CS worbook 2

Question 1

.sort() vs sorted() difference

Answer 1

(ig) .sort() modifies the original list in place.
sorted() returns a new list and leaves the original unchanged.

Question 2

What uses .pop, what’s the default parameter do(.pop())

Answer 2

(ig) Parameter Values
Parameter Description
pos Optional. A number specifying the position of the element you want to remove, default value is -1, which returns the last item

Question 3

Can/explain if the index out bounds, and how do you know when the index is out of bounds, what happens with insert() and pop() method?

Answer 3

(ig) out of bounds: if index < 0 or index >= len(list)

we will get an IndexError for both methods.

Question 4

What method removes the first occurrence of the element with the specified value. What uses this?

Parameter Description
elmnt Required. Any type (string, number, list etc.) The element you want to remove

Answer 4

explain the remove() method? list.remove(elmnt). Explain the parameter?

Question 5

using what function to load the name.csv file as a list of lists and store the data in the variable by creating a variable like colors(x) =

Answer 5

process_csv(‘csv_name’)

colors = process_csv(‘colors.csv’)

print(colors)

[[‘\ufeffName’, ‘HEX’, ‘RGB’], [‘Alice Blue’, ‘#F0F8FF’, ‘rgb(239,247,255)’], [‘Antique White’, ‘#FAEBD7’, ‘rgb(249,234,214)’],

Question 6

Elaborate the csv files types, optional to give more? What is it?

Answer 6

(ig) Don’t have types for their values—everything is a string. It’s just a text file of comma-separated values.
Don’t have settings for font size or color
Don’t have multiple worksheets
Can’t specify cell widths and heights
Can’t have merged cells
Can’t have images or charts embedded in them

Question 7

you should always use what for reading and writing CSV files. Give reason?

Answer 7

(ig) you should always use the csv module for reading and writing CSV files. Since CSV files also have their own set of escape characters to allow commas and other characters to be included as part of the values. The split() method doesn’t handle these escape characters.

Question 8

To read data from a CSV file with the csv module, you need to do what?

Answer 8

you need to create a reader object. A reader object lets you iterate over lines in the CSV file
» import csv
➋&raquo_space;> exampleFile = open(‘example.csv’)
➌&raquo_space;> exampleReader = csv.reader(exampleFile)
➍&raquo_space;> exampleData = list(exampleReader)
➎&raquo_space;> exampleData

Note that you don’t pass a filename string directly to the csv.reader() function.

The most direct way to access the values in the reader object is to convert it to a plain Python list by passing it to list()

Question 9

For large CSV files, you’ll want to use what for reading data?

Answer 9

(ig) you’ll want to use the reader object in a for loop. This avoids loading the entire file into memory at once.

import csv
»> exampleFile = open(‘example.csv’)
»> exampleReader = csv.reader(exampleFile)
»> for row in exampleReader:
print(‘Row #’ + str(exampleReader.line_num) + ‘ ‘ + str(row))

Question 10

Difference between using extend() and + operator on list?

Answer 10

(ig) Instead of using the extend() method there’s an even easier way to concatenate two lists in Python. We can use the + operator:
The only difference between this and the extend() method is that the + operator creates a new list, while the extend() method modifies the original list.

Question 11

What do you use for shallow copy and deep copy and reason to use deep copy?

Answer 11

use copy.deepcopy(list_name) for deep copies:
use list_name.copy() for shallow copies
If you had a list of lists, you would need to use the copy.deepcopy() method to create a deep copy.

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example of deepcopy
import copy

original_list = [[1, 2], [3, 4]]

cloned_list = copy.deepcopy(original_list)

Question 12

(important) explain the relationship between the original list and the shallow copy?

Answer 12

(ig)The shallow copy itself does not directly modify the original.
Changes to nested (mutable) objects within a shallow copy do affect the original due to shared references.

However, because the shallow copy only copies references to nested objects (like sublists or dictionaries within the list), modifications to these nested objects in the shallow copy will reflect in the original list, and vice versa.

This won’t affect original because you are not directly affecting the elements

Question 13

How does nametuple work? How to get fields, elements nametuple?

