Python Basics – Hayden Mikula

Values, Variables, and Types

A ‘value’ in Python is any amount of data, no matter what type

Examples of values:

10 #Integer
'Hello' # String
5.71 # Float
True # Bool

When these values are assigned to a data container, they become ‘variables’

Variables are capable of storing one or more values for use in data collection, transformation, etc.

a = 10 # 'a' is the name of the variable
print(a)
example_list = [20, 9, True, 'string']

Data Frames

A ‘data.frame’ is a format of data structure that stores data using observations (rows) and variables (columns). Each individual value corresponds to a ‘cell’, which has meaning based on its associated row index and variable.

Example:

import pandas as pd
nba = pd.read_csv("https://bcdanl.github.io/data/nba.csv")
nba

	Name	Team	Position	Birthday	Salary
0	Shake Milton	Philadelphia 76ers	SG	9/26/96	1445697
1	Christian Wood	Detroit Pistons	PF	9/27/95	1645357
2	PJ Washington	Charlotte Hornets	PF	8/23/98	3831840
3	Derrick Rose	Detroit Pistons	PG	10/4/88	7317074
4	Marial Shayok	Philadelphia 76ers	G	7/26/95	79568
...	...	...	...	...	...
445	Austin Rivers	Houston Rockets	PG	8/1/92	2174310
446	Harry Giles	Sacramento Kings	PF	4/22/98	2578800
447	Robin Lopez	Milwaukee Bucks	C	4/1/88	4767000
448	Collin Sexton	Cleveland Cavaliers	PG	1/4/99	4764960
449	Ricky Rubio	Phoenix Suns	PG	10/21/90	16200000

450 rows × 5 columns

Lists, Dictionaries, and Slicing

As previously shown, a ‘list’ is a data container that works in a singlular series of data (i.e. A single row of values). The values in a list are able to be gathered with [] (see below):

example_list

[20, 9, True, 'string']

example_list[0] # Produces the FIRST value in the list, because Python begins counting at 0 instead of 1

A ‘dictionary’, in comparison, is a list that utilizes a key-value pair to identify values rather than a numerical index:

example_dict = {'a' : 10, 'b' : 14, 'c' : 'Hello'}
  #example_dict[1] would not work, because dictionaries do not have numerical indexes

print(example_dict.keys())
print(example_dict.values())

example_dict['b']

dict_keys(['a', 'b', 'c'])
dict_values([10, 14, 'Hello'])

Strings and Lists can be ‘sliced’ with []

For strings, their characters are sliced
For lists, their individual values are sliced

Kinds of slicing:

[ _ :]
- Slices from the indicated position to the end
[ : _ ]
- Slices from the beginning to the indicated position
[ _ : _ ]
- Slices from the (left) indicated position to the (right) indicated position
  - Can add an additional ’: _’ at the end of any of these slicing methods to indicate the ‘step’ of the slicing (eg. A step of ‘2’ = every other value).

eg_string = "Hello, I am a string."
print(eg_string[4]) # 5th character, starting at 0

print(example_list[-1]) # Last item in the list

print(eg_string[3:13]) # Characters starting at position 3 and ending at position 13

o
string
lo, I am a

Operators

Python includes symbols that work as operations that act on data, including:

‘+’ for addition
‘-’ for subtraction
’*’ for multiplication
‘/’ for division
’**’ for exponents
‘//’ for integer division

These operations work on most data types, though some work better than others. For example:

string_1 = "My name is"
string_2 = "Steven"
print(string_1 + " " + string_2)
  #string_1 - string_2 would not work; subtraction is not supported by strings
print((string_2 + ' ') * 4)

My name is Steven
Steven Steven Steven Steven

Value Conversion

We are able to alter a value’s ‘type’ with built-in Python functions, such as:

int()
float()
str()
bool()

eg_int = int(29.75)
eg_float = float(10)
eg_str = str(92)
eg_bool = bool(0)

print(eg_int)
print(eg_float)
print(eg_str)
print(eg_bool)

