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A very quick and simple introduction to Python (part 1)

Hello and welcome to part 1 of the quick Python overview! This is a very basic tutorial that will quickly allow you to learn enough Python to attend the Intro to ML with Scikit-learn workshop. For the purpose of this tutorial, you do not have to install Python. You can do all of the exercises in the Online Python shell).

If you run into any trouble or you find that a concept is wrong or poorly explained, please do not hesitate to contact me at camillamon[at] I’ll try to get back to you as soon as I can! There is also a list of alternative Python resources at the end of this tutorial.

##1. Python and Objects One of the cornerstones of machine learning is (you guessed it!) manipulating data. In Python, data is manipulated using objects such as numbers, strings, lists and dictionaries. Some of these objects are built-in, others come from external libraries. You can also define your own objects.

###1.0 Examples of built-in Python Objects


"hello world"



my_nonempty_dictionary={'song':"Etude 9",

###1.1 Assigning names to objects Suppose we have a program that prints “hello world” several times. We could simply type “hello world” every time we want to print it.

print "hello world"
#do something else
print "hello world"
#do something else
print "hello world"

Instead of typing “hello world” every time, we can assign a name to “hello world”. In Python, assigning a name to an object is done using the “=” symbol. We can then rewrite the little program from above as follows

hello_string="hello world"
print hello_string
#do something else
print hello_string
#do something else
print hello_string

Giving an object a name and then referring to the object by a name will make it very easy for us to change the program. Suppose that instead of “hello world”, we want to print “hello everyone”. In the first version of this program, we would have to change every instance of “hello world” (tedious and you might miss some and break your program), but in the second version we have to change the string only once.

You can assign names to any object types (number, list, string etc.)

#basic examples with strings, numbers and dicts
title="Do Androids Dream of Electric Sheep"
my_favorite_books={'Donna Tart':'The Goldfinch',
                    'Sylvia Plath':'The Bell Jar'}

####A Brief Note on Variable Names It is good practice to give you variables descriptive names. This will save you from having a ‘WTF is this thing here’ moment when you come back to your code several weeks or months later. Python is quite relaxed about variable naming rules, but there are a few NO-NOs:

  1. Do not start a variables with numbers
  2. Do not use one of Python’s reserved keywords as a variable name
  3. Do not use symbols such as ‘@’in variable names


  1. Create a string object with the name of your favorite novel and assign it to a variable with a descriptive name
  2. Create a list with some of your favorite numbers and give it the name my_favorite_numbers
  3. Create a dictionary using whatever keys and value you prefer

###1.3 String operations In the machine learning workshop, we will manipulate textual data. Thus it is a good idea to go over some very basic string operations, which are built into Python.

#how do I create a string?

#how do I find out the length of a string?

#how do I obtain the first letter of a string (or nucleotide for the biologists among us!)
dna[0]   #note indexing starts at zero

#how do I obtain the last letter of a string?

dna[len(dna)-1]  #QUIZ: would the command dna[len(dna)] work? Why or why not?

# how do I obtain a substring? (also known as slicing)
#QUIZ: what does the operation dna[-2] return?


  1. Create a string in the Online Python interpreter(or your own interactive Python session) and give it a descriptive name (eg. my_string for those of us lacking imagination :D)
  2. Obtain the first 4 characters of my_string
  3. Find out the length of my_string
  4. Create a string object with the value “hello world” by concatenating two string objects, “hello” and “world”.

###1.4 Basic list operations and methods Lists allow us to store a group of related objects (strings, numbers etc) together.

#how do I create a list?
favorite_ice_cream=["vanilla", "chocolate", "strawberry"]
prices=[12, 56, 78]

#how do I access an element in the list?

#how do I find out the numbers of elements in a list?

#how do I concatenate two lists?
#['vanilla', 'chocolate', 'strawberry', 12, 56, 78]

# as we can see from above,
#Python allows you to have lists with objects of different types (ie. numbers and strings)

In addition to the basic operations illustrated above, lists come with several predefined methods.

#how do I add an element to the end of a list?
favorite_ice_cream.append("cherry garcia")

#how do I delete an item at position n (where n is the index of the element you want to delete)?
#['chocolate', 'strawberry', 'cherry garcia']
#the object 'vanilla' was deleted from the list


  1. Create a list with your favorite desserts and give it a meaningful name
  2. Print the length of my_random_list given by the expression

Find out more about the range() function by navigating to the Python docs page.

###1.5 Basic dictionary operations and methods Sometimes we want to associate particular keys with values. For example, a company may want to store some basic information about its employees.

#how do I create a dict object?
          'name':'Jane Doe',
#how do I access the value associated with a key?
#'Jane Doe'

#how do I obtain a list of all keys?
#['department', 'salary', 'name']

#how do I add another key-value pair?

#check that the new key has been added by printing the keys
#['department', 'salary', 'programming_language', 'name']

#note that the keys may be returned in a different order


  1. Create a dict object for employee with the name “John Smith”
  2. Populate it with key-value pairs of your choice

##Other resources for learning Python