Answer 13

Create a namedtuple called ‘Employee’ with fields ‘name’, ‘age’, and ‘position’
Employee = namedtuple(“Employee”, [“name”, “age”, “position”])
elements can be accessed both by index (like a tuple) and by name (like a dictionary).
Access fields by name instead of index, making code more readable.

look below for elaboration

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from collections import namedtuple

Define the namedtuple
Person = namedtuple(“Person”, [“name”, “age”, “city”])

Create instances of the namedtuple
person1 = Person(name=”Bob”, age=25, city=”New York”)
person2 = Person(name=”Jane”, age=32, city=”Los Angeles”)

Access the fields by name
print(person1.name) # Output: Bob
print(person2.city) # Output: Los Angeles

Access the fields by index
print(person1[1]) # Output: 25

Question 14

What should you know about modification of nametuple?

Answer 14

Like regular tuples, namedtuple instances are immutable, so you can’t modify their fields directly after creation.

Question 15

What do dictionary key have to be?

Answer 15

(ig) Dictionary keys have to be immutable types like strings, ints.

Question 16

What are the parameters with the open() function?

Answer 16

(ig)filename and mode
There are four different methods (modes) for opening a file:

“r” - Read - Default value. Opens a file for reading, error if the file does not exist

“a” - Append - Opens a file for appending, creates the file if it does not exist

“w” - Write - Opens a file for writing, creates the file if it does not exist

“x” - Create - Creates the specified file, returns an error if the file exists

Question 17

What are the 4 modes of the open function, don’t have to explain it?

Answer 17

(ig)”r” -read

“a” -append

“w” -write

“x” -create

Question 18

What does “r” do for the open function?

Answer 18

(ig) “r” - Read - Default value. Opens a file for reading, error if the file does not exist

Question 19

What does “w” do for the open function?

Answer 19

(ig)”w” - Write - Opens a file for writing, creates the file if it does not exist.

Question 20

Explain “w” for opening a file, and with existing files and if a file doesn’t exist and how about reading a file?

Answer 20

(ig) It opens the file for writing. If the file exists, it truncates (clears) its content. If the file doesn’t exist, Python creates a new, empty file. Reading from the file is not allowed in this mode.

Question 21

What is the syntax and describe parameters for list comprehension and give me an example? How does it affect the original list. Ways to write it?

Answer 21

(ig) newlist = [expression for item in iterable if condition == True]
The return value is a new list, leaving the old list unchanged.

The condition is like a filter that only accepts the items that valuate to True.
Example
Only accept items that are not “apple”:
newlist = [x for x in fruits if x != “apple”]

The condition is optional and can be omitted:
With no if statement:
newlist = [x for x in fruits]

You can use the range() function to create an iterable:
Accept only numbers lower than 5:
newlist = [x for x in range(10) if x < 5]

EX:
fruits = [“apple”, “banana”, “cherry”, “kiwi”, “mango”]
newlist = [x for x in fruits if x != “apple”]
print(newlist)
[‘banana’, ‘cherry’, ‘kiwi’, ‘mango’]

Question 22

What can you do with the expression in the list comprehension(newlist = [expression for item in iterable if condition == True]):

Answer 22

(ig)The expression is the current item in the iteration, but it is also the outcome, which you can manipulate before it ends up like a list item in the new list:
You can set the outcome to whatever you like:

fruits = [“apple”, “banana”, “cherry”, “kiwi”, “mango”]
newlist = [x.upper() for x in fruits]
print(newlist)
[‘APPLE’, ‘BANANA’, ‘CHERRY’, ‘KIWI’, ‘MANGO’]

More EX;
fruits = [“apple”, “banana”, “cherry”, “kiwi”, “mango”]
newlist = [‘hello’ for x in fruits]
print(newlist)
[‘hello’, ‘hello’, ‘hello’, ‘hello’, ‘hello’]

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fruits = [“apple”, “banana”, “cherry”, “kiwi”, “mango”]
newlist = [x if x != “banana” else “orange” for x in fruits]
print(newlist)
[‘apple’, ‘orange’, ‘cherry’, ‘kiwi’, ‘mango’]

Question 23

What’s the syntax for dictionaries comprehension?

Answer 23

(ig) {key:value for item in iterable if condition}

Like list comprhension you modify all components

fruits = [“blackberry”, “apple”, “banana”, “fig”, “blueberry”, “strawberry”]

{x:len(x) for x in fruits}

new_scores_dict = {x[0]:len(x[1]) for x in scores_dict.items()}
new_scores_dict

# A dictionary of everyone’s average score
{x[0]:sum(x[1])/len(x[1]) for x in scores_dict.items()}