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University of California Los Angeles R Studio to Tidy Data Questions Exam

University of California Los Angeles R Studio to Tidy Data Questions Exam

Question Description

3 questions using R studio to tidy data

elements for each questions.




|1.2|2.|Tidy with data|



|1.5|1.|indentify words|



|2.1|1.|Redownload and tidy|

|2.2|1.|Calculate the tf-idf|


|2.4|1.|High tf-idf|

|2.5|2.|Plot top 7|


|3.Extra Credit Podcast|2.|Summarize|

||20|Total (Plus Extra Credit)|

## Download Victor Hugo’s *Les Miserables* (135) and Dickens’ *A Tale of Two Cities* (98)

“`{r get_two_books, cache = TRUE}


## Tidy the two books with added line numbers and chapter numbers.

“`{r tidy_book}


## Measure the net sentiment using bing for each 100 lines and plot it for each book.

“`{r plot_sentiment}


## Graph all the sentiments for each book using a faceted graph.

“`{r graph_all_sentiments}


## Look at which words contribute to the positive and negative sentiment

– Identify any to exclude as part of the sentiment.

“`{r bing_word_counts}


## Plot the top ten for each positive and negative sentiment

– by book

“`{r bing_word_counts_plot}


## Briefly summarize your analysis and any recommended next steps

# tf-idf for Mark Twains books from Q1

## Create a tf-idf ready dataframe for Mark Twain’s books from Q1

– Remember to leave the stop words in the text

– Re-download with the book title from the meta data fields





## Calculate the tf-idf



## Plot the tf for each book

– Facet by book


## look at terms with high tf-idf.

– Across all books



## Plot the the top 7 words from each book.

– Sort by most frequent



## Summarize your analysis and any recommended next steps

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