DataCamp

Bing tidy polarity: Call me Ishmael (with ggplot2)!

The last Bing lexicon exercise! We started with this lexicon since its similar to the results in Chapter 1. In this exercise you will use the pipe operator (%>%) to create a timeline of the sentiment in Moby Dick. In the end you will also create a simple visual following the code structure below. The next chapter goes into more depth for visuals.

ggplot(spread_data, aes(index_column, polarity_column)) +
  geom_smooth()

Your R session has moby as your text and bing as your lexicon. After this exercise you should know Is Moby Dick a happy or sad book?

Inner join moby to the bing lexicon.
- Call inner_join() to join the tibbles.
- Join by the term column in the text and the word column in the lexicon.
Count by sentiment and index.
Reshape so that each sentiment has its own column.
- Call spread().
- The key column (to split into multiple columns) is sentiment.
- The value column (containing the counts) is n.
- Also specify fill = 0 to fill out missing values with a zero.
Use mutate() to add the polarity column. Define it as the difference between the positive and negative columns.
Lastly, create a sentiment time series with ggplot().
- Pass in moby_polarity to the data argument.
- Then specify the x and y aesthetics, calling aes() and passing index and polarity without quotes.
- Add a smoothed sentiment curve with geom_smooth().

Take Hint (-30 XP)

Exercise

Bing tidy polarity: Call me Ishmael (with ggplot2)!

Instructions