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Lab 7: Part 3. Practice sorting lists of tuples
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# Lab 7: Part 3. Practice sorting lists of tuples
In your `lab07` folder, open the file called `babySorting.py`.
At the top of this file, there is a predefined variable called
`office` that is a list of tuples.
```py
office = [('Michael','Scott',45),
('Dwight','Schrute',50),
('Angela','Martin',25),
('Jim','Halpert',27),
('Pam','Beesly',25),
('Phyllis','Lapin',60)]
```
The following are short exercises that take a few lines of code, with a
definition for a key function plus a call to `sorted`. The goal is to get
you more comfortable with sorting before moving onto more complex data.
### Task 1a: Basic sorting
Run the file, and then, in the `babySorting.py` file under `Task 1a`,
write a line of code to print the `office` sorted by first name.
The printed list should have this same tuple order:
```py
[('Angela', 'Martin', 25), ('Dwight', 'Schrute', 50), ('Jim', 'Halpert', 27),
('Michael', 'Scott', 45), ('Pam', 'Beesly', 25), ('Phyllis', 'Lapin', 60)]
```
### Task 1b: Sort by last name
Under `Task 1b`, write code to sort the `office` by **last name**. Hint:
you will need to write a helper function that will return the relevant
part of the tuple.
The printed list should have this same tuple order:
```py
[('Pam', 'Beesly', 25), ('Jim', 'Halpert', 27), ('Phyllis', 'Lapin', 60),
('Angela', 'Martin', 25), ('Dwight', 'Schrute', 50), ('Michael', 'Scott', 45)]
```
### Task 1c: Reverse sort by last name
Under `Task 1c`, write one line of code to sort the `office` by last name
in **reverse** alphabetical order.
The printed list should have this same tuple order:
```py
[('Michael', 'Scott', 45), ('Dwight', 'Schrute', 50), ('Angela', 'Martin', 25),
('Phyllis', 'Lapin', 60), ('Jim', 'Halpert', 27), ('Pam', 'Beesly', 25)]
```
### Task 1d: Sort by more than one thing
Under `Task 1d`, sort the `office` first by age and then by last name
(e.g., Pam and Angela are the same age, but Pam should come before Angela
because "Beesly" comes before "Martin"). Hint: you will need a helper
function that returns a tuple.
The printed list should have this same tuple order:
```py
[('Pam', 'Beesly', 25), ('Angela', 'Martin', 25), ('Jim', 'Halpert', 27),
('Michael', 'Scott', 45), ('Dwight', 'Schrute', 50), ('Phyllis', 'Lapin', 60)]
```
-----
## Sorting with more complex Yelp data
This part of the lab has a video walkthrough. If you get stuck or want extra
context, you can watch the video below, or click the download link to download
it and watch it later. The full video description on YouTube includes a
breakdown of all of the topics in the video with links to each one.
[Download Video](https://sakai.wellesley.edu/access/content/group/77109fc3-0650-48b0-aeb4-22c7e2e94cba/Lab%209%3A%20Nested%20Loops%20%2B%20Sorting/lab9_yelp.mp4) | [Download Captions](https://sakai.wellesley.edu/access/content/group/77109fc3-0650-48b0-aeb4-22c7e2e94cba/Lab%209%3A%20Nested%20Loops%20%2B%20Sorting/lab9_yelp.sbv)
Now you're ready to work with more complex (real world) data.
Inside your `lab07` folder, there is a file called `smallYelpSample.py`
that contains a variable with the same name. This is a list of 39 tuples,
and each tuple represents a business. [Note: this is a subset of actual
Yelp data, which we will revisit again later this semester].
### Understand the structure of the Yelp data
Here are two sample tuples:
```py
# bizName city state numRatings stars list_of_categories
('Starbucks', 'Toronto', 'ON', 21, 4.0, ['Food', 'Coffee & Tea']),
('Panera Bread', 'Elyria', 'OH', 4, 2.0, ['Soup', 'Salad', 'Sandwiches', 'Restaurants'])
```
The Starbucks, for example, in Toronto, Ontario, has 21 user ratings, and an average rating of 4.0 stars. Starbucks has two categories, Food and Coffee & Tea. Similar remarks hold true for Panera in Elyria, OH.
