- A diurnal plot, which shows the date and time each email was sent (or received), with years running along the x axis and times of day on the y axis.
- And a daily distribution histogram, which represents the distribution of emails sent by time of day.
from imaplib import IMAP4_SSL
from datetime import date,timedelta,datetime
from time import mktime
from email.utils import parsedate
from pylab import plot_date,show,xticks,date2num
from pylab import figure,hist,num2date
from matplotlib.dates import DateFormatter
def getHeaders(address,password,folder,d):
""" retrieve the headers of the emails
from d days ago until now """
# imap connection
mail = IMAP4_SSL('imap.gmail.com')
mail.login(address,password)
mail.select(folder)
# retrieving the uids
interval = (date.today() - timedelta(d)).strftime("%d-%b-%Y")
result, data = mail.uid('search', None,
'(SENTSINCE {date})'.format(date=interval))
# retrieving the headers
result, data = mail.uid('fetch', data[0].replace(' ',','),
'(BODY[HEADER.FIELDS (DATE)])')
mail.close()
mail.logout()
return data
The second one, make us able to make the diurnal plot:
def diurnalPlot(headers):
""" diurnal plot of the emails,
with years running along the x axis
and times of day on the y axis.
"""
xday = []
ytime = []
for h in headers:
if len(h) > 1:
timestamp = mktime(parsedate(h[1][5:].replace('.',':')))
mailstamp = datetime.fromtimestamp(timestamp)
xday.append(mailstamp)
# Time the email is arrived
# Note that years, month and day are not important here.
y = datetime(2010,10,14,
mailstamp.hour, mailstamp.minute, mailstamp.second)
ytime.append(y)
plot_date(xday,ytime,'.',alpha=.7)
xticks(rotation=30)
return xday,ytime
And this is the function for the daily distribution histogram:
def dailyDistributioPlot(ytime):
""" draw the histogram of the daily distribution """
# converting dates to numbers
numtime = [date2num(t) for t in ytime]
# plotting the histogram
ax = figure().gca()
_, _, patches = hist(numtime, bins=24,alpha=.5)
# adding the labels for the x axis
tks = [num2date(p.get_x()) for p in patches]
xticks(tks,rotation=75)
# formatting the dates on the x axis
ax.xaxis.set_major_formatter(DateFormatter('%H:%M'))
Now we got everything we need to make the graphs. Let's try to analyze the outgoing mails of last 5 years:
print 'Fetching emails...'
headers = getHeaders('[email protected]',
'ofcourseiamsupersexy','inbox',365*5)
print 'Plotting some statistics...'
xday,ytime = diurnalPlot(headers)
dailyDistributioPlot(ytime)
print len(xday),'Emails analysed.'
show()
The result would appear as follows
We can analyze the outgoing mails just using selecting the folder '[Gmail]/Sent Mail':
print 'Fetching emails...'
headers = getHeaders('[email protected]',
'ofcourseiamsupersexy','[Gmail]/Sent Mail',365*5)
print 'Plotting some statistics...'
xday,ytime = diurnalPlot(headers)
dailyDistributioPlot(ytime)
print len(xday),'Emails analysed.'
show()
And this is the result:
