"
],
"text/plain": [
" Unnamed: 0 regiao estado municipio coduf codmun codRegiaoSaude \\\n",
"0 0 Brasil NaN NaN 76 NaN NaN \n",
"1 1 Brasil NaN NaN 76 NaN NaN \n",
"2 2 Brasil NaN NaN 76 NaN NaN \n",
"3 3 Brasil NaN NaN 76 NaN NaN \n",
"4 4 Brasil NaN NaN 76 NaN NaN \n",
"\n",
" nomeRegiaoSaude data semanaEpi populacaoTCU2019 casosAcumulado \\\n",
"0 NaN 2020-02-25 9 210147125 0 \n",
"1 NaN 2020-02-26 9 210147125 1 \n",
"2 NaN 2020-02-27 9 210147125 1 \n",
"3 NaN 2020-02-28 9 210147125 1 \n",
"4 NaN 2020-02-29 9 210147125 2 \n",
"\n",
" casosNovos obitosAcumulado obitosNovos Recuperadosnovos \\\n",
"0 0 0 0 NaN \n",
"1 1 0 0 NaN \n",
"2 0 0 0 NaN \n",
"3 0 0 0 NaN \n",
"4 1 0 0 NaN \n",
"\n",
" emAcompanhamentoNovos interior/metropolitana \n",
"0 NaN NaN \n",
"1 NaN NaN \n",
"2 NaN NaN \n",
"3 NaN NaN \n",
"4 NaN NaN "
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"covid_BR.head()"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### Gráfico de Linhas\n",
"\n",
" O gráfico de linhas é formado por pontos no plano a partir de duas variáveis e, em seguida, estes pontos são ligados por segmentos de retas. Este é o gráfico padrão construído pelo método `plot`. Para construí-lo basta \"chamar\" o método `plot` sem argumentos adicionais."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"data": {
"image/png": 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gc5clhMlIkAubVVhSyMqjK/n80OdomsbLXV9mdOvRODtKN4qwLRLkwibtTtzN9LDpxF2K47bGt/Gvbv+ifrX65i5LiEohQS5sSnJOMrPCZ/FL3C8EVA9g8ZDF9PLtZe6yhKhUEuTCJhSVFLH62GoWH1qMUooXOr/A2LZjcXF0MXdpQlQ6CXJh9UKTQgkJDSEmM4ZBfoN4vfvrNPRsaO6yhKgyEuTCaqXkpDAnYg4/xf6En5cfCwcvpF+jfuYuS4gqJ0EurE6RoYivjn/FogOLKFElTOo0ifHtxuPq6Gru0oQwCwlyYVXCk8OZHjqd0xdP069RP97o/gZ+Xn7mLksIs5IgF1YhLS+N2RGz2RK9BV9PXz4Z9AkD/AaYuywhLIIEubBoxYZi1p5Yy8IDCykoKeDpDk8zof0E3J3czV2aEBZDglxYrMjzkUzbO41TF07Ru2Fv3gx+k8bVG5u7LCEsjgS5sDjpeel8tO8jNp3ZRP1q9Zk7YC6D/QejaZq5SxPCIkmQC4tRYihh3al1fBL5CXnFeTzZ/kkmtp+Ih7OHuUsTwqJJkAuLcDD1ICF7QziecZzgBsFMDZ5KYI1Ac5clhFWQIBdmdSH/AvP3z+f7qO+p616XD/t/yNDGQ6UbRYgykCAXZlFiKOH7qO+Zv38+uUW5jGs7jmc6PkM152rmLk0IqyNBLqrckbQjhOwN4Uj6EYLqBfFW8Fs0q9XM3GUJYbUkyEWVySzIZP7++Xx36jt83H34oO8HDGsyTLpRhKggCXJR6QzKwMbTG5m7by5ZhVk81voxJnWahJeLl7lLE8ImSJCLSnU8/TjTQqdxKPUQXep2YWrwVFp6tzR3WULYFAlyUSkuFV5iQeQCvjn5DTVdazKt9zSGNx0u3ShCVAIJcmFSSik2ndnER/s+4mLBRR5q+RDPd36e6i7VzV2aEDbLZEGuaZojEAEkKqXuNlW7wnqczDjJ9NDp7D+/nw51OvDpkE9p49PG3GUJYfNMeUb+InAckFMvO5NVmMWiA4v4+sTXeLl48V6v9xjRbAQOmoO5SxPCLpgkyDVNawTcBYQAr5iiTWH5lFJsjdnK7IjZpOel82CLB3mhywvUcK1h7tKEsCumOiOfB/wLuOF4Mk3TngKeAvD39zfRboW5nL5wmpDQECJSImjr05ZPBn1Cu9rtzF2WEHapwkGuadrdwHml1D5N0wbcaDul1BJgCUBQUJCq6H6FeeQU5fDZwc/48tiXeDh78O8e/+b+5vfj6OBo7tKEsFumOCPvDQzXNG0Y4AZU1zTtS6XU4yZoW1gIpRTbYrfxYfiHnM87z8jmI3mpy0vUcqtl7tKEsHsVDnKl1JvAmwDGM/IpEuK2JTozmhmhM9ibtJfW3q35aOBHdKzT0dxlCSGMZBy5uKHcolyWHFrCqmOrcHd0Z2rwVEa1GCXdKEJYGJMGuVJqF7DLlG2KqqeUYsfZHcwMn0lyTjLDmw7n5a4vU9u9trlLE0Jch5yRi6vEXYpjRugM/jz3Jy1qtWBm35l0qdfF3GUJIW5CglwAkFecx9LDS1lxZAUuji683u11Hm71ME4O8i0ihKWTn1LBr2d/ZWb4TBKzE7kr8C5e7foqdTzqmLssIUQpSZDbsfiseGaGzeS3hN9oWqMpy4cup1v9buYuSwhRRhLkdqigpIDlR5az7PAyHDVHpgRN4dHWj+Ls4Gzu0oQQ5SBBbmd+T/idGWEziM+K546AO5gSNIV61eqZuywhRAVIkNuJc9nnmBk2k53xOwmoHsCS25bQs2FPc5clhDABCXIbV1hSyKqjq1hyaAmapvFSl5cY02YMzo7SjSKErZAgt2G7E3czI2wGsZdiua3xbbwW9BoNPBuYuywhhIlJkNug5JxkZoXP4pe4X/D38ufTIZ/Sx7ePucsSQlQSCXIbUlRSxBfHv+Czg59hUAae7/Q849qNw9XR1dylCSEqkQS5jQhNCmV66HSiM6MZ4DeAN7q/ga+nr7nLEkJUAQlyK3c+9zyzw2fzU+xP+Hr6smDQAvr79Td