Open the provided starter called `sorting.py`. Add your usual comments at the top of the file, and note this line so you can access the Yelp data:
```py
from smallYelpSample import smallYelpSample
```
### Task 0: Write a function called `sortDataByName` to sort by business name
Here is a sample test:
```py
sortedByName = sortDataByName(smallYelpSample)
print(sortedByName[:5]) # just printing first 5
```
produces (scroll right to see all data):
```py
[("Alfredo's Jewelry", 'Las Vegas', 'NV', 23, 4.5, ['Shopping', 'Jewelry', 'Watch Repair', 'Local Services']),
('Alize Catering', 'Toronto', 'ON', 12, 3.0, ['Italian', 'French', 'Restaurants']),
('Any Given Sundae', 'Wexford', 'PA', 15, 5.0, ['Coffee & Tea', 'Ice Cream & Frozen Yogurt', 'Food']),
('BDJ Realty', 'Las Vegas', 'NV', 5, 4.0, ['Real Estate Services', 'Real Estate', 'Home Services', 'Property Management']),
('Bampot House of Tea & Board Games', 'Toronto', 'ON', 55, 4.0, ['Coffee & Tea', 'Restaurants', 'Food', 'Mediterranean', 'Tea Rooms'])]
```
## Task 1: What are the highest (and lowest) rated businesses?
### Task 1a: Write `howManyStars` to get the rating for any business
`howManyStars` is a fruitful function that, given a single business tuple, will return the star rating from that tuple.
For example,
```py
howManyStars(('Starbucks', 'Toronto', 'ON', 21, 4.0, ['Food', 'Coffee & Tea']))
```
returns `4.0`
and
```py
howManyStars(('Panera Bread', 'Elyria', 'OH', 4, 2.0, ['Soup', 'Salad', 'Sandwiches', 'Restaurants']))
```
returns `2.0`
### Task 1b: Write `sortDataByStars`
This function will return the list of all 39 businesses, sorted by the star ranking, from high stars to low stars. `sortDataByStars` should use `howManyStars` from Task 1a above. Here is a sample test:
```py
sortedByStars = sortDataByStars(smallYelpSample)
print(sortedByStars[:5]) # Best 5 businesses
```
Five highest rated businesses (can scroll right to view all data):
```py
# top 5
[('Pampered Hair Passionate about Hair', 'Henderson', 'NV', 3, 5.0, ['Hair Salons', 'Blow Dry/Out Services', 'Hair Stylists', 'Beauty & Spas', 'Hair Extensions']),
('Kool Pool Care & Repair', 'Phoenix', 'AZ', 5, 5.0, ['Home Services', 'Contractors', 'Pool & Hot Tub Service', 'Pool Cleaners']),
("Senior's Barber Shop", 'Goodyear', 'AZ', 65, 5.0, ['Barbers', 'Beauty & Spas']),
('Any Given Sundae', 'Wexford', 'PA', 15, 5.0, ['Coffee & Tea', 'Ice Cream & Frozen Yogurt', 'Food']),
('Olsen Firearms', 'Cave Creek', 'AZ', 9, 5.0, ['Shopping', 'Guns & Ammo'])]
```
```py
sortedByStars = sortDataByStars(smallYelpSample)
print(sortedByStars[-5:]) # Worst 5 businesses
```
Five lowest rated businesses (can scroll right to view all data):
```py
[('Ciao Baby Catering', 'Scottsdale', 'AZ', 5, 2.0, ['Event Planning & Services', 'Caterers']),
('TSA Checkpoint T-4 A - Phoenix Sky Harbor International Airport', 'Phoenix', 'AZ', 46, 1.5, ['Public Services & Government']),
('Soccer Zone', 'Las Vegas', 'NV', 9, 1.5, ['Shopping', 'Sporting Goods']),
('Western Motor Vehicle', 'Phoenix', 'AZ', 18, 1.5, ['Departments of Motor Vehicles', 'Public Services & Government']),
("McDonald's", 'Phoenix', 'AZ', 10, 1.0, ['Fast Food', 'Burgers', 'Restaurants'])]
```
{{-- Fall 19 skipping lambda
## Task 1c: Write `sortDataByStars2` with a anonymous function
This will be a small change to your `sortDataByStars` function: use `lambda` instead of
`howManyStars`. The functionality will be exactly the same, so the
tests in Task 1b above will work the same way. Here are the [lecture
notes on lambda and anonymous functions](http://cs111.wellesley.edu/content/lectures/lec_sorting_lambda/files/lec_sorting_lambda.pdf)
Hint: your `sortDataByStars2` will look like this:
```py
return sorted(data, key=lambda_____________________________)
```
--}}
## Task 2: Write `sortByNumberCategories`
`sortByNumberCategories` sorts the list of tuples by the number of categories that a given business has. Those businesses with more categories should be at the top of the list.
