This is an adapted version of the pandas cookbook.
It uses 3 datasets:
- 311 calls in New York
- How many people were on Montréal's bike paths in 2012
- Montreal's weather for 2012, hourly
The lecture / problem set is going to be follow along, where we all code together.
- Chapter 1: Reading from a CSV
Explains how to load csvs into pandas and gives a first look at a pandas dataframe. - Chapter 2: Selecting data & finding the most common complaint type
This explains how to select columns or rows of data frames. - Chapter 3: Which borough has the most noise complaints? (or, more selecting data)
How to filter datasets and count occurrences. - Chapter 4: Find out on which weekday people bike the most with groupby and aggregate
How to do analyses at many levels using group_by and aggregate. - Chapter 5: String operations! Which month was the snowiest?
String and date processing are useful, and pandas has plenty of convenience functions.