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Graph Gmail Inbox Data in Python/v3

Learn how to graph your Gmail inbox data with plotly and IPython Notebook

Note: this page is part of the documentation for version 3 of Plotly.py, which is not the most recent version.
See our Version 4 Migration Guide for information about how to upgrade.
In [31]:
from IPython.display import Image
Image('http://i.imgur.com/SYija2N.png')
Out[31]:

Installations

Download your Gmail inbox as a ".mbox" file by clicking on "Account" under your Gmail user menu, then "Download data". Install the Python libraries mailbox and dateutils with sudo pip install mailbox and sudo pip install dateutils.

In [12]:
import plotly.plotly as py
import plotly.graph_objs as go

import mailbox
from email.utils import parsedate
from dateutil.parser import parse
import itertools
In [13]:
path = '/Users/jack/Desktop/All mail Including Spam and Trash.mbox'

Open your ".mbox" file with mailbox

In [22]:
mbox = mailbox.mbox(path)

Sort your mailbox by date

In [23]:
def extract_date(email):
    date = email.get('Date')
    return parsedate(date)

sorted_mails = sorted(mbox, key=extract_date)
mbox.update(enumerate(sorted_mails))
mbox.flush()

Organize dates of email receipt as a list

In [24]:
all_dates = []
mbox = mailbox.mbox(path)
for message in mbox:
    all_dates.append( str( parse( message['date'] ) ).split(' ')[0] )

Count and graph emails received per day

In [26]:
email_count = [(g[0], len(list(g[1]))) for g in itertools.groupby(all_dates)]
email_count[0]
Out[26]:
('2013-11-05', 1)
In [28]:
x = []
y = []
for date, count in email_count:
    x.append(date)
    y.append(count)

py.iplot( [ go.Scatter( x=x, y=y ) ] )
Out[28]:
Restyle the chart in Plotly's GUI
In [10]:
import plotly.tools as tls
tls.embed('https://plot.ly/~jackp/3266')
Out[10]: