How to use contextily - 10 common examples

def draw(self):
            ax = plot.ax
            if len(self.df.geometry) == 0:
                return ax

            basemap, extent = ctx.bounds2img(
                *self._webmap_extent, zoom=self.zoom, 
                url=getattr(ctx.sources, provider), ll=True
            )
            extent = (extent[0], extent[1], extent[3], extent[2])
            ax.imshow(basemap, extent=extent, interpolation='bilinear')
            return ax

def add_basemap(ax, zoom, url='http://tile.stamen.com/terrain/tileZ/tileX/tileY.png'):
    xmin, xmax, ymin, ymax = ax.axis()
    basemap, extent = ctx.bounds2img(xmin, ymin, xmax, ymax, zoom=zoom, url=url)
    ax.imshow(basemap, extent=extent, interpolation='bilinear')
    # restore original x/y limits
    ax.axis((xmin, xmax, ymin, ymax))

ctx.add_basemap(ax)

###############################################################################
# We can control the detail of the map tiles using the optional `zoom` keyword
# (be careful to not specify a too high `zoom` level,
# as this can result in a large download).:

ax = df.plot(figsize=(10, 10), alpha=0.5, edgecolor='k')
ctx.add_basemap(ax, zoom=12)

###############################################################################
# By default, contextily uses the Stamen Terrain style. We can specify a
# different style using ``ctx.providers``:

ax = df.plot(figsize=(10, 10), alpha=0.5, edgecolor='k')
ctx.add_basemap(ax, url=ctx.providers.Stamen.TonerLite)
ax.set_axis_off()

# Add background tiles to plot
# ============================
#
# We can use `add_basemap` function of contextily to easily add a background
# map to our plot. :

ax = df.plot(figsize=(10, 10), alpha=0.5, edgecolor='k')
ctx.add_basemap(ax)

###############################################################################
# We can control the detail of the map tiles using the optional `zoom` keyword
# (be careful to not specify a too high `zoom` level,
# as this can result in a large download).:

ax = df.plot(figsize=(10, 10), alpha=0.5, edgecolor='k')
ctx.add_basemap(ax, zoom=12)

###############################################################################
# By default, contextily uses the Stamen Terrain style. We can specify a
# different style using ``ctx.providers``:

ax = df.plot(figsize=(10, 10), alpha=0.5, edgecolor='k')
ctx.add_basemap(ax, url=ctx.providers.Stamen.TonerLite)
ax.set_axis_off()

df = df.to_crs(epsg=3857)

###############################################################################

import contextily as ctx

###############################################################################
# Add background tiles to plot
# ============================
#
# We can use `add_basemap` function of contextily to easily add a background
# map to our plot. :

ax = df.plot(figsize=(10, 10), alpha=0.5, edgecolor='k')
ctx.add_basemap(ax)

###############################################################################
# We can control the detail of the map tiles using the optional `zoom` keyword
# (be careful to not specify a too high `zoom` level,
# as this can result in a large download).:

ax = df.plot(figsize=(10, 10), alpha=0.5, edgecolor='k')
ctx.add_basemap(ax, zoom=12)

###############################################################################
# By default, contextily uses the Stamen Terrain style. We can specify a
# different style using ``ctx.providers``:

ax = df.plot(figsize=(10, 10), alpha=0.5, edgecolor='k')
ctx.add_basemap(ax, url=ctx.providers.Stamen.TonerLite)
ax.set_axis_off()

zoom = kwargs.pop('zoom', None)

            # The plot extent is a well-defined function of plot data geometry and user input to
            # the "extent" parameter, except in the case of numerical instability or invalid user
            # input, in which case the default plot extent for the given projection is used. But
            # the default extent is not well-exposed inside of the Cartopy API, so in edge cases
            # where we are forced to fall back to default extent we don't actually know the true
            # plot extent.
            #
            # For this reason we (1) recalculate "good case" plot extent here, instead of saving
            # the value to an init variable and (2) accept that this calculation is potentially
            # incorrect in edge cases.
            extent = relax_bounds(*self.df.total_bounds) if self.extent is None else self.extent

            if zoom is None:
                zoom = ctx.tile._calculate_zoom(*extent)
            else:
                howmany = ctx.tile.howmany(*extent, zoom, ll=True, verbose=False)
                if howmany > 100:
                    better_zoom_level = ctx.tile._calculate_zoom(*extent)
                    warnings.warn(
                        f'Generating a webmap at zoom level {zoom} for the given plot extent '
                        f'requires downloading {howmany} individual tiles. This slows down '
                        f'plot generation and places additional pressure on the tile '
                        f'provider\'s server, which many deny your request when placed under '
                        f'high load or high request volume. Consider setting "zoom" to '
                        f'{better_zoom_level} instead. This is the recommended zoom level for '
                        f'the given plot extent.'
                    )
            self.zoom = zoom
            self._webmap_extent = extent