3WUKIKiRBbqWKDEV8dfwrFh1YRLGhmGc7Psv4duNxc3Izd2lCiComQW6FIpIjCAkN4fTF0/T17cub3d/Er7qfucsSQpiJBLkVSctLY07EHH6M/pGG1Royf+B8BvoNRNM0c5cmhDAjCXIrUGwo5puT37AgcgEFJQVMbD+RiR0m4u7kbu7ShBAWQILcwh04f4Bpe6dx8sJJejboydTgqQTUCDB3WUIICyJBbqHS89KZt38eG09vpJ5HPT4a8BFD/IdIN4oQ4h8kyC1MiaGE7059x/zI+eQV5TG+3Xie7vA0Hs4e5i5NCGGhJMgtyOHUw0wLncax9GN0r9+dt4LfIrBmoLnLEkJYOAlyC3Ax/yLz9s9jfdR6arvXZla/WdwRcId0owghSkWCvCyUgqhfYO9CqN0Chn1YoeYMysD6qPXM2z+P7MJsRrcZzbMdn8XTxdNEBQsh7IEEeWmUFMGR7+HP+XD+GLh4QvQuaNIfWt9driaPph8lZG8Ih9MO07VeV94KfovmtZqbtm4hhF2QIL+ZgmyI/AL2LITMeKjTGkZ8Bm3uhWW3w5ZXoHEv8PAudZOZBZl8EvkJ606uw9vNm+l9pnN34N3SjSKEKDcJ8uvJSYPQxRC2BPIvgn8vuGsONL8d/grcEQvh80GwbSrc99ktmzQoAz+c/oG5++aSWZjJo60fZVKnSVR3qV7Jb0YIYeskyK+UEQN7FkDkl1BcAK3ugt4vgl/3f27boCP0eRn+9yG0HQktbr9hsycyThCyN4QDqQfoVKcTb/d4m5beLSvxjQgh7IkEOUDSQfhjHhzbCJojdHwYer0AdVrc/HX9XoPjP8LmF+G5veBW46qnswqzWBC5gLUn11LTtSbv936f4U2H46A5VOKbEULYG/sNcqX0C5Z/zofoX8HFC3o+Dz0mQfVSrmvp5Ar3LoRlQ+Dnf8Pwj41NK36M/pE5EXPIyM9gVMtRTO48mRquNW7RoBBClJ39BXlJMRzfpAd40gHwrAdD3oWg8f84oy6VRl31XwC7P4a293HK25eQvSHsP7+f9rXbs3DIQtr6tDX1uxBCiL/ZT5AX5cGBNbD7E7gQCz7N4J6P9W4UpwquaTlwKtknt/DpLy+wxsMRTxdP3un5DiObj5RuFCFEpatwkGua5gesBuoDBmCJUmp+Rds1mdwMCF8GoZ9Bbhr4BsHt06DlMHBwrHDzSil+iv+V2bU9SCu4yP2uDXjx3q+p6VbTBMULIcStmeKMvBh4VSm1X9M0L2Cfpmm/KKWOmaDt8stM0Md/71sFRTn60MHeL+njvk00ZvvMxTNMD51OWHIYbXzaML9aO9rv/xqCj0BAH5PsQwghbqXCQa6USgKSjJ9naZp2HPAFzBPkKcf0/urD3+oXNNs/oA8hrGe6furcolw+O/QZXxz9Andnd94OfpsHWjyAY3E+xOyBH56HZ3eDi8xYKISofCbtI9c0LQDoDISast1bUgrO7tGHEEZtA2cP6DYRek6Cmv4m3I3il7hfmBU+i5TcFO5rdh8vdX0JbzfjnZ0u1WD4Alh1N+ycBndMN9m+hRDiRkwW5JqmeQLfAy8ppS5d5/mngKcA/P1NFK4GA5zcCn/Og4Rw8PCBgW9BtyfLdNt8acRkxjAjdAZ7kvbQslZLZvefTae6nf65YZO+EDQB9i6CtiOufzOREEKYkKaUqngjmuYM/AhsU0p9dKvtg4KCVERERPl3WFwAh76BPz+G9Cio2Rh6TYZOj5m8OyO3KJelh5ey4ugK3BzdeL7z8zzU8iGcHG7yO7AgCxb1BGd3ePp3cHYzaU1CCPukado+pVTQtY+bYtSKBiwDjpcmxCskPxMiVsDeTyE7Gep3gPuXQZsR4GjakZRKKXbG72Rm2EyScpK4J/AeXgl6hdrutW/9YlcvuGc+fDkSfvtAH6cuhBCVxBTp1xsYDRzWNO2A8bGpSqmtJmj7altf08/EAwfAfZ9C4ECTjUC5UvyleKaHTeePxD9oVrMZK4auIKj+P34J3lyzwdD5cf2vhtbDwbeLyesUQggwUddKWZW7ayX1lD6UsGFn0xcF5Bfns+zIMpYfXo6TgxPPdXqOR1o/grODc/kazLsIi3qAey146jdwcjFtwUIIu1JpXStV6laTWFXAb/G/MSNsBonZidzZ5E6mBE2hrkfdijXqXhPungdfPwS/z4aBU01TrBBCXMG6grwSJGQlMDNsJrsSdhFYI5Blty+jewMTjjRpeQd0eAh+nwOt74H67U3XthBCYMdBXlBSwIojK1h6eCkOmgMvd32Z0a1H4+xYzm6Um7njAzjzK2ycBBN3QmXsQwhht+xyRqc/Ev9g5A8jWXhgIf0b9WfTiE2Mbze+ckIc9DHtd82B5EP6rItCCGFCdnVGnpSdxKzwWWw/u52A6gEsHrKYXr69qmbnbYZD2/vgt5n6ykN1W1fNfoUQNs8ugryopIhVx1ax5NASlFK80PkFxrYdi4tjFY8iufNDiPkf/PAcTPjFJLMvCiGEzXet7Dm3h5GbRjJ//3x6NezFDyN+YGKHiVUf4gCedeDOWZC4T5+ZUZjM+ax8Fv92hsSLeeYuRYgqZ7Nn5Mk5ycyOmM222G34efmxaPAi+jbqa+6yoN39cGQ9/Bqiz4leu5m5K7J6x5MuMWFlOOcy85n980lGBfnx3MBmNKzpbu7ShKgSNndGXmQoYsWRFQzfOJxd8bt4rtNzbLh3g2WEOOh3ot79kb4q0Q/P6RN/WbOkg7DmQX1UjhnsPJHCA5/upkQpVozrxqggP9ZFxDPgw138e+MRkjLlDF3YPuu6s/MWwpPDCdkbwpnMM/Rv1J/Xu7+On5efyfdjEge+go3Pwh0zoccz5q6m7JSCiGXw36lQUgBObvCocfqEKtm9YvmfsYRsOUabhtVZOqYb9Wvok5MlXMhl4a9n+DYiHgdN45Hufkwa2Ix61WXyMmHdbnRnp00EeWpuKrMjZrM1Ziu+nr680f0NBvgNMFn7lUIp/Uw27k99EQrvJuauqPTyM2HTC3BsIzQbAkOnw7fjICMGHvtWn8q3EhWVGHh301HWhJ7ljrb1+eihjni4/LOXMD4jl4W/nua7fQk4OGg82t2fSQOaUlcCXVgpmwzyYkMxX5/4moUHFlJYUsj4duOZ0H4C7k5W0jeamajPxdKgI4zZBA5W0NN1LhK+fQIunoXB/4ZeL+p1Z6fqC2pcPAuPfQcBvStl95l5RTz/1X5+j0rjmf5N+dfQljg43HzitPiMXBbsPM13+xNwctB4NNifZwc0pa6XBLqwLjYX5PtT9jMtdBpRF6Lo7dubqd2n4l/ddKsBVZl9K2Hzi3D3XAgab+5qbkwpCPscfn4LqtWBB5aDf4+rt8k+Dyvv0n9BjV7/z+crKC49h/ErwzmbkUvIfe0ZFVS2brOz6bl8sjOK9ZGJODloPN6jMc/0b0odL1eT1ilEZbGZIE/LS2PuvrlsOrOJ+tXq80a3NxjkPwitEqazrRJKwep7IXE/TNoDNS2wTz/vImyaDMc3QfOhcN9nN16BKStZD/OsZBi9wWQrJIXFZPD0FxEo4LPHu9Ij0KfcbcWm5fDJztNsiEzAxcmB0T0a83T/ptT2lEAXls0mgnx91Hpmh88mrySPcW3HMbH9RDycbWCB4wtx+opC/j3g8e8rZY71ckvcp3elXEqEwe9Az+dv3QV06Zwe5jlpMHojNOpaoRK+35fAm+sP06iWO8vGdaNJ7WoVau8vMWk5fLIjio0HEnF1cmRMz8Y81S8QHwl0YaFuFORW0Cl7WVZhFm1rt2X98PW82OVF2whxgFqN4bb34MwOOLDG3NXolNJXYlo2FAwl8MRP0PuF0vXjV28IY3/Uz9q/uE//a6McDAbF7G0nefXbgwQF1GLDpN4mC3GAJrWr8dFDnfjllf4MbVuPz3+Pps/MX5nx03EycgpNth8hKptVnZEblAENzXq7UW7GYNAvFiYfgedCoXoD89WSdwF+eB5O/Agt7oQRi8q3mPXFeFg5TB/lMmYTNLzOYtU3KqGwhFe/PcDWw8k83M2P90e0w9mxcs87Tp/P5pOdUWw6eA53Z0fG9grgqb6B1KomC1S5/34AAByPSURBVIIIy2ATXSs2L/0MfNpbH4v9yNfm6WJJ2KcPJcw6B7f9B3pMqlgdF+L0bpbCbBi7uVTzsZ+/lM/E1REcSsxk6p2tebJvkyr95X36fBbzd5zmx0Pn8HB2ZFzvACb2DaSmhwS6MC8JcmuxZyFsmwojl0KHB6tuv0rp+97+Dng1hAdXQKMyrlN6IxkxsPJuKMqFcT9CvbY33PTYuUs8uSqci3lFzH+4M7e1qWeaGsrhVEoW83dEsfVwEtVcnHiidwBP9gmkhofMJy/MQ4LcWhhKYPkdkB4Fz4WBZwWXmyuN3Ax9uoCTW6HV3XDvAn2dUVNKP6OHeUmhHubXmcZ3+7EUXlgbSXU3Z5aNC6JtwxqmraGcTiZnMX/HKbYeTsbL1Ykn+jRhQp8m1HCXQBdVS4LcmqSegs/66MvEjVpdufuKD4PvxuvDBW+fBsFPV16XTvoZWDEMVAmM2wJ1WgL67fbL/oghZOtx2vvW4PMxQRZ5O/3xpEvM3x7Ff48m4+XmxPjeTRgvgS5KKSu/iIjYC3QNqEV1t/J9z0iQW5vfP4Id78GDq6DtCNO3bzDAngX6Pqr76l0pvhUbJlgqaVF6mGsajNtCUa2m/N8PR/k67Cx3tqvPR6M64e5i2fO0Hz2Xycc7oth2NIXqbk5M6BPIE30Cyv3DKWxTZl4R4TEZhMakszc6g6PnMjEoWDK6K7e3rV+uNiXIrU1JMSwdDJkJehdLtfLfAPMPuRmw4RmI2qYvCD18AbjXNF37t3L+BKy6GwMOTPGcwfo4N54b2JRXb7v17faW5EhiJvN3RPHLsRRquDvzZJ8mjOsdgJcEul26kFNIWGwGodEZ7I1O53jyJZQCF0cHOvnXpEcTb3oE+tDZv1a5T1YkyK1RylFY3F8/I79/6d8Px2fksmp3LOsi4qnj5cqITr6M6OyLn3cpxtWfDYXvnoCcVLg9BLpPNMvomMST+6i2dgT5BiciB6/hzn5VtOReJTiSmMm87afYfvw8Ndydmdi3CeN6N8HT1Wan+xdAenYBYTEZhMbowX0iOQsAVycHuvjXIjhQD+5OfjVxczbNX5kS5NZq10zYNR318FfscQpmxe5Yth9PwUHTGNq2HmnZhYTFZAAQ1LgW93b25e72Df459tlggN3zYcf7UNNf70pp2NkMbwhCo9N5+st9NFdxfOUSgrNrNXhiC9QKMEs9pnIo4SLztkex88R5ano4M7FvIGN7BUig24jUrAJCY9IJjda7S06lZAPg7uxI18a1CG7iTY+mPnRoVANXp+sEd9Ih2LcCBr4F1WqXqwYJciuVl5dH/qJ+GLLTGJj3AU7VvHm0uz+P9fCnQQ19lseEC7n8cOAcGyMTiTqfjbOjRv8WdRnRuSFDWtfDrfCC3pVy+hdoMwKGfwxu5hkR8m1EPFM3HMbP24PlY7sRUHQGVg8HFy99NEutxmapy5QOxl9k3vZT/HoylVoezkzsF8iYnhLo1iblUj57o9MJjckgNDqdM6k5AFRzcaRrgLce3IE+tPetgYvTDW5WK8qHoxv0ufsTwvV5+0d9AS1uL1dNEuRWJuFCLl/sjWNtWDyN8k+xyfXfnG00nAZjl9/wzzSlFMeSLrExMpFNB8+RcqmAfq5RfOy8gOqGTLhjBg7dJpilK8VgUHz480k+3XWG3s18WPRo18vjsc8d0MPcraY+msUSJw4rhwPGQN9lDPSn+jVlTM/GVJNAt0jnLuZdccadQUyaHtxerk4EBdQiONCHHoE+tGtYHadb3WWcfgYilutTbuRdAJ9mEDQBOj1SoaG9EuRWQClFWEwGK/6M5edjyQDc0a4+43o1oVv0QrTfZ8Nj30PzIbdsq6SkhITNITQ6MI8EVYdJhS+Q5tWS4R0bMqKzL20aVK+yuyXzCkt4+ZsD/PdoMo909+c/97b95+32ifth9QjwqAXjtkIN3yqprSpEnr3A/B1R7DqZinc1F57qF8joHhLo5pZwIZe90frZdmhMBmczcgGo7uZE9ybeBDfxITjQmzYNShHcoA9QOPVf/ez7zE7QHKH13XqAN+lnkhMoCXILll9UwqYD51ixO5bjSZeo6eHMw938Gd2zMb5/LSBcXACL+0FBFkzaC27Vb9xgdipseEr/Zmp3P/l3zGF7dB4bI8+x6+R5ig2KFvU8ubeTL/d2akijWpU3+VjKpXyeXBXBkXOZvDWsNRP63OR2+4QIfZKtarX1MDfnfDOVYP/ZC8zfHsVvp/RAf7pfIKN7Nr7u6kbCtJRSxGfksTcmXe8uic4g8aK+nmtND2e6B3gTHOhDcBNvWjeojmNZRk9dSoL9q2H/Kn2WUK+G0HUcdBlj8u9hCXILlJSZx5d74/gq9CwXcotoWc+LJ3oHcG8n3+sPT0qIgGW3QZexcM+86zca+wd8N0H/c+7Omfo31BXBeSGnkC2Hk9gYmUhE3AUAugd4M6KzL3e1b2DS28+PJGby5KoILuUX8fHDnRlSmtvt48P0MPeqr3ezeJVvvK0l2xenn6H/71QqPtVceLp/II/3kECvLAfiL/LKugNEG/u4vau5ENxE7+MODvShZT2vsg97VQpifoPwZXBii36TW9NB+tl3izvAsXK+lhLkFkIpxb64C6zYHct/jySjlGJI63qM6x1Az0CfW3d3/Pw27P5En00wsP/lxw0l+k1Eu6aDdyA8uPKWE1TFZ+Tyw4FENkQmciY1BxdHBwa0rMN9nX0Z2KpuhYZM/XIshRe+jqSWhzNLx3ajTcOb/AVxrbg98OX9evfKuC1VM02BGeyLy2De9ih+j0qjtqcLT/dryuM9Glv8DVHWQinF6j1xTNtyjLpebjzTP5DgQB+a1/Usf7di3gV94fSI5ZB+Gty9ofNj0PUJ8Glq2jdwHRLkZlZQXMKPB5NYuTuWw4mZVHdz4uHu/ozu0bh047//UpSnz5BoKNYXbXb11JdYWz8RondB+1Fw90fg6lXqJpVSHEm8xMYD+kXS1KwCvNycGNauASM6+xLcxLvUZyxKKT7/PZoZP52gg/F2+3Itdhz7J6x5QB8qOfZH8KxT9jasRERsBvN3XA70Z/o35bFgCfSKyC4o5vXvD7HlUBKDW9VlzqiO5Z+9Uin9Gk7EMjjyPRTnQ6Pu0G2CPgrMueqmk6jUINc07Q5gPuAILFVKfXCz7e0pyFMu5bNmbxxfhZ0lLbuQZnU9GdcrgJFdfMv/p3TcHlhxJ3R/Sr+Y8v2T+pzfwz6EzqMrdFGluMTAnuh0NkQmsu1IMjmFJTSo4cbwTg25r7Mvrerf+My6sNjA//1whLXh8QxrX585D1bwdvuY32HNg/pfGGM3m/buVgsUHpvB/O1R/HFaAr0iTiRfYtKX+4lNz2HK0JY8069p+e4YLsyBw9/pAZ50EJyrQYdReoCXYjrmylBpQa5pmiNwCrgNSADCgUeUUsdu9Bp7CPLIsxdYuTuWLYeSKFGKQS3r8kTvJvRuVoruk9L46XUI/Qw0B31o04Mrbzo9bHnkFZbwy/EUNkYm8r9TqRQbFK3qezGisy/DOzak4V8XYoGLuYU8++V+9kSnM3lQM14e0sI0t9tH74KvHgKf5jB2U/kWuLAyYTEZzN9xij9Pp1Pb05VnjH3opro70JZ9ty+BtzcexsvNmU8e6Vy+tV1TT+p93wfXQkEm1G2jL4ze4aGbDzKoApUZ5D2Bd5VSQ43/fxNAKTXjRq+x1SAvLDbw05Eklv8Zy8H4i3i5OvFgkB9jejYmwIRLlOk7y4FVw6FOK/2ipqunadu/Rnp2AVsOJ7EhMpHIsxfRNAhu4s19nX1p06AGL66NJOFCHh/c356RXRqZduend8DXj+izJY7dZPopdi1UaHQ683dEsftMOnW8XI1n6P4S6NeRX1TCOz8c5ZuIeHoEevPxI52p61WGLo/iQn1FrIjlEPs7OLpAm3v1i5f+PSxmHd3KDPIHgDuUUk8a/z8aCFZKPX/Ndk8BTwH4+/t3jYuLq9B+LUlqVgFfhZ7ly9A4UrMKCKxdjXG9AxjZpZFN3s0Xl57Dxshz/HAgkWjjTRO1PJxZMiaIbgGVdMYctR3WPqKfHY35oWon+TKzvdHpzN8exZ5oPdCf7d+UR60h0A0lsOsDSDsJ1erqF62r1TH+W1e/7lGtLrhUbPhrbFoOz67Zz/GkSzw3sCkvD2lRunHfoC9HuG+lPnww57x+TSZoPHR63CKvy1RmkD8IDL0myLsrpSbf6DW2ckZ+OCGTFbtj+PFgEoUlBga0rMO4XgH0a17HqmbxKy+lFIcSMtkTnc6wdg3w96nkxbBPbYO1j0GDDjB6g9mmGTCXPWfSmbf9FKExGdT1cuXZAU15pLuFBrqhRF/39eBX+jWOvAv6x/W4eBoDvt7lcL9R6F/zl+d/jyTx2reHcHDQmPtQRwa1KsUQV4NBX+g8fJk+A6hS0GKofvbdbDA4WODxNJKuFRO4kFPIqZQsTqZk8cOBc+yLu0A1F0ce6NqIsb0CCKxTud0bAjixFdaN1if8eny92fsszWHPmXTmbj9FWEwG9arrZ+gPW1KgXxniA6bCgNf1x4sL9Vk3c87rN63lnNdHXOWkGv81Pp6dAnkZ12/b2QM862KoVodT2e7sS3PGsXo9hnZvT626vlf/EnD1urpLJCcNIr+AiBVwMU7fpssY/V6Lmv6VflhMoTKD3An9YudgIBH9YuejSqmjN3qNpQf5xdxCTqVkcyoli6iULE6lZBN1Ppu07IK/t2ns48HYngE8ENRIFhSoasc36wtE+wbB49+VaailrVBKsSc6nXm/RBEWqwf6pAHNeKibn3kD3VACmybrc4xcGeJlVVKkB+91Qj/vQhKnoqNxzU/DzyULj+JMNK6TY07uV5/Jx+3Wlxps3Ae6jYdW94CTdS2oXdnDD4cB89CHHy5XSoXcbHtLCfLMvKK/g/pUShZR5/XPU7MuB3Y1F0ea1fOiRV1PWtTzonk9/d8GNdyqdGV3cY2jG/Ul6vyC9TB3MfHFZCuhlPr7DD089gL1q7sxaWBTRgWZIdCvCvE3YcAbJt/F/06l8tI3BygoKuGD+ztwT8eG+hwnuem3PsP366H3f9dtZfK6qopd3xB0Kb+IqJTsK86usziVkkXKpcuB7e7sSPN6njSv60WLepdD27emuwS2pTryvT6GvnFveHRdhS+aWTOlFLvPpDP3l1NExOmB/nT/QB4M8quaC+4GgzHEv6yUEC8xKD7eEcXHO6NoUdeLRY93oakddmXaRZBnFxQTlZJFlPEM+9R5PbyTMvP/3sbN2YFmdT1pUdeL5vUuh7ZvTXe7uEBpcw59q08QFtAXHv0GnN1v/RobppTiz9P6RdGIuAt4ujrxQNdGjOnZuPKu4VwZ4v3fgIFvmrT59OwCXlx7gD9OpzGyiy8hI9rb7U1SNhXkOQXFnD7/V3fIX33Z2X/PZgb6ckvNjN0hf/3bop4nfrU8JLBtzcG1+sIZgf3h/mXlXn3F1kSevcCq3bFsOZxEUYmifwt9VFX/FiYcVVXJIR4Rm8HzX0WSkVvIf4a35aFufnb9F7JNBPmiXaf5KvQsCRcuB7aLkwNN63he7g4xhraft0fZpqIU1i1yjR4oLtWg76sQ/EyVzoFhyc5n5fNV6FnWhJ4lNauAAB8PxpjiQn0lhrhSimV/xPDBTyfwreXOwke70M7XvoabXo9NBPmXe+MIjcmgRV3Pv7tF/L09Sj/4X9i21JPwy//pk/vX8Ich70C7+y3mrjxz++vO41W7Y9l/9iIeLo7c36URY3s1plndMo78MRhg82SI/BL6vw4Dp5qszsy8Iv713UG2HU1haNt6fPhgRxkZZmQTQS5EqUTvgm1vQ8phfYji0OngH2zuqizKoYSLrNwd+/fNbH2b12ZszwAGtqp7679krw3xAW+a7Jfl0XOZTFqzn8QLebxxZ6ubL0RihyTIhX0xlMDBr2HH+5CdrM+bMeQ98G5i7sosSlp2AWvDzvLl3rMkX8rH39uDMT0b82CQHzXcr3MWbDDA5hf0G2v6/Us/EzdB0CqlWBsezzubjuLt4cKCRzsTVFnTPVgxCXJhnwpz9IU4/pyvz+He/SnoN8VuJt4qraISA9uOJrNqdyzhsRdwd3bkvi6+jOsVQIt6xm6XSgrx3MJi3t54hPX7E+nbvDbzHuqEj6drhdu1RRLkwr5dSoJfp+