29
10.0
92
False

Boolean Conditions

Boolean conditions are operations which result in a boolean ‘True’ or ‘False’ value, and are used to either filter the data we are looking at or proceed with an action based on the True/False value of the condition.

print(10 == 20) # False
print(20 == '20') # False

False
False

Kinds of conditions (using x/y as placeholders for data):

x and y
- “Are both x and y True?”
x or y
- “Is either x or y True?”
not x
- “Is x False?”
x in y
- “Does x exist within y?”
x == y
- “Is x equal to y?”
x != y
- “Is x not equal to y?”
x > y
- “Is x greater than y?”
x >= y
- “Is x greater than or equal to y?”
x < y
- “Is x less than y?”
x <= y
- “Is x less than or equal to y?”

‘if’ statements are lines of code that run when the outlined condition is met

num = 20
if num == 20:
  print('That is correct!')

That is correct!

‘else’ statements are lines of code that are run when the outlined condition of an ‘if’ statement is NOT met

num = 15
if num == 20:
  print('That is correct!')
else:
  print('That is incorrect...')

That is incorrect...

‘elif’ statements are lines of code that are run when the previous ‘if’ or ‘elif’ condition is not met

num = 0
if num == 20:
  print('That is correct!')
elif 18 <= num < 20:
  print("You're getting closer.")
elif num > 20:
  print('Too far!')
else:
  print("Too low!")

Too low!

While and For loops

A ‘while’ loop carries out a set of instructions for as long as a certain condition is met
A ‘for’ loop iterates on a data container and carries out a set of instructions for as many times as the container is iterated
- ‘continue’ is used to skip to the end of the loop
- ‘break’ is used to stop the loop

count = 1
while count <= 5:
    print(count)
    count += 1

word = 'thud'
for letter in word:
    print(letter)

word = 'thud'
for letter in word:
    if letter == 'u':
        break # Ends the loop before it can finish fully
    print(letter)

t
h

word = 'thud'
for letter in word:
    if letter == 'u':
        continue # Skips over the print() function for 'u'
    print(letter)

t
h
d

List Comprehension

A way of creating or filtering list values using conditions

Syntax: listname_new = [ _ for _ in listname_old if ‘condition’ ]

numbers = list(range(1, 21))
print(numbers)

evens = [num for num in numbers if num % 2 == 0]
print(evens)

[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20]
[2, 4, 6, 8, 10, 12, 14, 16, 18, 20]

Dictionary Comprehension

A way of creating or filtering dictionary keys / values using conditions

Syntax: dictname_new = { k:v for k, v in dictname_old if ‘condition’ }

# Filtering
my_dict = {'a': 1, 'b': 2, 'c': 3, 'd': 4}
filtered_dict = {k: v for k, v in my_dict.items() if v != 2}
print(filtered_dict)

# Swapping Values
original_dict = {'a': 1, 'b': 2, 'c': 3}
swapped_dict = {v: k for k, v in original_dict.items()}
print(swapped_dict)

{'a': 1, 'c': 3, 'd': 4}
{1: 'a', 2: 'b', 3: 'c'}

List / Dictionary Modification

A method (.__) can be used to modify certain aspects of lists and dictionaries

Lists

list.append(): Add a new item to the end of the list
list. remove(): Remove the FIRST occurrence of the specified value
del list[]: Deletes a list’s values by index rather than value

Dictionaries:

dict.update({}): Add a new key-value pair or change an existing pair
del dict[]: Deletes a dictionary’s key-value pair based on the specified key

Try-Except

Try-Except code blocks tries to run a block of code, and if an error is raised from attempting to run that code, then an exception is raised instead that is specified by the user.

For example:

eg_list = [1, 2, 3, 4, 5, 6]
position = 9
try:
  print(eg_list[position])
except:
  print(f"Invalid position. Expected a value between 0 and {len(eg_list)-1} but got '{position}' instead.")

Invalid position. Expected a value between 0 and 5 but got '9' instead.