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Basic Containers and Functions

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%% Cell type:markdown id:3c2a4f39 tags:
# Basic Containers
Understanding and Using Basic Containers in Python
%% Cell type:markdown id:2b78245b tags:
![Google Python Symbol- Image found in the public domain](https://freesvg.org/img/387.png)
https://freesvg.org/img/387.png
Python Language Logo from Free SVG
%% Cell type:markdown id:71e867d9 tags:
## Description
Many times, in using python, there will be a need to store values. A common way to do so and store the values under a single variable is to use basic containers. This page will breakdown the common container types in Python.
%% Cell type:markdown id:58ec20e8 tags:
## Self Assessment
Click the following link to assess your knowledge on Basic Containers:
https://realpython.com/quizzes/pybasics-tuples-lists-dicts/
%% Cell type:markdown id:5d237ca9 tags:
## Training Materials
%% Cell type:markdown id:21f9b14e tags:
Video Description (URL Link to video)
%% Cell type:code id:deeec8f7 tags:
``` python
from IPython.display import YouTubeVideo
YouTubeVideo("aBqTgR-gP3g",width="100%", height=360, cc_load_policy=True)
```
%% Output
<IPython.lib.display.YouTubeVideo at 0x1cd12db60d0>
%% Cell type:raw id:08e8ef5c tags:
|Container Type|Mutable or Immutable|Initialization *Without* Values|Initializtion *With* Values|Adding Values to Container|Removing Values from Container|Modifying Values|Access Method|Notable Operations and Additional Information|
|---|---|---|---|---|---|---|---|---|
|**List**| Mutable |<ul><li>`a=list()` </li><li> `a=[]` </li></ul> | `a=['1', '2', '3']`| <ul><li>` list.append(item) #Adds item to the end of the list` </li><li> ` list.insert(index, item) #Adds item to the specified index in the list`</li></ul>|`list.remove(item) #removes the first instance of 'item' from the list. If there is not such element, this will cause an error`|`>>> a[0] = 'cat'` <br> `>>> a` <br> `['cat', '2', '3']` |Access by index: <br> `>>> a[0]` <br> `1`|See webpage at http://www.linuxtopia.org/online_books/programming_books/python_programming/python_ch14s07.html for some helpful methods when dealing with lists.|
|**Dictionary**|Mutable| `student={}` | `>>> student={'name': 'John Doe', 'age': 22, 'college': 'MSU'}` | `>>> student['major']='Computer Science'` <br> `>>> student` <br> `{'name': 'John Doe', 'age': 22, 'college': 'MSU', 'major': 'Computer Science'}` | `del dictName[keyName] #This method removes all entries associated with the given key` | `>>> student['age'] = 23` <br> `>>> student` <br> `{'name': 'John Doe', 'age': 23, 'college': 'MSU', 'major': 'Computer Science'}`| Access by key word. Note that this key **must** be a string. <br> `>>>student['college']` <br> `MSU`| The 'in' keyword can be very helpful with dictionaries. Ex: <br><ul><li>`'k' in dict #Returns true if key 'k' is in dictionary dict`</li><li>`'k' not in dict #Returns true if key 'k' is not in dicitonary dict`</li><li>`for key in dict #This will iterate over all keys in dictionary dict`</li></ul> <br>See webpage at http://www.python-course.eu/python3_dictionaries.php for additional helpful methods and operations|
