Convert a csv file so that all attributes will become columns with corresponding element
Here's two different ways to do it. One reading through the file one line at a time to generate a list of dictionaries and one using pure pandas;

import pandas as pd

with open('datafile.csv', 'r') as f:
    data = []
    current_university = {}
    for line in f:
        line = [x.lstrip().strip() for x in line.split(',')]
        if (line[0] == 'University'):
            if current_university:
                data.append(current_university)
            current_university = {line[0]: line[1]}
        else:
            current_university[line[0]] = line[1]
    data.append(current_university)
df = pd.DataFrame(data)
df.set_index('University', inplace=True)


And then pandas;

df = pd.read_csv('datafile.csv', header=None)
df = df.set_index(0).T
df = df.groupby(df.columns.values, axis=1).agg(lambda x: x.values.tolist()).sum().apply(pd.Series).T.sort_values('University')
df.set_index('University', inplace=True)


Personally I think it's much easier to see what's going on in the first option but just wanted to show that it can be done using only pandas as well.