python plotly 使用教程

1、plotly介绍

lotly的Python图形库使互动的出版质量图表成为在线。 如何制作线图，散点图，面积图，条形图，误差线，箱形图，直方图，热图，子图，多轴，极坐标图和气泡图的示例。

推荐最好使用jupyter notebook，使用pycharm的话不是很方便。

2、安装

pip install plotly

2、使用

1）在线使用

在setting里找到用户名和api key

 

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##在线使用
import plotly.plotly as py
from plotly import tools from plotly.graph_objs import * tools.set_credentials_file(username='yours', api_key='yours') trace0 = Scatter( x=[1, 2, 3, 4], y=[10, 15, 13, 17], mode='markers' ) trace1 = Scatter( x=[1, 2, 3, 4], y=[16, 5, 11, 9] ) data = Data([trace0, trace1]) py.iplot(data) 

散点图

 

散点图.png

2）offline

import plotly.offline as of
import plotly.graph_objs as go of.offline.init_notebook_mode(connected=True) trace0 = go.Scatter( x=[1, 2, 3, 4], y=[10, 15, 13, 17], mode='markers' ) trace1 = go.Scatter( x=[1, 2, 3, 4], y=[16, 5, 11, 9] ) data = go.Data([trace0, trace1]) of.plot(data) 

3、其他图

下面我们画几个其他类型的图

柱状图

import plotly.figure_factory as ff
import pandas as pd

df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/school_earnings.csv") data = [Bar(x=df.School, y=df.Gap)] py.iplot(data) 

 

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3D图

import numpy as np

s = np.linspace(0, 2 * np.pi, 240) t = np.linspace(0, np.pi, 240) tGrid, sGrid = np.meshgrid(s, t) r = 2 + np.sin(7 * sGrid + 5 * tGrid) # r = 2 + sin(7s+5t) x = r * np.cos(sGrid) * np.sin(tGrid) # x = r*cos(s)*sin(t) y = r * np.sin(sGrid) * np.sin(tGrid) # y = r*sin(s)*sin(t) z = r * np.cos(tGrid) # z = r*cos(t) surface = Surface(x=x, y=y, z=z) data = Data([surface]) layout = Layout( title='Parametric Plot', scene=Scene( xaxis=XAxis( gridcolor='rgb(255, 255, 255)', zerolinecolor='rgb(255, 255, 255)', showbackground=True, backgroundcolor='rgb(230, 230,230)' ), yaxis=YAxis( gridcolor='rgb(255, 255, 255)', zerolinecolor='rgb(255, 255, 255)', showbackground=True, backgroundcolor='rgb(230, 230,230)' ), zaxis=ZAxis( gridcolor='rgb(255, 255, 255)', zerolinecolor='rgb(255, 255, 255)', showbackground=True, backgroundcolor='rgb(230, 230,230)' ) ) ) fig = Figure(data=data, layout=layout) py.iplot(fig,) 

 

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折线图

import numpy as np

N = 100
random_x = np.linspace(0, 1, N) random_y0 = np.random.randn(N)+5 random_y1 = np.random.randn(N) random_y2 = np.random.randn(N)-5 # Create traces trace0 = go.Scatter( x = random_x, y = random_y0, mode = 'markers', name = 'markers' ) trace1 = go.Scatter( x = random_x, y = random_y1, mode = 'lines+markers', name = 'lines+markers' ) trace2 = go.Scatter( x = random_x, y = random_y2, mode = 'lines', name = 'lines' ) data = [trace0, trace1, trace2] py.iplot(data) 

 

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堆叠图

trace1 = go.Bar(
    x=['giraffes', 'orangutans', 'monkeys'],
    y=[20, 14, 23],
    name='SF Zoo'
)
trace2 = go.Bar(
    x=['giraffes', 'orangutans', 'monkeys'], y=[12, 18, 29], name='LA Zoo' ) data = [trace1, trace2] layout = go.Layout( barmode='stack' ) fig = go.Figure(data=data, layout=layout) py.iplot(fig) 

