Four score and seven years ago our fathers brought forth on this continent, a new nation, conceived in Liberty, and dedicated to the proposition that all men are created equal. Now we are engaged in a great civil war, testing whether that nation, or any nation so conceived and so dedicated, can long endure. We are met on a great battle-field of that war. We have come to dedicate a portion of that field, as a final resting place for those who here gave their lives that that nation might live. It is altogether fitting and proper that we should do this.

But, in a larger sense, we can not dedicate - we can not consecrate - we can not hallow - this ground. The brave men, living and dead, who struggled here, have consecrated it, far above our poor power to add or detract. The world will little note, nor long remember what we say here, but it can never forget what they did here. It is for us the living, rather, to be dedicated here to the unfinished work which they who fought here have thus far so nobly advanced. It is rather for us to be here dedicated to the great task remaining before us - that from these honored dead we take increased devotion to that cause for which they gave the last full measure of devotion - that we here highly resolve that these dead shall not have died in vain - that this nation, under God, shall have a new birth of freedom - and that government of the people, by the people, for the people, shall not perish from the earth.

Part 1 - Word Counts **Read in the text file** - In the cell below, read the #gettysburg_address.txt* file into Python. In [ ]: Question: What is the difference between read() and readlines()? Type Markdown and LaTeX: a? Split the text - Split the text into a list of individual words. This process is called tokenization and is a common data pre-processing step when working with any text data. In [ ]: Create a dictionary - Initialize an empty dictionary to hold the word counts. In [ ]: Populate your dictionary - Iterate over your list of words and update the word counts for each word in the text. In [ ]: Sort your word count dictionary - Dictionaries are unordered collections in Python. You will need to find a way to sort the dictionary by its values. Save the sorted output to a new variable. Example output: Dictionary: ('of': 14, 'was: 5, 'The': 27} Sorted output: ('The', 27), ('of, 14), ('was', 5) In [ ]: Question: How does items() return the dictionary key-value pairs? Type Markdown and LaTeX: a? Print out the top 10 most used words. In [ ]: Bonus - Your script will consider 'The' and 'the' to be separate words. Likewise, 'war' and war.' (note the period) will be considered differently. Before adding your words to the dictionary, clean up the text to remove capitalization and punctuation