---
# System prepended metadata

title: Lab 05
tags: [Labs-S23, ' 2023']

---

---
tags: Labs-S23, 2023
title: Lab 05
---
# Lab 5: Maps & More Maps

In this lab, you’ll be using everything you’ve learned about tables (and some of what you’ve learned about lists) to create a data visualization tool. Specifically, you’ll use a dataset of **active Providence business licenses** published by the Rhode Island government to mark locations on a map.

## Learning Objective

A key goal of this lab is to give you practice breaking large problems into separate tasks, each of which gets handled with its own collection of functions, expressions, and operators. As you work on the problems, practice writing out the lists of tasks and using those to guide your work.

## Resources
[Pyret List documentation
](https://www.pyret.org/docs/latest/lists.html#%28part._lists_.List_shared._methods_filter%29
)
## Part 1: Warm up with Lists

Before we get into maps, however, let's practice writing functions with lists. We're going to do a set of problems that involve processing emails. Your goal is to use a combination of `filter`, `map`, `distinct`, `length`, and `.get` on lists to solve these problems.

**Task:** Define two lists of strings, one that has all valid email addresses (like "kathi@brown.edu", "ice@google.com", etc) and one that also has some invalid ones (missing @, anything after the username, etc). You'll use these for testing.

**Task:** Write a function that takes a list of email addresses and counts the number that are from `.edu` addresses (it's okay to just use `string-contains` here, rather than checking that `.edu` is at the end of the address).

**Task:** Write a function that takes a list of emails and returns the ones that lack the "@" sign.

**Task:** Write a function that takes a list of email addresses and returns just a list of the usernames (dropping everything starting from the @. Look up `string-split`; there's also `LIST.get(n)` which gets the nth item from a list, starting from 0).

If you have time (meaning you are less than 40 minutes into lab) also try the following task:

**Task:** Return a list of unique school names represented in a list of email addresses. The school names appear between the "@" and ".edu" in .edu addresses. (You can assume that all emails contain "@" and ".edu")



## Part 2: Making a Simple Map

### Question 2.1: Loading the data
Before you start working with the data, take a look at [the Providence Business License dataset](https://docs.google.com/spreadsheets/d/18eKc_o-eZ8TWno6ePYkcMGKhx-Y2Fe8LEERqV5gClaU/edit#gid=1437433378). The first sheet (inside the file) is the original dataset, and the second sheet is a pruned version with only the columns you’ll need for this lab. Load the pruned sheet into Pyret by pasting the following code into the definitions window:

```include tables
include shared-gdrive("dcic-2021", "1wyQZj_L0qqV9Ekgr9au6RX2iqt2Ga8Ep")
include gdrive-sheets
import data-source as ds
include shared-gdrive("stencil.arr", "1W61RYJDms4y-1tP_oQ9igydaYr-nmHCr")
include image-structs
import lists as L

##############
# SETUP CODE #
##############

ssid = "18eKc_o-eZ8TWno6ePYkcMGKhx-Y2Fe8LEERqV5gClaU"
data-sheet = load-spreadsheet(ssid)
pvd-businesses = 
  load-table: license-id, name, extended-hours, hotel, parking, 
    restaurant, food-and-liquor, food-dispenser, lat, long
    source: data-sheet.sheet-by-name("Licenses_Pruned", true)
    sanitize license-id using ds.string-sanitizer
    sanitize name using ds.string-sanitizer
    sanitize extended-hours using ds.bool-sanitizer
    sanitize hotel using ds.bool-sanitizer
    sanitize parking using ds.bool-sanitizer
    sanitize restaurant using ds.bool-sanitizer
    sanitize food-and-liquor using ds.bool-sanitizer
    sanitize food-dispenser using ds.bool-sanitizer
    sanitize lat using ds.num-sanitizer
    sanitize long using ds.num-sanitizer
  end
```

### Question 2.2: Generate a Map
We have provided you with a function `table-to-map(t :: Table) -> Image`, which takes in a table and plots rows as dots on a map of Providence, based on their `"x"`, `"y"`, and `"color"` columns. **Treat `table-to-map` like a built-in function**; you can call it just like you called `filter-by` or any other built-in function in previous labs.

To use `table-to-map` to map the locations of the businesses listed in `pvd-businesses`, you will need to convert the longitude and latitude values in the table to x- and y-coordinate values. Only locations that fit within the bounds of the Providence map can be included (`table-to-map` will account for this automatically). We’ve defined the following values for you in the `stencil.arr` file that the setup code includes:

* `LAT-MIN` - the minimum latitude that fits the map
* `LAT-MAX` - the maximum latitude that fits the map
* `LON-MIN` - the minimum longitude that fits the map
* `LON-MAX` - the maximum longitude that fits the map
* `HEIGHT` - the height of the map
* `WIDTH` - the width of the map


:::info
Try typing `LAT-MIN` or any of these values in the interactions window, you should see they are predefined values that you can use in your functions.
:::

Use these values to write functions that **scale** latitudes to `y` values and longitudes to `x` values **relative to the map dimensions**. You must proportionally scale the businesses' (`long`, `lat`) coordinates to (`x`, `y`) coordinates in order for the rows to be read by the `table-to-map` function correctly. 

To make things easier for you, we've included scaling formulas!

![](https://i.imgur.com/or0UFi2.png)


**TASK:** Use these scaling functions to add columns named `x` and `y` to the `pvd-businesses` table with these scaled values. 

**TASK:** Add a column labeled `color` and set each row’s color to "black." After adding these columns, the computed table can then be used as an input to `table-to-map`. 

