Python3 - plotly 练习题

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

先展示要使用的数据：

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_Power_Consumption')
df.head()

数据如下：

# locations: Either a name of a column in data_grame, or a pandas Series or array_like object.
# locationmode: One of 'ISO-3','USA-states', or 'country names' Determines the set of locations used to match entries in locations to regions on the map
data = dict(type = 'choropleth',
           locations = df['Country'],
           locationmode = 'country names',
           z = df['Power Consumption KWH'],
           text = df['Country'],
           colorbar = {'title': 'Power Consumption KWH'})

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

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

结果如下：

data = dict(type = 'choropleth',
           locations = df['Country'],
           colorscale = 'Viridis',
           reversescale = True,
           locationmode = 'country names',
           z = df['Power Consumption KWH'],
           text = df['Country'],
           colorbar = {'title': 'Power Consumption KWH'})

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

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

结果如下：

data = dict(type = 'choropleth',
           locations = df['Country'],
           colorscale = 'Viridis',
           reversescale = True,
           locationmode = 'country names',
           z = df['Power Consumption KWH'],
           text = df['Country'],
           colorbar = {'title': 'Power Consumption KWH'})

layout = dict(title='2014 Power Consumption',
             geo = dict(showframe=True, projection={'type':'mercator'}))

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

结果如下：

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本文地址：https://blog.csdn.net/BSCHN123/article/details/112004659