kXRd1r6hfnuk0AR+l7vdaRxExW74ll44FzFBYb6NXUh7E9/bntzAwcIldDv9dg4FsmCfEzqdk8++U+os5n8+Lg5kwe1FwGKdyEBLkQAEmH9OXyYn4D76Zw23+g1V1yQfQ6MnIKWRt+ljW7Y3g+dyGPOP3KvsZP0nTUdGpWq/gZ8+aD53jj+0O4Ojsy76FO9GthebMNWhoJciH+ohRE/Qw//1ufYrVxHxg6TZ+IS1zNYMCw+SUcIlex3vNhXkm7BzdnR0Z08mVsrwBaNyj7pGUFxSVM33KcVXvi6Nq4Fgse7UyDGvZ9I1dpSZALca2SYti/En6dAblp0OFhGPxvqGHihTGslcEAP74E+1dB3ykw6G2OJ2exek8sGyITyS8yENzEm3G9AritTb1SDQNOuJDLc2v2czAhkyf7NOH1O1vhLMOHS02CXIgbyc+EP+bCnkV6F0vP56HPS3Y5q+LfDAbY8rK+6ELfV2HQv6/qfrqYW8g34fGs3hNH4sU8GtZw4/GejXm4mz/e1a4/o+DOEym8/M1BDAbFhw924I52DarozdgOCXIhbuXiWdjxHzj8rT716cCp+mLWjra3ytNN3SLEr1RiUOw4nsKqPbH8eTodFycH7u3YkLG9Av6+E7O4xMBHv5xi0a4ztGlQnUWPdTH90od2QoJciNJK2AfbpkL8Xn1pudvfh2ZDzF1V1TAYYMsrsG8F9HkFBv9fqS8En0rJYtXuWNbvTySvqISgxrV4NNifdRHx7I3O4OFufrw7vK3lLIBhhSTIhSgLpeD4JvjlHbgQA00Hw+3ToF4bc1dWeSoQ4lfKzCvi2wi92+VsRi5uzg6EjGjP/V3l2kNFSZALUR7FBRC+FH6bCQVZelfLwLfAqxRrQ1oTgwG2vqqvIt/nZRj8ToWHZJYYFKEx6fjWdKexj3SlmIIEuRAVkZsBv82C8M/ByU2/GNrjOdtYzKISQlxUjhsFuYz7EaI0PLzhzg/guTAIHAA7p8GCIH0udIPB3NWVn8EAW6foId77JQlxKyVBLkRZ+DSFh9fAuK36au0bnobPB0LsH+aurOyUMob4Mj3Eh7wrIW6lJMiFKI+A3vDkThj5ub7a+8q7YO1jkHba3JWVjlKw5VVjiL8oIW7lJMiFKC8HB+gwCiZH6CM8onfBomDY9AIc3QhZyeau8Pr+EeLvSYhbObnYKYSpZJ+HX6fr86AXGxf8rtkY/IL1hS38ekDd1uBgxnHUf3WnhC+FXi/ok4ZJiFsNGbUiRFUpLoTkQxAfCmf36v9mp+jPuVaHRkF6qPsHg2/XqpsKQELc6kmQC2EuSsGFWIgP0+8WPRsK548BCjQHqNcO/HvoZ+5+wVDTr3Jq2PqaPnyy12S47X0JcSskQS6EJcnPhIRwPdTj9+rTAhTl6M9V970c6v7BUK99xeZ7kRC3GTcKcjubDUgIC+FWQ5+/5a85XEqKIeXIFd0xYXB0vf6cczVo1NUY7j3Ar5v++tJQCn76lx7iPZ+XELdREuRCWAJHJ2jYSf8Iflp/LDPhcqjH74Xf54AyAJp+0dQv+HKXTK2Afwb0XyEetkQP8dunSYjbKOlaEcJaFGRDYoQe7Gf36l0zBZf05zzrgV9340XUHlC/vb4CUthiCXEbIl0rQlg7V099eoDAAfr/DSVw/rjeHfNXl8zxzfpzDs5gKJIQtxMS5EJYKwdHqN9O/+g2QX8sK9kY6qF6d0v3iRLidkCCXAhb4lUf2tyrfwi7IbfoCyGElatQkGua9qGmaSc0TTukadoGTdNqmqowIYQQpVPRM/JfgHZKqQ7AKeDNipckhBCiLCoU5Eqpn5VSxcb/7gVkUT4hhKhipuwjHw/8dKMnNU17StO0CE3TIlJTU024WyGEsG+3HLWiadp2oP51nnpLKfWDcZu3gGJgzY3aUUotAZaAfkNQuaoVQgjxD7cMcqXUkJs9r2naWOBuYLAyx22iQghh5yo0jlzTtDuA14H+Sqlc05QkhBCiLCo014qmaacBVyDd+NBepdQzpXhdKhBXzt3WBtLK+VpbJMfjMjkWV5PjcTVbOB6NlVJ1rn3QLJNmVYSmaRHXmzTGXsnxuEyOxdXkeFzNlo+H3NkphBBWToJcCCGsnDUG+RJzF2Bh5HhcJsfianI8rmazx8Pq+siFEEJczRrPyIUQQlxBglwIIaydUqpCH4Af8CtwHDgKvGh83Bt9dsQo47+1jI/fBuwDDhv/HXRFW12Nj58GPsbY9XOdfV53O6AfsB99uoAHblKzK/CN8fWhQMAVz/0XuAj8aM/HAmhsrOmA8b08Y8/Hw/hcifF4HAA22fPxAAZecSwOAPnACHs8FsbnZgJHjB8PlfV7o6IfFW8AGgBdjJ97oU9n2waYBbxhfPwNYKbx885AQ+Pn7YDEK9oKA3oCGvoEXHfeYJ/X3Q4IADoAq2/xBZkEfGb8/GHgmyueGwzcQ/mC3GaOBeACuBo/9wRi/6rVHo+H8f/Z8rNy+XhcsY03kAF42OOxAO5C/6XjBFQDIoDqFfleKfP3lskbhB/Qf3ueBBpc8UU7eZ1tNfS7Ql2N25y44rlHgMU3+Aa46XbAylt8QbYBPY2fO6Hf7aVd8fwAyhHktngsjI/7AGcpY5Db2vGggkFua8fjim2eAtbY67EAXgPevmK7ZcAoU36v3OrDpH3kmqYFoP/mDAXqKaWSAIz/1r3OS+4HIpVSBYAvkHDFcwnGx65V2u1uxheIN9ZWDGSih5XJ2MKx0DTNT9O0Q8bnZyqlzpWx7b/ZwvEA3IxTMe/VNG1EGdu9io0cj788DHxdxnb/ZgPH4iBwp6ZpHpqm1UbvdvIrY9sVYrLFlzVN8wS+B15SSl3SbrFyt6ZpbdH7lW7/66HrbKau99JSbnfT3ZugjRs3biPHQikVD3TQNK0hsFHTtO+UUillbN9mjgfgr5Q6p2laILBT07TDSqkzZWzflo4HmqY1ANqjn62WmS0cC6XUz5qmdQN2A6nAHvT+9ipjkjNyTdOc0b8Ya5RS640Ppxi/yH99sc9fsX0jYAMw5oofhASuXmGoEXBO0zRHTdMOGD/+c6PtblFfyF9tXLEvP+NzTkAN9D6+CrPFY2E8Ez8K9C3NMbhmfzZzPP76i0QpFQ3sQj+LLBNbOh5Go4ANSqmi0h2Bq/ZlM8dCKRWilOqklLoNPfCjynIsKqyifTPGolcD8655/EOuvmgxy/h5TfQ/Re6/TlvhQA8uX4wYdoN93nQ7bt3X9RxXX7RYd83zAyjfxU6bORbo3+juxs9roV+Mam/Hx6MWly/+1kb/QW1jr8fjiuf3AgPt/GfFEfAxft4BfeSKU1mPSUU+Kt4A9EH/E+UQl4ciDUPvO9ph/IbfAXgbt38byOHqoUt1jc8FGQ/CGWABNx5GdN3tgG7ovzVz0C+GHL3B692Ab9GHEYUBgVc89zv6n0d5xraG2uOxQL/wdMj4w3MIeMqevzeAXuhD1w4a/51gz8fD+FwAkAg42POxMD5+zPixF+hU1uNR0Q+5RV8IIayc3NkphBBWToJcCCGsnAS5EEJYOQlyIYSwchLkQghh5STIhRDCykmQCyGElft/5Rv0hRaIxBUAAAAASUVORK5CYII=\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"covid_regioes.plot(figsize=(12,7));"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### Gráfico de Colunas\n",
