2.1.9.2.Choropleth Maps - World

1. 使用library

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

2.從實際資料中繪製Choropleth Map

  • 讀取資料

    • 可在資料中放入想要顯示的country code, z值 (數量), label

      import pandas as pd
      df = pd.read_csv('2014_World_GDP')
      df.head()

  • Choropleth Map的兩個要素 Data, Layout

    • Data的locationmode預設為country code, 因此若locations是country code則不需指定locationmode

      data = dict(
        type = 'choropleth',
        locations = df['CODE'],
        z = df['GDP (BILLIONS)'],
        text = df['COUNTRY'],
        colorbar = {'title' : 'GDP Billions US'},
      ) 
      
      layout = dict(
      title = '2014 Global GDP',
      geo = dict(
        showframe = False,
        projection = {'type':'Mercator'}
      )
      )
    • 若資料來源是country name, 則必須在指定locationmode中指定: locationmode = "country names"

      data = dict(
        type = 'choropleth',
        locations = df['COUNTRY'],
        locationmode = "country names",
        z = df['GDP (BILLIONS)'],
        text = df['COUNTRY'],
        colorbar = {'title' : 'GDP Billions US'},
      )
      
      layout = dict(
      title = '2014 Global GDP',
      geo = dict(
        showframe = False,
        projection = {'type':'Mercator'}
      )
      )
  • 製作Choropleth Map

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

Last updated

Was this helpful?