IntroductionToCourse.ipynb

Kernel: Python 3

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The Python Programming Language: Functions

x = 1
y = 2
x + y

3

y

2

`add_numbers` is a function that takes two numbers and adds them together.

def add_numbers(x, y):
    return x + y

add_numbers(1, 2)

3

'add_numbers' updated to take an optional 3rd parameter. Using `print` allows printing of multiple expressions within a single cell.

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))

3
6

`add_numbers` updated to take an optional flag parameter.

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))

Flag is true!
3

Assign function `add_numbers` to variable `a`.

def add_numbers(x,y):
    return x+y

a = add_numbers
a(1,2)

3

The Python Programming Language: Types and Sequences

Use `type` to return the object's type.

type('This is a string')

str

type(None)

NoneType

type(1)

int

type(1.0)

float

type(add_numbers)

function

Tuples are an immutable data structure (cannot be altered).

x = (1, 'a', 2, 'b')
type(x)

tuple

Lists are a mutable data structure.

x = [1, 'a', 2, 'b']
type(x)

list

Use `append` to append an object to a list.

x.append(3.3)
print(x)

[1, 'a', 2, 'b', 3.3]

This is an example of how to loop through each item in the list.

for item in x:
    print(item)

1
a
2
b
3.3

Or using the indexing operator:

i=0
while( i != len(x) ):
    print(x[i])
    i = i + 1

1
a
2
b
3.3

Use `+` to concatenate lists.

[1,2] + [3,4]

[1, 2, 3, 4]

Use `*` to repeat lists.

[1]*3

[1, 1, 1]

Use the `in` operator to check if something is inside a list.

1 in [1, 2, 3]

True

Now let's look at strings. Use bracket notation to slice a string.

x = 'This is a string'
print(x[0]) #first character
print(x[0:1]) #first character, but we have explicitly set the end character
print(x[0:2]) #first two characters

T
T
Th

This will return the last element of the string.

x[-1]

'g'

This will return the slice starting from the 4th element from the end and stopping before the 2nd element from the end.

x[-4:-2]

'ri'

This is a slice from the beginning of the string and stopping before the 3rd element.

x[:3]

'Thi'

And this is a slice starting from the 4th element of the string and going all the way to the end.

x[3:]

's is a string'

firstname = 'Christopher'
lastname = 'Brooks'

print(firstname + ' ' + lastname)
print(firstname*3)
print('Chris' in firstname)

Christopher Brooks
ChristopherChristopherChristopher
True

`split` returns a list of all the words in a string, or a list split on a specific character.

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)

Christopher
Brooks

Make sure you convert objects to strings before concatenating.

'Chris' + 2

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-27-9d01956b24db> in <module>
----> 1 'Chris' + 2

TypeError: can only concatenate str (not "int") to str

'Chris' + str(2)

Dictionaries associate keys with values.

x = {'Christopher Brooks': '[email protected]', 'Bill Gates': '[email protected]'}
x['Christopher Brooks'] # Retrieve a value by using the indexing operator

x['Kevyn Collins-Thompson'] = None
x['Kevyn Collins-Thompson']

Iterate over all of the keys:

for name in x:
    print(x[name])

Iterate over all of the values:

for email in x.values():
    print(email)

Iterate over all of the items in the list:

for name, email in x.items():
    print(name)
    print(email)

You can unpack a sequence into different variables:

x = ('Christopher', 'Brooks', '[email protected]')
fname, lname, email = x

fname

lname

Make sure the number of values you are unpacking matches the number of variables being assigned.

x = ('Christopher', 'Brooks', '[email protected]', 'Ann Arbor')
fname, lname, email = x

The Python Programming Language: More on Strings

print('Chris' + 2)

print('Chris' + str(2))

Python has a built in method for convenient string formatting.

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_record['num_items']*sales_record['price']))

Reading and Writing CSV files

Let's import our datafile mpg.csv, which contains fuel economy data for 234 cars.

• mpg : miles per gallon

• class : car classification

• cty : city mpg

• cyl : # of cylinders

• displ : engine displacement in liters

• drv : f = front-wheel drive, r = rear wheel drive, 4 = 4wd

• fl : fuel (e = ethanol E85, d = diesel, r = regular, p = premium, c = CNG)

• hwy : highway mpg

• manufacturer : automobile manufacturer

• model : model of car

• trans : type of transmission

• year : model year

import csv

%precision 2

with open('mpg.csv') as csvfile:
    mpg = list(csv.DictReader(csvfile))
    
mpg[:3] # The first three dictionaries in our list.

`csv.Dictreader` has read in each row of our csv file as a dictionary. `len` shows that our list is comprised of 234 dictionaries.

len(mpg)

`keys` gives us the column names of our csv.

mpg[0].keys()

This is how to find the average cty fuel economy across all cars. All values in the dictionaries are strings, so we need to convert to float.

sum(float(d['cty']) for d in mpg) / len(mpg)

Similarly this is how to find the average hwy fuel economy across all cars.

sum(float(d['hwy']) for d in mpg) / len(mpg)

Use `set` to return the unique values for the number of cylinders the cars in our dataset have.

cylinders = set(d['cyl'] for d in mpg)
cylinders

Here's a more complex example where we are grouping the cars by number of cylinder, and finding the average cty mpg for each group.

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

Use `set` to return the unique values for the class types in our dataset.

vehicleclass = set(d['class'] for d in mpg) # what are the class types
vehicleclass

And here's an example of how to find the average hwy mpg for each class of vehicle in our dataset.

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

The Python Programming Language: Dates and Times

import datetime as dt
import time as tm

`time` returns the current time in seconds since the Epoch. (January 1st, 1970)

tm.time()

Convert the timestamp to datetime.

dtnow = dt.datetime.fromtimestamp(tm.time())
dtnow

Handy datetime attributes:

dtnow.year, dtnow.month, dtnow.day, dtnow.hour, dtnow.minute, dtnow.second # get year, month, day, etc.from a datetime

`timedelta` is a duration expressing the difference between two dates.

delta = dt.timedelta(days = 100) # create a timedelta of 100 days
delta

`date.today` returns the current local date.

today = dt.date.today()

today - delta # the date 100 days ago

today > today-delta # compare dates

The Python Programming Language: Objects and map()

An example of a class in python:

class Person:
    department = 'School of Information' #a class variable

    def set_name(self, new_name): #a method
        self.name = new_name
    def set_location(self, new_location):
        self.location = new_location

person = Person()
person.set_name('Christopher Brooks')
person.set_location('Ann Arbor, MI, USA')
print('{} live in {} and works in the department {}'.format(person.name, person.location, person.department))

Here's an example of mapping the `min` function between two lists.

store1 = [10.00, 11.00, 12.34, 2.34]
store2 = [9.00, 11.10, 12.34, 2.01]
cheapest = map(min, store1, store2)
cheapest

Now let's iterate through the map object to see the values.

for item in cheapest:
    print(item)

The Python Programming Language: Lambda and List Comprehensions

Here's an example of lambda that takes in three parameters and adds the first two.

my_function = lambda a, b, c : a + b

my_function(1, 2, 3)

Let's iterate from 0 to 999 and return the even numbers.

my_list = []
for number in range(0, 1000):
    if number % 2 == 0:
        my_list.append(number)
my_list

Now the same thing but with list comprehension.

my_list = [number for number in range(0,1000) if number % 2 == 0]
my_list