"\n",
"O gráfico de colunas é formado por uma coleção de colunas, com bases de mesmo comprimento, e igualmente espaçados. O eixo horizontal do gráfico consiste das diferentes categorias consideradas, e o eixo vertical é proporcional ao valor do dado. Podemos criar gráficos em colunas utilizando o argument `kind` do método `plot`. Assim, para criar um gráfico de colunas, basta utilizar `plot(kind = 'bar')`. Também podemos criar estes gráficos utilizando o método `plot.bar()`. As duas formas são equivalentes."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"covid_Regioes_casos_obitos.transpose().plot.bar(stacked=True);"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### Gráfico de Barras\n",
"\n",
"O gráfico de barras é construído da mesma forma do gráfico em colunas, entretanto, muda-se a orientação. Neste caso, o eixo horizontal do gráfico é proporcional ao valor do dado, e o eixo vertical consiste das diferentes categorias consideradas. Para criar um gráfico de barras, basta utilizar `plot(kind = 'barh')`. Também podemos criar estes gráficos utilizando o método `plot.barh()`. As duas formas são equivalentes."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"data": {
"image/png": 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1Z+27k5lZP6SI/Dms/rERR8WIMgeAmVl3SFodEaVt230rCDOzjHIAmJlllAPAzCyjHABmZhnlADAzy6i8uh108chCKn3VjZlZKjwDMDPLKAeAmVlGOQDMzDLKAWBmllEOADOzjHIAmJlllAPAzCyjHABmZhnlADAzyygHgJlZRjkAzMwyygFgZpZRDgAzs4xyAJiZZZQDwMwsoxwAZmYZ5QAwM8soB4CZWUY5AMzMMsoBYGaWUQ4AM7OMGpDrArqjtqGW4kXFuS7DzKxPVZdV98p2PQMwM8soB4CZWUY5AMzMMsoBYGaWUQ4AM7OMcgCYmWVUjy8DlbQ1Ig7qZP03gTnABuDbEfHc/r7WhB3vU7n+j/v7dMuy8i25rsCs3+n17wFExI3Ajb39OmZm1j2pHAJSsx9IqpFULWl20n6QpJWS1iTtZ7d6zmVJ/5pklmBmZn0orRnAuUAJcCwwDKiQ9DCwCZgREe9IGgY8IeleYDIwH5gKCHhS0kMR8XRK9ZiZ2T6kdRJ4GrAkIpoiYiPwEDCF5jf3ayStBX4HjAT+POm/PCLei4itwH8AJ7W3YUkXSqqUVLlpW6RUrpmZpRUA6qD9fGA48JmIKAE2AoM66b+XiLg1IkojonT4kC4/zczM9iGtAHgYmC2pQNJw4GTgKaAQeDMidko6FRjdqv85koZIOhCYATySUi1mZtYFPToHIGkAsANYDnwWeAYI4B8j4g1Ji4FfSaoEqoBnASJijaSf0RwSAP+3K8f/q2MsRY25v6Co7tqzcl2CmVmP9fQk8ATgpYgI4H8lPy0iYjPNwbCXiLgBuKGHr29mZvtpvw8BSboYWAJ8O71yzMysr+z3DCAibgFuSbEWMzPrQ74XkJlZRjkAzMwyygFgZpZRefVH4YtHFlLpSzDNzFLhGYCZWUY5AMzMMsoBYGaWUQ4AM7OMcgCYmWWUA8DMLKMcAGZmGeUAMDPLKAeAmVlGOQDMzDLKAWBmllEOADOzjHIAmJlllAPAzCyjHABmZhnlADAzyygHgJlZRjkAzMwyygFgZpZRDgAzs4xyAJiZZdSAXBfQHbUNtRQvKs51GWaWYdVl1bkuITWeAZiZZZQDwMwsoxwAZmYZ5QAwM8soB4CZWUY5AMzMMiqvLgOdsON9Ktf/MddlWPmWXFdgZilIdQYgaYakkPTpNLdrZmbpS/sQ0HnAo8CclLdrZmYpSy0AJB0EnAhcQBIAkk6R9KCkZZKelbRYkpJ1V0iqkFQj6dbd7WZm1jfSnAGcA9wfEc8Db0manLRPAr4JHA2MpTkkAP41IqZExERgMDC9vY1KulBSpaTKTdsixXLNzLItzQA4D7grWb4reQzwVETUR8QuoAooStpPlfSkpGrgL4EJ7W00Im6NiNKIKB0+xJMEM7O0pHIVkKShNL+JT5QUQAEQwH3AjlZdm4ABkgYB/waURsQGSeXAoDRqMTOzrklrBjALuCMiRkdEUUQcAawHpnXQf/eb/ebk3MGslOowM7MuSut7AOcB17Zp+yXwdeCltp0j4m1JtwHVQB1Q0ZUXqY6xFDXe2LNKU1R37Vm5LsHMbL8pIn9OrH5sxFExoswBYGbWHZJWR0Rp23bfCsLMLKMcAGZmGeUAMDPLKAeAmVlGOQDMzDIqr24HXTyykEpfeWNmlgrPAMzMMsoBYGaWUQ4AM7OMcgCYmWWUA8DMLKMcAGZmGeUAMDPLKAeAmVlGOQDMzDLKAWBmllF59QdhJL0LPJfrOrppGLA510V0Q77VC665r7jm3tdb9Y6OiOFtG/PqXkDAc+39VZv+TFJlPtWcb/WCa+4rrrn39XW9PgRkZpZRDgAzs4zKtwC4NdcF7Id8qznf6gXX3Fdcc+/r03rz6iSwmZmlJ99mAGZmlhIHgJlZRuVFAEg6Q9Jzkl6UtCDX9bRH0hGSfi9pnaRaSf89aS+X9KqkquTnzFzX2pqkOknVSW2VSdthkv5L0gvJv4fmus7dJH2q1VhWSXpH0jf72zhL+qmkNyXVtGrrcFwlXZ7s389JOr2f1PsDSc9KWitpuaSPJ+1Fkra3Gutb+rreTmrucD/I9Rh3UvPSVvXWSapK2nt/nCOiX/8ABcBLwFjgAOAZ4Ohc19VOnSOAycnywcDzwNFAOfAPua6vk7rrgGFt2v4ZWJAsLwCuy3WdnewbbwCj+9s4AycDk4GafY1rsp88A3wMGJPs7wX9oN7TgAHJ8nWt6i1q3a+fjXG7+0F/GOOOam6z/l+AK/pqnPNhBnAc8GJEvBwR7wN3AWfnuKa9RMTrEbEmWX4XWAeMzG1V++1sYFGyvAg4J4e1dObzwEsR8UquC2krIh4G3mrT3NG4ng3cFRE7ImI98CLN+32faa/eiHggIj5IHj4BjOrLmvalgzHuSM7HGDqvWZKAvwWW9FU9+RAAI4ENrR7X08/fWCUVAZOAJ5Omv0+m0T/tT4dTEgE8IGm1pAuTtj+PiNehOdiAT+Ssus7NYc//LP15nKHjcc2HffyrwIpWj8dIelrSQ5JOylVRHWhvP8iHMT4J2BgRL7Rq69VxzocAUDtt/fbaVUkHAb8EvhkR7wA3A38BlACv0zzF609OjIjJwJeASyWdnOuCukLSAcBfA79Imvr7OHemX+/jkr4FfAAsTppeB46MiEnAZcC/SzokV/W10dF+0K/HOHEee36g6fVxzocAqAeOaPV4FPBajmrplKSBNL/5L46I/wCIiI0R0RQRu4DbyMG0szMR8Vry75vAcprr2yhpBEDy75u5q7BDXwLWRMRG6P/jnOhoXPvtPi6pDJgOnB/JgenkMEpDsrya5uPp43JX5Yc62Q/67RgDSBoAnAss3d3WF+OcDwFQARwlaUzyqW8OcG+Oa9pLcvzudmBdRNzQqn1Eq24zgJq2z80VSQdKOnj3Ms0n/WpoHt+ypFsZ8J+5qbBTe3xa6s/j3EpH43ovMEfSxySNAY4CnspBfXuQdAbwT8BfR8S2Vu3DJRUky2Nprvfl3FS5p072g345xq18AXg2Iup3N/TJOPf1WfD9PHN+Js1X1bwEfCvX9XRQ4zSap5Rrgark50zgTqA6ab8XGJHrWlvVPJbmKyOeAWp3jy0wFFgJvJD8e1iua21T9xCgAShs1davxpnmcHod2Enzp88LOhtX4FvJ/v0c8KV+Uu+LNB83370/35L0nZnsL88Aa4C/6kdj3OF+kOsx7qjmpP1nwMVt+vb6OPtWEGZmGZUPh4DMzKwXOADMzDLKAWBmllEOADOzjHIAmJlllAPAzCyjHABmZhn1/wHFGZX4iZi28QAAAABJRU5ErkJggg==\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"covid_Regioes_casos_obitos.transpose().plot.barh(stacked=True);"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### Gráfico de Setores\n",
"\n",
"O gráfico de setores, que também é popularmente conhecido como **gráfico pizza**, é um gráfico em que um círculo é dividido em setores, onde cada setor representa uma categoria considerada pelo conjunto de dados, e os ângulos dos setores são proporcionais aos valores dos dados em cada categoria. \n",
"\n",
"Podemos criar gráficos de setores utilizando o argumento `kind` do método `plot`. Assim, para criar um gráfico de setores, basta utilizar `plot(kind = 'pie')`. Também podemos criar estes gráficos utilizando o método `plot.pie()`. As duas formas são equivalentes. Para este gráfico é conveniente utilizar o argumento `figsize` já que o tamanho padrão tende a ser muito pequeno.\n",
"\n",
"Além disso, tipicamente é necessário acrescentar `subplots=True` para a criação de uma \"pizza\" para cada coluna numérica.\n",
"Em uma *Series* do *pandas*, não é necessário o argumento `subplots=True`."
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df_dict_series.plot.pie(subplots=True,figsize=(22,7));"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"Aqui temos um gráfico acerca da mortalidade de COVID-19 através das diferentes regiões do Brasil."
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"slideshow": {
"slide_type": "-"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"covid_Regioes_casos_obitos.obitosNovos.plot.pie(figsize=(7,7));"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### Gráfico de Dispersão\n",
"\n",
"O gráfico de dispersão representa dados de duas (ou mais) variáveis utilizando as coordenadas cartesianas para exibir valores de um conjunto de dados. Os dados são exibidos como uma coleção de pontos, cada um com o valor de uma variável determinando a posição no eixo horizontal e o valor da outra variável determinando a posição no eixo vertical. Quando há mais de duas variáveis, utilizam-se recursos adicionais como tamanhos dos pontos e/ou cores dos pontos.\n",
