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    上学期写过一篇关于地图制作的博客，这里介绍第二种方法，利用plotly绘制地图。然而博主研究的过程中遇到很多问题，到现在也未解决，所以在这里将结果和问题一起呈现，欢迎大神赐教

    Plotly是一个用于做分析和可视化的在线平台，曾被网友称为“有史以来最牛逼”可视化神器，其功能强大到不仅与多个主流绘图软件的对接，而且还可以像Excel那样实现交互式制图，而且图表种类齐全。有关于python中使用plotly的介绍可以参考其官方文档。

一、安装

    plotly的安装直接pip install即可。如果不成功，可以参考博主的旧博文进行安装。

二、地图上画线

from plotly.offline import init_notebook_mode, iplot
init_notebook_mode(connected='True')

#需要连线的点
nyc_london = [ dict(
    type = 'scattergeo',
    lat = [ 40.7127, 51.5072 ],
    lon = [ -74.0059, 0.1275 ],
    mode = 'lines',
    line = dict(
        width = 2,
        color = 'blue',
    ),
) ]

#布局    
layout = dict(
        title = 'London to NYC Great Circle',
        showlegend = False,         
        geo = dict(
            resolution = 50,
            showland = True,
            showlakes = True,
            landcolor = 'rgb(204, 204, 204)',
            countrycolor = 'rgb(204, 204, 204)',
            lakecolor = 'rgb(255, 255, 255)',
            projection = dict( type="equirectangular" ),
            coastlinewidth = 2,
            lataxis = dict(
                range = [ 20, 60 ],
                showgrid = True,
                tickmode = "linear",
                dtick = 10
            ),
            lonaxis = dict(
                range = [-100, 20],
                showgrid = True,
                tickmode = "linear",
                dtick = 20
            ),
        )
    )
    
fig = dict( data=nyc_london, layout=layout )
iplot( fig, validate=False, filename='d3-great-circle' )

    上面是对其官方的demo的修改。官方demo满心欢喜想要运行时会报错。这里将其原先demo中引用的库

import plotly.plotly as py

  改为

from plotly.offline import init_notebook_mode, iplot
init_notebook_mode(connected='True')

  同时，将最后一句原本的"py.iplot..."改为"iplot..."，代码可以在jupyter notebook上运行。效果如下（仅仅是截图，真正效果是交互性的，可以实现地图缩小、放大等功能）：

三、地图上画气泡

from plotly.offline import init_notebook_mode, iplot
init_notebook_mode(connected='True')
import pandas as pd

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_us_cities.csv')
df.head()

df['text'] = df['name'] + '<br>Population ' + (df['pop']/1e6).astype(str)+' million'
limits = [(0,2),(3,10),(11,20),(21,50),(50,3000)]
colors = ["rgb(0,116,217)","rgb(255,65,54)","rgb(133,20,75)","rgb(255,133,27)","lightgrey"]
cities = []
scale = 5000

for i in range(len(limits)):
    lim = limits[i]
    df_sub = df[lim[0]:lim[1]]
    city = dict(
        type = 'scattergeo',
        locationmode = 'USA-states',
        lon = df_sub['lon'],
        lat = df_sub['lat'],
        text = df_sub['text'],
        marker = dict(
            size = df_sub['pop']/scale,
            # sizeref = 2. * max(df_sub['pop']/scale) / (25 ** 2),
            color = colors[i],
            line = dict(width=0.5, color='rgb(40,40,40)'),
            sizemode = 'area'
        ),
        name = '{0} - {1}'.format(lim[0],lim[1]) )
    cities.append(city)

layout = dict(
        title = '2014 US city populations<br>(Click legend to toggle traces)',
        showlegend = True,
        geo = dict(
            scope='usa',
            projection=dict( type='albers usa' ),
            showland = True,
            landcolor = 'rgb(217, 217, 217)',
            subunitwidth=1,
            countrywidth=1,
            subunitcolor="rgb(255, 255, 255)",
            countrycolor="rgb(255, 255, 255)"
        ),
    )

fig = dict(data=cities, layout=layout)
iplot(fig, validate=False, filename='d3-bubble-map-populations')

    这段代码同样是对其官方demo的修改，可以直接在jupyter notebook上运行成功，效果如下：

四、plotly调用mapbox绘制散点图

    这里，首先要申请一个Mapbox Access Token，根据提示即可申请。之后，便可以写代码进行可视化。

import plotly.graph_objs as go
from plotly.offline import init_notebook_mode, iplot
init_notebook_mode(connected='True')

mapbox_access_token ="xxx"
data = [
    go.Scattermapbox(
        lat=['38.91427','38.91538','38.91458',
             '38.92239','38.93222','38.90842',
             '38.91931','38.93260','38.91368',
             '38.88516','38.921894','38.93206',
             '38.91275'],
        lon=['-77.02827','-77.02013','-77.03155',
             '-77.04227','-77.02854','-77.02419',
             '-77.02518','-77.03304','-77.04509',
             '-76.99656','-77.042438','-77.02821',
             '-77.01239'],
        mode='markers',
        marker=dict(
            size=9
        ),
        text=["The coffee bar","Bistro Bohem","Black Cat",
             "Snap","Columbia Heights Coffee","Azi's Cafe",
             "Blind Dog Cafe","Le Caprice","Filter",
             "Peregrine","Tryst","The Coupe",
             "Big Bear Cafe"],
    )
]

layout = go.Layout(
    autosize=True,
    hovermode='closest',
    mapbox=dict(
        accesstoken=mapbox_access_token,
        bearing=0,
        center=dict(
            lat=38.92,
            lon=-77.07
        ),
        pitch=0,
        zoom=10
    ),
)

fig = dict(data=data, layout=layout)
iplot(fig, filename='Multiple Mapbox')

    这里同样是对官方样例的修改，然而修改后在jupyter notebook中仍然报错。最后笔者是在kesci的运行环境中运行成功的。效果如下：