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{
"cells": [
{
"cell_type": "code",
"execution_count": 345,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x1fe89ae7d68>"
]
},
"execution_count": 345,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Use the 'hue' argument to provide a factor variable\n",
"sns.lmplot( x=\"Likes\", y=\"RTs\", data=data, fit_reg=False, hue='sentiment', legend=False)\n",
" \n",
"# Move the legend to an empty part of the plot\n",
"plt.legend(loc='lower right')"
]
}
],
"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": "3.7.0"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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