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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"df = pd.DataFrame(\n",
" np.matrix(\n",
" \"0 0 1 1 2 2 2 4; 1 1 2 1 2 3 4 4; 1 2 2 2 3 4 4 6; \"\n",
" \"2 3 3 4 4 4 5 6; 2 4 4 4 5 5 6 7; 3 4 5 6 7 7 8 8; \"\n",
" \"4 5 7 5 4 5 9 9; 6 6 7 4 3 6 9 10\"\n",
" )\n",
")\n",
"\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.imshow(df.values, cmap=\"gray\")\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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": "3.8.12"
"nbformat_minor": 4