Numbers

For these exercises, we’ll use the dog breed traits and dog breed popularity rankings data sets.

1. Load tidyverse and import dog_breed_traits_clean.csv to traits.

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2. Create a column of per-row means over all rating columns called mean_ratings and assign to traits2.

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3. Convert mean_ratings to a proportion in a column called pmean_ratings and add to traits2.

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4. Apply a natural log transformation to the pmeans_ratings vector.

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5. Round pmean_ratings to two decimal places.

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6. Convert pmean_ratings to scientific notation.

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7. Sum up the total grooming ratings for each coat type.

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8. Add inline R code to the following sentence in R Markdown to say how many rows have NA for grooming:

We are missing grooming data for [insert inline R code] breeds.