Introduction

A new taxi company hired an advertising agency to advertise their services on screens at Times Square in New York, NY. The marketing

company was tasked to identify the five best screens for their client. In order to reach the maximum number of potential clients for the

new taxi company the criterion they decided to use was the average number of taxi pickups in close proximity to an advertising screen.

The marketing company found two public datasets that they are going to use:

1. The list of screens at the Time Square (https://canvas.park.edu/courses/76064/files/10359799/download?wrap=1)

(https://canvas.park.edu/courses/76064/files/10359799/download?download_frd=1):/n2. Public taxi ridership data (for NYC) (https://www1.nyc.gov/site/tlc/about/tic-trip-record-data.page).:

Large datasets like this one are usually consist of a) data dictionary, a table that lists all the fields in the dataset; b) and the actual

dataset in a variety of formats (Excel compatible comma separated values (.cvs), XML or JSON).

Large datasets like this one usually consist of a) data dictionary, a table that lists all the fields in the dataset; b) and the actual dataset in

a variety of formats (Excel compatible comma-separated values (.cvs), XML or JSON).

Directions

>

(https://canvas.park.edu/courses/76064/modules/items/5464879)

>

(https://canvas.park.edu/courses/76064/modules/items/5464883)

Sub

Assignment

With the dataset structures (field names, or dictionaries) in mind, use Word to design a flow chart of the algorithm to describe the

process of identifying the top five screens that would be seen most often by the taxi riders.

Note that you don't need to provide code, and you don't need to calculate top screens, just provide a pseudo code for the algorithm

that would perform that task.

Pseudocode is a somewhat structured description of the steps of an algorithm written in plain English. You may also use variable

names to refer to the same data multiple times if needed.