使用python在国家地图上绘制数据的最简单方法

虽然此问题在当前形式下似乎无法回答，但我至少要注意，使用底图时您似乎有问题-您不会想要导入Shapefile，但只需使用Basemap对象的readshapefile方法读取它，如下所示:

While this question seems to be unanswerable in its current form, I'll at least note that you seem to be something wrong when using basemap - you don't want to import Shapefile, but simply read it using the readshapefile method of a Basemap object like so:

m = Basemap(projection='tmerc')
m.readshapefile("/path/to/your/shapefile", "mexican_states")

然后您将能够通过m.mexican_states(作为数组列表)访问每个州边界的坐标，并通过m.mexican_states_info访问相应的信息(例如名称，可能是一个识别码).然后，您将需要某种dict或DataFrame，其中包含状态的名称/代码(与m.mexican_states_info中的内容相对应)和要绘制的值.一个简单的示例将像这样工作，假设您有一个名为mexican_states_sick_people的字典，其外观类似于{"Mexico City":123, "Chiapas":35, ...}:

You will then be able to access the coordinates of each state's boundaries via m.mexican_states (as a list of arrays) and the corresponding information (such as names, maybe an indentifying code) by m.mexican_states_info. You will then need some sort of dict or DataFrame containing names/codes for states (corresponding to what is in m.mexican_states_info) and the values you want to plot. A simple example would work something like this, assuming that you have a dict called mexican_states_sick_people that looks something like {"Mexico City":123, "Chiapas":35, ...}:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import PatchCollection
from mpl_toolkits.basemap import Basemap
from shapely.geometry import Polygon
from descartes import PolygonPatch

fig, ax = plt.subplots()

# Set up basemap and read in state shapefile (this will draw all state boundaries)
m = Basemap(projection='tmerc')
m.readshapefile("/path/to/your/shapefile", "mexican_states")

# Get maximum number of sick people to calculate shades for states based on relative number    
max_sick = np.max(mexican_states_sick_people.values())

# Loop through the states contained in shapefile, attaching a PolygonPatch for each of them with shade corresponding to relative number of sick people
state_patches = []
for coordinates, state in zip(m.mexican_states, m.mexican_states_info):
    if state["State_name"] in mexican_states_sick_people.keys():
        shade = mexican_states_sick_people[state["State_name"]]/max_sick       
        state_patches.append(PolygonPatch(Polygon(coordinates), fc = "darkred", ec='#555555', lw=.2, alpha=shade, zorder=4)

 # Put PatchCollection of states on the map
ax.add_collection(PatchCollection(state_patches, match_original=True))

如果您有一个有效的州shapefile，并确保您拥有的患者数据集具有每种州的某种标识符(名称或代码)，以使您与之匹配，则此示例应该或多或少地起作用在shapefile中带有状态标识符的数字(这是循环中的shade = ...行所依赖的-在本例中，我使用shapefile中的名称作为键来访问字典中的val).

This example should be more or less functional, if you have a working shapefile of states and make sure that the dataset of sick people you have has some sort of identifier (name or code) for each state that allows you to match up the numbers with the identifier of states in the shapefile (this is what the shade = ... line in the loop relies upon - in the example I'm accessing the vals in the dictionary using a name from the shapefile as key).

希望这会有所帮助，祝您好运！

Hope this helps, good luck!