 

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pie

labels = ['Oxygen','Hydrogen','Carbon_Dioxide','Nitrogen']
values = [4500,2500,1053,500]
colors = ['#FEBFB3', '#E1396C', '#96D38C', '#D0F9B1'] trace = go.Pie(labels=labels, values=values, hoverinfo='label+percent', textinfo='value', textfont=dict(size=20), marker=dict(colors=colors, line=dict(color='#000000', width=2))) py.iplot([trace]) 

 

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不知道叫什么图

title = 'Main Source for News'

labels = ['Television', 'Newspaper', 'Internet', 'Radio'] colors = ['rgba(67,67,67,1)', 'rgba(115,115,115,1)', 'rgba(49,130,189, 1)', 'rgba(189,189,189,1)'] mode_size = [8, 8, 12, 8] line_size = [2, 2, 4, 2] x_data = [ [2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2013], [2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2013], [2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2013], [2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2013], ] y_data = [ [74, 82, 80, 74, 73, 72, 74, 70, 70, 66, 66, 69], [45, 42, 50, 46, 36, 36, 34, 35, 32, 31, 31, 28], [13, 14, 20, 24, 20, 24, 24, 40, 35, 41, 43, 50], [18, 21, 18, 21, 16, 14, 13, 18, 17, 16, 19, 23], ] traces = [] for i in range(0, 4): traces.append(go.Scatter( x=x_data[i], y=y_data[i], mode='lines', line=dict(color=colors[i], width=line_size[i]), connectgaps=True, )) traces.append(go.Scatter( x=[x_data[i][0], x_data[i][11]], y=[y_data[i][0], y_data[i][11]], mode='markers', marker=dict(color=colors[i], size=mode_size[i]) )) layout = go.Layout( xaxis=dict( showline=True, showgrid=False, showticklabels=True, linecolor='rgb(204, 204, 204)', linewidth=2, autotick=False, ticks='outside', tickcolor='rgb(204, 204, 204)', tickwidth=2, ticklen=5, tickfont=dict( family='Arial', size=12, color='rgb(82, 82, 82)', ), ), yaxis=dict( showgrid=False, zeroline=False, showline=False, showticklabels=False, ), autosize=False, margin=dict( autoexpand=False, l=100, r=20, t=110, ), showlegend=False, ) annotations = [] # Adding labels for y_trace, label, color in zip(y_data, labels, colors): # labeling the left_side of the plot annotations.append(dict(xref='paper', x=0.05, y=y_trace[0], xanchor='right', yanchor='middle', text=label + ' {}%'.format(y_trace[0]), font=dict(family='Arial', size=16, color=colors,), showarrow=False)) # labeling the right_side of the plot annotations.append(dict(xref='paper', x=0.95, y=y_trace[11], xanchor='left', yanchor='middle', text='{}%'.format(y_trace[11]), font=dict(family='Arial', size=16, color=colors,), showarrow=False)) # Title annotations.append(dict(xref='paper', yref='paper', x=0.0, y=1.05, xanchor='left', yanchor='bottom', text='Main Source for News', font=dict(family='Arial', size=30, color='rgb(37,37,37)'), showarrow=False)) # Source annotations.append(dict(xref='paper', yref='paper', x=0.5, y=-0.1, xanchor='center', yanchor='top', text='Source: PewResearch Center & ' + 'Storytelling with data', font=dict(family='Arial', size=12, color='rgb(150,150,150)'), showarrow=False)) layout['annotations'] = annotations fig = go.Figure(data=traces, layout=layout) py.iplot(fig) 

 

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4、各种具体语法

pdf

 

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5、总结

画的图真是好看，而且划过的图会自动上传到云端。

 

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作者：五长生
链接：https://www.jianshu.com/p/57bad75139ca
来源：简书
简书著作权归作者所有，任何形式的转载都请联系作者获得授权并注明出处。