Difference between revisions of "Python functions"

def add_numbers(x,y,z=None):
    if (z==None):
        return x+y
    else:
        return x+y+z
 
print(add_numbers(1, 2))
print(add_numbers(1, 2, 3))

def add_numbers(x, y, z=None, flag=False):
    if (flag):
        print('Flag is true!')
    if (z==None):
        return x + y
    else:
        return x + y + z
 
print(add_numbers(1, 2, flag=True))

def add_numbers(x,y):
    return x+y
 
a = add_numbers
a(1,2)

type('This is a string')
type(None)
type(1)
type(1.0)
type(add_numbers)
 
x = (1, 'a', 2, 'b')
type x     tuples are immutable wheras lists are mutable
x = [1, 'a', 2, 'b']   list
x.append(3.3)
 
for item in x:
   print(item)
OR
i=0
while( i != len(x) ):
    print(x[i])
    i = i + 1
 
[1,2] + [3,4]
 
[1]*3
 
1 in [1, 2, 3]
 
x[-4:-2]
 
firstname = 'Christopher'
lastname = 'Brooks'
 
print(firstname + ' ' + lastname)
print(firstname*3)
print('Chris' in firstname)
 
firstname = 'Christopher Arthur Hansen Brooks'.split(' ')[0] # [0] selects the first element of the list
lastname = 'Christopher Arthur Hansen Brooks'.split(' ')[-1] # [-1] selects the last element of the list
print(firstname)
print(lastname)
 
'Chris' + 2
'Chris' + str(2)
 
x = {'Christopher Brooks': 'brooksch@umich.edu', 'Bill Gates': 'billg@microsoft.com'}
x['Christopher Brooks'] # Retrieve a value by using the indexing operator
 
x['Kevyn Collins-Thompson'] = None
x['Kevyn Collins-Thompson']
 
for name in x:
    print(x[name])
 
for email in x.values():
    print(email)
 
for name, email in x.items():
    print(name)
    print(email)
 
x = ('Christopher', 'Brooks', 'brooksch@umich.edu')
fname, lname, email = x
 
x = ('Christopher', 'Brooks', 'brooksch@umich.edu', 'Ann Arbor')
fname, lname, email = x
 
more on strings
 
sales_record = {
'price': 3.24,
'num_items': 4,
'person': 'Chris'}
 
sales_statement = '{} bought {} item(s) at a price of {} each for a total of {}'
 
print(sales_statement.format(sales_record['person'],
                             sales_record['num_items'],
                             sales_record['price'],
                             sales_r

import csv
 
%precision 2
 
with open('mpg.csv') as csvfile:
    mpg = list(csv.DictReader(csvfile))
 
mpg[:3] # The first three dictionaries in our list.
==
len(mpg)
==
mpg[0].keys()
==
sum(float(d['cty']) for d in mpg) / len(mpg)
==
sum(float(d['hwy']) for d in mpg) / len(mpg)
==
 
cylinders = set(d['cyl'] for d in mpg)
cylinders
 
==
CtyMpgByCyl = []
 
for c in cylinders: # iterate over all the cylinder levels
    summpg = 0
    cyltypecount = 0
    for d in mpg: # iterate over all dictionaries
        if d['cyl'] == c: # if the cylinder level type matches,
            summpg += float(d['cty']) # add the cty mpg
            cyltypecount += 1 # increment the count
    CtyMpgByCyl.append((c, summpg / cyltypecount)) # append the tuple ('cylinder', 'avg mpg')
 
CtyMpgByCyl.sort(key=lambda x: x[0])
CtyMpgByCyl
 
==
vehicleclass = set(d['class'] for d in mpg) # what are the class types
vehicleclass
 
===
 
HwyMpgByClass = []
 
for t in vehicleclass: # iterate over all the vehicle classes
    summpg = 0
    vclasscount = 0
    for d in mpg: # iterate over all dictionaries
        if d['class'] == t: # if the cylinder amount type matches,
            summpg += float(d['hwy']) # add the hwy mpg
            vclasscount += 1 # increment the count
    HwyMpgByClass.append((t, summpg / vclasscount)) # append the tuple ('class', 'avg mpg')
 
HwyMpgByClass.sort(key=lambda x: x[1])
HwyMpgByClass

import datetime as dt
import time as tm
 
tm.time()
 
==
dtnow = dt.datetime.fromtimestamp(tm.time())
dtnow
==
 
dtnow.year, dtnow.month, dtnow.day, dtnow.hour, dtnow.minute, dtnow.second # get year, month, day, etc.from a datetime
 
==
 
delta = dt.timedelta(days = 100) # create a timedelta of 100 days
delta
 
==
today = dt.date.today()
today - delta # the date 100 days ago
today > today-delta # compare dates