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"# Introduction to Spark Visualization\n",
"\n",
"## Feng Li\n",
"\n",
"### Central University of Finance and Economics\n",
"\n",
"### [feng.li@cufe.edu.cn](feng.li@cufe.edu.cn)\n",
"### Course home page: [https://feng.li/distcomp](https://feng.li/distcomp)"
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"/home/fli/.APP/spark/python/pyspark/pandas/__init__.py:50: UserWarning: 'PYARROW_IGNORE_TIMEZONE' environment variable was not set. It is required to set this environment variable to '1' in both driver and executor sides if you use pyarrow>=2.0.0. pandas-on-Spark will set it for you but it does not work if there is a Spark context already launched.\n",
" warnings.warn(\n",
"Setting default log level to \"WARN\".\n",
"To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).\n",
"23/06/08 17:14:14 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable\n"
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"title": {
"text": "length"
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"title": {
"text": "width"
}
}
}
},
"text/html": [
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},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df = ps.DataFrame([[5.1, 3.5, 0], [4.9, 3.0, 0], [7.0, 3.2, 1],\n",
" [6.4, 3.2, 1], [5.9, 3.0, 2]],\n",
" columns=['length', 'width', 'species'])\n",
"fig = df.plot.scatter(x='length', y='width')\n",
"fig.update_layout(template=\"plotly_dark\") "
]
},
{
"cell_type": "markdown",
"id": "5ca9c39c",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## What else can we do?"
]
},
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"cell_type": "code",
"execution_count": 11,
"id": "afa73109",
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"source": [
"## Lab\n",
"\n",
"- Use the `airdelay_small.csv` data to visualize the delay trend."
]
}
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