@buildwithakshita GitHub

Day 2 · NYC Airbnb
the resource list

Everything behind Day 2 of 30 Days to MLE: my notebook, the dataset, and the free guides and videos to learn pandas, NumPy and Matplotlib yourself.

1 dataset3 librariesDocs + videosAll free
← All 30 Days to MLE resources
01
The data · Kaggle

NYC Airbnb Open Data

Listings across all five boroughs

The dataset from the video: price, neighbourhood, room type and reviews for every listing. Load it with pandas and start asking questions.

  • CSV, beginner friendly
  • Free Kaggle account
  • Runs in a Kaggle notebook, no setup
My Kaggle notebook Code from the video The dataset Kaggle
  1. Load and cleanRead the CSV with pandas, check for missing values, fix the price column
  2. Remove outliersUse NumPy to drop the extreme listings that drag the average up
  3. Group and compareMedian price by neighbourhood with a single groupby
  4. VisualisePlot the most overpriced neighbourhoods and the hidden gems
02
Library · tables

Learn pandas

Think SQL table, living in your Python code

pandas loads, cleans, filters and groups your data. If you know SQL, groupby will feel familiar straight away.

  • ~1 hour to the basics
  • Docs + videos
  • Free
10 minutes to pandas Official Kaggle pandas course Pandas in 30 minutes Tech With Tim · video Pandas by example, full course freeCodeCamp · video
  1. DataFrames and SeriesThe two core objects, and how to read a CSV
  2. Selecting and filteringColumns, rows and conditions like price > 200
  3. groupbySplit, aggregate, combine: the GROUP BY of Python
  4. CleaningMissing values, types and renaming
03
Library · numbers

Learn NumPy

Maths on thousands of numbers, no for-loops

NumPy is the base every ML library is built on. Vectorised maths makes it fast and short to write.

  • ~45 min to the basics
  • Docs + videos
  • Free
NumPy for absolute beginners Official NumPy tutorial for beginners freeCodeCamp · video NumPy fundamentals session CampusX · video NumPy tutorial series Build with Akshit · playlist
  1. ArraysCreating arrays and checking their shape
  2. Vectorised mathsOperate on a whole column at once instead of looping
  3. Percentiles and statisticsMean, median and the 99th-percentile cut used for outliers
04
Library · charts

Learn Matplotlib

console.log, but for data

Turns your results into charts people actually look at. Every chart in the Day 2 video was made with it.

  • ~45 min to the basics
  • Free
Matplotlib quick start Official Python Data Science Handbook Matplotlib crash course freeCodeCamp · video
  1. Figure and axesThe two objects behind every plot
  2. Bar charts and histogramsComparing neighbourhoods and spotting outliers
  3. Scatter plotsPrice vs popularity, where the hidden gems show up
05
Put it together · projects

All three, in practice

Once the basics click, watch them work together

A full course that uses NumPy, pandas and Matplotlib side by side, and a portfolio project you can follow along and then redo on your own dataset.

  • Pick one, not both
  • Free
Data analysis with Python, full course freeCodeCamp Book sales portfolio project Onur Baltaci · video
  1. Follow along onceCode every cell yourself instead of just watching
  2. Redo it on new dataSame steps on the NYC Airbnb dataset, or anything you care about
  3. Share one chartPost your favourite plot, the best proof you learned it