**HINT:** Think about whether the output for this column is dependent on each specific row. How can we generate this column using `build-column`?

Complete the tasks and pass the transformed table into `table-to-map`. The output should look something like this:

![](https://i.imgur.com/6rfakrA.jpg)

___

### *CHECKPOINT:* Call over a TA once you reach this point.
___

## Part 3: Analyzing the Data

Now that you have a map of Providence (albeit not a very pretty one), we need to put it to good use. Your friend Sofia has taken you up on your invitation to visit and has just arrived in Providence. She wants to know what she should do while she's here!

### Question 3.1: Generate a tourist map

Write a function `generate-tourist-map(needs-hotel :: Boolean, 
has-car :: Boolean, stays-up-late :: Boolean, eats-out :: Boolean, businesses :: Table) -> Image` that takes in a series of Booleans and the original `pvd-businesses` table and returns a map marked with the places that Sofia might want to visit.

* `needs-hotel`: If this Boolean is `true`, Sofia needs a hotel to stay at! Mark all of the inns on the map with a color of your choice. 
* `has-car`: If `true`, Sofia has decided to drive and will need to find places with parking. Mark all places with parking with a second color.
* `stays-up-late`: If `true`, Sofia is ready for a night out! Mark all places with extended hours (Look at the column entitled `extended-hours`) with a third color.
* `eats-out`: If `true`, Sofia has given up on cooking for herself and wants to eat out. Mark all eateries with a fourth color.

:::info
Remember that your `generate-tourist-map` function should take in the **original** pvd-businesses table, not the modified one made in Part 1.
:::

If a place has more than one relevant characteristic, **it should be colored according to the characteristic that's most important** to Sofia. Any non-relevant places should be colored black. Starting with the most important characteristic, Sofia cares first about hotels, then eating out, then places that have parking, and lastly, places that stay open late. 

*Depending on the values of the parameters (`needs-hotel`, `has-car`, `stays-up-late`, `eats-out`), the computed colors for places will be different. Think about how you can accomplish this behavior with a nested function.*

**NOTE:** Look at the list of predefined colors in the [Pyret Documentation](https://www.pyret.org/docs/latest/image-structs.html#%28part._image-structs_.Color%29) to see what options you have.

___

### *CHECKPOINT:* Call over a TA once you reach this point.
___

## Part 4: Games Games Games!
It turns out that your game-enthusiast friend Sofia wants nothing more than to buy and play Monopoly. However, before she can buy Monopoly, Sofia would like a doughnut (everyone gets hungry!). Good thing Sofia is a big advocate for local businesses and wants to visit all the local doughnut shops in Providence!

How do we distinguish local shops from those in national chains?  One way is to find all the doughnut shops and see which ones have names that appear many times in the data---local shops will have fewer entries in the list. A frequency-bar chart would show us this answer visually, but what if we had to compute this information from a list of names of doughnut shops, rather than read it off of a frequency-bar-chart?

### Question 4.1

***TASK:*** Write an expression that gets the list of all donut shops from the original table.

:::info
Something to keep in mind: There are two spellings for the tasty dessert of interest: donut and doughnut. Be aware of this when you are looking for businesses.
:::

***TASK:*** Based on inspecting the list of donut shops, determine which shops are local or a chain. We'll consider a doughnut shop to be local if it has **no more than 2 locations** in the `pvd-businesses` table.

Filter out the chain donut shops to create a list called `donuts-lst`  of names of local doughnut shops. 


*Remember to write out your list of tasks first and use that to guide your work.*

### Question 4.2
***TASK:*** Filter the original `pvd-businesses` table to only include donut shops (both local and chain).


***TASK:*** On this filtered table, add a color column where local stores are **red** and chain stores are **black**.

***TASK:*** Using the `table-to-map` function and your updated table, create a map that highlights all of the donut shops in their correct colors.


___

### *CHECKPOINT:* Call over a TA once you reach this point.
___

## Part 5: A Different Kind of Map 

Now that Sofia got her doughnut, she is ready to purchase Monopoly. Unsatisfied with how few stores sell them in Providence, Sofia decides to open her own game store. After conducting a survey of existing options, she's created a list of the most popular board games. With Monopoly, Sofia can finally have fun!


### Question 5.1
Write a function `create-token(token-colors :: List<String>) -> List<Image>` that takes in a list of strings representing valid colors and produces a list of game tokens of these colors. Each token should have this shape, but with its index-specific color and a yellow star:

![](https://i.imgur.com/fch3Dxl.png)


Each token should also have a randomly generated size, such that its radius is between 15-35 units.

**HINT:** Take a look at the List operations from part 3.1.

*Discuss why you think lists are being used in this problem as opposed to tables. When would it be preferable to use tables over lists?*


### Question 5.2
Sofia has discovered that the ideal token size has a radius within 20-30. She wants to discard all of the token images that are outside of that range and make display signs out of the rest.


Write a function `generate-token-signs(token-images :: List<Image>) -> List<Image>` that takes in the output list from `create-token`. This function should remove all of the tokens that lie outside of the size range and put the remaining token on square backgrounds. This is what an output list item should look like:

![](https://i.imgur.com/tLx0v0H.png)


***HINT:*** look at the `image-width` function in the documentation when making the function

___

### *CHECKPOINT:* Call over a TA once you reach this point.
___

## Success!

Sofia finally bought her new token! Hooray! As a gift, she has provided you with a $5 gift card for her game store! Business at Sofia's store is booming, all thanks to you.

------

> Brown University CSCI 0111 (Spring 2023)
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