Simple .NET/ASP.NET PDF document editor web control SDK

To tie together even more tightly the slides in this example, consider sketching one image across all of Act I. Figure 7-9 shows how to do this. The Title slide includes a sketch of a magnifying glass, then the Setting slide shows a chart of the industry returns declining, and then the Role slide shows the chart and magnifying glass. The Point A slide keeps the industry returns line of the chart but now adds the speci c company s data to do this, use a different color ink on either your Tablet PC or on paper to distinguish the different lines in the chart. The Point B slide illustrates what the company wants to achieve by showing three arrows pointing upward. The nal Call to Action slide adds the magnifying glass directly over the upward arrows and shows the logo of your company.

winforms pdf 417 reader, winforms qr code reader, winforms upc-a reader, winforms data matrix reader, winforms ean 128 reader, winforms ean 13 reader, c# remove text from pdf, find and replace text in pdf using itextsharp c#, winforms code 39 reader, itextsharp remove text from pdf c#,

# analyzer.rb -- Text Analyzer stop_words = %w{the a by on for of are with just but and to the my I has some in} lines = File.readlines("text.txt") line_count = lines.size text = lines.join # Count the characters character_count = text.length character_count_nospaces = text.gsub(/\s+/, '').length # Count the words, sentences, and paragraphs word_count = text.split.length sentence_count = text.split(/\.|\ |!/).length paragraph_count = text.split(/\n\n/).length # Make a list of words in the text that aren't stop words, # count them, and work out the percentage of non-stop words # against all words all_words = text.scan(/\w+/) good_words = all_words.select{ |word| !stop_words.include (word) } good_percentage = ((good_words.length.to_f / all_words.length.to_f) * 100).to_i # Summarize the text by cherry picking some choice sentences sentences = text.gsub(/\s+/, ' ').strip.split(/\.|\ |\!/) sentences_sorted = sentences.sort_by { |sentence| sentence.length } one_third = sentences_sorted.length / 3 ideal_sentences = sentences_sorted.slice(one_third, one_third + 1) ideal_sentences = ideal_sentences.select { |sentence| sentence =~ /is|are/ } # Give the analysis back to the user puts "#{line_count} lines" puts "#{character_count} characters" puts "#{character_count_nospaces} characters (excluding spaces)" puts "#{word_count} words"

"#{sentence_count} sentences" "#{paragraph_count} paragraphs" "#{sentence_count / paragraph_count} sentences per paragraph (average)" "#{word_count / sentence_count} words per sentence (average)" "#{good_percentage}% of words are non-fluff words" "Summary:\n\n" + ideal_sentences.join(". ") "-- End of analysis"

7

As you can see, when you replace a value in the copy, the original is unaffected. However, if you modify a value (in place, without replacing it), the original is changed as well because the same value is stored there (like the machines list in this example).

Note If you re a Windows user, you might want to replace the ARGV[0] reference with an explicit reference to "text.txt" to make sure it works okay from FreeRIDE or SciTE. However, if you re running the program from the command prompt, it should operate correctly.

Running the completed analyzer.rb with the Oliver Twist text now results in an output like so:

This is a good example of how your PowerPoint slides are no longer like pieces of paper lled with lists of facts. Now your slides are like frames in a lmstrip, moving at a pace of about one frame per minute, with your voice providing the soundtrack to a clear and compelling story. Although to the audience, your presentation is a single smooth and seamless experience, in fact you have packed a great deal of information into these frames and have covered the ve essential elements that ensure that you always start strong, as described in 4: orienting, interesting, engaging, motivating, and focusing your audience.