Urban evolution of Mexico City. Animation video at https://www.youtube.com/watch?v=VoqyihiVzxw

animacion_catastro.py

import pandas as pd
import geopandas as gpd
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import time

start = time.time()

dir_datos = 'D:/datos/catastro_cdmx'
centroides = pd.read_pickle(f'{dir_datos}/centroides_completa.pkl')
fig, ax = plt.subplots(figsize=(15, 16.5))
fig.subplots_adjust(left=0, bottom=0, right=1, top=1, wspace=None, hspace=None)
for s in ax.spines.values():
    s.set_visible(False)

xlims = (-99.37, -98.92)
ylims = (19.1, 19.6)

def animate(frame):
    ax.cla()
    year = frame
    # plot año y
    centroides.query('anio_construccion==@year').plot(markersize=0.1, figsize=(10, 10), color='green', label=str(year), ax=ax)
    # plot años anteriores
    centroides.query('anio_construccion<@year').plot(markersize=0.001, color='white', label=f'antes de {year}', ax=ax)
    # Detalles de la gráfica
    ax.set(aspect='equal', yticks=[], xticks=[], ylim=ylims, xlim=xlims, facecolor='k')
    # titulo
    ax.text(s=str(year), x=0.5, y=0.97, fontsize=20, color='white', transform=ax.transAxes)
    # fuente
    fuente = ax.text(s='Elaborado por @jjsantoso con datos de ADIP.', x=1, y=0, ha='right', color='white', fontsize=10, transform=ax.transAxes)
    # Leyenda
    ax.legend(loc='center right')
    ley = ax.get_legend()
    if ley:
        for handle in ley.legendHandles:
            handle.set_sizes([15])
    
    print(frame)

frames = list(range(1950, 2020))
duracion = 30 # en segundos
interval = round(1000 * (duracion/len(frames)), 0)
ani = animation.FuncAnimation(fig, animate, frames=frames, blit=False, interval=interval)
ani.save("catastro_cdmx.mp4", dpi=200)
end = time.time()
print(end-start)
# plt.show()

preprocesamiento_catastro_cdmx.ipynb

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   "source": [
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "from shapely.geometry import MultiPolygon, Polygon\n",
    "dir_datos = 'D:/datos/catastro_cdmx'\n",
    "\n",
    "def convierte_multipolygon(x):\n",
    "    return MultiPolygon([Polygon(p) for P in eval(x)['coordinates'] for p in P])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   },
   "source": [
    "# Leyendo datos\n",
    "* Descargados de: https://sig.cdmx.gob.mx/datos/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "Collapsed": "false"
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   "outputs": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fid</th>\n",
       "      <th>geo_shape</th>\n",
       "      <th>anio_construccion</th>\n",
       "      <th>alcaldia_cumplimiento</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1156094</td>\n",
       "      <td>{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-99.0...</td>\n",
       "      <td>1979.0</td>\n",
       "      <td>XOCHIMILCO</td>\n",
       "      <td>(POLYGON ((-99.09918847801011 19.2639981760647...</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1156091</td>\n",
       "      <td>{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-99.0...</td>\n",
       "      <td>1982.0</td>\n",
       "      <td>XOCHIMILCO</td>\n",
       "      <td>(POLYGON ((-99.099195807972 19.2639096566576, ...</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1156080</td>\n",
       "      <td>{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-99.0...</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>XOCHIMILCO</td>\n",
       "      <td>(POLYGON ((-99.0992006818359 19.2638508724769,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1156081</td>\n",
       "      <td>{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-99.0...</td>\n",
       "      <td>1979.0</td>\n",
       "      <td>XOCHIMILCO</td>\n",
       "      <td>(POLYGON ((-99.09920514478129 19.2637970005209...</td>\n",
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       "    <tr>\n",
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       "      <td>{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-99.0...</td>\n",
       "      <td>1970.0</td>\n",
       "      <td>XOCHIMILCO</td>\n",
       "      <td>(POLYGON ((-99.099207906649 19.2637636533644, ...</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "       fid                                          geo_shape  \\\n",
       "0  1156094  {\"type\":\"MultiPolygon\",\"coordinates\":[[[[-99.0...   \n",
       "1  1156091  {\"type\":\"MultiPolygon\",\"coordinates\":[[[[-99.0...   \n",
       "2  1156080  {\"type\":\"MultiPolygon\",\"coordinates\":[[[[-99.0...   \n",
       "3  1156081  {\"type\":\"MultiPolygon\",\"coordinates\":[[[[-99.0...   \n",
       "4  1156078  {\"type\":\"MultiPolygon\",\"coordinates\":[[[[-99.0...   \n",
       "\n",
       "   anio_construccion alcaldia_cumplimiento  \\\n",
       "0             1979.0            XOCHIMILCO   \n",
       "1             1982.0            XOCHIMILCO   \n",
       "2             1986.0            XOCHIMILCO   \n",
       "3             1979.0            XOCHIMILCO   \n",
       "4             1970.0            XOCHIMILCO   \n",
       "\n",
       "                                            geometry  \n",
       "0  (POLYGON ((-99.09918847801011 19.2639981760647...  \n",
       "1  (POLYGON ((-99.099195807972 19.2639096566576, ...  \n",
       "2  (POLYGON ((-99.0992006818359 19.2638508724769,...  \n",
       "3  (POLYGON ((-99.09920514478129 19.2637970005209...  \n",
       "4  (POLYGON ((-99.099207906649 19.2637636533644, ...  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "df = pd.read_csv(f'{dir_datos}/sig_cdmx_cuentas_06_2020.csv', dtype={'fid': str}, usecols=['fid', 'geo_shape', 'anio_construccion', 'alcaldia_cumplimiento'])\\\n",
    "    .dropna(subset=['fid', 'geo_shape'])\n",
    "df['geometry'] = df['geo_shape'].apply(convierte_multipolygon)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "Collapsed": "false"
   },
   "source": [
    "## Calcula centroides"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "Collapsed": "false"
   },
   "outputs": [],
   "source": [
    "gdf = gpd.GeoDataFrame(df)\n",
    "centroides = gdf[['fid', 'anio_construccion', 'geometry']].copy()\n",
    "centroides['geometry'] = centroides['geometry'].centroid\n",
    "centroides.to_pickle(f'{dir_datos}/centroides_completa.pkl')"
   ]
  }
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