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

 

image.png

##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)

 

image.png

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,)

 

image.png

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)

 

image.png

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)

 

image.png

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])

 

image.png

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。