I am new to Python and need some help with trying to come up with a text content analyzer that will help me find 7 things within a text file:
So far I have this Python program to print total word count:
with open('/Users/name/Desktop/20words.txt', 'r') as f:
p = f.read()
words = p.split()
wordCount = len(words)
print "The total word count is:", wordCount
So far I have this Python program to print unique words and their frequency: (it's not in order and sees words such as: dog
, dog.
, "dog
, and dog,
as different words)
file=open("/Users/name/Desktop/20words.txt", "r+")
wordcount={}
for word in file.read().split():
if word not in wordcount:
wordcount[word] = 1
else:
wordcount[word] += 1
for k, v in wordcount.items():
print k, v
Thank you for any help you can give!
Certainly the most difficult part is identifying the sentences. You could use a regular expression for this, but there might still be some ambiguity, e.g. with names and titles, that have a dot followed by an upper case letter. For words, too, you can use a simple regex, instead of using split
. The exact expression to use depends on what qualifies as a "word". Finally, you can use collections.Counter
for counting all of those instead of doing this manually. Use str.lower
to convert either the text as a whole or the individual words to lowercase.
This should help you getting startet:
import re, collections
text = """Sentences start with an upper-case letter. Do they always end
with a dot? No! Also, not each dot is the end of a sentence, e.g. these two,
but this is. Still, some ambiguity remains with names, like Mr. Miller here."""
sentence = re.compile(r"[A-Z].*?[.!?](?=\s+[A-Z]|$)", re.S)
sentences = collections.Counter(sentence.findall(text))
for n, s in sentences.most_common():
print n, s
word = re.compile(r"\w+")
words = collections.Counter(word.findall(text.lower()))
for n, w in words.most_common():
print n, w
For "more power", you could use some natural language toolkit, but this might be a bit much for this task.