Reorder Rows into Columns in Pandas (Python 3, Pandas) - python-3.x

Question

Right now, my code takes scraped web data from a file (BigramCounter.txt), and then finds all the bigrams within that file so that the data looks like this:
Counter({('the', 'first'): 45, ('on', 'purchases'): 42, ('cash', 'back'): 39})
After this, I try to feed it into a pandas DataFrame where it spits this df out:
the on cash
first purchases back
0 45 42 39
This is very close to what I need but not quite. First off, the DF does not read my attempt to name the columns. Furthermore, I was hoping for something formatted more like this where its two COLUMNS and the Words are not split between Cells:
Words Frequency
the first 45
on purchases 42
cash back 39
For reference, here is my code. I think I may need to reorder an axis somewhere but I'm not sure how? Any ideas?
import re
from collections import Counter
main_c = Counter()
words = re.findall('\w+', open('BigramCounter.txt', encoding='utf-8').read())
bigrams = Counter(zip(words,words[1:]))
main_c.update(bigrams) #at this point it looks like Counter({('the', 'first'): 45, etc...})
comm = [[k,v] for k,v in main_c]
frame = pd.DataFrame(comm)
frame.columns = ['Word', 'Frequency']
frame2 = frame.unstack()
frame2.to_csv('text.csv')

Answer 1

I think I see what you're going for, and there are many ways to get there. You were really close. My first inclination would be to use a series, especially since you'd (presumably) just be getting rid of the df index when you write to csv, but it doesn't make a huge difference.
frequencies = [[" ".join(k), v] for k,v in main_c.items()]
pd.DataFrame(frequencies, columns=['Word', 'Frequency'])
Word Frequency
0 the first 45
1 cash back 39
2 on purchases 42
If, as I suspect, you want word to be the index, add frame.set_index('Word')
Word Frequency
the first 45
cash back 39
on purchases 42