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Range Slider and Selector in Python

Now you can implement range sliders and selectors in your Plotly graphs purely with python!


New to Plotly?

Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

Basic Range Slider and Range Selectors

In [1]:
import plotly.graph_objects as go

import pandas as pd

# Load data
df = pd.read_csv(
    "https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv")
df.columns = [col.replace("AAPL.", "") for col in df.columns]

# Create figure
fig = go.Figure()

fig.add_trace(
    go.Scatter(x=list(df.Date), y=list(df.High)))

# Set title
fig.update_layout(
    title_text="Time series with range slider and selectors"
)

# Add range slider
fig.update_layout(
    xaxis=dict(
        rangeselector=dict(
            buttons=list([
                dict(count=1,
                     label="1m",
                     step="month",
                     stepmode="backward"),
                dict(count=6,
                     label="6m",
                     step="month",
                     stepmode="backward"),
                dict(count=1,
                     label="YTD",
                     step="year",
                     stepmode="todate"),
                dict(count=1,
                     label="1y",
                     step="year",
                     stepmode="backward"),
                dict(step="all")
            ])
        ),
        rangeslider=dict(
            visible=True
        ),
        type="date"
    )
)

fig.show()

Range Slider with Vertically Stacked Subplots

In [2]:
import plotly.graph_objects as go

# Create figure
fig = go.Figure()

# Add traces
fig.add_trace(go.Scatter(
    x=["2013-01-15", "2013-01-29", "2013-02-26", "2013-04-19", "2013-07-02",
       "2013-08-27",
       "2013-10-22", "2014-01-20", "2014-05-05", "2014-07-01", "2015-02-09",
       "2015-04-13",
       "2015-05-13", "2015-06-08", "2015-08-05", "2016-02-25"],
    y=["8", "3", "2", "10", "5", "5", "6", "8", "3", "3", "7", "5", "10", "10", "9",
       "14"],
    name="var0",
    text=["8", "3", "2", "10", "5", "5", "6", "8", "3", "3", "7", "5", "10", "10", "9",
          "14"],
    yaxis="y",
))

fig.add_trace(go.Scatter(
    x=["2015-04-13", "2015-05-13", "2015-06-08", "2015-08-05", "2016-02-25"],
    y=["53.0", "69.0", "89.0", "41.0", "41.0"],
    name="var1",
    text=["53.0", "69.0", "89.0", "41.0", "41.0"],
    yaxis="y2",
))

fig.add_trace(go.Scatter(
    x=["2013-01-29", "2013-02-26", "2013-04-19", "2013-07-02", "2013-08-27",
       "2013-10-22",
       "2014-01-20", "2014-04-09", "2014-05-05", "2014-07-01", "2014-09-30",
       "2015-02-09",
       "2015-04-13", "2015-06-08", "2016-02-25"],
    y=["9.6", "4.6", "2.7", "8.3", "18", "7.3", "3", "7.5", "1.0", "0.5", "2.8", "9.2",
       "13", "5.8", "6.9"],
    name="var2",
    text=["9.6", "4.6", "2.7", "8.3", "18", "7.3", "3", "7.5", "1.0", "0.5", "2.8",
          "9.2",
          "13", "5.8", "6.9"],
    yaxis="y3",
))

fig.add_trace(go.Scatter(
    x=["2013-01-29", "2013-02-26", "2013-04-19", "2013-07-02", "2013-08-27",
       "2013-10-22",
       "2014-01-20", "2014-04-09", "2014-05-05", "2014-07-01", "2014-09-30",
       "2015-02-09",
       "2015-04-13", "2015-06-08", "2016-02-25"],
    y=["6.9", "7.5", "7.3", "7.3", "6.9", "7.1", "8", "7.8", "7.4", "7.9", "7.9", "7.6",
       "7.2", "7.2", "8.0"],
    name="var3",
    text=["6.9", "7.5", "7.3", "7.3", "6.9", "7.1", "8", "7.8", "7.4", "7.9", "7.9",
          "7.6",
          "7.2", "7.2", "8.0"],
    yaxis="y4",
))

fig.add_trace(go.Scatter(
    x=["2013-02-26", "2013-07-02", "2013-09-26", "2013-10-22", "2013-12-04",
       "2014-01-02",
       "2014-01-20", "2014-05-05", "2014-07-01", "2015-02-09", "2015-05-05"],
    y=["290", "1078", "263", "407", "660", "740", "33", "374", "95", "734", "3000"],
    name="var4",
    text=["290", "1078", "263", "407", "660", "740", "33", "374", "95", "734", "3000"],
    yaxis="y5",
))

