diff --git a/README.md b/README.md
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+++ b/README.md
@@ -1,3 +1,5 @@
 # TextMining
 
 This is the base repo for the text mining and analysis project for Software Design at Olin College.
+
+Look for my pdf submitted in the general repository.
diff --git a/TextMiningWriteUp.pdf b/TextMiningWriteUp.pdf
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diff --git a/text_mining.py b/text_mining.py
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+++ b/text_mining.py
@@ -0,0 +1,36 @@
+import requests
+import re
+from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
+
+amontillado = requests.get('http://www.gutenberg.org/cache/epub/1063/pg1063.txt').text
+raven = requests.get('http://www.gutenberg.org/cache/epub/17192/pg17192.txt').text
+house = requests.get('http://www.gutenberg.org/cache/epub/932/pg932.txt').text
+
+def words(text):
+    #This removed all of the non-alphanumeric characters in a given string
+    return re.compile(r'\W+', re.UNICODE).split(text)
+
+def makeDict(wlist):
+    #This returns a dictionary of words and how frequently they appear in the story
+    wfreq = [wlist.count(p) for p in wlist]
+    return dict(zip(wlist,wfreq))
+
+def sortDict(dfreq):
+    #This sorts the dictionary created in makeDict
+    sort = [(dfreq[key], key) for key in dfreq]
+    sort.sort()
+    sort.reverse()
+    return sort
+
+analyzer = SentimentIntensityAnalyzer()
+analyzer2 = SentimentIntensityAnalyzer()
+analyzer3 = SentimentIntensityAnalyzer()
+
+
+if __name__ == "__main__":
+    print(sortDict(makeDict(words(amontillado))))
+    print(sortDict(makeDict(words(raven))))
+    print(sortDict(makeDict(words(house))))
+    print(analyzer.polarity_scores(amontillado))
+    print(analyzer2.polarity_scores(raven))
+    print(analyzer3.polarity_scores(house))