Dash学习记录

发表于2021-05-12更新于2021-05-20字数统计1.1k阅读时长12分

添加子图

效果

subplot

代码

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import plotly.graph_objects as go
from plotly.subplots import make_subplots

fig = make_subplots(rows=2, cols=2, start_cell="bottom-left")

fig.add_trace(go.Scatter(x=[1, 2, 3], y=[4, 5, 6]),
              row=1, col=1)

fig.add_trace(go.Scatter(x=[20, 30, 40], y=[50, 60, 70]),
              row=1, col=2)

fig.add_trace(go.Scatter(x=[300, 400, 500], y=[600, 700, 800]),
              row=2, col=1)

fig.add_trace(go.Scatter(x=[4000, 5000, 6000], y=[7000, 8000, 9000]),
              row=2, col=2)

fig.show()

定时刷新app

Dash app 的实时刷新功能主要依赖于 dash_core_components.Interval， 将Interval元素作为回调函数的输入，需要实时刷新的元素的相关属性值作为输出，通过监听Interval元素的 n_intervals 属性从而实现app的动态自动更新。Interval元素的interval属性可以控制刷新频率，该属性单位为毫秒，取整数值。例如需要app每分钟刷新一次，可以设置 interval = 60*1000

代码

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dcc.Interval(
         id='interval',
         interval=second * 1000,
         n_intervals=0
     )

自定义子图

效果

custom subplot

代码

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from plotly.subplots import make_subplots
import plotly.graph_objects as go

fig = make_subplots(
    rows=5, cols=2,
    specs=[[{}, {"rowspan": 2}],
           [{}, None],
           [{"rowspan": 2, "colspan": 2}, None],
           [None, None],
           [{}, {}]],
    print_grid=True)

fig.add_trace(go.Scatter(x=[1, 2], y=[1, 2], name="(1,1)"), row=1, col=1)
fig.add_trace(go.Scatter(x=[1, 2], y=[1, 2], name="(1,2)"), row=1, col=2)
fig.add_trace(go.Scatter(x=[1, 2], y=[1, 2], name="(2,1)"), row=2, col=1)
fig.add_trace(go.Scatter(x=[1, 2], y=[1, 2], name="(3,1)"), row=3, col=1)
fig.add_trace(go.Scatter(x=[1, 2], y=[1, 2], name="(5,1)"), row=5, col=1)
fig.add_trace(go.Scatter(x=[1, 2], y=[1, 2], name="(5,2)"), row=5, col=2)

fig.update_layout(height=600, width=600, title_text="specs examples")
fig.show()

多类型子图

效果

multi-types-subplot

代码

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from plotly.subplots import make_subplots
import plotly.graph_objects as go

fig = make_subplots(
    rows=2, cols=2,
    specs=[[{"type": "xy"}, {"type": "polar"}],
           [{"type": "domain"}, {"type": "scene"}]],
)

fig.add_trace(go.Bar(y=[2, 3, 1]),
              row=1, col=1)

fig.add_trace(go.Barpolar(theta=[0, 45, 90], r=[2, 3, 1]),
              row=1, col=2)

fig.add_trace(go.Pie(values=[2, 3, 1]),
              row=2, col=1)

fig.add_trace(go.Scatter3d(x=[2, 3, 1], y=[0, 0, 0],
                           z=[0.5, 1, 2], mode="lines"),
              row=2, col=2)

fig.update_layout(height=700, showlegend=False)

fig.show()

共享x轴

效果

shared-x

代码

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import plotly.graph_objects as go

trace1 = go.Scatter(
    x=[0, 1, 2],
    y=[10, 11, 12]
)
trace2 = go.Scatter(
    x=[2, 3, 4],
    y=[100, 110, 120],
    yaxis="y2"
)
trace3 = go.Scatter(
    x=[3, 4, 5],
    y=[1000, 1100, 1200],
    yaxis="y3"
)
data = [trace1, trace2, trace3]
layout = go.Layout(
    yaxis=dict(
        domain=[0, 0.33]
    ),
    legend=dict(
        traceorder="reversed"
    ),
    yaxis2=dict(
        domain=[0.33, 0.66]
    ),
    yaxis3=dict(
        domain=[0.66, 1]
    )
)
fig = go.Figure(data=data, layout=layout)
fig.show()

按照指定字段划分出子图

效果

鸢尾花数据集按照species字段划分出子图

subplot

代码

facet_col = "species"

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import plotly.express as px
import plotly.graph_objects as go

df = px.data.iris()

fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species", facet_col="species",
                 title="Adding Traces To Subplots Within A Plotly Express Figure")

reference_line = go.Scatter(x=[2, 4],
                            y=[4, 8],
                            mode="lines",
                            line=go.scatter.Line(color="gray"),
                            showlegend=False)

fig.add_trace(reference_line, row=1, col=1)
fig.add_trace(reference_line, row=1, col=2)
fig.add_trace(reference_line, row=1, col=3)

fig.show()

指定颜色

效果

color

代码

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from plotly.subplots import make_subplots

fig = make_subplots(rows=1, cols=2)

fig.add_scatter(y=[4, 2, 3.5], mode="markers",
                marker=dict(size=20, color="LightSeaGreen"),
                name="a", row=1, col=1)

fig.add_bar(y=[2, 1, 3],
            marker=dict(color="MediumPurple"),
            name="b", row=1, col=1)

fig.add_scatter(y=[2, 3.5, 4], mode="markers",
                marker=dict(size=20, color="MediumPurple"),
                name="c", row=1, col=2)

fig.add_bar(y=[1, 3, 2],
            marker=dict(color="LightSeaGreen"),
            name="d", row=1, col=2)

fig.show()

不同风格的主题

效果

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代码

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import plotly.express as px

df = px.data.gapminder()
df_2007 = df.query("year==2007")

for template in ["plotly", "plotly_white", "plotly_dark", "ggplot2", "seaborn", "simple_white", "none"]:
    fig = px.scatter(df_2007,
                     x="gdpPercap", y="lifeExp", size="pop", color="continent",
                     log_x=True, size_max=60,
                     template=template, title="Gapminder 2007: '%s' theme" % template)
    fig.show()

注册自己的主题+混合主题

效果

theme

代码

theme 

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import plotly.io as pio
import plotly.express as px
import plotly.graph_objects as go

pio.templates["draft"] = go.layout.Template(
    layout_annotations=[
        dict(
            name="draft watermark",
            text="DRAFT",
            textangle=-30,
            opacity=0.1,
            font=dict(color="black", size=100),
            xref="paper",
            yref="paper",
            x=0.5,
            y=0.5,
            showarrow=False,
        )
    ]
)
pio.templates.default = "seaborn+draft"

df = px.data.gapminder()
df_2007 = df.query("year==2007")

fig = px.scatter(df_2007,
                 x="gdpPercap", y="lifeExp", size="pop", color="continent",
                 log_x=True, size_max=60,
                 title="Gapminder 2007: current default theme")
fig.show()

另存为

效果

支持很多格式

save-as

代码

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fig.write_image("images/fig1.png")
fig.write_image("images/fig1.jpeg")
fig.write_image("images/fig1.webp")
fig.write_image("images/fig1.svg")
fig.write_image("images/fig1.pdf")

保存为网页

代码

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plotly.offline.plot(fig, html_name)