Note that the Brick House Tavern + Tap has 7 categories: ['American (New)', 'Nightlife', 'Bars', 'Sandwiches', 'American (Traditional)', 'Burgers', 'Restaurants'].
```py
print(sortDataByNumberCategories(smallYelpSample)[:5]) # the top five
```
```py
[('Brick House Tavern + Tap', 'Cuyahoga Falls', 'OH', 116, 3.5, ['American (New)', 'Nightlife', 'Bars', 'Sandwiches', 'American (Traditional)', 'Burgers', 'Restaurants']),
('Stephen Szabo Salon', 'McMurray', 'PA', 11, 3.0, ['Hair Stylists', 'Hair Salons', "Men's Hair Salons", 'Blow Dry/Out Services', 'Hair Extensions', 'Beauty & Spas']),
('Chula Taberna Mexicana', 'Toronto', 'ON', 39, 3.5, ['Tiki Bars', 'Nightlife', 'Mexican', 'Restaurants', 'Bars']),
('William Jon Salon & Spa', 'Madison', 'WI', 14, 4.5, ['Tanning', 'Day Spas', 'Spray Tanning', 'Beauty & Spas', 'Hair Salons']),
('Pampered Hair Passionate about Hair', 'Henderson', 'NV', 3, 5.0, ['Hair Salons', 'Blow Dry/Out Services', 'Hair Stylists', 'Beauty & Spas', 'Hair Extensions'])]
```
## Task 3: Write `sortByStateCityName`
`sortByStateCityName` sorts the list of tuples by the state, and then by the city, and then by the business name. Use a helper function. Note that in the example below, the first 10 businesses are all in AZ, since we sorted by state first. Within AZ, the businesses are alphabetically sorted by city. Note that the 5 businesses that are in `Phoenix, AZ` are sorted by business name (`Charr, Kool Pool, McDonald's, TSA Checkpoint, Western Motor Vehicle`).
```py
print(sortByStateCityName(smallYelpSample)[:10]) # the top 10
```
produces this list:
This is just an image with relevant parts highlighted:
And this is the actual data (horizontally scrollable):
```py
[('Olsen Firearms', 'Cave Creek', 'AZ', 9, 5.0, ['Shopping', 'Guns & Ammo']),
('CubeSmart Self Storage', 'Chandler', 'AZ', 23, 5.0, ['Local Services', 'Self Storage']),
("Senior's Barber Shop", 'Goodyear', 'AZ', 65, 5.0, ['Barbers', 'Beauty & Spas']),
('T & Y Nail Spa', 'Peoria', 'AZ', 20, 3.0, ['Beauty & Spas', 'Nail Salons']),
('Charr An American Burger Bar', 'Phoenix', 'AZ', 232, 3.0, ['Burgers', 'Restaurants']),
('Kool Pool Care & Repair', 'Phoenix', 'AZ', 5, 5.0, ['Home Services', 'Contractors', 'Pool & Hot Tub Service', 'Pool Cleaners']),
("McDonald's", 'Phoenix', 'AZ', 10, 1.0, ['Fast Food', 'Burgers', 'Restaurants']),
('TSA Checkpoint T-4 A - Phoenix Sky Harbor International Airport', 'Phoenix', 'AZ', 46, 1.5, ['Public Services & Government']),
('Western Motor Vehicle', 'Phoenix', 'AZ', 18, 1.5, ['Departments of Motor Vehicles', 'Public Services & Government']),
('Ciao Baby Catering', 'Scottsdale', 'AZ', 5, 2.0, ['Event Planning & Services', 'Caterers'])]
```
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