Dropping levels

The contingency table from the last exercise revealed that there are some levels that have very low counts. To simplify the analysis, it often helps to drop such levels.

In R, this requires two steps: first filtering out any rows with the levels that have very low counts, then removing these levels from the factor variable with droplevels(). This is because the droplevels() function would keep levels that have just 1 or 2 counts; it only drops levels that don't exist in a dataset.

This is a part of the course

“Exploratory Data Analysis in R”

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Exercise instructions

The contingency table from the last exercise is available in your workspace as tab.

Load the dplyr package.
Print tab to find out which level of align has the fewest total entries.
Use filter() to filter out all rows of comics with that level, then drop the unused level with droplevels(). Save the simplified dataset as comics_filtered.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Load dplyr
___

# Print tab
___

# Remove align level
comics_filtered <- ___ %>%
  ___(align != ___) %>%
  ___()

# See the result
comics_filtered

Edit and Run Code