Data Exploration with Python

Learning Goals

  1. Explain how NumPy arrays differ from Python lists.
  2. Read data from CSV files into NumPy array data structures and explore and manipulate the data.
  3. Use Matplotlib to create simple 2D plots.

The IPython notebooks for this lesson are in data-explore.zip. Please download that archive, unzip it in your bootcamp repo, then add and commit the files.

First, We Need Data...

  • Work in groups
  • Use your browser to go to http://climate.weather.gc.ca/ and work your way through to the "Hourly Data Report" for yesterday at the VANCOUVER INTL A station
  • Download the August 2013 hourly data as a CSV file
  • Use your shell skills to confirm that:
    • You really got a CSV file
    • It's for the VANCOUVER INTL A station
    • It contains hourly data for the whole month of August 2013
  • Move or copy the CSV file into the data-explore/ directory in your repo and commit it
  • Back on the web page and use the "Nearby Stations with Data" link to get to the "Daily Data Report" for the POINT ATKINSON station
  • Download a different year's daily data as a CSV file at the POINT ATKINSON station (We'll map out who gets which year on the whiteboard)
  • Confirm that the file contains the data you expect, and commit it into your repo

Each member of each group should end up with a hourly data report for YVR in August 2013 in their repo, and a daily data report from Point Atkinson for a different year.

Now for Exploration

Launch IPython notebook in your data-explore/ directory and create a new notebook. We're going to interactively work through the following notebooks:

The notebooks and supporting files for this lesson are available in this data-explore.zip archive.

References

Back to Topics

Facebook Google+ Twitter GitHub RSS License Bug Report