"\n",
"Para criar um gráfico de dispersão, basta utilizar `plot(kind = 'scatter')`. Também podemos criar estes gráficos utilizando o método `plot.scatter()`. As duas formas são equivalentes. \n",
"\n",
"Neste caso, devemos incluir dois argumentos: `x` e `y`, representando a abscissa e a ordenada, respectivamente. Para utilizar o *index* como eixo `x` é preciso que o *index* seja uma coluna, para tanto pode-se utilizar o método `reset_index()`. Assim, como nos outros métodos, podemos utilizar o argumento `rot` para rotacionar os rótulos do eixo `x`."
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"df_exemplo.reset_index().plot.scatter(x = 'index', y ='coluna_1' , rot = 45);"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"Podemos utilizar o argumento **s** para inserir o *tamanho* como uma variável gráfica (lembrando que o tamanho deve ser positivo):"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
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"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"ax = df_exemplo.reset_index().plot.scatter(x = 'index', y = 'coluna_1', label = 'coluna_1', \n",
" color = 'black', rot = 45)\n",
"df_exemplo.reset_index().plot.scatter(x = 'index', y = 'coluna_2', label = 'coluna_2', color = 'red',\n",
" rot = 45, ax = ax)\n",
"df_exemplo.reset_index().plot.scatter(x = 'index', y = 'coluna_3', label = 'coluna_3', color = 'green',\n",
" rot = 45, ax = ax)\n",
"\n",
"ax.set_ylabel(\"Valor\")\n",
"ax.set_xlabel(\"Data\")"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### Histograma\n",
"\n",
"O histograma é formado por uma justaposição de retângulos de bases com o mesmo comprimento. O comprimento da base é justamente a amplitude do intervalo e a altura do retângulo é dada pela frequência absoluta do intervalo. O histograma é a representação gráfica de *distribuição de frequência*.\n",
"\n",
"Para criar um histograma, basta utilizar `plot(kind = 'hist')`. Também podemos criar histogramas utilizando o método `plot.hist()`. As duas formas são equivalentes.\n",
"\n",
"Um parâmetro comumente utilizado é `alpha` que define a transparência dos histogramas e é dado por um número entre 0 e 1. Outro parâmetro comumente utilizado é `bins` que determina o número de intervalos a serem considerados. Se quisermos que os histogramas sejam \"plotados\" separadamente, utilizamos o método `hist()` diretamente."
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [
{
"data": {
"text/html": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"covid_BR_reg.plot.hist(bins=30);"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### BoxPlot\n",
"\n",
"O boxplot representa a variação dos dados de uma variável, por meio de uma caixa, onde são apresentados os *quartis*, e retas apresentando os limites inferior e superior dos dados. Os valores discrepantes ou *outliers* são plotados como pontos individuais.\n",
"\n",
"Para criar um BoxPlot, basta utilizar `plot(kind = 'box')`. Também podemos criar BoxPlots utilizando o método `plot.box()`. As duas formas são equivalentes. O argumento `vert=False` faz com que os BoxPlots fiquem horizontais."
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [
{
"data": {
"text/html": [
"