Plotly: Change y-axis scale

Often times we use data which is in different scales, and scaling the data would mask a characteristic we wish to display. One way to handle this is to add a secondary y-axis. An example is shown below.

Key points:

• Create a layout dictionary object
• Add a yaxis2 key to the dict, with the following: 'side': 'right', 'overlaying': 'y1'
  • This tells Plotly to create a secondary y-axis on the right side of the graph, and to overlay the primary y-axis.
• Assign the appropriate trace to the newly created secondary y-axis as: 'yaxis': 'y2'
  • The other trace does not need to be assigned, as 'y1' is the default y-axis.

Comments (TL;DR):
The example code shown here uses the lower-level Plotly API, rather than a convenience wrapper such as graph_object to express. The reason is that I (personally) feel it's helpful to users to show what is occurring 'under the hood', rather than masking the underlying code logic with a convenience wrapper.

This way, when the user needs to modify a finer detail of the graph, they will have a better understanding of the lists and dicts which Plotly is constructing for the underlying graphing engine (orca).

The Docs:
Here is a link to the Plotly docs referencing multiple axes.

Example Code:

import pandas as pd
from plotly.offline import iplot

df = pd.DataFrame({'x': ['Jan', 'Feb'],
                   'y': [28446000, 43267700],
                   'z': [110489.0, 227900.0]})

layout = {'title': 'Secondary Y-Axis Demonstration',
          'legend': {'orientation': 'h'}}

traces = []
traces.append({'x': df['x'], 'y': df['y'], 'name': 'Y Values'})
traces.append({'x': df['x'], 'y': df['z'], 'name': 'Z Values', 'yaxis': 'y2'})


# Add config common to all traces.
for t in traces:
    t.update({'line': {'shape': 'spline'}})

layout['yaxis1'] = {'title': 'Y Values', 'range': [0, 50000000]}
layout['yaxis2'] = {'title': 'Z Values', 'side': 'right', 'overlaying': 'y1', 'range': [0, 400000]}


iplot({'data': traces, 'layout': layout})

Graph: