Exercise

Slicing time series

Slicing is particularly useful for time series since it's a common thing to want to filter for data within a date range. Add the date column to the index, then use .loc[] to perform the subsetting. The important thing to remember is to keep your dates in ISO 8601 format, that is, "yyyy-mm-dd" for year-month-day, "yyyy-mm" for year-month, and "yyyy" for year.

Recall from Chapter 1 that you can combine multiple Boolean conditions using logical operators, such as &. To do so in one line of code, you'll need to add parentheses () around each condition.

pandas is loaded as pd and temperatures, with no index, is available.

Instructions

100 XP
  • Use Boolean conditions, not .isin() or .loc[], and the full date "yyyy-mm-dd", to subset temperatures for rows in 2010 and 2011 and print the results.
  • Set the index of temperatures to the date column and sort it.
  • Use .loc[] to subset temperatures_ind for rows in 2010 and 2011.
  • Use .loc[] to subset temperatures_ind for rows from Aug 2010 to Feb 2011.