# input, in which case the default plot extent for the given projection is used. But
            # the default extent is not well-exposed inside of the Cartopy API, so in edge cases
            # where we are forced to fall back to default extent we don't actually know the true
            # plot extent.
            #
            # For this reason we (1) recalculate "good case" plot extent here, instead of saving
            # the value to an init variable and (2) accept that this calculation is potentially
            # incorrect in edge cases.
            extent = relax_bounds(*self.df.total_bounds) if self.extent is None else self.extent

            if zoom is None:
                zoom = ctx.tile._calculate_zoom(*extent)
            else:
                howmany = ctx.tile.howmany(*extent, zoom, ll=True, verbose=False)
                if howmany > 100:
                    better_zoom_level = ctx.tile._calculate_zoom(*extent)
                    warnings.warn(
                        f'Generating a webmap at zoom level {zoom} for the given plot extent '
                        f'requires downloading {howmany} individual tiles. This slows down '
                        f'plot generation and places additional pressure on the tile '
                        f'provider\'s server, which many deny your request when placed under '
                        f'high load or high request volume. Consider setting "zoom" to '
                        f'{better_zoom_level} instead. This is the recommended zoom level for '
                        f'the given plot extent.'
                    )
            self.zoom = zoom
            self._webmap_extent = extent

def draw(self):
            ax = plot.ax
            if len(self.df.geometry) == 0:
                return ax

            basemap, extent = ctx.bounds2img(
                *self._webmap_extent, zoom=self.zoom, 
                url=getattr(ctx.sources, provider), ll=True
            )
            extent = (extent[0], extent[1], extent[3], extent[2])
            ax.imshow(basemap, extent=extent, interpolation='bilinear')
            return ax

# ============================
#
# Now we can use the above function to easily add a background map to our
# plot. The `zoom` keyword is required and let's you specify the detail of the
# map tiles (be careful to not specify a too high `zoom` level, as this can
# result in a large download):

ax = df.plot(figsize=(10, 10), alpha=0.5, edgecolor='k')
add_basemap(ax, zoom=10)

###############################################################################
# By default, contextily uses the Stamen Terrain style. We can specify a
# different style using ``ctx.sources``:

ax = df.plot(figsize=(10, 10), alpha=0.5, edgecolor='k')
add_basemap(ax, zoom=11, url=ctx.sources.ST_TONER_LITE)
ax.set_axis_off()

# The plot extent is a well-defined function of plot data geometry and user input to
            # the "extent" parameter, except in the case of numerical instability or invalid user
            # input, in which case the default plot extent for the given projection is used. But
            # the default extent is not well-exposed inside of the Cartopy API, so in edge cases
            # where we are forced to fall back to default extent we don't actually know the true
            # plot extent.
            #
            # For this reason we (1) recalculate "good case" plot extent here, instead of saving
            # the value to an init variable and (2) accept that this calculation is potentially
            # incorrect in edge cases.
            extent = relax_bounds(*self.df.total_bounds) if self.extent is None else self.extent

            if zoom is None:
                zoom = ctx.tile._calculate_zoom(*extent)
            else:
                howmany = ctx.tile.howmany(*extent, zoom, ll=True, verbose=False)
                if howmany > 100:
                    better_zoom_level = ctx.tile._calculate_zoom(*extent)
                    warnings.warn(
                        f'Generating a webmap at zoom level {zoom} for the given plot extent '
                        f'requires downloading {howmany} individual tiles. This slows down '
                        f'plot generation and places additional pressure on the tile '
                        f'provider\'s server, which many deny your request when placed under '
                        f'high load or high request volume. Consider setting "zoom" to '
                        f'{better_zoom_level} instead. This is the recommended zoom level for '
                        f'the given plot extent.'
                    )
            self.zoom = zoom
            self._webmap_extent = extent