PyNoon Data Lesson 3

Warm-Up Exercise

  1. Load libraries and data in a notebook:

    import pandas as pd
import plotly.express as px

listings_df = pd.read_csv('https://pynoon.github.io/data/inside_airbnb_listings_nz_2023_09.csv')
listings_df

  2. Using what you learned in lesson 2’s tutorial:

    • Make a histogram plot of listing prices in Auckland
    • Make a scatter plot of listing of price against review rating for listings that only accomodate one person
    • Challenge: Add an island column to listings_df that indicates which island the listing is located in based on lat and lon

Thanks

  • To the host for the great venue!
  • To our sponsors

Administrivia

  • Fire escapes
  • Toilets
  • Cleaning up after ourselves
  • WiFi

Lunch Talk: Intro to Software Design

  • Just one possible way to go about software design
  • We’ll look at an example of a simple report generating system

1. Identify Inputs and Outputs

  • What formats will inputs and outputs be in?

2. Plan high-level steps

  • Work forwards from the inputs, backwards from the outputs, or both!
  • First think about the data you need to produce, then how to produce it

3. Fill in details

  • Think about what libraries or techniques you will use for each part
  • If necessary, break up major steps into sub-steps
  • Next lesson we’ll look at how to write your own functions to split your code according to your identified steps

4. Get started!

  • Start with the most uncertain parts:
    • The part that you don’t know how to do yet
    • The part that might not work
  • Prioritise working code over perfect code for this
    • You’ll likely rewrite it based on what you learn!
  • What you learn from doing that might also make you reconsider parts or all of your design

Tutorial Objectives

  • Grouping and summarising data in Pandas and Plotly
  • Extra: Handling missing data in Pandas

Independent Work/Homework

  1. Exercise Notebook:
  2. Work through futurecoder.io sections:
    1. Functions (we’ll also be covering functions in the next lesson)