UCI dataset: How to extract features and change the data into usable format after reading the data on python

Question

I am looking to apply some ml algorithms on the data set from https://archive.ics.uci.edu/ml/datasets/University. I noticed that the data is unstructured. Indeed, I want the data to have the features as the columns and have observations as the rows. Therefore, I need help with parsing this dataset.

Any help will be appreciated. Thanks.

Below is what I have tried:

column_names = ["University-name"
 ,"State"
 ,"location"
 ,"Control"
,"number-of-students"
,"male:female (ratio)"
 ,"student:faculty (ratio)",
 "sat-verbal"
 ,"sat-math"
,"expenses"
,"percent-financial-aid"
,"number-of-applicants"
,"percent-admittance"
,"percent-enrolled"
,"academics" 
,"social"
,"quality-of-life"
,"academic-emphasis"]
data_list =[]
data = ['https://archive.ics.uci.edu/ml/machine-learning- 
databases/university/university.data','https://archive.ics.uci.edu/ml/machine- 
learning-databases/university/university.data',...]' 


for file in in data:
    df = pd.read_csv(file, names = column_names)
    data_list.append(df)