Plotly: How to add a horizontal scrollbar to a plotly express figure?

Question

I'm beginning to learn more about plotly and pandas and have a multivariate time series I wish to plot and interact with using plotly.express features. I also want my plot to a horizontal scrollbar so that the initial plot is for a pre-specified initial time interval. Here's my example involving three time series along with 100K time points:

import plotly.express as px
import numpy as np
import pandas as pd

np.random.seed(123)
e = np.random.randn(100000,3)  
df=pd.DataFrame(e, columns=['a','b','c'])

df['x'] = df.index
df_melt = pd.melt(df, id_vars="x", value_vars=df.columns[:-1])
fig=px.line(df_melt, x="x", y="value",color="variable")
fig.show()

(For my ultimate purposes, the time series will be larger--likely 40 to 70 time series in 900K+ time points.)

This creates a graph with which I can interact using plotly.express features like zooming, panning, rectangle selection, etc.

Is there a way I can augment this so that the initial plot shows merely the first 500 time points and a scroll bar permits me to investigate what happens as time increases?

Using Mac OS 10.15.4 and Python 3.7 with IDLE. I wish to create this in IDLE and not in a Jupyter notebook environment.

Answer 1

The easiest way is to add the following to your setup:

fig.update_layout(xaxis=dict(rangeslider=dict(visible=True),
                             type="linear"))

And you'll get:

This will enable you to both subset and pan the original figure:

Complete code:

import plotly.express as px
import numpy as np
import pandas as pd

np.random.seed(123)
e = np.random.randn(100000,3)  
df=pd.DataFrame(e, columns=['a','b','c'])

df['x'] = df.index
df_melt = pd.melt(df, id_vars="x", value_vars=df.columns[:-1])
fig=px.line(df_melt, x="x", y="value",color="variable")

# Add range slider
fig.update_layout(xaxis=dict(rangeslider=dict(visible=True),
                             type="linear")
)

fig.show()

Answer 2

Use plotly.graphing_objects to use plotly offline

You could also use plotly.graphing_objects as follows.

Quoting the following example from the official documentation .

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()