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Biggest jumps in a name

Previously, you added a ratio column to describe the ratio of the frequency of a baby name between consecutive years to describe the changes in the popularity of a name. Now, you'll look at a subset of that data, called babynames_ratios_filtered, to look further into the names that experienced the biggest jumps in popularity in consecutive years. 

babynames_ratios_filtered <- babynames_fraction %>%
                     arrange(name, year) %>%
                     group_by(name) %>%
                     mutate(ratio = fraction / lag(fraction)) %>%
                     filter(fraction >= 0.00001)

Deze oefening maakt deel uit van de cursus

Data Manipulation with dplyr

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Oefeninstructies

  • From each name in the data, keep the observation (the year) with the largest ratio; note the data is already grouped by name.
  • Sort the ratio column in descending order.
  • Filter the babynames_ratios_filtered data further by filtering the fraction column to only display results greater than or equal to 0.001.

Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

babynames_ratios_filtered %>%
  # Extract the largest ratio from each name 
  ___
  # Sort the ratio column in descending order 
  ___
  # Filter for fractions greater than or equal to 0.001
  ___
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