Here's my solution:
In order to set the proper options for the dropdown menu, it would be helpful to have a function that creates the list of options (shown below)
# Create proper buttons list
def makeButtonsList(idxs):
buttons = []
for i, idx in enumerate(idxs):
visibleArr = np.full((2*df.index.shape[0],),
False, dtype=bool) # 2x number of booleans since one/two vals are separate plots
visibleArr[2*i] = True # Set two booleans next to each other (representing one & two) to true
visibleArr[(2*i)+1] = True
buttons.append(dict(label=str(idx),
method='update',
args=[{'visible': list(visibleArr)}])) # 'Visible' arg determines which plots are shown
# depending on which dropdown is selected
return buttons
Next create the traces for the data (with your sample data, I created a bar chart but you could easily modify this)
traces = []
for i in range(df.Time.shape[0]):
rowData = df.iloc[i, :]
time = rowData.Time
one = rowData.one
two = rowData.two
traces.append(go.Bar(x=[time], y=[one], name='One'))
traces.append(go.Bar(x=[time], y=[two], name='Two'))
where df
is the dataframe you are working with.
Finally put it all together and create the Plotly plot!
# Import packages
import pandas as pd
import numpy as np
import plotly.graph_objs as go
import plotly.express as px
# Create proper buttons list
def makeButtonsList(idxs):
buttons = []
for i, idx in enumerate(idxs):
visibleArr = np.full((2*df.index.shape[0],),
False, dtype=bool) # 2x number of booleans since one/two vals are separate plots
visibleArr[2*i] = True # Set two booleans next to each other (representing one & two) to true
visibleArr[(2*i)+1] = True
buttons.append(dict(label=str(idx),
method='update',
args=[{'visible': list(visibleArr)}])) # 'Visible' arg determines which plots are shown
# depending on which dropdown is selected
return buttons
# Create traces
traces = []
for i in range(df.Time.shape[0]):
rowData = df.iloc[i, :]
time = rowData.Time
one = rowData.one
two = rowData.two
traces.append(go.Bar(x=[time], y=[one], name='One'))
traces.append(go.Bar(x=[time], y=[two], name='Two'))
# Create figure
fig = go.Figure(data=traces)
# Add dropdown options
fig.update_layout(
updatemenus=[
dict(
buttons=makeButtonsList(df.index),
direction="down",
pad={"r": 10, "t": 10},
showactive=True,
x=0.55,
xanchor="left",
y=1.2,
yanchor="top"
),
]
)
# Add annotation for index selected
fig.update_layout(
annotations=[
dict(text="Index:", showarrow=False,
x=0, y=1.15, yref="paper", align="left")
],
xaxis_title = 'Time',
yaxis_title = 'Value',
)
# Show the plot
fig.show()
Here is a sample plot:
BONUS:
If you think this method is tedious, and a slider bar would do the job just fine, Plotly supports animation of bar charts. Here is the following code you could use:
fig = px.bar(df, x='Time', y=['one','two'], animation_frame=df.index)
fig.update_layout(title='Data', barmode='group')
fig.show()
Here is the resulting plot: