Resample and roll with it

As of pandas version 0.18.0, the interface for applying rolling transformations to time series has become more consistent and flexible, and feels somewhat like a groupby (If you do not know what a groupby is, don't worry, you will learn about it in the next course!).

You can now flexibly chain together resampling and rolling operations. In this exercise, the same weather data from the previous exercises has been pre-loaded for you. Your job is to extract one month of data, resample to find the daily high temperatures, and then use a rolling and aggregation operation to smooth the data.

Use partial string indexing to extract August 2010 temperature data, and assign to august.
Resample to daily frequency, saving the maximum daily temperatures, and assign the result to daily_highs.
As part of one long method chain, repeat the above resampling (or you can re-use daily_highs) and then combine it with .rolling() to apply a 7 day .mean() (with window=7 inside .rolling()) so as to smooth the daily highs. Assign the result to daily_highs_smoothed and print the result.

Exercise

Resample and roll with it

Instructions