|**Set**|Mutable. However the objects contained within a set **must** be immutable. | `s=set()`|`s=set(['a','b','c'])` | `s.add(item)`|<ul><li> `set.discard(item) #If item is in the set, the item is removed, otherwise nothing happens` </li><li> `set.remove(item) #If item is in the set, the item is removed, otherwise raise a KeyError` </li><li> `set.pop() #Remove and return an arbitrary element from the set. If the set is empty, raise a KeyError` </li>| Sets are unordered, therefore indexing does not mean anything. To modify a set, you must directly add or remove elements. |`>>> set.pop() #This will remove and return an arbitrary element from the set`|Some helpful methods include:<ul><li>`difference()`</li><li>`intersection()`</li><li>`isdisjoint()`</li><li>`union()`</li></ul><br> See webpage at http://www.programiz.com/python-programming/set for additional helpful methods and operations|
| **Tuple** |Immutable|<ul><li>`t=()`</li><li> `t=tuple()`</li><ul>|<ul><li>1-tuple:<br>`t=('Hello',)`</li><li> 2-tuple:<br> `t=('Hello', 'Goodbye')`</li><ul>|N/A|N/A|N/A|`t=('Hello','Goodbye','Goodnight')`<ul><li>Access By Index: <br> `>>> t[0]` <br> `'Hello'` </li><br><li> Access By Slice <br> `>>>t[0:1:2]` <br> `('Hello','Goodbye')`</li></ul>|<ul><li>Packing and Unpacking</li><br><li>Tuple to List: `list(tupleName)`</li></ul>|
| **NumPy Array\***|Mutable|`a=np.array([])`| `a=np.array([1,2,3,4,5])` | <ul><li>`np.insert(arrayName,index,values,axis) #Inserts a value for an array at the given index.` </li><li>`np.append(arrayName,value,axis) #Appends values to the end of an array.`</li></ul>|`np.array(array,index/indices,axis) #Returns a new array with the given index or array of indices deleted on the given axis`|`>>> a[4] = 12` <br> `array([ 1, 2, 3, 4, 12])` <br><br> For additional information on manipulating NumPy Arrays see the webpage at http://docs.scipy.org/doc/numpy/reference/routines.array-manipulation.html |<ul><li>Access By Index: <br> `>>> a[0] `<br>` 1 `</li><li>Access By Slice: <br> `>>> a[0:5:2] `<br> `array([1, 3, 5])` </li></ul><br>See webpage at http://docs.scipy.org/doc/numpy/reference/arrays.indexing.html for further information about indexing of NumPy Arrays|See webpages at http://www.scipy-lectures.org/intro/numpy/array_object.html and https://docs.scipy.org/doc/numpy-dev/user/quickstart.html for additional information on NumPy Arrays|
\*Use of the NumPy Array requires the NumPy Python Module. Assuming import statement is "import numpy as np"
%% Cell type:markdown id:8bdbe577 tags:
List – a data structure in Python that is a mutable ordered sequence of elements.
my_list = [1, “world”, 5.9]
Dictionary – a mutable data storage method which is used to store data values in key : value pairs.
my_dict = {‘msu’: 1, ‘spartans’ : ‘green’, “mcdonel’ : ‘hall’}
Tuple – used to store multiple items in a single variable.
my_tuple = (“apple”. “bananas”, “cherry”, “strawberry”)
NumPy Array – a grid of values, all of the same type, and is indexed by a tuple of nonnegative integers.
import numpy as np
arr = np.array(1, 2, 3, 4, 5, 6)
print(arr)
output: [1, 2, 3, 4, 5, 6]
Array – a collection of items stored at contiguous memory locations. Values can be accessed by referring to an index number.
cars = [“bmw”, “jeep”, “toyota”, “kia”]
Map – a built-in function that allows the user to process and transform all the items in a container in an iterable(such as a list or dictionary without using a loop.
# Return double of n
def addition(n):
return n + n
# We double all numbers using map()
numbers = (1, 2, 3, 4)
result = map(addition, numbers)
print(list(result))
output: [2, 4, 6, 8]
%% Cell type:markdown id:44b461a0 tags:
---
Written by Suliah Apatira, Michigan State University
As part of the Data Science Bridge Project
<a rel="license" href="http://creativecommons.org/licenses/by-nc/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc/4.0/">Creative Commons Attribution-NonCommercial 4.0 International License</a>.
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