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Copy file name to clipboardExpand all lines: src/notebooks/web-lollipop-plot-with-python-mario-kart-64-world-records.ipynb
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"As always, several libraries are needed in order to build the chart. `numpy`, `pandas` and `matplotlib` are pretty usual, but we also need some lesser known libraries like `palettable` to get some nice colors."
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"cell_type": "code",
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"metadata": {},
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"outputs": [
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"output_type": "execute_result",
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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"\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>track</th>\n",
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" <th>type</th>\n",
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" <th>shortcut</th>\n",
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" <th>player</th>\n",
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" <th>system_played</th>\n",
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" <th>date</th>\n",
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" <th>time_period</th>\n",
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" <th>time</th>\n",
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" <th>record_duration</th>\n",
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" <tbody>\n",
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" <th>0</th>\n",
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" <td>Luigi Raceway</td>\n",
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" <td>Three Lap</td>\n",
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" <td>No</td>\n",
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" <td>Salam</td>\n",
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" <td>NTSC</td>\n",
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" <td>1997-02-15</td>\n",
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" <td>2M 12.99S</td>\n",
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" <td>132.99</td>\n",
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" <td>1</td>\n",
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" <th>1</th>\n",
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" <td>Luigi Raceway</td>\n",
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" <td>No</td>\n",
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" <td>Booth</td>\n",
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" <td>1997-02-16</td>\n",
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"</div>"
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" track type shortcut player system_played date \\\n",
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"0 Luigi Raceway Three Lap No Salam NTSC 1997-02-15 \n",
"That was a lot of work! And many more lines of code than using R. But here we are, a pretty good looking lollipop chart showcasing the possibilities offered by Matplotlib, which are basically infinite!"
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"cell_type": "markdown",
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"metadata": {}
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"metadata": {
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"chartType": "lollipop",
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"description": "A highly customized lollipop chart showing world records for the Mario Kart 64 racing game on the Nintendo 64. Built with Python and Matplotlib. This blogpost will guide you through a very custom plot with Matplotlib, including custm fonts, custom scales, custom legends, and more!",
"seoDescription": "This post explains how to build a highly customized lollipop plot with Matplotlib. Step by step code snippets with explanations are provided.",
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