR REPLACE TABLE parking_violations_2023 AS\n",
"SELECT *\n",
"FROM read_csv_auto(\n",
"'data/parking_violations_issued_fiscal_year_2023_sample.csv',\n",
"normalize_names=True\n",
")\n",
"'''\n",
"with duckdb.connect('data/prod_nyc_parking_violations.db') as con:\n",
" con.sql(sql_query_import_1)\n",
" con.sql(sql_query_import_2)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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" vertical-align: top;\n",
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" .dataframe thead th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>registration_state</th>\n",
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" </thead>\n",
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" <td>NB</td>\n",
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" <td>PE</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>61</th>\n",
" <td>SK</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>62 rows × 2 columns</p>\n",
"</div>"
],
"text/plain": [
" registration_state ticket_count\n",
"0 NJ 9258\n",
"1 PA 3514\n",
"2 FL 2414\n",
"3 CT 1787\n",
"4 GA 840\n",
".. ... ...\n",
"57 AB 1\n",
"58 BC 1\n",
"59 NB 1\n",
"60 PE 1\n",
"61 SK 1\n",
"\n",
"[62 rows x 2 columns]"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sql_query = '''\n",
"SELECT * FROM gold_vehicles_metrics\n",
"'''\n",
"\n",
"with duckdb.connect('data/prod_nyc_parking_violations.db') as con:\n",
" display(con.sql(sql_query).df())"
]
}
],
"metadata": {
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