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Refactor webscraping-and-apis notebook:
- Import `lets_plot` at the beginning for clarity. - Adjust DataFrame column operations for better readability. - Simplify plot creation by using parentheses for chaining. - Remove unnecessary imports and whitespace for cleaner code.
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data/bake_sale.xlsx

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databases.ipynb

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"outputs": [],
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"source": [
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"df = pl.read_database(\n",
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" query=sql_join, # your SQL query (string)\n",
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" connection=con # your connection object (SQLAlchemy, psycopg2 cursor, etc.)\n",
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" query=sql_join, # your SQL query (string)\n",
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" connection=con, # your connection object (SQLAlchemy, psycopg2 cursor, etc.)\n",
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")"
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]
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},

rectangling.ipynb

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" {\"name\": {\"given\": \"Mark\", \"family\": \"Regner\"}},\n",
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" {\"id\": 2, \"name\": \"Faye Raker\"},\n",
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"]\n",
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"pl.json_normalize(data)\n",
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"\n"
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"pl.json_normalize(data)"
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]
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},
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{

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