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Exercise

Calculating on a pivot table

Pivot tables are filled with summary statistics, but they are only a first step to finding something insightful. Often you'll need to perform further calculations on them. A common thing to do is to find the rows or columns where the highest or lowest value occurs.

Recall from Chapter 1 that you can easily subset a Series or DataFrame to find rows of interest using a logical condition inside of square brackets. For example: series[series > value].

pandas is loaded as pd and the DataFrame temp_by_country_city_vs_year is available.

Instructions
100 XP
  • Calculate the mean temperature for each year, assigning to mean_temp_by_year.
  • Filter mean_temp_by_year for the year that had the highest mean temperature.
  • Calculate the mean temperature for each city (across columns), assigning to mean_temp_by_city.
  • Filter mean_temp_by_city for the city that had the lowest mean temperature.
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