I’ll be honest with you, maybe this is another one of those Python Data Analysis blog posts. Perhaps there’s one difference, I want to do this quick and “easy”, also I’ll be working with dates.

I’ll be analyzing AirBnB listings data for Seattle, WA 2016. The data shows which listings are available and filled on each day.

First, import necessary libraries. Libraries are a bunch of tools that very nice people have kindly put together and made available to us.

import numpy as np
import pandas as pd
import seaborn as sns

The second tasks is to import your file…


As part of my Udacity Data Science course, I’ll be answering some questions about this AirBnB data for Seattle, WA, USA.

First question: Are listings similar for each weekday and month in the data?

I’ve generated bar charts to represent the number of listings for each day (Fig. 2) and each month (Fig. 3) below.

Mujeeb Lawal

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store