Lecture 1 in-class exercise

Lecture 1 in-class exercise#

We’ll be doing calculations on a subset of 2021 Yellow Taxi Trips data.

Step 0#

The data needs to available on the machine where Python is running in order to process it, so let’s download from the NYC Open Data site directly:

!wget -O 2021_yellow_taxi_trips.csv --no-verbose https://data.cityofnewyork.us/resource/m6nq-qud6.csv

2025-06-29 23:01:23 URL:https://data.cityofnewyork.us/resource/m6nq-qud6.csv [136065] -> "2021_yellow_taxi_trips.csv" [1]

This is using a command-line program to do the downloading. We’ll download data ourselves manually later.

Look at the files in the sidebar. You should see 2021_yellow_taxi_trips.csv there. (You may need to refresh that list.)

Your turn!#

Do the following steps:

  • Using generative AI only

  • Using pure Python, not pandas or other packages

    • In other words, import csv should probably be the only import.

Step 1#

Print out the trip distances.

# your code here

Step 2#

Calculate the average ride distance.

# your code here

Step 3#

Calculate the percent of trips that were paid for by credit card.

  • The data dictionary will be helpful - see the Attachment on the dataset page.

  • Pair with a neighbor.

# your code here