# style all the traces
fig.update_traces(
    hoverinfo="name+x+text",
    line={"width": 0.5},
    marker={"size": 8},
    mode="lines+markers",
    showlegend=False
)

# Add annotations
fig.update_layout(
    annotations=[
        dict(
            x="2013-06-01",
            y=0,
            arrowcolor="rgba(63, 81, 181, 0.2)",
            arrowsize=0.3,
            ax=0,
            ay=30,
            text="state1",
            xref="x",
            yanchor="bottom",
            yref="y"
        ),
        dict(
            x="2014-09-13",
            y=0,
            arrowcolor="rgba(76, 175, 80, 0.1)",
            arrowsize=0.3,
            ax=0,
            ay=30,
            text="state2",
            xref="x",
            yanchor="bottom",
            yref="y"
        )
    ],
)

# Add shapes
fig.update_layout(
    shapes=[
        dict(
            fillcolor="rgba(63, 81, 181, 0.2)",
            line={"width": 0},
            type="rect",
            x0="2013-01-15",
            x1="2013-10-17",
            xref="x",
            y0=0,
            y1=0.95,
            yref="paper"
        ),
        dict(
            fillcolor="rgba(76, 175, 80, 0.1)",
            line={"width": 0},
            type="rect",
            x0="2013-10-22",
            x1="2015-08-05",
            xref="x",
            y0=0,
            y1=0.95,
            yref="paper"
        )
    ]
)

# Update axes
fig.update_layout(
    xaxis=dict(
        autorange=True,
        range=["2012-10-31 18:36:37.3129", "2016-05-10 05:23:22.6871"],
        rangeslider=dict(
            autorange=True,
            range=["2012-10-31 18:36:37.3129", "2016-05-10 05:23:22.6871"]
        ),
        type="date"
    ),
    yaxis=dict(
        anchor="x",
        autorange=True,
        domain=[0, 0.2],
        linecolor="#673ab7",
        mirror=True,
        range=[-60.0858369099, 28.4406294707],
        showline=True,
        side="right",
        tickfont={"color": "#673ab7"},
        tickmode="auto",
        ticks="",
        titlefont={"color": "#673ab7"},
        type="linear",
        zeroline=False
    ),
    yaxis2=dict(
        anchor="x",
        autorange=True,
        domain=[0.2, 0.4],
        linecolor="#E91E63",
        mirror=True,
        range=[29.3787777032, 100.621222297],
        showline=True,
        side="right",
        tickfont={"color": "#E91E63"},
        tickmode="auto",
        ticks="",
        titlefont={"color": "#E91E63"},
        type="linear",
        zeroline=False
    ),
    yaxis3=dict(
        anchor="x",
        autorange=True,
        domain=[0.4, 0.6],
        linecolor="#795548",
        mirror=True,
        range=[-3.73690396239, 22.2369039624],
        showline=True,
        side="right",
        tickfont={"color": "#795548"},
        tickmode="auto",
        ticks="",
        title="mg/L",
        titlefont={"color": "#795548"},
        type="linear",
        zeroline=False
    ),
    yaxis4=dict(
        anchor="x",
        autorange=True,
        domain=[0.6, 0.8],
        linecolor="#607d8b",
        mirror=True,
        range=[6.63368032236, 8.26631967764],
        showline=True,
        side="right",
        tickfont={"color": "#607d8b"},
        tickmode="auto",
        ticks="",
        title="mmol/L",
        titlefont={"color": "#607d8b"},
        type="linear",
        zeroline=False
    ),
    yaxis5=dict(
        anchor="x",
        autorange=True,
        domain=[0.8, 1],
        linecolor="#2196F3",
        mirror=True,
        range=[-685.336803224, 3718.33680322],
        showline=True,
        side="right",
        tickfont={"color": "#2196F3"},
        tickmode="auto",
        ticks="",
        title="mg/Kg",
        titlefont={"color": "#2196F3"},
        type="linear",
        zeroline=False
    )
)

# Update layout
fig.update_layout(
    dragmode="zoom",
    hovermode="x",
    legend=dict(traceorder="reversed"),
    height=600,
    template="plotly_white",
    margin=dict(
        t=100,
        b=100
    ),
)

fig.show()

What About Dash?

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash at https://dash.plot.ly/installation.

Everywhere in this page that you see fig.show(), you can display the same figure in a Dash application by passing it to the figure argument of the Graph component from the built-in dash_core_components package like this:

import plotly.graph_objects as go # or plotly.express as px
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.add_trace( ... )
# fig.update_layout( ... )

import dash
import dash_core_components as dcc
import dash_html_components as html

app = dash.Dash()
app.layout = html.Div([
    dcc.Graph(figure=fig)
])

app.run_server(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter