Adding additional text to the hovertext label - python-3.x

Question

I've searched for some time now and I can't seem to find a related question. There are similar questions, but nothing that gets to the heart of what I am trying to do with the code I have.
I am trying to add additional text to the hovertext in plotly. Here is my code so far:
import pandas as pd
import numpy as np
from plotly.offline import *
init_notebook_mode(connected=True)
graph1 = merged.groupby(['study_arm', 'visit_label'])['mjsn'].mean().unstack('study_arm')
graph1.iplot(mode='lines+markers',
symbol=['diamond-open', 'square-open', 'circle-dot', 'hexagon-open'],
size=8, colorscale = 'dark2', yTitle='ytitle', xTitle='xtitle',
title='Title of Graph',
hoverformat = '.2f')
hv = merged.groupby(['study_arm', 'visit_label']).size()
print(hv)
Note: 'merged' is the dataframe and is shown in the sample data below.
The code above gives the following output (note: hovering over the timepoint gives some information for each trace, and I took a picture to show what that looks like).
My question is how can I get the subject count number from the table into the hovertext for each trace at each timepoint (preferably on the second line of the hovertext that looks like 'N=x', where x is the subject number from the table under the graph in the picture).
Here is a sample of the dummy dataset I used to create this graph and table:
subject_number visit_label mjsn study_arm
20001 Day 1 0 B
20001 Month 06 0.4 B
20001 Month 12 0.2 B
20003 Day 1 0 B
20003 Month 06 -0.9 B
20003 Month 12 -0.7 B
20005 Day 1 0 C
20005 Month 06 0.1 C
20005 Month 12 -0.1 C
20007 Day 1 0 D
20007 Month 06 0 D
20007 Month 12 -0.3 D
20008 Day 1 0 C
20008 Month 06 -0.3 C
20008 Month 12 -0.1 C
20010 Day 1 0 A
20010 Month 06 -0.6 A
20010 Month 12 -0.4 A

Answer 1

You want to set the text or hovertext element for each chart/trace. Both text and hovertext will work here. The reason you may need both can be seen here. You may also want to change the hoverinfo element. Your options are 'x', 'y', 'none', 'text', 'all'. Additional resources are: text and annotations, docs, and python example. In addition, to get the count of cases at a time period I took two different groupby operations and then concatenated them together.
Example using your dataframe:
import plotly.graph_objs as go
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
init_notebook_mode(connected=True)
import pandas as pd
df = pd.DataFrame({
'subject_number' : [20001, 20001, 20001, 20003, 20003, 20003, 20005, 20005,
20005, 20007, 20007, 20007, 20008, 20008, 20008, 20010, 20010, 20010],
'visit_label' : ['Day 1', 'Month 6', 'Month 12', 'Day 1', 'Month 6',
'Month 12', 'Day 1', 'Month 6', 'Month 12', 'Day 1', 'Month 6',
'Month 12', 'Day 1', 'Month 6', 'Month 12', 'Day 1', 'Month 6',
'Month 12'],
'mjsn':[0, 0.4, 0.2, 0, -0.9, -0.7, 0, 0.1, -0.1, 0, 0, -0.3, 0, -0.3, -0.1,
0, -0.6, -0.4],
'study_arm':['B', 'B', 'B', 'B', 'B', 'B', 'C', 'C', 'C', 'D', 'D', 'D',
'C', 'C', 'C', 'A', 'A', 'A']
})
grouped = df.groupby(['study_arm', 'visit_label'])
tmp1 = grouped.mean()["mjsn"]
tmp2 = grouped.count()["subject_number"]
output_df = pd.concat([tmp1, tmp2], axis = 1)
data = []
for study in output_df.index.get_level_values(0).unique():
trace = go.Scatter(
x = output_df.loc[study, :].index,
y = output_df.loc[study, "mjsn"],
hovertext= ["msjn:{0}<br>subject:{1}".format(x, int(y))
for x,y in zip(output_df.loc[study, "mjsn"],
output_df.loc[study, "subject_number"])],
mode = 'lines+markers',
hoverinfo = 'text'
)
data += [trace]
#
iplot(data)
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