Plotting a map using geopandas and matplotlib

I have small csv that has 6 coordinates from Birmingham England. I read the csv with pandas then transformed it into GeoPandas DataFrame changing my latitude and longitude columns with Shapely Points. I am now trying to plot my GeoDataframe and all I can see are the points. How do I get the Birmingham map represented as well? A good documentation source on GeoPandas would be strongly appreciated too.

from shapely.geometry import Point
import geopandas as gpd
import pandas as pd

df = pd.read_csv('SiteLocation.csv')
df['Coordinates'] = list(zip(df.LONG, df.LAT))
df['Coordinates'] = df['Coordinates'].apply(Point)
# Building the GeoDataframe 
geo_df = gpd.GeoDataFrame(df, geometry='Coordinates')
geo_df.plot()

The GeoPandas documentation contains an example on how to add a background to a map (https://geopandas.readthedocs.io/en/latest/gallery/plotting_basemap_background.html), which is explained in more detail below.

You will have to deal with tiles, that are (png) images served through a web server, with a URL like

http://.../Z/X/Y.png, where Z is the zoom level, and X and Y identify the tile

And geopandas's doc shows how to set tiles as backgrounds for your plots, fetching the correct ones and doing all the otherwise difficult job of spatial syncing, etc...

Installation

Assuming GeoPandas is already installed, you need the contextily package in addition. If you are under windows, you may want to pick a look at How to install Contextily?

Use case

Create a python script and define the contextily helper function

import contextily as ctx

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))

and play

import matplotlib.pyplot as plt
from shapely.geometry import Point
import geopandas as gpd
import pandas as pd

# Let's define our raw data, whose epsg is 4326
df = pd.DataFrame({
    'LAT'  :[-22.266415, -20.684157],
    'LONG' :[166.452764, 164.956089],
})
df['coords'] = list(zip(df.LONG, df.LAT))

# ... turn them into geodataframe, and convert our
# epsg into 3857, since web map tiles are typically
# provided as such.
geo_df = gpd.GeoDataFrame(
    df, crs  ={'init': 'epsg:4326'},
    geometry = df['coords'].apply(Point)
).to_crs(epsg=3857)

# ... and make the plot
ax = geo_df.plot(
    figsize= (5, 5),
    alpha  = 1
)
add_basemap(ax, zoom=10)
ax.set_axis_off()
plt.title('Kaledonia : From Hienghène to Nouméa')
plt.show()

Note: you can play with the zoom to find the good resolution for the map. E.g./I.e. :

... and such resolutions implicitly call for changing the x/y limits.

Try df.unary_union. The function will aggregate points into a single geometry. Jupyter Notebook can plot it

来源：https://stackoverflow.com/questions/54088858/plotting-a-map-using-geopandas-and-matplotlib

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geopandas