博主是在Jupyter Notebooks上进行练习的，如果想知道如何创建Jupyter Notebooks，请点击这里

在coding 之前，得安装graph_objs

pip install graph_objs

这次实验使用的数据只是用来练习

先看要使用的数据：

import chart_studio.plotly as py
from plotly.offline import download_plotlyjs,init_notebook_mode,plot,iplot
import plotly.graph_objs as go
import pandas as pd
init_notebook_mode(connected=True)

df = pd.read_csv('2014_World_GDP')
df.head()

结果如下：

data = dict(type='choropleth',
           locations = df['CODE'],
           z = df['GDP (BILLIONS)'],
           text = df['COUNTRY'],
           colorbar = {'title': 'GDP in Billions USD'})

layout = dict(title = '2014 Global GDP',
             geo = dict(showframe = False,
                       projection = {'type':'mercator'}))

choromap = go.Figure(data=[data], layout = layout)
iplot(choromap)

结果如下：

data = dict(type='choropleth',
           locations = df['CODE'],
           z = df['GDP (BILLIONS)'],
           text = df['COUNTRY'],
           colorbar = {'title': 'GDP in Billions USD'})

layout = dict(title = '2014 Global GDP',
             geo = dict(showframe = False,
                       projection = {'type':'stereographic'}))

choromap = go.Figure(data=[data], layout = layout)
iplot(choromap)

结果如下：

data = dict(type='choropleth',
           locations = df['CODE'],
           z = df['GDP (BILLIONS)'],
           text = df['COUNTRY'],
           colorbar = {'title': 'GDP in Billions USD'})

layout = dict(title = '2014 Global GDP',
             geo = dict(showframe = False,
                       projection = {'type':'natural earth'}))

choromap = go.Figure(data=[data], layout = layout)
iplot(choromap)

效果如下：

如果觉得不错，就点赞或者关注或者留言~~
谢谢~ ~